Acoustic coupling of transverse waves as a mechanism for the label-free detection of protein–small molecule interactions
Bibliographic record
Abstract
An on-line acoustic transverse wave device has been used to study the binding interactions of human serum albumin with the small molecule drug, warfarin. Four linking systems for the covalent attachment of the protein to the surface of the gold electrode of the sensor were employed, namely thioctic acid, cysteamine, an N-hydroxysuccinimide ester and 11-mercaptoundecanoic acid. All the attachment protocols involve the ability of thiols to form gold-sulfur bonds at the metal surface. The functional group present at the distal end of each thiol was chemically activated in order to facilitate covalent attachment of the protein. On-line sensor measurements of acoustic parameters show that the binding of warfarin to the protein can be detected, and depending on the linking monolayer used three of four possible combinations of changes in series resonance frequency and motional resistance are observed. Calculations of possible mass and thickness viscoelastic effects demonstrate that these conventional notions are invalid in terms of an explanation of the acoustic signals observed for the warfarin-protein interaction. The responses are ascribed to acoustic coupling phenomena.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".