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Record W3110098604 · doi:10.1080/14760584.2020.1857736

B cell targeting by molecular adjuvants for enhanced immunogenicity

2020· review· en· W3110098604 on OpenAlexafffund
Taylor Sicard, Audrey Kassardjian, Jean‐Philippe Julien

Bibliographic record

VenueExpert Review of Vaccines · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAdjuvantImmune systemImmunogenicityAntigenImmunologyBiologyReceptorB-cell activating factorAntibodyB cell

Abstract

fetched live from OpenAlex

INTRODUCTION: Adjuvants are critical components of vaccines to improve the quality and durability of immune responses. Molecular adjuvants are a specific subclass of adjuvants where ligands of known immune-modulatory receptors are directly fused to an antigen. Co-stimulation of the B cell receptor (BCR) and immune-modulatory receptors through this strategy can augment downstream signaling to improve antibody titers and/or potency, and survival in challenge models. AREAS COVERED: C3d has been the most extensively studied molecular adjuvant and shown to improve immune responses to a number of antigens. Similarly, tumor necrosis superfamily ligands, such as BAFF and APRIL, as well as CD40, CD180, and immune complex ligands can also improve humoral immunity as molecular adjuvants. EXPERT OPINION: However, no single strategy has emerged that improves immune outcomes in all contexts. Thus, systematic exploration of molecular adjuvants that target B cell receptors will be required to realize their full potential as next-generation vaccine technologies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.699
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.325
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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2020
Admission routes2
Has abstractyes

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