Hyaluronan decorated layer-by-layer assembled lipid nanoparticles for miR-181a delivery in glioblastoma treatment
Bibliographic record
Abstract
Glioblastoma multiforme (GBM) is the most common and lethal primary brain cancer. Current pharmacological interventions marginally increase the 12-month overall survival of patients with GBM. Among the novel therapeutic strategies being pursued, micro-RNAs, a class of non-coding RNAs, are receiving considerable attention for their regulation of several pathways implicated in tumorigenesis and survival. Notably, microRNA-181a-5p (miR-181a) has consistently been reported to be downregulated in GBM clinical samples, and its overexpression negatively affects tumor growth both in vitro and in vivo. To improve the delivery of miR-181a to GBM cells, we sought to develop a modified lipid-based nanocarrier capable of encapsulating and delivering miR-181a to GBM cells in vitro and in vivo. Optimized ionizable-lipid containing lipid nanoparticles (LNP) were constructed by covering the miR-181a-loaded LNP with alternating layers of miR-181a, poly-l-arginine and hyaluronic acid through the layer-by-layer technique. The resulting hyaluronan-decorated lipid nanoparticles (HA-LNP) targeted GBM cells more efficiently than non-modified LNP and mediated siRNA and miRNA transfection in vitro. Finally, delivery of miR-181a by HA-LNP induced significant cellular death of U87 GBM cells in vitro and delayed tumor growth in an in vivo subcutaneous tumor model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".