The Effects of Six Potent Age-Delaying Plant Extracts on the Cellular Lipidome of Saccharomyces cerevisiae
Bibliographic record
Abstract
The objective of this study is to better understand the involvement of anti-aging plant extracts on the lipidome. My hypothesis was that some of the previously studied twenty-one age-delaying plant extracts extend aging by altering lipid and free fatty acid synthesis and/or metabolism. To test this hypothesis, my thesis analyzed the lipidome of Saccharomyces cerevisiae after treatment with Plant Extract 4, 6, 12, 21, 26, and 39, all of which have been previously shown to delay aging. The lipids were extracted from the treated and untreated S. cerevisiae and analyzed by a Mass Spectrometer. My results revealed that the six plant extracts enhanced the level of certain lipids and significantly decreased the level of free fatty acids. Similar results were obtained in a previous study done on caloric restriction, where caloric restriction enhanced the level of lipids and decreased the level of free fatty acids. Notably, while some lipids increased or decreased, during both caloric restriction and plant extract exposure, there was a general trend for free fatty acids to decrease, supporting that they may have a more consistent role in aging compared to lipids.
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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".