Expression of TLR10 in human lungs and neutrophils
Bibliographic record
Abstract
Toll‐like receptors (TLRs) are conserved immune receptors that play critical roles in innate immunity. TLR10 dimerize with TLR1 or TLR2 on the plasma membrane but the identity of its ligand remains unclear. There also is a lack of information regarding expression of TLR10 in the lungs and neutrophils. Because functional TLR10 gene is present in human and chicken but not in mice, we examined TLR10 protein expression in normal and inflamed human and chicken lungs. Immunohistochemistry showed TLR10 in the vascular endothelium in the human and chicken lungs. Immunohistochemistry and Western blots detected an increase in TLR10 protein in lungs of chicken infected with E. coli or Fowl Adenovirus. Human neutrophils stimulated with E. coli lipopolysaccharide (1μg/ml), which binds TLR4, showed increased expression of TLR10 protein at 60 and 120 minutes but a reduction at 90 minutes with Western blots. The surface expression of TLR10 examined with flow cytometry mirrored the changes observed with Western blots. Confocal microscopy showed cytosolic and nuclear TLR 10 in normal neutrophils. TLR10 in activated neutrophils co‐localized with flotallin‐1, a lipid raft marker, and EEA‐1, an early endosomal marker, to suggest its endocytosis. We conclude that TLR10 is expressed in human and chicken lung vasculature, and that LPS alters expression of TLR10 and induce its endocytosis in human neutrophils. Grant Funding Source : NSERC
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".