Vascular protection by ethanol extract of Morus alba root bark: Endothelium-dependent relaxation of rat aorta and decrease of smooth muscle cell migration and proliferation

Copyright © 2018 Nisha Panth et al. This is an open access article distributed under the Creative Commons Attribution License Morus alba (white mulberry) is native to the northern part of Korea and popularly used as a traditional medicine due to its numerous health benefits against human's disease. However, the possibility that M. alba may also affect the cardiovascular system remains unexplored. This study sought to investigate the vascular protective effects of the root bark extract of M. alba (MAE). Vascular reactivity was performed in organ baths using isolated rat thoracic aorta, while platelet derived growth factor (PDGF) induced proliferation and migration of vascular smooth muscle cells (VSMCs) were studied by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) and wound healing assay, respectively. MAE evoked a concentration dependent vasorelaxation following endothelium-dependent pathway. However, vessel relaxations in response to MAE were markedly reduced after endothelium removal; treatment of endothelial nitric oxide synthase inhibitor, guanylyl cyclase inhibitor, and nonspecific potassium channel inhibitor, however, was not altered by cyclooxygenase inhibitor. Furthermore, MAE also significantly blunted contractile response to vasoconstrictor agent, phenylephrine. Taken together, the current evidence revealed that MAE is a potent endothelium-dependent vasodilator and this effect was involved in, at least in part, nitric oxide cyclic-guanosine monophosphate (NO-cGMP) pathway in combination with potassium (K + ) channel activation. Moreover, MAE inhibited proliferation and migration of VSMCs induced by PDGF. Therefore, MAE could be a promising candidate of natural medicine for preventing and controlling cardiovascular diseases linked with endothelial dysfunction

Extracting the Groupwise Core Structural Connectivity Network: Bridging Statistical and Graph-Theoretical Approaches

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuro-science. Recent evidence suggests there's a tightly connected network shared between humans. Obtaining this network will, among many advantages , allow us to focus cognitive and clinical analyses on common connections, thus increasing their statistical power. In turn, knowledge about the common network will facilitate novel analyses to understand the structure-function relationship in the brain. In this work, we present a new algorithm for computing the core structural connectivity network of a subject sample combining graph theory and statistics. Our algorithm works in accordance with novel evidence on brain topology. We analyze the problem theoretically and prove its complexity. Using 309 subjects, we show its advantages when used as a feature selection for connectivity analysis on populations, outperforming the current approaches

Investigation of the IoT Device Lifetime with Secure Data Transmission

This paper represents the approach for estimation of the lifetime of the IoT end devices. The novelty of this approach is in the taking into account not only the energy consumption for data transmission, but also for ensuring the security by using the encryption algorithms. The results of the study showed the effect of using data encryption during transmission on the device lifetime depending on the key length and the principles of the algorithm used

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents

RNA-seq reveals conservation of function among the yolk sacs of human, mouse, and chicken

The yolk sac is phylogenetically the oldest of the extraembryonic membranes. The human embryo retains a yolk sac, which goes through primary and secondary phases of development, but its importance is controversial. Although it is known to synthesize proteins, its transport functions are widely considered vestigial. Here, we report RNA-sequencing (RNA-seq) data for the human and murine yolk sacs and compare those data with data for the chicken. We also relate the human RNA-seq data to proteomic data for the coelomic fluid bathing the yolk sac. Conservation of transcriptomes across the species indicates that the human secondary yolk sac likely performs key functions early in development, particularly uptake and processing of macro- and micronutrients, many of which are found in coelomic fluid. More generally, our findings shed light on evolutionary mechanisms that give rise to complex structures such as the placenta. We identify genetic modules that are conserved across mammals and birds, suggesting these modules are part of the core amniote genetic repertoire and are the building blocks for both oviparous and viviparous reproductive modes. We propose that although a choriovitelline placenta is never established physically in the human, the placental villi, the exocoelomic cavity, and the secondary yolk sac function together as a physiological equivalent.M.G.E. is the recipient of a Research Fellowship from St. John’s College, University of Cambridge. This study was supported by Medical Research Council Grant MR/L020041/1

Field evidence for the upwind velocity shift at the crest of low dunes

Wind topographically forced by hills and sand dunes accelerates on the upwind (stoss) slopes and reduces on the downwind (lee) slopes. This secondary wind regime, however, possesses a subtle effect, reported here for the first time from field measurements of near-surface wind velocity over a low dune: the wind velocity close to the surface reaches its maximum upwind of the crest. Our field-measured data show that this upwind phase shift of velocity with respect to topography is found to be in quantitative agreement with the prediction of hydrodynamical linear analysis for turbulent flows with first order closures. This effect, together with sand transport spatial relaxation, is at the origin of the mechanisms of dune initiation, instability and growth.Comment: 13 pages, 6 figures. Version accepted for publication in Boundary-Layer Meteorolog

A Study of Brain Networks Associated with Swallowing Using Graph-Theoretical Approaches

Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI) was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, 23.1±1.52 years of age). To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia. © 2013 Luan et al

Prediction and Topological Models in Neuroscience

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone

Genetic relationships and evolution in Cucurbita pepo (pumpkin, squash, gourd) as revealed by simple sequence repeat polymorphisms

Genetic relationships among 104 accessions of Cucurbita pepo were assessed from polymorphisms in 134 SSR (microsatellite) and four SCAR loci, yielding a total of 418 alleles, distributed among all 20 linkage groups. Genetic distance values were calculated, a dendrogram constructed, and principal coordinate analyses conducted. The results showed 100 of the accessions as distributed among three clusters representing each of the recognized subspecies, pepo, texana, and fraterna. The remaining four accessions, all having very small, round, striped fruits, assumed central positions between the two cultivated subspecies, pepo and texana, suggesting that they are relicts of undescribed wild ancestors of the two domesticated subspecies. In both, subsp. texana and subsp. pepo, accessions belonging to the same cultivar-group (fruit shape) associated with one another. Within subsp. pepo, accessions grown for their seeds or that are generalists, used for both seed and fruit consumption, assumed central positions. Specialized accessions, grown exclusively for consumption of their young fruits, or their mature fruit flesh, or seed oil extraction, tended to assume outlying positions, and the different specializations radiated outward from the center in different directions. Accessions of the longest-fruited cultivar-group, Cocozelle, radiated bidirectionally, indicating independent selection events for long fruits in subsp. pepo probably driven by a common desire to consume the young fruits. Among the accessions tested, there was no evidence for crossing between subspecies after domestication