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Record W4362696568 · doi:10.1186/s12977-023-00619-6

Biomolecular condensates: insights into early and late steps of the HIV-1 replication cycle

2023· review· en· W4362696568 on OpenAlexafffund
Francesca Di Nunzio, Vladimir N. Uversky, Andrew J. Mouland

Bibliographic record

VenueRetrovirology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health ResearchAgence Nationale de Recherches sur le Sida et les Hépatites ViralesStyrelsen för Internationellt Utvecklingssamarbete
KeywordsViral replicationBiologySubgenomic mRNAComputational biologyVirologyViral evolutionViral entryGenomeVirusGeneticsGene

Abstract

fetched live from OpenAlex

A rapidly evolving understanding of phase separation in the biological and physical sciences has led to the redefining of virus-engineered replication compartments in many viruses with RNA genomes. Condensation of viral, host and genomic and subgenomic RNAs can take place to evade the innate immunity response and to help viral replication. Divergent viruses prompt liquid-liquid phase separation (LLPS) to invade the host cell. During HIV replication there are several steps involving LLPS. In this review, we characterize the ability of individual viral and host partners that assemble into biomolecular condensates (BMCs). Of note, bioinformatic analyses predict models of phase separation in line with several published observations. Importantly, viral BMCs contribute to function in key steps retroviral replication. For example, reverse transcription takes place within nuclear BMCs, called HIV-MLOs while during late replication steps, retroviral nucleocapsid acts as a driver or scaffold to recruit client viral components to aid the assembly of progeny virions. Overall, LLPS during viral infections represents a newly described biological event now appreciated in the virology field, that can also be considered as an alternative pharmacological target to current drug therapies especially when viruses become resistant to antiviral treatment.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.319
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations27
Published2023
Admission routes2
Has abstractyes

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