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Record W3022906021 · doi:10.1126/sciimmunol.aba6466

A respiratory syncytial virus (RSV) F protein nanoparticle vaccine focuses antibody responses to a conserved neutralization domain

2020· article· en· W3022906021 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

VenueScience Immunology · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsWillow Biosciences (Canada)
FundersSanofi Genzyme
KeywordsNeutralizationVirologyAntibodyEpitopeGlycanVirusBiologyNeutralizing antibodyMicrobiologyGlycoproteinImmunologyMolecular biology

Abstract

fetched live from OpenAlex

A stabilized form of the respiratory syncytial virus (RSV) fusion (F) protein has been explored as a vaccine to prevent viral infection because it presents several potent neutralizing epitopes. Here, we used a structure-based rational design to optimize antigen presentation and focus antibody (Ab) responses to key epitopes on the pre-fusion (pre-F) protein. This protein was fused to ferritin nanoparticles (pre-F-NP) and modified with glycans to mask nonneutralizing or poorly neutralizing epitopes to further focus the Ab response. The multimeric pre-F-NP elicited durable pre-F-specific Abs in nonhuman primates (NHPs) after >150 days and elicited potent neutralizing Ab (NAb) responses in mice and NHPs in vivo, as well as in human cells evaluated in the in vitro MIMIC system. This optimized pre-F-NP stimulated a more potent Ab response than a representative pre-F trimer, DS-Cav1. Collectively, this pre-F vaccine increased the generation of NAbs targeting the desired pre-F conformation, an attribute that facilitates the development of an effective RSV vaccine.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.087
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.062
GPT teacher head0.388
Teacher spread0.326 · 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