Curcumin attenuates intracerebral hemorrhage-induced neuronal apoptosis and neuroinflammation by suppressing JAK1/STAT1 pathway
Bibliographic record
Abstract
L., possesses a potential anti-inflammatory activity in many types of disease. In the current study, the mechanism underlying curcumin attenuated ICH-induced neuronal apoptosis and neuroinflammation was explored. Herein, we studied that curcumin decreased brain edema and improved neurological function by using brain edema measurement, assessment of neurological-deficient score, immunofluorescence, and Western blotting analyses after ICH. The results showed that curcumin improved ICH-induced neuronal apoptosis and neuroinflammation. Functionally, the polarization of microglia was assessed by immunofluorescence and Western blotting analyses after ICH in the absence or presence of curcumin. The results suggested that the M1-type microglia were activated after ICH, while the effect was blocked by curcumin treatment, suggesting that curcumin alleviates the neuroinflammation and apoptosis of neurons by suppressing the M1-type polarization of microglia. Mechanically, M1 polarization of microglia was regulated by JAK1/STAT1, and the activation of JAK1/STAT1 was blocked by curcumin. Meanwhile, the protective function of curcumin can be blocked by RO8191, an activator of JAK1. Taken together, our study suggested that curcumin improved the ICH-induced brain injury through alleviating M1 polarization of microglia/macrophage and neuroinflammation via suppressing the JAK1/STAT1 pathway.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".