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Record W1434077798 · doi:10.1093/jaoac/84.1.143

Polyclonal-Based ELISA for the Identification of Cyclohexanedione Analogs that Inhibit Maize Acetyl Coenzyme-A Carboxylase

2001· article· en· W1434077798 on OpenAlexaff
Steven R. Webb, J. Christopher Hall

Bibliographic record

VenueJournal of AOAC International · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPolyclonal antibodiesAcetyl-CoA carboxylaseBiochemistryChemistryPyruvate carboxylaseIdentification (biology)Coenzyme AEnzymeBiologyAntibodyBotanyImmunology

Abstract

fetched live from OpenAlex

Cyclohexanedione herbicides inhibit monocotyledonous acetyl coenzyme-A carboxylase (ACCase; E.C. 6.4.1.2.), which catalyzes the first committed step in fatty acid biosynthesis. Although the target site has been identified, little is known about the mechanisms involved in herbicide binding. An immunological study was undertaken to create a model to better characterize the herbicide-enzyme interaction. Cyclohexanedione-specific antiserum was raised in New Zealand white rabbits by immunizing them with a cyclohexanedione analog-bovine serum albumin conjugate. Two indirect enzyme-linked immunosorbent assays (ELISA) were developed using 2 different cyclohexanedione analogs conjugated to ovalbumin as coating conjugates. Nineteen cyclohexanedione analogs, 13 active ACCase inhibitors, and 6 inactive analogs were tested for their ability to compete with both coating conjugates for antiserum binding. All active ACCase inhibitors were observed to compete with both coating conjugates, whereas all inactive analogs failed to compete with at least one coating conjugate. On the basis of these results, the immunological model could be used to distinguish all active ACCase inhibitors from inactive analogs using the 2 ELISAs sequentially.

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 score0.065
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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

Citations3
Published2001
Admission routes1
Has abstractyes

Explore more

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