Protective Efficacy and Pharmacokinetics of Human/Mouse Chimeric Anti-Stx1 and Anti-Stx2 Antibodies in Mice
Bibliographic record
Abstract
In the United States, Shiga toxin (Stx)-producing Escherichia coli (STEC) is the most frequent infectious cause of hemorrhagic colitis. Hemolytic uremic syndrome (HUS) is a serious sequela that may develop after STEC infection that can lead to renal failure and death in up to 10% of cases. STEC can produce one or more types of Stx, Stx1 and/or Stx2, and Stx1 and Stx2 are responsible for HUS-mediated kidney damage. We previously generated two monoclonal antibodies (MAbs) that neutralize the toxicity of Stx1 or Stx2. In this study, we evaluated the protective efficacy of human/mouse chimeric versions of those monoclonal antibodies, named cαStx1 and cαStx2. Mice given an otherwise lethal dose of Stx1 were protected from death when injected with cαStx1 either 1 h before or 1 h after toxin injection. Additionally, streptomycin-treated mice fed the mouse-lethal STEC strain B2F1 that produces the Stx2 variant Stx2d were protected when given a dose of 0.1 mg of cαStx2/kg of body weight administered up to 72 h post-oral bacterial challenge. Since many STEC strains produce both Stx1 and Stx2 and since either toxin may lead to the HUS, we also assessed the protective efficacy of the combined MAbs. We found that both antibodies were required to protect mice from the presence of both Stx1 and Stx2. Pharmacokinetic studies indicated that cαStx1 and cαStx2 had serum half-lives (t1/2) of about 50 and 145 h, respectively. We propose that cαStx1 and cαStx2, both of which have been tested for safety in humans, could be used therapeutically for prevention or treatment early in the development of HUS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".