Microdialysis hollow fiber as a macromolecule trap for on-line coupling of solid phase microextraction and capillary electrophoresis
Bibliographic record
Abstract
On-line coupling of solid phase microextraction (SPME) and capillary electrophoresis (CE) is highly desirable due to the apparent advantages of the two techniques particularly in the context of microanalysis. However, the hyphenation is a significant challenge, because of band broadening and analyte carryover caused by the slow kinetics of analyte desorption in liquid phase. A novel strategy was presented in this study to overcome these problems. Analytes desorbed from an SPME fiber, which was held by an adapter, were first transferred by electrophoretic migration into a short piece of microdialysis hollow fiber, which was located at the inlet of a CE system. Analytes with molecular weights greater than the molecular weight cut-off of the microdialysis material were trapped in the microdialysis hollow fiber due to the dialysis effect. Then, under another electric field with different electrode polarity, the analytes trapped in the microdialysis hollow fiber migrated into the separation capillary and were separated. In the coupling approach, the microdialysis hollow fiber functioned as a macromolecule trap and a sample pre-concentrator as well. Band broadening was eliminated because the initial sample volume was very small (at nL level). Meanwhile, analyte carryover was eliminated because the desorption time could be as long as needed. Coupling of SPME with CE including two modes, capillary zone electrophoresis (CZE) and capillary isoelectric focusing (CIEF), was successfully demonstrated with proteins as test analytes. High efficiency and high resolution were obtained. The detection limits with UV absorbance whole-column imaging detection were 3.0 x 10(-7) and 3.0 x 10(-8) M (S/N = 3) for beta-lactoglobulin A and ovalbumin, respectively.
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 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 | 0.000 |
| 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 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".