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Record W4414305767 · doi:10.1021/acs.jafc.5c10372

Phenylglyoxal-induced Ana o 3 Modification Reduces Antibody Binding with Minimal Alteration in Protein Structure

2025· article· en· W4414305767 on OpenAlexaff
C. Nacaya Brown, Tien Thuy Vuong, Austin T. Weigle, Yu‐Jou Chou, Qinchun Rao, Christopher C. Ebmeier, Rebecca A. Dupre, Stephen M. Boué, Brennan Smith, Christopher P. Mattison

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsIONICS Mass Spectrometry (Canada)
FundersOak Ridge Institute for Science and EducationU.S. Department of EnergyMississippi State UniversityNational Institute of Food and AgricultureAgricultural Research ServiceOak Ridge Associated UniversitiesU.S. Department of Agriculture
KeywordsAllergenChemical modificationAntibodyFood allergensArginineMass spectrometryProtein structureTandem mass spectrometry

Abstract

fetched live from OpenAlex

The nutritional benefits of nut consumption are complicated by the presence of allergens. Food processing techniques can modify the food protein properties by altering their biophysical characteristics and allergen activity. This study examines the phenylglyoxal-based chemical modification of the cashew nut allergen Ana o 3. Immunoassays with multiple antibodies demonstrate reduced recognition of phenylglyoxal-modified Ana o 3. Mass spectrometry identified multiple Ana o 3 modification sites, including arginine 41, 54, 85, and 111. Circular dichroism, biochemical assays, and molecular simulation indicate that the modifications resulted in minimal protein structure alteration. The research presented here provides insight into Ana o 3 surface chemistry and structure, and it could be applied in the design of alternative forms of immunotherapy to treat cashew nuts and other food allergies.

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 score0.014
Threshold uncertainty score0.262

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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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