On-line coupling of high performance gel filtration chromatography with imaged capillary isoelectric focusing using a membrane interface
Bibliographic record
Abstract
A high performance liquid chromatography system, a sample preparation device, and an imaged capillary IEF (CIEF) instrument are integrated and multiplexed on-line. The system is equivalent to two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), by transferring the principle of 2-D separation to the capillary format. High performance liquid chromatography (HPLC) provides protein separation based on size using a gel filtration chromatography (GFC) column. Each eluted protein is sampled and directed to a novel microdialysis hollow fiber membrane device, where simultaneous desalting and carrier ampholyte mixing occurs. The sample is then driven to the separation column in an on-line fashion, where CIEF takes place. The fluidic technology used by our 2-D system leads to natural automation. The coupling of the two techniques is simple. This is attributed to high speed and efficiency of the sample preparation device that acts as an interface between the two systems, as well as the speed and simplicity of our whole column absorption imaged CIEF instrument. To demonstrate the feasibility of this approach, the separation of a mixture of two model proteins is studied. Sample preparation and CIEF were complete in just 4-5 min, for each of the eluted proteins. Total analysis time is about 24 min. Three-dimensional data representations are constructed. Challenges and methods to further improve our instrument are discussed, and the design of an improved horseshoe-shaped sample preparation sample loop membrane interface is presented and characterized.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".