Phage–antibiotic combinations: a promising approach to constrain resistance evolution in bacteria
Bibliographic record
Abstract
Antibiotic resistance has reached dangerously high levels throughout the world. A growing number of bacteria pose an urgent, serious, and concerning threat to public health. Few new antibiotics are available to clinicians and only few are in development, highlighting the need for new strategies to overcome the antibiotic resistance crisis. Combining existing antibiotics with phages, viruses the infect bacteria, is an attractive and promising alternative to standalone therapies. Phage-antibiotic combinations have been shown to suppress the emergence of resistance in bacteria, and sometimes even reverse it. Here, we discuss the mechanisms by which phage-antibiotic combinations reduce resistance evolution, and the potential limitations these mechanisms have in steering microbial resistance evolution in a desirable direction. We also emphasize the importance of gaining a better understanding of mechanisms behind physiological and evolutionary phage-antibiotic interactions in complex in-patient environments.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".