Search results for "Hine"

showing 10 items of 5088 documents

Sicilian Litchi Fruit Extracts Induce Autophagy versus Apoptosis Switch in Human Colon Cancer Cells

2018

Litchi chinensis Sonnerat is a tropical tree whose fruits contain significant amounts of bioactive polyphenols. Litchi cultivation has recently spread in Sicily where the climate conditions are particularly favorable for this crop. Recent findings have shown that Litchi extracts display anti-tumor and pro-apoptotic effects in vitro, but the precise underlying mechanisms have not been fully elucidated. In this study, we report for the first time the effects of Sicilian litchi fruit extracts on colon cancer cells. The results indicated that litchi exocarp, mesocarp and endocarp fractions reduce the viability and clonogenic growth of HT29 cells. These effects were due to cell cycle arrest in t…

0301 basic medicineProgrammed cell deathautophagyCell cycle checkpointAtg1Apoptosislcsh:TX341-641Litchi chinensisArticle03 medical and health sciencesHT29 Cells0302 clinical medicineLitchiSettore BIO/10 - BiochimicaHumansClonogenic assaySicilyNutrition and DieteticsPlant ExtractsChemistryKinaseAutophagyPolyphenolsLitchi chinensiCell Cycle CheckpointsAntineoplastic Agents PhytogenicCell biology030104 developmental biologycolon cancerApoptosisFruit030220 oncology & carcinogenesisColonic Neoplasmsanti-tumor activityCaco-2 Cells<i>Litchi chinensis</i>HT29 Cellslcsh:Nutrition. Foods and food supplyPhytotherapySignal TransductionFood ScienceNutrients
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Evaluating the stability of pharmacophore features using molecular dynamics simulations.

2016

Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in …

0301 basic medicineProtein FlexibilityProtein ConformationBiophysicsStability (learning theory)Molecular Dynamics SimulationLigands01 natural sciencesBiochemistryLigandScoutSet (abstract data type)03 medical and health sciencesMolecular dynamicsComputational chemistryFeature (machine learning)Pharmacophore ModelingSensitivity (control systems)Molecular BiologyBinding Sites010405 organic chemistryChemistryStructure-based Pharmacophore ModelingMolecular DynamicProteinsHydrogen BondingCell Biology0104 chemical sciences030104 developmental biologyRankingModels ChemicalDrug DesignPharmacophoreBiological systemProtein BindingBiochemical and biophysical research communications
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Metabolites related to purine catabolism and risk of type 2 diabetes incidence; modifying effects of the TCF7L2-rs7903146 polymorphism

2019

Studies examining associations between purine metabolites and type 2 diabetes (T2D) are limited. We prospectively examined associations between plasma levels of purine metabolites with T2D risk and the modifying effects of transcription factor-7-like-2 (TCF7L2) rs7903146 polymorphism on these associations. This is a case-cohort design study within the PREDIMED study, with 251 incident T2D cases and a random sample of 694 participants (641 non-cases and 53 overlapping cases) without T2D at baseline (median follow-up: 3.8 years). Metabolites were semi-quantitatively profiled with LC-MS/MS. Cox regression analysis revealed that high plasma allantoin levels, including allantoin-to-uric acid rat…

0301 basic medicinePurineMalePolymorphism (Crystallography)endocrine system diseaseslcsh:MedicineType 2 diabetesDiabetis no-insulinodependentchemistry.chemical_compound0302 clinical medicineBlood plasmaMetabolitesNon-insulin-dependent diabetesProspective Studieslcsh:ScienceMultidisciplinaryDiabetisIncidencePrognosisMetabòlits3. Good healthMetabolomeFemaleTranscription Factor 7-Like 2 Proteinmedicine.drugmedicine.medical_specialtyendocrine systemPolymorphism Single NucleotideArticle03 medical and health sciencesAllantoin:Ciencias de la Salud::Medicina preventiva [Materias Investigacion]Diabetes mellitusInternal medicinemedicineHumansGenetic Predisposition to DiseaseInosineAgedbusiness.industrylcsh:Rnutritional and metabolic diseasesPolimorfisme (Cristal·lografia)Xanthinemedicine.disease030104 developmental biologyEndocrinologychemistryDiabetes Mellitus Type 2PurinesSpainCase-Control Studieslcsh:QbusinessTCF7L2030217 neurology & neurosurgeryBiomarkersFollow-Up Studies
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Quantitative characterization of translational riboregulators using an in vitro transcription–translation system

2018

Riboregulators are short RNA sequences that, upon binding to a ligand, change their secondary structure and influence the expression rate of a downstream gene. They constitute an attractive alternative to transcription factors for building synthetic gene regulatory networks because they can be engineered de novo. However, riboregulators are generally designed in silico and tested in vivo, which provides little quantitative information about their performances, thus hindering the improvement of design algorithms. Here we show that a cell-free transcription-translation (TX-TL) system provides valuable information about the performances of in silico designed riboregulators. We first propose a …

0301 basic medicineRiboregulator[SDV.BIO]Life Sciences [q-bio]/BiotechnologyTranscription GeneticIn silicoBiomedical EngineeringComputational biologyReal-Time Polymerase Chain ReactionRibosomeBiochemistry Genetics and Molecular Biology (miscellaneous)FluorescenceSynthetic biologyViral Proteins03 medical and health scienceschemistry.chemical_compound0302 clinical medicineRNA Transfer[CHIM]Chemical SciencesQH426GeneTranscription factor030304 developmental biology0303 health sciencesCell-free protein synthesisCell-Free SystemModels GeneticChemistryActivator (genetics)030302 biochemistry & molecular biologyRNADNADNA-Directed RNA PolymerasesGeneral MedicineCell-free protein synthesisMolecular machine3. Good health030104 developmental biologyGene Expression RegulationGenetic TechniquesProtein BiosynthesisRNA translational riboregulatorNucleic Acid ConformationRNAIn vitro synthetic biology5' Untranslated Regions030217 neurology & neurosurgeryDNA
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GSaaS: A Service to Cloudify and Schedule GPUs

2018

Cloud technology is an attractive infrastructure solution that provides customers with an almost unlimited on-demand computational capacity using a pay-per-use approach, and allows data centers to increase their energy and economic savings by adopting a virtualized resource sharing model. However, resources such as graphics processing units (GPUs), have not been fully adapted to this model. Although, general-purpose computing on graphics processing units (GPGPU) is becoming more and more popular, cloud providers lack of flexibility to manage accelerators, because of the extended use of peripheral component interconnect (PCI) passthrough techniques to attach GPUs to virtual machines (VMs). F…

0301 basic medicineScheduleGeneral Computer ScienceComputer scienceDistributed computingnetworkingCloud computing02 engineering and technologycomputer.software_genre03 medical and health sciencesGPU resource management020204 information systems0202 electrical engineering electronic engineering information engineeringCloud computingGeneral Materials ScienceResource managementplatform virtualizationbusiness.industrycloud computingGeneral EngineeringVirtualizationShared resource030104 developmental biologyVirtual machineScalabilityGPU cloudificationlcsh:Electrical engineering. Electronics. Nuclear engineeringGeneral-purpose computing on graphics processing unitsbusinesscomputerlcsh:TK1-9971IEEE Access
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A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines

2018

Being capable of online learning in unknown stochastic environments, Tsetlin Automata (TA) have gained considerable interest. As a model of biological systems, teams of TA have been used for solving complex problems in a decentralized manner, with low computational complexity. For many domains, decentralized problem solving is an advantage, however, also may lead to coordination difficulties and unstable learning. To combat this negative effect, this paper proposes a novel TA coordination scheme designed for learning problems with continuous input and output. By saving and updating the best solution that has been chosen so far, we can avoid having the overall system being led astray by spur…

0301 basic medicineScheme (programming language)Computational complexity theoryLearning automatabusiness.industryComputer scienceStochastic process030231 tropical medicineFunction (mathematics)Machine learningcomputer.software_genre030112 virologyAutomaton03 medical and health sciences0302 clinical medicineArtificial intelligencebusinesscomputercomputer.programming_language2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)
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Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.

2021

Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…

0301 basic medicineSimeprevirArtificial intelligencevirusesMERS Middle East Respiratory SyndromeHealth InformaticsBiologyMachine learningcomputer.software_genremedicine.disease_causeAntiviral AgentsArticleWHO World Health OrganizationAUC area under the curve03 medical and health sciences0302 clinical medicinessRNA single-stranded RNA virusmedicineChemotherapyHumansSARS severe acute respiratory syndromeCOVID-19 coronavirus disease 2019CoronavirusNatural productsVirtual screeningACE2 angiotensin converting enzyme 2Drug discoverybusiness.industrySARS-CoV-2COVID-19LBE lowest binding energyFDA Food and Drug AdministrationROC receiver operating characteristicComputer Science ApplicationsHIV human immunodeficiency virusMolecular Docking SimulationDrug repositioning030104 developmental biologyDrug developmentSevere acute respiratory syndrome-related coronavirusParitaprevirInfectious diseasesRespiratory virusArtificial intelligenceSupervised Machine Learningbusinesscomputer030217 neurology & neurosurgeryComputers in biology and medicine
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Regulating T-cell differentiation through the polyamine spermidine

2021

Background The cross-talk between the host and its microbiota plays a key role in the promotion of health. The production of metabolites such as polyamines by intestinal-resident bacteria is part of this symbiosis shaping host immunity. The polyamines putrescine, spermine, and spermidine are abundant within the gastrointestinal tract and might substantially contribute to gut immunity. Objective We aimed to characterize the polyamine spermidine as a modulator of T-cell differentiation and function. Methods Naive T cells were isolated from wild-type mice or cord blood from healthy donors and submitted to polarizing cytokines, with and without spermidine treatment, to evaluate CD4+ T-cell diff…

0301 basic medicineSpermine oxidaseSpermidineImmunologySpermineBiologyT-Lymphocytes RegulatoryOrnithine decarboxylaseMice03 medical and health scienceschemistry.chemical_compound0302 clinical medicineAnimalsImmunology and AllergyImmunity MucosalMice KnockoutMice Inbred BALB CFOXP3Cell DifferentiationDendritic cellColitisCell biologySpermidine030104 developmental biologychemistryCardiovascular and Metabolic DiseasesPutrescinePolyamine030215 immunology
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Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies

2016

Mieth, Bettina et al.

0301 basic medicineStatistical methodsComputer scienceGenome-wide association studyMachine learningcomputer.software_genreGenome-wide association studiesStatistical powerArticle[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Set (abstract data type)03 medical and health sciences[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]10007 Department of EconomicsStatistical significanceReplication (statistics)genomeStatistical hypothesis testingGenetic association1000 MultidisciplinaryMultidisciplinarybusiness.industryComputational scienceInstitut für Mathematik330 EconomicsSupport vector machine030104 developmental biologyMultiple comparisons problemwide association studiesstatistical methodsArtificial intelligencebusinesscomputer
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Partitioned learning of deep Boltzmann machines for SNP data.

2016

Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…

0301 basic medicineStatistics and ProbabilityComputer scienceMachine learningcomputer.software_genre01 natural sciencesBiochemistryPolymorphism Single NucleotideMachine Learning010104 statistics & probability03 medical and health sciencessymbols.namesakeJoint probability distributionHumans0101 mathematicsMolecular BiologyStatistical hypothesis testingArtificial neural networkbusiness.industryGene Expression Regulation LeukemicDeep learningUnivariateComputational BiologyManifoldComputer Science ApplicationsData setComputational Mathematics030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONComputational Theory and MathematicsLeukemia MyeloidBoltzmann constantsymbolsData miningArtificial intelligencebusinesscomputerSoftwareCurse of dimensionalityBioinformatics (Oxford, England)
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