The role of semaphorin3A in myogenic regeneration and the formation of functional neuromuscular junctions on new fibres
Bibliographic record
Abstract
Current research on skeletal muscle injury and regeneration highlights the crucial role of nerve-muscle interaction in the restoration of innervation during that process. Activities of muscle satellite or stem cells, recognized as the 'currency' of myogenic repair, have a pivotal role in these events, as shown by ongoing research. More recent investigation of myogenic signalling events reveals intriguing roles for semaphorin3A (Sema3A), secreted by activated satellite cells, in the muscle environment during development and regeneration. For example, Sema3A makes important contributions to regulating the formation of blood vessels, balancing bone formation and bone remodelling, and inflammation, and was recently implicated in the establishment of fibre-type distribution through effects on myosin heavy chain gene expression. This review highlights the active or potential contributions of satellite-cell-derived Sema3A to regulation of the processes of motor neurite ingrowth into a regenerating muscle bed. Successful restoration of functional innervation during muscle repair is essential; this review emphasizes the integrative role of satellite-cell biology in the progressive coordination of adaptive cellular and tissue responses during the injury-repair process in voluntary 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".