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Record W4410137946 · doi:10.1016/j.vaccine.2025.127206

Intranasal vaccination with multi-neuraminidase and M2e virus-like particle vaccine results in greater mucosal immunity and protection against influenza than intramuscular injection

2025· article· en· W4410137946 on OpenAlexaff
Jannatul Ruhan Raha, Ki‐Hye Kim, Chau Thuy Tien Le, Noopur Bhatnagar, Surya Sekhar Pal, Rong Liu, Phillip B Grovenstein, Mahmuda Yeasmin, Farayola Racheal, Chong Hyun Shin, Bao‐Zhong Wang, Sang‐Moo Kang

Bibliographic record

VenueVaccine · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthDivision of Intramural Research, National Institute of Allergy and Infectious Diseases
KeywordsVirologyNasal administrationNeuraminidaseVaccinationImmunityMedicineMucosal immunityInfluenza vaccineVirusIntramuscular injectionHerd immunityImmunologyImmune systemInternal medicine

Abstract

fetched live from OpenAlex

Intramuscular injection of seasonal influenza vaccines provides strain-specific neutralizing antibodies, but not against variants, and no effective mucosal immunity. Here, we report that multi-subtype neuraminidase (NA) and M2 ectodomain repeat (5xM2e) virus-like particle vaccine (NA-M2e) conferred higher efficacy of broad cross-protection after two doses of intranasal delivery than intramuscular injection. The intranasally vaccinated mice displayed high levels of IgA antibodies, IFN-γ + CD4 and CD8 T cells, germinal center B cells, plasma cells, and early innate immune cells locally in the lungs. In contrast, intramuscular vaccination systemically induced innate and adaptive immune responses in the spleen. Our findings demonstrate that the intranasal delivery of NA-M2e vaccine induces enhanced mucosal immunity and comparable serum IgG antibodies, offering improved efficacy of cross-protection against diverse influenza virus strains compared to the intramuscular injection in a mouse model.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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 designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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