Circulating cell wall components derived from gram‐negative, not gram‐positive, bacteria cause a profound induction of the gene‐encoding Toll‐like receptor 2 in the CNS
Bibliographic record
Abstract
The recent characterization of human homologs of Toll may be the missing link for the transduction events leading to nuclear factor-kappaB (NF-kappaB) activity and proinflammatory gene transcription during innate immune response. Mammalian cells may express as many as 10 distinct Toll-like receptors (TLRs), although TLR2 is a key receptor for recognizing cell wall components of Gram-positive bacteria. The present study investigated the effects of circulating bacterial cell wall components on the expression of the gene-encoding TLR2 across the mouse brain. Surprisingly, while Gram-negative components caused a robust increase in TLR2 transcription within the cerebral tissue, peptidoglycan (PGN) and lipoteichoic acid (LTA), either alone or combined, failed to modulate the receptor transcript. Indeed, the mRNA levels for TLR2 in the choroid plexus and few other regions of the brain remained similar between vehicle-, LTA-, PGN-, and LTA/PGN-administered mice at all the times evaluated (i.e. 30 min to 24 h post-intraperitoneal injection). This contrasts with the profound de novo expression of TLR2 following a single systemic injection of the lipopolysaccharide (LPS). The signal was first detected in regions devoid of blood-brain barrier and few blood vessels and microcapillaries. A second wave of TLR2 expression was also detected from these structures to their surrounding parenchymal cells that stained for a microglial marker iba1. The rapid induction of IkappaBalpha (index of NF-kappaB activity) and up-regulation of the adaptor protein MyD88 suggest that LPS-induced TLR2 transcription may be dependent on the NF-kappaB pathway. These data provide the evidence that TLR2 is not only present in the brain, but its encoding gene is regulated by cell wall components derived from Gram-negative, not Gram-positive, bacteria. The robust wave of TLR2-expressing microglial cells may have a determinant impact on the innate immune response that occurs in the brain during systemic infection by Gram-negative, not Gram-positive, bacteria.
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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".