Function and Regulation of Lipid Biology in Caenorhabditis elegans Aging
Bibliographic record
Abstract
Rapidly expanding aging populations and a concomitant increase in the prevalence of age-related diseases are global health problems today. Over the past three decades, a large body of work has led to the identification of genes and regulatory networks that affect longevity and health span, often benefiting from the tremendous power of genetics in vertebrate and invertebrate model organisms. Interestingly, many of these factors appear linked to lipids, important molecules that participate in cellular signaling, energy metabolism, and structural compartmentalization. Despite the putative link between lipids and longevity, the role of lipids in aging remains poorly understood. Emerging data from the model organism Caenorhabditis elegans suggest that lipid composition may change during aging, as several pathways that influence aging also regulate lipid metabolism enzymes; moreover, some of these enzymes apparently play key roles in the pathways that affect the rate of aging. By understanding how lipid biology is regulated during C. elegans aging, and how it impacts molecular, cellular, and organismal function, we may gain insight into novel ways to delay aging using genetic or pharmacological interventions. In the present review we discuss recent insights into the roles of lipids in C. elegans aging, including regulatory roles played by lipids themselves, the regulation of lipid metabolic enzymes, and the roles of lipid metabolism genes in the pathways that affect aging.
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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 | 0.001 | 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) | 0.000 | 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".