Rapid Detection of Protein Kinase on Capacitive Sensing Platforms
Bibliographic record
Abstract
In this study, we developed a capacitive sensor for the one-step and label-free detection of protein kinase A (PKA) enzyme. Metal-insulator-semiconductor (MIS) and electrolyte-insulator-semiconductor (EIS) are a simple electronic transducer, which allows efficient detection of the target analyte. For this reason, we performed a comparative sensing of PKA on the MIS and EIS capacitive sensor. The PKA-specific aptamer was used for the one-step detection. For the immobilization of thiolated aptamer, the MIS sensor contained a thin gold layer, whereas the EIS sensor had a self-aligned monolayer of gold nanoparticles. The interaction of aptamer and PKA changed the charge and density of the sensor surface. The quantitative detection of PKA was performed by analyzing the capacitance-voltage curve after the aptamer-PKA interaction. The MIS and EIS sensor showed a detection limit of 5 U/mL and 1 U/mL, respectively, for the detection of PKA. This study suggests valuable sensing platforms for the rapid and sensitive biochemical diagnosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".