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On-line coupling of high performance gel filtration chromatography with imaged capillary isoelectric focusing using a membrane interface

2000· article· en· W1980824834 on OpenAlexaff
Charalambos Tragas, Janusz Pawliszyn

Bibliographic record

VenueElectrophoresis · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChromatographyElutionIsoelectric focusingChemistryIsotachophoresisSize-exclusion chromatographyCapillary actionMembraneFiltration (mathematics)Analytical Chemistry (journal)Sample preparationMaterials science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.197
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations44
Published2000
Admission routes1
Has abstractyes

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