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Record W2151554822 · doi:10.1038/mtna.2011.3

Systemic RNAi-mediated Gene Silencing in Nonhuman Primate and Rodent Myeloid Cells

2012· article· en· W2151554822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Therapy — Nucleic Acids · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of British Columbia
FundersNational Heart, Lung, and Blood InstituteAlnylam Pharmaceuticals
KeywordsGene silencingRNA interferenceSmall interfering RNAImmune systemMyeloidBiologyCancer researchIn vivoInflammationImmunologyMedicineRNAGeneGenetics

Abstract

fetched live from OpenAlex

Leukocytes are central regulators of inflammation and the target cells of therapies for key diseases, including autoimmune, cardiovascular, and malignant disorders. Efficient in vivo delivery of small interfering RNA (siRNA) to immune cells could thus enable novel treatment strategies with broad applicability. In this report, we develop systemic delivery methods of siRNA encapsulated in lipid nanoparticles (LNP) for durable and potent in vivo RNA interference (RNAi)-mediated silencing in myeloid cells. This work provides the first demonstration of siRNA-mediated silencing in myeloid cell types of nonhuman primates (NHPs) and establishes the feasibility of targeting multiple gene targets in rodent myeloid cells. The therapeutic potential of these formulations was demonstrated using siRNA targeting tumor necrosis factor-α (TNFα) which induced substantial attenuation of disease progression comparable to a potent antibody treatment in a mouse model of rheumatoid arthritis (RA). In summary, we demonstrate a broadly applicable and therapeutically relevant platform for silencing disease genes in immune cells.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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