Genetic Expression between Ageing and Exercise: Secreted Protein Acidic and Rich in Cysteine as a Potential “Exercise Substitute” Antiageing Therapy
Bibliographic record
Abstract
Ageing is the effect of time on biological entities. It represents a risk factor for a variety of diseases and health disorders; thus, therapeutic options are required to tackle ageing issues. Modern geriatric medicine prescribes exercise to counteract ageing effects. This work presents secreted protein acidic and rich in cysteine (SPARC) as a potential antiageing therapy. Indeed, SPARC declines with ageing, exercise induces SPARC, and SPARC overexpression in mice mimics exercise. Thus, we hypothesize that SPARC is an exercise-induced factor that is beyond-at least part of-the antiageing effects induced by exercise. This could become a potential antiageing therapy for the elderly that counteracts ageing by mimicking the effects of exercise without needing to perform exercise. This is of particular importance because ageing usually reduces mobility and age-related diseases can reduce the ability to perform the required physical activity. On the other hand, the possibilities of mimicking exercise benefits via SPARC are not limited to ageing, and can be applied in various contexts in which exercise cannot be performed because of physical disabilities, health disorders, or limited mobility.
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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 | 0.001 |
| 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".