Microelectronic-sensing assay to detect presence of Verotoxins in human faecal samples
Bibliographic record
Abstract
AIMS: To develop a novel Vero cell assay that implements a real-time cell electronic sensing (RT-CES) system for the determination of the presence of verotoxin-producing Escherichia coli (VTEC). The assay overcomes the major drawbacks in conventional Vero cell assay, for example, labour-intensive and time-consuming. METHODS AND RESULTS: Cells were grown onto the surfaces of microelectronic sensors that are integrated into the bottom surfaces of the microtiter plate. Cellular viability was monitored in real-time and quantified based on changes in the sensor's electrical impedance. For cell viability measurement, the data generated on the RT-CES system correlated well with those obtained by the Vero cell assay for Verotoxins. To assess cytotoxicity, test cells growing on microelectronic sensors were treated with either supernatant from pure cultures, or stool samples. The specific neutralizing antibodies of VT1 and VT2 were used to identify specific toxins in the samples. CONCLUSIONS: The RT-CES assay provides a sensitive measurement comparable to conventional crystal violet assay. The assay has been successfully and specifically used to identify VTEC in human faecal samples. SIGNIFICANCE AND IMPACT OF THE STUDY: The RT-CES assay significantly shortens the testing time from 48 to 72 h required by the crystal violet assay to only 15 h with automated operation.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".