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Record W4200330805 · doi:10.1101/2021.12.21.473679

SARS-CoV-2 Omicron Spike recognition by plasma from individuals receiving BNT162b2 mRNA vaccination with a 16-weeks interval between doses

2021· preprint· en· W4200330805 on OpenAlexafffund
Debashree Chatterjee, Alexandra Tauzin, Lorie Marchitto, Shang Yu Gong, Marianne Boutin, Catherine Bourassa, Guillaume Beaudoin-Bussières, Yuxia Bo, Shilei Ding, Annemarie Laumaea, Dani Vézina, Josée Perreault, Laurie Gokool, Chantal Morrisseau, Pascale Arlotto, Éric Fournier, Aurélie Guilbault, Benjamin Delisle, Inès Levade, Guillaume Goyette, Gabrielle Gendron‐Lepage, Halima Medjahed, Gaston De Serres, Cécile Tremblay, Valérie Martel‐Laferrière, Daniel E. Kaufmann, Renée Bazin, Jérémie Prévost, Sandrine Moreira, Jonathan Richard, Marceline Côté, Andrés Finzi

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of OttawaInstitut National de Santé Publique du QuébecHéma-QuébecUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMitacsFondation du CHUMUniversité de MontréalPfizer
KeywordsSpike (software development)Interval (graph theory)Coronavirus disease 2019 (COVID-19)VaccinationMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)RegimenCohortVirologyImmunologyInternal medicineComputer scienceMathematicsCombinatoricsDisease

Abstract

fetched live from OpenAlex

SUMMARY Continuous emergence of SARS-CoV-2 variants of concern (VOC) is fueling the COVID-19 pandemic. Omicron (B.1.1.529), is rapidly spreading worldwide. The large number of mutations in its Spike raised concerns about a major antigenic drift that could significantly decrease vaccine efficacy and infection-induced immunity. A long interval between BNT162b2 mRNA doses was shown to elicit antibodies that efficiently recognize Spikes from different VOCs. Here we evaluated the recognition of Omicron Spike by plasma from a cohort of SARS-CoV-2 naïve and previously-infected individuals that received their BNT162b2 mRNA vaccine 16-weeks apart. Omicron Spike was recognized less efficiently than D614G, Alpha, Beta, Gamma and Delta Spikes. We compared to plasma activity from participants receiving a short (4-weeks) interval regimen. Plasma from individuals of the long interval cohort recognized and neutralized better the Omicron Spike compared to those that received a short interval. Whether this difference confers any clinical benefit against Omicron remains unknown.

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 score0.003
Threshold uncertainty score0.011

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)0.0030.001

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 head0.039
GPT teacher head0.290
Teacher spread0.251 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

Explore more

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