Search results for "specificity"

showing 10 items of 2234 documents

The membrane anchor of microsomal epoxide hydrolase from human, rat, and rabbit displays an unexpected membrane topology.

1997

The microsomal epoxide hydrolase (mEH) and cytochrome P450s catalyze the sequential formation of carcinogenic metabolites. According to one algorithm for predicting the membrane topology of proteins, the human, the rabbit, and the rat mEH should adopt a type II topology. The type II topology is also predicted by a recently established neuronal network which is trained to recognize signal peptides with very high accuracy. In contrast to these predictions we find, based on N-glycosylation analysis in a cell-free and in a cellular system, that the membrane anchor of human, rat, and rabbit mEH displays a type I topology. This result is correctly predicted by the positive inside rule in which ne…

Signal peptide1303 BiochemistryGlycosylationGlycosylationCytochromeStereochemistryRecombinant Fusion ProteinsImmunoblottingMolecular Sequence DataBiophysics10050 Institute of Pharmacology and Toxicology610 Medicine & healthProtein Sorting SignalsTransfectionBiochemistry1307 Cell BiologyCell membranechemistry.chemical_compoundSpecies Specificity1312 Molecular BiologymedicineElectrochemistryAnimalsHumansAmino Acid SequenceMolecular BiologyPeptide sequenceEpoxide HydrolasesbiologyCell MembraneCell BiologyRatsmedicine.anatomical_structurechemistryMutagenesisMicrosomal epoxide hydrolaseMembrane topologyEpoxide HydrolasesCOS Cellsbiology.protein570 Life sciences; biologyRabbits1304 BiophysicsBiochemical and biophysical research communications
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Characterization of a glycosylphosphatidylinositol-bound cell-wall protein (GPI-CWP) in Yarrowia lipolytica.

2004

The structure and composition of the cell wall of yeast has so far been studied mainly in Saccharomyces cerevisiae. It is basically made up of three components: beta-glucans, chitin and mannose-containing glycoproteins, also called mannoproteins. Most covalently bound cell-wall mannoproteins belong to the so-called glycosylphosphatidylinositol cell-wall protein (GPI-CWP) family, cell-wall proteins that are bound through the remnant of a GPI residue to 1,6-beta-glucan. The non-conventional yeast Yarrowia lipolytica shares Generally Regarded As Safe (GRAS) status with S. cerevisiae, has some industrial applications and is increasingly being proposed as a host for the production of recombinant…

Signal peptideSaccharomyces cerevisiae ProteinsGlycosylphosphatidylinositolsSaccharomyces cerevisiaeGenes FungalMolecular Sequence DataYarrowiaSaccharomyces cerevisiaeBiologyMicrobiologyGene productFungal ProteinsSpecies SpecificityCell WallAmino Acid SequenceDNA FungalPeptide sequencechemistry.chemical_classificationMembrane GlycoproteinsBase SequenceSequence Homology Amino AcidFungal geneticsMembrane ProteinsYarrowiabiology.organism_classificationYeastcarbohydrates (lipids)BiochemistrychemistryGlycoproteinMicrobiology (Reading, England)
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Identification and study of a Candida albicans protein homologous to Saccharomyces cerevisiae Ssr1p, an internal cell-wall protein

2003

After screening of aCandida albicansgenome database, the product of an ORF (IPF 3054) that has 62 % homology withSaccharomyces cerevisiaeSsr1p, an internal cell-wall protein, was identified and named CaSsr1p. The deduced amino acid sequence shows that CaSsr1p contains an N-terminal hydrophobic signal peptide, is rich in Ser and Thr amino acids and has a potential glycosylphosphatidylinositol-attachment signal. CaSsr1p is released following degradation of isolated cell walls by zymolyase (mainly a 1,3-β-glucanase) and therefore seems to be covalently linked to theβ-glucan of the cell walls. Both disruption and overexpression of theCaSSR1gene caused an increased sensitivity to calcofluor whit…

Signal peptideSaccharomyces cerevisiae ProteinsMolecular Sequence DataSaccharomyces cerevisiaeGene ExpressionSaccharomyces cerevisiaeCalcofluor-whiteMicrobiologyFungal ProteinsCell wallSpecies SpecificityCell WallCandida albicansAmino Acid SequenceCloning MolecularDNA FungalCandida albicansGenePeptide sequencechemistry.chemical_classificationBase SequenceSequence Homology Amino Acidbiologybiology.organism_classificationAmino acidBiochemistrychemistryGene DeletionMicrobiology
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A method for quantifying atrial fibrillation organization based on wave-morphology similarity

2002

A new method for quantifying the organization of single bipolar electrograms recorded in the human atria during atrial fibrillation (AF) is presented. The algorithm relies on the comparison between pairs of local activation waves (LAWs) to estimate their morphological similarity, and returns a regularity index (/spl rho/) which measures the extent of repetitiveness over time of the detected activations. The database consisted of endocardial data from a multipolar basket catheter during AF and intraatrial recordings during atrial flutter. The index showed maximum regularity (/spl rho/=1) for all atrial flutter episodes and decreased significantly when increasing AF complexity as defined by W…

Signal processingBundle of Hismedicine.medical_specialtyMorphological similarityAtrial fibrillation (AF)Biomedical EngineeringSensitivity and SpecificityPattern Recognition AutomatedElectrocardiographySimilarity (network science)Heart RateInternal medicineAtrial Fibrillationotorhinolaryngologic diseasesmedicineHumansClinical treatmentWaveform morphologyMathematicsmedicine.diagnostic_testMinimum distanceModels CardiovascularReproducibility of ResultsSignal Processing Computer-AssistedAtrial fibrillationEndocardial signalmedicine.diseaseTachyarrhythmia organizationCardiologysense organsRhythm classificationBasket catheterElectrocardiographyAlgorithmsAtrial flutterBiomedical engineeringIEEE Transactions on Biomedical Engineering
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An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

2008

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…

Signal processingComputer scienceFeature extractionBiomedical EngineeringFeature extraction and selectionFeature selectionSensitivity and SpecificityIntracardiac injectionPattern Recognition AutomatedArtificial IntelligenceSearch algorithmAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedIntracardiac ElectrogramArrhythmia organizationSignal processingmedicine.diagnostic_testbusiness.industrySupport vector machines (SVMs)Reproducibility of ResultsPattern recognitionAtrial fibrillationHuman atrial fibrillationmedicine.diseaseSupport vector machineSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAutomatic classificationArtificial intelligenceIntracardiac electrogrambusinessElectrocardiographyAlgorithmsIEEE Transactions on Biomedical Engineering
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P300-based brain computer interface experimental setup

2009

A Brain-Computer interface (BCI) is a communication system that enables the generation of a control signal from brain signals such as sensorymotor rhythms and evoked potentials; therefore, it constitutes a novel communication option for people with severe motor disabilities (such as Amyotrophic Lateral Sclerosis patients). This paper presents the development of a P300-based BCI. This prototype uses a homemade six-channel electroencephalograph for the acquisition of the signals, and a visual stimulation matrix; since this matrix contains letters of the alphabet as well as images associated to them, it permits word-writing and the elaboration of messages with the images. To process the signal…

Signal processingmedicine.diagnostic_testComputer scienceSpeech recognitionInterface (computing)BrainReproducibility of ResultsElectroencephalographyElectroencephalographyLinear discriminant analysisEvent-Related Potentials P300Sensitivity and SpecificityLeast squaresUser-Computer InterfacePattern Recognition VisualmedicineAlgorithmsVisual CortexBrain–computer interface2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Quantification of synchronization during atrial fibrillation by Shannon entropy: Validation in patients and computer model of atrial arrhythmias

2005

Atrial fibrillation (AF), a cardiac arrhythmia classically described as completely desynchronized, is now known to show a certain amount of synchronized electrical activity. In the present work a new method for quantifying the level of synchronization of the electrical activity recorded in pairs of atrial sites during atrial fibrillation is presented. A synchronization index (Sy) was defined by quantifying the degree of complexity of the distribution of the time delays between sites by Shannon entropy estimation. The capability of Sy to discriminate different AF types in patients was assessed on a database of 60 pairs of endocardial recordings from a multipolar basket catheter. The analysis…

Signal processingmedicine.medical_specialtyTime delaysPhysiologyEntropyBiomedical EngineeringBiophysicsSensitivity and SpecificitySynchronizationHeart Conduction SystemArrhythmia (mechanisms)Internal medicinePhysiology (medical)medicineHumansIn patientDiagnosis Computer-AssistedMathematicsBody Surface Potential MappingModels CardiovascularCardiac arrhythmiaReproducibility of ResultsAtrial fibrillationAtrial arrhythmiasComputer simulationmedicine.diseaseAtrial fibrillationElectrophysiologyElectrophysiologymedicine.anatomical_structureBiophysicCardiologyRight atriumAlgorithms
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Understanding disease mechanisms with models of signaling pathway activities

2014

Background Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine. Results Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation s…

Signaling pathwaysComputer scienceSystems biologyStem cellsDiseaseDrug actionComputational biologyModels BiologicalMiceSpecies SpecificityStructural BiologyModelling and SimulationAnimalsHumansComputer SimulationDiseaseObesityMolecular BiologyCancerRegulation of gene expressionInternetMechanism (biology)Methodology ArticleApplied MathematicsProbabilistic modelPrecision medicineStatistical modelPrecision medicineComputer Science ApplicationsGene Expression RegulationFanconi anemiaModeling and SimulationDisease mechanismSignal transductionAlgorithmBiomarkersSoftwareSignal TransductionBMC Systems Biology
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Timing performance of the silicon PET insert probe

2010

Simulation indicates that PET image could be improved by upgrading a conventional ring with a probe placed close to the imaged object. In this paper, timing issues related to a PET probe using high-resistivity silicon as a detector material are addressed. The final probe will consist of several (four to eight) 1-mm thick layers of silicon detectors, segmented into 1 x 1 mm(2) pads, each pad equivalent to an independent p + nn+ diode. A proper matching of events in silicon with events of the external ring can be achieved with a good timing resolution. To estimate the timing performance, measurements were performed on a simplified model probe, consisting of a single 1-mm thick detector with 2…

SiliconMaterials scienceSiliconPhysics::Instrumentation and DetectorsTransducerschemistry.chemical_elementIntegrated circuitScintillatorTracking (particle physics)Sensitivity and Specificity01 natural sciencesLyso-030218 nuclear medicine & medical imaginglaw.invention03 medical and health sciences0302 clinical medicineOpticslaw0103 physical sciencesRadiology Nuclear Medicine and imagingDiodeRadiationCt Spect/Ct Pet/CtRadiological and Ultrasound Technology010308 nuclear & particles physicsbusiness.industryDetectorPublic Health Environmental and Occupational HealthReproducibility of ResultsEquipment DesignGeneral MedicineImage EnhancementEquipment Failure AnalysisTransducerchemistryPositron-Emission TomographybusinessRadiation Protection Dosimetry
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Comparison of the exoproducts of gram-negative bacteria by SDS-page

1985

The protein exoproducts released during exponential growth of Gram-negative bacteria were analysed and compared by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-Page). The following bacterial strains were tested: Escherichia coli, Klebsiella pneumoniae, Citrobacter freundii, Enterobacter cloacae, Serratia liquefaciens, Serratia rubidaea, Proteus mirabilis, Proteus vulgaris, Salmonella minnesota, Pseudomonas aeruginosa and Pseudomonas fluorescens. It is demonstrated by SDS-Page that members of one species show identical protein pattern, whereas different species show besides comparable protein bands a species characteristic pattern. All members of Enterobacteriaceae were sho…

SilverStaining and LabelingbiologyImmunologyPseudomonasProteus vulgarisPseudomonas fluorescensUrinebiology.organism_classificationSerratia liquefaciensProteus mirabilisEnterobacteriaceaeMicrobiologyCitrobacter freundiiMolecular WeightBacterial ProteinsEnterobacteriaceaeSpecies SpecificityBiochemistryGram-Negative BacteriaHumansElectrophoresis Polyacrylamide GelSulfhydryl CompoundsPeptidesEnterobacter cloacaeZentralblatt für Bakteriologie, Mikrobiologie und Hygiene. Series A: Medical Microbiology, Infectious Diseases, Virology, Parasitology
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