Novel resonant-frequency sensor to detect the kinetics of protein adsorption
Bibliographic record
Abstract
Proteins prefer interfaces, and in aqueous solutions they rapidly adsorb to available solid–liquid interfaces. The adsorption process often involves a change in protein conformation at the surface that can result in functional inactivation of the protein. These changes in protein conformation, which are thought to lead to the formation of an entangled gel-like layer of denatured protein, are responsible for a number of deliterious processes, including biofouling on contact lenses and medical implants. The adsorption process is generally irreversible; dilution of protein in the solution phase does not result in protein desorption from the solid. Presumably, this is due to the effects of the protein denaturation and entanglement process on the rate constant for desorption. Nonspecific protein adsorption to solid–liquid interfaces is, therefore, a kinetically controlled process. Hence, measuring and understanding the kinetics of protein adsorption to solid surfaces, including the kinetics of protein conformational changes, is of considerable interest. We have developed a sensor that responds to protein adsorption kinetics and also, we believe, is sensitive to protein conformational changes during adsorption. The device is operated by monitoring the change in resonant frequency of an elastomeric film (25 μm thick), as an aqueous protein solution is exposed to the surface. Since the mass of a monolayer of the protein or other adsorbent is an extremely small fraction of the mass of the film, the observed change in resonant frequency is due almost entirely to changes in the surface tension of the film. Upon exposing the elastomeric film to a protein solution, we observe a continuing change in resonant frequency for more than 24 h, which is well beyond the time it would take for the population of proteins on the surface to equilibrate under diffusion-limited kinetics. This prolonged response is likely due to the surface energy changes of the sensor as the adsorbed protein molecules change their conformation. We present a description of the basic operation of this sensor as well as some examples of its response to bulk protein and surfactant concentrations.
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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 | 0.001 | 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) | 0.001 | 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 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".