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Record W4243455690 · doi:10.2174/2210304x11101020118

Delivery Systems for Applications in siRNA Technology

2011· article· en· W4243455690 on OpenAlexaff
Kathleen Hefferon

Bibliographic record

VenueDrug Delivery Letters · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSmall interfering RNARNA interferenceNanocarriersRNATrans-acting siRNAViral vectorGene silencingComputational biologyBiologyCell biologyGeneGeneticsPharmacologyDrug

Abstract

fetched live from OpenAlex

Short interfering RNAs, or siRNAs, belong to a class of RNA species which play a role in both cellular defence and gene regulation. siRNAs are members of a larger RNA interference pathway found within cells and are involved in the degradation of RNAs which possess complementarity to specific target sequences. This property has given siRNA technology the potential to become a powerful new tool for a wide variety of disciplines, ranging from the design of novel anti-cancer agents to agricultural applications. The following review outlines novel delivery systems that can be used for applied siRNA technologies. Improved delivery systems for the cellular uptake of siRNAs using both viral expression vectors and nanoliposomal particles are discussed. New therapeutics that can be used to combat human disease and agricultural applications of siRNA technologies are also described. This review attempts to pave the way for future innovations based upon RNA interference in medicine and agriculture. Keywords: siRNA, nanocarrier, lentiviral vector, delivery vehicle, RNA interference, siRNA Conjugates, virus expression vectors, Nonviral Nanocarrier Systems, VEGFR, neurodegenerative diseases

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 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 score0.177
Threshold uncertainty score0.759

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.219
Teacher spread0.206 · 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 teacher head, 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

Citations0
Published2011
Admission routes1
Has abstractyes

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