Glibenclamide treatment prevents depressive-like behavior and memory impairment induced by chronic unpredictable stress in female mice
Bibliographic record
Abstract
Glibenclamide is a second-generation sulfonylurea used in the treatment of Type 2 Diabetes Mellitus. The primary target of glibenclamide is ATP-sensitive potassium channels inhibition; however, other possible targets include the control of inflammation and blood-brain barrier permeability, which makes this compound potentially interesting for the management of brain-related disorders. Here, we showed that systemic treatment with glibenclamide (5 mg/kg, p.o., for 21 days) could prevent the behavioral despair and the cognitive dysfunction induced by chronic unpredictable stress (CUS) in mice. In nonhypoglycemic doses, glibenclamide attenuated the stress-induced weight loss, decreased adrenal weight, and prevented the increase in glucocorticoid receptors in the prefrontal cortex, suggesting an impact in hypothalamic-pituitary-adrenal (HPA) axis function. Additionally, we did not observe changes in Iba-1, NLRP3 and caspase-1 levels in the prefrontal cortex or hippocampus after CUS or glibenclamide treatment. Thus, this study suggests that chronic treatment with glibenclamide prevents the emotional and cognitive effects of chronic stress in female mice. On the other hand, the control of neuroinflammation and NLRP3 inflammasome pathway is not the major mechanism mediating these effects. The behavioral effects might be mediated, in part, by the normalization of glucocorticoid receptors and HPA axis.
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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 | 0.000 |
| 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".