The Src kinase Fyn is protective in acute chemical-induced colitis and promotes recovery from disease
Bibliographic record
Abstract
Despite progress in understanding enteric inflammation, current therapies, although effective in many patients with inflammatory bowel disease (IBD), have significant side-effects, and, in many patients, it is refractory to treatment. The Src kinase Fyn mediated IFN-γ-induced increased permeability in model epithelia, and so we hypothesized that inhibition of Fyn kinase would be anti-colitic. Mice [B6.129SF2/J wild-type (WT), Fyn KO, or chimeras] received 2.5% dextran sodium sulfate (DSS) or normal water for 10 d and were necropsied immediately or 3 d later. Gut permeability was assessed by FITC-dextran flux, colitis by macroscopic and histologic parameters, and immune cell status by cytokine production and CD4(+) T cell Foxp3 expression. Fyn KO mice consistently displayed significantly worse DSS-induced disease than WT, correlating with decreased IL-10 and increased IL-17 in splenocytes and the gut; Fyn KO mice failed to thrive after removal of the DSS water. Analysis of chimeric mice indicated that the increased sensitivity to DSS was due to the lack of Fyn kinase in hematopoietic, but not stromal, cells, in accordance with Fyn(+) T cell increases in WT mice exposed to DSS and Fyn KO mice having a reduced number of CD4(+)Foxp3(+) cells in baseline or colitic conditions and a reduced capacity to induce Foxp3 expression in vitro. Other experiments suggest that the colonic microbiota in Fyn KO mice is not preferentially colitogenic. Contrary to our expectation, the absence of Fyn kinase resulted in greater DSS-induced disease, and analysis of chimeric mice indicated that leukocyte Fyn kinase is beneficial in limiting colitis.
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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".