Requirement for serum response factor for skeletal muscle growth and maturation revealed by tissue-specific gene deletion in mice
Bibliographic record
Abstract
Serum response factor (SRF) controls the transcription of muscle genes by recruiting a variety of partner proteins, including members of the myocardin family of transcriptional coactivators. Mice lacking SRF fail to form mesoderm and die before gastrulation, precluding an analysis of the roles of SRF in muscle tissues. To investigate the functions of SRF in skeletal muscle development, we conditionally deleted the Srf gene in mice by skeletal muscle-specific expression of Cre recombinase. In mice lacking skeletal muscle SRF expression, muscle fibers formed, but failed to undergo hypertrophic growth after birth. Consequently, mutant mice died during the perinatal period from severe skeletal muscle hypoplasia. The myopathic phenotype of these mutant mice resembled that of mice expressing a dominant negative mutant of a myocardin family member in skeletal muscle. These findings reveal an essential role for the partnership of SRF and myocardin-related transcription factors in the control of skeletal muscle growth and maturation in vivo.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".