11β-Hydroxysteroid Dehydrogenase Type 1(11β-HSD1) mediates insulin resistance through JNK activation in adipocytes
Bibliographic record
Abstract
Glucocorticoids are used to treat a number of human diseases but often lead to insulin resistance and metabolic syndrome. 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a key enzyme that catalyzes the intracellular conversion of cortisone to physiologically active cortisol. Despite the known role of 11β-HSD1 and active glucocorticoid in causing insulin resistance, the molecular mechanisms by which insulin resistance is induced remain elusive. The aim of this study is to identify these mechanisms in high fat diet (HFD) experimental models. Mice on a HFD were treated with 11β-HSD1 inhibitor as well as a JNK inhibitor. We then treated 3T3-L1-derived adipocytes with prednisone, a synthetic glucocorticoid, and cells with 11β-HSD1 overexpression to study insulin resistance. Our results show that 11β-HSD1 and JNK inhibition mitigated insulin resistance in HFD mice. Prednisone stimulation or overexpression of 11β-HSD1 also caused JNK activation in cultured adipocytes. Inhibition of 11β-HSD1 blocked the activation of JNK in adipose tissue of HFD mice as well as in cultured adipocytes. Furthermore, prednisone significantly impaired the insulin signaling pathway, and these effects were reversed by 11β-HSD1 and JNK inhibition. Our study demonstrates that glucocorticoid-induced insulin resistance was dependent on 11β-HSD1, resulting in the critical activation of JNK signaling in adipocytes.
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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 | 0.001 |
| 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 | 0.000 |
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".