Intestinal lesions in dogs with acute hemorrhagic diarrhea syndrome associated with <i>netF</i> -positive <i>Clostridium perfringens</i> type A
Bibliographic record
Abstract
Acute hemorrhagic diarrhea syndrome (AHDS), formerly named canine hemorrhagic gastroenteritis, is one of the most common causes of acute hemorrhagic diarrhea in dogs, and is characterized by acute onset of diarrhea, vomiting, and hemoconcentration. To date, histologic examinations have been limited to postmortem specimens of only a few dogs with AHDS. Thus, the aim of our study was to describe in detail the distribution, character, and grade of microscopic lesions, and to investigate the etiology of AHDS. Our study comprised 10 dogs with AHDS and 9 control dogs of various breeds, age, and sex. Endoscopic biopsies of the gastrointestinal tract were taken and examined histologically (H&E, Giemsa), immunohistochemically ( Clostridium spp., parvovirus), and bacteriologically. The main findings were acute necrotizing and neutrophilic enterocolitis (9 of 10) with histologic detection of clostridia-like, gram-positive bacteria on the necrotic mucosal surface (9 of 10). Clostridium perfringens isolated from the duodenum was identified as type A (5 of 5) by multiplex PCR (5 of 5). In addition, each of the 5 genotyped isolates encoded the pore-forming toxin netF. Clostridium spp. (not C. perfringens) were cultured from duodenal biopsies in 2 of 9 control dogs. These findings suggest that the pore-forming netF toxin is responsible for the necrotizing lesions in the intestines of a significant proportion of dogs with AHDS. Given that the stomach was not involved in the process, the term "acute hemorrhagic diarrhea syndrome" seems more appropriate than the frequently used term "hemorrhagic gastroenteritis."
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".