Multiparameter antibiotic resistance detection based on hydrodynamic trapping of individual <i>E. coli</i>
Why this work is in the frame
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Bibliographic record
Abstract
There is an urgent need to develop novel methods for assessing the response of bacteria to antibiotics in a timely manner. Antibiotics are traditionally assessed via their effect on bacteria in a culture medium, which takes 24-48 h and exploits only a single parameter, i.e. growth. Here, we present a multiparameter approach at the single-cell level that takes approximately an hour from spiking the culture to correctly classify susceptible and resistant strains. By hydrodynamically trapping hundreds of bacteria, we simultaneously monitor the evolution of motility and morphology of individual bacteria upon drug administration. We show how this combined detection method provides insights into the activity of antimicrobials at the onset of their action which single parameter and traditional tests cannot offer. Our observations complement the current growth-based methods and highlight the need for future antimicrobial susceptibility tests to take multiple parameters into account.
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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) | 0.000 | 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) | 0.000 | 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