Molecular Identification through Membrane Engineering as a Revolutionary Concept for the Construction of Cell Sensors with Customized Target Recognition Properties: the Example of Superoxide Detection
Why this work is in the frame
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Bibliographic record
Abstract
Membrane-engineering is a generic methodology for increasing the selectivity of a cell biosensor against a target molecule, by electroinserting target-specific receptor molecules on the cell surface. We have previously reported the construction of an ultra-sensitive superoxide anion (O 2 •− ) sensor based on immobilized cells, which have been membrane-engineered with superoxide dismutase (SOD). In the present study, we provide evidence that superoxide dismutation triggered changes to the membrane potential of membrane-engineered fibroblast cells, as confirmed by electrophysiological and fluorescence assays. In addition, by conducting selective inhibition assays, we show that electroinserted SOD molecules retained their characteristic catalytic properties. We also investigated the effect of the concentration of electroinserted SOD molecules. Finally, we increased the sensitivity of the sensor by hundredfold to a detection limit of 1 pM O 2 •− by changing the intensity of the electrical field during electroinsertion and the concentration of immobilized cells on the performance of the biosensor.
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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) | 0.000 | 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 it