MétaCan
Menu
Back to cohort
Record W2013727257 · doi:10.1371/journal.ppat.1002087

HIV/SIV Infection Primes Monocytes and Dendritic Cells for Apoptosis

2011· article· en· W2013727257 on OpenAlexaff
Mireille Laforge, L. Campillo-Gimenez, Valérie Monceaux, Marie‐Christine Cumont, Bruno Hurtrel, Jacques Corbeil, John Zaunders, Carole Elbim, Jérôme Estaquier

Bibliographic record

VenuePLoS Pathogens · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversité Laval
FundersNational Health and Medical Research Council
KeywordsApoptosisImmunologyBiologyCD14Fas ligandProgrammed cell deathImmune systemVirology

Abstract

fetched live from OpenAlex

Subversion or exacerbation of antigen-presenting cells (APC) death modulates host/pathogen equilibrium. We demonstrated during in vitro differentiation of monocyte-derived macrophages and monocyte-derived dendritic cells (DCs) that HIV sensitizes the cells to undergo apoptosis in response to TRAIL and FasL, respectively. In addition, we found that HIV-1 increased the levels of pro-apoptotic Bax and Bak molecules and decreased the levels of anti-apoptotic Mcl-1 and FLIP proteins. To assess the relevance of these observations in the context of an experimental model of HIV infection, we investigated the death of APC during pathogenic SIV-infection in rhesus macaques (RMs). We demonstrated increased apoptosis, during the acute phase, of both peripheral blood DCs and monocytes (CD14(+)) from SIV(+)RMs, associated with a dysregulation in the balance of pro- and anti-apoptotic molecules. Caspase-inhibitor and death receptors antagonists prevented apoptosis of APCs from SIV(+)RMs. Furthermore, increased levels of FasL in the sera of pathogenic SIV(+)RMs were detected, compared to non-pathogenic SIV infection of African green monkey. We suggest that inappropriate apoptosis of antigen-presenting cells may contribute to dysregulation of cellular immunity early in the process of HIV/SIV infection.

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 categoriesnone
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 score1.000

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)0.0000.001

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 head0.039
GPT teacher head0.247
Teacher spread0.208 · 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 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

Citations59
Published2011
Admission routes1
Has abstractyes

Explore more

Same venuePLoS PathogensSame topicHIV Research and TreatmentFrench-language works237,207