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Record W2314929224 · doi:10.1021/cb500880f

Biophysical and Biological Characterization of Hairpin and Molecular Beacon RNase H Active Antisense Oligonucleotides

2015· article· en· W2314929224 on OpenAlexaff
Michael E. Østergaard, George Thomas, Erich Koller, Amber L. Southwell, Michael R. Hayden, Punit P. Seth

Bibliographic record

VenueACS Chemical Biology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsOligonucleotideRNase PRNAHuntingtinRNase HNucleic acidMolecular beaconGene silencingCleavage (geology)ChemistryCell biologyHuntingtin ProteinBiologySmall hairpin RNABiophysicsMolecular biologyBiochemistryDNAGene

Abstract

fetched live from OpenAlex

Antisense oligonucleotides (ASOs) are single stranded, backbone modified nucleic acids, which mediate cleavage of complementary RNA by directing RNase H cleavage in cell culture and in animals. It has generally been accepted that the single stranded state in conjunction with the phosphorothioate modified backbone is necessary for cellular uptake and transport to the active compartment. Herein, we examine the effect of using hairpin structured ASOs to (1) determine if an ASO agent requires a single stranded conformation for efficient RNA knock down, (2) use a fluorophore-quencher labeled ASO to evaluate which moieties the ASO interacts with in cells and examine if cellular distribution can be determined with such probes, and (3) evaluate if self-structured ASOs can improve allele selective silencing between closely related huntingtin alleles. We show that hairpin shaped ASOs can efficiently down-regulate RNA in vitro, but potency correlates strongly negatively with increasing stability of the hairpin structure. Furthermore, self-structured ASOs can efficiently reduce huntingtin mRNA in the central nervous system of mice.

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 score0.005
Threshold uncertainty score0.423

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 head0.017
GPT teacher head0.269
Teacher spread0.253 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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