Search results for "recognition"

showing 10 items of 3607 documents

Biological Effect of a Hybrid Anticancer Agent Based on Kinase and Histone Deacetylase Inhibitors on Triple-Negative (MDA-MB231) Breast Cancer Cells

2016

We examined the effects of the histone deacetylase inhibitor (HDACi) suberoylanilide\ud hydroxamic acid (SAHA) combined with the vascular endothelial growth factor receptor-1/2 inhibitor\ud (3Z)-5-hydroxy-3-(1H-pyrrol-2-ylmethylidene)-2,3-dihydro-1H-indol-2-one on MDA-MB-231 breast\ud cancer cells (triple-negative) in the form of both a cocktail of the separate compounds and a chemically\ud synthesized hybrid (N-hydroxy-N'-[(3Z)-2-oxo-3-(1H-pyrrol-2-ylmethylidene)-2,3-dihydro-1H-indol-\ud 5-yl]octanediamide). Comparative flow cytometric and Western blot analyses were performed on\ud cocktail- and hybrid-treated cells to evaluate cell cycle distribution, autophagy/apoptosis modulation,\ud an…

0301 basic medicineVascular Endothelial Growth Factor AIndolesCytotoxicityTriple Negative Breast Neoplasmsbreast cancer; MDA-MB231 cells; histone deacetylase inhibitor; vascular endothelial growth factor receptor-2 inhibitor; cytotoxicity; cell cycle; apoptosis; autophagy; mitochondrial metabolismHydroxamic AcidsCatalysi0302 clinical medicineBreast cancerTumor Cells CulturedCytotoxic T cellSettore BIO/06 - Anatomia Comparata E CitologiaSpectroscopyVorinostatVascular endothelial growth factor receptor-2 inhibitorApoptosis; Autophagy; Breast cancer; Cell cycle; Cytotoxicity; Histone deacetylase inhibitor; MDA-MB231 cells; Mitochondrial metabolism; Vascular endothelial growth factor receptor-2 inhibitor; Catalysis; Molecular Biology; Spectroscopy; Computer Science Applications1707 Computer Vision and Pattern Recognition; Physical and Theoretical Chemistry; Organic Chemistry; Inorganic ChemistryKinaseHistone deacetylase inhibitorapoptosisComputer Science Applications1707 Computer Vision and Pattern RecognitionGeneral MedicineCell cycleFlow CytometryComputer Science ApplicationsCell biologyMDA-MB231 cell030220 oncology & carcinogenesisFemaleQD0241Programmed cell deathmedicine.drug_classCell SurvivalBlotting WesternAntineoplastic AgentsBiologyCell cycleCatalysisArticleInorganic Chemistry03 medical and health sciencesmedicineAutophagyHumansPhysical and Theoretical ChemistryProtein Kinase InhibitorsMolecular BiologyQD0415Histone deacetylase inhibitorAutophagyOrganic ChemistryApoptosiHistone Deacetylase Inhibitors030104 developmental biologyApoptosisMitochondrial metabolismMDA-MB231 cellsHistone deacetylaseInternational Journal of Molecular Sciences; Volume 17; Issue 8; Pages: 1235
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Luminance Information Is Required for the Accurate Estimation of Contrast in Rapidly Changing Visual Contexts.

2020

Summary Visual perception scales with changes in the visual stimulus, or contrast, irrespective of background illumination. However, visual perception is challenged when adaptation is not fast enough to deal with sudden declines in overall illumination, for example, when gaze follows a moving object from bright sunlight into a shaded area. Here, we show that the visual system of the fly employs a solution by propagating a corrective luminance-sensitive signal. We use in vivo 2-photon imaging and behavioral analyses to demonstrate that distinct OFF-pathway inputs encode contrast and luminance. Predictions of contrast-sensitive neuronal responses show that contrast information alone cannot ex…

0301 basic medicineVisual perceptiongenetic structuresAccurate estimationFeature extractionStimulus (physiology)BiologyLuminanceGeneral Biochemistry Genetics and Molecular BiologyVisual processingContrast Sensitivity03 medical and health sciences0302 clinical medicineAnimalsComputer visionbusiness.industryGaze030104 developmental biologyDrosophila melanogasterPattern Recognition VisualVisual Perceptionsense organsArtificial intelligenceGeneral Agricultural and Biological Sciencesbusiness030217 neurology & neurosurgeryPhotic StimulationCurrent biology : CB
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Full-automatic computer aided system for stem cell clustering using content-based microscopic image analysis

2017

Abstract Stem cells are very original cells that can differentiate into other cells, tissues and organs, which play a very important role in biomedical treatments. Because of the importance of stem cells, in this paper we propose a full-automatic computer aided clustering system to assist scientists to explore potential co-occurrence relations between the cell differentiation and their morphological information in phenotype. In this proposed system, a multi-stage Content-based Microscopic Image Analysis (CBMIA) framework is applied, including image segmentation, feature extraction, feature selection, feature fusion and clustering techniques. First, an Improved Supervised Normalized Cuts (IS…

0301 basic medicinebusiness.industryComputer scienceFeature extractionBiomedical EngineeringStability (learning theory)Pattern recognitionFeature selection02 engineering and technologyImage segmentation03 medical and health sciences030104 developmental biologyFeature (computer vision)Robustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationArtificial intelligencebusinessCluster analysisBiocybernetics and Biomedical Engineering
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The janus face of NKT cell function in autoimmunity and infectious diseases

2018

Natural killer T cells (NKT) are a subset of T lymphocytes bridging innate and adaptive immunity. These cells recognize self and microbial glycolipids bound to non-polymorphic and highly conserved CD1d molecules. Three NKT cell subsets, type I, II and NKT-like expressing different antigen receptors (TCR) were described and TCR activation promotes intracellular events leading to specific functional activities. NKT can exhibit different functions depending on the secretion of soluble molecules and the interaction with other cell types. NKT cells act as regulatory cells in the defence against infections but, on the other hand, their effector functions can be involved in the pathogenesis of sev…

0301 basic medicineglycolipidsAutoimmunityReviewAdaptive Immunitymedicine.disease_causeAutoimmunityCatalysiimmunologylcsh:Chemistry0302 clinical medicineT-Lymphocyte Subsetslcsh:QH301-705.5SpectroscopyInnate lymphoid cellhemic and immune systemsComputer Science Applications1707 Computer Vision and Pattern RecognitionGeneral MedicineNKTNatural killer T cellAcquired immune systemComputer Science ApplicationsCell biologyCD1DmicrobesCell typechemical and pharmacologic phenomenaGlycolipidBiologyCD1dCommunicable DiseasesCatalysisInorganic Chemistry03 medical and health sciencesmedicineAnimalsHumansMicrobePhysical and Theoretical ChemistryMolecular BiologyInflammationT-cell receptorOrganic ChemistryModels ImmunologicalAlpha-galactosylceramideAlpha-galactosylceramide; Autoimmunity; CD1d; Glycolipids; Microbes; NKT; Sulfatide; Catalysis; Molecular Biology; Spectroscopy; Computer Science Applications1707 Computer Vision and Pattern Recognition; Physical and Theoretical Chemistry; Organic Chemistry; Inorganic ChemistryImmunity InnateSettore MED/16 - Reumatologia030104 developmental biologylcsh:Biology (General)lcsh:QD1-999biology.proteinNatural Killer T-CellsSulfatideCD8030215 immunology
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Graphical Workflow System for Modification Calling by Machine Learning of Reverse Transcription Signatures

2019

Modification mapping from cDNA data has become a tremendously important approach in epitranscriptomics. So-called reverse transcription signatures in cDNA contain information on the position and nature of their causative RNA modifications. Data mining of, e.g. Illumina-based high-throughput sequencing data, is therefore fast growing in importance, and the field is still lacking effective tools. Here we present a versatile user-friendly graphical workflow system for modification calling based on machine learning. The workflow commences with a principal module for trimming, mapping, and postprocessing. The latter includes a quantification of mismatch and arrest rates with single-nucleotide re…

0301 basic medicinelcsh:QH426-470Downstream (software development)Computer scienceRT signatureMachine learningcomputer.software_genre[SDV.BBM.BM] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyField (computer science)m1A03 medical and health sciencesRNA modifications0302 clinical medicineEpitranscriptomics[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]GeneticsTechnology and CodeGalaxy platformGenetics (clinical)ComputingMilieux_MISCELLANEOUSbusiness.industryPrincipal (computer security)[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyAutomationWatson–Crick faceVisualizationlcsh:Geneticsmachine learningComputingMethodologies_PATTERNRECOGNITION030104 developmental biologyWorkflow030220 oncology & carcinogenesisMolecular Medicine[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]TrimmingArtificial intelligencebusinesscomputer
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Review: the Use of Electromyography on Food Texture Assessment

2001

Sensory evaluation (SE) involves evoking, measuring and interpreting human responses to the properties of foods. Among these properties texture is an important one for food acceptability. Texture is mainly perceived through mastication, a process that changes food characteristics throughout time by comminuting and salivation. Electromyography (EMG) has emerged as a new tool in sensory evaluation mainly for assessing texture characteristics. Thus, it is interesting to analyze the knowledge so far generated and the procedures employed. Bipolar surface electrodes are placed on the four main masticatory muscles (masseter right-left and temporalis right-left) and their electric activity recorded…

0301 basic medicinemedicine.diagnostic_testbusiness.industryGeneral Chemical EngineeringPattern recognition030206 dentistryElectromyographyTexture (music)Industrial and Manufacturing EngineeringMasticatory force03 medical and health sciences030104 developmental biology0302 clinical medicineCrunchinessFood texturemedicineCooked meatArtificial intelligencebusinessMasticationFood ScienceMathematicsFood Science and Technology International
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Automatic detection and measurement of nuchal translucency.

2017

In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…

0301 basic medicinemedicine.medical_specialtyWavelet AnalysisFirst trimester of pregnancyHealth InformaticsSensitivity and SpecificityWavelet analysi030218 nuclear medicine & medical imagingPattern Recognition AutomatedMachine Learning03 medical and health sciencesPrenatal ultrasound0302 clinical medicineNuchal regionNuchal translucencyUltrasound fetal examinationMedian sagittal sectionNuchal Translucency MeasurementImage Interpretation Computer-AssistedMedicineHumansPixelbusiness.industryMulti resolution analysisUltrasoundReproducibility of ResultsPattern recognitionComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsSurgeryClinical ultrasound030104 developmental biologyNuchal translucencyArtificial intelligenceDown SyndromebusinessNuchal Translucency MeasurementAlgorithmsComputers in biology and medicine
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PRR signaling during in vitro macrophage differentiation from progenitors modulates their subsequent response to inflammatory stimuli.

2017

Toll-like receptor (TLR) agonists drive hematopoietic stem and progenitor cells (HSPCs) to differentiate along the myeloid lineage in vitro and also in vivo following infection. In this study, we used an in vitro model of HSPC differentiation to investigate the functional consequences (cytokine production) that exposing HSPCs to various pathogen-associated molecular patterns (PAMPs) and Candida albicans cells have on the subsequently derived macrophages. Mouse HSPCs (Lin- cells) were cultured with GM-CSF to induce macrophage differentiation in the presence or absence of the following pattern recognition receptor (PRR) agonists: Pam3CSK4 (TLR2 ligand), LPS (TLR4 ligand), depleted zymosan (wh…

0301 basic medicinemedicine.medical_treatmentClinical BiochemistryImmunologyProinflammatory cytokineMajor Histocompatibility Complex03 medical and health scienceschemistry.chemical_compoundMicemedicineEscherichia coliImmunology and AllergyAnimalsAntigens LyProgenitor cellCells CulturedChemistryMacrophagesZymosanPattern recognition receptorCell DifferentiationFlow CytometryCell biologyMice Inbred C57BLHaematopoiesisTLR2030104 developmental biologyCytokineReceptors Pattern RecognitionTLR4CytokinesFemaleSignal TransductionEuropean cytokine network
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Drosophila Food-Associated Pheromones: Effect of Experience, Genotype and Antibiotics on Larval Behavior

2016

International audience; Animals ubiquitously use chemical signals to communicate many aspects of their social life. These chemical signals often consist of environmental cues mixed with species-specific signals-pheromones-emitted by conspecifics. During their life, insects can use pheromones to aggregate, disperse, choose a mate, or find the most suitable food source on which to lay eggs. Before pupariation, larvae of several Drosophila species migrate to food sources depending on their composition and the presence of pheromones. Some pheromones derive from microbiota gut activity and these food-associated cues can enhance larval attraction or repulsion. To explore the mechanisms underlying…

0301 basic medicinemelanogasterlcsh:Medicine[ SDV.BA ] Life Sciences [q-bio]/Animal biologyBiochemistryPheromonesLarvaeAntibioticsMedicine and Health Sciencesinsectslcsh:ScienceAnimal Signaling and CommunicationLarvaMultidisciplinaryInsect MetamorphosisbiologyAnimal BehaviorBehavior AnimalEcologyAntimicrobialscommunicationDrosophila Melanogaster[SDV.BA]Life Sciences [q-bio]/Animal biologyaggressionsex-pheromonesDrugsAnimal ModelsAttractionPupaSex pheromoneLarvacourtshipNeurosciences (Sciences cognitives)DrosophilaDrosophila melanogasterCuesrecognitionPupariationResearch ArticleattractionComputer and Information SciencesArthropodaGenotypeZoologyResearch and Analysis MethodsMicrobiology03 medical and health sciencesModel OrganismsInvertebrate ZoologySEX-PHEROMONES;MELANOGASTER;AGGRESSION;COURTSHIP;COMMUNICATION;RECOGNITION;ATTRACTION;EVOLUTION;MUTATION;INSECTSMicrobial ControlevolutionAnimalsDrosophilaSensory cuePharmacologyBehaviorMetamorphosisData Visualizationlcsh:RfungiOrganismsBiology and Life SciencesPupaebiology.organism_classificationZoologie des invertébrésInvertebratesColor Codes030104 developmental biologyFoodOdorantslcsh:QmutationZoologyEntomologyNeuroscienceDevelopmental Biology
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Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors

2017

International audience; The perception of odor is an important component of smell; the first step of odor detection, and the discrimination of structurally diverse odorants depends on their interactions with olfactory receptors (ORs). Indeed, the perception of an odor's quality results from a combinatorial coding, in which the deciphering remains a major challenge. Several studies have successfully established links between odors and odorants by categorizing and classifying data. Hence, the categorization of odors appears to be a promising way to manage odors. In the proposed study, we performed a computational analysis using odor descriptions of the odorants present in Flavor-Base 9th Edit…

0301 basic medicinemultidimensional scalingmedia_common.quotation_subjectAgglomerative hierarchical clusteringKohonen self-organizing mapsodorants03 medical and health sciences0302 clinical medicinePerceptionComputational analysisMultidimensional scalingmedia_commonChemistrybusiness.industrymusculoskeletal neural and ocular physiologyPattern recognitionKohonen self organizing mapGeneral Chemistrycategorization030104 developmental biologyCategorizationOdorodor notesagglomerative hierarchical clusteringArtificial intelligenceMultivariate statisticalbusiness[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition030217 neurology & neurosurgerypsychological phenomena and processesFood Science
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