Molecular Characterization of Multiple Antibiotic-Resistant Acinetobacter baumannii Isolated from Egyptian Patients
Bibliographic record
Abstract
Acinetobacter baumannii is an opportunistic microorganism commonly found in intensive care units (ICUs), and it is responsible for a broad span of hospital-acquired infections. Persistence of nosocomial infection caused by multidrug-resistant (MDR) A. baumannii is an alarming health care issue in Egypt, and at present, colistin remains the treatment of choice for the management of MDR A. baumannii infections. A. baumannii possesses great capacity to develop and acquire resistance to a broad range of antibiotics. The acquisition and dissemination of antibiotic-resistant determinants in A. baumannii strains are mediated by integrons, especially class I integrons. This study focuses on the characterization of some genetic mechanisms underlying the multidrug-resistant phenotypes of A. baumannii isolates in Egypt. Forty-eight A. baumannii specimens were isolated from different hospitalized patients; least resistance was observed against amikacin and tigecycline, with 60% and 58.5% of the isolates resistant, respectively, whereas 62.5% of the isolates were resistant to imipenem and meropenem. The highest sensitivity was found for colistin. Genetic analysis revealed that blaoxa-51 was detected in all isolates, the blaoxa-23-like gene was detected in 80% of the isolates, and blaoxa-24 and blaoxs-58 were not detected in any isolate. Finally, PCR analysis revealed that 6.6% of isolates carried the class I integron gene.
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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 | 0.000 | 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".