Broussonetia papyrifera Root Bark Extract Exhibits Anti-inflammatory Effects on Adipose Tissue and Improves Insulin Sensitivity Potentially Via AMPK Activation

The chronic low-grade inflammation in adipose tissue plays a causal role in obesity-induced insulin resistance and its associated pathophysiological consequences. In this study, we investigated the effects of extracts of Broussonetia papyrifera root bark (PRE) and its bioactive components on inflammation and insulin sensitivity. PRE inhibited TNF-alpha-induced NF-kappa B transcriptional activity in the NF-kappa B luciferase assay and pro-inflammatory genes' expression by blocking phosphorylation of I kappa B and NF-kappa B in 3T3-L1 adipocytes, which were mediated by activating AMPK. Ten-week-high fat diet (HFD)-fed C57BL6 male mice treated with PRE had improved glucose intolerance and decreased inflammation in adipose tissue, as indicated by reductions in NF-kappa B phosphorylation and pro-inflammatory genes' expression. Furthermore, PRE activated AMP-activated protein kinase (AMPK) and reduced lipogenic genes' expression in both adipose tissue and liver. Finally, we identified broussoflavonol B (BF) and kazinol J (KJ) as bioactive constituents to suppress pro-inflammatory responses via activating AMPK in 3T3-L1 adipocytes. Taken together, these results indicate the therapeutic potential of PRE, especially BF or KJ, in metabolic diseases such as obesity and type 2 diabetes

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

General Chemical Reaction Network Theory for Olfactory Sensing Based on G-Protein-Coupled Receptors : Elucidation of Odorant Mixture Effects and Agonist-Synergist Threshold

This work presents a general chemical reaction network theory for olfactory sensing processes that employ G-protein-coupled receptors as olfactory receptors (ORs). The theory is applicable to general mixtures of odorants and an arbitrary number of ORs. Reactions of ORs with G-proteins, both in the presence and the absence of odorants, are explicitly considered. A unique feature of the theory is the definition of an odor activity vector consisting of strengths of odorant-induced signals from ORs relative to those due to background G-protein activity in the absence of odorants. It is demonstrated that each component of the odor activity defined this way reduces to a Michaelis-Menten form capable of accounting for cooperation or competition effects between different odorants. The main features of the theory are illustrated for a two-odorant mixture. Known and potential mixture effects, such as suppression, shadowing, inhibition, and synergy are quantitatively described. Effects of relative values of rate constants, basal activity, and G-protein concentration are also demonstrated

Efficient and Privacy Preserving Group Signature for Federated Learning

Federated Learning (FL) is a Machine Learning (ML) technique that aims to reduce the threats to user data privacy. Training is done using the raw data on the users' device, called clients, and only the training results, called gradients, are sent to the server to be aggregated and generate an updated model. However, we cannot assume that the server can be trusted with private information, such as metadata related to the owner or source of the data. So, hiding the client information from the server helps reduce privacy-related attacks. Therefore, the privacy of the client's identity, along with the privacy of the client's data, is necessary to make such attacks more difficult. This paper proposes an efficient and privacy-preserving protocol for FL based on group signature. A new group signature for federated learning, called GSFL, is designed to not only protect the privacy of the client's data and identity but also significantly reduce the computation and communication costs considering the iterative process of federated learning. We show that GSFL outperforms existing approaches in terms of computation, communication, and signaling costs. Also, we show that the proposed protocol can handle various security attacks in the federated learning environment

A Feasibility Study on the Application of TVDI on Accessing Wildfire Danger in the Korean Peninsula

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation

Anti-diabetic effect of Cyclo-His-Pro (CHP)-enriched yeast hydrolysate in streptozotocin-induced diabetic mice

The present study was designed to investigate the hypoglycemic effects of the daily oral dose of 0.50 to 0.75 g/kg of yeast hydrolysate (YH) containing high Cyclo-His-Pro (51.0 mg CHP/g YH) on normal and streptozotocin (STZ)-induced diabetic rats for 14 days. In STZ-induced diabetic rats, after administrations of the YH for 14 days, the body weight gain was significantly increased in dose dependent manner, and the plasma glucose levels were decreased approximately (60%) as compared to the STZ induced diabetic control group. Glucose level showed significant differences between the diabetic control (DC) and the YH administered groups in oral glucose tolerance test (OGTT) (P<0.05). Results of the OGTT showed a significant decrease in the area under curve (AUC) value of YH supplemented groups as compared to the DC group. The present data suggests that the CHP-enriched YH has potential anti-diabetic effect, which can help in the cure and management of diabetes.Keywords: Yeast hydrolysate, Cyclo-His-Pro (CHP), diabetes, streptozotocin.African Journal of Biotechnology Vol. 12(35), pp. 5473-547

Deep tissue space-gated microscopy via acousto-optic interaction

© 2020, The Author(s).To extend the imaging depth of high-resolution optical microscopy, various gating operations—confocal, coherence, and polarization gating—have been devised to filter out the multiply scattered wave. However, the imaging depth is still limited by the multiply scattered wave that bypasses the existing gating operations. Here, we present a space gating method, whose mechanism is independent of the existing methods and yet effective enough to complement them. Specifically, we reconstruct an image only using the ballistic wave that is acousto-optically modulated at the object plane. The space gating suppresses the multiply scattered wave by 10–100 times in a highly scattering medium, and thus enables visualization of the skeletal muscle fibers in whole-body zebrafish at 30 days post fertilization. The space gating will be an important addition to optical-resolution microscopy for achieving the ultimate imaging depth set by the detection limit of ballistic wav