Electrochemical Detection of Tobramycin Resistance in Escherichia Coli
Bibliographic record
Abstract
The development of techniques to detect the presence of resistance in pathogens are urgently needed to face the deadly spread of multi-drug-resistant bacteria. The present work presents the electroanalytical quantification of tobramycin (TOB) retention in susceptible and resistant bacterial strains of Escherichia coli. The electrochemical characterization of TOB demonstrates the suitability of electrochemistry for drug detection. Differential pulse voltammetry (DPV) parameters were optimized by full factor experimental designs, which increased two-times the electrochemical current response, improving the overall sensitivity of the method. The developed assay was able to differentiate between resistant and susceptible E. coli strains within 15 min. The demonstrated methodology is expected to be applicable to both drug efflux-mediated and drug uptake inhibition-mediated resistant bacteria. Because these two mechanisms represent the most predominant reasons for drug resistance in bacteria, the reported method has a strong potential to be a reliable, fast, and cost-efficient alternative for antibiotic resistance detection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".