Ac-YVAD-cmk improves neurological function by inhibiting caspase-1-mediated inflammatory response in the intracerebral hemorrhage of rats
Bibliographic record
Abstract
OBJECTIVE: Intracerebral hemorrhage (ICH) is acknowledged as a serious clinical problem lacking effective treatments. And caspase-1-mediated inflammatory response happened during the progression of ICH. Therefore, we aimed to investigate the effects of caspase-1 inhibitor Ac-YVAD-cmk on ICH. MATERIALS AND METHODS: Microglia cells were isolated and activated by thrombin for 24 h. Then the transcript and protein expressions of NLRP3 and inflammatory factors were assessed by RT-PCR and western blotting. Moreover, Ac-YVAD-cmk was injected into the ICH model. The mNSS and brain water content were tested at 24 h post-ICH. Finally, the pathological changes of microglia activation following ICH were discovered by the immunohistochemical and HE staining ways. RESULTS: Ac-YVAD-cmk inhibited the activation of pro-caspase-1 and decreased brain edema, in association with decreasing activated microglia and the expression of inflammation-related factors at 24 h post-ICH. Consequently, Ac-YVAD-cmk reduced the release of mature IL-1β/IL-18 in perihematoma, improved the behavioral performance, and alleviated microglia in perihematoma region in ICH rats. CONCLUSIONS: These results indicate that caspase-1 could amplify the plural inflammatory responses in the ICH. Administration of Ac-YVAD-cmk has the potential to be a novel therapeutic strategy for ICH.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".