Search results for "User"

showing 10 items of 1060 documents

Gene Expression and Apoptosis Levels in Cumulus Cells of Patients with Polymorphisms of FSHR and LHB Undergoing in Vitro Fertilization Program

2017

Background/Aims: FSH receptor (FSHR) Ala307Thr and Asn680Ser and LHβ chain (LHB) Trp28Arg and Ile35Thr polymorphisms affect the response to pharmacological ovarian stimulation with r-FSH in women undergoing assisted reproductive treatment (ART). Here, we evaluated the expression level of selected genes involved in follicle maturation and the possible onset of apoptosis in cumulus cells of patients with single and double FSHR and LHB polymorphisms, as potential markers of oocyte competence. Methods: Cumulus cells from 36 stimulated patients were collected and SNP genotyping performed by PCR. Gene expression was evaluated through real-time PCR, and apoptosis estimated via TUNEL assay, and cle…

0301 basic medicineApoptosis; Cumulus cells; FSHR; Gene expression; LH; Polymorphism; PhysiologyLHPhysiologyApoptosislcsh:PhysiologyGonadotropin-Releasing Hormone0302 clinical medicineGene FrequencyFSHRGene expressionlcsh:QD415-436Settore BIO/06 - Anatomia Comparata E CitologiaCells CulturedIn Situ Hybridization Fluorescence030219 obstetrics & reproductive medicinelcsh:QP1-981Caspase 3Apoptosis; Cumulus cells; FSHR; Gene expression; LH; Polymorphismmedicine.anatomical_structureCumulus cellReceptors FSHDNA fragmentationFemaleSignal TransductionAdultHeterozygotemedicine.medical_specialtyendocrine systemGenotypeGranulosa cellCumulus cellsDNA FragmentationFertilization in VitroBiologyReal-Time Polymerase Chain ReactionBuserelinPolymorphism Single Nucleotidelcsh:Biochemistry03 medical and health sciencesFollicleInternal medicinemedicineHumansPolymorphismApoptosiHeterozygote advantageLuteinizing Hormone beta SubunitOocyte030104 developmental biologyEndocrinologyHaplotypesApoptosisMultivariate AnalysisOocytesGene expressionFollicle-stimulating hormone receptorProto-Oncogene Proteins c-aktCellular Physiology and Biochemistry
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CHK1 inhibitor sensitizes resistant colorectal cancer stem cells to nortopsentin

2021

Summary Limited therapeutic options are available for advanced colorectal cancer (CRC). Herein, we report that exposure to a neo-synthetic bis(indolyl)thiazole alkaloid analog, nortopsentin 234 (NORA234), leads to an initial reduction of proliferative and clonogenic potential of CRC sphere cells (CR-CSphCs), followed by an adaptive response selecting the CR-CSphC-resistant compartment. Cells spared by the treatment with NORA234 express high levels of CD44v6, associated with a constitutive activation of Wnt pathway. In CR-CSphC-based organoids, NORA234 causes a genotoxic stress paralleled by G2-M cell cycle arrest and activation of CHK1, driving the DNA damage repair of CR-CSphCs, regardless…

0301 basic medicineCell cycle checkpointColorectal cancerScienceSettore MED/50 - Scienze Tecniche Mediche Applicate02 engineering and technologyGenotoxic StressArticleMolecular Physiology03 medical and health sciencesSettore MED/04 - PATOLOGIA GENERALERabusertibmedicineClonogenic assayCancerMultidisciplinarybusiness.industryQWnt signaling pathwayDrugsCancerCell Biology021001 nanoscience & nanotechnologymedicine.disease030104 developmental biologyCancer researchSettore MED/46 - Scienze Tecniche Di Medicina Di LaboratorioStem cell0210 nano-technologybusinesscolorectal cancer cancer stem cells alkaloids DNA damage repair CHK1.iScience
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Reactome graph database: Efficient access to complex pathway data

2018

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its qu…

0301 basic medicineDatabases FactualComputer scienceData managementKnowledge BasesSocial SciencesInformation Storage and RetrievalNoSQLcomputer.software_genreComputer ApplicationsDatabase and Informatics MethodsUser-Computer Interface0302 clinical medicineKnowledge extractionPsychologyDatabase Searchinglcsh:QH301-705.5Data ManagementLanguageBiological dataEcologySystems BiologyGenomicsGenomic DatabasesComputational Theory and MathematicsModeling and SimulationWeb-Based ApplicationsGraph (abstract data type)Information TechnologyResearch ArticleComputer and Information SciencesRelational databaseQuery languageResearch and Analysis MethodsEcosystems03 medical and health sciencesCellular and Molecular NeuroscienceDatabasesGeneticsComputer GraphicsHumansMolecular BiologyEcology Evolution Behavior and SystematicsInternetInformation retrievalGraph databasebusiness.industryEcology and Environmental SciencesCognitive PsychologyBiology and Life SciencesComputational BiologyGenome AnalysisRelational Databases030104 developmental biologyBiological Databaseslcsh:Biology (General)Cognitive Sciencebusinesscomputer030217 neurology & neurosurgerySoftwareNeurosciencePLoS Computational Biology
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A framework for data-driven adaptive GUI generation based on DICOM

2018

Computer applications for diagnostic medical imaging provide generally a wide range of tools to support physicians in their daily diagnosis activities. Unfortunately, some functionalities are specialized for specific diseases or imaging modalities, while other ones are useless for the images under investigation. Nevertheless, the corresponding Graphical User Interface (GUI) widgets are still present on the screen reducing the image visualization area. As a consequence, the physician may be affected by cognitive overload and visual stress causing a degradation of performances, mainly due to unuseful widgets. In clinical environments, a GUI must represent a sequence of steps for image investi…

0301 basic medicineDiagnostic ImagingAutomatedComputer scienceData-driven GUI generation; DICOM; Faceted classification; Graphical user interfaces; Medical diagnostic software; Algorithms; Brain; Cognition; Computers; Decision Support Systems Clinical; Diagnostic Imaging; Feasibility Studies; Humans; Magnetic Resonance Imaging; Medical Informatics; Pattern Recognition Automated; Software; Computer Graphics; Radiology Information Systems; User-Computer InterfaceGraphical user interfacesDecision Support SystemsHealth InformaticsPattern Recognitioncomputer.software_genrePattern Recognition Automated030218 nuclear medicine & medical imaging03 medical and health sciencesDICOMClinicalUser-Computer Interface0302 clinical medicineSoftwareCognitionHuman–computer interactionComputer GraphicsHumansDICOMGraphical user interfaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFaceted classificationbusiness.industryComputersData-driven GUI generationBrainComputer Science Applications1707 Computer Vision and Pattern RecognitionMedical diagnostic softwareDecision Support Systems ClinicalMagnetic Resonance ImagingComputer Science ApplicationsVisualizationSoftware frameworkGraphical user interface030104 developmental biologyWorkflowRadiology Information SystemsInformation modelSoftware designFeasibility StudiesbusinesscomputerAlgorithmsMedical InformaticsSoftware
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Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations.

2017

We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and rescored to generate a single hi…

0301 basic medicineGeneral Chemical EngineeringDrug Evaluation PreclinicalLibrary and Information SciencesMolecular Dynamics Simulationcomputer.software_genreLigandsLigandScoutCommon Hits Approach (CHA)03 medical and health sciencesMolecular dynamicsUser-Computer InterfaceComputational chemistryPharmacophore ModelingFlexibility (engineering)Virtual screeningChemistryFrame (networking)ProteinsGeneral ChemistryInto-structureSettore CHIM/08 - Chimica FarmaceuticaComputer Science Applications030104 developmental biologyData miningPharmacophorecomputerJournal of chemical information and modeling
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CLOVE: classification of genomic fusions into structural variation events

2017

Background A precise understanding of structural variants (SVs) in DNA is important in the study of cancer and population diversity. Many methods have been designed to identify SVs from DNA sequencing data. However, the problem remains challenging because existing approaches suffer from low sensitivity, precision, and positional accuracy. Furthermore, many existing tools only identify breakpoints, and so not collect related breakpoints and classify them as a particular type of SV. Due to the rapidly increasing usage of high throughput sequencing technologies in this area, there is an urgent need for algorithms that can accurately classify complex genomic rearrangements (involving more than …

0301 basic medicineGenomicsBiologycomputer.software_genrelcsh:Computer applications to medicine. Medical informaticsBiochemistryChromosomesDNA sequencingSet (abstract data type)Structural variationUser-Computer Interface03 medical and health sciencesStructural BiologyEscherichia coliHumansCopy-number variationMolecular Biologylcsh:QH301-705.5InternetMethodology ArticleApplied MathematicsBreakpointGenomic rearrangementsDNAGenomicsStructural variationsComputer Science ApplicationsIdentification (information)030104 developmental biologylcsh:Biology (General)Nucleic Acid ConformationGraph (abstract data type)lcsh:R858-859.7Data miningcomputerAlgorithmsBMC Bioinformatics
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HIPPIE v2.0: Enhancing meaningfulness and reliability of protein-protein interaction networks

2016

The increasing number of experimentally detected interactions between proteins makes it difficult for researchers to extract the interactions relevant for specific biological processes or diseases. This makes it necessary to accompany the large-scale detection of protein-protein interactions (PPIs) with strategies and tools to generate meaningful PPI subnetworks. To this end, we generated the Human Integrated Protein-Protein Interaction rEference or HIPPIE (http://cbdm.uni-mainz.de/hippie/). HIPPIE is a one-stop resource for the generation and interpretation of PPI networks relevant to a specific research question. We provide means to generate highly reliable, context-specific PPI networks …

0301 basic medicineHippieReliability (computer networking)BiologyWeb BrowserBioinformaticsProtein protein interaction networkComputational biology03 medical and health sciences0302 clinical medicineResource (project management)GeneticsHumansDatabase IssueGraph algorithmsProtein Interaction MapsDatabases ProteinResearch questionGraphical user interfacebusiness.industryReproducibility of ResultsData science030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONProtein interaction mappingbusiness030217 neurology & neurosurgeryProtein Interaction MapSoftware
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Identification of noncovalent proteasome inhibitors with high selectivity for chymotrypsin-like activity by a multistep structure-based virtual scree…

2016

Noncovalent proteasome inhibitors introduce an alternative mechanism of inhibition to that of covalent inhibitors, e.g. carfilzomib, used in cancer therapy. A multistep hierarchical structure-based virtual screening (SBVS) of the 65,375 NCI lead-like compound library led to the identification of two compounds (9 and 28) which noncovalently inhibited the chymotrypsin-like (ChT-L) activity (Ki = 2.18 and 2.12 μM, respectively) with little or no effects on the other two major proteasome proteolytic activities, trypsin-like (T-L) and post-glutamyl peptide hydrolase (PGPH) activities. A subsequent hierarchical similarity search over the full NCI database with the most active tripeptide-based inh…

0301 basic medicineNon-covalentVirtual screeningProteasome Endopeptidase ComplexStereochemistryProtein ConformationProteolysisDrug Evaluation PreclinicalTripeptideSubstrate Specificity03 medical and health scienceschemistry.chemical_compoundStructure-Activity RelationshipUser-Computer Interface0302 clinical medicineProtein structureCell Line TumorDrug DiscoverymedicineStructure–activity relationshipChymotrypsinHumansProteasome inhibitorCell ProliferationPharmacologyVirtual screeningmedicine.diagnostic_testOrganic ChemistryGeneral MedicineCarfilzomibPeptide scaffoldMolecular Docking SimulationProteasome inhibitors; Non-covalent; Peptide scaffold; Docking studies; Virtual screening030104 developmental biologyProteasomechemistryBiochemistryDocking (molecular)030220 oncology & carcinogenesisDocking studieProteolysisProteasome InhibitorsEuropean journal of medicinal chemistry
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CoverageAnalyzer (CAn): A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

2016

Combination of reverse transcription (RT) and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modifi…

0301 basic medicineRNA modifications; reverse transcription; reverse transcription (RT) signature; RNA sequencing (RNA-Seq); Next-Generation Sequencing (NGS); candidate screening; alignment viewerNext-Generation Sequencing (NGS)lcsh:QR1-502[ SDV.BBM.BM ] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyBiologycomputer.software_genre01 natural sciencesBiochemistryField (computer science)Differential analysisDeep sequencinglcsh:MicrobiologyArticleWorld Wide Web03 medical and health sciencesUser-Computer InterfaceRNA modificationsRNA sequencing (RNA-Seq)[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]candidate screeningMolecular BiologyComputingMilieux_MISCELLANEOUS010405 organic chemistrySequence Analysis RNAGene Expression ProfilingRNAComputational BiologyHigh-Throughput Nucleotide Sequencing[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyreverse transcription (RT) signaturereverse transcriptionFile formatalignment viewer0104 chemical sciencesVisualizationVisual inspection030104 developmental biology[ SDV.BBM.GTP ] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Data miningcomputerSoftwareBiomolecules
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Accelerating metagenomic read classification on CUDA-enabled GPUs.

2016

Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed. We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced k-mers (…

0301 basic medicineTheoretical computer scienceWorkstationGPUsComputer scienceContext (language use)CUDAParallel computingBiochemistryGenomelaw.invention03 medical and health sciencesCUDAUser-Computer Interface0302 clinical medicineStructural BiologylawTaxonomic assignmentHumansMicrobiomeMolecular BiologyInternetXeonApplied MathematicsHigh-Throughput Nucleotide SequencingSequence Analysis DNAExact k-mer matchingComputer Science Applications030104 developmental biologyTitan (supercomputer)Metagenomics030220 oncology & carcinogenesisMetagenomicsDNA microarraySoftwareBMC bioinformatics
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