MétaCan
Menu
← Back to cohort
Record W2953645330 · doi:10.82308/30837

Long term non progressors : clues for defining immune correlates of protection from HIV disease progression

2007· article· en· W2953645330 on OpenAlexfundno aff
Yoav Peretz

Bibliographic record

VenueeScholarship@McGill (McGill) · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersFonds de Recherche du Québec - SantéNational Institutes of HealthMcGill UniversityCanadian Foundation for AIDS ResearchStyrelsen för Internationellt Utvecklingssamarbete
KeywordsImmunologyImmune systemViral loadDiseasePandemicInfectious disease (medical specialty)MedicineBiologyVirologyHuman immunodeficiency virus (HIV)Coronavirus disease 2019 (COVID-19)Internal medicine

Abstract

fetched live from OpenAlex

Throughout history, human populations have continuously been challenged by new and emerging infectious diseases. For the past 26 years, sub-Saharan Africa and other countries around the world have been dealing with a pandemic caused by a relatively new pathogen called the human immunodeficiency virus (HIV). Although antiretroviral (ARV) therapies effectively reduce morbidity and mortality rates, the long term use in those who have access to treatment inevitably leads to drug-related toxicity and resistance. Even with a strong commitment from governments to expand and finance prevention and treatment programs, transmission rates continue to outpace the benefits of these efforts. Therefore to effectively eradicate the disease, research is focusing on the design of protective and therapeutic vaccines. The first major step in designing these alternative therapies is to define correlates of immune protection. The research presented in this thesis focuses on characterizing the quantitative and qualitative features of T cell immune responses in individuals who spontaneously control viral replication and exhibit a benign course of disease while remaining off ARV therapy. A comprehensive analysis of HIV-specific IFN-gamma secreting immune responses revealed that neither the breadth nor the magnitude of responses directed against the entire HIV proteome accurately predicts the viral load or rate of CD4 decline. Subsequent analyses showed that the preferential targeting of Gag was associated with reduced rates of CD4 decline and was later confirmed in a cohort of individuals in primary infection whereby the relative breadth and magnitude of Gag p24 was inversely correlated with viral load set point. The maintenance of polyfunctional immune responses in HIV-infected subjects with a benign course of disease prompted us to develop a method that could comprehensively assess the breadth, magnitude and specificity of three functionally distinct subsets of HIV-specific lymphocytes (single IFN-gamma, single IL-2 and dual IFN-gamma/IL-2 secretors). Survey of immune responses in chronically infected individuals revealed that only the breadth and magnitude of dual IFN-gamma/IL-2 secreting lymphocytes correlated with reduced viral loads and increased CD4 counts suggesting that secretion of IFN-gamma alone was a poor correlate of protection. We also showed that the contribution of polyfunctional lymphocytes to the total response was greater for epitopes restricted by major histocompatibility complex (MHC) class I alleles associated with slow disease progression compared to those restricted by alleles associated with rapid or neutral rates of HIV disease progression. Taken together, this work supports the view that immune monitoring of infected and vaccinated individuals should include methodologies capable of detecting both IFN-gamma and IL-2 secretion from responding T lymphocytes. The studies presented here have furthered our understanding of what constitutes protection from disease progression emphasizing that both specificity and polyfunctionality are features of effective control of viral replication.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.271
Teacher spread0.254 · 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 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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)→Same topicHIV Research and Treatment→French-language works237,207→