Search results for "Bios"

showing 10 items of 2557 documents

A novel peat-based biosorbent for the removal of phosphate from synthetic and real wastewater and possible utilization of spent sorbent in land appli…

2015

AbstractRemoval of potentially harmful phosphorus compounds from wastewater by adsorption onto biosorbents is a cost-effective alternative to the conventional treatment methods. Raw peat and peat modified with iron(III) hydroxy ions were used in this study to remove phosphate ions from synthetic solution and household wastewater. Interaction of iron(III) ions with carboxylic groups of peat occurred during peat modification, which was confirmed by the FTIR technique. The effect of the initial phosphate concentration, pH, contact time, temperature, and ionic strength was studied in batch experiments. It was found that the sorption capacity increased with the increasing temperature, i.e. the m…

SorbentPeatChemistryBiosorptionEnvironmental engineeringOcean EngineeringSorption02 engineering and technology010501 environmental sciences021001 nanoscience & nanotechnologyPhosphate01 natural sciencesPollutionchemistry.chemical_compoundAdsorptionWastewaterIonic strength0210 nano-technology0105 earth and related environmental sciencesWater Science and TechnologyNuclear chemistryDesalination and Water Treatment
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Determination of aerobic-anaerobic metabolism-related compounds in aChaoborus flavicans population by infusion ion trap mass spectrometry of extracts…

2006

In a daily migration, the aquatic larvae of Chaoborus flavicans (a phantom midge) alternate oxygen-saturated and anoxic lake strata. To investigate this cycle, larvae were collected at a natural environment, and acetate, propionate, pyruvate, lactate, glycerol, phosphate, maleate, succinate, glucose and citrate were determined. Each larva was homogenized with 200 microL water and deproteinized with a spin-filter; 50 microL aliquots were mixed with 50 microL of a buffer containing 80 mM propylamine, 20 mM HCl and 0.06 mM 2,4-dihydroxybenzoic acid (internal standard) in methanol. The extracts were infused in an electrospray ionization ion-trap mass spectrometer. The limits of detection for th…

Spectrometry Mass Electrospray IonizationElectrospray ionizationPopulationCeratopogonidaeMass spectrometryModels BiologicalAnalytical Chemistrychemistry.chemical_compoundFumaratesChaoborus flavicansGlycerolAnimalsAnaerobiosiseducationSpectroscopychemistry.chemical_classificationeducation.field_of_studyChromatographyOrganic ChemistryDiscriminant AnalysisMetabolismAerobiosischemistryLarvaPropionateAmmonium acetateRapid Communications in Mass Spectrometry
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3′-Demethyldihydromaldoxin and dihydromaldoxin, two anti-inflammtory diaryl ethers from a Steganospora species

2012

CXCL10 (IP-10) is a highly inducible chemoattractant, which contributes to the recruitment of inflammatory cells such as macrophages and T-lymphocytes and thereby has important roles in chronic inflammatory conditions. In a search for new inhibitors of CXCL10 expression in MonoMac6 (MM6) cells, the new diaryl ether 3'-demethyldihydromaldoxin (1) along with the known compound dihydromaldoxin (2), were isolated from fermentations of a Steganospora species. The structures of the compounds were elucidated by a combination of one- and two-dimensional NMR spectroscopy and mass spectrometry. Compounds (1) and (2) inhibited lipopolysaccharide (LPS)/interferon-γ (IFN-γ)-induced CXCL10 promoter activ…

Spectrometry Mass Electrospray IonizationLipopolysaccharideCell SurvivalAntiparasiticmedicine.drug_classAnti-Inflammatory AgentsBiologyTransfectionCell LineInhibitory Concentration 50Lactoneschemistry.chemical_compoundBiosynthesisInterferonDrug DiscoverymedicineProtein biosynthesisAnimalsHumansCXCL10Spiro CompoundsNuclear Magnetic Resonance BiomolecularPharmacologyDose-Response Relationship DrugMolecular StructurePhenyl EthersFungiChemotaxisTransfectionChemokine CXCL10chemistryBiochemistrymedicine.drugThe Journal of Antibiotics
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Where Does Nε-Trimethyllysine for the Carnitine Biosynthesis in Mammals Come from?

2014

N(ε)-trimethyllysine (TML) is a non-protein amino acid which takes part in the biosynthesis of carnitine. In mammals, the breakdown of endogenous proteins containing TML residues is recognized as starting point for the carnitine biosynthesis. Here, we document that one of the main sources of TML could be the vegetables which represent an important part of daily alimentation for most mammals. A HPLC-ESI-MS/MS method, which we previously developed for the analysis of N(G)-methylarginines, was utilized to quantitate TML in numerous vegetables. We report that TML, believed to be rather rare in plants as free amino acid, is, instead, ubiquitous in them and at not negligible levels. The occurrenc…

Spectrometry Mass Electrospray IonizationLysinelcsh:MedicineGene ExpressionEndogenyPlant ScienceBiologyBiosynthesisFree aminoBiochemistryFluorescenceAnalytical Chemistrychemistry.chemical_compoundBiosynthesisCarnitineChemical BiologyVegetablesGeneticsmedicineAnimalsCarnitinelcsh:ScienceBiologyProtein MetabolismNutritionMammalschemistry.chemical_classificationChromatographyChromatography Reverse-PhaseMultidisciplinaryPlant ExtractsLysinelcsh:RApplied ChemistryBiosynthetic PathwaysAmino acidChemistryProtein catabolismMetabolismBiochemistrychemistryCarnitine biosynthesisMedicinelcsh:QProtein TranslationResearch ArticleChromatography Liquidmedicine.drugPLoS ONE
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Levansucrases from Pseudomonas syringae pv. tomato and P. chlororaphis subsp. aurantiaca: Substrate specificity, polymerizing properties and usage of…

2011

Levansucrases of Pseudomonas syringae pv. tomato DC3000 (Lsc3) and Pseudomonas chlororaphis subsp. aurantiaca (also Pseudomonas aurantiaca) (LscA) have 73% identity of protein sequences, similar substrate specificity and kinetic properties. Both enzymes produce levan and fructooligosaccharides (FOS) of varied length from sucrose, raffinose and sugar beet molasses. A novel high-throughput chip-based nanoelectrospray mass spectrometric method was applied to screen alternative fructosyl acceptors for levansucrases. Lsc3 and LscA could both transfructosylate D-xylose, D-fucose, L- and D-arabinose, D-ribose, D-sorbitol, xylitol, xylobiose, D-mannitol, D-galacturonic acid and methyl-α-D-glucopyra…

Spectrometry Mass Electrospray IonizationSucroseRecombinant Fusion ProteinsMolecular Sequence DataPseudomonas syringaeBioengineeringFructoseXylitolApplied Microbiology and BiotechnologySubstrate SpecificityStructure-Activity Relationshipchemistry.chemical_compoundRaffinoseBacterial ProteinsPseudomonasPseudomonas aurantiacaPseudomonas syringaeXylobioseHistidineAmino Acid SequenceRaffinoseHistidinebiologySubstrate (chemistry)General Medicinebiology.organism_classificationPseudomonas chlororaphisFructansHexosyltransferaseschemistryBiochemistryMutagenesis Site-DirectedChromatography Thin LayerOligopeptidesSequence AlignmentBiotechnologyJournal of Biotechnology
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Measurement technique for real-time and low-cost biosensing using photonic bandgap structures

2011

We present a sensing technique based on using photonic bandgap structures where only the output power is monitored, without the need of tunable sources or spectrum analyzers, thus providing a real-time and low-cost system.

Spectrum analyzerMaterials sciencebusiness.industryPhysics::OpticsPower (physics)Electricity generationOpticsHardware_INTEGRATEDCIRCUITSOptoelectronicsPhotonicsbusinessRefractive indexBiosensorPhotonic bandgapPhotonic crystal8th IEEE International Conference on Group IV Photonics
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Effect of starvation on haemolymph vitellogenins and ovary uptake in Spilostethus pandurus

1993

Abstract 1. 1. Starvation reduces haemolymph vitellogenins and their incorporation by developing oocytes in S. pandurus adult females. 2. 2. Access to food restores unspecifically the protein levels in both haemolymph and ovaries. 3. 3. Topical treatments with JH promote de novo specific synthesis of vitellogenins and incorporation by the ovaries. 4. 4. These results point to a strong role of the JH as the regulatory factor of both reproductive phenomena in S. pandurus .

Starvationmedicine.medical_specialtyanimal structuresbiologyPhysiologyOvaryGeneral Medicinebiology.organism_classificationBiochemistrychemistry.chemical_compoundVitellogeninEndocrinologymedicine.anatomical_structureBiosynthesischemistrySpilostethus pandurusInternal medicineHemolymphmedicinebiology.proteinmedicine.symptomMolecular BiologyVitellogeninsComparative Biochemistry and Physiology Part B: Comparative Biochemistry
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Sample size planning for survival prediction with focus on high-dimensional data

2011

Sample size planning should reflect the primary objective of a trial. If the primary objective is prediction, the sample size determination should focus on prediction accuracy instead of power. We present formulas for the determination of training set sample size for survival prediction. Sample size is chosen to control the difference between optimal and expected prediction error. Prediction is carried out by Cox proportional hazards models. The general approach considers censoring as well as low-dimensional and high-dimensional explanatory variables. For dimension reduction in the high-dimensional setting, a variable selection step is inserted. If not all informative variables are included…

Statistics and ProbabilityClustering high-dimensional dataClinical Trials as TopicLung NeoplasmsModels StatisticalKaplan-Meier EstimateEpidemiologyProportional hazards modelDimensionality reductionGene ExpressionFeature selectionKaplan-Meier EstimateBiostatisticsPrognosisBrier scoreSample size determinationCarcinoma Non-Small-Cell LungSample SizeCensoring (clinical trials)StatisticsHumansProportional Hazards ModelsMathematicsStatistics in Medicine
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Sparse relative risk regression models

2020

Summary Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios…

Statistics and ProbabilityClustering high-dimensional dataComputer sciencedgLARSInferenceScale (descriptive set theory)BiostatisticsMachine learningcomputer.software_genreRisk Assessment01 natural sciencesRegularization (mathematics)Relative risk regression model010104 statistics & probability03 medical and health sciencesNeoplasmsCovariateHumansComputer Simulation0101 mathematicsOnline Only ArticlesSurvival analysis030304 developmental biology0303 health sciencesModels Statisticalbusiness.industryLeast-angle regressionRegression analysisGeneral MedicineSurvival AnalysisHigh-dimensional dataGene expression dataRegression AnalysisArtificial intelligenceStatistics Probability and UncertaintySettore SECS-S/01 - StatisticabusinessSparsitycomputerBiostatistics
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Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks

2015

Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epide…

Statistics and ProbabilityEpidemiologyComputer scienceBayesian probabilityBiostatisticsPoisson distributionBayesian inferenceDisease OutbreaksNormal distributionsymbols.namesakeHealth Information ManagementInfluenza HumanStatisticsEconometricsHumansPoisson DistributionPoisson regressionEpidemicsHidden Markov modelProbabilityInternetModels StatisticalIncidenceBayes TheoremMarkov ChainsSearch EngineMoment (mathematics)Autoregressive modelSpainsymbolsMonte Carlo MethodSentinel Surveillance
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