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Record W2438003748 · doi:10.1007/978-1-60761-588-0_19

Transfection of siRNAs in Multiple Myeloma Cell Lines

2010· article· en· W2438003748 on OpenAlexaff
Jose Luis R. Brito, Nicola Brown, Gareth J. Morgan

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversité de Sherbrooke
FundersKay Kendall Leukaemia Fund
KeywordsSmall interfering RNATransfectionRNA interferenceGene silencingStreptolysinTrans-acting siRNACell cultureCell biologyFunctional genomicsBiologyMolecular biologyGeneChemistryRNAComputational biologyGenomicsGeneticsGenomeBacterial protein

Abstract

fetched live from OpenAlex

RNA interference (RNAi), a valuable tool to specifically silence gene expression, is becoming an indispensable weapon in the arsenal of functional genomics, target validation and gene-specific therapeutic research. We have shown that Streptolysin-O (SLO) reversible permeabilization is an efficient method to deliver small interfering RNAs (siRNAs) to hard-to-transfect human myeloma cell lines. In addition, we have shown that transfection of siRNAs, using the SLO reversible permeabilization, specifically and efficiently induces gene silencing in myeloma cell lines.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.006

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 head0.016
GPT teacher head0.347
Teacher spread0.331 · 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
GenreMethods

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

Citations6
Published2010
Admission routes1
Has abstractyes

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