Electrochemical Quartz Crystal Nanobalance to Detect Solvent Displacement by pH-Induced Conformational Changes of Proteins at Pt
Bibliographic record
Abstract
The electrochemical quartz crystal nanobalance (EQCN) techniques of simultaneous measurements of frequency and cyclic voltammetry (CV) were used to investigate protein adsorption behavior resulting from pH-induced conformational changes at the Pt electrode at 298 K. The adsorption behavior of holo- and apo-alpha-lactalbumin was studied in electrolyte solutions of pH < 2, 7.4, and 11. The EQCN frequency measurements did not directly monitor the mass of the adsorbed protein at anodic potentials, but instead, at a potential characteristic of the double layer for platinum, gave a measure of the extent of solvent displacement by the adsorbed protein (i.e., a "footprint"), which correlated well with known pH-induced conformational changes of the protein. Simultaneous CV charge transfer measurements provided information on the number of layers of protein adsorbed to the surface. This ability of the EQCN to detect solvent displacement by protein adsorption is potentially useful for biosensors to detect and to monitor protein conformational changes in the bulk and during the adsorption process. The Langmuir adsorption isotherm provided the Gibbs energy of adsorption, DeltaG(ADS), and showed excellent agreement between the CV and EQCN frequency measurements.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".