Hepatic stellate cells (HSCs) transdifferentiate into myofibroblasts during liver fibrosis and exhibit increased glycolysis. Phosphorylated focal adhesion kinase (FAK) (pY397-FAK) promotes monocarboxylate transporter 1 (MCT-1) expression in HSCs to increase aerobic glycolysis and cause liver fibrosis. A combined multiomics analysis of C57BL/6 mice with tetrachloromethane (CCl)-induced liver fibrosis was performed to identify the downstream FAK signaling pathway.
View Article and Find Full Text PDFHighly myopic optic nerve head (ONH) abnormalities encompass a series of complications resulting from the stretching of papillary and peripapillary structures during significant axial elongation. The morphological changes in the ONH typically initiate with disk tilting or rotation, progressing to PHOMS and PPA. Tissue defects in each layer manifest as focal lamina cribrosa defects (FLDs), peripapillary intrachoroidal cavitations (PICCs), and acquired pits of the optic nerve (APON).
View Article and Find Full Text PDFActivation of hepatic stellate cells (HSCs) is critical in the progression of liver fibrosis and is a promising target for anti-hepatic fibrosis drug development. Moreover, effective pharmacological interventions targeting this pathomechanism are scarce. Our study confirms the therapeutic value of β-sitosterol, a major constituent of Thunb, in hepatic fibrosis and identifies its underlying mechanisms.
View Article and Find Full Text PDFDiamide insecticides have always been a hot research topic in the field of pesticides. To further discover new compounds with high activity and safety, indane and its analogs were introduced into chlorantraniliprole, and a battery of chlorfenil derivatives, including indane and its analogs, were designed and prepared for biological testing. Their characterization and verification were carried out through nuclear magnetic resonance (NMR) and high-resolution mass spectrometry (HRMS).
View Article and Find Full Text PDFBackground: Hepatic stellate cell (HSC) hyperactivation is a central link in liver fibrosis development. HSCs perform aerobic glycolysis to provide energy for their activation. Focal adhesion kinase (FAK) promotes aerobic glycolysis in cancer cells or fibroblasts, while FAK-related non-kinase (FRNK) inhibits FAK phosphorylation and biological functions.
View Article and Find Full Text PDFis an opportunistic pathogen that causes serious infections and hospital-acquired pneumonia in immunocompromised patients. accounts for up to 20% of all cases of hospital-acquired pneumonia, with an attributable mortality rate of ~30-40%. The poor clinical outcome of -induced pneumonia is ascribed to its ability to disrupt lung barrier integrity, leading to the development of lung edema and bacteremia.
View Article and Find Full Text PDFBackground: Hepatic stellate cells (HSCs) are the key effector cells mediating the occurrence and development of liver fibrosis, while aerobic glycolysis is an important metabolic characteristic of HSC activation. Transforming growth factor-β1 (TGF-β1) induces aerobic glycolysis and is a driving factor for metabolic reprogramming. The occurrence of glycolysis depends on a high glucose uptake level.
View Article and Find Full Text PDFVideos are used widely as the media platforms for human beings to touch the physical change of the world. However, we always receive the mixed sound from the multiple sound objects, and cannot distinguish and localize the sounds as the separate entities in videos. In order to solve this problem, a model named the Deep Multi-Modal Attention Network (DMMAN), is established to model the unconstrained video datasets for further finishing the sound source separation and event localization tasks in this paper.
View Article and Find Full Text PDFIdiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease without effective therapy. Animal models effectively reproducing IPF disease features are needed to study the underlying molecular mechanisms. Tree shrews are genetically, anatomically, and metabolically closer to humans than rodents or dogs; therefore, the tree shrew model presents a unique opportunity for translational research in lung fibrosis.
View Article and Find Full Text PDFBackground: Liver fibrosis is a refractory disease whose persistence can eventually induce cirrhosis or even liver cancer. Early liver fibrosis is reversible by intervention. As a member of the transforming growth factor-beta (TGF-β) superfamily, bone morphogenetic protein 7 (BMP7) has anti-liver fibrosis functions.
View Article and Find Full Text PDFComput Intell Neurosci
January 2020
The ensemble pruning system is an effective machine learning framework that combines several learners as experts to classify a test set. Generally, ensemble pruning systems aim to define a region of competence based on the validation set to select the most competent ensembles from the ensemble pool with respect to the test set. However, the size of the ensemble pool is usually fixed, and the performance of an ensemble pool heavily depends on the definition of the region of competence.
View Article and Find Full Text PDFInt J Neural Syst
October 2019
Neural networks are powerful computation tools for mimicking the human brain to solve realistic problems. Since spiking neural networks are a type of brain-inspired network, called the novel spiking system, Monitor-based Spiking Recurrent network (MbSRN), is derived to learn and represent patterns in this paper. This network provides a computational framework for memorizing the targets using a simple dynamic model that maintains biological plasticity.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
July 2019
Error functions are normally based on the distance between output spikes and target spikes in supervised learning algorithms for spiking neural networks (SNNs). Due to the discontinuous nature of the internal state of spiking neuron, it is challenging to ensure that the number of output spikes and target spikes kept identical in multispike learning. This problem is conventionally dealt with by using the smaller of the number of desired spikes and that of actual output spikes in learning.
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