Characterisation of <i>InlA</i> truncation in <i>Listeria monocytogenes</i> isolates from farm animals and human cases in the province of Quebec
Bibliographic record
Abstract
The introduction of Listeria monocytogenes into the food production chain is a concern, with numerous grouped cases of listeriosis associated with milk‐derived or pork‐derived products have been documented. Management of this zoonotic pathogen considers all strains as an equal risk. Recently, a new perspective for characterisation of strain virulence was introduced with the discovery of the unaltered sequence of InlA as a determinant of strain virulence; this has also been reported as an infrequent finding among so‐called environmental strains, that is, strains isolated from food or from surfaces in food industries. The aim of this study was to differentiate L monocytogenes strains isolated from animal cases versus those from human cases and to differentiate clinical strains from environmental ones using a Caenorhabditis elegans virulence testing model. In Quebec in 2013/2014, the surveillance of L monocytogenes clinical isolates registered a total of 20 strains of animal origin and 16 pulsed‐field gel electrophoresis types isolated from human cases. The mixed PCR multiplex agglutination protocol used for geno‐serotyping clearly discriminated genogroup IVB strains from bovine and human origins. The presence of a premature stop codon single nucleotide polymorphism in the inlA gene sequence in clinical strains and the identical behaviour of particular strains in the C elegans model are discussed in this paper from the perspective of industrial management of L monocytogenes risk.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".