Results 81 to 90 of about 1,639,507 (316)
RIPK4 function interferes with melanoma cell adhesion and metastasis
RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski +9 more
wiley +1 more source
Topological Properties of Neuromorphic Nanowire Networks
Graph theory has been extensively applied to the topological mapping of complex networks, ranging from social networks to biological systems. Graph theory has increasingly been applied to neuroscience as a method to explore the fundamental structural and
Alon Loeffler +8 more
doaj +1 more source
The convolution operator at the core of many modern neural architectures can effectively be seen as performing a dot product between an input matrix and a filter. While this is readily applicable to data such as images, which can be represented as regular grids in the Euclidean space, extending the convolution operator to work on graphs proves more ...
Cosmo, Luca +6 more
openaire +4 more sources
Metformin mediates mitochondrial quality control in Leber's hereditary optic neuropathy (LHON) fibroblasts carrying mtDNA mutations. At therapeutic levels, metformin activates AMPK signaling to restore mitochondrial dynamics by promoting fusion and restraining fission, while preserving mitochondrial mass, enhancing autophagy/mitophagy and biogenesis ...
Chatnapa Panusatid +3 more
wiley +1 more source
Graph Convolutional Network for 3D Object Pose Estimation in a Point Cloud
Graph Neural Networks (GNNs) are neural networks that learn the representation of nodes and associated edges that connect it to every other node while maintaining graph representation.
Tae-Won Jung +5 more
doaj +1 more source
Stochastic graph recurrent neural network
Representation learning over graph structure data has been widely studied due to its wide application prospects. However, previous methods mainly focus on static graphs while many real-world graphs evolve over time. Modeling such evolution is important for predicting properties of unseen networks.
Yan, Tijin +3 more
openaire +2 more sources
A tri‐culture of iPSC‐derived neurons, astrocytes, and microglia treated with ferroptosis inducers as an Induced ferroptosis model was characterized by scRNA‐seq, cell survival, and cytokine release assays. This analysis revealed diverse microglial transcriptomic changes, indicating that the system captures key aspects of the complex cellular ...
Hongmei Lisa Li +6 more
wiley +1 more source
Identifying influential nodes is a key research topic in complex networks, and there have been many studies based on complex networks to explore the influence of nodes.
Ying Xi, Xiaohui Cui
doaj +1 more source
Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz +3 more
wiley +1 more source
MGATs: Motif-Based Graph Attention Networks
In recent years, graph convolutional neural networks (GCNs) have become a popular research topic due to their outstanding performance in various complex network data mining tasks.
Jinfang Sheng +3 more
doaj +1 more source

