Toll-like receptor 5 deficiency protects from wasting disease in a T cell transfer colitis model in T cell receptor-β-deficient mice
Bibliographic record
Abstract
BACKGROUND: Toll-like receptor 5 (TLR5) is implicated in the innate and adaptive immune responses that are associated with inflammatory bowel disease (IBD). In humans TLR5 is expressed on CD4(+) T cells and costimulation with flagellin potentiates effector and regulatory T cell responses. The aim of this study was to determine the role of TLR5 in CD4(+) T cell subsets versus other cells in induction of disease in a model of T cell-dependent colitis. METHODS: TLR5 expression on CD4(+) T cells was assessed by real-time reverse-transcriptase polymerase chain reaction (RT-PCR). Wildtype (WT) or TLR5-deficient (5-/-) CD4(+) T conventional cells (Tconv) and T regulatory cells (Treg) were compared for their ability to induce and suppress T cell transfer colitis, respectively. In addition, the role of TLR5 expression in recipient mice was analyzed. RESULTS: TLR5 is preferentially expressed on mouse Treg compared to Tconv, although expression levels were low. The colitogenic capacity of WT and 5-/- Tconv was found to be similar and Treg from WT or 5-/- donor animals both prevented T cell transfer colitis in TLR-competent hosts. TLR5 deficiency in recipient mice, however, did affect the disease process, as T cell receptor-β (TCRβ) 5-/- recipients had decreased weight loss compared to TCRβ recipient mice when WT Tconv were used. CONCLUSIONS: TLR5 expression on T cells is not required for induction of or protection from T cell-dependent colitis. Expression of TLR5 in non-T cells has a pathogenic role, since TLR5 deficiency in recipient mice protects against weight loss induced by WT T cells.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".