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Record W2743748917 · doi:10.1186/s13567-017-0445-2

Role of transcription regulatory sequence in regulation of gene expression and replication of porcine reproductive and respiratory syndrome virus

2017· article· en· W2743748917 on OpenAlexaff
Chengbao Wang, Han Meng, Yujin Gao, Hui Gao, Kangkang Guo, Fernando Almazán, Isabel Sola, Luis Enjuanes, Yanming Zhang, Levon Abrahamyan

Bibliographic record

VenueVeterinary Research · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversité de Montréal
FundersNational Institute of Allergy and Infectious DiseasesNational Natural Science Foundation of China
KeywordsBiologyPorcine reproductive and respiratory syndrome virusGeneGene expressionRegulatory sequenceRegulation of gene expressionGeneticsTranscription (linguistics)Viral replicationArterivirusMolecular biologyVirusCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

In order to gain insight into the role of the transcription regulatory sequences (TRSs) in the regulation of gene expression and replication of porcine reproductive and respiratory syndrome virus (PRRSV), the enhanced green fluorescent protein (EGFP) gene, under the control of the different structural gene TRSs, was inserted between the N gene and 3'-UTR of the PRRSV genome and EGFP expression was analyzed for each TRS. TRSs of all the studied structural genes of PRRSV positively modulated EGFP expression at different levels. Among the TRSs analyzed, those of GP2, GP5, M, and N genes highly enhanced EGFP expression without altering replication of PRRSV. These data indicated that structural gene TRSs could be an extremely useful tool for foreign gene expression using PRRSV as a vector.

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 score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.205
GPT teacher head0.373
Teacher spread0.168 · 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

Citations30
Published2017
Admission routes1
Has abstractyes

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