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Affinity protection chromatography for efficient labeling of antibodies for use in affinity capillary electrophoresis

2002· article· en· W2019512659 on OpenAlexaff
Said Attiya, Terrina Dickinson-Laing, John Cesarz, Raymond D. Giese, William Lee, David Mah, D. Jed Harrison

Bibliographic record

VenueElectrophoresis · 2002
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryChromatographyAffinity chromatographyMonoclonal antibodyCyanogen bromideCapillary electrophoresisPolyclonal antibodiesOvalbuminImmunoassayDetection limitAntibodyEnzymeBiochemistryAntigenPeptide sequence

Abstract

fetched live from OpenAlex

Capillary electrophoresis immunoassay (CEIA) is shown to be substantially more sensitive to the antibody (Ab) reagent quality than are immunosorbent methods such as enzyme-linked immunosorbent assays (ELISA). Cyanine 5 (Cy5)-labeled monoclonal anti-ovalbumin (mAb*) was inactive for CEIA of ovalbumin (Ov), yet was functional in ELISA for Ov. ELISA showed the mAb* was at least ten times less active, accounting for the poor CEIA performance. Labeled polyclonal Ab was inactive for a dye to protein ratio greater than 1.6. An affinity protection chromatography procedure (APC) was developed for Ab labeling, which avoided degradation of the Ab binding site. Ov was covalently bound to cyanogen bromide activated cellulose gel in a column, and used to capture the Ab. The coupling efficiency for Ov to the gel was 74-97%, Ab could then be bound with 95-100% efficiency, and Ab* was recovered in 50% yield following labeling on the column. This procedure was performed successfully in three different laboratories, indicating the robustness of the optimized APC synthetic method. No inactive Ab* could be detected in the APC product. The CEIA detection limit for ovalbumin using APC labeled mAb was 173 nM, when [Ab*] was fixed at 163 nM. The association constants of mAb and mAb* were determined by CEIA.

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 score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.211
Teacher spread0.190 · 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

Citations18
Published2002
Admission routes1
Has abstractyes

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