Search results for "Fluorescence"

showing 10 items of 2463 documents

Lasers for in-vivo skin diagnostics: some recent developments

2019

The recent advancements of three laser-based diagnostic technologies developed at the Riga group are briefly reviewed: (i) RGB imaging of cw-laser excited skin autofluorescence intensity and photobleaching rate distributions, (ii) ps-laser excited skin autofluorescence and diffuse reflectance kinetics analysis, (iii) snapshot RGB skin chromophore mapping under triple-laser illumination. These techniques have passed preliminary laboratory and clinical tests which have demonstrated a promising potential for further implementation in portable devices for routine clinical applications. Operation principles, set-up schemes and some clinical results obtained by the above-mentioned techniques are …

Clinical testsAutofluorescenceOpticsMaterials sciencelawbusiness.industrySkin autofluorescenceLaserbusinessPhotobleachinglaw.invention20th International Conference and School on Quantum Electronics: Laser Physics and Applications
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Colonization pattern of primary tomato roots by Pseudomonas fluorescens A6RI characterized by dilution plating, flow cytometry, fluorescence, confoca…

2004

Early colonization of primary tomato roots, grown in vitro, by Pseudomonas fluorescens A6RI, introduced by seed bacterization, was monitored for 7 days in three different root zones (zone A, apex+elongation+young hairy zone; zone B, hairy zone; zone C, old hairy zone+collar). Bacterial quantification was assessed by enumeration of (i) colony forming units (cfu) after dilution plating and of (ii) total bacterial cells by flow cytometry. Bacterial distribution and organization in the root zones were analyzed by fluorescence, confocal and scanning electron microscopy. For all sampling dates and zones, the densities of total bacterial cells were significantly higher than those of the cfu. The k…

Colony Count MicrobialPseudomonas fluorescensPseudomonas fluorescensPlant RootsApplied Microbiology and BiotechnologyMicrobiologylaw.inventionFlow cytometry03 medical and health sciencesSolanum lycopersicumlawConfocal microscopyBotanymedicine[SDV.MP] Life Sciences [q-bio]/Microbiology and ParasitologyComputingMilieux_MISCELLANEOUS030304 developmental biologyColony-forming unit0303 health sciencesMicroscopy ConfocalEcologybiologyEpidermis (botany)medicine.diagnostic_test030306 microbiologyFlow Cytometrybiology.organism_classificationApex (geometry)Horticulture[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyMicroscopy FluorescenceMicroscopy Electron ScanningDNS root zoneElectron microscope
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Overview of the Evolution of Silica-Based Chromo-Fluorogenic Nanosensors

2019

[EN] This review includes examples of silica-based, chromo-fluorogenic nanosensors with the aim of illustrating the evolution of the discipline in recent decades through relevant research developed in our group. Examples have been grouped according to the sensing strategies. A clear evolution from simply functionalized materials to new protocols involving molecular gates and the use of highly selective biomolecules such as antibodies and oligonucleotides is reported. Some final examples related to the evolution of chromogenic arrays and the possible use of nanoparticles to communicate with other nanoparticles or cells are also included. A total of 64 articles have been summarized, highlight…

ColorNanoparticleNanotechnologyReviewMesoporous010402 general chemistry01 natural sciencesBiochemistryFluorescencegated materialsAnalytical ChemistryQUIMICA ORGANICAMolecular recognitionsensorNanosensorarraysGated materialsElectrical and Electronic EngineeringArraysInstrumentationSensorchemistry.chemical_classification010405 organic chemistryChemistryChromogenicOligonucleotideBiomoleculeQUIMICA INORGANICASilicaHighly selectiveAtomic and Molecular Physics and Opticscolor0104 chemical sciencessilicaNanoparticlesnanoparticlesfluorescencemolecular recognitionMolecular recognitionmesoporousMesoporous materialSensors
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Conception et synthèse de nouvelles sondes fluorogéniques à coeur Bodipy pour la détection

2020

Therefore this project is aimed at the development of novel improved multi-analyte fluorogenic probes for heavy metals ions and bioanalytes within the framework “AND” fluorescent molecular logic gates concept. The biothiols and cations of Cd(II), Pb(II), Cr(III) and Cu(II) heavy metals will be selected as the targeted analytes. To the best of our knowledge, no “AND” molecular logic gates using metal ions besides Zn(II), Hg(II), Ca(II) inputs, likewise no multi-analyte probes for biothiols along with heavy metal cations, has been described in the literature. While the development of a highly sensitive and selective recognition of thiols and metal cations has emerged as a significant interest…

Colorants BodipySmart probes[CHIM.CRIS]Chemical Sciences/CristallographySondes intelligentes[CHIM.CRIS] Chemical Sciences/CristallographyFluorescenceBodipy dyes
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Dye-Labeled Poly(organosiloxane) Microgels with Core−Shell Architecture

1999

Poly(organosiloxane) microgels are highly cross-linked rather monodisperse spherical particles of radius about 10 nm. Using a functionalized silane comonomer, i.e., (chlorobenzyl)trimethoxysilane, model particles suitable for studies in colloid physics are available:  photoreactive and fluorescent dyes can be covalently bound within the microgels to prepare tracers for diffusion studies using forced Rayleigh scattering (FRS) and fluorescence correlation spectroscopy (FCS). For the application as tracer particles, it is important not to influence the diffusion behavior by the coupled chromophores. Therefore, functionalized precursors with a core−shell architecture are used to minimize labeli…

ComonomerDispersityFluorescence correlation spectroscopySurfaces and InterfacesCondensed Matter PhysicsFluorescenceSilaneColloidchemistry.chemical_compoundPhotochromismchemistryChemical engineeringPolymer chemistryElectrochemistryRhodamine BGeneral Materials ScienceSpectroscopyLangmuir
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Citocentrifugación como un método adicional para estudiar celomitos de equinodermos: un enfoque comparativo que combina células vivas, preparaciones …

2021

Abstract Introduction: Echinoderm coelomocytes have traditionally been investigated through a morphological approach using light microscopy, which relies on the idea of constant cell shape as a stable character. However, this can be affected by biotic or abiotic conditions. Objective: To analyze if the consistency in cell morphology offered by the cytocentrifugation method, might be used as a convenient tool to study echinoderm coelomocytes. Methods: Cells of Echinaster (Othilia) brasiliensis (Asteroidea), Holothuria (Holothuria) tubulosa (Holothuroidea), Eucidaris tribuloides, Arbacia lixula, Lytechinus variegatus, and Echinometra lucunter (Echinoidea) were spread on microscope slides by c…

Comparative cell morphologyenergy-dispersive x-ray spectroscopyinmunología de invertebradosinvertebrate immunologyEnergy-dispersive x-ray spectroscopycomparative cell morphologyvibratile cellscélulas vibrátilesMicroscopyFluorescence microscopecomparative cell morphology; echinoderm physiology; energy-dispersive x-ray spectroscopy; invertebrate immunology; spherulocytes; vibratile cells.morfología celular comparativa; fisiología de equinodermos; espectroscopía de rayos-x de energía dispersiva; inmunología de invertebrados; esferulocitos; células vibrátiles.Arbacia lixulaesferulocitosLytechinus variegatusVibratile cellsespectroscopía de rayos-x de energía dispersivamorfología celular comparativabiologyechinoderm physiologyChemistryEchinoderm physiologyEchinometra lucunterbiology.organism_classificationspherulocytesSpherulocytesfisiología de equinodermosEchinodermBiochemistryEucidaris tribuloidesInvertebrate immunologyGeneral Agricultural and Biological SciencesHolothuriaRevista de Biología Tropical
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Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples

2014

Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle …

Computer and Information SciencesFluorescence-lifetime imaging microscopyMatching (graph theory)Cell SurvivalImage ProcessingAssociation (object-oriented programming)SciencerakkulatBioinformaticsTime-Lapse ImagingFluorescenceImage (mathematics)cellular structuresfluorescence imagingCell Line TumorMolecular Cell BiologyalgoritmitHumansComputer SimulationkuvantamismenetelmätPhysicsta113MicroscopyvesiclesMultidisciplinarySoftware Toolsbusiness.industryCytoplasmic VesiclesQRta1182Biology and Life SciencesSoftware EngineeringColocalizationExperimental dataPattern recognitionCell BiologyObject (computer science)imaging techniquesMolecular ImagingfluoresenssimikroskopiaSignal ProcessingEngineering and TechnologyMedicineArtificial intelligenceCellular Structures and OrganellesbusinessVesicle localizationResearch ArticlePLoS ONE
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Deep CNN for IIF Images Classification in Autoimmune Diagnostics

2019

The diagnosis and monitoring of autoimmune diseases are very important problem in medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An indirect immunofluorescence (IIF) test performed by Human Epithelial type 2 (HEp-2) cells as substrate antigen is the most common methods to determine ANA. In this paper we present an automatic HEp-2 specimen system based on a convolutional neural network method able to classify IIF images. The system consists of a module for features extraction based on a pre-trained AlexNet network and a classification phase for the cell-pattern association using six support vector machines and a k-nearest neighbors classifier. The class…

Computer science02 engineering and technologyConvolutional neural networklcsh:TechnologyIIF imageAlexNetlcsh:Chemistry03 medical and health sciencesconvolutional neural networks (CNNs)Autoimmune diseaseClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringGeneral Materials Scienceautoimmune diseasesInstrumentationlcsh:QH301-705.5030304 developmental biologyIIF imagesFluid Flow and Transfer Processes0303 health sciencesDeep cnnIndirect immunofluorescenceaccuracybusiness.industrylcsh:TProcess Chemistry and Technologyk-nearest neighbors (KNN)General EngineeringPattern recognitionIIfClass (biology)lcsh:QC1-999Computer Science ApplicationsSupport vector machinelcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040System parameters020201 artificial intelligence & image processingsupport vector machine (SVM)Artificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsApplied Sciences
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Deep Convolutional Neural Network for HEp-2 fluorescence intensity classification

2019

Indirect ImmunoFluorescence (IIF) assays are recommended as the gold standard method for detection of antinuclear antibodies (ANAs), which are of considerable importance in the diagnosis of autoimmune diseases. Fluorescence intensity analysis is very often complex, and depending on the capabilities of the operator, the association with incorrect classes is statistically easy. In this paper, we present a Convolutional Neural Network (CNN) system to classify positive/negative fluorescence intensity of HEp-2 IIF images, which is important for autoimmune diseases diagnosis. The method uses the best known pre-trained CNNs to extract features and a support vector machine (SVM) classifier for the …

Computer scienceSVM02 engineering and technologyConvolutional neural networklcsh:TechnologyIIF image030218 nuclear medicine & medical imaginglcsh:Chemistry03 medical and health sciences0302 clinical medicineClassifier (linguistics)Autoimmune disease0202 electrical engineering electronic engineering information engineeringGeneral Materials Scienceautoimmune diseasesReceiver operating characteristic (ROC) curveInstrumentationlcsh:QH301-705.5AccuracyIIF imagesFluid Flow and Transfer ProcessesIndirect immunofluorescencebusiness.industrylcsh:TProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionIIfGold standard (test)Convolutional Neural Network (CNN)lcsh:QC1-999Computer Science ApplicationsIntensity (physics)Support vector machineFluorescence intensitylcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)lcsh:Physics
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A multi-process system for HEp-2 cells classification based on SVM

2016

An automatic system for pre-segmented IIF images analysis was developed.A non-standard pipeline for supervised image classification was adopted.The system uses a two-level pyramid to retain some spatial information.From each cell image 216 features are extracted.15 SVM classifiers one-against-one have been implemented. This study addresses the classification problem of the HEp-2 cells using indirect immunofluorescence (IIF) image analysis, which can indicate the presence of autoimmune diseases by finding antibodies in the patient serum. Recently, studies have shown that it is possible to identify the cell patterns using IIF image analysis and machine learning techniques. In this paper we de…

Computer scienceSVM02 engineering and technologyImmunofluorescencecomputer.software_genre030218 nuclear medicine & medical imagingImage (mathematics)03 medical and health sciences0302 clinical medicineArtificial IntelligencePyramid0202 electrical engineering electronic engineering information engineeringmedicinePyramid (image processing)Spatial analysisAccuracy1707Contextual image classificationmedicine.diagnostic_testFeatures reductionIndirect immunofluorescencePipeline (software)Class (biology)Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)StainingSupport vector machineHep-2 cells classificationSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionData miningcomputerSoftware
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