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Record W4210760063 · doi:10.1371/journal.pone.0262873

Antibodies directed towards neuraminidase restrict influenza virus replication in primary human bronchial epithelial cells

2022· article· en· W4210760063 on OpenAlexfundno aff
Anouk Smet, João Paulo Portela Catani, Tine Ysenbaert, Amanda Gonçalves, Harry Kleanthous, Thorsten U. Vogel, Xavier Saelens, Emma R. Job

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersHealth CanadaSanofi PasteurSanofi
KeywordsNeuraminidaseVirologyPolyclonal antibodiesMonoclonal antibodyVirusAntibodyBiologyViral replicationInfluenza A virusViral entryImmunology

Abstract

fetched live from OpenAlex

Influenza neuraminidase (NA) is implicated in various aspects of the virus replication cycle and therefore is an attractive target for vaccination and antiviral strategies. Here we investigated the potential for NA-specific antibodies to interfere with A(H1N1)pdm09 replication in primary human airway epithelial (HAE) cells. Mouse polyclonal anti-NA sera and a monoclonal antibody could block initial viral entry into HAE cells as well as egress from the cell surface. NA-specific polyclonal serum also reduced virus replication across multiple rounds of infection. Restriction of virus entry correlated with the ability of the serum or monoclonal antibody to mediate neuraminidase inhibition (NI). Finally, human sera with NI activity against the N1 of A(H1N1)pdm09 could decrease H6N1 virus infection of HAE cells, highlighting the potential contribution of anti-NA antibodies in the control of influenza virus infection in humans.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.124
GPT teacher head0.349
Teacher spread0.225 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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