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Record W82184047 · doi:10.1182/blood.v96.9.2951

Mechanisms of HIV-associated lymphocyte apoptosis

2000· article· en· W82184047 on OpenAlexaff
Andrew D. Badley, André A. Pilon, Alan Landay, David H. Lynch

Bibliographic record

VenueBlood · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsImmune systemApoptosisCytotoxic T cellImmunologyBiologyCD8T cellLymphocyteVirologyIn vitro

Abstract

fetched live from OpenAlex

Infection with the human immunodeficiency virus (HIV) is associated with a progressive decrease in CD4 T-cell number and a consequent impairment in host immune defenses. Analysis of T cells from patients infected with HIV, or of T cells infected in vitro with HIV, demonstrates a significant fraction of both infected and uninfected cells dying by apoptosis. The many mechanisms that contribute to HIV-associated lymphocyte apoptosis include chronic immunologic activation; gp120/160 ligation of the CD4 receptor; enhanced production of cytotoxic ligands or viral proteins by monocytes, macrophages, B cells, and CD8 T cells from HIV-infected patients that kill uninfected CD4 T cells; and direct infection of target cells by HIV, resulting in apoptosis. Although HIV infection results in T-cell apoptosis, under some circumstances HIV infection of resting T cells or macrophages does not result in apoptosis; this may be a critical step in the development of viral reservoirs. Recent therapies for HIV effectively reduce lymphoid and peripheral T-cell apoptosis, reduce viral replication, and enhance cellular immune competence; however, they do not alter viral reservoirs. Further understanding the regulation of apoptosis in HIV disease is required to develop novel immune-based therapies aimed at modifying HIV-induced apoptosis to the benefit of patients infected with HIV.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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

Citations304
Published2000
Admission routes1
Has abstractyes

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