The glucocorticoid receptor is affected by its target ZBTB16 in a dissociated manner
Bibliographic record
Abstract
The glucocorticoid receptor (GR) mediates many activating and repressive effects of glucocorticoids in multiple contexts. Glucocorticoids can robustly induce the transcriptionally active protein Zinc finger and BTB domain containing 16 (ZBTB16). We evaluated how cortisol-induced ZBTB16, in turn, affects various GR-mediated actions in human cells and in zebrafish. We found that prevention of ZBTB16 induction led to potentiated GR-dependent effects on the human endothelial cell barrier and blood glucose levels in zebrafish larvae. In contrast, zbtb16 functional knockout abolished the GR-dependent effects on the inflammatory response in zebrafish larvae. At the mRNA level, zbtb16 knockdown potentiated transactivation and attenuated transrepression in a subset of GR target genes. Finally, ZBTB16 protein was strongly induced by dexamethasone in fibroblast-like synoviocytes derived from osteoarthritis patients. The data suggest that cortisol-induced ZBTB16 acts as an intracellular modulator of glucocorticoid action by limiting GR-mediated activating effects and enhancing repressive effects. This mechanism may facilitate a return to the initial cellular state after (proinflammatory) stimulation and enhance GR's anti-inflammatory effects. This mechanism is similar to that of 'dissociated' GR ligands and may guide drug development that aims to reduce side effects while retaining the clinical benefits of glucocorticoid treatment.
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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 | 0.001 |
| 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".