Extracellular Matrix and Hormones Modulate DAX-1 Localization in the Human Fetal Adrenal Gland
Bibliographic record
Abstract
CONTEXT: The orphan nuclear receptor DAX-1 is essential for human adrenal cortex development and functions as a transcriptional repressor of multiple genes implicated in steroidogenic pathways. OBJECTIVE: The aim of this study was to investigate the localization of the DAX-1 protein in human fetal adrenal glands and to assess whether this protein can be modulated by the extracellular matrix and hormones. RESULTS: DAX-1 is localized mainly in the nucleus in the outer definitive zone and in the cytoplasm in the fetal zone, whereas the number of DAX-1 positive cells decreases from the external to the internal portion of the gland. When cultured on a collagen or a fibronectin matrix, DAX-1 is localized in the nucleus of the definitive cells and exhibits a nucleocytoplasmic distribution in the fetal cells. ACTH stimulation induces nuclear localization of DAX-1 in fetal cells cultured on collagen without modifying nucleocytoplasmic localization on fibronectin. In contrast, angiotensin II induces the protein to be localized only in the cytoplasm in fetal cells cultured on either collagen or fibronectin. CONCLUSIONS: The localization of DAX-1 is compatible with the known functional properties of DAX-1 regarding the steroidogenic activity of adrenal cells. Moreover, this study suggests that modulation of DAX-1 localization in the fetal adrenal gland by hormones and components of the extracellular matrix may represent a mechanism for controlling the expression of steroidogenic enzymes in the definitive and fetal zones.
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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) | 0.002 | 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".