Regulation of heart development and function through combinatorial interactions of transcription factors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding the molecular mechanisms controlling cardiac-specific gene transcription requires the dissection of the cis-elements that govern the complex spatio-temporal expression of these genes. The four-chambered vertebrate heart is formed during the late phases of fetal development following a series of complex morphogenetic events that require the functional presence of different proteins. The gradient-like expression of some genes, as well as the chamber-specific expression of others, is tightly regulated by combinatorial interactions of several transcription factors and their cofactors. Chamber- and stage-specific cardiac myocyte cultures have been invaluable for identifying transcription factor binding sites involved in basal, chamber-specific, and inducible expression of many cardiac promoters; these studies, which were largely confirmed in vivo in transgenic mouse models, led to the isolation of key regulators of heart development. In addition, the use of pluripotent embryonic stem cells helped elucidate the early molecular events controlling cardiomyocyte differentiation. Together, these studies point to a major role for GATA transcription factors and their interacting partners in transcriptional control of heart development. In addition, members of the T-box family of transcription factors and homeodomain containing proteins, together with chamber-restricted transcriptional repressors and co-repressors play critical roles in heart septation and chamber specification. These fine-tuned cooperative interactions between different classes of proteins are at the basis of normal cardiac function, and alteration in their expression level or function leads to cardiac pathologies.
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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) | 0.001 | 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) | 0.000 | 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