CD36 neutralisation blunts TLR2-IRF7 but not IRF3 pathway in neonatal mouse brain and immature human microglia following innate immune challenge
Bibliographic record
Abstract
Innate immune response in neonatal brain is associated with a robust microglial activation and induction of Toll-like Receptors (TLRs). To date, the role of the scavenger receptor CD36 in TLRs modulation, particularly TLR2 signaling, has been well established in adult brain. However, the crosstalk between TLR4, TLR2 and CD36 and its immunogenic influence in the neonatal brain remains unclear. In this study, using a CD36 blocking antibody (anti-CD36) at post-natal day 8, we evaluated the response of neonates to systemic endotoxin (lipopolysaccharide; LPS) challenge. We visualized the TLR2 response by bioluminescence imaging using the transgenic mouse model bearing the dual reporter system luciferase/green fluorescent protein under transcriptional control of a murine TLR2 promoter. The anti-CD36 treatment modified the LPS induced inflammatory profile in neonatal brains, causing a significant decrease in inflammatory cytokine levels and the TLR2 and TLR3 mediated signalling.The interferon regulatory factor 3 (IRF3) pathway remained unaffected. Treatment of the LPS-challenged human immature microglia with anti-CD36 induced a marked decrease in TLR2/TLR3 expression levels while TLR4 and IRF3 expression was not affected, suggesting the shared CD36 regulatory mechanisms in human and mouse microglia. Collectively, our results indicate that blocking CD36 alters LPS-induced inflammatory profile of mouse and human microglia, suggesting its role in fine-tuning of neuroinflammation.
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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 | 0.001 |
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".