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Record W2002489327 · doi:10.1186/1742-4690-6-42

TLR2 and TLR4 triggering exerts contrasting effects with regard to HIV-1 infection of human dendritic cells and subsequent virus transfer to CD4+T cells

2009· article· en· W2002489327 on OpenAlexafffund
Sandra Thibault, Rémi Fromentin, Mélanie R. Tardif, Michel J. Tremblay

Bibliographic record

VenueRetrovirology · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersCanadian Institutes of Health ResearchFaculté de Médecine, Université LavalUniversité Laval
KeywordsTLR2TLR4ImmunologyVirusInnate immune systemToll-like receptorVirologyTLR7Viral entryTransmission (telecommunications)BiologyImmune systemInterferonViral replication

Abstract

fetched live from OpenAlex

BACKGROUND: Recognition of microbial products through Toll-like receptors (TLRs) initiates inflammatory responses orchestrated by innate immune cells such as dendritic cells (DCs). As these cells are patrolling mucosal surfaces, a portal of entry for various pathogens including human immunodeficiency virus type-1 (HIV-1), we investigated the impact of TLR stimulation on productive HIV-1 infection of DCs and viral spreading to CD4+ T cells. RESULTS: We report here that engagement of TLR2 on DCs increases HIV-1 transmission toward CD4+ T cells by primarily affecting de novo virus production by DCs. No noticeable and consistent effect was observed following engagement of TLR5, 7 and 9. Additional studies indicated that both HIV-1 infection of DCs and DC-mediated virus transmission to CD4+ T cells were reduced upon TLR4 triggering due to secretion of type-I interferons. CONCLUSION: It can thus be proposed that exposure of DCs to TLR2-binding bacterial constituents derived, for example, from pathogens causing sexually transmissible infections, might influence the process of DC-mediated viral dissemination, a phenomenon that might contribute to a more rapid disease progression.

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 categoriesnone
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 score0.061
Threshold uncertainty score0.738

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)0.0000.000

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 head0.005
GPT teacher head0.213
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations43
Published2009
Admission routes2
Has abstractyes

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