Search results for "Protein Abundance"

showing 4 items of 4 documents

Clinical and Functional Studies Reveal That TP73 Isoforms Levels Are Associated with Prognosis and RA-Resistance in Acute Promyelocytic Leukemia

2019

Background: TP73 isoforms gained particular relevance in acute promyelocytic leukemia (APL) since Bernasola et al (JEM. 2004) demonstrated that TAp73 was directly regulated by the PML protein in the nuclear body. The isoforms differ in their transcriptional activity, with those lacking domains in the N-terminal part of the protein exerting a dominant negative effect on TP73 function. In a retrospective analysis of patients with APL treated in ICAPL study, Lucena-Araujo et al (Blood 2015) demonstrated the association between higher ΔNp73/TAp73 ratio values and poor clinical outcome. However,there is a diversity of TP73 isoforms and specially those lacking N-terminal domains (e.g.ΔEx2p73, ΔEx…

Acute promyelocytic leukemiaTranscriptional activitymedicine.medical_specialtySupervisory boardbusiness.industryeducationImmunologyDisease progressionCell BiologyHematologyNewly diagnosedmedicine.diseaseBiochemistryFamily medicinemedicineFunctional studiesProtein abundancebusinessHematology+Oncologyhealth care economics and organizationsBlood
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Proteome response of Tribolium castaneum larvae to Bacillus thuringiensis toxin producing strains.

2012

Susceptibility of Tribolium castaneum (Tc) larvae was determined against spore-crystal mixtures of five coleopteran specific and one lepidopteran specific Bacillus thuringiensis Cry toxin producing strains and those containing the structurally unrelated Cry3Ba and Cry23Aa/Cry37Aa proteins were found toxic (LC(50) values 13.53 and 6.30 µg spore-crystal mixture/µL flour disc, respectively). Using iTRAQ combined with LC-MS/MS allowed the discovery of seven novel differentially expressed proteins in early response of Tc larvae to the two active spore-crystal mixtures. Proteins showing a statistically significant change in treated larvae compared to non-intoxicated larvae fell into two major cat…

Models MolecularProteomicsProteomeTranscription GeneticOdorant bindingProtein ConformationApplied Microbiologylcsh:MedicinePathogenesismedicine.disease_causeReceptors OdorantBiochemistryProtein structureBacillus thuringiensislcsh:SciencePhylogenyTriboliumMultidisciplinaryImmune System ProteinsSpectrometric Identification of ProteinsbiologyChemosensory proteinAgricultureHost-Pathogen InteractionLarvaHost-Pathogen InteractionsInsect ProteinsResearch Articleanimal structuresProtein subunitLipoproteinsBacterial ToxinsMolecular Sequence DataBacillus thuringiensisMicrobiologyBacterial ProteinsRibosomal proteinMicrobial ControlDefense ProteinsmedicineAnimalsAmino Acid SequencePesticidesBiologyToxinfungilcsh:RProteinsbiology.organism_classificationMolecular biologyApolipoproteinsOdorant-binding proteinbiology.proteinlcsh:QPest ControlSequence AlignmentZoologyEntomologyProtein AbundancePLoS ONE
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Cellular effects of bacterial N-3-Oxo-dodecanoyl-L-Homoserine lactone on the sponge Suberites domuncula (Olivi, 1792): insights into an intimate inte…

2014

International audience; Sponges and bacteria have lived together in complex consortia for 700 million years. As filter feeders, sponges prey on bacteria. Nevertheless, some bacteria are associated with sponges in symbiotic relationships. To enable this association, sponges and bacteria are likely to have developed molecular communication systems. These may include molecules such as N-acyl-L-homoserine lactones, produced by Gram-negative bacteria also within sponges. In this study, we examined the role of N-3-oxododecanoyl-L-homoserine lactone (3-oxo-C12-HSL) on the expression of immune and apoptotic genes of the host sponge Suberites domuncula. This molecule seemed to inhibit the sponge inn…

ProteomicsApoptosisPathogenesisPathology and Laboratory MedicineBiochemistrycaspase 74-Butyrolactonecaspase 3lcsh:ScienceCytoskeletoncaspase like 7 gene0303 health sciencesToll-like receptorMarine Ecologytoll like receptorGenomicsproto oncogeneEndocytosisCell biologySuberites domunculaCellular Structures and Organellesalpha actininCell signalingtoll like receptor associated factor 6Gram negative bacteriumparacrine signalingMicrobiology03 medical and health sciencesGeneticsRNA Messengerhost pathogen interactionprotein expressiontwo dimensional electrophoresisBacteria030306 microbiologyEcology and Environmental Scienceslcsh:RBiology and Life SciencesComputational BiologyImmunity Innatecarrier proteinSpongebacterial membranelcsh:Qimmunological toleranceSuberitesProtein AbundanceSuberitessuberites domuncula[SDV]Life Sciences [q-bio]lcsh:MedicineMolecular Cell BiologyMedicine and Health Sciencesinnate immunityperforinMultidisciplinaryEcologybiologymessenger RNAarticlecell communicationAnimal Modelsmatrix assisted laser desorption ionization time of flight mass spectrometryunclassified drugPoriferaHost-Pathogen InteractionscytotoxicityactinTranscriptome Analysishormone actionResearch ArticleSymbiotic bacteriaprotein bcl 2Marine BiologycofilinResearch and Analysis Methodsn (3 oxododecanoyl)homoserine lactoneMicrobial EcologycogninModel OrganismsHomoserineAnimalscontrolled study14. Life underwatergeneSymbiosiscell viabilityadenosine triphosphatase030304 developmental biologynonhumanChemical EcologyMembrane ProteinsCell Biologytumor necrosis factor receptor associated factor 6Genome Analysisbiology.organism_classificationalpha tubulinGene Expression RegulationMembrane proteingene expressioncaspase like 3 geneGenome Expression AnalysisBacteriaPLoS ONE
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Using Deep Learning to Extrapolate Protein Expression Measurements

2020

Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, in…

ProteomicsIn silicoQuantitative proteomicsComputational biologyBiologyBiochemistryprotein abundance predictionMass SpectrometryProtein expressionMice03 medical and health sciencesDeep LearningAbundance (ecology)AnimalsMolecular BiologyGeneResearch Articles030304 developmental biologydeep learning networks0303 health sciencesUniProt keywordsbusiness.industryDeep learning030302 biochemistry & molecular biologyProteinsRNAMolecular Sequence AnnotationMissing dataGene OntologyArtificial intelligencebusinessResearch ArticlePROTEOMICS
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