Cross-protection against challenge by intravenous<i>Escherichia coli</i>verocytotoxin 1 (VT1) in rabbits immunized with VT2 toxoid
Bibliographic record
Abstract
Rabbits challenged intravenously with Escherichia coli verocytotoxin (VT1, Shiga toxin 1, Stx1) die after developing diarrhea and paralysis, and this outcome can be prevented by pre-immunization with VT1 toxoid. In nonimmune rabbits, intravenously administered 125I-VT1 binds to the central nervous system and gastrointestinal tract, whereas in immunized animals, these organs are spared and the toxin localizes in the liver and spleen. In rabbits immunized with either VT1 or VT2 toxoids, both the homologous or heterologous toxins are prevented from binding to target organs. This has lead to the advancement of a hypothesis that cross-protection in vivo can be induced to both toxins by immunization with a toxoid even though these toxins do not exhibit cross-neutralization in vitro. It was shown that rabbits immunized with VT2 were fully protected from the intravenous administration of 10 LD50 and 50 LD50 of VT1, and this correlated directly with the protection from binding of this toxin to target organs. These findings have important implications on the design of the vaccination strategies to prevent human VT-mediated diseases and also validate the concept of testing for immunity to VT by monitoring the inhibition of binding of the 125I-VT to target organs in preference to performing LD50 assays.
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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) | 0.000 | 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 | 0.001 | 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".