Age-related impairment of T cell-induced skeletal muscle precursor cell function
Bibliographic record
Abstract
Sarcopenia is the age-associated loss of skeletal muscle mass and strength. Recent evidence suggests that an age-associated loss of muscle precursor cell (MPC) functionality contributes to sarcopenia. The objectives of the present study were to examine the influence of activated T cells on MPCs and determine whether an age-related defect in this signaling occurs. MPCs were collected from the gastrocnemius and plantaris of 3-mo-old (young) and 32-mo-old (old) animals. Splenic T cells were harvested using anti-CD3 Dynabead isolation. T cells were activated for 48 h with costimulation of 100 IU/ml interleukin-2 (IL-2) and 5 μg/ml of anti-CD28. Costimulation increased 5-bromo-2'-deoxyuridine incorporation of T cells from 13.4 ± 4.6% in control to 64.8 ± 6.0% in costimulated cells. Additionally, T cell cytokines increased proliferation on MPCs isolated from young muscle by 24.0 ± 5.7%, whereas there was no effect on MPCs isolated from aged muscle. T cell cytokines were also found to be a chemoattractant. T cells were able to promote migration of MPCs isolated from young muscle; however, MPCs isolated from aged muscle did not respond to the T cell-released chemokines. Conversely, whereas T cell-released cytokines did not affect myogenesis of MPCs isolated from young animals, there was a decrease in MPCs isolated from old animals. These data suggest that T cells may play a critical role in mediating MPC function. Furthermore, aging may alter T cell-induced MPC function. These findings have implications for developing strategies aimed at increasing MPC migration and proliferation leading to an improved regenerative capacity of aged skeletal muscle.
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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".