Intermittent fasting reduces neuroinflammation in intracerebral hemorrhage through the Sirt3/Nrf2/HO-1 pathway
Bibliographic record
Abstract
Abstract Background Inflammation contributes to the poor prognosis of intracerebral hemorrhage (ICH). Intermittent fasting (IF) has been shown to be protective against inflammation in multiple pathogenic processes. In the present study, we aimed to investigated the beneficial effects of IF in attenuating neuroinflammation and neurological deficits in a mouse model of ICH and to investigate the underlying mechanism. Methods ICH was modeled by intrastriatal injection of autologous blood and IF was modeled by every-other-day feeding in male control mice (C57BL/6), mice with and microglia specific knockout Sirt3 f/f ;Cx3cr1-Cre (Sirt3 cKO), and Sirt3 f/f (wild-type) mice. Brain tissues and arterial blood were harvested at 1, 3, 7 and 28 days after ICH for immunohistochemistry analysis of Iba-1, DARPP-32 and HO-1, morphological analysis by HE staining and inflammatory factor release tests by ELISA. Neurological functions were approached by corner test and cylinder test. Fluorescent double-labeled staining of Iba-1 with CD16, Arg1 or Sirt3 was used to provide direct image of co-expression of these molecules in microglia. TUNEL, cleaved caspase-3 and Nissl staining was performed to evaluate cellular injuries. Results IF alleviated neurological deficits in both acute and chronic phases after ICH. Morphologically, IF enhanced hematoma clearance, reduced brain edema in acute phase and attenuated striatum atrophy in chronic phase. In addition, IF decreased the numbers of TUNEL + cells and increased Nissl + neuron number at day 1, 3 and 7 after ICH. IF suppressed CD16 + Iba-1 + microglia activation at day 3 after ICH and reduced inflammatory releases, such as IL-1β and TNF-α. The above effects of IF were attenuated by microglia Sirt3 deletion partly because of an inhibition of Nrf2/HO-1 signaling pathway. Interestingly, IF increased Iba-1 + microglia number at day 7 which mainly expressed Arg1 while decreased the proinflammatory factor levels. In mice with microglia-specific Sirt3 deletion, the effects of IF on Iba-1 + microglia activation and anti-inflammatory factor expressions were attenuated when compared with wild-type Sirt3 f/f mice. Conclusions IF protects against ICH by suppressing the inflammatory responses via the Sirt3/Nrf2/HO-1 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 | 0.000 | 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) | 0.002 | 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".