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https://www.readbyqxmd.com/read/28915268/large-scale-cross-species-chemogenomic-platform-proposes-a-new-drug-discovery-strategy-of-veterinary-drug-from-herbal-medicines
#1
Chao Huang, Yang Yang, Xuetong Chen, Chao Wang, Yan Li, Chunli Zheng, Yonghua Wang
Veterinary Herbal Medicine (VHM) is a comprehensive, current, and informative discipline on the utilization of herbs in veterinary practice. Driven by chemistry but progressively directed by pharmacology and the clinical sciences, drug research has contributed more to address the needs for innovative veterinary medicine for curing animal diseases. However, research into veterinary medicine of vegetal origin in the pharmaceutical industry has reduced, owing to questions such as the short of compatibility of traditional natural-product extract libraries with high-throughput screening...
2017: PloS One
https://www.readbyqxmd.com/read/28915238/a-high-resolution-atlas-of-gene-expression-in-the-domestic-sheep-ovis-aries
#2
Emily L Clark, Stephen J Bush, Mary E B McCulloch, Iseabail L Farquhar, Rachel Young, Lucas Lefevre, Clare Pridans, Hiu Tsang, Chunlei Wu, Cyrus Afrasiabi, Mick Watson, C Bruce Whitelaw, Tom C Freeman, Kim M Summers, Alan L Archibald, David A Hume
Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset...
September 15, 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28910696/tissue-microstructure-estimation-using-a-deep-network-inspired-by-a-dictionary-based-framework
#3
Chuyang Ye
Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies...
September 6, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28904202/discrete-dynamical-modeling-of-influenza-infection-suggests-age-dependent-differences-in-immunity
#4
Ericka Keef, Li Ang Zhang, David Swigon, Alisa Urbano, G Bard Ermentrout, Michael Matuszewski, Franklin R Toapanta, Ted M Ross, Robert S Parker, Gilles Clermont
Immunosenescence, an age-related decline in immune function, is a major contributor to morbidity and mortality in the elderly. Older hosts exhibit delayed onset of immunity and prolonged inflammation after an infection, leading to excess damage and greater likelihood of death. Our study applies a rule-based model to infer which components of immune response are most changed in an aged host. Two groups of BALB/c mice (age 12-16 wks and 72-76 wks) were infected at 2 inocula: a survivable 50 PFU dose and a lethal 500 PFU dose...
September 13, 2017: Journal of Virology
https://www.readbyqxmd.com/read/28903485/editor-s-highlight-mechanistic-toxicity-tests-based-on-an-adverse-outcome-pathway-network-for-hepatic-steatosis
#5
Michelle M Angrish, Charlene A McQueen, Elaine Cohen-Hubal, Maribel Bruno, Yue Ge, Brian N Chorley
Risk assessors use liver endpoints in rodent toxicology studies to assess the safety of chemical exposures. Yet, rodent endpoints may not accurately reflect human responses. For this reason and others, human-based invitro models are being developed and anchored to adverse outcome pathways to better predict adverse human health outcomes. Here, a networked adverse outcome pathway-guided selection of biology-based assays for lipid uptake, lipid efflux, fatty acid oxidation, and lipid accumulation were developed...
September 1, 2017: Toxicological Sciences: An Official Journal of the Society of Toxicology
https://www.readbyqxmd.com/read/28891109/strengthening-community-mental-health-competence-a-realist-informed-case-study-from-dehradun-north-india
#6
Kaaren Mathias, Jeph Mathias, Isabel Goicolea, Michelle Kermode
Few accounts exist of programmes in low- and middle-income countries seeking to strengthen community knowledge and skills in mental health. This case study uses a realist lens to explore how a mental health project in a context with few mental health services, strengthened community mental health competence by increasing community knowledge, creating safer social spaces and engaging partnerships for action. We used predominantly qualitative methods to explore relationships between context, interventions, mechanisms and outcomes in the "natural setting" of a community-based mental health project in Dehradun district, Uttarakhand, North India...
September 11, 2017: Health & Social Care in the Community
https://www.readbyqxmd.com/read/28890691/predicting-intentions-of-a-familiar-significant-other-beyond-the-mirror-neuron-system
#7
Stephanie Cacioppo, Elsa Juan, George Monteleone
Inferring intentions of others is one of the most intriguing issues in interpersonal interaction. Theories of embodied cognition and simulation suggest that this mechanism takes place through a direct and automatic matching process that occurs between an observed action and past actions. This process occurs via the reactivation of past self-related sensorimotor experiences within the inferior frontoparietal network (including the mirror neuron system, MNS). The working model is that the anticipatory representations of others' behaviors require internal predictive models of actions formed from pre-established, shared representations between the observer and the actor...
2017: Frontiers in Behavioral Neuroscience
https://www.readbyqxmd.com/read/28888644/genetic-diversity-of-porcine-circovirus-type-2-pcv2-in-thailand-during-2009-2015
#8
Nattarat Thangthamniyom, Pradit Sangthong, Pariwat Poolperm, Narut Thanantong, Alongkot Boonsoongnern, Payuda Hansoongnern, Ploypailin Semkum, Nantawan Petcharat, Porntippa Lekcharoensuk
Porcine circovirus type 2 (PCV2), the essential cause of porcine circovirus associated disease (PCVAD), has evolved rapidly and it has been reported worldwide. However, genetic information of PCV2 in Thailand has not been available since 2011. Herein, we studied occurrence and genetic diversity of PCV2 in Thailand and their relationships to the global PCV2 based on ORF2 sequences. The results showed that 306 samples (44.09%) from 56 farms (80%) were PCV2 positive by PCR. Phylogenetic trees constructed by both neighbor-joining and Bayesian Inference yielded similar topology of the ORF2 sequences...
September 2017: Veterinary Microbiology
https://www.readbyqxmd.com/read/28887489/hardware-emulation-of-stochastic-p-bits-for-invertible-logic
#9
Ahmed Zeeshan Pervaiz, Lakshmi Anirudh Ghantasala, Kerem Yunus Camsari, Supriyo Datta
The common feature of nearly all logic and memory devices is that they make use of stable units to represent 0's and 1's. A completely different paradigm is based on three-terminal stochastic units which could be called "p-bits", where the output is a random telegraphic signal continuously fluctuating between 0 and 1 with a tunable mean. p-bits can be interconnected to receive weighted contributions from others in a network, and these weighted contributions can be chosen to not only solve problems of optimization and inference but also to implement precise Boolean functions in an inverted mode...
September 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28881992/image-based-spatiotemporal-causality-inference-for-protein-signaling-networks
#10
Xiongtao Ruan, Christoph Wülfing, Robert F Murphy
Motivation: Efforts to model how signaling and regulatory networks work in cells have largely either not considered spatial organization or have used compartmental models with minimal spatial resolution. Fluorescence microscopy provides the ability to monitor the spatiotemporal distribution of many molecules during signaling events, but as of yet no methods have been described for large scale image analysis to learn a complex protein regulatory network. Here we present and evaluate methods for identifying how changes in concentration in one cell region influence concentration of other proteins in other regions...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28878997/social-learning-in-otters
#11
Zosia Ladds, William Hoppitt, Neeltje J Boogert
The use of information provided by others to tackle life's challenges is widespread, but should not be employed indiscriminately if it is to be adaptive. Evidence is accumulating that animals are indeed selective and adopt 'social learning strategies'. However, studies have generally focused on fish, bird and primate species. Here we extend research on social learning strategies to a taxonomic group that has been neglected until now: otters (subfamily Lutrinae). We collected social association data on captive groups of two gregarious species: smooth-coated otters (Lutrogale perspicillata), known to hunt fish cooperatively in the wild, and Asian short-clawed otters (Aonyx cinereus), which feed individually on prey requiring extractive foraging behaviours...
August 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28873858/adaptive-sampling-technique-using-regression-modelling-and-fuzzy-inference-system-for-network-traffic
#12
Abdussalam Salama, Reza Saatchi, Derek Burke
Electronic-health relies on extensive computer networks to facilitate access and to communicate various types of information in the form of data packets. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of packets, examining their transmission parameters individually is not practical, especially when performed in real time. Sampling allows a subset of packets that accurately represents the original traffic to be chosen. In this study an adaptive sampling method based on regression and fuzzy inference system was developed...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28866483/a-multi-modal-discriminative-and-spatially-invariant-cnn-for-rgb-d-object-labeling
#13
Umar Asif, Mohammed Bennamoun, Ferdous Sohel
While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i...
August 30, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28861338/increased-default-mode-variability-is-related-to-reduced-task-performance-and-is-evident-in-adults-with-adhd
#14
Athanasia M Mowinckel, Dag Alnæs, Mads L Pedersen, Sigurd Ziegler, Mats Fredriksen, Tobias Kaufmann, Edmund Sonuga-Barke, Tor Endestad, Lars T Westlye, Guido Biele
Insufficient suppression and connectivity of the default mode network (DMN) is a potential mediator of cognitive dysfunctions across various disorders, including attention deficit/hyperactivity disorder (ADHD). However, it remains unclear if alterations in sustained DMN suppression, variability and connectivity during prolonged cognitive engagement are implicated in adult ADHD pathophysiology, and to which degree methylphenidate (MPH) remediates any DMN abnormalities. This randomized, double-blinded, placebo-controlled, cross-over clinical trial of MPH (clinicaltrials...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28860069/gernet-a-gene-regulatory-network-tool
#15
J S Dussaut, C A Gallo, F Cravero, M J Martínez, J A Carballido, I Ponzoni
Gene regulatory networks (GRNs) are crucial in every process of life since they govern the majority of the molecular processes. Therefore, the task of assembling these networks is highly important. In particular, the so called model-free approaches have an advantage modeling the complexities of dynamic molecular networks, since most of the gene networks are hard to be mapped with accuracy by any other mathematical model. A highly abstract model-free approach, called rule-based approach, offers several advantages performing data-driven analysis; such as the requirement of the least amount of data...
August 28, 2017: Bio Systems
https://www.readbyqxmd.com/read/28851837/rna-structure-inference-through-chemical-mapping-after-accidental-or-intentional-mutations
#16
Clarence Y Cheng, Wipapat Kladwang, Joseph D Yesselman, Rhiju Das
Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called "mutate-and-map read out through next-generation sequencing" (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling...
August 29, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28843214/constructing-fine-granularity-functional-brain-network-atlases-via-deep-convolutional-autoencoder
#17
Yu Zhao, Qinglin Dong, Hanbo Chen, Armin Iraji, Yujie Li, Milad Makkie, Zhifeng Kou, Tianming Liu
State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases...
August 18, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28841552/reflectance-and-natural-illumination-from-single-material-specular-objects-using-deep-learning
#18
Stamatios Georgoulis, Konstantinos Rematas, Tobias Ritschel, Efstratios Gavves, Mario Fritz, Luc Van Gool, Tinne Tuytelaars
In this paper, we present a method that estimates reflectance and illumination information from a single image depicting a single-material specular object from a given class under natural illumination. We follow a data-driven, learning-based approach trained on a very large dataset, but in contrast to earlier work we do not assume one or more components (shape, reflectance, or illumination) to be known. We propose a two-step approach, where we first estimate the object's reflectance map, and then further decompose it into reflectance and illumination...
August 22, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28838064/a-comparison-of-agent-based-models-and-the-parametric-g-formula-for-causal-inference
#19
COMPARATIVE STUDY
Eleanor J Murray, James M Robins, George R Seage, Kenneth A Freedberg, Miguel A Hernán
Decision-making requires choosing from treatments on the basis of correctly estimated outcome distributions under each treatment. In the absence of randomized trials, 2 possible approaches are the parametric g-formula and agent-based models (ABMs). The g-formula has been used exclusively to estimate effects in the population from which data were collected, whereas ABMs are commonly used to estimate effects in multiple populations, necessitating stronger assumptions. Here, we describe potential biases that arise when ABM assumptions do not hold...
July 15, 2017: American Journal of Epidemiology
https://www.readbyqxmd.com/read/28837810/defining-human-tyrosine-kinase-phosphorylation-networks-using-yeast-as-an-in-vivo-model-substrate
#20
Thomas Corwin, Jonathan Woodsmith, Federico Apelt, Jean-Fred Fontaine, David Meierhofer, Johannes Helmuth, Arndt Grossmann, Miguel A Andrade-Navarro, Bryan A Ballif, Ulrich Stelzl
Systematic assessment of tyrosine kinase-substrate relationships is fundamental to a better understanding of cellular signaling and its profound alterations in human diseases such as cancer. In human cells, such assessments are confounded by complex signaling networks, feedback loops, conditional activity, and intra-kinase redundancy. Here we address this challenge by exploiting the yeast proteome as an in vivo model substrate. We individually expressed 16 human non-receptor tyrosine kinases (NRTKs) in Saccharomyces cerevisiae and identified 3,279 kinase-substrate relationships involving 1,351 yeast phosphotyrosine (pY) sites...
August 23, 2017: Cell Systems
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