Alternative Requirements for Vestigial, Scalloped, and Dmef2 during Muscle Differentiation in<i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Vertebrate development requires the activity of the myocyte enhancer factor 2 (mef2) gene family for muscle cell specification and subsequent differentiation. Additionally, several muscle-specific functions of MEF2 family proteins require binding additional cofactors including members of the Transcription Enhancing Factor-1 (TEF-1) and Vestigial-like protein families. In Drosophila there is a single mef2 (Dmef2) gene as well single homologues of TEF-1 and vestigial-like, scalloped (sd), and vestigial (vg), respectively. To clarify the role(s) of these factors, we examined the requirements for Vg and Sd during Drosophila muscle specification. We found that both are required for muscle differentiation as loss of sd or vg leads to a reproducible loss of a subset of either cardiac or somatic muscle cells in developing embryos. This muscle requirement for Sd or Vg is cell specific, as ubiquitous overexpression of either or both of these proteins in muscle cells has a deleterious effect on muscle differentiation. Finally, using both in vitro and in vivo binding assays, we determined that Sd, Vg, and Dmef2 can interact directly. Thus, the muscle-specific phenotypes we have associated with Vg or Sd may be a consequence of alternative binding of Vg and/or Sd to Dmef2 forming alternative protein complexes that modify Dmef2 activity.
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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) | 0.001 | 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".