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showing 10 items of 14511 documents

Target Identification of Active Constituents of Shen Qi Wan to Treat Kidney Yang Deficiency Using Computational Target Fishing and Network Pharmacolo…

2019

Background: Kidney yang deficiency syndrome (KYDS) is one of the most common syndromes treated with traditional Chinese medicine (TCM) among elderly patients. Shen Qi Wan (SQW) has been effectively used in treating various diseases associated with KYDS for hundreds of years. However, due to the complex composition of SQW, the mechanism of action remains unknown. Purpose: To identify the mechanism of the SQW in the treatment of KYDS and determine the molecular targets of SQW. Methods: The potential targets of active ingredients in SQW were predicted using PharmMapper. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out using the …

0301 basic medicinePharmacology03 medical and health scienceschemistry.chemical_compoundtraditional Chinese medicinetranscriptomics0302 clinical medicinemedicinenetwork pharmacologyPharmacology (medical)HRASKEGGBlood urea nitrogenMAPK14Original ResearchPharmacologyCreatinineKidneylcsh:RM1-950phytotherapy030104 developmental biologymedicine.anatomical_structurelcsh:Therapeutics. PharmacologychemistryMechanism of action030220 oncology & carcinogenesisgene ontologypotential targetsmedicine.symptomProto-oncogene tyrosine-protein kinase SrcFrontiers in Pharmacology
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2019

Background: Focal dystonias are severe and disabling movement disorders of a still unclear origin. The structural brain networks associated with focal dystonia have not been well characterized. Here, we investigated structural brain network fingerprints in patients with blepharospasm (BSP) compared with those with hemifacial spasm (HFS), and healthy controls (HC). The patients were also examined following treatment with botulinum neurotoxin (BoNT). Methods: This study included matched groups of 13 BSP patients, 13 HFS patients, and 13 HC. We measured patients using structural-magnetic resonance imaging (MRI) at baseline and after one month BoNT treatment, at time points of maximal and minim…

0301 basic medicinePharmacologyDystoniaBrain networkMovement disordersbusiness.industryBlepharospasmFocal dystoniamedicine.diseaseBotulinum neurotoxin03 medical and health sciences030104 developmental biology0302 clinical medicineNeurologymedicineFocal DystoniasNeurology (clinical)medicine.symptombusinessNeuroscience030217 neurology & neurosurgeryTherapeutic Advances in Neurological Disorders
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Modeling Chronic Toxicity: A Comparison of Experimental Variability With (Q)SAR/Read-Across Predictions

2018

This study compares the accuracy of (Q)SAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs) from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar) algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain) are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended.

0301 basic medicinePharmacologyTraining setlazarbusiness.industrylcsh:RM1-950Pattern recognition010501 environmental sciences01 natural sciencesexperimental variability(Q)SAR03 medical and health sciences030104 developmental biologylcsh:Therapeutics. PharmacologySimilarity (network science)Pharmacology (medical)Artificial intelligencebusinessChronic toxicityLOAEL0105 earth and related environmental sciencesApplicability domainMathematicsread-acrossFrontiers in Pharmacology
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2019

Background: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. Methods: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network conne…

0301 basic medicinePharmacologybusiness.industryMultiple sclerosisGraph theoryNetwork sciencemedicine.disease03 medical and health sciences030104 developmental biology0302 clinical medicineNeurologyRelapsing remittingCortical networkStructural covariancemedicineNeurology (clinical)businessNeuroscience030217 neurology & neurosurgeryTherapeutic Advances in Neurological Disorders
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Stochastic sampling effects favor manual over digital contact tracing.

2020

Isolation of symptomatic individuals, tracing and testing of their nonsymptomatic contacts are fundamental strategies for mitigating the current COVID-19 pandemic. The breaking of contagion chains relies on two complementary strategies: manual reconstruction of contacts based on interviews and a digital (app-based) privacy-preserving contact tracing. We compare their effectiveness using model parameters tailored to describe SARS-CoV-2 diffusion within the activity-driven model, a general empirically validated framework for network dynamics. We show that, even for equal probability of tracing a contact, manual tracing robustly performs better than the digital protocol, also taking into accou…

0301 basic medicinePhysics - Physics and SocietyComputer scienceEpidemiologyScienceComplex networksFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)Tracingcomputer.software_genreGeneral Biochemistry Genetics and Molecular BiologyArticleSpecimen Handling03 medical and health sciences0302 clinical medicineHumans030212 general & internal medicineQuantitative Biology - Populations and EvolutionPandemicsCondensed Matter - Statistical Mechanicsstochastic modelProtocol (science)Stochastic ProcessesMultidisciplinaryStatistical Mechanics (cond-mat.stat-mech)Stochastic processDiagnostic Tests RoutineSARS-CoV-2QPopulations and Evolution (q-bio.PE)Sampling (statistics)COVID-19General ChemistryComplex networkModels TheoreticalNetwork dynamics030104 developmental biologyFOS: Biological sciencesScalabilityQuarantineData miningContact TracingcomputerContact tracingAlgorithmsNature communications
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Statistical characterization of deviations from planned flight trajectories in air traffic management

2016

Understanding the relation between planned and realized flight trajectories and the determinants of flight deviations is of great importance in air traffic management. In this paper we perform an in depth investigation of the statistical properties of planned and realized air traffic on the German airspace during a 28 day periods, corresponding to an AIRAC cycle. We find that realized trajectories are on average shorter than planned ones and this effect is stronger during night-time than daytime. Flights are more frequently deviated close to the departure airport and at a relatively large angle to destination. Moreover, the probability of a deviation is higher in low traffic phases. All the…

0301 basic medicinePhysics - Physics and SocietyEngineeringStrategy and ManagementFOS: Physical sciencesTransportationPhysics and Society (physics.soc-ph)Management Monitoring Policy and LawStability (probability)socio-technical complex systemAviation safety03 medical and health sciencesControl theory0502 economics and business11. SustainabilityAir traffic management complex networks trajectoriesSimulationRandomness050210 logistics & transportationbusiness.industry05 social sciencesAir traffic managementAir traffic controlSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)030104 developmental biologyMetric (mathematics)TrajectoryNull hypothesisbusinessLawair traffc managementJournal of Air Transport Management
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2016

The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown to obtain high quality mappings at the expense of long execution times. Finding fast yet accurate software solutions is of high importance to research, since availability and size of NGS datasets continue to increase. In this work we present an efficient parallelization approach for NGS short-read alignment on multi-core clusters. Our approach takes advantage of a distributed shared memory programming model based on the new UPC++ language. Experimental results using the CUSHAW3 alig…

0301 basic medicinePhysics020203 distributed computingMulti-core processorDistributed shared memoryMultidisciplinarySource codemedia_common.quotation_subjectNode (networking)02 engineering and technologyDynamic priority schedulingParallel computingBioinformatics03 medical and health sciences030104 developmental biologyScalability0202 electrical engineering electronic engineering information engineeringProgramming paradigmPartitioned global address spacemedia_commonPLOS ONE
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MicroRNA Intercellular Transfer and Bioelectrical Regulation of Model Multicellular Ensembles by the Gap Junction Connectivity.

2017

We have studied theoretically the microRNA (miRNA) intercellular transfer through voltage-gated gap junctions in terms of a biophysically grounded system of coupled differential equations. Instead of modeling a specific system, we use a general approach describing the interplay between the genetic mechanisms and the single-cell electric potentials. The dynamics of the multicellular ensemble are simulated under different conditions including spatially inhomogeneous transcription rates and local intercellular transfer of miRNAs. These processes result in spatiotemporal changes of miRNA, mRNA, and ion channel protein concentrations that eventually modify the bioelectrical states of small multi…

0301 basic medicinePhysicsModels MolecularCell signalingQuantitative Biology::Molecular NetworksEnsemble averageGap junctionIon Channel ProteinGap JunctionsNanotechnologyTransfectionQuantitative Biology::GenomicsQuantitative Biology::Cell BehaviorSurfaces Coatings and FilmsCoupled differential equations03 medical and health sciencesMulticellular organismMicroRNAs030104 developmental biologymicroRNAMaterials ChemistryBiophysicsPhysical and Theoretical ChemistryIntracellularThe journal of physical chemistry. B
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Chimeric proteins tagged with specific 3xHA cassettes may present instability and functional problems

2017

Epitope-tagging of proteins has become a widespread technique for the analysis of protein function, protein interactions and protein localization among others. Tagging of genes by chromosomal integration of PCR amplified cassettes is a widely used and fast method to label proteins in vivo. Different systems have been developed during years in the yeast Saccharomyces cerevisiae. In the present study, we analysed systematically a set of yeast proteins that were fused to different tags. Analysis of the tagged proteins revealed an unexpected general effect on protein level when some specific tagging module was used. This was due in all cases to a destabilization of the proteins and caused a red…

0301 basic medicinePhysiologyProtein Extractionlcsh:MedicineYeast and Fungal ModelsPolymerase Chain ReactionBiochemistryGreen fluorescent proteinEpitopesDatabase and Informatics MethodsGene Expression Regulation FungalImmune PhysiologyProtein purificationMacromolecular Structure AnalysisMedicine and Health SciencesProto-Oncogene Proteins c-myclcsh:ScienceStainingExtraction TechniquesImmune System ProteinsMultidisciplinarybiologyGene targetingProtein subcellular localization predictionMembrane StainingExperimental Organism SystemsGene TargetingArtifactsSequence AnalysisPlasmidsResearch ArticleProtein StructureSaccharomyces cerevisiae ProteinsBioinformaticsRecombinant Fusion ProteinsGenetic VectorsGreen Fluorescent ProteinsImmunologySaccharomyces cerevisiaeHemagglutinins ViralSaccharomyces cerevisiaeComputational biologyResearch and Analysis MethodsGreen Fluorescent ProteinGenomic InstabilityAntibodiesProtein–protein interactionProto-Oncogene Proteins c-mycSaccharomyces03 medical and health sciencesModel OrganismsAmino Acid Sequence AnalysisMolecular BiologyStaining and Labelinglcsh:ROrganismsFungiBiology and Life SciencesProteinsbiology.organism_classificationFusion proteinYeastLuminescent Proteins030104 developmental biologySpecimen Preparation and Treatmentlcsh:QProtein Structure NetworksPLOS ONE
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Automatic sleep scoring: A deep learning architecture for multi-modality time series

2020

Background: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning architecture to automate sleep scoring using raw polysomnography recordings. Method: The model adopts a linear function to address different numbers of inputs, thereby extending model applications. Two-dimensional convolution neural networks are used to learn features from multi-modality polysomnographic signals, a “squeeze and excitation” block to recalibrate channel-wise features, together with a long short-term memory module to exploit long-range co…

0301 basic medicineProcess (engineering)Computer sciencePolysomnographyPolysomnographyMachine learningcomputer.software_genreuni (lepotila)03 medical and health sciencesDeep Learning0302 clinical medicinepolysomnographymedicineHumansBlock (data storage)Sleep Stagesmedicine.diagnostic_testArtificial neural networksignaalinkäsittelybusiness.industryunitutkimusGeneral NeuroscienceDeep learningdeep learningsignaalianalyysiElectroencephalographyautomatic sleep scoringmulti-modality analysiskoneoppiminen030104 developmental biologyMemory moduleSleep StagesArtificial intelligenceSleepTransfer of learningbusinesscomputer030217 neurology & neurosurgeryJournal of Neuroscience Methods
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