Search results for "Presentation"

showing 10 items of 2405 documents

MHC class I loaded ligands from breast cancer cell lines: A potential HLA-I-typed antigen collection.

2018

Abstract To build a catalog of peptides presented by breast cancer cells, we undertook systematic MHC class I immunoprecipitation followed by elution of MHC class I-loaded peptides in breast cancer cells. We determined the sequence of 3196 MHC class I ligands representing 1921 proteins from a panel of 20 breast cancer cell lines. After removing duplicate peptides, i.e., the same peptide eluted from more than one cell line, the total number of unique peptides was 2740. Of the unique peptides eluted, more than 1750 had been previously identified, and of these, sixteen have been shown to be immunogenic. Importantly, half of these immunogenic peptides were shared between different breast cancer…

0301 basic medicineProteomicsPlant BiologyPeptideLigandsBiochemistryEpitopeAnalytical ChemistryEpitopesBreast cancerT cell-mediated immune responseHLA Antigens2.1 Biological and endogenous factorsAetiologyCancerchemistry.chemical_classificationAntigen PresentationTumorbiologyBiochemistry & Molecular BiologyBiophysicsBreast NeoplasmsArticleCell LineVaccine Related03 medical and health sciencesImmune systemBreast cancerAntigenAntigens NeoplasmCell Line TumorMHC class ImedicineGeneticsHumansAmino Acid SequenceAntigensMHC class I-restricted peptidesTumor associated antigensPreventionHistocompatibility Antigens Class ICancermedicine.diseaseHigh-Throughput Screening Assays030104 developmental biologychemistryCell cultureNeo-antigensMutationbiology.proteinCancer researchNeoplasmImmunizationBiochemistry and Cell Biology
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Variable Ranking Feature Selection for the Identification of Nucleosome Related Sequences

2018

Several recent works have shown that K-mer sequence representation of a DNA sequence can be used for classification or identification of nucleosome positioning related sequences. This representation can be computationally expensive when k grows, making the complexity in spaces of exponential dimension. This issue effects significantly the classification task computed by a general machine learning algorithm used for the purpose of sequence classification. In this paper, we investigate the advantage offered by the so-called Variable Ranking Feature Selection method to select the most informative k − mers associated to a set of DNA sequences, for the final purpose of nucleosome/linker classifi…

0301 basic medicineSequenceSettore INF/01 - InformaticaEpigenomic030102 biochemistry & molecular biologybusiness.industryComputer scienceDeep learningPattern recognitionFeature selectionDNA sequencesNucleosomesRanking (information retrieval)Set (abstract data type)03 medical and health sciencesVariable (computer science)030104 developmental biologyDimension (vector space)Feature selectionDeep learning modelsArtificial intelligenceDeep learning models Feature selection DNA sequences Epigenomic NucleosomesRepresentation (mathematics)business
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The latent geometry of the human protein interaction network

2017

Abstract Motivation A series of recently introduced algorithms and models advocates for the existence of a hyperbolic geometry underlying the network representation of complex systems. Since the human protein interaction network (hPIN) has a complex architecture, we hypothesized that uncovering its latent geometry could ease challenging problems in systems biology, translating them into measuring distances between proteins. Results We embedded the hPIN to hyperbolic space and found that the inferred coordinates of nodes capture biologically relevant features, like protein age, function and cellular localization. This means that the representation of the hPIN in the two-dimensional hyperboli…

0301 basic medicineStatistics and ProbabilityGeometric analysisComputer scienceHyperbolic geometrySystems biologyComplex systemContext (language use)GeometryBiochemistryProtein–protein interaction03 medical and health sciencesInteraction networkHumansProtein Interaction MapsRepresentation (mathematics)Cluster analysisMolecular BiologySystems BiologyHyperbolic spaceProteinsFunction (mathematics)Original PapersComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicsEmbeddingSignal transductionAlgorithmsSignal Transduction
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Gut germinal center regeneration and enhanced antiviral immunity by mesenchymal stem/stromal cells in SIV infection.

2021

Although antiretroviral therapy suppresses HIV replication, it does not eliminate viral reservoirs or restore damaged lymphoid tissue, posing obstacles to HIV eradication. Using the SIV model of AIDS, we investigated the effect of mesenchymal stem/stromal cell (MSC) infusions on gut mucosal recovery, antiviral immunity, and viral suppression and determined associated molecular/metabolic signatures. MSC administration to SIV-infected macaques resulted in viral reduction and heightened virus-specific responses. Marked clearance of SIV-positive cells from gut mucosal effector sites was correlated with robust regeneration of germinal centers, restoration of follicular B cells and T follicular h…

0301 basic medicineStromal cellAntigen presentationSimian Acquired Immunodeficiency SyndromeMesenchymal Stem Cell TransplantationAIDS/HIV03 medical and health sciences0302 clinical medicinemedicineAnimalsIntestinal MucosaB cellInnate immune systembiologyMesenchymal stem cellGerminal centerMesenchymal Stem CellsGeneral MedicineCellular immune responseGerminal CenterMacaca mulattaImmunity Humoral030104 developmental biologymedicine.anatomical_structure030220 oncology & carcinogenesisImmunologybiology.proteinCytokinesSimian Immunodeficiency VirusAntibodyCell activationResearch ArticleJCI insight
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Towards Self-explanatory Ontology Visualization with Contextual Verbalization

2016

Ontologies are one of the core foundations of the Semantic Web. To participate in Semantic Web projects, domain experts need to be able to understand the ontologies involved. Visual notations can provide an overview of the ontology and help users to understand the connections among entities. However, the users first need to learn the visual notation before they can interpret it correctly. Controlled natural language representation would be readable right away and might be preferred in case of complex axioms, however, the structure of the ontology would remain less apparent. We propose to combine ontology visualizations with contextual ontology verbalizations of selected ontology (diagram) e…

0301 basic medicineStructure (mathematical logic)Computer sciencebusiness.industry05 social sciences050301 educationRepresentation (arts)Ontology (information science)computer.software_genreNotationlanguage.human_languageDomain (software engineering)03 medical and health sciences030104 developmental biologyControlled natural languagelanguageArtificial intelligencebusiness0503 educationcomputerSemantic WebNatural language processingAxiom
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Lymph node - an organ for T-cell activation and pathogen defense.

2016

The immune system is a multicentered organ that is characterized by intimate interactions between its cellular components to efficiently ward off invading pathogens. A key constituent of this organ system is the distinct migratory activity of its cellular elements. The lymph node represents a pivotal meeting point of immune cells where adaptive immunity is induced and regulated. Additionally, besides barrier tissues, the lymph node is a critical organ where invading pathogens need to be eliminated in order to prevent systemic distribution of virulent microbes. Here, we explain how the lymph node is structurally and functionally organized to fulfill these two critical functions - pathogen de…

0301 basic medicineT cellImmunologyAntigen presentationContext (language use)BiologyAdaptive ImmunityCD8-Positive T-LymphocytesLymphocyte Activation03 medical and health sciences0302 clinical medicineImmune systemCell MovementmedicineLymph node stromal cellImmunology and AllergyCytotoxic T cellAnimalsHumansLymph nodeAntigens ViralAntigen PresentationDendritic CellsAcquired immune system030104 developmental biologymedicine.anatomical_structureVirus DiseasesImmunologyHost-Pathogen InteractionsLymph Nodes030215 immunologyImmunological reviews
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Combined Analysis of Antigen Presentation and T-cell Recognition Reveals Restricted Immune Responses in Melanoma.

2018

Abstract The quest for tumor-associated antigens (TAA) and neoantigens is a major focus of cancer immunotherapy. Here, we combine a neoantigen prediction pipeline and human leukocyte antigen (HLA) peptidomics to identify TAAs and neoantigens in 16 tumors derived from seven patients with melanoma and characterize their interactions with their tumor-infiltrating lymphocytes (TIL). Our investigation of the antigenic and T-cell landscapes encompassing the TAA and neoantigen signatures, their immune reactivity, and their corresponding T-cell identities provides the first comprehensive analysis of cancer cell T-cell cosignatures, allowing us to discover remarkable antigenic and TIL similarities b…

0301 basic medicineT cellmedicine.medical_treatmentT-LymphocytesAntigen presentationHuman leukocyte antigenMice SCIDBiologyArticle03 medical and health sciencesMiceImmune systemLymphocytes Tumor-InfiltratingAntigenCancer immunotherapyAntigens NeoplasmMice Inbred NODmedicineTumor Cells CulturedAnimalsHumansMelanomaAntigen Presentationintegumentary systemMelanomaHistocompatibility Antigens Class Imedicine.diseaseXenograft Model Antitumor Assays3. Good health030104 developmental biologymedicine.anatomical_structureOncologyCancer cellCancer researchCancer discovery
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Novel Opportunities for Cathepsin S Inhibitors in Cancer Immunotherapy by Nanocarrier-Mediated Delivery

2020

Cathepsin S (CatS) is a secreted cysteine protease that cleaves certain extracellular matrix proteins, regulates antigen presentation in antigen-presenting cells (APC), and promotes M2-type macrophage and dendritic cell polarization. CatS is overexpressed in many solid cancers, and overall, it appears to promote an immune-suppressive and tumor-promoting microenvironment. While most data suggest that CatS inhibition or knockdown promotes anti-cancer immunity, cell-specific inhibition, especially in myeloid cells, appears to be important for therapeutic efficacy. This makes the design of CatS selective inhibitors and their targeting to tumor-associated M2-type macrophages (TAM) and DC an attr…

0301 basic medicineT-Lymphocytesmedicine.medical_treatmentReview02 engineering and technologyCancer immunotherapyNeoplasmsTumor-Associated MacrophagesTumor Microenvironmentcysteine proteaseMolecular Targeted TherapySulfoneslcsh:QH301-705.5Cathepsin SAntigen PresentationDrug Carrierscysteine cathepsintumor-associated macrophage (TAM)ChemistrynanoparticleAzepinesDipeptidesGeneral Medicine021001 nanoscience & nanotechnologyGene Expression Regulation NeoplasticImmunotherapy0210 nano-technologydendritic cellAntigen presentationAntineoplastic AgentsTumor-associated macrophageM2 macrophage03 medical and health sciencesLeucinemedicineHumansProtease InhibitorsAntigen-presenting celltargetingtherapypolarizationTumor microenvironmentT cellDendritic CellsDendritic cellextracellular matrix (ECM)Cathepsinstumor associated macrophage030104 developmental biologylcsh:Biology (General)antigen presenting cellCancer researchNanoparticlesimmune suppressionNanocarriers
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Activation and selective IL-17 response of human Vγ9Vδ2 T lymphocytes by TLR-activated plasmacytoid dendritic cells.

2016

// Elena Lo Presti 1,2 , Nadia Caccamo 1,2 , Valentina Orlando 1,2 , Francesco Dieli 1,2 and Serena Meraviglia 1,2 1 Central Laboratory of Advanced Diagnosis and Biomedical Research (CLADIBIOR), University of Palermo, Palermo, Italy 2 Department of Biopathology and Medical Biotechnologies (DIBIMED), University of Palermo, Palermo, Italy Correspondence to: Serena Meraviglia, email: // Keywords : γδ T cells, plasmacytoid dendritic cells, IL-17, TLR activation, proliferation, Immunology and Microbiology Section, Immune response, Immunity Received : July 20, 2016 Accepted : August 02, 2016 Published :August 31, 2016 Abstract Vγ9Vδ2 T cells and plasmacytoid dendritic cells (pDCs) are two distinc…

0301 basic medicineTLR activationCellCell CommunicationLigandsLymphocyte Activation0302 clinical medicineT-Lymphocyte SubsetsCoculture TechniqueAntigen PresentationInterleukin-17Research Paper: Immunologyhemic and immune systemsIL-17medicine.anatomical_structurePhenotypeOncologyplasmacytoid dendritic cellsImmunology and Microbiology SectionInterleukin 17HumanCell typeproliferationCD40 LigandLigandBiologyDendritic Cellγδ T cells03 medical and health sciencesInducible T-Cell Co-Stimulator LigandInterferon-gammaImmune systemImmunityplasmacytoid dendritic cellmedicineHumansImmune responseCell Proliferationγδ T cellCD40Innate immune systemImmunityTLR9Dendritic CellsReceptors OX40Coculture TechniquesImmunity Innate030104 developmental biologyImmunologybiology.proteinLeukocytes MononuclearCpG IslandsCpG IslandImmunologic Memory030215 immunologyOncotarget
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Deep learning models for bacteria taxonomic classification of metagenomic data.

2018

Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…

0301 basic medicineTime FactorsDBNComputer scienceBiochemistryStructural BiologyRNA Ribosomal 16SDatabases Geneticlcsh:QH301-705.5Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionibiologySettore INF/01 - InformaticaShotgun sequencingApplied MathematicsAmpliconClassificationComputer Science Applicationslcsh:R858-859.7DNA microarrayShotgunAlgorithmsCNN030106 microbiologyk-mer representationlcsh:Computer applications to medicine. Medical informaticsDNA sequencing03 medical and health sciencesMetagenomicDeep LearningMolecular BiologyBacteriaModels GeneticPhylumbusiness.industryDeep learningResearchReproducibility of ResultsPattern recognitionBiological classification16S ribosomal RNAbiology.organism_classificationAmpliconHypervariable region030104 developmental biologyTaxonlcsh:Biology (General)MetagenomicsMetagenomeArtificial intelligenceMetagenomicsNeural Networks ComputerbusinessClassifier (UML)BacteriaBMC bioinformatics
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