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Record W2068829341 · doi:10.2174/1567201043479993

Biphasic Lipid Vesicles (Biphasix™) Enhance the Adjuvanticity of CpG Oligonucleotides Following Systemic and Mucosal Administration

2004· article· en· W2068829341 on OpenAlexaff
Shawn Babiuk, Maria E. Baca‐Estrada, Dorothy M. Middleton, Rolf Hecker, Lorne A. Babiuk, Marianna Földvári

Bibliographic record

VenueCurrent Drug Delivery · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsImmunoadjuvantAdjuvantCpG OligodeoxynucleotideImmunizationImmune systemAntigenPharmacologyCpG siteImmunologySystemic administrationChemistryAntibodyMedicineBiologyIn vivoBiochemistryDNA methylation

Abstract

fetched live from OpenAlex

CpG oligonucleotides (ODNs) are potent mucosal and systemic adjuvants. For practical applications however, improvements in delivery need to be developed. A mouse model was used to determine if the biological activity of CpG ODNs could be enhanced using a novel delivery system of biphasic lipid vesicles (Biphasix Vaccine-Targeting Adjuvant; VTA). Immunization studies were performed to evaluate the potential of VTA formulations to enhance the immunoadjuvant activity of CpG ODNs following systemic or mucosal administration with gD. Immune responses following immunization were assessed by protection from HSV-1 viral challenge and characterization of serum gD-specific antibody responses using ELISA. VTA formulations in combination with CpG and glycoprotein D (gD) were able to increase gD-specific IgG in serum compared to gD alone, and protect from a lethal HSV-1 challenge following subcutaneous immunization. Following mucosal immunization, VTA formulations in combination with CpG and antigen enhanced mucosal IgA responses compared to CpG and antigen administered in PBS.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
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 head0.016
GPT teacher head0.278
Teacher spread0.263 · 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

Citations8
Published2004
Admission routes1
Has abstractyes

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