Mechanisms of muscle cells alterations and regeneration decline during aging
Bibliographic record
Abstract
Skeletal muscles are essential for locomotion and body metabolism regulation. As muscles age, they lose strength, elasticity, and metabolic capability, leading to ineffective motion and metabolic derangement. Both cellular and extracellular alterations significantly influence muscle aging. Satellite cells (SCs), the primary muscle stem cells responsible for muscle regeneration, become exhausted, resulting in diminished population and functionality during aging. This decline in SC function impairs intercellular interactions as well as extracellular matrix production, further hindering muscle regeneration. Other muscle-resident cells, such as fibro-adipogenic progenitors (FAPs), pericytes, and immune cells, also deteriorate with age, reducing local growth factor activities and responsiveness to stress or injury. Systemic signaling, including hormonal changes, contributes to muscle cellular catabolism and disrupts muscle homeostasis. Collectively , these cellular and environmental components interact, disrupting muscle homeostasis and regeneration in advancing age. Understanding these complex interactions offers insights into potential regenerative strategies to mitigate age-related muscle degeneration. • Satellite, fibro-adipogenic progenitors and side-population cells are responsible for muscle development and regeneration. • Muscle regenerative capacity deteriorates with age due to cellular and extracellular changes alongside pillars of aging. • Aged progenitor cells undergo cellular changes, leading to cell proliferation and function defects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".