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Record W4404822470 · doi:10.1080/19420862.2024.2435476

Heavy chain-only antibodies with a stabilized human VH in transgenic chickens for therapeutic antibody discovery

2024· article· en· W4404822470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuemAbs · 2024
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsOmniActive Health Technologies (Canada)
Fundersnot available
KeywordsAntibodyEpitopeImmunogenicityHeavy chainSingle-domain antibodyImmunoglobulin light chainBiologyTransgeneAntigenImmune systemComputational biologyEx vivoGenetically modified mouseImmunologyIn vivoCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

Heavy chain-only antibodies have found many applications where conventional heavy-light heterodimeric antibodies are not favorable. Heavy chain-only antibodies with their single antigen-binding domain offer the advantage of a smaller size and higher stability relative to conventional antibodies, and thus, the potential for novel targeting modalities. Domain antibodies have commonly been sourced from camelids with ex-vivo humanization or transgenic rodents expressing heavy chains without light chains, but these host species are all mammalian, limiting their capacity to elicit robust immune responses to conserved mammalian targets. We have developed transgenic chickens expressing heavy chain-only antibodies with a human variable region to combine the superior target recognition advantages of a divergent, non-mammalian host with the ability to discover single-domain binders. These birds produce robust immune responses, consisting of antigen-specific antibodies targeting diverse epitopes with a range of affinities. Biophysical attributes are favorable, with good developability profiles and low predicted immunogenicity.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.694

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 head0.034
GPT teacher head0.368
Teacher spread0.334 · 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