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Record W2316742416 · doi:10.1089/nat.2013.0471

DNA-Aptamer Targeting Vimentin for Tumor Therapy <i>In Vivo</i>

2014· article· en· W2316742416 on OpenAlexaff
Tatyana N. Zamay, Olga S. Kolovskaya, Yury E. Glazyrin, Galina S. Zamay, Светлана А. Кузнецова, Е. А. Спивак, Mohamed Wehbe, Anna Savitskaya, Olga A. Zubkova, Anastasia Kadkina, Xiaoyan Wang, Darija Muharemagic, Anna V. Dubynina, Yuliya Sheina, А. Б. Салмина, Maxim V. Berezovski, Anna S. Zamay

Bibliographic record

VenueNucleic Acid Therapeutics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAptamerIn vivoIntracellularArabinogalactanNucleic acidCancer cellCell biologyBiologyChemistryCancer researchCancerMolecular biologyBiochemistryPolysaccharide

Abstract

fetched live from OpenAlex

In recent years, new prospects for the use of nucleic acids as anticancer drugs have been discovered. Aptamers for intracellular targets can regulate cellular functions and cause cell death or proliferation. However, intracellular aptamers have limited use for therapeutic applications due to their low bioavailability. In this work, we selected DNA aptamers to cell organelles and nucleus of cancer cells, and showed that an aptamer NAS-24 binds to vimentin and causes apoptosis of mouse ascites adenocarcinoma cells in vitro and in vivo. To deliver the aptamer NAS-24 inside cells, natural polysaccharide arabinogalactan was used as a carrier reagent. The mixture of arabinogalactan and NAS-24 was injected intraperitonealy for 5 days into mice with adenocarcinoma and inhibited adenocarcinoma growth more effectively than free arabinogalactan or the aptamer alone. The use of aptamers to intracellular targets together with arabinogalactan becomes a promising approach for anticancer therapy.

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 score0.291
Threshold uncertainty score0.720

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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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

Citations51
Published2014
Admission routes1
Has abstractyes

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