Phage display for the detection, analysis, disinfection, and prevention of <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
Abstract The World Health Organization has designated Staphylococcus aureus as a global health concern. This designation stems from the emergence of multiple drug‐resistant strains that already account for hundreds of thousands of deaths globally. The development of novel treatment strategies to eradicate S. aureus or mitigate its pathogenic potential is desperately needed. In the effort to develop emerging strategies to combat S. aureus, phage display is uniquely positioned to assist in this endeavor. Leveraging bacteriophages, phage display enables researchers to better understand interactions between proteins and their antagonists. In doing so, researchers have the capacity to design novel inhibitors, biosensors, disinfectants, and immune modulators that can target specific S. aureus strains. In this review, we highlight how phage display can be leveraged to design novel solutions to combat S. aureus. We further discuss existing uses of phage display as a detection, intervention, and prevention platform against S. aureus and provide outlooks on how this technology can be optimized for future applications.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".