Faculty Opinions recommendation of Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study.
Bibliographic record
Abstract
Life extension by calorie restriction (CR) has been widely reported in a variety of species and remains on the forefront of anti-aging intervention studies.We report healthspan and survival effects of CR from a 23-year study in rhesus macaques conducted at the National Institute on Aging (NIA).CR initiated at older ages did not increase survival relative to Controls; however, CR monkeys demonstrated an improved metabolic profile and may have less oxidative stress as indicated by plasma isoprostane levels.When initiated in young monkeys, there was a trend (p=0.06) for a delay in age-associated disease onset in CR monkeys; but again, survival curves were not improved, in contrast to another study reported in the literature.This suggests that the effects of CR in a long-lived animal are complex and likely dependent on a variety of environmental, nutritional, and genetic factors.Calorie restriction (CR) is often reported as the most robust non-genetic mechanism to extend lifespan and healthspan.Typically involving reductions of 10-40% in intake of a nutritious diet, the CR paradigm is frequently used as a tool to understand mechanisms that contribute to aging and age-associated diseases.In addition to lifespan, CR has also been reported to delay or prevent the occurrence of many chronic diseases in a variety of animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.020 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".