Antimicrobial Use, Human Gut Microbiota and Clostridium difficile Colonization and Infection
Bibliographic record
Abstract
Clostridium difficile infection (CDI) is the most important cause of nosocomial diarrhea. Broad-spectrum antimicrobials have profound detrimental effects on the structure and diversity of the indigenous intestinal microbiota. These alterations often impair colonization resistance, allowing the establishment and proliferation of C. difficile in the gut. Studies involving animal models have begun to decipher the precise mechanisms by which the intestinal microbiota mediates colonization resistance against C. difficile and numerous investigations have described gut microbiota alterations associated with C. difficile colonization or infection in human subjects. Fecal microbiota transplantation (FMT) is a highly effective approach for the treatment of recurrent CDI that allows the restoration of a healthy intestinal ecosystem via infusion of fecal material from a healthy donor. The recovery of the intestinal microbiota after FMT has been examined in a few reports and work is being done to develop custom bacterial community preparations that could be used as a replacement for fecal material.
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 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.005 | 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".