Delineating the relationship between immune system aging and myogenesis in muscle repair
Bibliographic record
Abstract
Abstract How aging affects the communication between immune cells and myoblasts during myogenesis is unclear. We therefore investigated how aging impacts the cellular synchronization of these two processes after muscle injury. Muscles of old mice (20 months) had chronic inflammation and fewer satellite cells compared to young mice (3 months). After injury, young mice developed a robust, but transient inflammatory response and a stepwise myogenic gene expression program. These responses were impaired with age. Replacement of old bone marrow (BM) via heterochronic bone marrow transplantation (BMT) increased muscle mass and performance on locomotive and behavioural tests. After injury, Y-O BMT restored the immune cell and cytokine profiles to a young phenotype and enhanced satellite cell activity while O-O BMT amplified a late-onset proinflammatory response. In vitro, conditioned media from young or old macrophages had no effect or impaired myoblast proliferation, respectively. Thus, BM age negatively affects myogenesis by inhibiting myoblast proliferation.
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 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".