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Role for Human Immunodeficiency Virus Type 1 Tat Protein in Suppression of Viral Reverse Transcriptase Activity during Late Stages of Viral Replication

2001· article· en· W1984882587 on OpenAlexaff
Masanori Kameoka, Liwei Rong, Matthias Götte, Chen Liang, Rodney S. Russell, Mark A. Wainberg

Bibliographic record

VenueJournal of Virology · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNational Institute of Allergy and Infectious Diseases
KeywordsBiologyReverse transcriptaseViral replicationVirologyTranscription (linguistics)RNAExonVirusMolecular biologyInfectivityGeneGenetics

Abstract

fetched live from OpenAlex

We have examined the role of the human immunodeficiency virus type 1 (HIV-1) Tat protein in the regulation of reverse transcription. We show that a two-exon but not a one-exon form of Tat markedly suppressed cell-free reverse transcriptase (RT) activity. Conversely, viruses expressing two-exon Tat (pNL43 and pNL101) showed rapid replication kinetics and more efficient endogenous RT activity compared with viruses expressing one-exon Tat (pM1ex). The pM1ex virions, as well as pM1ex-infected cells, also contained higher levels of viral DNA than did either the pNL43 or pNL101 viruses, indicating that reverse transcription might have continued during later stages of viral replication in the absence of the second Tat exon. Moreover, degradation of viral genomic RNA was more apparent in the pM1ex virions. Accordingly, we propose that the two-exon Tat may help augment viral infectivity by suppressing the reverse transcription reaction during late stages of viral synthesis and by preventing the synthesis of potentially deleterious viral DNA products.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.002

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 communication0.0010.000
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 head0.019
GPT teacher head0.304
Teacher spread0.284 · 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

Labeled directly by 2 models reading the full record.

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

Citations33
Published2001
Admission routes1
Has abstractyes

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