Electrophoretic Deposition Interferometric Scattering Mass Photometry
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Bibliographic record
Abstract
Interferometric scattering microscopy (iSCAT) has rapidly developed as a quantitative tool for the label-free detection of single macromolecules and nanoparticles. In practice, this measurement records the interferometric scattering signal of individual nanoparticles in solution as they land and stick on a coverslip, exhibiting an intensity that varies linearly with particle volume and an adsorption rate that reflects the solution-phase transport kinetics of the system. Together, such measurements provide a multidimensional gauge of the particle size and concentration in solution over time. However, the landing kinetics of particles in solution also manifest a measurement frequency limitation imposed by the slow long-range mobility of particle diffusion to the measurement interface. Here we introduce an effective means to overcome the inherent diffusion-controlled sampling limitation of spontaneous mass photometry. We term this methodology electrophoretic deposition interferometric scattering microscopy (EPD-iSCAT). This approach uses a coverslip supporting a conductive thin film of indium tin oxide (ITO). Charging this ITO film to a potential of around +1 V electrophoretically draws charged nanoparticles from solution and binds them in the focal plane of the microscope. Regulating this potential offers a direct means of controlling particle deposition. Thus, we find for a 0.1 nM solution of 50 nm polystyrene nanoparticles that the application of +1 V to an EPD-iSCAT coverslip assembly drives an electrophoretic deposition rate constant of 1.7 s –1 μm –2 nM –1 . Removal of the potential causes deposition to cease. This user control of EPD-iSCAT affords a means to apply single-molecule mass photometry to monitor long-term changes in solution, owing to slow kinetic processes. In contrast with conventional coverslips chemically derivatized with charged thin films, EPD-iSCAT maintains a deposition rate that varies linearly with the bulk concentration.
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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 it