Prevalence and genetic variability of Plesiomonas shigelloides in temperate climate surface waters of the Pannonian Plain
Bibliographic record
Abstract
Plesiomonas shigelloides, a Gram-negative bacterium and the causative agent of intestinal diseases and extraintestinal infections in humans and animals, is most frequently found in aquatic environments in tropical or subtropical areas. The present study was designed to establish the prevalence and genetic variability of P. shigelloides in surface waters (lakes, rivers, ponds, inlets and canals) located in a temperate climate zone, namely the Pannonian Plain of the northern part of Serbia and southern part of Hungary. The strains were isolated directly by plating samples on inositol-brilliant green-bile agar with neutral red or phenol red as indicators. Our results indicate that phenol red effectively facilitates differentiation of P. shigelloides from other bacteria. A number of samples were enriched using alkaline peptone water broth, peptone inositolbile broth and tetrathionate broth. The recovery of the isolates was more successful with the first medium. Out of a total of 51 water samples collected from 28 different locations, 22 samples (43.1%) were found positive for P. shigelloides. Among the 37 isolated strains, 34 were from lakes (Satrinci, Ludas, Panonija, Krivaja, Pecs, Kapetanski rit, Pavlovci, Kovacsszenaja, Dobrodol, Vranjas, Borkovac, Hermann Otto, Sot, Selevrenac, Zobnatica, Palic, Orfui, Jarkovci, Conoplja) and 3 were from rivers (Danube, Sava). The strains were identified by phenotypic characteristic or by the VITEK2 system and confirmed by PCR using 23S rRNA species-specific oligos. The strains showed a high genetic variability, displaying a variety of RAPD profiles. Our results reveal for the first time a high prevalence of genetically diverse P. shigelloides populations in surface waters located in the temperate climate of central and southeastern Europe.
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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 | 0.001 |
| 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".