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Record W2049978415 · doi:10.1089/vim.2005.18.283

Adenoviral Vectors for Mucosal Vaccination Against Infectious Diseases

2005· review· en· W2049978415 on OpenAlexaff
Michael Santosuosso, Sarah McCormick, Zhou Xing

Bibliographic record

VenueViral Immunology · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsVaccinationImmunologyVirologyViral vectorImmunityImmune systemMedicineImmunizationVector (molecular biology)TropismVirusBiologyRecombinant DNA

Abstract

fetched live from OpenAlex

Adenoviral vector has been extensively studied as a vaccine platform because of its ability to induce potent cellular and humoral immunity. One main advantage of adenoviral vectors is their natural tropism for mucosal surfaces, which makes them ideal for the purpose of mucosal vaccination against pathogens that preferentially initiate infection at the mucosal site. The current understanding of mucosal immunity suggests that mucosal vaccination is far superior to parenteral vaccination in protecting mucosal surfaces. Mucosal vaccination is particularly relevant to those infections for which parenteral immunization strategies have failed to confer protection. This review examines the use of adenoviral vector at mucosal sites for infectious disease against which the current vaccination strategies have been unsuccessful in eliciting protection. Data from animal models have suggested that adenoviral vectors are effective in protecting against infections caused by HIV, herpes simplex virus and Mycobacterium tuberculosis. We believe that these encouraging results will lead to further evaluation in clinical trials in the near future.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.349
Teacher spread0.325 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations72
Published2005
Admission routes1
Has abstractyes

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