Exercise Protects Against Olanzapine-Induced Hyperglycemia in Male C57BL/6J Mice
Bibliographic record
Abstract
Olanzapine is a widely prescribed antipsychotic drug. While effective in reducing psychoses, treatment with olanzapine causes rapid increases in blood glucose. We wanted to determine if a single bout of exercise, immediately prior to treatment, would attenuate the olanzapine-induced rise in blood glucose and if this occurred in an IL-6 dependent manner. We found that exhaustive, but not moderate exercise, immediately prior to treatment, prevented olanzapine-induced hyperglycemia and this occurred in parallel with increases in serum IL-6. To determine if IL-6 was involved in the mechanisms through which exhaustive exercise protected against olanzapine-induced hyperglycemia several additional experiments were completed. Treatment with IL-6 (3 ng/g bw, IP) alone did not protect against olanzapine-induced increases in blood glucose. The protective effects of exhaustive exercise against olanzapine-induced increases in blood glucose were intact in whole body IL-6 knockout mice. Similarly, treating mice with an IL-6 neutralizing antibody prior to exhaustive exercise did not negate the protective effect of exercise against olanzapine-induced hyperglycemia. Our findings provide evidence that a single bout of exhaustive exercise protects against acute olanzapine-induced hyperglycemia and that IL-6 is neither sufficient, nor required for exercise to protect against increases in blood glucose with olanzapine 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".