Pressure‐assisted capillary electrophoresis frontal analysis for faster binding constant determination
Bibliographic record
Abstract
Abstract Adding external pressure during the process of capillary electrophoresis usually add to the band broadening, especially if the pressure induced flow is significant. The resolution is normally negatively affected in pressure‐assisted capillary electrophoresis (PACE). Frontal analysis (FA), however, can potentially benefit from using an external pressure while avoiding the drawbacks in other modes of CE. In this work, possible impact from the external pressure was simulated by COMSOL Multiphysics®. Under a typical CE‐FA set‐up, it was found that the detected concentrations of analyte will not be significantly affected by an external pressure less than 5 psi. Besides, the measured ligand concentration in PACE‐FA was also not affected by common variables (molecular diffusion coefficient (10−8 to 10−11 m2/s), capillary length etc). To provide an experimental proof, PACE‐FA is used to study the binding interactions between hydroxypropyl β‐cyclodextrin (HP‐β‐CD) and small ligand molecules. Taking the HP‐β‐CD /benzoate pair as an example, the binding constants determined by CE‐FA (18.3 ± 0.8 M−1) and PACE‐FA (16.5 ± 0.5 M−1) are found to be similar. Based on the experimental results, it is concluded that PACE‐FA can reduce the time of binding analysis while maintaining the accuracy of the 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".