Drugs, Nutrients, and Phytoactive Principles Improving the Health Span of Rodent Models of Human Age-Related Diseases
Bibliographic record
Abstract
Rodents are often the species of choice to examine the effect of drugs on survival and on the progression of specific diseased tissues. This statement is also true for research laboratories working in the field of nutrition and aging. In addition to diets that can reduce the life expectancy of rodents, such as diabetogenic or high-fat diets, genetically modified rodents exhibiting different accelerated age-associated diseases also provide important biologic tools to decipher the impact of drugs, nutrients, or phytoactive compounds on their health and life span. This review covers some of the chemicals believed to decelerate the appearance of age-related diseases in different rodent models. Such chemicals include antioxidants, anti-inflammatory molecules, modulators of metabolic sensors, calorie restriction mimetics, and vegetal polyphenolic compounds that affect mitochondrial functions, cellular proliferation or differentiation as well as cell functionality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".