A Study of the Role of the Six Family of Transcription Factors in Adult Skeletal Muscle Homeostasis
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Bibliographic record
Abstract
Duchenne Muscular Dystrophy (DMD) is characterized by persistent deterioration and regeneration of skeletal muscles. This occurs when ablation of the Dystrophin protein – through deleterious, nonsense, or frameshift mutations in the coding gene – destabilizes the Dystrophin-Associated Glycoprotein Complex (DAPC), resulting in a multitude of signaling defects. Upregulation of a closely related protein, Utrophin A, has been shown to alleviate the DMD phenotype, and slow-twitch oxidative muscle fibers express innately increased sarcolemmal Utrophin levels conferring resistance to the disease. Studies have shown that the Six family of Transcription Factors (TFs) promote the formation and maintenance of fast-twitch muscle, suggesting that antagonizing the Six TFs and causing a fiber type switch may be a therapeutic approach to treating DMD. In this study, partial loss-of function through RNA interference methodologies in adult skeletal muscles were combined with bioinformatic analyses, to elucidate the therapeutic potential of the antagonism of the Six TFs. Knockdown of Six1 is shown to increase Utrophin levels, with a suggested increase in Nuclear factor of activated T-cells (NFAT) activity. This may be partially mediated by Six1 regulation of a known inhibitor of the NFAT pathway, Myoz1, described herein. Six1 knockdown is also shown to modulate thyroid hormone regulated gene expression, mediated through a novel target, MCT10. This thesis elucidates putative mechanisms by which Six TFs may regulate pro-fast-twitch skeletal muscle fiber type by both antagonizing NFAT activity and promoting thyroid hormone signaling.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it