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Record W4378611084 · doi:10.1101/2023.05.27.542563

Sequential Switching Through IgG1 is Redundant for Allergic Reactivity and Memory to Allergens

2023· preprint· en· W4378611084 on OpenAlexafffund
Joshua F. E. Koenig, Adam K. Wade‐Vallance, Rodrigo Jiménez‐Saiz, Kelly Bruton, Siyon Gadkar, Emily Grydziuszko, Tina D. Walker, Melissa E. Gordon, Susan Waserman, Manel Jordana

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersUniversity of Illinois at Urbana-ChampaignMcMaster University
KeywordsImmunoglobulin EImmunoglobulin class switchingImmunologyAllergenIsotypeAntibodySensitizationAllergyBiologyB cellMonoclonal antibody

Abstract

fetched live from OpenAlex

Abstract Allergic reactions to foods are driven by allergen-binding immunoglobulin (Ig)E antibodies. IgE- expressing cells can be generated through a sequential class switching pathway where activated B cells first switch to an intermediary isotype, most frequently IgG1, and then to IgE. It has been proposed that sequential class switch recombination is important in generating high affinity IgE, augmenting anaphylactic reactions, and in holding the memory of IgE responses. Here, we observed surprising redundancy of sequential switching through IgG1 for the functional affinity of the IgE repertoire against multiple food allergens as well as for the ability of IgE to elicit anaphylaxis. We further found that sequential switching via IgG1 was irrelevant for allergic memory. These results indicate that allergen-specific IgG1 B cells are redundant in sensitization, anaphylaxis, and food allergy persistence, thereby implicating other switching pathways as important considerations in the development of therapeutics for allergic diseases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.277
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicAllergic Rhinitis and SensitizationFrench-language works237,207