Innate Immunity and Microbes: Conversations with the Gut Leading to Intestinal Tissue Repair and Fibrosis
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD) are thought to occur because of impaired mucosal integrity that allows enteric bacteria to leak out of the intestine, triggering maladaptive intestinal inflammation. While the exact pathogenesis of IBD is unclear, studies have recently demonstrated that bacterial activation of innate receptors not only causes inflammation, but may also play an important role in modulating intestinal epithelial barrier function, as well as intestinal epithelial cell proliferation and repair. These mucosal homeostatic mechanisms are essential in limiting as well as repairing mucosal damage. Therefore bacterial activation of the innate immune system can have both inflammatory as well as protective healing roles in the intestine. Strikingly, these findings suggest that dysregulation of these processes could be responsible for both the barrier dysfunction as well as the heightened inflammatory tone that characterize IBD. In this review we explore the current state of knowledge underlying this novel role for innate immunity in the gastrointestinal tract, and discuss the strengths and weaknesses of the chemical and infectious models used in these studies. In addition, we discuss preliminary evidence that exaggerated microbial activation of the innate immune system may cause the fibrotic responses that develop in some patients with IBD. Keywords: TLR, colitis, tissue repair, Citrobacter rodentium, IBD, fibrosis, dextran sodium sulfate
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".