Impaired Th17 immunity in recurrent <i>C. difficile</i> infection is ameliorated by fecal microbial transplantation
Bibliographic record
Abstract
ABSTRACT Background & Aims Clostridioides difficile is a leading cause of infectious diarrhea and an urgent antimicrobial resistant threat. Symptoms are caused by its toxins, TcdA and TcdB, with many patients developing recurrent C. difficile infection (CDI), requiring fecal microbiota transplant (FMT). Antibody levels have not been useful in predicting patient outcomes, which is an unmet need. We aimed to characterize T cell-mediated immunity to C. difficile toxins and assess how these responses were affected by FMT. Methods We obtained blood samples from patients with newly acquired CDI, recurrent CDI (with a subset receiving FMT), inflammatory bowel disease with no history of CDI, and healthy individuals (controls). Toxin-specific CD4 + T cell responses were analysed using a whole blood flow cytometry antigen-induced marker assay. Serum antibodies were measured by ELISA. Tetramer guided mapping was used to identify HLA-II-restricted TcdB epitopes and DNA was extracted from TcdB-specific CD4 + T cells for TCR repertoire analysis by Sanger sequencing. Results CD4 + T cell responses to C. difficile toxins were functionally diverse. Compared to controls, individuals with CDI, or inflammatory bowel disease had significantly higher frequencies of TcdB-specific CD4 + T cells. Subjects with recurrent CDI had reduced proportions of TcdB-specific CD4 + Th17 cells, FMT reversed this deficit and increased toxin-specific antibody production. Conclusions These data suggest that effective T cell immunity to C. difficile requires the development of Th17 cells. In addition, they show that an unknown aspect of the therapeutic effect of FMT may be enhanced T and B cell-mediated immunity to TcdB. GRAPHICAL ABSTRACT
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".