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Record W4386859224 · doi:10.1016/j.isci.2023.107959

Third COVID-19 vaccine dose boosts antibody function in Rwandans with high HIV viral load

2023· article· en· W4386859224 on OpenAlexafffund
Cynthia L. Swan, Valentine Dushimiyimana, Pacifique Ndishimye, Rachelle Buchanan, Anthony Yourkowski, Sage Semafara, Sabin Nsanzimana, Magen E. Francis, Brittany Thivierge, J. Lew, Antonio Facciuolo, Volker Gerdts, Darryl Falzarano, Calvin Sjaarda, David J. Kelvin, Léopold Bitunguhari, Alyson A. Kelvin

Bibliographic record

VenueiScience · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsQueen's UniversityDalhousie UniversityUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchCenters for Disease Control and PreventionGovernment of SaskatchewanCanada Foundation for Innovation
KeywordsVirologyAntibodyMedicineVaccinationNeutralizing antibodyViral loadCoronavirusVirusImmunologyCoronavirus disease 2019 (COVID-19)Antibody titerTiterHIV vaccineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseInfectious disease (medical specialty)Internal medicineVaccine trial

Abstract

fetched live from OpenAlex

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) causing COVID-19 (coronavirus disease 2019) poses a greater health risk to immunocompromized individuals including people living with HIV (PLWH). However, most studies on PLWH have been conducted in higher-income countries. We investigated the post-vaccination antibody responses of PLWH in Rwanda by collecting peripheral blood from participants after receiving a second or third COVID-19 vaccine. Virus-binding antibodies as well as antibody neutralization ability against all major SARS-CoV-2 variants of concern were analyzed. We found that people with high HIV viral loads and two COVID-19 vaccine doses had lower levels of binding antibodies that were less virus neutralizing and less cross-reactive compared to control groups. A third vaccination increased neutralizing antibody titers. Our data suggest that people with high HIV viral loads require a third dose of vaccine to neutralize SARS-CoV-2 virus and new variants as they emerge.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.032
GPT teacher head0.356
Teacher spread0.325 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2023
Admission routes2
Has abstractyes

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