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Record W1996321192 · doi:10.1073/pnas.1002894107

Establishment of HIV-1 latency in resting CD4 <sup>+</sup> T cells depends on chemokine-induced changes in the actin cytoskeleton

2010· article· en· W1996321192 on OpenAlexaff
Paul Cameron, Suha Saleh, Georgina Sallmann, Ajantha Solomon, Fiona Wightman, Vanessa A. Evans, Geneviève Boucher, Elias K. Haddad, Rafick‐Pierre Sékaly, Andrew N. Harman, Jenny L. Anderson, Kate Jones, Johnson Mak, Anthony L. Cunningham, Anthony Jaworowski, Sharon R. Lewin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsCofilinCXCL10Cell biologyCCL20C-C chemokine receptor type 6ActinBiologyChemokineCCL5CCL19CytoskeletonCXCL9Actin cytoskeletonChemokine receptorT cellImmunologyCellIL-2 receptorInflammationBiochemistry

Abstract

fetched live from OpenAlex

Eradication of HIV-1 with highly active antiretroviral therapy (HAART) is not possible due to the persistence of long-lived, latently infected resting memory CD4(+) T cells. We now show that HIV-1 latency can be established in resting CD4(+) T cells infected with HIV-1 after exposure to ligands for CCR7 (CCL19), CXCR3 (CXCL9 and CXCL10), and CCR6 (CCL20) but not in unactivated CD4(+) T cells. The mechanism did not involve cell activation or significant changes in gene expression, but was associated with rapid dephosphorylation of cofilin and changes in filamentous actin. Incubation with chemokine before infection led to efficient HIV-1 nuclear localization and integration and this was inhibited by the actin stabilizer jasplakinolide. We propose a unique pathway for establishment of latency by direct HIV-1 infection of resting CD4(+) T cells during normal chemokine-directed recirculation of CD4(+) T cells between blood and tissue.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.307
Teacher spread0.269 · 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

Citations231
Published2010
Admission routes1
Has abstractyes

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