Early immune innate hallmarks and microbiome changes across the gut during Escherichia coli O157: H7 infection in cattle
Bibliographic record
Abstract
Abstract The zoonotic enterohemorrhagic Escherichia coli (EHEC) O157: H7 bacterium causes diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome (HUS) in humans. Cattle are primary reservoirs and EHEC O157: H7; the bacteria predominately inhabit the colon and recto-anal junctions (RAJ). The early innate immune reactions in the infected gut are critical in the pathogenesis of EHEC O157: H7. In this study, calves orally inoculated with EHEC O157: H7 showed infiltration of neutrophils in the lamina propria of ileum and RAJ at 7 and 14 days post-infection. Infected calves had altered mucin layer and mast cell populations across small and large intestines. There were differential transcription expressions of key bovine β defensins, tracheal antimicrobial peptide ( TAP ) in the ileum, and lingual antimicrobial peptide ( LAP ) in RAJ. The main Gram-negative bacterial/LPS signaling Toll-Like receptor 4 ( TLR4 ) was downregulated in RAJ. Intestinal infection with EHEC O157: H7 impacted the gut bacterial communities and influenced the relative abundance of Negativibacillus and Erysipelotrichaceae in mucosa-associated bacteria in the rectum. Thus, innate immunity in the gut of calves showed unique characteristics during infection with EHEC O157: H7, which occurred in the absence of major clinical manifestations but denoted an active immunological niche.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".