MyD88 signalling plays a critical role in host defence by controlling pathogen burden and promoting epithelial cell homeostasis during Citrobacter rodentium-induced colitis
Bibliographic record
Abstract
Myeloid differentiation factor (MyD)88, an adaptor protein shared by the Toll-interleukin 1 receptor superfamily, plays a critical role in host defence during many systemic bacterial infections by inducing protective inflammatory responses that limit bacterial growth. However, the role of innate responses during gastrointestinal (GI) infections is less clear, in part because the GI tract is tolerant to commensal antigens. The current study investigated the role of MyD88 following infection by the murine bacterial pathogen, Citrobacter rodentium. MyD88-deficient mice suffered a lethal colitis coincident with colonic mucosal ulcerations and bleeding. Their susceptibility was associated with an overwhelming bacterial burden and selectively impaired immune responses in colonic tissues, which included delayed inflammatory cell recruitment, reduced iNOS and abrogated production of TNF-alpha and IL-6 from MyD88-deficient macrophages and colons cultured ex vivo. Immunostaining for Ki67 and BrDU revealed that MyD88 signalling mediated epithelial hyper-proliferation in response to C. rodentium infection. Thus, MyD88-deficient mice could not promote epithelial cell turnover and repair, leading to deep bacterial invasion of colonic crypts, intestinal barrier dysfunction and, ultimately, widespread mucosal ulcerations. In conclusion, MyD88 signalling within the GI tract plays a critical role in mediating host defence against an enteric bacterial pathogen, by controlling bacterial numbers and promoting intestinal epithelial homeostasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".