Search results for "Vector"

showing 10 items of 2660 documents

Louseborne relapsing fever in young migrants, sicily, Italy, july-september 2015

2016

To the Editor: During the early 20th century, at the end of World War I, and during World War II, louseborne relapsing fever (LBRF) caused by Borrelia recurrentis was a major public health problem, especially in eastern Europe and northern Africa (1,2). Currently, poor living conditions, famine, war, and refugee camps are major risk factors for epidemics of LBRF in resource-poor countries, such as those in the Horn of Africa (3,4). Increased migration from resource-poor countries and war/violence create new routes for spread of vectorborne diseases. Recently, several cases of LBRF have been reported among asylum seekers from Eritrea in the Netherlands, Switzerland, and Germany (5–8). All of…

Settore MED/07 - Microbiologia E Microbiologia ClinicaLetterrelapsing feverEpidemiologyExpeditedvector-borne infectionslcsh:MedicinemigrantsDengue fever0302 clinical medicinerefugee030212 general & internal medicinebacteriaSicilyLouse-Borne Relapsing Feverbody lousebiologyrefugeesLeptospirosisInfectious DiseasesItalyChillsmedicine.symptomRickettsia conoriizoonoserefugee campsMicrobiology (medical)medicine.medical_specialtyBorrelia recurrentis; Italy; Libya; Sicily; Somalia; bacteria; body louse; louseborne infections; louseborne relapsing fever; migrants; refugee camps; refugees; vector-borne infections; zoonoses; Microbiology (medical); Infectious Diseases; EpidemiologySomalia030231 tropical medicineInfectious DiseaseLibyalouseborne infectionslouseborne infectionlcsh:Infectious and parasitic diseases03 medical and health sciencesInternal medicinemedicinevector-borne infectionlcsh:RC109-216Letters to the EditorLouseborne Relapsing Fever in Young Migrants Sicily Italy July–September 2015louseborne relapsing feverBorrelia recurrentisBorrelia recurrentilouse-borne relapsing feverbusiness.industrylcsh:Rmedicine.diseasebiology.organism_classificationrefugee campzoonosesmigrantImmunologyBorrelia recurrentisbusinessMalaria
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DEVELOPMENT OF S/MAR MINICIRLES VECTOR FOR PERSISTENT EXPRESSION IN VIVO.

2009

An ideal vector for gene therapy must fulfil the following requirements: non-toxicity, mitotic stability and persistent therapeutic levels of transgene expression. Viral vectors are widely used due to their ability to sustain prolonged expression. Their potentially tumorigenic effects are a limiting factor for in vivo applications. Non-viral vectors, which can be designed to be free from viral sequences, are a promising alternative for gene transfer although they often produce transient transgene expression. This limitation of this vector type is primarily due to bacterial sequences they contain and these have proven to be toxic for the mammalian cells as they contain a high number of unmet…

Settore MED/38 - Pediatria Generale E SpecialisticaMINICIRCLE VECTOR NON-VIRAL GENE THERAPY.
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Development of S/MAR plasmid vector for persistent expression and maintenance in vivo

2007

An ideal gene therapy vector should enable persistent transgene expression without limitations of safety and reproducibility. Here we report the development of a non-viral episomal plasmid DNA (pDNA) vector that appears to fulfil these criteria. This pDNA vector combines a scaffold/matrix attachment region (S/MAR) with a human liver-specific promoter (a1-antitrypsin (AAT)) in such a way that long-term expression is enabled in murine liver following hydrodynamic injection. Long-term expression is demonstrated by monitoring the longitudinal luciferase expression profile for up to 6 months by means of in situ bioluminescent imaging. We conclude that the combination of a mammalian, tissue-speci…

Settore MED/38 - Pediatria Generale E SpecialisticaNon-viral episomal plasmid DNA (pDNA) vector S/MAR element AAT-promoter.
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Development of a new S/MAR containing Minicircle DNA vector: a new promise for Gene Therapy.

2009

A barrier limiting the use of nonviral vectors for gene therapy is related to the short duration of transgene expression in vivo. Development, evaluation, and optimisation of a long term transgene expression using a non viral vector is currently the primary aim in our research field. Recently, we have demonstrate that a nonviral episomal plasmid (pDNA) vector combined with a scaffold/matrix attachment region (S/MAR) is able to sustain long-term expression in murine liver for at least six months following hydrodynamic injection. However, plasmids contain sequences, which are essential for propagation in bacteria but are unnecessary for expression in mammalian cells. These bacterial component…

Settore MED/38 - Pediatria Generale E Specialistica“Minicircle VECTOR" S/MAR.
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ESSAYS ON FINANCIAL STRESS: A MIXED FREQUENCY DATA ANALYSIS

Settore SECS-P/05 - EconometriaFINANCIAL STRESS MIXED FREQUENCY DATA VECTOR AUTOREGRESSIVE (VAR) MODELS
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MAST solution of irrotational flow problems in 2D domains with strongly unstructured triangular meshes

2010

A new methodology for the solution of irrotational 2D flow problems in domains with strongly unstructured meshes is presented. A fractional time step procedure is applied to the original governing equations, solving consecutively a convective prediction system and a diffusive corrective system. The non linear components of the problem are concentrated in the prediction step, while the correction step leads to the solution of a linear system, of the order of the number of computational cells. A MArching in Space and Time (MAST) approach is applied for the solution of the convective prediction step. The major advantages of the model, as well as its ability to maintain the solution monotonicit…

Shallow water numerical models MASTConvectionNonlinear systemSpacetimeLinear systemApplied mathematicsMonotonic functionPolygon meshGeometryConservative vector fieldShallow water equationsSettore ICAR/01 - IdraulicaMathematicsAIP Conference Proceedings
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Automatic differentiation of melanoma from dysplastic nevi.

2015

International audience; Malignant melanoma causes the majority of deaths related to skin cancer. Nevertheless, it is the most treatable one, depending on its early diagnosis. The early prognosis is a challenging task for both clinicians and dermatologist, due to the characteristic similarities of melanoma with other skin lesions such as dysplastic nevi. In the past decades, several computerized lesion analysis algorithms have been proposed by the research community for detection of melanoma. These algorithms mostly focus on differentiating melanoma from benign lesions and few have considered the case of melanoma against dysplastic nevi. In this paper, we consider the most challenging task a…

Shape featuresSkin Neoplasms[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingDysplastic02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imagingColourPattern Recognition Automated0302 clinical medicine0202 electrical engineering electronic engineering information engineeringMelanoma[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingMelanomaClassificationComputer Graphics and Computer-Aided DesignDermoscopy imaging3. Good healthRandom forest020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionAlgorithmsmedicine.medical_specialtyAutomatic differentiationFeature extractionHealth InformaticsDermoscopySensitivity and SpecificityDiagnosis Differential03 medical and health sciencesLesion analysisMachine learningImage Interpretation Computer-Assistedmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansRadiology Nuclear Medicine and imagingTextureneoplasmsbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicine.diseaseDermatologySupport vector machineBag-of-words modelSkin cancerbusinessDysplastic Nevus SyndromeComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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Shock formation in the dispersionless Kadomtsev-Petviashvili equation

2016

The dispersionless Kadomtsev-Petviashvili (dKP) equation $(u_t+uu_x)_x=u_{yy}$ is one of the simplest nonlinear wave equations describing two-dimensional shocks. To solve the dKP equation we use a coordinate transformation inspired by the method of characteristics for the one-dimensional Hopf equation $u_t+uu_x=0$. We show numerically that the solutions to the transformed equation do not develop shocks. This permits us to extend the dKP solution as the graph of a multivalued function beyond the critical time when the gradients blow up. This overturned solution is multivalued in a lip shape region in the $(x,y)$ plane, where the solution of the dKP equation exists in a weak sense only, and a…

Shock formationFOS: Physical sciencesGeneral Physics and AstronomyKadomtsev–Petviashvili equation01 natural sciencesCritical point (mathematics)010305 fluids & plasmasDissipative dKP equation[ MATH.MATH-AP ] Mathematics [math]/Analysis of PDEs [math.AP]Mathematics - Analysis of PDEsMethod of characteristicsPosition (vector)[MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]0103 physical sciencesFOS: Mathematics[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]0101 mathematicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsMathematical physicsMathematicsCusp (singularity)Multiscales analysisdispersionless Kadomtsev-Petviashvili equation; dissipative dKP equation; multiscales analysis; shock formationPlane (geometry)Multivalued functionApplied Mathematics010102 general mathematics[ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph]Statistical and Nonlinear PhysicsMathematical Physics (math-ph)Nonlinear Sciences::Exactly Solvable and Integrable SystemsDispersionless Kadomtsev-Petviashvili equationDissipative systemAnalysis of PDEs (math.AP)
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Monitoring displacements of an earthen dam using GNSS and remote sensing

2014

This paper shows the results of a scientific research in which a GNSS continuous monitoring system for earth-dam deformations has been developed, then, deformations have been related with reservoir water surface and level. The experiment was conducted near Bivona (Sicily, Italy), on the Castello dam (Magazzolo Lake). On the top of the dam three control points were placed and three GNSS permanent stations were installed. The three stations continuously transmitted data to the control centre of the University of Palermo. The former has been determined using freely available satellite data (specifically Landsat 7 SLC-Off) collected during the whole study period (DOYs 101 to 348 2011). Issues r…

Shoregeography.geographical_feature_categoryLevellingbusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaContinuous monitoringMonitoring Earthen dam Reservoir surface GNSS Landsat ETM+ SLC-Off.Displacement (vector)Base stationGeographyGNSS applicationsRemote sensing (archaeology)Global Positioning SystembusinessSettore ICAR/06 - Topografia E CartografiaRemote sensingSPIE Proceedings
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Dynamic network identification from non-stationary vector autoregressive time series

2018

Learning the dynamics of complex systems features a large number of applications in data science. Graph-based modeling and inference underpins the most prominent family of approaches to learn complex dynamics due to their ability to capture the intrinsic sparsity of direct interactions in such systems. They also provide the user with interpretable graphs that unveil behavioral patterns and changes. To cope with the time-varying nature of interactions, this paper develops an estimation criterion and a solver to learn the parameters of a time-varying vector autoregressive model supported on a network of time series. The notion of local breakpoint is proposed to accommodate changes at individu…

Signal Processing (eess.SP)Dynamic network analysisTheoretical computer scienceComputer scienceStationary vectorComplex systemBehavioral patternInference020206 networking & telecommunications02 engineering and technologySolver01 natural sciences010104 statistics & probabilityComplex dynamicsAutoregressive model0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineering0101 mathematicsElectrical Engineering and Systems Science - Signal Processing
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