Longevity Extension by Phytochemicals
Bibliographic record
Abstract
Phytochemicals are structurally diverse secondary metabolites synthesized by plants and also by non-pathogenic endophytic microorganisms living within plants. Phytochemicals help plants to survive environmental stresses, protect plants from microbial infections and environmental pollutants, provide them with a defense from herbivorous organisms and attract natural predators of such organisms, as well as lure pollinators and other symbiotes of these plants. In addition, many phytochemicals can extend longevity in heterotrophic organisms across phyla via evolutionarily conserved mechanisms. In this review, we discuss such mechanisms. We outline how structurally diverse phytochemicals modulate a complex network of signaling pathways that orchestrate a distinct set of longevity-defining cellular processes. This review also reflects on how the release of phytochemicals by plants into a natural ecosystem may create selective forces that drive the evolution of longevity regulation mechanisms in heterotrophic organisms inhabiting this ecosystem. We outline the most important unanswered questions and directions for future research in this vibrant and rapidly evolving field.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".