Impact of Glucocorticoid Excess on Glucose Tolerance: Clinical and Preclinical Evidence
Bibliographic record
Abstract
Glucocorticoids (GCs) are steroid hormones that exert important physiological actions on metabolism. Given that GCs also exert potent immunosuppressive and anti-inflammatory actions, synthetic GCs such as prednisolone and dexamethasone were developed for the treatment of autoimmune- and inflammatory-related diseases. The synthetic GCs are undoubtedly efficient in terms of their therapeutic effects, but are accompanied by significant adverse effects on metabolism, specifically glucose metabolism. Glucose intolerance and reductions in insulin sensitivity are among the major concerns related to GC metabolic side effects, which may ultimately progress to type 2 diabetes mellitus. A number of pre-clinical and clinical studies have aimed to understand the repercussions of GCs on glucose metabolism and the possible mechanisms of GC action. This review intends to summarize the main alterations that occur in liver, skeletal muscle, adipose tissue, and pancreatic islets in the context of GC-induced glucose intolerance. For this, both experimental (animals) and clinical studies were selected and, whenever possible, the main cellular mechanisms involved in such GC-side effects were discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".