Twist2‐expressing cells reside in human skeletal muscle and are responsive to aging and resistance exercise training
Bibliographic record
Abstract
Skeletal muscle is maintained and repaired by sub-laminar, Pax7-expressing satellite cells. However, recent mouse investigations have described a second myogenic progenitor population that resides within the myofiber interstitium and expresses the transcription factor Twist2. Twist2-expressing cells exclusively repair and maintain type IIx/b muscle fibers. Currently, it is unknown if Twist2-expressing cells are present in human skeletal muscle and if they function as myogenic progenitors. Here, we perform a combination of single-cell RNA sequencing analysis and immunofluorescence staining to demonstrate the identity and localization of Twist2-expressing cells in human skeletal muscle. Twist2-expressing cells were identified to be anatomically and transcriptionally comparable to fibro-adipogenic progenitors (FAPs) and lack expression of typical satellite cell markers such as Pax7. Comparative analysis revealed that human and mouse Twist2-expressing cells were highly transcriptionally analogous and resided within the same anatomical structures in vivo. Examination of young and aged skeletal muscle biopsy samples revealed that Twist2-positive cells are more prevalent in aged muscle and increase following 12-weeks of resistance exercise training (RET) in humans. However, the quantity of Twist2-positive cells was not correlated with indices of muscle mass or muscle fiber cross-sectional area (CSA) in young or older muscle, and their abundance was surprisingly, negatively correlated with CSA and myonuclear domain size following RET. Taken together, we have identified cells expressing Twist2 in human skeletal muscle which are responsive to aging and exercise. Further examination of their myogenic potential is warranted.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".