Bibliographic record
Abstract
The etiology of inflammatory bowel disease (IBD) is unknown, but it is thought to arise from an aberrant immune response to a change in colonic environment in a genetically susceptible individual. The intestinal microbiota are located at the complex interface of the epithelial barrier and are sensitive to changes in environmental factors, such as diets, drugs or smoking and signals derived from the intestinal immune system and the gut-brain axis. In patients with IBD, an imbalance in the structural and/or functional configuration of the intestinal microbiota leading to the disruption of the host-microorganism homeostasis (dysbiosis) has been reproducibly reported. As animal models of IBD require gut bacteria to induce inflammation, it is hypothesized that the dysbiosis observed in patients is not only a surrogate of changes at the intestinal barrier but also a potential cause or at least enhancer of the mucosal inflammatory process. That burgeoning notion has stimulated thoughts to modify the intestinal microbiota and rekindled interest in previous work on the efficacy of antibiotics in patients with IBD. The feasibility and tremendous success of fecal microbiota transplantation (FMT) to treat antibiotic resistant Clostridium difficile has finally paved the way to embark into the unchartered territory of IBD using FMT. Different routes and number of administrations, choices of donors, disease status and permitted therapies might have contributed to mixed results, particularly from the so far published randomized controlled trials. However, microbiome analysis suggests that a durable transplantation of donor bacteria to the host appears feasible and might be associated with a higher likelihood of response. On the other hand, this raises the concern of transplanting not only anti-inflammatory active bacteria and their products, but also not-yet-known dispositions for other diseases including cancer. Attempts are being made to better characterize those components of the microbiome of healthy individuals, which might mediate anti-inflammatory functions and assemble 'synthetic stools' for more standardized treatment approaches.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".