Shiga Toxins: Potent Poisons, Pathogenicity Determinants, and Pharmacological Agents
Bibliographic record
Abstract
The Shiga toxins (Stxs), also known as Vero toxins and previously called Shiga-like toxins, are a family of potent protein synthesis inhibitors made by Shigella dysenteriae type 1 and some serogroups of Escherichia coli that cause bloody diarrhea in humans. Stxs act as virulence factors for both S. dysenteriae and E. coli and contribute to the disease process initiated by those organisms both directly and indirectly. A handful of methods exist for toxin purification, and the toxins can now even be purchased commercially. However, the Stxs are now classified as select agents, and specific rules govern the distribution of both the toxin and clones of the toxin. Toxin delivery into the host in S. dysenteriae type 1 is most likely aided by the invasiveness of that organism. Although the Stxs are made and produced by bacteria, they do not appear to act against either their host organism or other bacteria under normal circumstances, most likely because the A subunit is secreted from the cytoplasm as soon as it is synthesized and because the holotoxin cannot enter intact bacterial cells. The effectiveness of antibiotic therapy in patients infected with Stx-producing E. coli (STEC) such as O157:H7 as well as the potential risks of such treatment are areas of controversy. Several studies indicate that the course of the diarrhea stage of the disease is unaltered by antibiotic treatment. Several groups anticipate that a therapy that targets the Stxs is an important component of trying to alleviate disease caused by Stx-producing bacteria.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".