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Record W2302583067 · doi:10.1126/science.aad9195

HIV-1 broadly neutralizing antibody precursor B cells revealed by germline-targeting immunogen

2016· article· en· W2302583067 on OpenAlexaff
Joseph G. Jardine, Daniel W. Kulp, Colin Havenar‐Daughton, Anita Sarkar, Bryan Briney, Devin Sok, Fabian Sesterhenn, June Ereño‐Orbea, Oleksandr Kalyuzhniy, Isaiah Deresa, Xiaozhen Hu, Skye Spencer, Meaghan Jones, Erik Georgeson, Yumiko Adachi, Michael Kubitz, Allan C. deCamp, Jean‐Philippe Julien, Ian A. Wilson, Dennis R. Burton, Shane Crotty, William R. Schief

Bibliographic record

VenueScience · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersSLAC National Accelerator LaboratoryBiological and Environmental ResearchNational Institute of Allergy and Infectious DiseasesNational Center for Research ResourcesNational Institute of General Medical SciencesInternational AIDS Vaccine InitiativeNational Institutes of HealthOffice of ScienceHoward Hughes Medical InstituteHelen Hay Whitney FoundationU.S. Department of Energy
KeywordsImmunogenGermlineVirologyHIV vaccineAntibodyBiologyHuman immunodeficiency virus (HIV)ImmunologyMonoclonal antibodyGeneticsGene

Abstract

fetched live from OpenAlex

Induction of broadly neutralizing antibodies (bnAbs) is a major HIV vaccine goal. Germline-targeting immunogens aim to initiate bnAb induction by activating bnAb germline precursor B cells. Critical unmet challenges are to determine whether bnAb precursor naïve B cells bind germline-targeting immunogens and occur at sufficient frequency in humans for reliable vaccine responses. Using deep mutational scanning and multitarget optimization, we developed a germline-targeting immunogen (eOD-GT8) for diverse VRC01-class bnAbs. We then used the immunogen to isolate VRC01-class precursor naïve B cells from HIV-uninfected donors. Frequencies of true VRC01-class precursors, their structures, and their eOD-GT8 affinities support this immunogen as a candidate human vaccine prime. These methods could be applied to germline targeting for other classes of HIV bnAbs and for Abs to other pathogens.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.283
Teacher spread0.273 · 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

Citations483
Published2016
Admission routes1
Has abstractyes

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