Carbon Monoxide Protects against Hepatic Ischemia/Reperfusion Injury via ROS-Dependent Akt Signaling and Inhibition of Glycogen Synthase Kinase 3β

Carbon monoxide (CO) may exert important roles in physiological and pathophysiological states through the regulation of cellular signaling pathways. CO can protect organ tissues from ischemia/reperfusion (I/R) injury by modulating intracellular redox status and by inhibiting inflammatory, apoptotic, and proliferative responses. However, the cellular mechanisms underlying the protective effects of CO in organ I/R injury remain incompletely understood. In this study, a murine model of hepatic warm I/R injury was employed to assess the role of glycogen synthase kinase-3 (GSK3) and phosphatidylinositol 3-kinase (PI3K)-dependent signaling pathways in the protective effects of CO against inflammation and injury. Inhibition of GSK3 through the PI3K/Akt pathway played a crucial role in CO-mediated protection. CO treatment increased the phosphorylation of Akt and GSK3-beta (GSK3β) in the liver after I/R injury. Furthermore, administration of LY294002, an inhibitor of PI3K, compromised the protective effect of CO and decreased the level of phospho-GSK3β after I/R injury. These results suggest that CO protects against liver damage by maintaining GSK3β phosphorylation, which may be mediated by the PI3K/Akt signaling pathway. Our study provides additional support for the therapeutic potential of CO in organ injury and identifies GSK3β as a therapeutic target for CO in the amelioration of hepatic injury

Rice Mitogen-Activated Protein Kinase Interactome Analysis Using the Yeast Two-Hybrid System

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Stochastic electrotransport selectively enhances the transport of highly electromobile molecules

Nondestructive chemical processing of porous samples such as fixed biological tissues typically relies on molecular diffusion. Diffusion into a porous structure is a slow process that significantly delays completion of chemical processing. Here, we present a novel electrokinetic method termed stochastic electrotransport for rapid nondestructive processing of porous samples. This method uses a rotational electric field to selectively disperse highly electromobile molecules throughout a porous sample without displacing the low-electromobility molecules that constitute the sample. Using computational models, we show that stochastic electrotransport can rapidly disperse electromobile molecules in a porous medium. We apply this method to completely clear mouse organs within 1–3 days and to stain them with nuclear dyes, proteins, and antibodies within 1 day. Our results demonstrate the potential of stochastic electrotransport to process large and dense tissue samples that were previously infeasible in time when relying on diffusion.Simons Foundation. Postdoctoral FellowshipLife Sciences Research FoundationBurroughs Wellcome Fund (Career Awards at the Scientific Interface)Searle Scholars ProgramMichael J. Fox Foundation for Parkinson's ResearchUnited States. Defense Advanced Research Projects AgencyJPB FoundationNational Institutes of Health (U.S.)National Institutes of Health (U.S.) (Grant 1-U01-NS090473-01

Lightweight Monocular Depth Estimation via Token-Sharing Transformer

Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera can be deployable at a low cost and compact size. Due to its significant and growing needs, many lightweight monocular depth estimation networks have been proposed for mobile robotics systems. While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently. However, massive parameters and large computational costs in the Transformer disturb the deployment to embedded devices. In this paper, we present a Token-Sharing Transformer (TST), an architecture using the Transformer for monocular depth estimation, optimized especially in embedded devices. The proposed TST utilizes global token sharing, which enables the model to obtain an accurate depth prediction with high throughput in embedded devices. Experimental results show that TST outperforms the existing lightweight monocular depth estimation methods. On the NYU Depth v2 dataset, TST can deliver depth maps up to 63.4 FPS in NVIDIA Jetson nano and 142.6 FPS in NVIDIA Jetson TX2, with lower errors than the existing methods. Furthermore, TST achieves real-time depth estimation of high-resolution images on Jetson TX2 with competitive results.Comment: ICRA 202

Autophagy deficiency leads to protection from obesity and insulin resistance by inducing Fgf21 as a mitokine

Despite growing interest and a recent surge in papers, the role of autophagy in glucose and lipid metabolism is unclear. We produced mice with skeletal muscle–specific deletion of Atg7 (encoding autophagy-related 7). Unexpectedly, these mice showed decreased fat mass and were protected from diet-induced obesity and insulin resistance; this phenotype was accompanied by increased fatty acid oxidation and browning of white adipose tissue (WAT) owing to induction of fibroblast growth factor 21 (Fgf21). Mitochondrial dysfunction induced by autophagy deficiency increased Fgf21 expression through induction of Atf4, a master regulator of the integrated stress response. Mitochondrial respiratory chain inhibitors also induced Fgf21 in an Atf4-dependent manner. We also observed induction of Fgf21, resistance to diet-induced obesity and amelioration of insulin resistance in mice with autophagy deficiency in the liver, another insulin target tissue. These findings suggest that autophagy deficiency and subsequent mitochondrial dysfunction promote Fgf21 expression, a hormone we consequently term a 'mitokine', and together these processes promote protection from diet-induced obesity and insulin resistance

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. © 2016 Optical Society of America.1