Lipoteichoic Acid-Induced Lung Inflammation Depends on TLR2 and the Concerted Action of TLR4 and the Platelet-Activating Factor Receptor
Bibliographic record
Abstract
Lipoteichoic acid (LTA) is a major outer cell wall component of Gram-positive bacteria that has been implicated as an important factor in the inflammatory response following bacterial infection. In vitro data indicate roles for TLR2, platelet-activating factor receptor (PAFR), CD14, and LPS-binding protein (LBP) in cellular responsiveness to LTA, whereas the mechanisms contributing to LTA effects in vivo have never been investigated. Using mice deficient for LBP, CD14, TLR2, TLR4, or PAFR, we now examined the role of these molecules in pulmonary inflammation induced by highly purified LTA in vivo. Although pulmonary LBP increased dose-dependently following administration of LTA, the inflammatory response was unaltered in LBP-/- mice. TLR2 proved to be indispensable for the initiation of an inflammatory response, as polymorphonuclear cell influx, TNF-alpha, keratinocyte-derived chemokine, and MIP-2 release were abolished in TLR2-/- mice. Minor effects such as moderately decreased TNF-alpha and MIP-2 levels were observed in the absence of CD14, indicating a role for CD14 as a coreceptor. Quite surprisingly, the absence of TLR4 greatly diminished pulmonary inflammation and the same phenotype was observed in PAFR-/- animals. In contrast to all other mice studied, only TLR4-/- and PAFR-/- mice displayed significantly elevated IL-10 pulmonary concentrations. These data suggest that TLR2 is the single most important receptor signaling the presence of LTA within the lungs in vivo, whereas TLR4 and PAFR may influence lung inflammation induced by LTA either by sensing LTA directly or through recognition and signaling of endogenous mediators induced by the interaction between LTA and TLR2.
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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 | 0.001 | 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".