Interaction between Host Cells and Septicemic<i>Salmonella enterica</i>Serovar Typhimurium Isolates from Pigs
Bibliographic record
Abstract
Salmonella enterica serovar Typhimurium is an important pathogen in swine and is also a frequently reported zoonotic agent. The objective of this study was to characterize isolates of S. enterica serovar Typhimurium associated with septicemia in swine and to compare them to isolates recovered from clinically healthy pigs. We were particularly interested in comparing the two groups of isolates for their ability to adhere to and invade host cells, to be phagocytized and survive in monocyte cells, to induce apoptosis, and to adhere to intestinal mucus. Their surface properties were also evaluated by interactions with solvents. The isolates recovered from diseased animals were shown to invade intestinal epithelial cell lines at a higher rate (P = 0.003) than isolates from healthy pigs. Septicemic isolates were phagocytized by human monocytes at a higher rate than isolates from healthy pigs (P = 0.009). The mean percentages of phagocytosis were significantly lower for human monocytes than for porcine monocytes (P = 0.02 and P = 0.008, respectively) for isolates from both diseased and healthy animals. Healthy animal isolates were phagocytized more by porcine monocytes at 15 min (P = 0.02) than septicemic isolates. No difference between isolates from septicemic pigs and isolates from healthy pigs was detected for other tested parameters. These results suggest that septicemic isolates have a particular pattern of invasion.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".