Real-Time Ultralow Bacterial Detection With A Gap-Method Microcantilever Biosensor
Bibliographic record
Abstract
Detecting ultralow concentrations of pathogenic bacteria is important for public health, environmental monitoring, and therapeutic research. This study presents the development and testing of a microcantilever biosensor based on the gap-method for the detection of E. coli and P. aeruginosa bacteria in water. The biosensor utilizes dielectrophoresis (DEP) force to attract bacteria to the gap area for real-time detection of extremely low bacteria concentrations (10 cells/mL) within a 7-min timeframe. This design demonstrates excellent performance with a low limit of detection (LoD) (< 10 cells/mL), high sensitivity (minimum sensitivity of 2.59 pg/Hz), and a high signal-to-noise ratio (SNR) (minimum SNR of 23.38). In addition, the surface of the biosensor was functionalized with pyoverdine (PVD), a siderophore of pseudomonas bacteria. The test results show that the surface functionalization was effective and that the frequency shift of the functionalized microcantilever was much higher when testing P. aeruginosa compared to the testing with E. coli bacteria.
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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 | 0.000 | 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) | 0.001 | 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; both teacher heads agree on what is shown here.
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".