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Record W2966776527 · doi:10.1684/vir.2018.0737

Les protéines antisens des virus HTLV

2018· article· fr· W2966776527 on OpenAlexaff
Clément Caté, Émilie Larocque, Jean‐Marie Péloponèse, Jean-Michel Mesnard, Éric Rassart, Benoı̂t Barbeau

Bibliographic record

VenueVirologie · 2018
Typearticle
Languagefr
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMolecular biologyBiologyVirusVirology

Abstract

fetched live from OpenAlex

Les virus T-lymphotropiques humains (HTLV) sont composs de quatre membres : HTLV-1, 2, 3 et 4. Issus d'une transmission de virus simiens, les virus HTLV sont capables d'infecter plusieurs types de cellules du systme immunitaire. HTLV-1 est le premier rtrovirus humain isol responsable de pathologies chez l'individu infect. Bien que l'expression des gnes des rtrovirus dpende gnralement du promoteur situ dans leur LTR 5 , il a t dmontr que le LTR 3'des HTLV possdait aussi une activit promotrice responsable de la production d'un transcrit antisens in vivo. Ces transcrits sont capables de produire des protines dites antisens, nommes HBZ, APH-2, APH-3 et APH-4, respectivement pour HTLV-1, 2, 3 et 4. La transcription antisens chez HTLV-1 a t analyse en dtail et la protine HBZ est la plus tudie des quatre protines antisens. Il est aujourd'hui avr qu'elle possde des rles importants pour la rplication virale et le dveloppement de la leucmie. Peu d'tudes ont cependant t ralises sur la transcription antisens chez HTLV-2 et encore moins chez HTLV-3/4, bien qu'il semble trs probable que la transcription antisens joue galement un rle crucial dans leur processus infectieux.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score1.000

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 studies0.0010.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.008

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 head0.063
GPT teacher head0.299
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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