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Record W1963577094 · doi:10.1021/pr700677u

Rapid and Effective Focusing in a Carrier Ampholyte Solution Isoelectric Focusing System: A Proteome Prefractionation Tool

2008· article· en· W1963577094 on OpenAlexaff
John C. Tran, Alan A. Doucette

Bibliographic record

VenueJournal of Proteome Research · 2008
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIsoelectric focusingProteomeChromatographyChemistryProtein precipitationMass spectrometryBiochemistry

Abstract

fetched live from OpenAlex

Preparative (solution) isoelectric focusing (sIEF) is a proven technique for proteome prefractionation, but carries limitations which include the risk of protein loss from isoelectric precipitation, poor focusing, and excessively long separation times. This report describes a simple yet effective method to achieve rapid focusing (as fast as 1 h) and maximize protein recovery using a carrier ampholyte sIEF system. Cathodic drift was not present over the time course of the experiment using our eight-chamber device, and we demonstrate the effectiveness of this device for focusing proteome mixtures. We also discuss an MS-compatible acidic wash protocol, which is shown to enhance the recovery of proteins following sIEF, thus, improving detection by LC-MS/MS. These approaches overcome significant shortcomings of the technique, enabling effective prefractionation prior to MS analysis.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.019
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.343
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations41
Published2008
Admission routes1
Has abstractyes

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