Exploring the Potential of siRNA Delivery in Acute Myeloid Leukemia for Therapeutic Silencing
Bibliographic record
Abstract
We investigated the feasibility of using siRNA therapy for acute myeloid leukemia (AML) by developing macromolecular carriers that facilitated intracellular delivery of siRNA. The carriers were derived from low-molecular-weight (<2 kDa) polyethyleneimine (PEI) and modified with a range of aliphatic lipids. We identified linoleic acid and lauric acid-modified PEI as optimal carriers for siRNA delivery to AML cell lines KG1 and KG1a, as well as AML patient-derived mononuclear cells. As they have been proven to be potent targets in the treatment of AML, we examined the silencing of BCL2L12 and survivin and showed how it leads to the decrease in proliferation of KG1 and stem-cell-like KG1a cells. By optimizing the transfection schedule, we were able to enhance the effect of the siRNAs on proliferation over a period of 10 days. We additionally showed that with proper modifications of PEI, other genes, including MAP2K3, CDC20, and SOD-1, could be targeted to decrease the proliferation of AML cells. Our studies demonstrated the versatility of siRNA delivery with modified PEI to elicit an effect in leukemic cells that are difficult to transfect, offering an alternative to conventional drugs for more precise and targeted treatment options.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".