MyD88-mediated signaling in myo-/fibroblasts is required for control of macrophage maturation under mucosal tolerance in the gut
Bibliographic record
Abstract
Abstract Introduction Colonic myo-/fibroblasts (MFs) are cells of mesenchymal origin in a healthy gut are among the key players in the mucosal tolerance that involve MF-restricted MyD88 signaling. MFs and macrophages interact in colonic tissue. However, the mechanisms of MF mediated regulation of macrophages under intestinal mucosal tolerance has emerging evidence. We hypothesized that MF-restricted MyD88 signaling regulates macrophage maturation under colonic mucosal tolerance. Methods RNAseq, qRT-PCR, H&E, and flow cytometry was used for analysis of colonic tissue/cell derived from B6ACTA2CreMyD88fl/fl, B6Col1a2CreMyD88fl/fl and B6RagCol1a2CreMyD88fl/fl MF-specific conditional KO mice. Results MF-specific deletion of MyD88 in vivo resulted in the development of microcolitis and was associated with dysbiotic decrease in Firmicutes to Bacteroidetes bacterial ratio, a hallmark of intestinal inflammation. This process was associated with the increase in colonic expression of genes linked to the inflammatory activity of myeloid cells and accumulation of immature monocyte-derived macrophages. In vitro deletion of MyD88 from MFs (isolated from MF-specific MyD88 conditional KO mice) resulted in changes of basal and TLR4 mediated pathways involved in myeloid cell migration/maturation and inflammation. Using MF-macrophage co-cultures we demonstrated the MF-restricted MyD88 signaling suppresses myeloid cell inflammatory activity. Conclusion Intrinsic MyD88 signaling within colonic mesenchymal cells is critical to control myeloid cell differentiation and inflammatory activity under mucosal tolerance in the gut. Supported by CTSA/TL1 5TL1TR001440-04 UTMB Institute for Translational Science and R01 DK103150 National Institute of Diabetes and Digestive and Kidney Diseases.
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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 | 0.001 |
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".