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Record W1991422659 · doi:10.1371/journal.pone.0099535

miRNA-1236 Inhibits HIV-1 Infection of Monocytes by Repressing Translation of Cellular Factor VprBP

2014· article· en· W1991422659 on OpenAlexaff
Li Ma, Chanjuan Shen, Éric A. Cohen, Sidong Xiong, Jianhua Wang

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMontreal Clinical Research Institute
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNational Natural Science Foundation of ChinaSanofi
KeywordsmicroRNABiologyTranslation (biology)TransfectionVirologyMonocyteRegulation of gene expressionCell biologyGeneImmunologyMessenger RNAGenetics

Abstract

fetched live from OpenAlex

Primary monocytes are refractory to HIV-1 infection and become permissive upon differentiation into monocyte-derived dendritic cells (MDDCs) or macrophages. Multiple mechanisms have been proposed to interpret HIV-1 restriction in monocytes. Human cellular miRNAs can modulate HIV-1 infection by targeting either conserved regions of the HIV-1 genome or host gene transcripts. We have recently reported that the translation of host protein pur-alpha is repressed by abundant cellular miRNAs to inhibit HIV-1 infection in monocytes. Here, we report that the transcript of another cellular factor, VprBP [Vpr (HIV-1)-binding protein], was repressed by cellular miRNA-1236, which contributes to HIV-1 restriction in monocytes. Transfection of miR-1236 inhibitors enhanced translation of VprBP in monocytes and significantly promoted viral infection; exogenous input of synthesized miR-1236 mimics into MDDCs suppressed translation of VprBP, and, accordingly, significantly impaired viral infection. Our data emphasize the role of miRNA in modulating differentiation-dependent susceptibility of the host cell to HIV-1 infection. Understanding the modulation of HIV-1 infection by cellular miRNAs may provide key small RNAs or the identification of new important protein targets regulated by miRNAs for the development of antiviral strategies.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.242
Teacher spread0.197 · 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 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

Citations47
Published2014
Admission routes1
Has abstractyes

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