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Record W2935971634 · doi:10.3390/pharmaceutics11040188

Co-Delivery of M2e Virus-Like Particles with Influenza Split Vaccine to the Skin Using Microneedles Enhances the Efficacy of Cross Protection

2019· article· en· W2935971634 on OpenAlexaff
Minchul Kim, Ki‐Hye Kim, Jeong Woo Lee, Yuna Lee, Hyo‐Jick Choi, Yu‐Jin Jung, Yu-Jin Kim, Richard W. Compans, Mark R. Prausnitz, Sang‐Moo Kang

Bibliographic record

VenuePharmaceutics · 2019
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of Alberta
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsInfluenza vaccineVirologyImmunizationVirusHeterologousVirus-like particleMedicineImmune systemImmunologyBiology

Abstract

fetched live from OpenAlex

It is a high priority to develop a simple and effective delivery method for a cross-protective influenza vaccine. We investigated skin immunization by microneedle (MN) patch with human influenza split vaccine and virus-like particles containing heterologous M2 extracellular (M2e) domains (M2e5x virus-like particles (VLP)) as a cross-protective influenza vaccine candidate. Co-delivery of influenza split vaccine and M2e5x VLP to the skin by MN patch was found to confer effective protection against heterosubtypic influenza virus by preventing weight loss and reducing lung viral loads. Compared to intramuscular immunization, MN-based delivery of combined split vaccine and M2e5x VLPs shaped cellular immune responses toward T helper type 1 responses increasing IgG2a isotype antibodies as well as IFN-γ producing cells in mucosal and systemic sites. This study provides evidence that potential immunological and logistic benefits of M2e5x VLP with human influenza split vaccine delivered by MN patch can be used to develop an easy-to-administer cross-protective influenza vaccine.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.146
GPT teacher head0.451
Teacher spread0.305 · 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

Citations16
Published2019
Admission routes1
Has abstractyes

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