Bibliographic record
Abstract
In this review we discuss the recent findings concerning the mechanisms that restrict somitic cells to the skeletal muscle fate, the myogenic regulatory factors controlling skeletal muscle differentiation and specification of myogenic cell lineages, the nature of inductive signals and the role of secreted proteins in embryonic patterning of the myotome. More specifically, we review data which strongly support the hypothesis that Myf-5 plays a unique role in development of epaxial muscle, that MyoD plays a unique role in development of hypaxial muscles derived from migratory myogenic precursor cells, and that both genes are responsible for development of intercostal and abdominal muscles (hypaxial muscles that develop from the dermatomal epithelia). In addition, while discussing upstream and post-translational regulation of myogenic regulatory factors (MRFs), we suggest that correct formation of the myotome requires a complex cooperation of DNA binding proteins and cofactors, as well as inhibitory function of non-muscle cells of the forming somite, whose proteins would sequester and suppress the transcription of MRFs. Moreover, in the third part of our review, we discuss embryonic structures, secreted proteins and myogenic induction. However, although different signaling molecules with activity in the process of somite patterning have been identified, not many of them are found to be necessary during in vivo embryonic development. To understand their functions, generation of multiple mutants or conditional/tissue-specific mutants will be necessary.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.011 |
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".