Search results for "HM"

showing 10 items of 10594 documents

Modelos animales de adicción a las drogas

2017

El desarrollo de modelos animales de refuerzo y adicción a las drogas es imprescindible para el avance en el conocimiento de las bases biológicas de este trastorno y la identificación de nuevas dianas terapéuticas. En función del componente del refuerzo que deseemos estudiar podemos servirnos de un tipo de modelos animales u otros. Podemos utilizar modelos de refuerzo basados en el efecto hedónico primario que produce el consumo de la sustancia adictiva, como los modelos de autoadministración (AA) y autoestimulación eléctrica intracraneal (AEIC), o modelos basados en el componente relacionado con el aprendizaje asociativo y la capacidad cognitiva de realizar predicciones sobre la obtención …

0301 basic medicinePunishment (psychology)media_common.quotation_subjectMedicine (miscellaneous)03 medical and health sciencesTratamiento médicoLucha contra la toxicomanía0302 clinical medicinemedicineReinforcementmedia_commonToxicomaníaComportamientoAddictionConductaCognitionExtinction (psychology)medicine.diseaseConditioned place preferenceAssociative learningPsychiatry and Mental health030104 developmental biologyPsychologyAddictive behaviorSocial psychology030217 neurology & neurosurgery
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New Approach of Controlling Cardiac Alternans

2018

The alternans of the cardiac action potential duration is a pathological rhythm. It is considered to be relating to the onset of ventricular fibrillation and sudden cardiac death. It is well known that, the predictive control is among the control methods that use the chaos to stabilize the unstable fixed point. Firstly, we show that alternans (or period-2 orbit) can be suppressed temporally by the predictive control of the periodic state of the system. Secondly, we determine an estimation of the size of a restricted attraction's basin of the unstable equilibrium point representing the unstable regular rhythm stabilized by the control. This result allows the application of predictive control…

0301 basic medicineQuantitative Biology::Tissues and Organs[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS]Beat (acoustics)[MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingFixed point01 natural sciences010305 fluids & plasmasSudden cardiac death03 medical and health sciencesRhythmControl theory0103 physical sciencesmedicineDiscrete Mathematics and CombinatoricsComputingMilieux_MISCELLANEOUSMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingApplied MathematicsCardiac action potentialmedicine.diseaseModel predictive control030104 developmental biology[NLIN.NLIN-CD] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Ventricular fibrillation[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingStationary state
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A Simple Method to Predict Blood-Brain Barrier Permeability of Drug- Like Compounds Using Classification Trees

2017

Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is a challenging task; despite the numerous efforts realized to predict/measure BBB passage, they still have several drawbacks. Methods: The prediction of the permeability through the BBB is carried out using classification trees. A large data set of 497 compounds (recently published) is selected to develop the tree model. Results: The best model shows an accuracy higher than 87.6% for training set; the model was also validated using 10-fold cross-validation procedure and through a test set achieving accuracy values of 86.1% and 87.9%, correspondingly. We give a brief explanation, in structural terms, o…

0301 basic medicineQuantitative structure–activity relationshipComputer scienceDatasets as TopicQuantitative Structure-Activity Relationshipcomputer.software_genre01 natural sciencesPermeability03 medical and health sciencesMolecular descriptorDrug DiscoveryInternational literatureComputer SimulationTraining setDecision tree learningDecision Trees0104 chemical sciences010404 medicinal & biomolecular chemistry030104 developmental biologyPharmaceutical PreparationsBlood-Brain BarrierTest setData miningBlood brain barrier permeabilitycomputerAlgorithmsDecision tree modelMedicinal Chemistry
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Genetic tools discriminate strains of Leishmania infantum isolated from  humans and dogs in Sicily, Italy

2020

Background Leishmaniasis is one of the most important vector-borne diseases and it represents a serious world health problem affecting millions of people. High levels of Leishmania infections, affecting both humans and animals, are recognized among Italian regions. Among these, Sicily has one of the highest prevalence of Leishmania infection. Methodology/Principal Findings Seventy-eight Leishmania strains isolated from human and animal samples across Sicily, were analyzed for the polymorphic k26-gene and genotypes were assigned according to the size of the PCR products. A multilocus microsatellite typing (MLMT) approach based on the analysis of 11 independent loci was used to investigate po…

0301 basic medicineRC955-962Population genetics0302 clinical medicineMedical ConditionsArctic medicine. Tropical medicineZoonosesMedicine and Health SciencesDog DiseasesLeishmaniasisGeneticsProtozoansLeishmaniaMammalseducation.field_of_studyGeographyEukaryotaInfectious DiseasesItalyVertebratesMicrosatelliteLeishmaniasis VisceralLeishmania infantumPublic aspects of medicineRA1-1270Research ArticleNeglected Tropical DiseasesLeishmania Infantum030231 tropical medicinePopulationBiology03 medical and health sciencesDogsParasitic DiseasesGeneticsAnimalsHumansTypingGenetic variabilityeducationGenetic diversityEvolutionary BiologyProtozoan InfectionsPopulation BiologyPublic Health Environmental and Occupational HealthOrganismsBiology and Life SciencesHuman GeneticsLeishmaniabiology.organism_classificationTropical DiseasesParasitic Protozoans030104 developmental biologyAmniotesEarth SciencesZoologyPopulation GeneticsPLoS Neglected Tropical Diseases
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Epigenetic Control of Phenotypic Plasticity in the Filamentous Fungus Neurospora crassa

2016

Abstract Phenotypic plasticity is the ability of a genotype to produce different phenotypes under different environmental or developmental conditions. Phenotypic plasticity is a ubiquitous feature of living organisms, and is typically based on variable patterns of gene expression. However, the mechanisms by which gene expression is influenced and regulated during plastic responses are poorly understood in most organisms. While modifications to DNA and histone proteins have been implicated as likely candidates for generating and regulating phenotypic plasticity, specific details of each modification and its mode of operation have remained largely unknown. In this study, we investigated how e…

0301 basic medicineRNA-interferenssiGenotypeInvestigationsQH426-470MethylationModels BiologicalHistone methylationEpigenesis GeneticNeurospora crassaHistonesGene Knockout Techniques03 medical and health sciencesRNA interferenceHistone demethylationGene Expression Regulation FungalHistone methylationGeneticshistone deacetylationEpigeneticshistone methylationGenetikMolecular BiologyGeneCrosses GeneticGenetic Association StudiesGenetics (clinical)Histone deacetylationGeneticsAnalysis of VariancePhenotypic plasticityModels StatisticalDNA methylationNeurospora crassabiologyAcetylationbiology.organism_classificationDNA-metylaatioPhenotype030104 developmental biologyHistonereaction normMutationDNA methylationbiology.proteinta1181fungisienetAlgorithmsG3: Genes, Genomes, Genetics
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A Methodological Framework to Discover Pharmacogenomic Interactions Based on Random Forests

2021

The identification of genomic alterations in tumor tissues, including somatic mutations, deletions, and gene amplifications, produces large amounts of data, which can be correlated with a diversity of therapeutic responses. We aimed to provide a methodological framework to discover pharmacogenomic interactions based on Random Forests. We matched two databases from the Cancer Cell Line Encyclopaedia (CCLE) project, and the Genomics of Drug Sensitivity in Cancer (GDSC) project. For a total of 648 shared cell lines, we considered 48,270 gene alterations from CCLE as input features and the area under the dose-response curve (AUC) for 265 drugs from GDSC as the outcomes. A three-step reduction t…

0301 basic medicineRandom ForestsPharmacogenomic Variantsdrug responseGenomicsComputational biologycell linesBiologyQH426-470Article03 medical and health sciences0302 clinical medicineNeoplasmsDrug responseGeneticsHumanscancerGene Regulatory Networksgenomic alterationGenetics (clinical)Random Forestcell linegenomic alterationsTumor tissueRandom forestpharmacogenomic interactions030104 developmental biologyConcordance correlation coefficientDrug Resistance Neoplasm030220 oncology & carcinogenesisPharmacogenomicsIdentification (biology)pharmacogenomic interactions.Cancer cell linesAlgorithmsGenome-Wide Association StudyGenes
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In cutaneous leishmaniasis, induction of retinoic acid in skin-derived Langerhans cells is not sufficient for induction of parasite persistence-media…

2017

0301 basic medicineReceptors CCR7Retinoic acidLeishmaniasis CutaneousTretinoinCell CommunicationDermatologyBiologyT-Lymphocytes RegulatoryBiochemistryHost-Parasite InteractionsPersistence (computer science)Mice03 medical and health scienceschemistry.chemical_compound0302 clinical medicineCutaneous leishmaniasismedicineAnimalsHumansParasite hostingMolecular BiologyLeishmania majorSkinMice Knockoutmedicine.diseaseDisease Models Animal030104 developmental biologychemistryLangerhans CellsImmunologyLymph Nodes030215 immunologyJournal of Dermatological Science
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Newly Digitized Database Reveals the Lives and Families of Forced Migrants from Finnish Karelia

2017

Studies on displaced persons often suffer from a lack of data on the long-term effects of forced migration. A register created during 1960s and published as a book series ‘Siirtokarjalaisten tie’ in 1970 documented the lives of individuals who fled the southern Karelian district of Finland after its first and second occupation by the Soviet Union in 1940 and 1944. To realize the potential value of these data for scientific research, we have recently scanned the register using optical character recognition (OCR) software, and developed proprietary computer code to extract these data. Here we outline the steps involved in the digitization process, and present an overview of the Migration Kare…

0301 basic medicineRegister (sociolinguistics)Historyväestönsiirrotdatabases [http://www.yso.fi/onto/yso/p3056]forced migrationmarriage [http://www.yso.fi/onto/yso/p2790]computer.software_genrelcsh:Social Sciences03 medical and health sciencesbirthsoccupations (professions) [http://www.yso.fi/onto/yso/p1179]avioituvuustietokannatrekisterit112 Statistics and probabilityDigitizationta119syntyvyysdatabaseFinlandmobility [http://www.yso.fi/onto/yso/p252]perheet (ryhmät)Databaseregister informationoccupationsDisplaced persondisplaced personsOptical character recognition113 Computer and information sciencesmarriagesmobilitylcsh:HForced migration030104 developmental biologyliikkuvuuslcsh:HB848-3697digitizationlcsh:Demography. Population. Vital eventsta1181Research findingsSoviet unionKarjalacomputerdigiointiFinnish Yearbook of Population Research
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RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures

2017

RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by a…

0301 basic medicineRepetitive Sequences Amino Acid[SDV.BC]Life Sciences [q-bio]/Cellular BiologyBiologyBioinformaticsSearch engineAnnotationStructure-Activity Relationship03 medical and health sciences0302 clinical medicineTandem repeatGeneticsAnimalsHumansDatabase IssueDatabases ProteinComputingMilieux_MISCELLANEOUSRepeat unit030304 developmental biology0303 health sciencesInformation retrievalProteinscomputer.file_formatProtein Data BankVisualizationSchema (genetic algorithms)030104 developmental biologyData qualityCorrigendumcomputerSoftware030217 neurology & neurosurgeryNucleic Acids Research
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Cancer: a disease at the crossroads of trade-offs

2017

11 pages; International audience; Central to evolutionary theory is the idea that living organisms face phenotypic and/or genetic trade-offs when allocating resources to competing life-history demands, such as growth, survival, and reproduction. These trade-offs are increasingly considered to be crucial to further our understanding of cancer. First, evidences suggest that neoplastic cells, as any living entities subject to natural selection, are governed by trade-offs such as between survival and proliferation. Second, selection might also have shaped trade-offs at the organismal level, especially regarding protective mechanisms against cancer. Cancer can also emerge as a consequence of add…

0301 basic medicineReproduction (economics)[SDV.CAN]Life Sciences [q-bio]/CancerDiseaseBiologyTrade-offLife history theory[ SDV.CAN ] Life Sciences [q-bio]/Cancer03 medical and health sciencesGeneticsmedicinecancertrade‐offEvolutionary dynamicsEcology Evolution Behavior and SystematicsSelection (genetic algorithm)ComputingMilieux_MISCELLANEOUSlife‐history traitsNatural selection[SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]Ecology[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE]Cancernatural selectionmedicine.disease3. Good health[ SDV.GEN.GPO ] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]030104 developmental biology[ SDV.BID.EVO ] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE]Evolutionary biologyGeneral Agricultural and Biological SciencesReviews and Syntheses
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