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Record W2032970509 · doi:10.1097/coh.0b013e32833d2cc0

New approaches to design HIV-1 T-cell vaccines

2010· review· en· W2032970509 on OpenAlexaff
Hélène Perrin, Glenda Canderan, Rafick‐Pierre Sékaly, Lydie Trautmann

Bibliographic record

VenueCurrent Opinion in HIV and AIDS · 2010
Typereview
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversité de Montréal
FundersNational Institute of Allergy and Infectious DiseasesNational Institute on Drug AbuseU.S. Public Health Service
KeywordsImmune systemImmunologyAcquired immune systemVaccine efficacyImmunityT cellHoming (biology)Human immunodeficiency virus (HIV)HIV vaccineInnate immune systemAntigenBiologyVirologyMedicineVaccine trial

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Following the evidence that T-cell responses are crucial in the control of HIV-1 infection, vaccines targeting T-cell responses were tested in recent clinical trials. However, these vaccines showed a lack of efficacy. This review attempts to define the qualitative and quantitative features that are desirable for T-cell-induced responses by vaccines. We also describe strategies that could lead to achievement of this goal. RECENT FINDINGS: Using the yellow fever vaccine as a benchmark of an efficient vaccine, recent studies identified factors of immune protection and more importantly innate immune pathways needed for the establishment of long-term protective adaptive immunity. SUMMARY: To prevent or control HIV-1 infection, a vaccine must induce efficient and persistent antigen-specific T cells endowed with mucosal homing capacity. Such cells should have the capability to counteract HIV-1 diversity and its rapid spread from the initial site of infection. To achieve this goal, the activation of a diversified innate immune response is critical. New systems biology approaches will provide more precise correlates of immune protection that will pave the way for new approaches in T-cell-based vaccines.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.003

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 head0.247
GPT teacher head0.366
Teacher spread0.119 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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