Mechanisms Through Which Some Mitochondria-Generated Metabolites Act as Second Messengers That Are Essential Contributors to the Aging Process in Eukaryotes Across Phyla
Bibliographic record
Abstract
Recent studies have revealed that some low-molecular weight molecules produced in mitochondria are essential contributing factors to aging and aging-associated pathologies in evolutionarily distant eukaryotes. These molecules are intermediates or products of certain metabolic reactions that are activated in mitochondria in response to specific changes in the nutrient, stress, proliferation, or age status of the cell. After being released from mitochondria, these metabolites directly or indirectly change activities of a distinct set of protein sensors that reside in various cellular locations outside of mitochondria. Because these protein sensors control the efficiencies of some pro- or anti-aging cellular processes, such changes in their activities allow to create a pro- or anti-aging cellular pattern. Thus, mitochondria can function as signaling platforms that respond to certain changes in cell stress and physiology by remodeling their metabolism and releasing a specific set of metabolites known as "mitobolites." These mitobolites then define the pace of cellular and organismal aging because they regulate some longevity-defining processes taking place outside of mitochondria. In this review, we discuss recent progress in understanding mechanisms underlying the ability of mitochondria to function as such signaling platforms in aging and aging-associated diseases.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".