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Record W1986917613 · doi:10.1021/ac0301548

On-Column Sample Enrichment for Capillary Electrophoresis Sheathless Electrospray Ionization Mass Spectrometry:  Evaluation for Peptide Analysis and Protein Identification

2003· article· en· W1986917613 on OpenAlexfundno aff
George M. Janini, Ming Zhou, Li‐Rong Yu, Josip Blonder, Michelle Gignac, Thomas P. Conrads, Haleem J. Issaq, Timothy D. Veenstra

Bibliographic record

VenueAnalytical Chemistry · 2003
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institute for Theoretical Astrophysics
KeywordsChemistryChromatographyCapillary electrophoresis–mass spectrometryCapillary electrophoresisAnalyteElectrospray ionizationMass spectrometryDetection limitElectrosprayTandem mass spectrometryCapillary electrochromatographyAnalytical Chemistry (journal)Sample preparationCapillary actionElectrophoresis

Abstract

fetched live from OpenAlex

Although several designs have been advanced for coupling sample enrichment devices to a sheathless electrospray ionization-mass spectrometry (MS) interface on a capillary electrophoresis (CE) column, most of these approaches suffer from difficulties in fabrication, and the CE separation efficiency is degraded as a result of the presence of coupling sleeves. We have developed a design that offers significant improvements in terms of ease of fabrication, durability, and maintenance of the integrity of the CE-separated analyte zones. Capillaries with different inside and outside diameters were evaluated to optimize the performance of the CE-MS system, resulting in a mass limit of detection of 500 amol for tandem MS analysis of a standard peptide using a 20-microm-i.d. capillary. The improved design incorporates an efficient method to preconcentrate a sample directly within the CE capillary followed by its electrophoretic separation and detection using a true zero dead-volume sheathless CE-MS interface. Testing of this novel CE-MS system showed its ability to characterize proteomic samples such as protein digests, in-gel-digested proteins, and hydrophobic peptides as well as to quantitate ICAT-labeled peptides.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.618
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.012
GPT teacher head0.280
Teacher spread0.267 · 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

Citations58
Published2003
Admission routes1
Has abstractyes

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