Mitigating dithiothreitol interference to gold/thiol interface in electrochemical detection of cathepsin B activity toward multiplex protease analysis
Bibliographic record
Abstract
Proteases are overexpressed at various stages of conditions such as cancers and thus can serve as biomarkers for disease diagnosis. Electrochemical techniques to detect the activity of extracellular proteases have gained attraction due to their multiplexing capability. Here we employ an electrochemical approach based on a 3 × 3 gold (Au) microelectrode array (MEA) functionalized with (2-aminoethyl)ferrocene (AEF) tagged specific peptide substrates to monitor cathepsin B (CB) protease activity. Cleavage of these peptide substrates by proteases leads to an exponential decay in the alternating current voltammetry (ACV) signal. The protease activity is represented by the inverse of the decay time constant (1/τ), which is equal to (k cat /K M )[CB] based on the heterogeneous Michaelis-Menton model. However, the thiol/Au chemisorption linking AEF-peptide to gold electrodes is susceptible to interference by the protease activation reagent dithiothreitol (DTT), causing the peptides to desorb from the Au surface during continuous ACV measurement. This induces a false signal decay, masking the protease activity and reducing the sensor sensitivity. To address this, DTT is removed after activating CB using centrifugal filtration while EDTA is incorporated to maintain the enzyme activity . This allows accurate CB proteolysis kinetics and clarifies the roles of EDTA and DTT in activation. The intrinsic substrate-dependent cleavage by CB to three different peptide substrates has been demonstrated with the MEA chip, showcasing the potential for rapid activity profiling of multiple proteases. The study highlights the importance of understanding the interference of active bioreagents to the thiol/Au interface in broad redox-tagged electrochemical biosensors.
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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 | 0.001 |
| 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".