Phage Therapy as an Emerging Antibiotic Alternative
Bibliographic record
Abstract
In 2019, nearly 5 million deaths worldwide were attributed to antimicrobial resistance (AMR), underscoring its profound threat to global public health. AMR causes traditional antibiotics to lose effectiveness against bacterial infections due to the emergence of resistant bacteria. Consequently, phage therapy, which employs bacteria viruses to combat bacterial infections, has become a potential solution. Phages can enhance antibiotic sensitivity by targeting bacterial mutants, influencing the evolution of populations and impacting receptors responsible for antibiotic efflux from cells. Despite the advantages, several limitations to the use of bacteriophages exist. Phage-Antibiotic Synergy (PAS) may address these limitations. PAS describes the phenomenon of improved antimicrobial effect caused by stimulated phage replication in the presence of sublethal concentrations of antibiotics. Phage-antibiotic therapy has effectively reduced the emergence of phage-resistant and antibiotic-resistant strains simultaneously.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".