Strategies to Overcome Antimicrobial Resistance in NosocomialInfections, A Review and Update
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
Abstract: Nosocomial infections, also known as healthcare-associated infections, are a significant global concern due to their strong association with high mortality and morbidity in both developed and developing countries. These infections are caused by a variety of pathogens, particularly the ESKAPE group of bacteria, which includes the six pathogens Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. These bacteria have demonstrated noteworthy resistance to different antibiotics. : Antimicrobial resistance mechanisms can manifest in various forms, including restricting drug uptake, modifying drug targets, inactivating drugs, active drug efflux, and biofilm formation. Accordingly, various strategies have been developed to combat antibiotic-resistant bacteria. These strategies encompass the development of new antibiotics, the utilization of bacteriophages that specifically target these bacteria, antimicrobial combination therapy and the use of peptides or enzymes that target the genomes or essential proteins of resistant bacteria. : Among promising approaches to overcome antibiotic resistance, the CRISPR/Cas system stands out and offers many advantages. This system enables precise and efficient editing of genetic material at specific locations in the genome. Functioning as a bacterial "adaptive immune system," the CRISPR/Cas system recognizes, degrades, and remembers foreign DNA sequences through the use of spacer DNA segments that are transcribed into CRISPR RNAs (crRNA). : This paper has focused on nosocomial infections, specifically the pathogens involved in hospital infections, the mechanisms underlying bacterial resistance, and the strategies currently employed to address this issue. Special emphasis has been placed on the application of CRISPR/Cas technology for overcoming antimicrobial resistance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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