Results 61 to 70 of about 256,120 (256)

Degradation mechanism of the von Willebrand factor A2 domain by nattokinase

FEBS Letters, EarlyView.
Nattokinase, a natto‐derived protease, exhibits potent antithrombotic effects. This study demonstrates that nattokinase directly cleaves the von Willebrand factor (vWF) A2 domain in vitro. Unlike the native regulator ADAMTS13, nattokinase degrades folded vWF independently of shear stress.
Ryuichi Hyakumoto, Masatomo So, Ayako Furukawa, Kenji Sugase   +3 more
wiley   +1 more source

Fast Superpixel Based Subspace Low Rank Learning Method for Hyperspectral Denoising

IEEE Access, 2018
Sequential data, such as video frames and event data, have been widely applied in the realworld. As a special kind of sequential data, hyperspectral images (HSIs) can be regarded as a sequence of 2-D images in the spectral dimension, which can be ...
Le Sun, Byeungwoo Jeon, Bushra Naz Soomro, Yuhui Zheng, Zebin Wu, Liang Xiao   +5 more
doaj   +1 more source

A Single-Image Noise Estimation Algorithm Based on Pixel-Level Low-Rank Low-Texture Patch and Principal Component Analysis

Sensors, 2022
Noise level is an important parameter for image denoising in many image-processing applications. We propose a noise estimation algorithm based on pixel-level low-rank, low-texture subblocks and principal component analysis for white Gaussian noise. First,
Yong Li, Chenguang Liu, Xiaoyu You, Jian Liu   +3 more
doaj   +1 more source

Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy

FEBS Letters, EarlyView.
The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson, Tomáš Gedeon, Mauricio Garcia Benitez, Campbell Putnam, William R. Harcombe, Radhakrishnan Mahadevan, Ashley E. Beck   +6 more
wiley   +1 more source

Structured Low Rank Approximation of a Bezout Matrix [PDF]

Mathematics in Computer Science, 2007
The task of determining the approximate greatest common divisor (GCD) of more than two univariate polynomials with inexact coefficients can be formulated as computing for a given Bezout matrix a new Bezout matrix of lower rank whose entries are near the corresponding entries of that input matrix. We present an algorithm based on a version of structured
Dongxia Sun, Lihong Zhi
openaire   +1 more source

Weighted Low Rank Matrix Approximation and Acceleration

CoRR, 2021
Low-rank matrix approximation is one of the central concepts in machine learning, with applications in dimension reduction, de-noising, multivariate statistical methodology, and many more. A recent extension to LRMA is called low-rank matrix completion (LRMC).
Elena Tuzhilina, Trevor Hastie
openaire   +2 more sources

Microbiome−host proteostasis crosstalk—An emerging perspective on mechanisms and interventions toward healthy longevity

FEBS Letters, EarlyView.
Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley   +1 more source

Dynamic Magnetic Resonance Imaging via Nonconvex Low-Rank Matrix Approximation

IEEE Access, 2017
Reconstruction of highly accelerated dynamic magnetic resonance imaging (MRI) is of crucial importance for the medical diagnosis. The application of general robust principal component analysis (RPCA) to MRI can increase imaging speed and efficiency ...
Fei Xu, Jingqi Han, Yongli Wang, Ming Chen, Yongyong Chen, Guoping He, Yunhong Hu   +6 more
doaj   +1 more source

Consistent independent low-rank matrix analysis for determined blind source separation

EURASIP Journal on Advances in Signal Processing, 2020
Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind source separation (BSS) in the determined situation (the number of microphones is greater than or equal to that of source signals). ILRMA achieves a great separation
Daichi Kitamura, Kohei Yatabe
doaj   +1 more source

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

FEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa, Shinya Sugimoto, Toshiro Sato   +2 more
wiley   +1 more source