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Record W4292966551 · doi:10.1016/j.isci.2022.104990

Humoral immune responses against SARS-CoV-2 Spike variants after mRNA vaccination in solid organ transplant recipients

2022· article· en· W4292966551 on OpenAlexaff
Alexandra Tauzin, Guillaume Beaudoin-Bussières, Shang Yu Gong, Debashree Chatterjee, Gabrielle Gendron‐Lepage, Catherine Bourassa, Guillaume Goyette, Normand Racine, Zineb Khrifi, Julie Turgeon, Cécile Tremblay, Valérie Martel‐Laferrière, Daniel E. Kaufmann, Héloïse Cardinal, Marc Cloutier, Renée Bazin, Ralf Duerr, Mélanie Dieudé, Marie‐Josée Hébert, Andrés Finzi

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsHéma-QuébecMontreal Heart InstituteTranslational Research in OncologyUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsImmune systemMedicineImmunologyCohortVaccinationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PopulationVirologyCoronavirus disease 2019 (COVID-19)Internal medicine

Abstract

fetched live from OpenAlex

Although SARS-CoV-2 mRNA vaccination has been shown to be safe and effective in the general population, immunocompromised solid organ transplant recipients (SOTRs) were reported to have impaired immune responses after one or two doses of vaccine. In this study, we examined humoral responses induced after the second and the third dose of mRNA vaccine in different SOTR (kidney, liver, lung, and heart). Compared to a cohort of SARS-CoV-2 naïve immunocompetent health care workers (HCWs), the second dose induced weak humoral responses in SOTRs, except for the liver recipients. The third dose boosted these responses but they did not reach the same level as in HCW. Interestingly, although the neutralizing activity against Delta and Omicron variants remained very low after the third dose, Fc-mediated effector functions in SOTR reached similar levels as in the HCW cohort. Whether these responses will suffice to protect SOTR from severe outcome remains to be determined.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.353
Teacher spread0.310 · 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 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

Citations12
Published2022
Admission routes1
Has abstractyes

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