TLR-3 receptor activation protects the very immature brain from ischemic injury
Bibliographic record
Abstract
BACKGROUND: We have shown that preconditioning by lipopolysaccharide (LPS) will result in 90% reduction in ischemic brain damage in P7 rats. This robust LPS neuroprotection was not observed in P3 or P5 pups (corresponding to human premature infant). LPS is a known Toll-like receptor 4 (TLR-4) ligand. We hypothesized that TLRs other than TLR-4 may mediate preconditioning against cerebral ischemic injury in the developing brain. METHODS: TLR-2, TLR-3, TLR-4, and TLR-9 expression was detected in brain sections from P3, P5, and P7 rats by immuno-staining. In subsequent experiments, P5 rats were randomly assigned to TLR-3 specific agonist, poly I:C, or saline treated group. At 48 h after the injections, hypoxic-ischemic (HI) injury was induced by unilateral carotid artery ligation followed by hypoxia for 65 min. Brains were removed 1 week after HI injury and infarct volumes were compared in H&E stained sections between the two groups. RESULTS: TLR-2 and TLR-3 were highly expressed in brains of P3 and P5 but not in P7 rats. The number of TLR-4 positive cells was lower in P3 and P5 compared to P7 brains (P <0.05). TLR-3 was predominately expressed in P5 pups (P <0.05). There was no significant difference in TLR-9 expression in the three age groups. There was a significant reduction in infarct volume (P=0.01) in poly I:C compared to saline pre-treated P5 pups. Pre-treatment with poly I:C downregulated NF-κB and upregulated IRF3 expression in P5 rat ischemic brains. Pre-treatment with poly I:C did not offer neuroprotection in P7 rat brains. CONCLUSION: TLRs expression and function is developmentally determined. Poly I:C-induced preconditioning against ischemic injury may be mediated by modulation of TLR-3 signaling pathways. This is the first study to show that TLR-3 is expressed in the immature brain and mediates preconditioning against ischemic injury.
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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) | 0.000 | 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) | 0.003 | 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".