Effects of glucocorticoids and exercise on pancreatic β‐cell function and diabetes development
Bibliographic record
Abstract
Peripheral insulin resistance and pancreatic β-cell dysfunction are hallmark characteristics of type 2 diabetes mellitus (T2DM). Several contributing factors have been proposed to promote these two defects in individuals with T2DM, including physical inactivity and chronic exposure to various psychosocial factors that increase the body's exposure to glucocorticoids, the main stress hormones in humans. Initially, β-cells have been shown to adapt to these stimuli, a phenomenon known as β-cell 'compensation'. However, long-term exposure to these physiologic and psychological stressors induces islet failure. Interestingly, glucocorticoids stimulate β-cell mass growth in parallel with promoting severe insulin resistance, the former being an important adaptive response to the latter. The direct relationship between glucocorticoids and β-cell dysfunction remains a controversial area of research. Elevations in circulating and/or tissue specific glucocorticoids have been associated with the development of obesity and T2DM in human and rodent models; however, the progression from insulin resistance to overt T2DM is highly disputed with respect to the in vivo and in vitro effects of glucocorticoids. Paradoxically, both intermittent physical stress and regular exercise alleviate insulin resistance and help to preserve β-cell mass, potentially by lowering glucocorticoid levels. Recent studies have begun to examine the mechanisms of intermittent and chronic glucocorticoid exposure and regular exercise in altering β-cell function. This review highlights recent discoveries on the physiological regulation of β-cells and diabetes development in conditions of elevated glucocorticoids, regular exercise and intermittent stress.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".