Modulation of the Innate Immune Response by NMDA Receptors Has Neuropathological Consequences
Bibliographic record
Abstract
The aim of this study was to determine whether glutamate receptors modulate the innate immune response in the brain of C3H/HeN and C3H/HeJ mice; the latter bear a loss of function in the toll-like receptor (TLR) 4 gene. Mice received an intrastriatal (IS) infusion of lipopolysaccharide (LPS), the exogenous ligand for TLR4, and were killed at several times thereafter. This treatment activated the transcription of a wide variety of genes involved in the control of the innate immune response. MK-801, an antagonist of NMDA glutamate receptor subtype, exacerbated the effects of the endotoxin in the brain of C3H/HeN mice but not in TLR4-deficient animals. The ipsilateral side of C3H/HeN mice exhibited stronger hybridization signals for the mRNA encoding TLR2, CD14, tumor necrosis factor-alpha, and inhibitory factor-kappaBalpha at various times after the treatment combining MK-801 and LPS. This robust inflammatory response in the brain of C3H/HeN mice was not associated with any convincing signs of neurodegeneration or demyelination that was verified via numerous approaches and at time up to 2 weeks after injection. However, animals that received long-term IS infusion of LPS, together with MK-801, exhibited a significant increase in demyelination levels within the ipsilateral side. Our results demonstrate that binding of glutamate to its cognate NMDA receptor modulates LPS-induced innate immune reaction in a TLR4-dependent manner. This acute response may be crucial to eliminate bacterial cell wall components and minimizing tissue injury. However, sustained deregulation of proinflammatory signaling involving NMDA receptors leads to demyelination and is likely to be a mechanism participating in such pathological conditions.
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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) | 0.001 | 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".