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Record W2163096595 · doi:10.1517/14712598.2013.779249

New developments in lentiviral vector design, production and purification

2013· review· en· W2163096595 on OpenAlexaff
María Mercedes Segura, Mathias Mangion, Bruno Gaillet, Alain Garnier

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversité LavalPROTEO
Fundersnot available
KeywordsGenetic enhancementLentivirusViral vectorVector (molecular biology)RetrovirusBioproductionVectors in gene therapyComputational biologyRecombinant DNAGene deliveryBiologyVirologyBiotechnologyGeneHuman immunodeficiency virus (HIV)VirusGeneticsViral disease

Abstract

fetched live from OpenAlex

INTRODUCTION: Lentiviruses are a very potent class of viral vectors for which there is presently a rapidly growing interest for a number of gene therapy. However, their construction, production and purification need to be performed according to state-of-the-art techniques in order to obtain sufficient quantities of high purity material of any usefulness and safety. AREAS COVERED: The recent advances in the field of recombinant lentivirus vector design, production and purification will be reviewed with an eye toward its utilization for gene therapy. Such a review should be helpful for the potential user of this technology. EXPERT OPINION: The principal hurdles toward the use of recombinant lentivirus as a gene therapy vector are the low titer at which it is produced as well as the difficulty to purify it at an acceptable level without degrading it. The recent advances in the bioproduction of this vector suggest these issues are about to be resolved, making the retrovirus gene therapy a mature technology.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.214
GPT teacher head0.411
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 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

Citations115
Published2013
Admission routes1
Has abstractyes

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