Emerging Technologies for the Electrochemical Detection of Bacteria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Infections are a huge economic liability to the health care system, although real-time detection can allow early treatment protocols to avoid some of this cost and patient morbidity and mortality. Pseudomonas aeruginosa (PA) is a drug-resistant gram-negative bacterium found ubiquitously in clinical settings, accounting for up to 27% of hospital acquired infections. PA secretes a vast array of molecules, ranging from secondary metabolites to quorum sensing molecules, of which many can be exploited to monitor bacterial presence. In addition to electrochemical immunoassays to sense bacteria via antigen-antibody interactions, PA pertains a distinct redox-active virulence factor called pyocyanin (PYO), allowing a direct electrochemical detection of the bacteria. There has been a surge of publications relating to the electrochemical tracing of PA via a myriad of novel biosensing techniques, materials, and methodologies. In addition to indirect methods, research approaches where PYO has been sensitively detected using surface modified electrodes are reviewed and compared with conventional PA-sensing methodologies. This review aims at presenting indirect and direct electrochemical methods currently developed using various surface modified electrodes, materials, and electrochemical configurations on their electrocatalytic effects on sensing of PA and in particular PYO.
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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) | 0.001 | 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 | 0.001 | 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 it