The TLR4–TRIF pathway can protect against the development of experimental allergic asthma
Bibliographic record
Abstract
Summary The Toll‐like receptor ( TLR ) adaptor proteins myeloid differentiating factor 88 (MyD88) and Toll, interleukin‐1 receptor and resistance protein ( TIR ) domain‐containing adaptor inducing interferon‐ β ( TRIF ) comprise the two principal limbs of the TLR signalling network. We studied the role of these adaptors in the TLR 4‐dependent inhibition of allergic airway disease and induction of CD 4 + ICOS + T cells by nasal application of Protollin™, a mucosal adjuvant composed of TLR 2 and TLR4 agonists. Wild‐type (WT), Trif −/− or Myd88 −/− mice were sensitized to birch pollen extract ( BPE x), then received intranasal Protollin followed by consecutive BPE x challenges. Protollin's protection against allergic airway disease was TRIF ‐dependent and MyD88‐independent. TRIF deficiency diminished the CD 4 + ICOS + T‐cell subsets in the lymph nodes draining the nasal mucosa, as well as their recruitment to the lungs. Overall, TRIF deficiency reduced the proportion of cervical lymph node and lung CD 4 + ICOS + Foxp3 − cells, in particular. Adoptive transfer of cervical lymph node cells supported a role for Protollin‐induced CD 4 + ICOS + cells in the TRIF ‐dependent inhibition of airway hyper‐responsiveness. Hence, our data demonstrate that stimulation of the TLR 4‐ TRIF pathway can protect against the development of allergic airway disease and that a TRIF ‐dependent adjuvant effect on CD 4 + ICOS + T‐cell responses may be a contributing mechanism.
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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 | 0.001 |
| 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".