Thymic stromal lymphopoetin is critical for recovery from DSS induced colitis
Bibliographic record
Abstract
Thymic stromal lymphopoetin (TSLP) influences a plethora of immune functions; including in the colonic mucosa. Aims Here we assessed the role of TSLP in mediating recovery from colonic inflammation. Methods Controls (WT), mice deficient for TSLP (TSLP −/− ), or bone marrow (BM) chimeric mice using TSLP receptor deficient (TSLPR −/− ) BM were subjected to dextran sodium sulfate colitis (DSS; 5% w/v). Mice were assessed daily for weight loss, and inflammation assessed 8 days post‐DSS during overt disease. Results TSLP −/− mice do not display enhanced colonic inflammation during DSS‐induced colitis as determined by similar weight loss, T H 1/T H 17 cytokine production and histological damage compared to WT controls. Despite this, TSLP −/− mice failed to recover from colitis, with progressive weight loss resulting in death. Reduced collagen deposition and increased neutrophil elastase (NE) activity but not metallomatrix protease activity occurred in TSLP −/− as compared to WT mice. Increased NE activity was paralleled by a reduction in the endogenous inhibitor of this enzyme, secretory leukocyte peptidase inhibitor (SLPI). Critically, BM chimeras identified that TSLPR on non‐hematopoeitc cells were sufficient for recovery from DSS‐induced colitis. Additionally, we identified TSLPR on intestinal epithelial cells (IEC), and stimulation of this receptor induced the expression of SLPI. Conclusion TSLP‐elicited signaling through TSLPR on IEC is a critical mediator in wound healing that does not involve restraining of T H 1/T H 17 cytokines. The disparity between TSLP −/− and TSLPR −/− mice suggests that signaling downstream of TSLPR could occur in response to cytokines other than TSLP.
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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) | 0.001 | 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".