Isolation, Characterization, And Therapeutic Potential Of Bacteriophages Against Multidrug-Resistant Bacteria
Bibliographic record
Abstract
The global rise in multidrug-resistant (MDR) bacterial infections is driven by excessive and prolonged antibiotic use in human and veterinary medicine.This study aimed to isolate and characterize bacteriophages targeting ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacteriaceae) -a group of bacteria responsible for the majority of hospital-acquired infections.Bacteriophages were isolated from clinical samples and wastewater.Morphological classification by electron microscopy revealed phages from the families Myoviridae, Podoviridae, and Siphoviridae.Genomic analysis confirmed the absence of toxin, integrase, or antibiotic resistance genes, supporting their therapeutic safety.The phages showed narrow host specificity, high lytic activity (up to 100% for some strains), low frequency of resistant mutants (10⁻⁷-10⁻⁸), and rapid adsorption and replication rates.Phage stability was maintained for 12 months under 4-25 °C.These findings support the potential of phage therapy as a targeted and safe treatment for MDR infections in clinical settings.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".