Search results for "AREs"

showing 10 items of 1717 documents

Towards development of a statistical framework to evaluate myotonic dystrophy type 1 mRNA biomarkers in the context of a clinical trial

2020

AbstractMyotonic dystrophy type 1 (DM1) is a rare genetic disorder, characterised by muscular dystrophy, myotonia, and other symptoms. DM1 is caused by the expansion of a CTG repeat in the 3’-untranslated region of DMPK. Longer CTG expansions are associated with greater symptom severity and earlier age at onset. The primary mechanism of pathogenesis is thought to be mediated by a gain of function of the CUG-containing RNA, that leads to trans-dysregulation of RNA metabolism of many other genes. Specifically, the alternative splicing (AS) and alternative polyadenylation (APA) of many genes is known to be disrupted. In the context of clinical trials of emerging DM1 treatments, it is important…

0301 basic medicineMicroarrayPhysiologyMicroarraysBioinformaticsBiochemistryMachine Learning0302 clinical medicineMathematical and Statistical TechniquesMedicine and Health SciencesMyotonic DystrophyMuscular dystrophyOligonucleotide Array Sequence AnalysisClinical Trials as TopicMultidisciplinaryMusclesQStatisticsRGenetic disorderMuscle AnalysisBody FluidsNucleic acidsBloodBioassays and Physiological AnalysisTreatment OutcomeGenetic DiseasesPhysical SciencesMedicineRegression AnalysisAnatomyDatabases Nucleic AcidResearch Articlemusculoskeletal diseasesGenetic Markerscongenital hereditary and neonatal diseases and abnormalitiesScienceContext (language use)Linear Regression AnalysisBiostatisticsResearch and Analysis MethodsPolyadenylationMyotonic dystrophyMyotonin-Protein Kinase03 medical and health sciencesmedicineGeneticsHumansRNA MessengerStatistical MethodsLeast-Squares AnalysisGeneClinical GeneticsModels Geneticbusiness.industryAlternative splicingBiology and Life Sciencesmedicine.diseaseMyotoniaAlternative Splicing030104 developmental biologyRNA processingRNAGene expressionbusinessTrinucleotide repeat expansionTrinucleotide Repeat Expansion030217 neurology & neurosurgeryBiomarkersMathematicsForecastingPLoS ONE
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Investigation on Quantitative Structure-Activity Relationships of 1,3,4-Oxadiazole Derivatives as Potential Telomerase Inhibitors.

2020

Background:Telomerase, a reverse transcriptase, maintains telomere and chromosomes integrity of dividing cells, while it is inactivated in most somatic cells. In tumor cells, telomerase is highly activated, and works in order to maintain the length of telomeres causing immortality, hence it could be considered as a potential marker to tumorigenesis.A series of 1,3,4-oxadiazole derivatives showed significant broad-spectrum anticancer activity against different cell lines, and demonstrated telomerase inhibition.Methods:This series of 24 N-benzylidene-2-((5-(pyridine-4-yl)-1,3,4-oxadiazol-2yl)thio)acetohydrazide derivatives as telomerase inhibitors has been considered to carry out QSAR studies…

0301 basic medicineModels MolecularTelomeraseQuantitative structure–activity relationship2D descriptorsDatasets as TopicQuantitative Structure-Activity RelationshipAntineoplastic Agents010402 general chemistry01 natural sciencesModels BiologicalAnticancer activityMLR03 medical and health sciencesInhibitory Concentration 50Drug DiscoveryLeast-Squares AnalysisTelomerase134-oxadiazolesOxadiazolesMolecular StructureDrug discoveryChemistryQSARQuantitative structureCombinatorial chemistry0104 chemical sciencesTelomerase inhibitors030104 developmental biology1 3 4 oxadiazole derivativesDrug Screening Assays AntitumorCurrent drug discovery technologies
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2020

Background Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects. Results We systematically evaluated the performance of univariate ANOVA, Welch’s ANOVA and linear mixed effects models …

0301 basic medicineMultivariate statisticsMultidisciplinaryUnivariateContrast (statistics)Linear discriminant analysis03 medical and health sciences030104 developmental biology0302 clinical medicineMultivariate analysis of variancePrincipal component analysisPartial least squares regressionStatisticsAnalysis of variance030217 neurology & neurosurgeryMathematicsPLOS ONE
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Alignment Free Dissimilarities for Nucleosome Classification

2016

Epigenetic mechanisms such as nucleosome positioning, histone modifications and DNA methylation play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have shown a role of DNA sequences in recruitment of epigenetic regulators. For this reason, the use of more suitable similarities or dissimilarity between DNA sequences could help in the context of epigenetic studies. In particular, alignment-free dissimilarities have already been successfully applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles…

0301 basic medicineNearest neighbour classifiersKnn classifierSettore INF/01 - Informatica030102 biochemistry & molecular biologybiologyComputer scienceSpeech recognitionEpigeneticContext (language use)Computational biologyL-tuples03 medical and health sciences030104 developmental biologyHistoneSimilarity (network science)DNA methylationbiology.proteinNucleosomeEpigeneticsAlignment free DNA sequence dissimilaritiesk-mersNucleosome classificationEpigenomics
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Hereditary Leiomyomatosis and Renal Cell Cancer Syndrome in Spain: Clinical and Genetic Characterization

2020

Simple Summary Hereditary leiomyomatosis and renal cell cancer (HLRCC) syndrome is a very rare hereditary disorder characterized by cutaneous leiomyomas (CLMs), uterine leiomyomas (ULMs), renal cysts (RCys) and renal cell cancer (RCC), with no data on its prevalence worldwide. No genotype-phenotype associations have been described. The aim of our study was to describe the genotypic and phenotypic features of the largest series of patients with HLRCC from Spain reported to date. Of 27 FH germline pathogenic variants, 12 were not previously reported in databases. Patients with missense pathogenic variants showed higher frequencies of CLMs, ULMs and RCys, than those with loss-of-function varia…

0301 basic medicineOncologyCancer ResearchCancer cellsmedicine.disease_causeurologic and male genital diseases:Male Urogenital Diseases::Urogenital Neoplasms::Urologic Neoplasms::Kidney Neoplasms::Male Urogenital Diseases::Carcinoma Renal Cell [DISEASES]<i>FH</i> gene0302 clinical medicineMalalties hereditàriesMissense mutationFH geneFH gene hereditary leiomyomatosis leiomyomas missense pathogenic variants renal cell cancerRenal cell cancerMutationKidney diseasesHereditary leiomyomatosis:Otros calificadores::Otros calificadores::/genética [Otros calificadores]:enfermedades urogenitales masculinas::neoplasias urogenitales::neoplasias urológicas::neoplasias renales::enfermedades urogenitales masculinas::carcinoma de células renales [ENFERMEDADES]leiomyomasmissense pathogenic variants renal cell cancerlcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogensRare diseases:Geographic Locations::Europe::Spain [GEOGRAPHICALS]Oncology030220 oncology & carcinogenesisCohortCèl·lules cancerosesMalalties raresRenal Cell CancersGenetic disordersmedicine.medical_specialtyMissense pathogenic variantsBiología Celularlcsh:RC254-282Article03 medical and health sciencesLeiomyomasInternal medicine:Other subheadings::Other subheadings::/genetics [Other subheadings]medicineRonyons - Malalties - Espanya:localizaciones geográficas::Europa (continente)::España [DENOMINACIONES GEOGRÁFICAS]business.industry:neoplasias::neoplasias por tipo histológico::neoplasias de tejido conjuntivo y de tejidos blandos::neoplasias de tejido muscular::leiomioma::leiomiomatosis [ENFERMEDADES]Retrospective cohort studymedicine.diseaseGenética030104 developmental biologyFumaraseClinical diagnosisHereditary leiomyomatosis and renal cell cancer syndromeMalalties del ronyó:Neoplasms::Neoplasms by Histologic Type::Neoplasms Connective and Soft Tissue::Neoplasms Muscle Tissue::Leiomyoma::Leiomyomatosis [DISEASES]hereditary leiomyomatosisbusiness
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Generation of three human iPSC lines from PLAN (PLA2G6-associated neurodegeneration) patients

2021

© 2021 The Authors.

0301 basic medicineQH301-705.5Cellular differentiationInduced Pluripotent Stem CellsNeuroaxonal Dystrophies:Cells::Stem Cells::Adult Stem Cells::Induced Pluripotent Stem Cells [ANATOMY]Biologymedicine.disease_cause:células::células madre::células madre adultas::células madre pluripotentes inducidas [ANATOMÍA]Sistema nerviós - DegeneracióCell LineDermal fibroblastGroup VI Phospholipases A203 medical and health sciencesKruppel-Like Factor 40302 clinical medicineSOX2medicineHumans:enfermedades del sistema nervioso::enfermedades neurodegenerativas [ENFERMEDADES]Biology (General)Induced pluripotent stem cellMutationNeurodegenerationCell DifferentiationCell BiologyGeneral Medicinemedicine.diseaseCellular Reprogramming030104 developmental biologyKLF4:Nervous System Diseases::Neurodegenerative Diseases [DISEASES]MutationCancer researchMalalties raresReprogramming030217 neurology & neurosurgeryGenèticaDevelopmental BiologyStem Cell Research
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HUMAN T-LYMPHOTROPIC VIRUS 1 (HTLV-1) AND HUMAN T-LYMPHOTROPIC VIRUS 2 (HTLV-2): GEOGRAPHICAL RESEARCH TRENDS AND COLLABORATION NETWORKS (1989-2012)

2016

Publications are often used as a measure of research work success. Human T-lymphotropic virus (HTLV) type 1 and 2 are human retroviruses, which were discovered in the early 1980s, and it is estimated that 15-20 million people are infected worldwide. This article describes a bibliometric review and a coauthorship network analysis of literature on HTLV indexed in PubMed in a 24-year period. A total of 7,564 documents were retrieved, showing a decrease in the number of documents from 1996 to 2007. HTLV manuscripts were published in 1,074 journals. Japan and USA were the countries with the highest contribution in this field (61%) followed by France (8%). Production ranking changed when the numb…

0301 basic medicineResearch groupsBiomedical Researchlcsh:Arctic medicine. Tropical medicinelcsh:RC955-962030231 tropical medicinePopulationBibliometricsGlobal HealthGross domestic product03 medical and health sciences0302 clinical medicineHuman T-lymphotropic virus (HTLV)Global healthMedicineHumansCooperative BehaviorSocioeconomicseducationeducation.field_of_studyHuman T-lymphotropic virus 1biologyGeographybusiness.industryHuman T-lymphotropic virus 2Tropical spastic paraparesisGeneral Medicinebiology.organism_classificationHTLV-I InfectionsT cell leukemia/lymphoma030104 developmental biologyInfectious DiseasesGross national incomeBibliometricsHuman T-lymphotropic virus 1Human T-lymphotropic virus 2ImmunologyOriginal ArticlePeriodicals as TopicbusinessResearch collaboration
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Correlation between work impairment, scores of rhinitis severity and asthma using the MASK-air ® App

2020

Background: In allergic rhinitis, a relevant outcome providing information on the effectiveness of interventions is needed. In MASK-air (Mobile Airways Sentinel Network), a visual analogue scale (VAS) for work is used as a relevant outcome. This study aimed to assess the performance of the work VAS work by comparing VAS work with other VAS measurements and symptom-medication scores obtained concurrently. Methods: All consecutive MASK-air users in 23 countries from 1 June 2016 to 31 October 2018 were included (14 189 users; 205 904 days). Geolocalized users self-assessed daily symptom control using the touchscreen functionality on their smart phone to click on VAS scores (ranging from 0 to 1…

0301 basic medicineSYMPTOMSSmart phoneAllergyEscala visual analógicaINNOVATION[SDV]Life Sciences [q-bio]Medical and Health SciencesCorrelationvisual analogue scale0302 clinical medicineQuality of lifeVisual analogue scaleQUALITY-OF-LIFEMàscaresImmunology and AllergyscoreNoseRinitisRhinitisPRODUCTIVITY COSTSasthma; MASK; rhinitis; score; visual analogue scaleScoreExplained variationResponse VariabilityMobile ApplicationsALLERGIC RHINITISrhinitimedicine.anatomical_structureTRIALSRinite1107 Immunology[SDV.IMM]Life Sciences [q-bio]/ImmunologySmartphonemedicine.medical_specialtyMASKVisual analogue scaleMASK study groupImmunologyMACVIA-ARIA03 medical and health sciencesAllergicrhinitismedicineHumansvisual analogue scale.TECHNOLOGYIMMUNOTHERAPYAsmaAsthmabusiness.industryasthma; MASK; rhinitis; score; visual analogue scale; Humans; Smartphone; Asthma; Mobile Applications; Rhinitis; Rhinitis Allergicasthmamedicine.diseaseRhinitis AllergicAsthmaRHINOCONJUNCTIVITIS030104 developmental biology030228 respiratory system3121 General medicine internal medicine and other clinical medicinePhysical therapyClinical Medicinebusiness[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.

2017

International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…

0301 basic medicineStatistics and ProbabilityMALDI-TOFexperimental designBiometryprotein quantificationQuantitative proteomicsVariance component analysis[ CHIM ] Chemical Sciences01 natural sciencesSignaltechnological variability010104 statistics & probability03 medical and health sciencesstatistical analysis[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[CHIM.ANAL]Chemical Sciences/Analytical chemistryComponent (UML)[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]biomarker discoverysum of squares type0101 mathematicsBiomarker discoverysignal processingMathematicsSignal processingAnalysis of Variance[ PHYS ] Physics [physics]Noise (signal processing)ProteinsGeneral MedicineVariance (accounting)[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]030104 developmental biologySpectrometry Mass Matrix-Assisted Laser Desorption-IonizationLinear Modelsvariance components[ CHIM.ANAL ] Chemical Sciences/Analytical chemistryStatistics Probability and UncertaintyBiological systemAlgorithmsBiomarkersBiometrical journal. Biometrische Zeitschrift
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A graphical model selection tool for mixed models

2017

Model selection can be defined as the task of estimating the performance of different models in order to choose the most parsimonious one, among a potentially very large set of candidate statistical models. We propose a graphical representation to be considered as an extension to the class of mixed models of the deviance plot proposed in the literature within the framework of classical and generalized linear models. This graphical representation allows, once a reduced number of models have been selected, to identify important covariates focusing only on the fixed effects component, assuming the random part properly specified. Nevertheless, we suggest also a standalone figure representing th…

0301 basic medicineStatistics and ProbabilityMixed modelModel selectionFeature selection01 natural sciencesTask (project management)Deviance plot Penalized Weighted Residual Sum of Squares Variable selection010104 statistics & probability03 medical and health sciences030104 developmental biologyModeling and SimulationStatisticsGraphical model0101 mathematicsSelection (genetic algorithm)Mathematics
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