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Record W3092241409 · doi:10.1038/s42003-020-01288-3

Multidimensional analyses reveal modulation of adaptive and innate immune subsets by tuberculosis vaccines

2020· article· en· W3092241409 on OpenAlexaff
Virginie Rozot, Elisa Nemes, Hennie Geldenhuys, Munyaradzi Musvosvi, Asma Toefy, Frances Rantangee, Lebohang Makhethe, Mzwandile Erasmus, Nicole Bilek, Simbarashe Mabwe, Greg Finak, William J. Fulp, Ann M. Ginsberg, David A. Hokey, Muki Shey, Sanjay Gurunathan, Carlos A. DiazGranados, Linda‐Gail Bekker, Mark Hatherill, Thomas J. Scriba, Charmaine Abrahams, Marcelene Aderiye, Hadn Africa, Deidre Albertyn, Fadia Alexander, Julia Amsterdam, Peter Andersen, Denis Arendsen, H. Bester, Elizabeth Beyers, Natasja Botes, Janelle Botes, Samentra Braaf, Roger A. Brooks, Yolundi Cloete, Alessandro Companie, Kristin Croucher, Ilse Davids, Guy de Bruyn, Bongani Diamond, Portia Dlakavu, Palesa Dolo, Sahlah Dubel, Cindy Elbring, Ruth D. Ellis, Margareth Erasmus, Terence Esterhuizen, Thomas G. Evans, Christine Fattore, Sebastian Gelderbloem, Diann Gempies, Sandra Goliath, Peggy Gomes, Yolande Gregg, Elizabeth Hamilton, Willem A. Hanekom, Johanna Hector, Roxanne Herling, Yulandi Herselman, Robert Hopkins, Jane Hughes, Devin J Hunt, Henry Issel, Helene Janosczyk, Lungisa Jaxa, Carolyn Jones, Jateel Kassiem, Sophie Keffers, Xoliswa Kelepu, Alana Keyser, Alexia Kieffer, Ingrid Kromann, Sandra Krüger, Maureen Lambrick, Bernard Landry, Phumzile Langata, Maria Lempicki, Marie-Christine Locas, Angelique Kany Kany Luabeya, Lauren Mactavie, Lydia Makunzi, Pamela Mangala, Clive Maqubela, Boitumelo Mosito, Angelique Mouton, Humphrey Mulenga, Mariana Mullins, Julia Noble, Onke Nombida, Dawn M. O’Dee, Amy O’Neil, Rose Ockhuis, Saleha Omarjee, Fajwa Opperman, Dhaval M. Patel, Christel Petersen, Abraham Pretorius, Debbie Pretorius, Michael Raine, Rodney Raphela, Maigan Ratangee, Christian Rauner, Susan Rossouw, Surita Roux, Kathryn Rutkowski, Robert Ryall, Elisma Schoeman, Constance Schreuder, Steven G. Self, Cashwin September, Justin Shenje, Barbara Shepherd, Heather Siefers, Eunice Sinandile, Danna Skea, Marcia Steyn, Jin Su, Sharon Egretta Sutton, Anne Swarts, Patrick Syntin, Michèle Tameris, Petrus Tyambetyu, Arrie van der Merwe, Elize van der Riet, Dorothy van der Vendt, Denise van der Westhuizen, Anja van der Westhuizen, Elma van Rooyen, Ashley Veldsman, Helen Veltdsman, Emerencia Vermeulen, Sindile Wiseman Matiwane, Noncedo Xoyana

Bibliographic record

VenueCommunications Biology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsSanofi (Canada)
FundersSanofi PasteurInternational Society for Advancement of CytometryWellcome TrustStatens Serum InstitutDepartment for International DevelopmentSanofiBill and Melinda Gates Foundation
KeywordsMycobacterium tuberculosisImmunologyTuberculosisImmune systemVaccinationBiologyInnate immune systemAcquired immune systemCytokineBCG vaccineAdjuvantVirologyMedicine

Abstract

fetched live from OpenAlex

Abstract We characterize the breadth, function and phenotype of innate and adaptive cellular responses in a prevention of Mycobacterium tuberculosis infection trial. Responses are measured by whole blood intracellular cytokine staining at baseline and 70 days after vaccination with H4:IC31 (subunit vaccine containing Ag85B and TB10.4), Bacille Calmette-Guerin (BCG, a live attenuated vaccine) or placebo (n = ~30 per group). H4:IC31 vaccination induces Ag85B and TB10.4-specific CD4 T cells, and an unexpected NKT like subset, that expresses IFN-γ, TNF and/or IL-2. BCG revaccination increases frequencies of CD4 T cell subsets that either express Th1 cytokines or IL-22, and modestly increases IFNγ-producing NK cells. In vitro BCG re-stimulation also triggers responses by donor-unrestricted T cells, which may contribute to host responses against mycobacteria. BCG, which demonstrated efficacy against sustained Mycobacterium tuberculosis infection, modulates multiple immune cell subsets, in particular conventional Th1 and Th22 cells, which should be investigated in discovery studies of correlates of protection.

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)0.000
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 score0.577
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.060
GPT teacher head0.332
Teacher spread0.272 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

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