Extraction of Features for Time Series Classification Using Noise Injection.

Time series data often display complex, time-varying patterns, which pose significant challenges for effective classification due to data variability, noise, and imbalance. Traditional time series classification techniques frequently fall short in addressing these issues, leading to reduced generalization performance. Therefore, there is a need for innovative methodologies to enhance data diversity and quality.

Synthesis and evaluation of nicotinamide derivative as anti-angiogenic agents.

Previously, we have found that BRN-103, a nicotinamide derivative, inhibits vascular endothelial growth factor (VEGF)-mediated angiogenesis signaling in human endothelial cells. During our continuous efforts to identify more potent anti-angiogenic agents, we synthesized various nicotinamide derivatives and evaluated their anti-angiogenic effects. We found that 2-{1-[1-(6-chloro-5-fluoropyrimidin-4-yl)ethyl]piperidin-4-ylamino}-N-(3-chlorophenyl) pyridine-3-carboxamide (BRN-250) significantly inhibited human umbilical vascular endothelial cells (HUVECs) proliferation, migration, tube formation, and microvessel growth in a concentration range of 10-100 nM.

BRN-103, a novel nicotinamide derivative, inhibits VEGF-induced angiogenesis and proliferation in human umbilical vein endothelial cells.

Anti-angiogenesis is regarded as an effective strategy for cancer treatment, and vascular endothelial growth factor (VEGF) plays a key role in the regulations of angiogenesis and vasculogenesis. In the present study, the authors synthesized five novel nicotinamide derivatives which structurally mimic the receptor tyrosine kinase inhibitor sunitinib and evaluated their anti-angiogenic effects. Transwell migration assays revealed that 2-(1-benzylpiperidin-4-yl) amino-N-(3-chlorophenyl) nicotinamide (BRN-103), among the five derivatives most potently inhibited VEGF-induced human umbilical vein endothelial cells (HUVECs).