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Record W2004921017 · doi:10.1021/ac049517+

Electrochemical Quartz Crystal Nanobalance to Detect Solvent Displacement by pH-Induced Conformational Changes of Proteins at Pt

2004· article· en· W2004921017 on OpenAlexaff
Nicholas P. Cosman, Sharon G. Roscoe

Bibliographic record

VenueAnalytical Chemistry · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsAcadia University
Fundersnot available
KeywordsChemistryAdsorptionCyclic voltammetrySolventProtein adsorptionElectrochemistryGibbs free energyAnalytical Chemistry (journal)Quartz crystal microbalanceElectrodeInorganic chemistryPhysical chemistryChromatographyOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.258
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2004
Admission routes1
Has abstractyes

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