Glucocorticoid receptors are downregulated in hepatic T lymphocytes in rats with experimental cholangitis
Bibliographic record
Abstract
BACKGROUND: and aims: Primary sclerosing cholangitis is a Th1 cytokine driven disease with a poor clinical responsiveness to glucocorticoid therapy. We have previously documented elevated circulating glucocorticoid levels in cholestatic rats and in addition have noted increased hepatic expression of the Th1 cytokine interferon gamma (IFN-gamma) in a rat model of cholangitis. Therefore, we examined the relationship between circulating glucocorticoid levels, hepatic IFN-gamma expression, and hepatic T cell glucocorticoid receptor (GR) expression in a rat model of cholangitis to provide insight into the possible mechanism underlying hepatic T cell glucocorticoid resistance in cholangitic diseases. METHODS: Cholangitis was induced in male Sprague-Dawley rats by oral administration of low dose alpha-naphthylisothiocyanate (ANIT). On day 14, ANIT fed and control rats were sacrificed, serum collected, and hepatic, splenic, and peripheral blood T lymphocytes isolated for GR expression, as determined by reverse transcription-polymerase chain reaction and western blotting. RESULTS: Circulating glucocorticoid levels were markedly elevated in ANIT fed rats. Hepatic T lymphocyte GR mRNA and protein levels were significantly reduced in ANIT treated rats compared with controls. In contrast, GR mRNA and protein expression in splenic and circulating T lymphocytes was similar in both groups. Furthermore, reduced hepatic T cell GR expression in ANIT fed rats was associated with reduced hepatic CD4(+) T cell sensitivity to dexamethasone inhibitory effects (that is, inhibition of interleukin 2 receptor expression). CONCLUSION: We conclude that hepatic T lymphocyte resistance to elevated endogenous glucocorticoid levels in rats with experimental cholangitis appears, in part, to be mediated by decreased GR expression.
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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 | 0.001 | 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) | 0.001 | 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".