Clostridium botulinum type C, D, C/D, and D/C: An update
Bibliographic record
Abstract
is the main causative agent of botulism, a neurological disease encountered in humans as well as animals. Nine types of botulinum neurotoxins (BoNTs) have been described so far. Amongst these "toxinotypes," the A, the B and E are the most frequently encountered in humans while the C, D, C/D and D/C are mostly affecting domestic and wild birds as well as cattle. In France for instance, many cases and outbreaks are reported in these animal species every year. However, underestimation is very likely at least for avifauna species where the detection of dead animals can be challenging. Knowledge about BoNTs C, D, C/D, and D/C and the diseases they cause in animals and humans is still scarce and unclear. Specifically, the potential role of animal botulism outbreaks in cattle and poultry as a source of human illness needs to be further assessed. In this narrative review, we present the current knowledge about toxinotypes C, D, C/D, and D/C in cattle and poultry with, amongst various other aspects, their epidemiological cycles. We also discuss the zoonotic potential of these toxinotypes and some possible ways of risk mitigation. An adapted and effective management of botulism outbreaks in livestock also requires a better understanding of these less common and known toxinotypes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".