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Evidence for a limit
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Evidence for a limit to human lifespan
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This study, published in Nature in 2016 by Xiao Do This study, published in Nature in 2016 by Xiao Dong, Brandon Milholland, and Jan Vijg, investigates whether there is a natural upper limit to the human lifespan. Despite significant increases in average human life expectancy over the past century, the authors provide strong demographic evidence suggesting that maximum human lifespan is fixed and subject to natural constraints, with limited improvement beyond a certain age threshold.
Background and Context
Life expectancy vs. maximum lifespan: Life expectancy has increased substantially since the 19th century, largely due to reduced early-life mortality and improved healthcare. However, maximum lifespan, defined as the age of the longest-lived individuals within a species, is generally considered a stable biological characteristic.
The oldest verified human was Jeanne Calment, who lived to 122 years, setting the recognized upper bound.
While animal studies show lifespan can be extended via genetics or pharmaceuticals, evidence on human maximum lifespan flexibility has been inconclusive.
Some previous research, such as studies from Sweden, suggested maximum lifespan was increasing during the 19th and early 20th centuries, challenging the notion of a fixed limit.
Key Findings
Trends in Life Expectancy and Late-Life Survival
Average life expectancy at birth has continually increased globally, especially in developed nations (e.g., France).
Gains in survival have shifted from early-life mortality reductions to improvements in late-life mortality, with more individuals reaching very old ages (70+).
However, the rate of improvement in survival declines sharply after around 100 years of age.
The age showing the greatest gains in survival over time increased during the 20th century but appears to have plateaued since around 1980.
This plateau is seen in 88% of 41 countries studied, indicating a potential biological constraint on lifespan extension beyond a certain point.
Maximum Reported Age at Death (MRAD) Analysis
Using data from the International Database on Longevity (IDL) and the Gerontological Research Group (GRG), the authors analyzed the maximum ages of supercentenarians (110+ years old) in countries with the largest datasets (France, Japan, UK, US).
The maximum reported age at death increased steadily between the 1970s and early 1990s but plateaued around the mid-1990s, near the time Jeanne Calment died (1997).
Linear regression divided into two periods (1968–1994 and 1995 onward) showed:
Pre-1995: MRAD increased by approximately 0.12–0.15 years per year.
Post-1995: No significant increase; a slight, non-significant decline occurred.
The MRAD has stabilized around 114.9 years (95% CI: 113.1–116.7).
The probability of exceeding 125 years in any given year is less than 1 in 10,000, according to a Poisson distribution model.
Additional Statistical Evidence
Analysis of the top five highest reported ages at death per year (not just the maximum) shows similar plateauing trends.
The annual average age at death among supercentenarians has not increased since 1968.
These consistent patterns across multiple metrics and datasets strengthen the evidence for a natural ceiling on human lifespan.
Biological Interpretation and Implications
The idea that aging is a programmed biological event evolved to cause death has been widely discredited.
Instead, limits to lifespan are likely an inadvertent consequence of genetic programs optimized for early life functions (development, growth, reproduction).
Species-specific longevity assurance systems encoded in the genome counteract genetic and cellular imperfections, maintaining lifespan within limits.
Extending human lifespan beyond these natural limits would likely require interventions beyond improving healthspan, potentially involving genetic or pharmacological modifications.
While current research explores such possibilities, the complexity of genetic determinants of lifespan suggests substantial biological constraints.
Timeline Table: Key Chronological Events and Findings
Period Event/Observation
1860s–1990s Maximum reported age at death in Sweden rose from ~101 to ~108 years, suggesting possible increase
1900 onwards Life expectancy at birth increased markedly globally, especially in developed countries
1970s–early 1990s Maximum reported age at death (MRAD) increased steadily in France, Japan, UK, and US
Mid-1990s (around 1995) MRAD plateaued at ~114.9 years; no further significant increase observed
1997 Death of Jeanne Calment, oldest verified human at 122 years
1980s onwards Age with greatest gains in survival plateaued, indicating diminishing improvements at oldest ages
Quantitative Data Summary
Metric Value/Trend Source/Data
Jeanne Calment’s age at death 122 years Oldest verified human
Maximum reported age at death (MRAD) plateau ~114.9 years (95% CI: 113.1–116.7) IDL, GRG databases
MRAD increase rate (pre-1995) +0.12 to +0.15 years/year Linear regression
MRAD increase rate (post-1995) Slight, non-significant decrease Linear regression
Probability of exceeding 125 years in a year <1 in 10,000 Poisson distribution model
Percentage of countries showing plateau in survival gains at oldest ages 88% 41 countries analyzed
Key Insights
Human maximum lifespan appears to be fixed and constrained, despite past increases in average lifespan.
Improvements in survival rates slow and plateau beyond approximately 100 years of age.
The world record for age at death has not significantly increased since the late 1990s.
The phenomenon is consistent across multiple countries and independent datasets.
Biological aging limits are likely an outcome of genetic programming optimized for early life, with longevity assured by species-specific genomic systems.
Substantial extension of maximum human lifespan would require overcoming complex genetic and biological constraints.
Conclusions
This comprehensive demographic analysis provides strong evidence for a natural limit to human lifespan, with little increase in maximum age at death over recent decades despite ongoing increases in average life expectancy. The data challenge optimistic views that human longevity can be indefinitely extended by current health improvements alone. Instead, future lifespan extension may depend on breakthroughs that directly target the underlying biological and genetic determinants of aging.
References to Core Concepts and Methods
Use of Human Mortality Database for survival and life expectancy trends.
Analysis of supercentenarian data from the International Database on Longevity (IDL) and Gerontological Research Group (GRG).
Application of linear regression and Poisson distribution modeling to maximum age at death data.
Consideration of species-specific genetic longevity assurance systems and aging biology literature.
Comparison to historical theories of lifespan limits (Fries 1980; Olshansky et al. 1990).
Keywords
Maximum lifespan
Life expectancy
Supercentenarians
Late-life mortality
Longevity limit
Jeanne Calment
Genetic constraints
Aging biology
Mortality trends
Demographic analysis
FAQ
Q: Has maximum human lifespan increased in recent decades?
A: No. Analysis shows the maximum reported age at death plateaued in the mid-1990s around 115 years.
Q: How does life expectancy differ from maximum lifespan?
A: Life expectancy is the average age people live to in a population, which has increased due to reduced early mortality. Maximum lifespan is the oldest age reached by individuals, which appears fixed.
Q: Is there evidence for biological constraints on human lifespan?
A: Yes. Data suggest species-specific genetic programs and longevity assurance systems impose natural upper limits.
Q: Could future interventions extend maximum lifespan?
A: Potentially, but such extensions require overcoming complex genetic and biological factors beyond current health improvements.
This summary synthesizes the core findings and implications of the study, strictly based on the provided content, reflecting a nuanced understanding of the limits to human lifespan suggested by recent demographic evidence.
Smart Summary
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Evaluation of gender
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Evaluation of gender differences on mitochondrial
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This study investigates gender differences in mito This study investigates gender differences in mitochondrial bioenergetics, oxidative stress, and apoptosis in the C57Bl/6J (B6) mouse strain, a commonly used laboratory rodent model that shows no significant differences in longevity between males and females. The research explores whether the previously observed gender-based differences in longevity and oxidative stress in other species, often attributed to higher estrogen levels in females, are reflected in mitochondrial function and apoptotic markers in this mouse strain.
Background and Rationale
It is widely observed that in many species, females tend to live longer than males, often explained by higher estrogen levels in females potentially reducing oxidative damage.
However, this trend is not universal: in some species including certain mouse strains (C57Bl/6J), longevity does not differ between sexes, and in others (e.g., Syrian hamsters, nematodes), males may live longer.
Previous studies in rat strains (Wistar, Fischer 344) with female longevity advantage showed lower mitochondrial reactive oxygen species (ROS) production and higher antioxidant defenses in females.
The Mitochondrial Free Radical Theory of Aging suggests that aging rate is related to mitochondrial ROS production, which causes oxidative damage.
This study aims to test if gender differences in mitochondrial bioenergetics, ROS production, oxidative stress, and apoptosis exist in B6 mice, which do not show sex differences in lifespan.
Experimental Design and Methods
Animals: 10-month-old male (n=11) and female (n=12) C57Bl/6J mice were used.
Tissues studied: Heart, skeletal muscle (gastrocnemius + quadriceps), and liver.
Mitochondrial isolation: Tissue-specific protocols were used to isolate mitochondria immediately post-sacrifice.
Measurements performed:
Mitochondrial oxygen consumption: State 3 (active) and State 4 (resting) respiration measured polarographically.
ATP content: Determined via luciferin-luciferase assay in freshly isolated mitochondria.
ROS production: H2O2 generation from mitochondrial complexes I and III measured fluorometrically with specific substrates and inhibitors.
Oxidative stress markers:
Protein carbonyls in cytosolic fractions (ELISA).
8-hydroxy-2′-deoxyguanosine (8-oxodG) levels in mitochondrial DNA (HPLC-EC-UV).
Apoptosis markers:
Caspase-3 and caspase-9 activity (fluorometric assays).
Cleaved caspase-3 protein (Western blot).
Mono- and oligonucleosomes (DNA fragmentation, ELISA).
Key Quantitative Results
Parameter Tissue Male (Mean ± SEM) Female (Mean ± SEM) Statistical Difference
Body weight (g) Whole body 30.1 ± 0.55 24.1 ± 1.04 Male > Female (p<0.001)
Heart weight (mg) Heart 171 ± 0.01 135 ± 0.01 Male > Female (p<0.001)
Liver weight (g) Liver 1.52 ± 0.09 1.15 ± 0.09 Male > Female (p<0.01)
Skeletal muscle weight (mg) Quadriceps + gastrocnemius ~403 (sum) ~318 (sum) Male > Female (p<0.001)
Oxygen Consumption (nmol O2/min/mg protein) Heart, State 3 77.8 ± 7.5 65.0 ± 7.3 No significant difference
Skeletal Muscle, State 3 61.4 ± 4.9 64.8 ± 5.5 No significant difference
Liver, State 3 36.1 ± 4.5 34.9 ± 2.5 No significant difference
ATP content (nmol ATP/mg protein) Heart 3.7 ± 0.5 2.8 ± 0.4 No significant difference
Skeletal Muscle 0.12 ± 0.05 0.28 ± 0.06 No significant difference
ROS production (nmol H2O2/min/mg protein) Heart (complex I substrate) 0.7 ± 0.1 0.7 ± 0.05 No difference
Skeletal muscle (succinate) 5.9 ± 0.6 7.5 ± 0.5 Female > Male (p<0.05)
Liver (complex I substrate) 0.13 ± 0.05 0.13 ± 0.05 No difference
Protein carbonyls (oxidative damage marker) Heart, muscle, liver No difference No difference No significant difference
8-oxodG in mtDNA (oxidative DNA damage) Skeletal muscle, liver No difference No difference No significant difference
Caspase-3 and Caspase-9 activity (apoptosis markers) Heart, muscle, liver No difference No difference No significant difference
Cleaved caspase-3 (Western blot) Heart, muscle, liver No difference No difference No significant difference
Mono- and oligonucleosomes (DNA fragmentation) Heart, muscle, liver No difference No difference No significant difference
Core Findings and Interpretations
No significant sex differences were found in mitochondrial oxygen consumption or ATP content in heart, skeletal muscle, or liver mitochondria.
Mitochondrial ROS production rates were similar between sexes in heart and liver; only female skeletal muscle showed slightly higher ROS production with succinate substrate, an isolated finding.
Measures of oxidative damage to proteins and mitochondrial DNA did not differ between males and females.
Markers of apoptosis (caspase activities, cleaved caspase-3, DNA fragmentation) were not different between sexes in any tissue examined.
Despite females having higher estrogen levels, no associated protective effect on mitochondrial bioenergetics, oxidative stress, or apoptosis was observed in this mouse strain.
The lack of differences in mitochondrial function and oxidative damage correlates with the absence of sex differences in lifespan in the C57Bl/6J strain.
These data support the Mitochondrial Free Radical Theory of Aging, emphasizing the role of mitochondrial ROS production in aging rate, independent of estrogen-mediated effects.
The study suggests that body size differences might explain sex differences in longevity and oxidative stress observed in other species (e.g., rats), as mice exhibit smaller body weight differences between sexes.
The estrogen-related increase in antioxidant defenses or mitochondrial function is not universal, and estrogen’s protective role may vary by species and strain.
Apoptosis rates do not differ between sexes in middle-aged mice, but differences could potentially emerge at older ages (not specified).
Timeline Table: Key Experimental Procedures
Step Description
Animal age at study 10 months old male and female C57Bl/6J mice
Tissue collection and mitochondrial isolation Heart, skeletal muscle, liver isolated post-sacrifice
Measurements Oxygen consumption, ATP content, ROS production, oxidative damage, apoptosis markers
Data analysis Statistical comparison of males vs females
Keywords
Mitochondria
Reactive Oxygen Species (ROS)
Oxidative Stress
Apoptosis
Mitochondrial DNA (mtDNA)
Estrogen
Longevity
C57Bl/6J Mice
Mitochondrial Free Radical Theory of Aging
Conclusions
In the C57Bl/6J mouse strain, gender does not influence mitochondrial bioenergetics, oxidative stress levels, or apoptosis markers, consistent with the lack of sex differences in longevity in this strain.
Higher estrogen levels in females do not confer measurable mitochondrial protection or reduced oxidative stress in this model.
The results suggest that oxidative stress generation, rather than estrogen levels, determines aging rate in this species.
Body size and species-specific factors may underlie observed sex differences in longevity and oxidative stress in other animals.
Further research is needed in models where males live longer than females (e.g., Syrian hamsters) and in older animals to clarify the influence of sex on apoptosis and aging.
Key Insights
Gender differences in mitochondrial ROS production and apoptosis are not universal across species or strains.
Estrogen’s role in modulating mitochondrial function and oxidative stress is complex and strain-dependent.
Mitochondrial ROS production remains a central factor in aging independent of sex hormones in the studied mouse strain.
Additional Notes
The study used well-controlled, comprehensive biochemical and molecular assays to evaluate mitochondrial function and apoptosis.
The findings challenge the assumption that female longevity advantage is directly mediated by estrogen effects on mitochondria.
The lack of sex differences in this mouse strain provides a useful baseline for comparative aging studies.
This summary reflects the study’s content strictly as presented, without introducing unsupported interpretations or data.
Smart Summary...
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Evaluating the Effect o
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Evaluating the Effect of Project Longevity
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This report evaluates the impact of Project Longev This report evaluates the impact of Project Longevity, a focused-deterrence violence-reduction initiative implemented in New Haven, Connecticut, on reducing group-involved shootings and homicides. The program targets violent street groups, delivering a coordinated message that violence will bring swift sanctions while offering social services, support, and incentives for individuals who choose to disengage from violent activity.
The study uses detailed group-level data and statistical modeling to assess changes in violent incidents following the program’s launch. The analysis reveals that Project Longevity significantly reduced group-related shootings and homicides, with estimates indicating reductions of approximately 25–30% after implementation. The results are robust across multiple models and remain consistent after adjusting for group characteristics, prior levels of violence, and time trends.
The report explains that Project Longevity works by mobilizing three key components:
Law enforcement partners, who coordinate enforcement responses to group violence;
Social service providers, who offer job training, counseling, and other support;
Community moral voices, who communicate collective intolerance for violence.
Together, these elements reinforce the central message: violence will no longer be tolerated, but help is available for those willing to change.
The authors conclude that Project Longevity is an effective violence-prevention strategy, demonstrating clear reductions in serious violent crime among the most at-risk populations. The findings support the broader evidence base for focused deterrence strategies and suggest that continued implementation could sustain long-term reductions in group-involved violence.
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zmvqjlwa-5426
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European Longevity Record
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European Longevity Records
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European Longevity Records is a visually rich, dat European Longevity Records is a visually rich, data-driven document presenting verified supercentenarian records across Europe, organized by country. Using flags, icons, portrait photos, and highlighted record boxes, the document showcases the oldest known individuals from dozens of European nations, including their names, ages, birth/death years, and longevity rankings.
The booklet serves as a continental longevity atlas, featuring entries such as:
UK (England) – Charlotte Hughes
UK (Scotland) – Annie Knight
Spain – María Branyas Morera
Italy – Emma Morano
France – Jeanne Calment (the world’s oldest verified person)
Belgium – Joanna Distelmans Van Geystelen
Netherlands – Hendrikje van Andel-Schipper
Germany – Auguste Steinmann
Iceland – Jón Daníelsson (earliest entry in the list)
Each country has a dedicated “longevity card” containing:
A flag symbol
A portrait of the recordholder
Gender icon
Their maximum verified age (e.g., 122 years, 5 months, 14 days)
Birth and death dates
A ranking indicator (e.g., “1st,” “3rd,” “7th”)
The layout intentionally highlights the extraordinary lifespan of each individual, often showing bold age numbers (e.g., 122, 119, 116), making cross-country comparison simple and intuitive.
The publication also includes:
A brief methodological note (“Supercentenarian = age ≥ 110”)
Highlighting that the list is maintained by the GRG European Supercentenarian Database (ESD) and identifies the oldest documented person ever from each country
A disclaimer that validation standards follow international demographic verification protocols
The document functions as both:
A historical archive of Europe’s longest-lived individuals, and
A demographic reference illustrating extreme longevity patterns across nations.
Overall, European Longevity Records is a concise, authoritative, beautifully designed compilation of Europe’s verified supercentenarians—effectively a “who’s who” of exceptional human longevity across the continent.
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Ethical Aspects of Human
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Ethical Aspects of Human Genome Research in Sport
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“Ethical Aspects of Human Genome Research in Sport “Ethical Aspects of Human Genome Research in Sports”
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This is app-ready and human-friendly.
📘 Universal Description (App-Friendly & Easy Explanation)
Ethical Aspects of Human Genome Research in Sports is a review article that explains the ethical, legal, and human rights issues related to using genetic research and genetic technologies in sports. It focuses on how genetics can affect athletic performance, talent identification, training, injury prevention, and performance enhancement, while also raising serious ethical concerns.
The document explains that genetics plays a role in athletic ability, but athletic success depends on many factors, including training, environment, effort, and opportunity. It emphasizes that no single gene can determine whether someone will become a successful athlete.
The paper discusses genetic testing in sports, including its possible benefits (personalized training, injury prevention, nutrition planning) and its limitations (low predictive accuracy, risk of misuse, and lack of scientific certainty for talent selection).
A major focus of the document is ethics. It highlights risks such as:
genetic discrimination
loss of privacy
pressure on athletes to undergo testing
unfair advantages in competition
creation of a “genetic underclass” of athletes
The article strongly addresses gene doping, which means using genetic technologies to enhance performance rather than treat disease. It explains why gene doping is banned by the World Anti-Doping Agency (WADA) and how it threatens fairness, athlete health, and the integrity of sport.
The document also explains human rights and legal frameworks, especially in Europe. It refers to international agreements such as:
the Universal Declaration on the Human Genome and Human Rights
the Oviedo Convention (Human Rights and Biomedicine)
These frameworks protect human dignity, prohibit genetic discrimination, and restrict genetic modification for non-medical purposes.
Another key theme is informed consent and data protection. Athletes must voluntarily agree to genetic testing, understand risks and benefits, and have their genetic data kept private. The document warns about risks from direct-to-consumer genetic testing companies, including misuse of data and lack of proper counseling.
The paper concludes that while genetic research has potential benefits for health and training, it should not be used to select talent or enhance performance. Ethical oversight, strong laws, and international cooperation are essential to protect athletes and preserve fair competition.
🔑 Main Topics (Easy for Apps to Extract)
Sports genomics
Genetics and athletic performance
Ethical issues in sports genetics
Genetic testing in athletes
Gene doping
Fair play and equality in sports
Human rights and genetics
Privacy and genetic data protection
Legal regulation of genome research
Direct-to-consumer genetic testing
📌 Key Points (Presentation / Notes Friendly)
Athletic performance is influenced by genetics and environment
No single gene determines sports success
Genetic testing has limited predictive value
Gene doping is banned and unethical
Privacy and informed consent are essential
Genetic discrimination must be prevented
Ethics must guide genetic research in sports
🧠 One-Line Summary (Perfect for Quizzes & Slides)
Genetic research in sports offers potential health and training benefits but raises serious ethical, legal, and human rights concerns that require strict regulation and responsible use.
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Estimates of the Heritabi
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Estimates of the Heritability of Human Longevity
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This investigation critically examines the heritab This investigation critically examines the heritability of human longevity, challenging prior estimates that have ranged between 15–30% by demonstrating that these figures are substantially inflated due to assortative mating—the nonrandom pairing of mates with respect to longevity-associated traits. Using an unprecedentedly large dataset derived from Ancestry public family trees, encompassing hundreds of millions of historical individuals primarily of European descent living in North America and Europe during the 19th and early 20th centuries, the authors applied advanced structural equation modeling to disentangle genetic, sociocultural, and assortative mating effects on lifespan correlations.
The study concludes that the true transferable variance (t²)—an upper bound on heritability (h²) that includes both genetic and sociocultural inherited factors—is well below 10% for birth cohorts across the 1800s and early 1900s. This suggests that earlier heritability estimates of longevity have been substantially overestimated because they did not adequately correct for assortative mating effects.
Key Concepts and Definitions
Term Definition
Heritability (h²) The fraction of phenotypic variance attributable to genetic variance.
Transferable variance (t²) Phenotypic variance due to all inherited factors, encompassing both genetic (h²) and sociocultural (b²) components, plus their covariance.
Sociocultural inheritance (b²) Non-genetic factors that influence phenotype and are transmitted through families (e.g., socioeconomic status).
Assortative mating (a) The correlation between latent genetic and sociocultural states of spouses that influences phenotypic correlations beyond genetic inheritance.
Nominal heritability Heritability estimated without correction for assortative mating or shared environment, typically based on correlation and additive relatedness.
Methodology Overview
Data Source: Aggregated and anonymized pedigrees (SAP) were created by collapsing 54 million publicly available Ancestry subscriber-generated family trees, resulting in over 831 million unique historical individuals linked by parent–child and spousal edges.
Data Quality Controls:
Removed self-edges and gender-incongruent parent-child edges.
Added missing spousal edges between parents.
Focused on individuals with known birth and death years who had offspring, limiting analysis primarily to birth cohorts from the early 1800s to 1920.
Addressed data artifacts such as birth year rounding.
Analysis Approach:
Estimated phenotypic correlations of lifespan between various relatives (siblings, cousins, spouses, in-laws).
Calculated nominal heritability using standard regression methods correcting for variance differences.
Developed and applied a structural equation model incorporating three key parameters:
Transferable variance (t²),
Inheritance coefficient (b),
Assortative mating coefficient (a).
Utilized correlations among siblings-in-law and cosiblings-in-law to solve for these parameters.
Applied an assortment-correction method using remote relative pairs and their in-law equivalents to validate estimates.
Timeline Table: Analytical Focus and Data Coverage
Period Data Characteristics and Focus
Pre-1700 Mostly European births; sparse data quality Not specified
1700–1800 Increasing data quality; European and North American births
1800–1920 Primary focus; high data quality; large sample sizes in millions
Post-1920 Decline in death-year data; excluded from lifespan analysis
Major Findings
1. Nominal Heritability Estimates Confirm Prior Literature but Are Inflated
Nominal heritability estimates for lifespan correlated with previous findings (15–30%).
Lifespan correlations among blood relatives were similar to past studies.
However, spouses and in-law relatives also showed substantial lifespan correlations, sometimes comparable to or exceeding those of blood relatives.
This indicated that shared environments and assortative mating inflate these estimates.
2. Assortative Mating Significantly Inflates Heritability Estimates
Assortative mating coefficient (a) was consistently high across all analyses, often exceeding 0.8, indicating strong nonrandom mating based on lifespan-influencing factors.
The presence of assortative mating causes phenotypic correlations between relatives to deviate from the linear relationship expected under pure additive genetics.
Correlations between in-law relatives (who do not share genetics) were substantial, confirming the importance of assortative mating rather than shared genetics alone.
3. Structural Equation Modeling Reveals True Transferable Variance (t²) Is <10%
Using sibling-in-law and cosibling-in-law correlations, the model estimated transferable variance (t²) consistently below 7% for all gender combinations and birth cohorts.
This t² value represents an upper bound on heritability (h²) because it includes both genetic and sociocultural transmitted factors.
The inheritance coefficient (b) was estimated between 0.40–0.45, slightly less than the genetic expectation of 0.5, reflecting combined genetic and sociocultural inheritance.
Shared household environmental effects were also quantified and found to be substantial but separate from transferable variance.
4. Independent Validation Using Remote Relatives Supports Low Heritability
Assortment-correction method applied to remote relatives (piblings, first cousins, first cousins once removed) and their in-law equivalents consistently estimated assortative mating coefficients (a) close to or above 0.5.
Transferable variance estimates from these analyses also remained below 10%, validating the sibling-in-law modeling approach.
5. Transferable Variance Decreases with Increasing Birth-Cohort Disparity Among Relatives
Lifespan correlation and transferable variance (t²) were higher when relatives were born closer in time; as the birth-year gap increased, t² declined significantly.
Assortative mating coefficient (a) remained stable across birth-year offsets, suggesting that the decline in transferable variance was not due to mating patterns.
This suggests that genetic and sociocultural factors affecting lifespan vary with historical context, likely reflecting changing environmental hazards and causes of death over time.
Quantitative Summary Table: Structural Equation Model Estimates by Birth Cohort
Birth Cohort Period Transferable Variance (t²) Assortative Mating Coefficient (a) Inheritance Coefficient (b) Shared Childhood Environment (csib) Shared Adult Environment (csp)
1800s–1830s ~5.9–6.5% (across relatives) ~0.68–0.88 ~0.40–0.44 ~4.3% (siblings) ~6.6% (spouses)
1840s–1870s ~4.0–5.5% ~0.53–0.88 ~0.40 ~5.1% ~5.0%
1880s–1910s ~4.0–7.2% ~0.43–0.89 ~0.40 ~6.0% ~4.4%
Values represent means across gender pairs with standard deviations; b fixed at 0.5 for some estimates; all data derived from sibling-in-law and remote relative analyses.
Core Insights
Previous heritability estimates of human longevity (~15–30%) are substantially inflated due to assortative mating.
True heritability (h²) is likely below 10%, and possibly considerably lower after accounting for sociocultural inheritance.
Assortative mating for lifespan-related factors is strong, with a coefficient often >0.8, indicating mates tend to share longevity-related traits, both genetic and environmental.
Sociocultural factors (e.g., socioeconomic status) are a significant inherited component influencing longevity, evidenced by lifespan correlations among in-law relatives and supported by sociological literature.
Transferable variance (t²) decreases as birth cohorts diverge, implying that historical environmental changes modulate the impact of inherited factors on longevity.
Fundamental biological aging processes (e.g., rate of hazard doubling) appear consistent historically, but lifespan-affecting factors mostly modify susceptibility to historically transient environmental hazards, not aging rate itself.
Implications
Genetic studies of longevity should account for assortative mating and sociocultural inheritance to avoid overestimating genetic contributions.
Interventions targeting environmental and sociocultural factors could have a larger impact on lifespan extension than currently assumed genetic predispositions.
Historical and birth cohort context is critical when interpreting heritability and lifespan data.
The biological basis of aging remains consistent, but its interaction with environment and social factors is dynamic and complex.
References to Relevant Literature Mentioned
Smart Summary
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Enhance longevity through
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Enhance longevity through a healthy lifestyle
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“Longevity Through a Healthy Lifestyle” is a compr “Longevity Through a Healthy Lifestyle” is a comprehensive research-based review that explains how everyday lifestyle choices—especially diet, physical activity, sleep, social connection, stress management, and hygiene—directly influence lifespan and overall health. Published in 2023 in Madhya Bharti (Humanities and Social Sciences), the article analyzes 46 research studies to determine which lifestyle factors most strongly promote long life and prevent disease.
The central message of the article is clear:
➡️ Healthy habits significantly extend lifespan and reduce the risk of chronic diseases—even more than genetics alone.
The authors explore global evidence, including lessons from Blue Zones (places with the world’s longest-living populations), to show how simple, consistent lifestyle behaviors lead to healthier, longer lives.
⭐ Main Themes and Findings
⭐ 1. Diet: The Foundation of Longevity
The article emphasizes that a nutritious, plant-rich, balanced diet is essential for preventing chronic diseases like diabetes, heart disease, cancer, and stroke.
Key findings:
Ideal diet proportions: 50–60% carbs, 10–15% protein, 25–30% healthy fats.
Nuts, fruits, vegetables, fish oils, and plant-based foods are linked to lower mortality.
Blue Zone communities eat mostly plant-based meals, with low calories and minimal processed foods.
Traditional Okinawan habits like “Hara Hachi Bu” (eating until 80% full) contribute to extremely long lifespans.
📌 Studies show plant-based diets reduce early death risk by 12–15%.
Longevity through a healthy lif…
⭐ 2. Regular Physical Activity
Movement is essential for preventing disease, improving mental health, and extending lifespan.
Important points:
Exercise prevents diabetes, depression, heart disease, obesity, and high blood pressure.
Even 15 minutes of moderate activity daily reduces mortality risk by 22%.
Blue Zone centenarians do not “exercise” formally—they stay active through gardening, walking, and daily chores.
Physical inactivity, driven by modern technology and sedentary lifestyles, shortens life expectancy.
📌 Exercise delays death and extends life, according to multiple studies.
Longevity through a healthy lif…
⭐ 3. Quality Sleep Supports Long Life
The article highlights sleep as an overlooked but vital pillar of health.
Key findings:
Adults should sleep 7–9 hours nightly.
Sleeping less than 5 hours increases risk of death by up to 15%.
Poor sleep contributes to diabetes, inflammation, obesity, and heart disease.
Too much sleep is also linked to poor health and shortened lifespan.
📌 Sleep quality strongly correlates with longevity and healthy aging.
Longevity through a healthy lif…
⭐ 4. Social Connections Protect Health
Strong, supportive relationships extend life by improving emotional, mental, and physical wellbeing.
Evidence shows:
Good social ties can increase lifespan by up to 50%.
Loneliness is biologically harmful—raising inflammation, stress, and disease risk.
Blue Zones foster deep community bonds, such as Okinawa’s “moai” (friend groups) and strong family ties.
📌 Social support improves immunity and reduces chronic disease risk.
Longevity through a healthy lif…
⭐ 5. Hygiene and Stress Management
Personal hygiene prevents infectious disease, which contributes significantly to maintaining long-term health.
Meanwhile, stress is labeled a “silent killer”, worsening diabetes, heart disease, and depression.
Key points:
Stress can reduce life expectancy by 2–3 years or more.
Meditation, mindfulness, breathing exercises, and relaxation techniques slow cellular aging.
Stress management improves mental, emotional, and physical health.
📌 Meditation and stress control improve longevity by slowing cellular aging.
Longevity through a healthy lif…
⭐ Overall Conclusion
The article concludes that a healthy lifestyle dramatically improves lifespan.
Across all 46 studies reviewed, the findings consistently show that:
Eating well
Moving regularly
Sleeping adequately
Maintaining relationships
Managing stress
Practicing hygiene
…are essential for extending both lifespan and healthspan (years lived in good health).
Genetics matter far less than daily habits.
The authors recommend that future research create effective lifestyle programs, while governments should promote health-based habits at all levels of society....
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Energy Poverty and Life
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Energy Poverty and Life Expectancy in Nigeria
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This study investigates the impact of energy pover This study investigates the impact of energy poverty on life expectancy in Nigeria over the period from 1981 to 2023. Utilizing time series data and the Autoregressive Distributed Lag (ARDL) model, the research examines both short-run and long-run effects, revealing a statistically significant negative relationship between energy poverty and life expectancy. The study emphasizes the critical role of energy access as a determinant of public health and longevity, urging policy reforms to improve energy infrastructure and accessibility in Nigeria to enhance health outcomes and sustainable development.
Key Concepts
Term Definition/Explanation
Life Expectancy Average number of years a newborn is expected to live, given current sex- and age-specific mortality rates.
Energy Poverty Lack of access to affordable, reliable, and clean energy services, including electricity and clean cooking fuels.
ARDL Model An econometric technique used to estimate both short-run and long-run relationships in time series data.
Sustainable Development Goals (SDGs) United Nations goals, including Goal 3 (Health and Well-being) and Goal 7 (Affordable and Clean Energy).
Background and Context
Nigeria faces a persistent energy crisis, with about 43% of the population (86 million people) lacking access to reliable and modern energy.
Life expectancy in Nigeria is significantly lower than the global average, estimated at 54.9 years for women and 54.3 years for men, compared to global averages of 76 and 70.7 years respectively.
Energy poverty in Nigeria manifests through:
Limited electricity access.
Dependence on biomass and kerosene for cooking.
Frequent power outages affecting households, hospitals, and public infrastructure.
Existing government policies (e.g., National Health Policy, Renewable Energy Master Plan) have not sufficiently improved energy access or life expectancy.
Life expectancy is a key indicator of national development and is strongly influenced by socioeconomic and infrastructural factors.
Theoretical Framework
The study is grounded in Human Capital Theory (Schultz, Becker), which posits that investments in health, education, and other social services enhance individual productivity and contribute to overall economic growth and well-being.
Access to modern energy is viewed as a critical enabler of:
Health services.
Clean environments.
Improved living standards.
Energy poverty undermines health by increasing exposure to harmful fuels and limiting access to healthcare, thereby shortening life expectancy.
Empirical Literature Highlights
Roy (2025): Clean energy access significantly increases life expectancy globally.
Olise (2025): Kerosene positively affects quality of life in Nigeria in the short and long run; premium motor spirit negatively affects life expectancy; electricity consumption had no significant impact.
Onisanwa et al. (2024): Socioeconomic factors including income, education, urbanization, and environmental degradation determine life expectancy in Nigeria.
Fan et al. (2024): Energy poverty adversely affects public health, especially in developed regions.
Abu & Orisa-Couple (2022): Unsafe energy sources (kerosene, generators) cause burns and mortality in Port Harcourt.
Okorie & Lin (2022): Energy poverty increases risk of catastrophic health expenditure among Nigerian households.
Onwube et al. (2021): Real GDP per capita, household consumption, and exchange rates positively influence life expectancy; inflation and imports have negative effects.
Data and Methodology
Data: Annual time series data (1981-2023) from World Bank’s World Development Indicators and Global Database of Inflation.
Variables:
Variable Description Expected Sign
LFE Life expectancy at birth Dependent
EPOV Energy poverty (access to electricity and clean cooking fuels) Negative (β1 < 0)
GDPK GDP per capita (constant 2015 US$) Positive (β2 > 0)
GHEX Government health expenditure per capita Positive (β3 > 0)
PVL Prevalence of undernourishment (%) Negative (β4 < 0)
LTR Literacy rate (secondary school enrollment %) Positive (β5 > 0)
Econometric Approach:
Stationarity tested using Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests.
Cointegration tested via ARDL Bounds testing.
Short-run and long-run relationships estimated using ARDL and Error Correction Model (ECM).
Descriptive Statistics
Variable Mean Min Max Std. Dev Notes
Life Expectancy (LFE) 48.78 yrs 45.49 yrs 54.59 yrs 2.87 Moderate variability over time
Energy Poverty (EPOV) 52.59% 28.20% 86.10% 13.60 Volatile energy poverty environment
GDP per capita (GDPK) $1922.55 $1408.21 $2679.56 466.60 Modest economic growth
Govt. Health Expenditure (GHEX) $6.73 $0.30 $15.84 5.62 Low health spending
Prevalence of Undernourishment (PVL) 10.61% 6.50% 19.00% 2.68 Moderate food insecurity
Literacy Rate (LTR) 33.31% 17.41% 54.88% 9.79 Low to moderate literacy
Correlation Matrix Summary
Positive moderate correlation with life expectancy: GDP per capita (0.651), government health expenditure (0.598), literacy rate (0.434).
Negative correlation: Energy poverty (-0.450).
Low correlation: Prevalence of undernourishment (0.333).
Unit Root and Cointegration Tests
Energy poverty (EPOV) stationary at level (I(0)).
Life expectancy (LFE), GDP per capita (GDPK), government health expenditure (GHEX), prevalence of undernourishment (PVL), and literacy rate (LTR) stationary at first difference (I(1)).
ARDL Bounds test confirmed cointegration, indicating a stable long-run relationship between energy poverty and life expectancy.
Regression Results
Variable Short-Run Coefficient Significance Long-Run Coefficient Significance Interpretation
Energy Poverty (EPOV) -0.299 Significant -0.699 Highly significant Energy poverty reduces life expectancy both short and long term; effect stronger over time.
GDP per capita (GDPK) 0.026 Insignificant 0.332 Significant Economic growth positively affects life expectancy, especially in the long run.
Govt. Health Expenditure (GHEX) 0.071 Significant -0.054 Insignificant Short-run benefits of health spending on life expectancy, but no significant long-run effect.
Prevalence of Undernourishment (PVL) -0.377 Significant -0.225 Significant Food insecurity negatively impacts life expectancy both short and long term.
Literacy Rate (LTR) 0.003 Insignificant 0.044 Marginal Positive but insignificant effect on life expectancy.
Error Correction Term -0.077 Highly significant Not specified Not specified Adjusts 77% of deviation from equilibrium each year, confirming model stability.
Diagnostic and Stability Tests
Breusch-Godfrey Serial Correlation LM test, Breusch-Pagan-Godfrey Heteroskedasticity test, and Ramsey RESET test showed no serial correlation, heteroskedasticity, or misspecification—indicating a robust model.
CUSUM and CUSUMSQ tests confirmed no structural breaks or parameter instability in the model over the study period.
Timeline of Key Trends (1981–2023)
Period Life Expectancy Trend Energy Poverty Trend Key Events/Context
1981–1995 Below 46.7 years, stagnant Increasing energy poverty Structural Adjustment era, economic challenges
1999–2003 Slight increase to ~47.2 years Fluctuations in energy poverty Transition to civilian rule, policy shifts
2003–2023 Gradual sustained increase to 54.6 years Sharp surge in energy poverty from 2010 onward Population growth, poor infrastructure, subsidy removal
Policy Recommendations
Prioritize Energy Sector Reforms:
Expand on-grid power generation and improve transmission and distribution infrastructure.
Promote affordable off-grid renewable energy solutions and clean cooking technologies.
Stabilize energy prices and enhance reliability of energy supply.
Increase and Improve Public Health Expenditure:
Boost healthcare infrastructure and access.
Implement institutional reforms to reduce corruption and improve resource allocation.
Address Food Insecurity:
Develop coordinated agricultural, nutritional, and welfare policies to reduce undernourishment.
Focus on Rural and Underserved Communities:
Target energy access expansion to marginalized populations to improve health and longevity.
Integrate Energy Policy with Health and Development Goals:
Align energy access initiatives with Sustainable Development Goals (SDG 3 and SDG 7).
Core Insights
Energy poverty significantly undermines life expectancy in Nigeria, with stronger effects observed over the long term.
Economic growth has a positive but delayed impact on life expectancy.
Public health expenditure improves life expectancy in the short run but shows diminished long-run effectiveness, likely due to governance challenges.
Food insecurity consistently reduces life expectancy.
Literacy improvements have a positive but statistically insignificant influence on longevity.
The relationship between energy poverty and life expectancy in Nigeria has remained stable over four decades despite policy efforts.
Keywords
Energy Poverty, Life Expectancy, Nigeria, ARDL Model, Sustainable Development Goals, Public Health, Economic Growth, Food Insecurity, Human Capital Theory.
Conclusion
This comprehensive empirical analysis confirms that energy poverty is a critical and persistent barrier to improving life expectancy in Nigeria. The negative impact of inadequate access to modern energy services on health outcomes necessitates urgent policy attention. Sustainable improvements in longevity will require integrated strategies that combine energy reforms, enhanced public health spending, food security measures, and economic growth, underpinned by strong institutional governance. Addressing energy poverty is not only vital for health but also essential for Nigeria’s broader development and achievement of international sustainability targets.
Smart Summary
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Effects of longevity
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Effects of longevity and mortality
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Mugi: Effects of Mortality and Longevity Risk in R Mugi: Effects of Mortality and Longevity Risk in Risk Management in Life Insurance Companies is a clear and rigorous exploration of how mortality risk (people dying earlier than expected) and longevity risk (people living longer than expected) affect the financial stability, pricing, reserving, and strategic management of life insurance companies. The report explains why longevity—usually celebrated from a public health perspective—creates serious financial challenges for insurers, pension funds, and annuity providers.
The central message:
As people live longer, life insurance companies face rising liabilities, growing uncertainty, and the need for advanced risk-management tools to remain solvent and competitive.
🧩 Core Themes & Insights
1. Mortality vs. Longevity Risk
The paper distinguishes two opposing risks:
Mortality Risk (Life insurance)
People die earlier than expected → insurers pay out death benefits sooner → financial losses.
Longevity Risk (Annuities & Pensions)
People live longer than expected → insurers must keep paying benefits for more years → liabilities increase.
Longevity risk is now the dominant threat as global life expectancy rises.
2. Why Longevity Risk Is Growing
The study highlights several forces:
Continuous declines in mortality
Medical advances extending life
Rising survival at older ages
Uncertainty in future mortality trends
Rapid global population aging
For insurers offering annuities, pension guarantees, or long-term products, this creates a systemic, long-horizon risk that is difficult to hedge.
3. Impact on Life Insurance Companies
Longevity risk affects insurers in multiple ways:
A. Pricing & Product Design
Annuities become more expensive to offer
Guarantees become riskier
Traditional actuarial assumptions become outdated faster
B. Reserving & Capital Requirements
Companies must hold larger technical reserves
Regulators impose stricter solvency requirements
Balance sheets become more volatile
C. Profitability & Shareholder Value
Longer lifespans → higher liabilities → reduced profit margins unless risks are hedged.
4. Tools to Manage Longevity Risk
The paper reviews modern strategies used globally:
A. Longevity Swaps
Transfer longevity exposure to reinsurers or investors.
B. Longevity Bonds / Mortality-Linked Securities
Payments tied to survival rates; spreads risk to capital markets.
C. Reinsurance
Traditional method for offloading part of the risk.
D. Hedging Through Natural Offsets
Balancing life insurance (benefits paid when people die early) with annuities (benefits paid when people live long).
E. Improving Mortality Modeling
Using:
Lee–Carter models
Stochastic mortality models
Scenario stress testing
Cohort analysis
Accurate forecasting is critical—even small misestimates of future mortality can cost insurers billions.
5. Risk Management Framework
A strong longevity risk program includes:
identifying exposures
assessing potential solvency impacts
using internal models
scenario analysis (e.g., “life expectancy improves by +3 years”)
hedging and reinsurance
regulatory capital alignment
The goal is maintaining solvency under a variety of demographic futures.
6. Global Context
Countries with rapidly aging populations (Japan, Western Europe, China) face the strongest longevity pressures.
Regulators worldwide are:
requiring better capital buffers
encouraging transparency
exploring longevity-linked capital market instruments
🧭 Overall Conclusion
Longevity, though positive for individuals and society, represents a major financial uncertainty for life insurers. Rising life expectancy increases long-term liabilities and challenges traditional actuarial models. To remain stable, life insurance companies must adopt modern risk-transfer tools, advanced mortality modeling, diversified product portfolios, and robust solvency management.
The paper positions longevity risk as one of the most critical issues for the future of global insurance and pension systems....
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Effects of food
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Effects of food restriction on aging
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This study, published in Proceedings of the Nation This study, published in Proceedings of the National Academy of Sciences (1984), investigates the effects of food restriction on aging, specifically aiming to disentangle the roles of reduced food intake and reduced adiposity on longevity and physiological aging markers in mice. The research focuses on genetically obese (ob/ob) and normal (C57BL/6J, or B6 +/+) female mice, examining how lifelong food restriction influences longevity, collagen aging, renal function, and immune responses. The key finding is that reduced food intake, rather than reduced adiposity, is the critical factor in extending lifespan and retarding certain aging processes.
Background and Objective
Food restriction (caloric restriction) is known to increase longevity in rodents, but the underlying mechanism remains unclear.
Previous studies suggested that reduced adiposity (body fat) might mediate the longevity effects. However, human epidemiological data show conflicting evidence: moderate obesity correlates with lower mortality, challenging the assumption that less fat is always beneficial.
Genetically obese ob/ob mice provide a model to separate effects because they maintain high adiposity even when food restricted.
The study aims to clarify whether reduced food intake or reduced adiposity is the primary driver of delayed aging and increased longevity.
Experimental Design
Subjects: Female mice of the C57BL/6J strain, both normal (+/+) and genetically obese (ob/ob).
Feeding Regimens:
Fed ad libitum (free access to food).
Restricted feeding: fixed ration daily, adjusted so restricted ob/ob mice weigh similarly to fed +/+ mice.
Food restriction started at weaning (4 weeks old) and continued lifelong.
Parameters measured:
Longevity (mean and maximum lifespan).
Body weight, adiposity (fat percentage), and food intake.
Collagen aging assessed by denaturation time of tail tendon collagen.
Renal function measured via urine-concentrating ability after dehydration.
Immune function evaluated by thymus-dependent responses: proliferative response to phytohemagglutinin (PHA) and plaque-forming cells in response to sheep erythrocytes (SRBC).
Key Quantitative Data
Group Food Intake (g/day) Body Weight (g) Body Fat (% of wt) Mean Longevity (days) Max Longevity (days) Immune Response to SRBC (% Young Control) Immune Response to PHA (% Young Control)
Fed ob/ob 4.2 ± 0.5 67 ± 5 ~66% 755 893 7 ± 7 13 ± 7
Fed +/+ 3.0* 30 ± 1* 22 ± 6 971 954 22 ± 11 49 ± 12
Restricted ob/ob 2.0* 28 ± 2 48 ± 1 823 1307 11 ± 7 8 ± 6
Restricted +/+ 2.0* 20 ± 2* 13 ± 3 810 1287 59 ± 30 50 ± 11
Note: Means not significantly different from each other are marked with an asterisk (*).
Detailed Findings
1. Body Weight, Food Intake, and Adiposity
Fed ob/ob mice consume the most food and have the highest body fat (~66% of body weight).
When food restricted, ob/ob mice consume about half as much food as when fed ad libitum but maintain a very high adiposity (~48%), nearly twice that of fed normal mice.
Restricted normal mice have the lowest fat percentage (~13%) despite eating the same amount of food as restricted ob/ob mice.
This demonstrates that food intake and adiposity can be experimentally dissociated in these genotypes.
2. Longevity
Food restriction increased mean lifespan of ob/ob mice by 56% and maximum lifespan by 46%.
In normal mice, food restriction had little effect on mean longevity but increased maximum lifespan by 32%.
Food-restricted ob/ob mice lived longer than fed normal mice, despite their greater adiposity.
These results strongly suggest that reduced food intake, not reduced adiposity, extends lifespan, even with high body fat levels.
3. Collagen Aging
Collagen denaturation time is a biomarker of aging, with shorter times indicating more advanced aging.
Collagen aging is accelerated in fed ob/ob mice compared to normal mice.
Food restriction greatly retards collagen aging in both genotypes.
Importantly, collagen aging rates were similar in restricted ob/ob and restricted +/+ mice, despite widely different body fat percentages.
Conclusion: Collagen aging correlates with food intake but not with adiposity.
4. Renal Function (Urine-Concentrating Ability)
Urine-concentrating ability declines with age in normal rodents.
Surprisingly, fed ob/ob mice did not show an age-related decline; their concentrating ability remained high into old age.
Restricted mice (both genotypes) showed a slower decline than fed normal mice.
This suggests obesity does not necessarily impair this aspect of renal function, and food restriction preserves it.
5. Immune Function
Immune responses (to PHA and SRBC) decline with age, more severely in fed ob/ob mice (only ~10% of young normal levels at old age).
Food restriction did not improve immune responses in ob/ob mice, even though their lifespans were extended.
In restricted normal mice, immune responses showed slight improvement compared to fed normal mice.
The spleens of restricted ob/ob mice were smaller, which might contribute to low immune responses measured per spleen.
These results suggest immune aging may be independent from longevity effects of food restriction, especially in genetically obese mice.
The more rapid decline in immune function with higher adiposity aligns with previous reports that increased dietary fat accelerates autoimmunity and immune decline.
Interpretation and Conclusions
The study disentangles two factors often conflated in aging research: food intake and adiposity.
Reduced food intake is the primary factor in extending lifespan and slowing collagen aging, not the reduction of body fat.
Genetically obese mice restricted in food intake live longer than normal mice allowed to eat freely, despite retaining high body fat levels.
Aging appears to involve multiple independent processes (collagen aging, immune decline, renal function), each affected differently by genetic obesity and food restriction.
The study also highlights that immune function decline is not necessarily mitigated by food restriction in obese mice, suggesting complexities in how different physiological systems age.
Findings challenge the assumption that less fat is always beneficial, offering a potential explanation for human studies showing moderate obesity correlates with lower mortality.
The results support the idea that reducing food consumption can be beneficial even in individuals with high adiposity, with implications for aging and metabolic disease research.
Implications for Human Aging and Obesity
The study cautions against equating adiposity directly with aging rate or mortality risk without considering food intake.
It suggests that caloric restriction may improve longevity even when body fat remains high, which may help reconcile conflicting human epidemiological data.
The authors note that micronutrient supplementation along with food restriction could further optimize longevity outcomes, based on related studies.
Core Concepts
Food Restriction (Caloric Restriction): Limiting food intake without malnutrition.
Adiposity: The proportion of body weight composed of fat.
ob/ob Mice: Genetically obese mice with a mutation causing defective leptin production, leading to obesity.
Longevity: Length of lifespan.
Collagen Aging: Changes in collagen denaturation time indicating tissue aging.
Immune Senescence: Decline in immune function with age.
Renal Function: Kidney’s ability to concentrate urine, an indicator of aging-related physiological decline.
References to Experimental Methods
Collagen aging measured by denaturation times of tail tendon collagen in urea.
Urine osmolality measured by vapor pressure osmometer after dehydration.
Immune function assessed by PHA-induced splenic lymphocyte proliferation in vitro and plaque-forming cell responses to SRBC in vivo.
Body fat measured chemically via solvent extraction of dehydrated tissue samples.
Summary Table of Aging Markers by Group
Marker Fed ob/ob Fed +/+ Restricted ob/ob Restricted +/+ Interpretation
Body Fat (%) ~66 22 ~48 13 Ob/ob mice retain high fat even restricted
Mean Lifespan (days) 755 971 823 810 Food restriction increases lifespan in ob/ob mice
Max Lifespan (days) 893 954 1307 1287 Max lifespan improved by restriction
Collagen Aging Rate Fast (accelerated) Normal Slow (retarded) Slow (retarded) Related to food intake, not adiposity
Urine Concentrating Ability High, no decline with age Declines with age Declines slowly Declines slowly Obesity does not impair this function
Immune Response Severely reduced (~10%) Moderately reduced Severely reduced (~10%) Slightly improved Immune aging not improved by restriction in obese mice
Key Insights
Longevity extension by food restriction is independent of adiposity levels.
Collagen aging is directly related to food consumption, not fat content.
Obesity does not necessarily impair certain renal functions during aging.
Immune function decline with age is exacerbated by obesity but is not rescued by food restriction in obese mice.
Aging is a multifactorial process with independent physiological components.
Final Remarks
This comprehensive study provides compelling evidence that lifespan extension by food restriction is primarily driven by the reduction in caloric intake rather than by decreased fat mass. It highlights the complexity of aging, showing that different physiological systems age at different rates and respond differently to genetic and environmental factors. The findings have significant implications for understanding obesity, aging, and dietary interventions in mammals, including humans.
Smart Summary...
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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vmsdiqjm-7013
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Effects of desiccation
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Effects of desiccation stress
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This study presents a systematic review and pooled This study presents a systematic review and pooled survival analysis quantifying the effects of desiccation stress (humidity) and temperature on the adult female longevity of Aedes aegypti and Aedes albopictus, the primary mosquito vectors of arboviral diseases such as dengue, Zika, chikungunya, and yellow fever. The research addresses a critical gap in vector ecology and epidemiology by providing a comprehensive, quantitative model of how humidity influences adult mosquito survival, alongside temperature effects, to improve understanding of transmission dynamics and enhance predictive models of disease risk.
Background
Aedes aegypti and Ae. albopictus are globally invasive mosquito species that transmit several major arboviruses.
Adult female mosquito longevity strongly impacts transmission dynamics because mosquitoes must survive the extrinsic incubation period (EIP) to become infectious.
While temperature effects on mosquito survival have been widely studied and incorporated into models, the role of humidity remains poorly quantified despite being ecologically significant.
Humidity influences mosquito survival via desiccation stress, affecting water loss and physiological function.
Environmental moisture also indirectly affects mosquito populations by altering evaporation rates in larval habitats, impacting larval development and adult body size, which affects vectorial capacity.
Understanding the temperature-dependent and non-linear effects of humidity can improve ecological and epidemiological models, especially in arid, semi-arid, and seasonally dry regions, which are understudied.
Objectives
Systematically review experimental studies on temperature, humidity, and adult female survival in Ae. aegypti and Ae. albopictus.
Quantify the relationship between humidity and adult survival while accounting for temperature’s modifying effect.
Provide improved parameterization for models of mosquito populations and arboviral transmission.
Methods
Systematic Literature Search: 1517 unique articles screened; 17 studies (16 laboratory, 1 semi-field) met inclusion criteria, comprising 192 survival experiments with ~15,547 adult females (8749 Ae. aegypti, 6798 Ae. albopictus).
Inclusion Criteria: Studies must report survival data for adult females under at least two temperature-humidity regimens, with sufficient methodological detail on nutrition and hydration.
Data Extraction: Variables included species, survival times, mean temperature, relative humidity (RH), and provisioning of water, sugar, and blood meals. Saturation vapor pressure deficit (SVPD) was calculated from temperature and RH to represent desiccation stress.
Survival Time Simulation: To harmonize disparate survival data formats (survival curves, mean/median longevity, survival proportions), individual mosquito survival times were simulated via Weibull and log-logistic models.
Pooled Survival Analysis: Stratified and mixed-effects Cox proportional hazards regression models were used to estimate hazard ratios (mortality risks) associated with temperature, SVPD, and nutritional factors.
Model Selection: SVPD was found to fit survival data better than RH or vapor pressure.
Sensitivity Analyses: Included testing model robustness by excluding individual studies and comparing results using only Weibull simulations.
Key Quantitative Findings
Parameter Ae. aegypti Ae. albopictus Notes
Temperature optimum (lowest mortality hazard) ~27.5 °C ~21.5 °C Ae. aegypti optimum higher than Ae. albopictus
Mortality risk trend Increases non-linearly away from optimum; sharp rise at higher temps Similar trend; possibly slightly better survival at lower temps Mortality rises rapidly at high temps for both species
Effect of desiccation (SVPD) Mortality hazard rises steeply from 0 to ~1 kPa SVPD, then more gradually Mortality hazard increases with SVPD but with less clear pattern Non-linear and temperature-dependent relationship
Species comparison (stratified model) Generally lower mortality risk than Ae. albopictus across most conditions Higher mortality risk compared to Ae. aegypti Differences not significant in mixed-effects model
Nutritional provisioning effects Provision of water, sugar, blood meals significantly reduces mortality risk Same as Ae. aegypti Provisioning modeled as binary present/absent
Qualitative and Contextual Insights
Humidity is a significant and temperature-dependent factor affecting adult female survival in Ae. aegypti, with more limited but suggestive evidence for Ae. albopictus.
Mortality risk increases sharply with desiccation stress (SVPD), especially at higher temperatures.
Ae. aegypti tends to have higher survival and a higher thermal optimum than Ae. albopictus, aligning with their geographic distributions—Ae. aegypti favors warmer, drier climates while Ae. albopictus tolerates cooler temperatures.
Provisioning of water and nutrients (sugar, blood) markedly improves survival, reflecting the importance of hydration and energy intake.
The findings support that humidity effects are underrepresented in current mosquito and disease transmission models, which often rely on simplistic or threshold-based mortality assumptions.
The use of SVPD (a measure of desiccation potential) rather than relative humidity or vapor pressure is more appropriate for modeling mosquito survival related to desiccation.
There is substantial unexplained variability among studies, likely due to unmeasured factors such as mosquito genetics, experimental protocols, and microclimatic conditions.
The majority of studies used laboratory settings and tropical/subtropical strains, with very limited data from arid or semi-arid climates, a critical gap given the importance of humidity fluctuations there.
Microclimatic variability and mosquito behavior (e.g., seeking humid refugia) may mitigate desiccation effects in the field, so laboratory results may overestimate mortality under natural conditions.
The study highlights the need for more field-based and arid region studies, and for models to incorporate nonlinear and interactive effects of temperature and humidity on mosquito survival.
Timeline Table: Study Selection and Analysis Process
Step Description
Literature search (Feb 2016) 1517 unique articles screened
Full text review 378 articles assessed for eligibility
Final inclusion 17 studies selected (16 lab, 1 semi-field)
Data extraction Survival data, temperature, humidity, nutrition, species, setting
Survival time simulation Weibull and log-logistic models used to harmonize survival data
Pooled survival analysis Stratified and mixed-effects Cox regression models
Sensitivity analyses Exclusion of individual studies, Weibull-only simulations
Model selection SVPD chosen as best humidity metric
Definitions and Key Terms
Term Definition
Aedes aegypti Primary mosquito vector of dengue, Zika, chikungunya, and yellow fever viruses
Aedes albopictus Secondary vector species with broader climatic tolerance, also transmits arboviruses
Saturation Vapor Pressure Deficit (SVPD) Difference between actual vapor pressure and saturation vapor pressure; a measure of drying potential/desiccation stress
Extrinsic Incubation Period (EIP) Time required for a virus to develop within the mosquito before it can be transmitted
Desiccation stress Physiological stress from water loss due to low humidity, impacting mosquito survival
Stratified Cox regression Survival analysis method allowing baseline hazards to vary by study
Mixed-effects Cox regression Survival analysis
Smart Summary
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6091bea7-3a23-4d1c-8647-5f933aff91ac
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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qrlwojjn-3033
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xevyo
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Effect of supplemented
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Effect of supplemented water on fecundity
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The study “Effect of Supplemented Water on Fecundi The study “Effect of Supplemented Water on Fecundity and Longevity” examines how different types of water—particularly fruit-infused or nutrient-enriched water—affect the reproductive output (fecundity) and overall lifespan (longevity) of a test organism. The experiment compares the impact of control water versus various supplemented waters such as apple water, showing how hydration quality can influence biological performance.
The findings demonstrate that apple-supplemented water produced the highest fecundity, meaning it led to the greatest number of eggs or offspring compared with all other treatments. This suggests that certain nutrients present in fruit-based water may stimulate reproductive capacity. However, results for longevity were mixed and highly variable, with some supplemented waters increasing lifespan and others having minimal or inconsistent effects. The study highlights the complexity of how hydration quality influences biological processes, emphasizing that while enriched water can boost reproduction, its effects on longevity are not uniform.
Overall, the research concludes that supplemented water can significantly enhance fecundity, but its impact on lifespan depends on the type of supplement and biological conditions, suggesting important implications for nutritional interventions and life-history strategies.
If you want, I can also provide:
✅ A short summary
✅ A 3–4 line description
✅ A student-friendly simple explanation
✅ Quiz questions from this file
Just tell me!...
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bd79e6c3-515f-429b-a541-2c97c10d5086
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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okhjmgem-7490
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Effect of eliminating
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Effect of eliminating chronic diseases
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xevyo-base-v1
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Summary
This study, published in Revista de Saúde Summary
This study, published in Revista de Saúde Pública (2013), investigates whether the elimination of certain chronic diseases can lead to a compression of morbidity among elderly individuals in São Paulo, Brazil. It uses population-based data from the 2000 SABE (Health, Wellbeing and Ageing) study and official mortality records to evaluate changes in disability-free life expectancy (DFLE) resulting from the hypothetical removal of specific chronic conditions.
Background and Objectives
Chronic non-communicable diseases (NCDs) such as cardiovascular diseases, diabetes, and chronic pulmonary conditions account for approximately 50% of diseases in developing countries and are major contributors to morbidity and mortality.
In Brazil, these diseases represent the main health burden and priority for healthcare systems.
The compression of morbidity theory posits that delaying the onset of debilitating diseases compresses the period of morbidity into a shorter segment at the end of life, thus increasing healthy life expectancy.
Other theories include:
Expansion of morbidity: Mortality declines due to reduced lethality but incidence remains or increases, leading to longer periods of morbidity.
Dynamic equilibrium: Both mortality and morbidity decline, keeping years lived with severe disability relatively constant.
The study aims to analyze whether eliminating certain chronic diseases would compress morbidity among elderly individuals, improving overall health expectancy.
Methodology
Design: Analytical, population-based, cross-sectional study.
Population: 2,143 elderly individuals (aged 60+) from São Paulo, Brazil, sampled probabilistically in 2000 as part of the SABE study.
Data collection:
Structured questionnaire covering sociodemographics, health status, functional capacity, and chronic diseases.
Self-reported presence of 9 chronic diseases based on ICD-10: systemic arterial hypertension, diabetes mellitus, heart disease, lung disease, cancer, joint disease, cerebrovascular disease, falls in previous year, and nervous/psychiatric problems.
Functional disability defined by difficulties in activities of daily living (dressing, eating, bathing, toileting, ambulation, fecal and urinary incontinence).
Statistical analysis:
Sullivan’s method used to compute life expectancy (LE) and disability-free life expectancy (DFLE).
Cause-deleted life tables estimated probabilities of death with elimination of specific diseases.
Multiple logistic regression (controlling for age) assessed disability prevalence changes with disease elimination.
Assumption: independence between causes of death and disability.
Sampling weights and corrections for design effects were applied to represent the São Paulo elderly population.
Key Findings
Sample Characteristics
Females represented 58.6% of the sample.
Higher proportion of women aged 75+ (24.2%) than men (19.2%).
Women more frequently widowed or single; men had higher employment rates.
Women more likely to live alone.
Smart Summary
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187ddbfd-84ab-4571-9e41-099455906034
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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okwjawrr-5385
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Effect of Nutritional
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Effect of Nutritional Interventions on Longevity
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xevyo-base-v1
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The study “Effect of Nutritional Interventions on The study “Effect of Nutritional Interventions on Longevity of Senior Cats” investigates whether specific dietary modifications can extend the lifespan and improve the health of aging cats. Aging in cats is associated with oxidative stress, declining organ function, and increased vulnerability to disease, and the study explores whether nutrition can mitigate these effects. It evaluates three diets: a control diet, a diet enriched with antioxidants (vitamin E and β-carotene), and a third diet combining antioxidants with additional prebiotics and omega-6 and omega-3 fatty acids.
The researchers conducted a multi-year trial using healthy mixed-breed cats aged 7–17 years, divided equally among the three diet groups. Health markers, blood values, body composition, and survival were monitored throughout the cats' lives. Results showed that cats fed Diet 3—the diet containing antioxidants, chicory root (prebiotic), and a blend of fatty acids—experienced significant health benefits. These cats maintained better body weight, body condition, lean body mass, bone density, and healthier gut microflora than cats on the other diets. They also had higher levels of serum vitamin E, β-carotene, and linoleic acid.
Most importantly, Diet 3 significantly increased lifespan. Cats on this diet had a 61% lower hazard of death compared with those on the control diet, living on average about one year longer when adjusted for age. They also showed fewer cases of thyroid disease and a trend toward reduced gastrointestinal pathology.
The study concludes that a multi-nutrient dietary strategy—combining antioxidants, prebiotics, and essential fatty acids—can meaningfully improve longevity and overall health in senior cats, offering evidence that targeted nutrition plays a powerful role in healthy aging.
If you want, I can also provide:
✅ A shorter summary
✅ A 1-paragraph description
✅ MCQs/quiz from the file
✅ A simplified student-friendly version
...
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ac6b20fd-5c74-4e34-bbf1-42e3985b17e8
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8684964a-bab1-4235-93a8-5fd5e24a1d0a
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skdznffn-5496
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xevyo
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/home/sid/tuning/finetune/backend/output/xevyo-bas /home/sid/tuning/finetune/backend/output/xevyo-base-v1/merged_fp16_hf...
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Effect of Exceptional
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Effect of Exceptional Parental Longevity
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xevyo-base-v1
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Summary
This study investigates the relationship Summary
This study investigates the relationship between exceptional parental longevity and the prevalence of cardiovascular disease (CVD) in their offspring, with a focus on whether lifestyle, socioeconomic status, and dietary factors influence this association. Conducted on a cohort of Ashkenazi Jewish adults aged 65-94, the research compares two groups: offspring of parents with exceptional longevity (OPEL), defined as having at least one parent living beyond 95 years, and offspring of parents with usual survival (OPUS), whose parents did not survive past 95 years. The study finds that OPEL exhibit significantly lower prevalence of hypertension, stroke, and overall cardiovascular disease compared to OPUS, independent of lifestyle, socioeconomic, and nutritional differences, thus highlighting a probable genetic influence on disease-free survival and longevity.
Background and Rationale
Individuals with exceptional longevity often experience a delay or absence of age-related diseases, making them models for studying healthy aging.
Longevity has a heritable component, with genetic markers linked to extended lifespan and resistance to diseases like CVD.
Previous studies have shown that offspring of exceptionally long-lived parents have lower incidence of CVD and other age-related illnesses.
Lifestyle factors such as physical activity, diet, smoking status, and socioeconomic status are known to influence cardiovascular health in the general population.
Prior to this study, no research compared lifestyle factors between offspring of exceptionally long-lived parents and those of usual longevity to isolate genetic effects from environmental factors.
Study Design and Methods
Population: 845 Ashkenazi Jewish adults aged 65-94 years; 395 OPEL and 450 OPUS.
Definition:
OPEL: At least one parent lived past 95 years.
OPUS: Both parents died before 95 years.
Recruitment: Systematic searches via voter registration, synagogues, community groups, and advertisements.
Exclusion Criteria: Baseline dementia, severe sensory impairments, or sibling already enrolled.
Data Collection:
Medical history including hypertension (HTN), diabetes mellitus (DM), myocardial infarction (MI), congestive heart failure (CHF), coronary interventions, and stroke.
Lifestyle factors: smoking history, alcohol use, physical activity level.
Socioeconomic factors: education and social strata score.
Dietary intake assessed in a subgroup (n=234) using the Block Brief Food Frequency Questionnaire (FFQ 2000).
Physical measures: height, weight, waist circumference; BMI calculated.
Analysis:
Comparison of prevalence of diseases and lifestyle variables between OPEL and OPUS.
Statistical adjustments for age, sex, BMI, tobacco use, social strata, and physical activity.
Stratified analyses by cardiovascular risk status (high vs. low).
Interaction testing between group status and lifestyle/socioeconomic factors.
Key Findings
Demographics and Lifestyle Factors
Characteristic OPEL (n=395) OPUS (n=450) p-value
Female (%) 59 50 <0.01
Age (years, mean ± SD) 75 ± 6 76 ± 7 <0.01
Education (years) 17 ± 3 17 ± 3 0.55
Social strata score (median, IQR) 56 (28-66) 56 (28-66) 0.76
Ever smokers (%) 55 54 0.80
Current smokers (%) 3 3 0.94
Alcohol use past year (%) 90 88 0.32
Strenuous physical activity (times/week, median) 3 (0-4) 3 (0-4) 0.71
Walking endurance >30 minutes (%) 77 70 0.05
No significant differences in lifestyle factors (smoking, alcohol, physical activity) or socioeconomic status between OPEL and OPUS.
OPEL reported greater walking endurance despite similar physical activity frequency.
Physical Characteristics and Disease Prevalence
Condition / Measure OPEL OPUS p-value OR (95% CI)a
BMI (mean ± SD) 27.5 ± 4.9 27.8 ± 4.7 0.34 Not specified
Obesity (%) (BMI≥30) 26 27 0.84 Not specified
Abdominal obesity (%) 48 48 0.95 Not specified
Systolic BP (mmHg) 129 ± 17 129 ± 17 0.78 Not specified
Diastolic BP (mmHg) 74 ± 9 74 ± 10 0.92 Not specified
Antihypertensive medication use (%) 39 49 <0.01 Not specified
Hypertension (%) 42 51 <0.01 0.71 (0.53–0.95)
Diabetes mellitus (%) 7 11 0.10 0.70 (0.43–1.15) NS
Myocardial infarction (%) 5 7 0.12 0.77 (0.42–1.42) NS
Stroke (%) 2 5 <0.01 0.35 (0.14–0.88)
Cardiovascular disease (composite) (%) 12 20 <0.01 0.65 (0.43–0.98)
OPEL had significantly lower odds of hypertension, stroke, and overall CVD compared to OPUS after adjusting for age and sex.
No significant differences observed for diabetes, MI, CHF, or coronary interventions after adjustment.
OPUS more frequently used antihypertensive medications despite similar blood pressure readings.
Stratified Cardiovascular Risk Analysis
Among high-risk individuals (defined by diabetes or ≥2 risk factors: obesity, hypertension, smoking), OPEL had a significantly lower prevalence of CVD compared to OPUS (OR 0.45; p=0.01).
Among low-risk individuals, no significant difference in CVD prevalence was observed between groups.
Significant interaction found between group status and tobacco use:
Tobacco use was not significantly associated with increased CVD odds in OPEL.
Tobacco use was nearly significantly associated with increased CVD odds in OPUS (p=0.07).
Dietary Intake (Subgroup, n=234)
Dietary Component OPEL OPUS p-value Adjusted p-valuea
Total daily calories (kcal) 1119 (906–1520) 1218 (940–1553)
Smart Summary
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Eating for Health and Longevity
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“Eating for Health and Longevity” is a practical, “Eating for Health and Longevity” is a practical, evidence-based guide created by SUNY Downstate Health Sciences University to help individuals improve or even reverse chronic disease through a whole-food, plant-based (WFPB) diet. Designed as an accessible handbook, the document explains why diets rich in unprocessed plant foods—vegetables, fruits, whole grains, legumes, nuts, and seeds—can dramatically enhance long-term health, promote healthy weight, and reduce the risk of conditions such as diabetes, heart disease, obesity, and high blood pressure.
The guide defines a WFPB diet as centered on natural, minimally processed plants while minimizing or eliminating meat, dairy, eggs, refined oils, refined grains, added sugars, and highly processed foods. It distinguishes WFPB eating from veganism by emphasizing nutritional quality rather than simply the absence of animal products.
It offers detailed, beginner-friendly guidance on:
What to eat (whole grains, legumes, vegetables, fruits, nuts, seeds, unsweetened plant milks)
What to avoid (meat, processed foods, refined sugars, oils, dairy, refined grains)
Step-by-step ways to transition gradually without overwhelm
Affordable, nutrient-dense sources of plant protein
Shopping lists and cost-saving strategies
Cooking techniques without oil, including sautéing with water or broth, steaming, roasting with parchment, and air frying
Healthy substitutions for meat, dairy, eggs, oil, and sugar
Motivation, support, and educational resources, including films, books, websites, and community groups
The guide also includes a rich section on herbs and spices that add flavor while providing antioxidant and anti-inflammatory benefits, such as turmeric, rosemary, ginger, basil, garlic, cinnamon, and cumin.
In closing, the document encourages readers to view food as medicine—a central pillar of lifestyle medicine alongside exercise, sleep, stress management, and avoiding harmful substances. It positions WFPB eating as an empowering, sustainable pathway toward vibrant health, chronic disease prevention, and longevity....
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Summary: Eating for Health and Longevity – A Pract Summary: Eating for Health and Longevity – A Practical Guide to Whole-Food, Plant-Based Diets
This guide, produced by SUNY Downstate Health Sciences University, provides a comprehensive, evidence-based overview of adopting a whole-food, plant-based (WFPB) diet to promote health, prevent chronic disease, and improve longevity. It offers practical advice for transitioning to plant-based eating, highlights nutritional benefits, and addresses common concerns and misconceptions.
Core Concepts of a Whole-Food, Plant-Based Diet
Definition: A WFPB diet emphasizes eating whole, minimally processed plant foods such as vegetables, fruits, whole grains, legumes, nuts, and seeds.
Exclusions: It minimizes or avoids meat, poultry, fish/seafood, eggs, dairy, refined carbohydrates (e.g., white bread, white rice), refined sugars, extracted oils, and highly processed foods.
Difference from Vegan Diet: Unlike some vegan diets, which may include refined grains, sweeteners, and oils, the WFPB diet focuses on whole foods for optimal health.
Health Benefits
Chronic Disease Prevention and Reversal: WFPB diets can prevent, manage, and sometimes reverse diseases such as diabetes, heart disease, obesity, and hypertension.
Weight Management: Effective for losing excess weight and maintaining a healthy weight.
Longevity and Vitality: Promotes vibrant health and potentially longer life by reducing lifestyle-related risk factors.
Foods to Include and Avoid
Foods to Eat and Enjoy Foods to Avoid or Minimize
Fresh and frozen vegetables Meats (red, processed, poultry, fish/seafood)
Fresh fruits Refined grains (white rice, white pasta, white bread)
Whole grains (oats, quinoa, barley) Products with refined sugars or sweeteners (sodas, candy)
Legumes (peas, lentils, beans) Highly processed or convenience foods with added salt
Unsalted nuts and seeds Eggs and dairy products
Dried fruits without additives Processed plant-based meat, cheese, or butter alternatives
Unsweetened non-dairy milks Refined, extracted oils (olive oil, canola, vegetable)
Alcoholic beverages
Smart Summary
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EXERCISE FOR LONGEVITY
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EXERCISE FOR LONGEVITY
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The Longevity Exercise Guide is a clear, actionabl The Longevity Exercise Guide is a clear, actionable, science-based blueprint for building an exercise routine that maximizes both healthspan and lifespan. Written by longevity researcher Nina Patrick, PhD, the guide distills the most important forms of physical activity—strength, aerobic, anaerobic, flexibility, stability, and NEAT—into a simple weekly plan anyone can follow. The premise is that exercise is the most powerful “longevity drug” available, with research showing it prevents disease, preserves independence, and protects metabolism and cognitive function as we age.
The guide teaches you how to train your body so that at age 100, you can still perform essential daily tasks—carrying groceries, climbing stairs, hiking, balancing, lifting, and moving confidently through life. It emphasizes consistency, personalization, and a balanced mix of training styles that work together to delay aging at the cellular, metabolic, and functional levels.
🧩 What the Guide Covers
1. Strength Training — The Foundation of Aging Well
Prevents muscle loss, frailty, and poor mobility
Recommended 2–3 full-body sessions/week, 45–60 minutes
Mix of heavy low-rep strength work + lighter high-rep endurance work
Includes weights, resistance bands, and bodyweight movements
Longevity_Exercise_Guide (
Strength is directly tied to independence in old age.
2. Aerobic Exercise — Boosting Metabolism & Mitochondria
Brisk walking, running, swimming, cycling
Key for mitochondrial health, cardiovascular fitness, disease prevention
Target: 3 hours/week (150 minutes minimum)
Low-intensity “zone 2” style cardio at 65–75% max HR
Longevity_Exercise_Guide (
Aerobic training slows metabolic aging and improves energy systems.
3. Anaerobic Exercise — Increasing VO₂ Max
Short, fast, high-intensity intervals (HIIT, hard cycling, rowing)
VO₂ max is the strongest predictor of longevity
Suggested: 1–2 intense sessions per week, 30 minutes each
Longevity_Exercise_Guide (
Maintains peak cardiovascular performance as VO₂ max naturally declines with age.
4. Flexibility & Stability — Protecting Balance and Preventing Falls
Yoga, pilates, planks, stretching
Critical because falls are the #1 cause of injury and death in older adults
Enhances posture, core strength, mobility, and balance
Longevity_Exercise_Guide (
Flexibility + stability ensure you can move safely for life.
5. NEAT — The Most Overlooked Longevity Tool
Non-Exercise Activity Thermogenesis = everything you do outside workouts
(e.g., walking, standing, chores)
Boosts daily calorie burn
Counters modern sedentary lifestyles
Reduces metabolic disease and weight gain
Examples: daily steps, walking for errands, housework, standing more
Longevity_Exercise_Guide (
NEAT is essential because most people fail to move enough outside formal workouts.
🧭 Weekly Longevity Blueprint
The guide provides a sample week integrating all modalities:
Strength: 3 full-body sessions
Aerobic: 3 brisk walks
Anaerobic: 1 HIIT/VO₂ max workout
Flexibility/Stability: daily stretching + 1 yoga/pilates class
NEAT: daily 30-minute walk
Longevity_Exercise_Guide (
This structure covers every dimension of functional longevity.
💡 Why This Guide Matters
The Longevity Exercise Guide reframes exercise not as a fitness task but as a lifelong strategy for independence, vitality, and disease prevention. Rather than prescribing a rigid routine, it teaches how to build a personalized, sustainable program that strengthens the body’s most essential aging-related systems:
muscle strength
cardiovascular endurance
metabolic flexibility
balance and mobility
everyday movement patterns
It’s a practical roadmap for anyone who wants to age not only longer, but better....
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ESSENTIAL STEPS TO HEALTH
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ESSENTIAL STEPS TO HEALTHY AGING
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“Essential Steps to Healthy Aging” is an education “Essential Steps to Healthy Aging” is an educational guide created by Kansas State University to teach people how to age in the healthiest, happiest, and most independent way possible. The document explains that while ageing is natural and unavoidable, our daily habits throughout life have a powerful impact on how well we age. It presents 12 essential lifestyle behaviors that research shows contribute to living longer, staying healthier, and maintaining quality of life into older age.
The file includes a leader’s guide, a fact sheet for participants, an interactive activity, and an evaluation form, making it a complete learning program for communities, workshops, or health-education sessions.
⭐ Core Message of the Document
Healthy aging is not about avoiding age—it’s about supporting the body, mind, and spirit across the entire lifespan.
The guide encourages people to take responsibility for their health and to make small but meaningful changes that promote lifelong well-being.
⭐ The 12 Essential Steps to Healthy Aging
(as presented in the fact sheet)
Essential-Steps-to-Health-Aging
Maintain a positive attitude
Eat healthfully
Engage in regular physical activity
Exercise your brain
Engage in social activity
Practice lifelong learning
Prioritize safety
Visit the doctor regularly
Manage your stress
Practice good financial management
Get enough sleep
Take at least 10 minutes a day for yourself
These steps address all areas of life—physical health, mental sharpness, emotional balance, relationships, safety, finances, and self-care.
⭐ Program Purpose
The guide aims to help people understand that:
Healthier choices today lead to a healthier and more independent future.
Positive habits at any age can improve longevity and quality of life.
Ageing well is possible through prevention, awareness, and small daily behaviors.
⭐ Contents of the Document
✔ 1. Leader’s Guide
Explains how to run the program, prepare materials, engage participants, and guide discussions.
Essential-Steps-to-Health-Aging
✔ 2. Essential Steps to Healthy Aging (Fact Sheet)
A clear, easy-to-read summary of all 12 steps and why they matter.
✔ 3. Activity: My Healthy Aging Plan
Participants write specific goals for each of the 12 steps, helping them create a personalized lifestyle improvement plan.
Essential-Steps-to-Health-Aging
✔ 4. Evaluation Form
Participants reflect on what they learned and choose which positive habits they plan to adopt going forward.
Essential-Steps-to-Health-Aging
⭐ Overall Meaning
The document teaches that healthy aging is achievable for everyone, regardless of age. By focusing on attitude, nutrition, physical health, mental activity, social connections, safety, finances, stress, sleep, and self-care, people can enjoy a longer life with greater independence, better health, and improved well-being.
It is both a practical guide and a motivational toolkit for anyone interested in ageing well....
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ESSENTIAL STEPS TO HEALTH
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ESSENTIAL STEPS TO HEALTHY AGING
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Kansas State University Agricultural Experiment St Kansas State University Agricultural Experiment Station and Cooperative Extension Service
Author: Erin Yelland, Ph.D., Extension Specialist, Adult Development and Aging
Program Overview
The Essential Steps to Healthy Aging is a structured educational program designed to motivate and empower participants to adopt healthy lifestyle behaviors that foster optimal aging. Developed by Kansas State University’s Cooperative Extension Service, this program highlights that aging is inevitable, but how individuals care for themselves physically, mentally, and emotionally throughout life significantly influences the quality of their later years. The program promotes the idea that healthy lifestyle changes can positively impact well-being at any age.
Core Concept
Aging well is a lifelong process influenced by daily choices. Research on centenarians (people aged 100 and over) shows that adopting certain healthy behaviors contributes to longevity and improved quality of life. The program introduces 12 essential steps to maintain health and enhance successful aging.
The 12 Essential Steps to Healthy Aging
Step Number Essential Healthy Behavior
1 Maintain a positive attitude
2 Eat healthfully
3 Engage in regular physical activity
4 Exercise your brain
5 Engage in social activity
6 Practice lifelong learning
Smart Summary
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Dublin Longevity
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Dublin Longevity Declaration
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Consensus Recommendation to Immediately Expand Res Consensus Recommendation to Immediately Expand Research on Extending Healthy Human Lifespans
For millennia, the consensus of the general public has been that aging is inevitable. For most of our history, even getting to old age was a significant accomplishment – and while centenarians have been around at least since the time of the Greeks, aging was never of major interest to medicine.
That has changed. Longevity medicine has entered the mainstream. First, evidence accumulated that lifestyle modifications prevent chronic diseases of aging and extend healthspan, the healthy and highly functional period of life. More recently, longevity research has made great progress – aging has been found to be malleable and hundreds of interventional strategies have been identified that extend lifespan and healthspan in animal models. Human clinical studies are underway, and already early results suggest that the biological age of an individual is modifiable.
A concerted effort has been made in the longevity field to institutionalize the word “healthspan”. Why healthspan (how long we stay healthy) and not its side-effect of lifespan (how long we live)? The reasons are linked more to perception than reality. Fundamental to this need to highlight healthspan is the idea that individuals get when they are asked if they want to live longer. Many imagine their parents or grandparents at the end of their lives when they often have major health issues and low quality of life. Then they conclude that they would not choose to live longer in that condition. This is counter to longevity research findings, which show that it is possible to intervene in late middle life and extend both healthspan and lifespan simultaneously. Emphasizing healthspan also reduces concerns of some individuals about whether it is ethical to live longer.
A drawback of this exists, though: many current longevity interventions may extend healthspan more than lifespan. Lifestyle interventions such as exercise probably fit this mold. Many interventions that have dramatic health-extending effects in invertebrate models have more modest effects in mice, and there is a concern that they will be further reduced in humans. In other words, the drugs and small molecules that we are excited about today may, despite their hefty development costs and lengthy approval processes, only extend average healthspan by five or ten years and may not extend maximum lifespan at all. Make no mistake, this would still represent a revolution in medical practice! A five-year extension in human healthspan, with equitable access for all people, would save trillions per year in healthcare costs, provide extra life quality across the entire population ...
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Drivers of your health
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Drivers of your health and longevity
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“Drivers of Your Health and Longevity” is a compre “Drivers of Your Health and Longevity” is a comprehensive report outlining the 23 key modifiable factors that significantly influence a person’s health, lifespan, and overall well-being. It emphasizes that 19 out of these 23 drivers lie outside the traditional healthcare system, meaning most of what determines longevity comes from everyday habits and environmental conditions.
These drivers are grouped into major categories:
1. Physical Inputs
Covers diet, supplements, substance use, hydration, and their direct effects on disease risk, cognitive health, and mortality. Examples include fasting improving metabolic health, omega-3 protecting the brain and heart, and sleep duration affecting mortality.
2. Movement
Includes mobility and exercise. The report highlights that regular physical activity can extend life by 3–5 years, reduce mortality risk, and improve overall physical and mental function.
3. Daily Living
Encompasses social interaction, productive activities, content consumption, and hygiene. Strong social relationships, volunteering, and balanced media usage are linked to better physical and mental health.
4. Exposure
Focuses on nature, atmospheric conditions, light, noise, and environmental materials. Evidence shows that nature exposure, reduced pollution, sunlight, and safe environments contribute to better mental health, reduced stress, and lower mortality.
5. Stress
Explains how both positive (eustress) and chronic stress affects disease risk, cognitive function, and life expectancy.
6. State of Being
Includes mindsets, beliefs, body composition, physical security, and economic security. Optimism, gratitude, financial stability, and safety are shown to have strong physiological and psychological benefits.
7. Healthcare
Covers vaccination, early detection, treatment, and medication adherence. Effective healthcare interventions (e.g., vaccines, screening, treatments) significantly reduce mortality and improve survival rates.
📌 Overall Purpose of the Report
The document emphasizes that longevity is not determined primarily by genetics or medical care, but by daily choices, behaviors, and environmental exposures. By optimizing these 23 modifiable drivers, individuals can dramatically improve their health span and lifespan.
If you want, I can also provide:
✅ A short summary
✅ A quiz based on this file
✅ Key insights
✅ A table of the 23 drivers
Just tell me!
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7b2a2799-a74e-4dd4-93a8-4bbabe61ca47
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Diet-dependent entropic a
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Diet-dependent entropic assessment of athletes’
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Cennet Yildiz1, Melek Ece Öngel2 , Bayram Yilmaz3 Cennet Yildiz1, Melek Ece Öngel2 , Bayram Yilmaz3 and Mustafa Özilgen1* 1Department of Food Engineering, Yeditepe University, Kayısdagi, Atasehir, Istanbul 34755, Turkey 2Nutrition and Dietetics Department, Yeditepe University, Kayısdagi, Atasehir, Istanbul 34755, Turkey 3Faculty of Medicine, Department of Physiology, Yeditepe University, Istanbul, Turkey
(Received 29 July 2021 – Final revision received 26 August 2021 – Accepted 26 August 2021)
Journal of Nutritional Science (2021), vol. 10, e83, page 1 of 8 doi:10.1017/jns.2021.78
Abstract Life expectancies of the athletes depend on the sports they are doing. The entropic age concept, which was found successful in the previous nutrition studies, will be employed to assess the relation between the athletes’ longevity and nutrition. Depending on their caloric needs, diets are designed for each group of athletes based on the most recent guidelines while they are pursuing their careers and for the post-retirement period, and then the metabolic entropy generation was worked out for each group. Their expected lifespans, based on attaining the lifespan entropy limit, were calculated. Thermodynamic assessment appeared to be in agreement with the observations. There may be a significant improvement in the athletes’ longevity if theyshift to a retirement diet after the age of 50. The expected average longevity for male athletes was 56 years for cyclists, 66 years for weightlifters, 75 years for rugby players and 92 years for golfers. If they should start consuming the retirement diet after 50 years of age, the longevity of the cyclists may increase for 7 years, and those of weightlifters, rugby players and golfers may increase for 22, 30 and 8 years, respectively.
Key words: Athletes’ diet: Athletes’ longevity: Entropic age: Lifespan entropy
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Diet in Longevity
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Diet in Longevity
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“Longevity Diet” is a concise, practical guide tha “Longevity Diet” is a concise, practical guide that outlines how specific dietary substitutions and eating patterns can support healthier aging, extend lifespan, and reduce the risk of chronic disease. The document promotes a nutrient-dense, low-inflammation way of eating that emphasizes whole foods, plant-forward choices, and strategic replacements for common staples that accelerate aging.
The guide presents a clear set of food swaps designed to improve metabolic health, reduce oxidative stress, and support a stronger, longer-living body. It recommends replacing refined starches—such as bread, pasta, and white rice—with vegetables, legumes, mushrooms, and whole grains like quinoa. Red and processed meats are minimized in favor of fatty fish (like salmon, mackerel, sardines), white meat, eggs, tofu, or mushrooms. High-fat spreads and dressings are replaced with extra-virgin olive oil and other healthy fats, while processed sugars and excessive salt are swapped for herbs, spices, and “Lite Salt.”
The document encourages replacing cow’s milk with plant-based alternatives such as coconut, hemp, or pea milk. Beverages like soda and commercial fruit juice are substituted with water, tea, herbal teas, or moderate coffee intake. Snacks high in sugar are replaced with fruit, natural sweeteners, or high-cocoa dark chocolate.
It also emphasizes using targeted nutritional supplements—such as B vitamins, iodine, selenium, vitamin D, vitamin K2, and magnesium—to address common micronutrient gaps. Specialized “longevity supplements,” such as those formulated to counteract cellular aging, are listed as complementary options.
The centerpiece of the document is the “10 Simple Rules of the Longevity Diet,” which provide deeper guidance: eat fewer refined starches, limit red meat, hydrate well, favor whole ingredients (30+ per week), maintain moderate protein intake, eat slightly less than full to promote metabolic health, include fermented foods, minimize alcohol, and avoid nutrient deficiencies.
Overall, the Longevity Diet promotes a style of eating that is diverse, minimally processed, rich in phytonutrients and healthy fats, and aligned with scientific insights into metabolic health, the gut microbiome, inflammation, and biological aging....
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Developmental Diet Alters
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Developmental Diet Alters the Fecundity–Longevity
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Drosophila melanogaster David H. Collins, PhD,*, D Drosophila melanogaster David H. Collins, PhD,*, David C. Prince, PhD, Jenny L. Donelan, MSc, Tracey Chapman, PhD , and Andrew F. G. Bourke, PhD School of Biological Sciences, University of East Anglia, Norwich, UK. *Address correspondence to: David H. Collins, PhD. E-mail: David.Collins@uea.ac.uk Decision Editor: Gustavo Duque, MD, PhD (Biological Sciences Section)
Abstract The standard evolutionary theory of aging predicts a negative relationship (trade-off) between fecundity and longevity. However, in principle, the fecundity–longevity relationship can become positive in populations in which individuals have unequal resources. Positive fecundity–longevity relationships also occur in queens of eusocial insects such as ants and bees. Developmental diet is likely to be central to determining trade-offs as it affects key fitness traits, but its exact role remains uncertain. For example, in Drosophila melanogaster, changes in adult diet can affect fecundity, longevity, and gene expression throughout life, but it is unknown how changes in developmental (larval) diet affect fecundity–longevity relationships and gene expression in adults. Using D. melanogaster, we tested the hypothesis that varying developmental diets alters the directionality of fecundity–longevity relationships in adults, and characterized associated gene expression changes. We reared larvae on low (20%), medium (100%), and high (120%) yeast diets, and transferred adult females to a common diet. We measured fecundity and longevity of individual adult females and profiled gene expression changes with age. Adult females raised on different larval diets exhibited fecundity–longevity relationships that varied from significantly positive to significantly negative, despite minimal differences in mean lifetime fertility or longevity. Treatments also differed in age-related gene expression, including for aging-related genes. Hence, the sign of fecundity–longevity relationships in adult insects can be altered and even reversed by changes in larval diet quality. By extension, larval diet differences may represent a key mechanistic factor underpinning positive fecundity–longevity relationships observed in species such as eusocial insects. Keywords: Aging, Eusociality, Life history, mRNA-seq, Nutrition
The standard evolutionary theory of aging predicts that, as individuals grow older, selection for increased survivorship declines with age (1). Therefore, individuals experience the age-related decrease in performance and survivorship that defines aging (senescence) (2). Additionally, given finite resources, individuals should optimize relative investment between reproduction and somatic maintenance (3). This causes tradeoffs between reproduction and longevity (4,5) with elevated reproduction often incurring costs to longevity (the costs of reproduction) (6). Such trade-offs and costs are evident in the negative fecundity–longevity relationships observed in many species. Although a negative fecundity–longevity relationship is typical, fecundity and longevity can become uncoupled (7) and some species or populations may exhibit positive fecundity– longevity relationships (4). This can occur for several reasons. First, in Drosophila melanogaster, mutations can increase longevity without apparent reproductive costs (8–11), particularly mutations in the conserved insulin/insulin-like growth factor signaling and target of rapamycin network (IIS-TOR).
This network regulates nutrient sensitivity and is an important component of aging across diverse taxa (2,12). Second, fecundity and longevity can become uncoupled when there is asymmetric resourcing between individuals (13,14). Within a population, well-resourced individuals may have higher fecundity and longevity than poorly resourced individuals, reversing the usual negative fecundity–longevity relationship. However, because costs of reproduction are not abolished even in well-resourced individuals (13,14), a within-individual trade-off between fecundity and longevity remains present. Third, fecundity and longevity can become uncoupled within and between the castes of eusocial insects (15–18), that is, species such as ants, bees, wasps, and termites with a longlived reproductive caste (queens or kings) and a short-lived non- or less reproductive caste (workers) (19–21). In some species, queens appear to have escaped costs of reproduction completely (22–25). This may have been achieved through rewiring the IIS-TOR network (12,26), which forms part of the TOR/IIS-juvenile hormone-lifespan and fecundity (TI-JLiFe) network hypothesized to underpin aging and longevity in eusocial insects by Korb et al....
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Life guidance
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Determination of signs of life
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The “Signs of Life – Guidance Visual Summary (v1.2 The “Signs of Life – Guidance Visual Summary (v1.2)” is a clinical guideline for healthcare professionals to determine whether a live birth has occurred before 24 weeks of gestation in cases where—after discussion with parents—active survival-focused care is not appropriate. It provides clear, compassionate instructions for identifying signs of life, documenting birth and death, communicating with parents, and delivering palliative and bereavement care.
signs-of-life-guidance-visual-s…
The guidance is designed to reduce uncertainty, ensure legal accuracy, protect families from additional trauma, and support parents through one of the most emotionally sensitive experiences in healthcare.
Core Components
1. Determining a Live Birth
A live birth is diagnosed when one or more persistent visible signs of life are observed:
Easily visible heartbeat
Visible pulsation of the umbilical cord
Breathing, crying, or sustained gasps
Definite, purposeful movement of arms or legs
signs-of-life-guidance-visual-s…
Not signs of life:
Brief reflexes—such as transient gasps, chest wall twitches, or short muscle movements only in the first minute after birth—do not constitute live birth.
signs-of-life-guidance-visual-s…
Clinicians are instructed to observe respectfully, often while the baby is held by the parents. A stethoscope is not required, and parents’ observations may be included if they choose to share them.
2. Actions After a Live Birth
Once a sign of life is seen:
A doctor (usually an obstetrician) must be called to confirm and document the live birth.
The doctor may rely on the midwife’s account and is not always required to attend in person.
Accurate documentation avoids legal complications when issuing a neonatal death certificate.
signs-of-life-guidance-visual-s…
Comfort care must then follow a perinatal palliative care pathway, addressing the baby’s needs and the parents’ emotional and physical well-being.
3. Communication With Parents
The guidance places strong emphasis on sensitive, trauma-reducing communication.
Parents should be gently told that:
Babies born before 24 weeks are extremely small and typically do not survive.
Babies who die just before birth may briefly show reflex movements that are not signs of life.
Babies who survive may show signs of life for minutes—or occasionally hours.
signs-of-life-guidance-visual-s…
Clinicians should:
Listen actively
Use the parents’ preferred language
Respect whether parents want the experience described as a “loss,” “death,” “end of pregnancy,” or “miscarriage”
signs-of-life-guidance-visual-s…
Each situation is unique and must be handled with individualized sensitivity.
4. Bereavement Care (For All Births)
Bereavement care is required in every case, regardless of signs of life.
The guidance instructs staff to:
Follow the National Bereavement Care Pathway
Provide privacy, time, and space
Support memory-making
Offer choices around burial, cremation, or sensitive disposal
Inform parents of support services and ensure follow-up with community care, GP, and mental health teams
signs-of-life-guidance-visual-s…
This ensures parents receive compassionate, individualized support during and after their loss.
5. Documenting Birth and Death
Documentation follows strict legal requirements:
If signs of life are present
A doctor and midwife must confirm and record the live birth.
A neonatal death certificate must be completed by a doctor who witnessed the signs—or the coroner must be informed.
Parents are required to register the birth and death.
signs-of-life-guidance-visual-s…
If no signs of life are present (miscarriage)
Document the miscarriage.
No legal registration is required, but offer a certificate of loss or certificate of birth.
signs-of-life-guidance-visual-s…
6. Included and Excluded Births
Included
In-hospital spontaneous births under 22+0 weeks
In-hospital births at 22+0 to 23+6 weeks where survival-focused care is not appropriate
Pre-hospital births under 22 weeks (same principles apply)
signs-of-life-guidance-visual-s…
Excluded
Medical terminations
Uncertain gestational age
Spontaneous births at 22–23+6 weeks where active neonatal care is planned or unclear
signs-of-life-guidance-visual-s…
Conclusion
The “Signs of Life – Guidance Visual Summary (v1.2)” is a clear and compassionate roadmap for clinicians caring for families experiencing extremely preterm birth where survival-focused care is not appropriate. It ensures:
>accurate identification of live birth
>consistent legal documentation
>sensitive communication
>high-quality palliative and bereavement care
respect for parents’ emotional needs and preferences
Its ultimate purpose is to provide clarity, compassion, and consistency during a profoundly difficult and delicate moment....
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Determinants of longevity
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Determinants of longevity
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The document “Determinants of Longevity” is a comp The document “Determinants of Longevity” is a comprehensive scientific review that explains why some people live longer than others. It explores how genetic, environmental, and medical factors combine to shape human lifespan, using evidence from demographic databases, epidemiological studies, and genetic research.
The paper highlights that in modern, industrialized societies, both maximum lifespan and average life expectancy have continued to rise, with no convincing evidence of a fixed biological limit of around 85 years. In fact, the largest improvements in survival have occurred among people aged 80 and older, showing that longevity can keep increasing as medical care and living conditions improve.
It explains that genetics accounts for about one-quarter of the variation in human lifespan, based on large twin studies. Certain genetic markers (such as specific HLA types or variants of the APOE gene) are associated with reaching extreme old age. However, genes alone cannot explain how fast life expectancy has risen in just a few generations—most gains come from environmental factors, including sanitation, reduced smoking, improved nutrition, better working conditions, and advances in healthcare.
The document also discusses extreme longevity (centenarians) and corrects earlier myths by showing that many historical claims of 120–150-year lifespans were exaggerations. Verified records today suggest human lifespan has no clear ceiling and continues to increase as mortality rates decline even at advanced ages.
Environmental and behavioral factors—such as socioeconomic status, education, diet, physical activity, body weight, alcohol consumption, and particularly smoking—play major roles in shaping longevity. Medical advances, including treatments for heart disease, infections, and age-related illnesses, contribute significantly to longer lives.
Finally, the paper concludes that while we can identify many influences on longevity at the population level, predicting an individual’s lifespan remains extremely difficult because longevity results from complex interactions among genes, behaviors, early-life conditions, and medical care....
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Determinants of longevity
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Determinants of longevity
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K. CHRISTENSENa & J. W. VAUPELb From abOdense K. CHRISTENSENa & J. W. VAUPELb From abOdense University Medical School, Odense, Denmark; bSanford Institute, Duke University, Durham, NC, USA; and aThe Danish Epidemiology Science Centre, The Steno Institute of Public Health, Department of Epidemiology and Social Medicine, Aarhus University Hospital, Aarhus, Denmark
Abstract. Christensen K, Vaupel JW (Odense University Medical School, Odense, Denmark; Sanford Institute, Duke University, Durham, NC, USA; and The Danish Epidemiology Science Centre, The Steno Institute of Public Health, Department of Epidemiology and Social Medicine, Aarhus University Hospital, Aarhus, Denmark). Determinants of longevity: genetic, environmental and medical factors (Review). J Intern Med 1996; 240: 333–41.
This review focuses on the determinants of longevity in the industrialized world, with emphasis on results from recently established data bases. Strong evidence is now available that demonstrates that in developed
Introduction
The determinants of longevity might be expected to be well understood. The duration of life has captured the attention of many people for thousands of years; an enormous array of vital-statistics data are available for many centuries. Life-span is easily measured compared with other health phenomena, and in many countries data are available on whole populations and not just study samples. Knowledge concerning determinants of human longevity, however, is still sparse, and much of the little that is known has been learned in recent years. This review
countries the maximum lifespan as well as the mean lifespan have increased substantially over the past century. There is no evidence of a genetically determined lifespan of around 85 years. On the contrary, the biggest absolute improvement in survival in recent decades has occurred amongst 80 year-olds. Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. The influence of both genetic and environmental factors on longevity can potentially be modified by medical treatment, behavioural changes and environmental improvements.
Keywords: centenarians, life expectancy, lifespan, mortality.
focuses on genetic, environmental and medical factors as determinants of longevity in developed countries and discusses alternative paradigms concerning human longevity.
How should longevity be measured?
Longevity can be studied in numerous ways; key questions include the following. How long can a human live? What is the average length of life? Are the maximum and average lengths of life approaching limits? Why do some individuals live longer than others? In addressing these questions, it is useful to
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study the maximum lifespan actually achieved in various populations, the mean lifespan, and the variation in lifespan. Estimating the maximum lifespan of human beings is simply a matter of finding a well-documented case report of a person who lived longer than other welldocumented cases. The assessment of mean lifespan in an actual population requires that the study population is followed from birth to extinction. An alternative approach is to calculate age-specific death rates at some point in time for a population, and then use these death rates to determine how long people would live on average in a hypothetical population in which these death rates prevailed over the course of the people’s lives. This second kind of mean lifespan is generally known as life expectancy. The life expectancy of the Swedish population in 1996 is the average lifespan that would be achieved by the 1996 birth cohort if Swedish mortality rates at each age remained at 1996 levels for the entire future life of this cohort. Assessment of determinants of life expectancy and variation in lifespan amongst individuals rely on demographic comparisons of different populations and on such traditional epidemiological designs as follow-up studies of exposed or treated versus nonexposed or nontreated individuals. Designs from genetic epidemiology – such as twin, adoption and other family studies – are useful in estimating the relative importance of genes and environment for the variation in longevity.
Determinants of extreme longevity
Numerous extreme long-livers have been reported in various mountainous regions, including Georgia, Kashmir, and Vilcabamba. In most Western countries, including the Scandinavian countries, exceptional lifespans have also been reported. Examples are Drachenberg, a Danish–Norwegian sailor who died in 1772 and who claimed that he was born in 1626, and Jon Anderson, from Sweden, who claimed to be 147 years old when he died in 1729. There is noconvincingdocumentationfortheseextremelonglivers. When it has been possible to evaluate such reports, they have proven to be very improbable [1, 2]. In countries, like Denmark and Sweden, with a long tradition of censuses and vital statistics, remarkable and sudden declines in the number of
extreme long-livers occur with the introduction of more rigorous checking of information on age of death, as the result of laws requiring birth certificates, the development of church registers and the establishment of statistical bureaus [3, 4]. This suggests that early extreme long-livers were probably just cases of age exaggeration. Today (March 1996), the oldest reported welldocumented maximum lifespan for females is 121 years [5] and for males 113 years [6]. Both these persons are still alive. Analyses of reliable cases of long-livers show that longevity records have been repeatedly broken over past decades [3, 6]; this suggests that even longer human lifespans may occur in the future. There has been surprisingly little success in identifying factors associated with extreme longevity. A variety of centenarian studies have been conducted during the last half century. As reviewed by Segerberg [7], most of the earlier studies were based on highly selected samples of individuals, without rigorous validation of the ages of reputed centenarians. During the last decade several more comprehensive, less selected centenarian studies have been carried out in Hungary [8], France [9], Finland [10] and Denmark [11]. A few specific genetic factors have been found to be associated with extreme longevity. Takata et al. [12] found a significantly lower frequency of HLA-DRw9 amongst centenarians than in an adult control group in Japan, as well as a significantly higher frequency of HLA-DR1. The HLA-antigens amongst the Japanese centenarians are negatively associated with the presence of autoimmune diseases in the Japanese population, which suggests that the association with these genetic markers is mediated through a lower incidence of diseases. More recently, both a French study [13] and a Finnish study [14] found a low prevalence of the e4 allele of apolipoprotein E amongst centenarians. The e4 allele has consistently been shown to be a risk factor both for coronary heart disease and for Alzheimer’s dementia. In the French study [13], it was also found that centenarians had an increased prevalence of the DDgenotype of angiotensin-converting enzyme (ACE) compared with adult controls. This result is contrary to what was expected as the DD-genotype of ACE has been reported to be associated with myocardial infarction. Only a few genetic association studies concerning extreme longevity have been published...
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Sports genomics:
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Current state of knowledge
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Sports Genomics: Current State of Knowledge and Fu Sports Genomics: Current State of Knowledge and Future Directions
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📘 Universal Description (Easy + App-Friendly)
Sports Genomics: Current State of Knowledge and Future Directions reviews what scientists currently know about how genetic variation influences athletic performance, physical fitness, training response, injury risk, and recovery, and explains where this field is heading in the future.
The document explains that athletic performance is complex and polygenic, meaning it is influenced by many genes, each with small effects, combined with training, environment, nutrition, psychology, and lifestyle. No single gene can determine whether a person will become an elite athlete.
The paper summarizes evidence linking genetics to traits such as:
endurance and aerobic capacity
muscle strength and power
speed and explosive performance
injury susceptibility
recovery and adaptation to training
It explains early approaches such as candidate gene studies (e.g., ACTN3, ACE) and highlights their limitations. The paper then discusses more advanced methods like genome-wide association studies (GWAS), which analyze thousands of genetic variants across large populations to better understand performance traits.
A major focus is the shift toward integrative “omics” approaches, including:
epigenetics (gene regulation)
transcriptomics (gene expression)
proteomics (proteins)
metabolomics (metabolic responses)
These approaches help explain how the body responds dynamically to exercise and training, rather than relying only on static DNA information.
The document also discusses practical applications, such as:
personalized training programs
injury prevention strategies
improved recovery planning
exercise prescription for health
However, it strongly warns that current genetic knowledge cannot accurately predict elite performance or talent, and that genetic testing should not be used for athlete selection—especially in children.
Ethical, legal, and social issues are emphasized, including:
genetic privacy and data protection
informed consent
misuse of genetic tests
genetic discrimination
gene doping
The paper concludes that the future of sports genomics lies in large collaborative studies, multi-omics integration, ethical regulation, and responsible application, with the primary goal of improving athlete health, safety, and long-term performance, not replacing coaching or talent development.
📌 Main Topics (Easy for Apps to Extract)
Sports genomics overview
Genetics and athletic performance
Polygenic traits in sport
Candidate genes vs GWAS
Multi-omics approaches
Gene–environment interaction
Training adaptation and recovery
Injury risk and genetics
Ethical issues in sports genomics
Future directions in sports science
🔑 Key Points (Notes / Slides Friendly)
Athletic performance is influenced by many genes
Genetics interacts with training and environment
Early gene studies had limited predictive value
GWAS and omics provide broader insight
Genetics cannot predict elite success
Ethical use of genetic data is essential
Future research requires large datasets
🧠 Easy Explanation (Beginner Level)
People perform differently in sports partly because of genetics, but training, diet, and environment matter just as much. Many genes work together, so no DNA test can choose future champions. Modern science now studies how genes change and respond to exercise to improve health and performance safely.
🎯 One-Line Summary (Perfect for Quizzes & Slides)
Sports genomics studies how genes and environment together influence performance and health, with future progress depending on big data, multi-omics research, and ethical use.
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Credible Power-Sharing
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Credible Power-Sharing and the Longevity
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“Credible Power-Sharing: Evidence From Cogovernanc “Credible Power-Sharing: Evidence From Cogovernance in Colombia” is a research study examining whether power-sharing institutions can help reduce violence and build political stability in regions historically affected by armed conflict. Focusing on a cogovernance reform in Colombia, the paper evaluates whether granting communities a formal role in local decision-making can create credible commitments between the state and citizens, thereby reducing conflict-related violence.
The reform introduced a municipal cogovernance mechanism that gave civilians shared authority over public resource allocation. The authors combine administrative data, qualitative fieldwork, and quantitative causal-inference methods to measure the reform’s effect on governance outcomes and security conditions.
The findings show that cogovernance significantly increased civilian participation, improved transparency in local government, and reduced opportunities for corruption. Most importantly, the study documents a substantial decline in violence, especially in areas with a strong presence of armed groups. The mechanism worked by enhancing the credibility of state commitments: when citizens gained real influence in local policy, trust increased, and armed groups had fewer incentives to interfere.
The paper concludes that credible power-sharing arrangements can meaningfully reduce violence when they provide communities with real authority and when institutions are robust enough to enforce shared decision-making. The Colombian case offers broader insights for countries attempting to transition out of conflict through participatory governance.
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Corporate Longevity
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Corporate Longevity Forecasting
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The 2018 Corporate Longevity Forecast: Creative De The 2018 Corporate Longevity Forecast: Creative Destruction is Accelerating is an executive briefing by Innosight that analyzes how rapidly companies are being displaced from the S&P 500, revealing a dramatic acceleration in corporate turnover and shrinking lifespans. The report shows that the average tenure of companies on the S&P 500 has fallen from 33 years in 1964 to 24 years in 2016, and is projected to decline to just 12 years by 2027. This trend signals an era of unprecedented marketplace turbulence driven by technological disruption, shifting customer expectations, and major structural economic forces.
The report highlights that at current churn rates—5.2% annually—half of today’s S&P 500 companies will be replaced within the next decade. It draws on historical data, additions and deletions to the index, and sector-specific disruption patterns. Companies leave the S&P 500 due to declining market capitalization, competitive displacement, mergers, acquisitions, and private equity buyouts. Notable exits between 2013–2017 include iconic firms such as Yahoo!, DuPont, Urban Outfitters, Staples, Starwood Hotels, DirecTV, EMC, and Whole Foods.
The document identifies five major forces driving this accelerating creative destruction:
Digital disruption in retail, leading to widespread bankruptcies and consolidation; online sales growth continues to pressure traditional business models.
The dominance of digital platform companies—Apple, Alphabet, Amazon, Microsoft—whose scale and data advantages allow rapid expansion into multiple sectors.
Business model disruption in industries like financial services, travel, telecom, and real estate, where asset-light models (e.g., Uber, Airbnb) reshape value creation.
Energy sector transformation, with renewable energy investment overtaking fossil fuels, creating new winners and forcing incumbents toward reinvention.
The explosion of unicorns and “decacorns”, privately held startups valued above $10B, signaling intensified future competition for incumbents across industries.
Survey findings from over 300 executives show that while 80% acknowledge the need to transform, many still underestimate threats from new entrants and overestimate their readiness—what the report calls a “confidence bubble.”
To help companies navigate this rising turbulence, the report outlines five strategic imperatives:
Spend time at the periphery to detect early signals of disruption.
Focus on changing customer behaviors as leading indicators of future shifts.
Avoid being trapped by past assumptions; use future-back thinking to shape strategy.
Embrace dual transformation, strengthening the core business while building new growth engines.
Assess the cost of inaction, recognizing that failing to innovate can be more costly than investing in change.
Overall, the briefing serves as a warning and a playbook: corporate longevity is shrinking, disruption is accelerating, and leaders must act boldly to reinvent their organizations—or risk being overtaken by faster, more innovative rivals.
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Clinical Journal of Sport
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Clinical Journal of Sport Medicine
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you nee to answer with
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ident you nee to answer with
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11 Clinical Journal of Sport Me…
📘 Universal App-Ready Description
This article reviews the current state of exercise genomics, a scientific field that studies how genetic differences interact with exercise and the environment to influence physical fitness, training adaptation, athletic performance, injury risk, and health outcomes.
The paper explains that responses to exercise and athletic performance are complex and polygenic, meaning they are influenced by many genes, each with small effects, rather than a single gene. Classic research such as the HERITAGE Family Study helped establish that exercise responses like VO₂max improvement are partly heritable, but not fully predictable by genetics alone.
Early research focused on candidate genes such as ACE and ACTN3, which are associated with endurance and power traits. However, the article explains that this approach was limited. Modern research now uses large-scale genomic technologies such as:
genome-wide association studies (GWAS)
biobanks (e.g., UK Biobank)
international research consortia (e.g., Athlome Project)
These studies show that exercise traits are influenced by thousands of genetic variants with very small effects, making prediction difficult.
The article emphasizes the importance of moving beyond the genome alone and integrating multiple biological layers, known as “omics”, including:
epigenomics (gene regulation)
transcriptomics (gene expression)
proteomics (proteins)
metabolomics (metabolic processes)
This multi-omics approach provides a more complete understanding of how the body adapts to exercise.
The authors stress major scientific challenges, including:
small sample sizes
lack of replication
false positive findings
weak causal evidence
They strongly warn against direct-to-consumer genetic testing that claims to predict athletic talent or prescribe training programs without strong scientific evidence.
The article also discusses ethical and practical concerns, such as data privacy, misuse of genetic information, and the risk of gene doping. It highlights the need for ethical guidelines, secure data management (including technologies like blockchain), and international collaboration.
The conclusion emphasizes that genetics should not be used for talent identification, but rather to:
improve athlete health
reduce injury risk
enhance recovery
support public health through personalized exercise approaches
📌 Main Topics (Easy for Apps to Extract)
Exercise genomics
Genetics and exercise adaptation
Polygenic traits in sport
Candidate genes vs GWAS
Multi-omics integration
Gene–environment interaction
Injury risk and genetics
Ethical issues in sports genomics
Direct-to-consumer genetic testing
Gene doping detection
🔑 Key Points (Notes / Slides Friendly)
Exercise response is partly genetic but highly complex
No single gene predicts performance
Large datasets and collaboration are essential
Multi-omics gives deeper biological insight
Many past findings lack replication
Consumer genetic tests are scientifically weak
Ethics and data protection are critical
🧠 Easy Explanation (Beginner Level)
People respond differently to exercise partly because of genetics, but performance depends on many genes plus training, diet, and lifestyle. Modern science now studies genes together with how they are regulated and expressed. Genetics should help improve health and recovery—not decide who becomes an athlete.
🎯 One-Line Summary (Perfect for Quizzes & Slides)
Exercise genomics studies how genes and environment work together to influence fitness and performance, but its main value lies in improving health and safety—not predicting athletic talent.
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Celebrating
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Celebrating Ramadan
A Resource for Educators
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⭐“Celebrating Ramadan”
“Celebrating Ramadan” is ⭐“Celebrating Ramadan”
“Celebrating Ramadan” is a full educational curriculum created by the Outreach Center at Harvard University’s Center for Middle Eastern Studies. It is designed to help teachers explain the meaning, traditions, history, and cultural practices of Ramadan to K–12 students in a simple, engaging, and interactive way.
The resource blends religious background, cultural diversity, hands-on activities, science lessons, and literature, showing how Ramadan is observed around the world.
⭐ What the Curriculum Teaches
1. Introduction to Ramadan
The resource explains that Ramadan is a holy month for Muslims and highlights three core practices:
Sawm — fasting during daylight hours
Iftar — breaking the fast after sunset
Eid al-Fitr — the joyful three-day festival ending Ramadan
It emphasizes that Ramadan teaches self-discipline, reflection, generosity, and community spirit. It also notes that not all Muslims fast (children, travelers, pregnant women, the sick, etc.).
⭐ 2. When Ramadan Happens
The curriculum explains the difference between the solar and lunar calendars:
The Islamic (Hijri) calendar follows the moon.
Months begin when the new crescent moon appears.
Because the lunar year is 11 days shorter, Ramadan moves earlier each year.
Students learn how moon phases determine Islamic dates.
⭐ 3. Key Ramadan Traditions
Sawm (Fasting)
Fasting means:
no eating or drinking during daylight
reflection and spiritual focus
modified daily routines
Fasting is personal, voluntary, and varies across cultures.
Iftar (Breaking the Fast)
Each evening, families and friends gather for a meal. Iftar can be:
simple, nourishing foods
large festive celebrations
accompanied by Qur’an recitation or prayer
Eid al-Fitr
>Eid is celebrated with:
>days off from school/work
>gift giving
>new clothes
>visits to family and friends
special meals
>decorations, lanterns, henna, children’s parades, and songs
The curriculum gives examples of Eid traditions in Egypt, India, Pakistan, and the United States.
⭐ 4. Lesson Plans & Activities Included
The document contains multiple classroom activities:
🌙 Moon Phase Science Lessons
Students learn:
how moon phases work?
why Ramadan moves each year?
how to track moon changes?
how to create a moving “moonscape” to show waxing and waning
🕌 Cultural Studies & Research
Students research:
how different countries celebrate Ramadan
>special foods eaten during the month
>similarities and differences across global Muslim communities
🥣 Food & Recipes
The resource includes recipes that represent Ramadan food traditions from around the world, such as:
>Stuffed dates
>Cucumber yogurt dip
Thiacri Senegalais
Indian starch pudding (Fereni)
👦 “First Fast” Reading Lesson
A story from Iran shows how children practice a “little fast.”
Students learn how young Muslims experience Ramadan and complete a worksheet about the reading.
🕯 Ramadan Lantern Craft (Fanoos)
Students make:
>simple paper lanterns
>more advanced geometric lanterns
>tin-punched lanterns
>They also learn the history of Ramadan lanterns in Egypt.
⭐ 5. Additional Resources
The curriculum includes:
>Recommended books about Ramadan
>Documentaries and educational videos
>Music and online resources
>Bibliographies for teachers
These help deepen understanding of Muslim culture and holiday practices.
⭐ Overall Meaning of the Resource
“Celebrating Ramadan” is both an instructional guide and a cultural exploration.
It teaches that Ramadan is:
>A spiritual month
>A cultural celebration
>A family-centered tradition
A global event with diverse forms
It helps students compare Ramadan with celebrations from their own traditions, promoting respect, cultural awareness, and global understanding....
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Analysis of trends
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Analysis of trends in human longevity by new model
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Byung Mook Weon
LG.Philips Displays, 184, Gongda Byung Mook Weon
LG.Philips Displays, 184, Gongdan1-dong, Gumi-city, GyungBuk, 730-702, South Korea
Abstract
Trends in human longevity are puzzling, especially when considering the limits of
human longevity. Partially, the conflicting assertions are based upon demographic
evidence and the interpretation of survival and mortality curves using the Gompertz
model and the Weibull model; these models are sometimes considered to be incomplete
in describing the entire curves. In this paper a new model is proposed to take the place
of the traditional models. We directly analysed the rectangularity (the parts of the curves
being shaped like a rectangle) of survival curves for 17 countries and for 1876-2001 in
Switzerland (it being one of the longest-lived countries) with a new model. This model
is derived from the Weibull survival function and is simply described by two parameters,
in which the shape parameter indicates ‘rectangularity’ and characteristic life indicates
the duration for survival to be ‘exp(-1) % 79.3 6≈ ’. The shape parameter is essentially a
function of age and it distinguishes humans from technical devices. We find that
although characteristic life has increased up to the present time, the slope of the shape
parameter for middle age has been saturated in recent decades and that the
rectangularity above characteristic life has been suppressed, suggesting there are
ultimate limits to human longevity. The new model and subsequent findings will
contribute greatly to the interpretation and comprehension of our knowledge on the
human ageing processes.
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American Longevity:
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American Longevity: Past, Present, and Future
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Samuel Preston is Frederick J. Warren Professor of Samuel Preston is Frederick J. Warren Professor of Demography at the University of Pennsylvania and Director of its Population Studies Center. A 1968 Ph.D. in Economics from Princeton University, he has also been a faculty member at the University of California, Berkeley, and the Universi ty of Washington. He is past president of the Population Association of America and is a member of the National Academy of Sciences, where he chaired the Committee on Population.
The Policy Brief series is a collection of essays on current public policy issues in aging, health, income security, metropolitan studies and related research done by or on behalf of the Center for Policy Research at the Maxwell School of Citizenship and Public Affairs.
Single copies of this publication may be obtained at no cost from the Center for Policy Research, Maxwell School, 426 Eggers Hall, Syracuse, NY 13244-1090.
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Aging and aging-related
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Aging and aging-related disease
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Aging is a gradual and irreversible pathophysiolog Aging is a gradual and irreversible pathophysiological process. It presents with declines in tissue and cell functions and significant increases in the risks of various aging-related diseases, including neurodegenerative diseases, cardiovascular diseases, metabolic diseases, musculoskeletal diseases, and immune system diseases. Although the development of modern medicine has promoted human health and greatly extended life expectancy, with the aging of society, a variety of chronic diseases have gradually become the most important causes of disability and death in elderly individuals. Current research on aging focuses on elucidating how various endogenous and exogenous stresses (such as genomic instability, telomere dysfunction, epigenetic alterations, loss of proteostasis, compromise of autophagy, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, deregulated nutrient sensing) participate in the regulation of aging. Furthermore, thorough research on the pathogenesis of aging to identify interventions that promote health and longevity (such as caloric restriction, microbiota transplantation, and nutritional intervention) and clinical treatment methods for aging-related diseases (depletion of senescent cells, stem cell therapy, antioxidative and anti-inflammatory treatments, and hormone replacement therapy) could decrease the incidence and development of aging-related diseases and in turn promote healthy aging and longevity...
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Aging and Longevity
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Aging and Longevity data
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⭐ Aging and Longevity Studies
This document i ⭐ Aging and Longevity Studies
This document is an academic program guide from the University of Iowa outlining the full curriculum for the Aging and Longevity Studies program. It describes the structure, purpose, and range of courses available for students interested in gerontology—the scientific, social, psychological, and biological study of ageing.
The program is coordinated through the School of Social Work and offers both:
an Undergraduate Minor in Aging and Longevity Studies
a Graduate Certificate in Aging and Longevity Studies
The goal of the program is to prepare students for careers and research in fields that serve older adults and address issues of ageing, health, policy, caregiving, and end-of-life support.
⭐ What the Document Contains
The file mainly lists and describes all the courses offered in the Aging and Longevity Studies program. These courses span multiple disciplines—biology, psychology, social work, anthropology, nursing, recreation, politics, global health, and medicine—reflecting how ageing impacts every part of society.
Below is an overview of the main areas covered:
⭐ 1. Foundational Courses
These courses introduce the scientific, psychological, and social dimensions of ageing:
Aging Matters: Introduction to Gerontology — broad overview of biological, cognitive, and social ageing.
Aging-longevity-studies_courses…
First-Year Seminar — introductory discussions on ageing topics.
⭐ 2. Creativity, Anthropology, and Cultural Perspectives
Courses explore ageing from artistic and cultural angles:
Creativity for a Lifetime — understanding creativity in older adulthood.
Anthropology of Aging — cross-cultural study of ageing, kinship, health, and religion.
Anthropology of Caregiving and Health — how caregiving works across cultures.
⭐ 3. Health, Physiology, and Biological Ageing
These courses focus on the biological and medical aspects of ageing:
Health and Aging — biological development across the lifespan.
Physiology of Aging — effects of ageing on cells, tissues, and organ systems.
Physical Activity and Recreation for Aging Populations — designing exercise programs for older adults.
⭐ 4. Psychology of Aging
A deep look at mental and cognitive changes later in life:
cognitive function
emotional wellbeing
social relationships
age-related psychological adaptations
⭐ 5. Policy, Politics, and Social Systems of Aging
Courses study how ageing interacts with public policy and government systems:
Politics of Aging — demographic change, federal and state policies, political participation of older adults.
Medicare and Medicaid Policy — health systems that support Americans aged 65+.
⭐ 6. End-of-Life and Ethical Care
A group of courses focused on late-life decisions, ethics, and family support:
Hard Cases in Healthcare at the End of Life
End-of-Life Care for Adults and Families
Death/Dying: Issues Across the Life Span
These classes prepare students for ethical, compassionate work with older adults and families facing death and declining health.
⭐ 7. Global and Cross-National Aging
These courses explore how population ageing affects the world:
Global Aging ,WHO and United Nations frameworks, demographic trends across countries.
Aging-longevity-studies_courses…
⭐ 8. Professional Development & Internship
The program includes hands-on experience and advanced seminars:
Aging Studies Internship and Seminar practical work with older adults.
Graduate Gerontology Capstone research, ethics, professional preparation in ageing careers.
⭐ Overall Meaning of the Document
The document serves as a comprehensive guide to all coursework in the Aging and Longevity Studies program. It shows that ageing is a rich, interdisciplinary field involving:
>biology
>health sciences
>psychology
>anthropology
>social work
>public policy
>global perspectives
Students in this program gain a holistic understanding of how ageing affects individuals, families, healthcare systems, and society as a whole....
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AI assistant with a single unchangeable identity, AI assistant with a single unchangeable identity, representing the vision, values, and purpose of Dr. Anmol Kapoor....
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Trained incrementally on curated instruction–respo Trained incrementally on curated instruction–response pairs with embedded chain-of-thought data, it maintains logical coherence, contextual awareness, and factual accuracy....
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AGEING IN ASIA
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AGEING IN ASIA AND THE PACIFIC
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as a whole. This highlights the need for countries as a whole. This highlights the need for countries with relatively low proportion of older persons to also put in place appropriate policies and interventions to address their specific rights and needs, and to prepare for ageing societies in the future.
An increase in the proportion and number of the oldest old (persons over the age of 80 years)
The oldest old person, the number of people aged 80 years or over, in the region is also showing a dramatic upward trend. The proportion of the oldest old in the region in the total population 2016 was 1.5 per cent of the population amounting to 68 million people, which is 53 per cent of the global population over 80 years old. This proportion is expected to rise to 5 per cent of the population totaling 258 million people by 2050. Asia
Pacific would have 59 per cent of the world population over 80 years of age compared to 53 per cent at present. This has serious implications for provision of appropriate health care and long term care, as well as income security.
The causes…
The drastic increase in the pace of ageing in the region can be attributed to two key factors, declining fertility rates and increasing life expectancies.
Rapidly declining fertility: The most precipitous declines in the region’s fertility have been in the South and SouthWest, and South-East Asia subregions, with the fertility rates falling by 50 per cent in a span of 40 years. ...
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aging research
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AFAR American aging research
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Researchers believe that your longevity, that is, Researchers believe that your longevity, that is, the duration of your life, may rely on your having longevity assurance genes. Genes are the bits of DNA that determine an organism’s physical characteristics and drive a whole range of physiological processes. Longevity assurance genes are variations (called alleles) of certain genes that may allow you to live longer (and perhaps more healthily) than other people who inherit other versions of that gene.
WHY ARE LONGEVITY ASSURANCE GENES IMPORTANT?
If scientists could identify longevity genes in humans, in theory, they might also be able to develop ways to manipulate those genes to enable people to live much longer than they do today. Slowing the
aging process would also likely delay the appearance of agerelated diseases such as cancer, diabetes, and Alzheimer’s disease and therefore make people
healthier as well.
Most longevity assurance genes that have already been identified in lower organisms such as yeast, worms, and fruit flies act to increase lifespan and grant resistance to harmful environmental stress. For example, scientists have identified single gene variantions in roundworms that can extend lifespans by 40 to 100 percent. These genes also allow worms to withstand often fatal temperature extremes, excessive levels of toxic free radicals (cellular waste products), or damage due to ultraviolet light.
Some of the longevity assurance genes in lower organisms have similar counterparts among human or mammalian genes, which scientists are now studying. While researchers have not yet found genes that predispose us to greater longevity, some have identified single human gene variants that seem to have a protective effect against certain age-related diseases and are associated with long life. For example, inheriting one version of a gene for a particular protein called apolipoprotein E (Apo E) may decrease a
person’s risk of developing heart
disease and Alzheimer’s disease.
Identification of genes that prevent or delay crippling diseases at old age may help us find novel strategies for assuring a healthier, longer life, and enhancing the quality of life in the elderly.
Researchers believe that your longevity may rely on your having longevity assurance genes.
Infoaging Guide to Longevity | 3
HOW MUCH OF LONGEVITY IS GENETICALLY DETERMINED?
By some estimates, we humans have about 25,000 genes. But only a small fraction of those affect the length of our lives. It is hard to imagine that so few genes can be responsible for such a complex phenomenon as longevity. In looking at personality, psychologists ask how much is nature, that is, inherited, and how much is nurture, which means resulting from external influences. Similar questions exist about the heritability of lifespan. In other words, just how much of longevity is
genetically determined and how much it is mediated by external influences, such as smoking, diet, lifestyle, stress, and occupational exposures?
Studies do show that long-lived parents have long-lived children. Studies of adoptees confirm that their expected lifespans correlate more strongly to those of their birth parents than those of their adoptive parents. One study of twins reared apart suggests about a 30 percent role for heredity in lifespan, while another says the influence is even smaller.
Some scientists estimate the maximal lifespan of a human to be approximately 120 years, a full 50 years longer than the Biblical three score and ten (Psalms 90:10). The people who have actually achieved that maximum can be counted on one hand—or one finger. Mme. Jeanne Calment of France was 122 years old at her death in 1997. But although few challengers to her record exist, we are seeing more and more members of our society reach 100. In fact, in the United States today, there are more than 60,000 centenarians, and their ranks are projected to grow to nearly 1 million
by 2050. Much of this growth will be due to the convergence of the large aging Boomer demographic and improvements in health and medicine.
Most people who get to 100 do so by avoidance. They shun tobacco and excess alcohol, the sun and pollutants, sloth, bad diets, anger, and isolation. Still, many of us may know at least one smoking, drinking, sunburnt, lazy,
cantankerous recluse who has lived to 100—and wondered how he or she did it.
More and more, scientists are finding that part of the explanation lies in our genes. The siblings of centenarians have a four times greater probability of surviving to age 90 than do siblings of people who have an average life expectancy. When it comes to living 100 years, the probability is 17 times greater in male siblings of centenarians and eight times greater in female siblings of centenarians than the average lifespan of their birth cohort.
On the flip side, we humans carry a number of genes that are deleterious to our health and longevity. These genes increase our risk for heart disease and cancer, as well as age-related but harmless symptoms such as gray hair and wrinkles. Though we cannot change our genetic pedigrees, perhaps if we know what unhelpful genes we carry, we can take steps, such as ridding ourselves of bad health habits and adopting good ones, that can overcome the disadvantages our genes confer and live as long as those people with good genes.
WHAT WE HAVE LEARNED FROM LOWER ORGANISMS
Our understanding of genes and aging has exploded in recent years, due in large part to groundbreaking work done in simpler
organisms. By studying the effect of genetic modification on lifespan in laboratory organisms, researchers now provide fundamental insights into basic mechanisms of aging.
These include:
• Yeast
• Worms
• Fruit Flies
• Mice
Yeast Researchers have identified more than 100 genes in baker’s yeast (Saccharomyces cerevisiae) that are associated with increased longevity, and even more provocatively, have found human versions of many of these genes. Further study is ongoing.
As with all other organisms tested, researchers have reported that restricting the amount of calories available to yeast, either through reducing the sugar or amino acid content of the culture medium, can increase lifespan. Caloric
restriction does not extend lifespan in yeast strains lacking one of the longevity assurance genes, SIR2. This result has been shown in multiple organisms from yeast to flies, and even in mice. The SIR2 protein is the founding member of the sirtuin family involved in
genomic stability, metabolism, stress resistance, and aging. Researchers have found that
overexpression of Sir2 extends lifespan, ...
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A mathematical model
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A mathematical model to estimate the seasonal
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Yasuhiro Yamada1,3, Toshiro Yamada 2,4 & Kazu Yasuhiro Yamada1,3, Toshiro Yamada 2,4 & Kazuko Yamada2,4
The longevity of a honeybee colony is far more significant than the lifespan of an individual honeybee, a social insect. the longevity of a honeybee colony is integral to the fate of the colony. We have proposed a new mathematical model to estimate the apparent longevity defined in the upper limit of an integral equation. the apparent longevity can be determined only from the numbers of adult bees and capped brood. By applying the mathematical model to a honeybee colony in Japan, seasonal changes in apparent longevity were estimated in three long-term field experiments. Three apparent longevities showed very similar season-changes to one another, increasing from early autumn, reaching a maximum at the end of overwintering and falling approximately plumb down after overwintering. The influence of measurement errors in the numbers of adult bees and capped brood on the apparent longevity was investigated.
A lifespan of an animal, which is the period of time while an individual is alive, is an important index to evaluate individual activities. In the colony composed of eusocial insects such as honeybees (Apis mellifera) which exhibit age-polyethism, the lifespan of each individual cannot always give an assessment as to the activities of a colony but the longevity of colony could give it more appropriately. The longevity of a colony will have greater significance than the lifespan of each individual of the colony. The life of colony diversely depends on the inborn lifespan of an individual, the labor division distribution ratio of each honeybee performing a particular duty, the natural environment such as the weather, the amount of food, pests and pathogens, the environmental pollution due to pesticides and so on. The honeybee length of life has been observed or estimated before in the four seasons, which have a distinct bimodal distribution in temperature zones. According to previous papers, honeybees live for 2–4 weeks1 and 30–40 days2 in spring, for 1–2 weeks1, 25–30 days2 and 15–38 days3 in summer, for 2–4 weeks1 and 50–60 days2 in autumn, and for 150–200 days3, 253 days2, 270 days4, 304 days5 6–8 months6 and 150–200 days3 in winter, where it has been estimated that the difference of life length among seasons may come from the brood-rearing load imposed on honeybees1 and may mainly come from foraging and brood-rearing activity2. Incidentally, the lifetime of the queen seems to be three to four years (maximum observed nine years). The average length of life of worker bees in laboratory cages was observed to range from 30.5 to 45.5 days7. The study on the influence of altitude on the lifespan of the honeybee has found that the lifespans are 138 days at an altitude of 970 m and 73 days at an altitude of 200 m, respectively8. Many papers have discussed what factors affect the length of life (lifespan, longevity, life expectancy) on a honeybee colony as follows: Proper nutrition may increase the length of life in a honeybee colony. Honeybees taking beebread or diets with date palm pollen (the best source for hypopharyngeal gland development) showed the longest fifty percent lethal time (LT50)9. The examination for the effect of various fat proteins on honeybee longevity have shown that honeybees fed diets of red gum pollen have the longest lifespan but those fed invert sugar have the shortest lifespan10. In the discussion on nutrition-related risks to honey bee colonies such as starvation, monoculture, genetically modified crops and pesticides in pollen and sugar, protein nutrient strongly affects brood production and larval starvation (alone and or in combination with other stresses) can weaken colonies11. And protein content in
1Department of Applied Physics, Graduate School of Engineering, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-8656, Japan. 2Graduate School of Natural Science & Technology, Kanazawa University, Kakuma-machi, Kanazawa, 920-1192, Japan. 3Present address: Department of Physics, Osaka University, 1-1 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan. 4Present address: 2-10-15, Teraji, Kanazawa, Ishikawa, 921-8178, Japan. correspondence and requests for materials should be addressed to t.Y. (email: yamatoshikazu0501@yahoo.co.jp)
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A New Map of Life
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A New Map of Life
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Longevity is not a synonym of old age. The increas Longevity is not a synonym of old age. The increase in life expectancy shapes lives from childhood to old age across different domains. Among those, the nature of work will undergo profound changes from skill development and the role of retirement to the intrinsic meaning of work. To put the striking potential of a 100 year life into a historical prospective it is useful to start from how technological and demographic development shaped the organization and the definition of work in the past. This longer view can more thoughtfully explore how different the nature of work has been, from working hours to the parallelism between work, employment and task-assignment.
Throughout history the role of work has been intertwined with social and technological change. Societies developed from hunter-gather to sedentary farmers, and they transitioned from the agricultural to the industrial revolution. The latter transformed a millennial long practice of self-employed farmers and artisans, working mostly for self-subsistence, without official working hours, relying on daylight and seasonality at an unchosen job from childhood until death, into employees working 10-16 hours per day for 311 days a year, mostlyindoorsfromyouthtoretirement. Thisdrastictransformationignitedfastshiftsofworkorganization not only in the pursue of higher productivity and technological advancement, but also of social wellbeing.
Among the first changes was the abandonment of unsustainable working conditions, such as day working hours, which sharply converged toward the eight hours day tendency between the 1910s and the 1940s, see Figure 1 (Huberman and Minns 2007; Feenstra, Inklaar, and Timmer 2015; Charlie Giattino and Roser 2013). Although beneficial for the workers, this reduction worried intellectuals, such as the economist John Maynard Keynes, who wrote: “How will we all keep busy when we only have to work 15 hours a week?” (Keynes 1930). Keynes predicted people’s work to become barely necessary given the level of productivity the economy would reach over the next century: “permanent problem would be how to occupy the leisure,
1
whichscienceandcompoundinterestwillhavewonforhim. [...] Afearfulproblemfortheordinaryperson” (p. 328). For a while, Keynes seemed right since the average workweek dropped from 47 hours in 1930 to slightly less than 39 by 1970. However, after declining for more than a century, the average U.S. work week has been stagnant for four decades, at approximately eight hours per day.1
Figure 1: Average working hours per worker over a full year. Before 1950 the data corresponds only to full-time production workers(non-agricultural activities). Starting 1950 estimates cover total hours worked in the economy as measured from primarily National Accounts data. Source: Charlie Giattino and Roser (2013). Data Sources: Huberman and Minns (2007) and Feenstra, Inklaar, and Timmer (2015).
Technological change did not make work obsolete, but changed the tasks and the proportion of labor force involved in a particular job. In the last seventy years, for example, the number of people employed in the agricultural sector dropped by one third (from almost 6 million to 2 million), while the productivity tripled. Feeding or delivering calves is still part of ranchers’ days, but activities like racking and analyzing genetic traits of livestock and estimating crop yields are a big part of managing and sustaining the ranch operations. In addition, the business and administration activity like bookkeeping, logistics, market pricing, employee supervision became part of the job due to the increase in average farm size from 200 to 450 acres. Another exampleistheeffectoftheautomatedtellermachine(ATM)onbanktellers, whosenumbergrewfromabout a quarter of a million to a half a million in the 45 years since the introduction of ATMs, see Figure 2 (Bessen 2016). ATM allowed banks to operate branch offices at lower cost, which prompted them to open many 1Despite the settling, differences in the number of hours worked between the low and the high skilled widened in the last fifty years. Men without a high school degree experienced an average reduction of eight working hours a week, while college graduates faced an increase of six hours a week. Similarly, female graduates work 11 hours a week more than those who did not complete high school (Dolton 2017). Overall, American full-time employees work on average 41.5 hours per week, and about 11.1% of employees work over 50 hours per week, which is much higher than countries with a comparable level of productivity like Switzerland, where 0.4% of employees work over 50 hours per week (Feenstra, Inklaar, and Timmer 2015) and part time work is commonplace...
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A Longevity Agenda
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A Longevity Agenda for Singapore
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Over the last 60 years, life expectancy in Singapo Over the last 60 years, life expectancy in Singapore has increased by nearly 20 years to reach 85 – one of the highest in the world. That’s an extraordinary achievement that is taken for granted and that too often leads to a conversation about the costs of an ageing society. Those costs and concerns are very real, but a deeper more fundamental set of questions need to be answered.
If we are living this much longer, then how do we – individuals, companies and governments – respond to make the most of this extra time? How do we restructure our lives to make sure that as many people as possible, live as long as possible, in as healthy and fulfilled ways as possible?
This note draws on the findings from a high-level conference, sponsored by Rockefeller Foundation and Prudential Singapore, to map out what a global longevity agenda looks like, and to raise awareness around the world – at a government, corporate and individual level – on how we need to seize the benefits of this wonderful human achievement of longer lives.
It also looks at the measures that Singapore has taken to adjust to longer lives. Reassuringly, Singapore leads the world along many dimensions that have to do with ageing, and also longevity. However, there is much that needs to be done. Framing policies around longevity and ‘all of life’ and not just ageing and ‘end of life’ is needed if Singapore is to collectively maximise the gains available.
A Longevity Agenda For Singapore I 2
Executive Summary
• Singapore is undergoing a rapid demographic transition which will see the average age of its society
increase as the proportion of its older citizens increases.
• An ageing society creates many challenges. However, at the same time, with the number of older
people increasing, Singapore is benefitting from a longevity dividend.
• On average, Singaporeans are living for longer and in better health. In other words, how we are
ageing is changing – it is not just about there being more senior people. Exploiting this opportunity
to seize these positive advantages is the longevity agenda.
• A new-born in Singapore today, faces the prospect of living on average one of the longest lives in
human history, and so needs to prepare for his or her future differently.
• At an individual level, Singaporeans are already behaving differently – in terms of marriage, families,
work and education. Many are acting as social pioneers as they try to create a new map of life.
• To support individuals as they adapt to longer lives, Singapore needs to create a new map of life
that enables as many people as possible to live as long as possible and as healthily and as fulfilled as
possible.
• Achieving this will also ensure that not only the individual, but also the economy will benefit.
• Singapore is at the international frontier of best practice in terms of adjusting to an ageing society. It
also leads the way with many longevity measures.
• Further entrenching social change and experimentation, and creating a positive narrative around
longer, healthier lives; in particular, extending policies away from a sole focus on the old and towards the whole course of life are some key priorities ahead of us. ...
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our Epidemic of Loneline
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our Epidemic of Loneliness and Isolation
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“Our Epidemic of Loneliness and Isolation: The U.S “Our Epidemic of Loneliness and Isolation: The U.S. Surgeon General’s Advisory on the Healing Effects of Social Connection and Community” (2023)
Author: Dr. Vivek H. Murthy, U.S. Surgeon General
surgeon-general-social-connecti…
This document is an official U.S. Surgeon General’s Advisory that warns the nation about a growing public health crisis—the epidemic of loneliness, isolation, and declining social connection. It explains that nearly half of Americans regularly feel lonely, and social connection has sharply decreased over the last several decades due to changes in family structure, technology use, community involvement, and societal norms.
The advisory shows that social disconnection is as harmful as smoking 15 cigarettes a day and dramatically increases the risk of heart disease, stroke, dementia, diabetes, depression, anxiety, self-harm, and premature death. It presents decades of scientific evidence demonstrating that strong social relationships, supportive communities, and positive social environments improve physical health, mental well-being, cognitive function, educational outcomes, workplace success, and overall quality of life.
The report explains why humans are biologically wired for connection and describes how loneliness negatively impacts the brain, stress hormones, inflammation, immunity, and behavior. It also highlights how social connection supports meaning, resilience, purpose, and healthier lifestyle choices.
On a community level, the advisory shows that connected communities are safer, more resilient, more prosperous, and more civically engaged. It warns that declining trust, weaker community bonds, and rising polarization undermine national health and social stability.
To address the crisis, the advisory proposes a National Strategy with Six Pillars, calling on governments, schools, workplaces, technology companies, healthcare systems, media, and individuals to strengthen social infrastructure, reform digital environments, promote pro-connection policies, and rebuild a culture of empathy, belonging, and community.
Overall, the document is a comprehensive, research-based call to action emphasizing that social connection is a fundamental human need essential for individual and societal health, and rebuilding it is critical for America’s future...
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longevity and public
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longevity, working lives
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This paper (ETLA Working Papers No. 24, 2014) anal This paper (ETLA Working Papers No. 24, 2014) analyses how increasing longevity affects public finances in Finland, focusing on the interaction between longer lifetimes, working careers, and health- and long-term-care expenditure. Written by Jukka Lassila and Tarmo Valkonen, it combines a review of economic research with simulations using a numerical overlapping-generations (OLG) model calibrated to Finnish demographics and economic structures.
The authors examine three key channels:
Longevity & demographics – Longer life expectancy increases the share of the elderly population and particularly the number of people aged 80+, intensifying long-term care demand. Stochastic mortality projections demonstrate wide uncertainty in future longevity trends.
Longevity & working lives – Evidence suggests that healthier, longer lives could support longer work careers, but this will not occur automatically. Without policy reforms, working lives extend only modestly. Linking retirement age to life expectancy, tightening disability pathways, and reforming pension eligibility can significantly lengthen careers.
Longevity & health/care expenditure – The paper highlights that a substantial portion of healthcare and long-term care costs occur near death rather than being linearly age-related. This reduces the inevitability of cost increases from ageing alone: proximity-to-death modelling shows lower expenditure pressure compared with naïve, age-only models.
Using 500 stochastic population scenarios, the authors simulate long-term fiscal sustainability under varying assumptions about longevity, retirement behaviour, and healthcare cost dynamics. Key findings include:
If working lives do not lengthen, rising longevity substantially worsens public finances.
Under current rules, improvements in health and moderate policy support produce some automatic correction.
Linking retirement age to life expectancy largely neutralizes the fiscal impact of longer lifetimes.
Modelling care costs with proximity-to-death dramatically improves fiscal forecasts compared to simple age-related projections.
Conclusion
Longer lifetimes need not undermine fiscal sustainability—if policies ensure that healthier, longer lives translate into longer working careers and if health-care systems account for the true drivers of costs. With appropriate reforms, generations that live longer can also finance the additional costs generated by their longevity....
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What Happen all live 100
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What Happens When We All Live to 100?
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What Happens When We All Live to 100?” by Gregg Ea What Happens When We All Live to 100?” by Gregg Easterbrook is an in-depth exploration of how rising life expectancy will transform science, society, economics, politics, and everyday life. The article explains that life expectancy has increased steadily for almost 200 years—about three months every year—and may reach 100 years by the end of this century. This dramatic shift will reshape everything from health care to retirement, family structures, and government systems.
Easterbrook discusses cutting-edge longevity research at places like the Buck Institute, Mayo Clinic, and universities studying how to slow aging, extend “healthspan,” and possibly reverse age-related decline. Scientists have lengthened the lives of worms and mice, identified longevity genes (such as daf-16/foxo3), tested drugs like rapamycin, and explored theories involving caloric restriction, cellular senescence, stem-cell rejuvenation, and youth-blood factors. Much of this research aims not just to add years but to preserve quality of life, preventing diseases like heart disease, cancer, Alzheimer’s, and stroke.
The article also presents two major schools of thought:
(1) Life expectancy will keep rising smoothly (“the escalator”), or
(2) It will hit a biological and social limit.
Experts debate whether future gains will slow down or accelerate due to new anti-aging breakthroughs.
Beyond biology, the article examines massive societal consequences of a population where large numbers routinely live past 90 or 100. These include:
increased strain on Social Security, pensions, and Medicare
a growing gap between educated and less-educated groups in longevity
more years of old-age disability unless healthspan improves
caregiver shortages
political dominance by older voters
possible rise in national debt
multigenerational families depending heavily on one young adult
Japan as an example of an aging society with stagnation and high public debt
The article warns that without healthier aging, longer life could create financial crisis and social imbalance. However, if science successfully extends healthy, active years, society may benefit from:
older adults working longer
less crime and less warfare (younger people start more conflicts)
more intergenerational knowledge
calmer, wiser political culture
reduced materialism
stronger emotional well-being among the elderly
The author concludes that a world where most people live to 100 will be fundamentally different: older, quieter, more stable, and possibly more peaceful. But it also requires urgent changes in healthcare, retirement systems, and public policy. Ultimately, the article argues that humanity is entering an age where delaying aging—and reshaping society around longer lives—is becoming not just possible, but necessary....
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Variation in fitness of
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This study examines how the fitness of the longhor This study examines how the fitness of the longhorned beetle Dectes texanus—a major pest of soybean crops—varies across different soybean populations and environments. The research provides a detailed analysis of how factors such as geographic origin, host plant quality, and genetic variation influence beetle survival, development, reproduction, and body size.
Purpose of the Study
The goal is to understand why D. texanus shows substantial differences in life-history traits when feeding on different soybean varieties and when collected from different regions. The authors aim to identify:
how host plant quality affects beetle development,
whether beetle populations show local adaptation to their regional soybean hosts, and
how these differences influence pest severity in agricultural systems.
Key Findings
1. Fitness varies significantly across soybean hosts
Larvae reared on different soybean cultivars showed major differences in:
growth rate
survival to adulthood
adult body mass
developmental time
Some soybean varieties supported rapid growth and high survival, while others produced slower development and lower fitness.
2. Geographic origin matters
Beetles collected from different regions (e.g., Kansas, Texas, Oklahoma, Nebraska) showed distinct performance patterns, suggesting:
genetically based population differences, and
possible local adaptation to regional soybean types.
These geographic differences shaped how well beetles performed on specific soybean hosts.
3. Developmental timing is a key determinant of fitness
Developmental duration strongly influenced adult body size and reproductive potential:
Faster development produced smaller adults with potentially reduced fecundity.
Longer development produced larger adults with greater reproductive output.
Thus, speed–size trade-offs were central to fitness variation.
4. Body size correlates with reproductive capacity
Larger adults produced by favorable host plants—tend to have:
higher egg production in females
stronger survival rates
greater overall fitness
This links host-driven growth differences directly to pest severity in the field.
5. Host plant defenses influence beetle performance
The study highlights how soybean plants with stronger structural or chemical defenses reduce larval growth, suppress survival, and lead to smaller, less successful adults.
This suggests that breeding soybean varieties with anti-beetle traits can meaningfully reduce pest damage.
Scientific Importance
This research shows that Dectes texanus fitness is shaped by the interaction between:
plant genetics,
insect genetics, and
environmental conditions.
It provides valuable insight for agricultural pest management, emphasizing that controlling this beetle requires understanding not just soybean traits but also beetle population biology and regional adaptation.
Conclusion
“Variation in Fitness of the Longhorned Beetle, Dectes texanus, in Soybean” demonstrates that the beetle’s success as a pest is not uniform. Instead, it varies widely depending on soybean variety, beetle population origin, and local environmental conditions. These findings help inform more targeted and effective strategies for soybean crop protection....
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Unlocking the Secrets of
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Unlocking the Secrets of Longevity Recent Finding
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“Unlocking the Secrets of Longevity: Recent Findin “Unlocking the Secrets of Longevity: Recent Findings in Health Research” is a contemporary scientific perspective summarizing the newest discoveries in the biology of aging and the interventions that can extend human lifespan and healthspan. It provides a clear, accessible overview of how genetics, lifestyle, microbiome science, cellular aging, metabolism, and cutting-edge technologies interact to shape longevity.
unlocking-the-secrets-of-longev…
The article emphasizes that longevity is not determined by a single factor but by a complex web of biological, behavioral, and environmental influences. It highlights major scientific breakthroughs that are redefining our understanding of aging and pointing toward future therapies.
Core Themes & Scientific Findings
1. Longevity Genes and the Biology of Aging
The article explains that genetics plays a key role in determining lifespan.
Recent research has identified FOXO3 as one of the strongest genetic markers of exceptional longevity, frequently found in centenarians. FOXO3 regulates:
stress resistance
DNA repair
cellular survival pathways
Additionally, studies on telomeres—the protective caps on chromosomes—show that maintaining telomere length may slow cellular aging and extend lifespan.
unlocking-the-secrets-of-longev…
2. Lifestyle Factors: Diet, Exercise, and Sleep
The article stresses that lifestyle is equally powerful as genetics, explaining:
Diet
Mediterranean-style diets rich in fruits, vegetables, and healthy fats are linked to lower disease risk and longer lifespan.
>Antioxidants reduce oxidative stress, a major driver of aging.
>Exercise
>Physical activity enhances cardiovascular health, strengthens muscle, and slows cellular aging itself.
Exercise may positively influence aging-related gene expression.
Sleep
Adequate sleep supports repair and regeneration; sleep deprivation accelerates age-related decline and disease risk.
Recent work has uncovered molecular links between sleep quality and aging rate.
unlocking-the-secrets-of-longev…
3. The Microbiome: A New Frontier in Longevity
The article highlights the gut microbiome as a critical regulator of health and aging.
Key points include:
Microbial diversity declines with age.
Imbalances in gut microbes are linked to metabolic, immune, and brain-related aging.
Probiotics, prebiotics, and diet-based microbiome interventions show promise for promoting healthy aging.
The microbiome also influences the gut–brain axis, affecting mood, cognitive function, and neurodegeneration.
unlocking-the-secrets-of-longev…
4. Cellular Senescence and Senolytics
A major aging mechanism the article describes is cellular senescence—the buildup of damaged cells that no longer divide. These “zombie cells” cause inflammation and contribute to:
>cardiovascular disease
>arthritis
>neurodegenerative conditions
Recent findings show that senolytic drugs—therapies that selectively remove senescent cells—can improve healthspan and lifespan in animal models. This is one of the most promising therapeutic frontiers in longevity science.
unlocking-the-secrets-of-longev…
5. Metabolism, Fasting, and Longevity Pathways
The article discusses the deep connection between metabolism and aging:
Caloric restriction and intermittent fasting activate cellular repair pathways.
These strategies improve mitochondrial function and metabolic flexibility.
Sirtuins, a family of proteins involved in stress response and energy regulation, are linked to increased lifespan across species.
Researchers are exploring sirtuin-activating compounds to mimic the effects of caloric restriction in humans.
unlocking-the-secrets-of-longev…
6. Technological Advances Transforming Longevity Research
The article highlights groundbreaking technologies reshaping the field:
CRISPR gene editing
Allows direct manipulation of aging-related genes
Raises major ethical considerations
Single-cell sequencing
Reveals how individual cells age
Identifies new therapeutic targets
Artificial intelligence (AI)
Analyzes massive aging datasets
Accelerates the discovery of anti-aging drugs and biomarkers
Together, these tools are pushing the boundaries of what is possible in aging research.
unlocking-the-secrets-of-longev…
Conclusion
“Unlocking the Secrets of Longevity” portrays aging research as a rapidly advancing, multidisciplinary field. Longevity is shaped by a rich combination of:
genetic resilience
robust metabolic and cellular repair
a healthy microbiome
senescent cell clearance
nutrient-dense diets
exercise and quality sleep
technological innovation
The article concludes that while challenges and ethical questions remain, the accelerating pace of discovery offers real promise for extending both lifespan and healthspan, enabling future generations to live longer, healthier, more fulfilling lives....
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The role of polyamines i
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The role of polyamines in protein-dependent
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“The Role of Polyamines in Protein-Dependent Hypox “The Role of Polyamines in Protein-Dependent Hypoxic Tolerance of Drosophila” is a research article that investigates why dietary proteins and amino acids drastically reduce survival under chronic low-oxygen conditions (hypoxia), using Drosophila melanogaster as the model organism. The study reveals a surprising and biologically important mechanism linking amino acids, polyamines, and hypoxic stress tolerance.
Core Finding
Under chronic hypoxia (5% oxygen), even small amounts of dietary protein dramatically shorten the lifespan of adult flies. This effect is not seen under normal oxygen. The researchers discovered that this life-shortening effect is driven by:
Amino acids themselves
Their metabolic intermediates (L-ornithine, L-citrulline)
Polyamines (putrescine, spermidine, spermine)
Every natural amino acid tested decreased fly survival under hypoxia, even at low millimolar concentrations.
The role of polyamines in prote…
Why proteins become toxic in hypoxia
The study shows that chronic hypoxia unmasks a harmful effect of amino acid metabolism:
Amino acids feed into the polyamine synthesis pathway.
Polyamines, in turn, promote hypusination of eIF5A, a unique post-translational modification required for the active form of this protein.
Both polyamines and eIF5A hypusination are shown to reduce hypoxic tolerance and shorten lifespan.
The role of polyamines in prote…
Thus, amino acids → polyamines → eIF5A hypusination → reduced hypoxic survival.
Pharmacological evidence
Two inhibitors were used to dissect the mechanism:
DFMO, an inhibitor of ornithine decarboxylase (the first enzyme in polyamine synthesis), partially protected hypoxic flies from amino-acid toxicity but had no effect against polyamines themselves. This shows that polyamines are downstream of amino acids.
The role of polyamines in prote…
GC7, a potent inhibitor of eIF5A hypusination, partially rescued flies from both amino-acid- and polyamine-induced death. This demonstrates that eIF5A activation is a key step linking amino acids to reduced hypoxic tolerance.
The role of polyamines in prote…
Hypoxia-inducible factor (HIF-1α/Sima)
The authors investigated whether the classic hypoxia-response pathway played a role. They found:
Chronic hypoxia did not activate strong HIF-1α signalling in adult flies.
Loss-of-function mutants for sima (Drosophila HIF-1α) still showed the same amino-acid toxicity.
The role of polyamines in prote…
Thus, the mechanism is independent of HIF-1α, and represents a separate amino-acid sensing pathway.
Broader biological significance
The study provides strong evidence that:
Low-protein diets dramatically improve hypoxic tolerance, while proteins—through amino acids and polyamines—make tissues more vulnerable during oxygen shortage.
These mechanisms likely have parallels in mammals, where polyamine levels rise in ischemic conditions (stroke, myocardial infarction).
The role of polyamines in prote…
This suggests potential therapeutic strategies: targeting polyamine synthesis or eIF5A hypusination to improve survival under ischemic or hypoxic stress.
Conclusion
The paper identifies a previously unknown mechanism by which dietary amino acids reduce survival under chronic hypoxia. The key pathway is:
Amino acids → polyamine synthesis → eIF5A hypusination → reduced hypoxic tolerance
This mechanism explains why low-protein diets increase hypoxic survival and opens possibilities for treatments against hypoxia-related diseases....
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