Role of the GATA Family of Transcription Factors in Endocrine Development, Function, and Disease
Bibliographic record
Abstract
The WGATAR motif is a common nucleotide sequence found in the transcriptional regulatory regions of numerous genes. In vertebrates, these motifs are bound by one of six factors (GATA1 to GATA6) that constitute the GATA family of transcriptional regulatory proteins. Although originally considered for their roles in hematopoietic cells and the heart, GATA factors are now known to be expressed in a wide variety of tissues where they act as critical regulators of cell-specific gene expression. This includes multiple endocrine organs such as the pituitary, pancreas, adrenals, and especially the gonads. Insights into the functional roles played by GATA factors in adult organ systems have been hampered by the early embryonic lethality associated with the different Gata-null mice. This is now being overcome with the generation of tissue-specific knockout models and other knockdown strategies. These approaches, together with the increasing number of human GATA-related pathologies have greatly broadened the scope of GATA-dependent genes and, importantly, have shown that GATA action is not necessarily limited to early development. This has been particularly evident in endocrine organs where GATA factors appear to contribute to the transcription of multiple hormone-encoding genes. This review provides an overview of the GATA family of transcription factors as they relate to endocrine function and disease.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".