TnIfast IRE enhancer: Multistep developmental regulation during skeletal muscle fiber type differentiation
Bibliographic record
Abstract
To identify developmental steps leading to adult skeletal muscle fiber-type-specific gene expression, we carried out transgenic mouse studies of the IRE enhancer of the quail TnIfast gene. Histochemical analysis of IRE/herpesvirus tk promoter/beta-galactosidase reporter transgene expression in adult muscle directly demonstrated IRE-driven fast vs. slow fiber-type specificity, and IIB>IIX>IIA differential expression among the fast fiber types: patterns similar to those of native-promoter TnIfast constructs. These tissue- and cell-type specificities are autonomous to the IRE and do not depend on interactions with a muscle gene promoter. Developmental studies showed that the adult pattern of IRE-driven transgene expression emerges in three steps: (1) activation during the formation of primary embryonic (presumptive slow) muscle fibers; (2) activation, to markedly higher levels, during formation of secondary (presumptive fast) fibers, and (3) differential augmentation of expression during early postnatal maturation of the IIB, IIX, IIA fast fiber types. These results provide insight into the roles of gene activation and gene repression mechanisms in fiber-type specificity and can account for apparently disparate results obtained in previous studies of TnI isoform expression in development. Each of the three IRE-driven developmental steps is spatiotemporally associated with a different major regulatory event at the fast myosin heavy chain gene cluster, suggesting that diverse muscle gene families respond to common, or tightly integrated, regulatory signals during multiple steps of muscle fiber differentiation.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".