Novel Clostridium difficile Anti-Toxin (TcdA and TcdB) Humanized Monoclonal Antibodies Demonstrate In Vitro Neutralization across a Broad Spectrum of Clinical Strains and In Vivo Potency in a Hamster Spore Challenge Model
Bibliographic record
Abstract
Clostridium difficile (C. difficile) infection (CDI) is the main cause of nosocomial antibiotic-associated colitis and increased incidence of community-associated diarrhea in industrialized countries. At present, the primary treatment of CDI is antibiotic administration, which is effective but often associated with recurrence, especially in the elderly. Pathogenic strains produce enterotoxin, toxin A (TcdA), and cytotoxin, toxin B (TcdB), which are necessary for C. difficile induced diarrhea and gut pathological changes. Administration of anti-toxin antibodies provides an alternative approach to treat CDI, and has shown promising results in preclinical and clinical studies. In the current study, several humanized anti-TcdA and anti-TcdB monoclonal antibodies were generated and their protective potency was characterized in a hamster infection model. The humanized anti-TcdA (CANmAbA4) and anti-TcdB (CANmAbB4 and CANmAbB1) antibodies showed broad spectrum in vitro neutralization of toxins from clinical strains and neutralization in a mouse toxin challenge model. Moreover, co-administration of humanized antibodies (CANmAbA4 and CANmAbB4 cocktail) provided a high level of protection in a dose dependent manner (85% versus 57% survival at day 22 for 50 mg/kg and 20 mg/kg doses, respectively) in a hamster gastrointestinal infection (GI) model. This study describes the protective effects conferred by novel neutralizing anti-toxin monoclonal antibodies against C. difficile toxins and their potential as therapeutic agents in treating CDI.
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) | 0.001 | 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".