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Cellular immune responses to recurring influenza strains have limited boosting ability and limited cross-reactivity to other strains

2015· article· en· W6884617197 on OpenAlexaff

Bibliographic record

VenueUniversity of Nairobi Research Archive (University of Nairobi) · 2015
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of CanadaUniversity of Manitoba
Fundersnot available
KeywordsImmune systemAntibodyVirusVaccinationInfluenza A virusCellular immunityImmunityInfluenza vaccineCytotoxic T cell

Abstract

fetched live from OpenAlex

Influenza vaccine provides protection against infection with matched strains, and this protection correlates with serum antibody titres. In addition to antibodies, influenza-specific CD8+ T-lymphocyte responses are important in decreasing disease severity and facilitating viral clearance. Because this response is directed at internal, relatively conserved antigens, it affords some cross-protection within a given subtype of influenza virus. With the possibility of a broader A(H1N1) Mexico outbreak in the fall of 2009, it appeared worthwhile studying the degree of cellular immune response-mediated cross-reactivity among influenza virus isolates. The composition of the 2006–2007 influenza vaccine included the A/New Caledonia/20/1999 strain (comprising a virus that has been circulating, and was included in vaccine preparations, for 6–7 years) and two strains not previously included (Wisconsin and Malaysia). This combination afforded us the opportunity to determine the degree of cross-reactive cellular immunity after exposure to new viral strains. We analysed the antibody responses and the phenotype and function of the T cell response to vaccine components. The results obtained show that antibody responses to A/New-Caledonia were already high and vaccination did not increase antibody or cytotoxic T lymphocyte responses. These data suggest that repeated exposure to the same influenza stain results in limited boosting of humoral and cellular immune responses.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.151
GPT teacher head0.367
Teacher spread0.216 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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