Blueberry polyphenols increase lifespan and thermotolerance in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
The beneficial effects of polyphenol compounds in fruits and vegetables are mainly extrapolated from in vitro studies or short-term dietary supplementation studies. Due to cost and duration, relatively little is known about whether dietary polyphenols are beneficial in whole animals, particularly with respect to aging. To address this question, we examined the effects of blueberry polyphenols on lifespan and aging of the nematode, Caenorhabditis elegans, a useful organism for such a study. We report that a complex mixture of blueberry polyphenols increased lifespan and slowed aging-related declines in C. elegans. We also found that these benefits did not just reflect antioxidant activity in these compounds. For instance, blueberry treatment increased survival during acute heat stress, but was not protective against acute oxidative stress. The blueberry extract consists of three major fractions that all contain antioxidant activity. However, only one fraction, enriched in proanthocyanidin compounds, increased C. elegans lifespan and thermotolerance. To further determine how polyphenols prolonged C. elegans lifespan, we analyzed the genetic requirements for these effects. Prolonged lifespan from this treatment required the presence of a CaMKII pathway that mediates osmotic stress resistance, though not other pathways that affect stress resistance and longevity. In conclusion, polyphenolic compounds in blueberries had robust and reproducible benefits during aging that were separable from antioxidant effects.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".