Probiotics and prebiotics in gastrointestinal disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review summarizes the clinical efficacy of probiotics and prebiotics in gastrointestinal disorders and examines the mechanisms of action related to their therapeutic effect. RECENT FINDINGS: The demonstration that immune and epithelial cells can discriminate between different microbial species has extended the known mechanism(s) of action of probiotics beyond simple barrier and antimicrobial effects. It has also confirmed that probiotic bacteria modulate mucosal and systemic immune activity and epithelial function. The progressive unraveling of these mechanisms of action has led to new credence for the use of probiotics and prebiotics in clinical medicine. Level I evidence now exists for the therapeutic use of probiotics in infectious diarrhea in children, recurrent Clostridium difficile-induced infections and postoperative pouchitis. Level II evidence is emerging for the use of probiotics in other gastrointestinal infections, prevention of postoperative bacterial translocation, irritable bowel syndrome, and in both ulcerative colitis and Crohn disease. Nevertheless, one consistent feature has emerged over the past year: Not all probiotic bacteria have similar therapeutic effects. Future clinical trials will need to incorporate this fact into trial planning and design. SUMMARY: The use of probiotics and prebiotics as therapeutic agents for gastrointestinal disorders is rapidly moving into the "mainstream." Mechanisms of action explain the therapeutic effects and randomized; controlled trials provide the necessary evidence for their incorporation into the therapeutic armamentarium.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".