Doxorubicin delivery by pYEEIE peptide-functionalized rhodiola rosea-derived exosome-like nanovesicles for targeted melanoma therapy.

Introduction: Melanoma is the most common cause of skin cancer-related deaths due to its aggressive nature. Plant-derived exosome-like nanovesicles (PELNs) are promising natural nanoparticles for therapeutic applications owing to their biocompatibility and diverse bioactive components. However, research on Rhodiola rosea-derived exosome-like nanovesicles (RELNs) remains limited.

Functionalized turmeric nanovesicles for precision delivery of doxorubicin in colorectal carcinoma treatment.

Nanoscale vesicles have emerged as promising biocompatible vehicles for precision drug delivery, owing to their inherent therapeutic properties and versatile structural configurations. This study introduces an innovative biomanufacturing strategy utilizing curcumin-extracted nanovesicles (TNVs) conjugated with a cancer-selective peptide and encapsulated with doxorubicin to optimize therapeutic outcomes in colorectal malignancies. TNVs were purified through refined ultracentrifugation protocols, demonstrating uniform saucer-shaped morphology with an average size of 162.

Attention-Linear Trajectory Prediction.

Recently, a large number of Transformer-based solutions have emerged for the trajectory prediction task, but there are shortcomings in the effectiveness of Transformers in trajectory prediction. Specifically, while position encoding preserves some of the ordering information, the self-attention mechanism at the core of the Transformer has its alignment invariance that leads to the loss of temporal information, which is crucial for trajectory prediction. For this reason, we design a simple and efficient strategy for temporal information extraction and prediction of trajectory sequences using the self-attention mechanism and linear layers.