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Record W1974900926 · doi:10.1039/b607359j

Lectin affinity chromatography using porous polymer monolith assisted nanoelectrospray MS/MS

2006· article· en· W1974900926 on OpenAlexafffund
Mohamed Bedair, Richard D. Oleschuk

Bibliographic record

VenueThe Analyst · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaGenome Prairie
KeywordsChemistryMonolithChromatographyGlycidyl methacrylatePolymerMethacrylatePolymerizationElectrosprayMass spectrometryOrganic chemistry

Abstract

fetched live from OpenAlex

An affinity porous polymer monolith is utilized as a nanoelectrospray emitter as well as an online affinity capture column for the preconcentration of glycans. Porous polymer monolith (PPM) assisted electrospray provides a facile methodology for coupling microfluidics to mass spectrometry that is sheathless and with zero dead volume. Affinity PPM was photopolymerized using glycidyl methacrylate/ethylene dimethacrylate utilizing different porogenic solvents based on aliphatic alcohols to provide PPMs with a variety of pore sizes. The use of longer alkyl chain alcohols decreased the pore size of the formed PPM as indicated by the higher flow back pressure generated. The effect of the pore size on the stability of the electrospray was tested showing higher stability of the TIC with lower pore size. A lectin, namely Concanavaline A, was immobilized on glycidyl methacrylate/ethylene dimethacrylate using the Schiff base method to provide an affinity monolith for high mannose glycans. The amount of the lectin immobilized was studied as a function of the porogenic solvent used in the polymerization. The glycopeptides of the glycoprotein Ribonuclease B was preconcentrated on the affinity PPM sprayer and detected by tandem MS.

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 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 score0.049
Threshold uncertainty score0.672

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations35
Published2006
Admission routes2
Has abstractyes

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