Adaptive immune response to <i>Clostridium difficile</i> infection: A perspective for prevention and therapy
Bibliographic record
Abstract
Clostridium difficile infection (CDI) is one of the most important nosocomial illnesses and a major cause of morbidity and mortality. While initial treatment of CDI is usually successful, unprovoked relapses remain an important and frustrating problem. This review examines the literature describing the natural immune response to CDI, and to what extent it can explain the propensity for relapses. In particular, we discuss studies on antibody and, to a lesser extent, B cell and T cell responses in CDI. Despite years of study, there remains incomplete understanding of the natural antibody response to the major pathogenic toxins, TcdA and TcdB, and other bacterial antigens, in CDI. Recent literature suggests that a specific subset of neutralizing antibodies that target the putative carbohydrate-binding domains of TcdB and possibly TcdA have the greatest protective ability. This is further supported by recent successful clinical trials of a humanized monoclonal antibody to the major toxin TcdB. A better understanding of how and why the most protective adaptive immune response develops may lead to improved vaccine and therapeutic targets for recurrent CDI.
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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 | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".