Omarigliptin Protects the Integrity of the Blood–Brain Barrier After Intracerebral Hemorrhage in Mice
Bibliographic record
Abstract
Purpose: Intracerebral hemorrhage (ICH) is a fatal disease without effective treatment. The damage of the blood-brain barrier (BBB) is a key cause of brain edema and herniation after ICH. Omarigliptin (also known as MK3102) is a potent antidiabetic that inhibits dipeptidyl peptidase (DPP4); the latter has the ability to bind and degrade matrix metalloproteinases (MMPs). The present study aims to investigate the protective effects of omarigliptin against the destruction of BBB following ICH in mice. Methods and Materials: Collagenase VII was used to induce ICH in C57BL/6 mice. MK3102 (7 mg/kg/day) was administered after ICH. The modified neurological severity scores (mNSS) were carried out to assess neurological functions. Nissl staining was applied to evaluate neuronal loss. Brain water content, Evans blue extravasation, Western blots, immunohistochemistry and immunofluorescence were used to study the protective effects of BBB with MK3102 at 3 days after ICH. Results: MK3102 reduced DPP4 expression and decreased hematoma formation and neurobehavioral deficits of ICH mice. This was correspondent with lowered activation of microglia/macrophages and infiltration of neutrophils after ICH. Importantly, MK3102 protected the integrity of the BBB after ICH, associated with decreased expression of MMP-9, and preservation of the tight junction proteins ZO-1 and Occludin on endothelial cells through putative degradation of MMP-9, and inhibition of the expression of CX43 on astrocytes. Conclusion: Omarigliptin protects the integrity of the BBB in mice after ICH injury.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".