Results 61 to 70 of about 248,234 (269)
Modelling stem cell differentiation related processes—A practical overview for biologists
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
AutoSegNet: An Automated Neural Network for Image Segmentation
Neural Architecture Search (NAS) has drawn significant attention as a tool for automatically constructing deep neural networks. The generated neural networks are mainly applied for image classification, and natural language processing. However, there are
Zhimin Xu +4 more
doaj +1 more source
Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta +3 more
wiley +1 more source
Image Segmentation Based on Deep Learning:A Survey [PDF]
Image segmentation is a fundamental task in computer vision and its main purpose is to extract meaningful and cohe-rent regions from the image input.Over the years,a wide variety oftechniques have been developed in the field of image segmentation ...
HUANG Wenke, TENG Fei, WANG Zidan, FENG Li
doaj +1 more source
Structure‐forward targeting of claudins with synthetic binders
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley +1 more source
Lung image segmentation via generative adversarial networks
IntroductionLung image segmentation plays an important role in computer-aid pulmonary disease diagnosis and treatment.MethodsThis paper explores the lung CT image segmentation method by generative adversarial networks.
Jiaxin Cai +4 more
doaj +1 more source
Lost in the Vaso‐Occlusion: A Patient's Abdominal Pain Returns With a Vengeance
Pediatric Blood &Cancer, EarlyView.
Dunia Hatabah +5 more
wiley +1 more source
Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas +4 more
wiley +1 more source
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Adaptive scale segmentation algorithm for polarimetric SAR image
Polarimetric SAR (PolSAR) data can be characterised by scattering matrix, which contains four elements. It is difficult to merge all the elements of the scattering matrix for segmentation.
Yifan Xu, Aifang Liu, Long Huang
doaj +1 more source

