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Record W4282041571 · doi:10.1101/2022.05.26.493643

Peptide and protein alphavirus antigens for broad spectrum vaccine design

2022· preprint· en· W4282041571 on OpenAlexaff
Catherine H. Schein, Grace Rafael, Wendy S. Baker, Elizabeth S. Anaya, Jürgen Schmidt, Scott C. Weaver, Surendra S. Negi, Werner Braun

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsInstitute of Infection and Immunity
FundersLos Alamos National LaboratoryLaboratory Directed Research and DevelopmentNational Institutes of Health
KeywordsAlphavirusVirologyVenezuelan equine encephalitis virusChikungunyaBiologyTogaviridaeAntibodyAlphavirus infectionAntigenVirusSindbis virusRNAGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Vaccines based on proteins and peptides may be safer and more broad-spectrum than other approaches Physicochemical property consensus (PCP con ) alphavirus antigens from the B-domain of the E2 envelope protein were designed and synthesized recombinantly. Those based on individual species (eastern or Venezuelan equine encephalitis (EEEVcon, VEEVcon), or chikungunya (CHIKVcon) viruses generated species-specific antibodies. Peptides designed to surface exposed areas of the E2-A-domain were added to the inocula to provide neutralizing antibodies against CHIKV. EVC con , based on the three different alphavirus species, combined with E2-A-domain peptides from AllAV, a PCPcon of 24 diverse alphavirus, generated broad spectrum antibodies. The abs in the sera bound and neutralized diverse alphaviruses with less than 35% amino acid identity to each other. These included VEEV and its relative Mucambo virus, EEEV and the related Madariaga virus, and CHIKV strain 181/25. Further understanding of the role of coordinated mutations in the envelope proteins may yield a single, protein and peptide vaccine against all alphaviruses.

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 score0.007

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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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