Expression of Toll-like receptor 4 and 2 in horse lungs
Bibliographic record
Abstract
Toll-like receptor (TLR) is a key component in launching innate immune response to microbial challenge. TLR4 and TLR2 are recognized as specific receptors for components of Gram-negative and Gram-positive bacteria, respectively. Horses are extremely sensitive to endotoxin-induced cardiopulmonary distress and mortality which causes significant economic losses. To date, there are no data on the expression of TLR4 and TLR2 in horse lungs. Therefore, we examined the expression of TLR4 and TLR2 in lungs from normal or Escherichia coli lipopolysaccharide (E. coli LPS; 50 ng/kg; iv) treated horses. We also studied the impact of the depletion of pulmonary intravascular macrophages (PIM) on TLR4 and TLR2 expression in normal or LPS-treated horses. RT-PCR showed TLR4 mRNA but not TLR2, in normal horse lungs. PIM depletion reduced TLR4 mRNA expression without affecting TLR2. The LPS treatment increased the expression of TLR4 and TLR2 mRNA in normal and PIM-depleted horses compared to normal saline-treated horses. Light and electron microscopic immunocytochemistry showed TLR4 protein in PIM, alveolar macrophages and septal endothelium in lungs from normal or LPS-treated horses. Immuno-gold electron microscopy showed TLR4 in PIM and dual-label immuno-electron microscopy co-localized TLR4 and LPS in the cytoplasm and nucleus of PIM of LPS-treated horses. The present manuscript is the first report on the expression of TLR4 and TLR2 in normal and LPS-treated horses and direct co-localization of TLR4 with LPS molecules in PIM. These data provide evidence that PIM are equipped with TLR4 to handle and rapidly respond to circulating endotoxins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".