The Correlation between Resistance to Antimicrobial Agents and Harboring Virulence Factors among Enterococcus Strains Isolated from Clinical Samples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p class="1Body"><strong>Objectives:</strong> In Iran as well as throughout the world Enterococci have been rated as the important cause of urinary tract and nosocomial infections. The aim of this study was to evaluate the relationship between high antimicrobial resistance activity and harboring the virulence factors among clinical Enterococcus isolates.</p><p class="1Body"><strong>Materials and Methods:</strong> Clinical strains were isolated from hospitalized patients. Prevalence of different virulence genes was evaluated by PCR method and the relation between resistance to antibiotics and harboring virulence genes was evaluated by statistical analysis.</p><p class="1Body"><strong>Results:</strong> The results showed that <em>E. faecalis</em> (60%) is more prevalent than <em>E. faecium </em>(26%) and harboring more virulence factors. The highest resistance was related to gentamicin in both <em>E. faecalis</em> and <em>E. faecium</em> isolates with the rate of 88.7% and 93.5% respectively. Harboring <em>esp</em>, <em>ace</em> and <em>cyl</em>A are significantly related to resistance to different antibiotics.</p><strong>Conclusion:</strong> The antimicrobial resistance and virulence pattern of Enterococcus must be constantly monitored in order to choose the best antimicrobial treat and prevent nosocomial infections.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it