Identification of Streptomycin Resistance Gene Among Enterococcus spp. Isolated from Hospitals of Tehran by PCR
Bibliographic record
Abstract
Background and Aim: Enterococci are normal flora and present in the intestinal tract of humans and many mammals. Today, the increasing prevalence of resistant enterococci to aminoglycosides is a major problem in hospitals around the world. In Enterococci, aph (3 ') - IIIa gene plays a major role in the emergence of resistance to streptomycin. The aim of this study was to identify this gene in enterococci isolated from patients using PCR method in Tehran. Materials and Methods: In this study, 350 clinical samples were collected from Milad, Imam Khomeini, and Baghiyatallah hospitals during the years 2015-2014. Enterococcus species were identified based on specific biochemical tests and culture. Then, disk diffusion method was performed according to CLSI guidelines to determine the drug resistance of Enterococcus isolates to different antibiotics. The following primer to streptomycin resistance genes, aph (3 ') - IIIa was used in the PCR method. Results: Among the 150 samples, 87 samples (58%) were reported as Enterococcus faecalis, and 63 (42%) as Enterococcus faecium. In Antibiotic test, strains showed high resistance to tetracycline and erythromycin whereas the least resistance was observed to chloramphenicol and vancomycin, respectively. The high resistance to Streptomycin was in 22.2% strains which included aph (3') -IIIa gene. Conclusions: The results of this study can be concluded that the presence of aph (3') -IIIa gene is the main cause of antibiotic resistance to streptomycin in Enterococcus faecium and E. faecalis strains that is growing gradually in the hospitals in Tehran. Therefore, early detection of this type of resistance with the PCR method could be the best way to prevent the spread of infections caused by this bacterium.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".