Rapid electrochemical phenotypic profiling of antibiotic-resistant bacteria
Bibliographic record
Abstract
Rapid phenotyping of bacteria to identify drug-resistant strains is an important capability for the treatment and management of infectious disease. At present, the rapid determination of antibiotic susceptibility is hindered by the requirement that, in existing devices, bacteria must be pre-cultured for 2-3 days to reach detectable levels. Here we report a novel electrochemical approach that achieves rapid readout of the antibiotic susceptibility profile of a bacterial infection within one hour. The electrochemical reduction of a redox-active molecule is monitored that reports on levels of metabolically-active bacteria. Bacteria are captured in miniaturized wells, incubated with antimicrobials and monitored for resistance. This electrochemical phenotyping approach is effective with clinically-relevant levels of bacteria, and provides results comparable to culture-based analysis. Results, however, are delivered on a much faster timescale, with resistance profiles available after a one hour incubation period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".