Optical Trapping and Fast Discrimination of Label‐Free Bacteriophages at the Single Virion Level
Bibliographic record
Abstract
There is a recent resurgence of interest in phage therapy (the therapeutic use of bacterial viruses) as an approach to eliminating difficult-to-treat infections. However, existing approaches for therapeutic phage selection and virulence testing are time-consuming, host-dependent, and facing reproducibility issues. Here, this study presents an innovative approach wherein integrated resonant photonic crystal (PhC) cavities in silicon are used as optical nanotweezers for probing and manipulating single bacteria and single virions with low optical power. This study demonstrates that these nanocavities differentiate between a bacterium and a phage without labeling or specific surface bioreceptors. Furthermore, by tailoring the spatial extent of the resonant optical mode in the low-index medium, phage distinction across phenotypically distinct phage families is demonstrated. The work paves the road to the implementation of optical nanotweezers in phage therapy protocols.
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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) | 0.000 | 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".