Virulence and antimicrobial susceptibility of clinical and environmental strains of <i>Aeromonas</i> spp. from northeastern Brazil
Bibliographic record
Abstract
The aims of the present study were to isolate and identify clinical and environmental strains of Aeromonas spp. by means of biochemical tests and the automated method VITEK 2 and to investigate the presence of the virulence genes cytotoxic enterotoxin (act), hemolysin (asa-1), and type III secretion system (ascV), and also the in vitro antimicrobial susceptibility of the strains. From the clinical isolates, 19 Aeromonas hydrophila, 3 Aeromonas veronii bv. sobria, and 1 Aeromonas caviae were identified, while from the environmental strains, 11 A. hydrophila, 22 A. veronii bv. sobria, 1 A. veronii bv. veronii, and 1 A. caviae were recovered. The gene act was detected in 69.5% of clinical isolates, asa-1 in 8.6%, and ascV in 34.7%. In the environmental strains, the detection rates were 51.4%, 45.7%, and 54.2% for the genes act, asa-1, and ascV, respectively. Resistance to amoxicillin-clavulanate and piperacillin-tazobactam was observed in 15 and 3 clinical strains, respectively, and resistance to ceftazidime, meropenem, imipenem, ciprofloxacin, and trimethoprim-sulfamethoxazole was observed in 1 strain for each drug. Resistance to amoxicillin-clavulanate and piperacillin-tazobactam was detected in 17 and 1 environmental strain, respectively. Higher resistance percentages were observed in clinical strains, but environmental strains also showed this phenomenon and presented a higher detection rate of virulence genes. Thus, it is important to monitor the antimicrobial susceptibility and pathogenic potential of the environmental isolates.
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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 | 0.002 |
| 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) | 0.000 | 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".