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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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.005

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; both teacher heads agree on what is shown here.

Study designBench or experimental
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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