Wnt family member 1 (Wnt1) overexpression-induced M2 polarization of microglia alleviates inflammation-sensitized neonatal brain injuries
Bibliographic record
Abstract
Intrauterine infection induces inflammation-mediated microglial activation and brain injury. This study aimed to explore the regulatory mechanism of Wnt family member 1 (Wnt1) in intrauterine infection-mediated microglial polarization. The cell counting kit-8 (CCK-8) assay was used to determine the viability of microglia, and cytokine expression levels were determined using enzyme linked immunosorbent assay (ELISA) kits and real-time quantitative PCR (RT-qPCR). The number of CD206+ and CD16/32+ cells was determined by flow cytometry. Wnt1 expression was analyzed using western blotting and immunofluorescence. Moreover, an in vivo assay was performed to verify the role of WNT1 in inflammation-sensitized brain injury in newborn mice. Lipopolysaccharide (LPS) exposure resulted in a decrease in microglial cell viability while increasing the expression levels of inflammatory cytokines (TNF-α, IL-6, and IL-1β), simultaneously promoting M1-type microglial conversion. However, these effects were rescued by overexpression of Wnt1, which was expressed less in microglia exposed to LPS in vitro and in vivo. Here, we found that Wnt1 activated the LKB1-AMPK pathway, and the inhibition of LKB1 attenuated the rescue effects of Wnt1. In addition, LPS exposure reduced the autophagy of microglia, and Wnt1 overexpression enhanced the autophagy, but this effect was reversed by treatment with an LKB1 inhibitor. Wnt1 activated LKB1 to suppress inflammation-mediated activation of microglia, promote M2-type microglia conversion via the AMPK pathway, and alleviate inflammation-sensitized neonatal brain injuries. This provides a potential avenue for the treatment of neonatal brain injuries.
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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 | 0.000 | 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".