Systemic RNAi-mediated Gene Silencing in Nonhuman Primate and Rodent Myeloid Cells
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".