Resveratrol Protects against Sepsis-Associated Encephalopathy and Inhibits the NLRP3/IL-1<i>β</i>Axis in Microglia
Bibliographic record
Abstract
Sepsis-associated encephalopathy (SAE) is characterized as brain dysfunction associated with sepsis. In this study we sought to investigate the effects of resveratrol in mice with SAE, as well as its effects in NLRP3 inflammasome and IL-1β, which were critical in the pathogenesis of SAE. SAE was induced in mice via cecal ligation and puncture (CLP), and resveratrol was administered at two doses after surgery. Spatial learning memory functions were evaluated by Morris water maze testing. Apoptosis in the hippocampus was quantified using TUNEL assay. Inflammation in the hippocampus was quantified by measuring the levels of microglial activation, NLRP3, and IL-1β. CLP mice treated with resveratrol demonstrated a better spatial memory during water maze training. The TUNEL assay demonstrated significantly attenuated rates of apoptosis, in resveratrol treated mice, while decreasing the number of iba-1 positive microglia in the hippocampus region. NLRP3 expression and IL-1β cleavage were well inhibited by resveratrol dose-dependently. The in vitro results showed that in the BV2 cell lines resveratrol prevents ATP induced NLRP3 activation and IL-1β cleavage, which were reversed by the sirtuin 1 inhibitor, nicotinamide. In conclusion, resveratrol improves the spatial memory in mice with SAE and inhibits the NLRP3/IL-1β axis in the microglia.
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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 | 0.000 | 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".