Search results for "Tetrahymena pyriformis"

showing 10 items of 11 documents

Roles for RpoS in survival of Escherichia coli during protozoan predation and in reduced moisture conditions highlight its importance in soil environ…

2017

The soil is a complex ecosystem where interactions between biotic and abiotic factors determine the survival and fate of microbial inhabitants of the system. Having previously shown that Escherichia coli requires the general stress response regulator, RpoS, to survive long term in soil, it was important to determine what specific conditions in this environment necessitate a functional RpoS. This study investigated the susceptibility of soil-persistent E. coli to predation by the single-celled eukaryotes Acanthamoeba polyphaga and Tetrahymena pyriformis, and the role RpoS plays in resisting this predation. Strain-specific differences were observed in the predation of E. coli strains, with so…

0301 basic medicine030106 microbiologyAcanthamoebaSigma Factormedicine.disease_causeEscherichia coli O157MicrobiologyPredationMicrobiology03 medical and health sciencesSoilBacterial ProteinsGeneticsmedicineEcosystemMolecular BiologyEscherichia coliSoil MicrobiologyAbiotic componentbiologyEcologyTetrahymena pyriformisFeeding BehaviorGene Expression Regulation Bacterialbiology.organism_classificationTetrahymena pyriformisbacteriaProtozoaAdaptationrpoSFEMS microbiology letters
researchProduct

Comparative study to predict toxic modes of action of phenols from molecular structures.

2013

Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…

Antiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringMachine learningcomputer.software_genreConstant false alarm ratePhenolsArtificial IntelligenceDrug DiscoveryTraining setModels StatisticalArtificial neural networkCiliated protozoanMolecular StructureChemistrybusiness.industryTetrahymena pyriformisGeneral MedicineLinear discriminant analysisSupport vector machineTest setTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerBiological systembusinesscomputerSAR and QSAR in environmental research
researchProduct

IDENTIFICATION OF LECTINS IN THE KINETIDS OFTETRAHYMENA PYRIFORMIS

1997

Previously we described lectin-like molecules in the ciliate Tetrahymena pyriformis; by application of synthetic neoglycoconjugates it is now shown that T. pyriformis contains considerable amounts of both a beta-D-glucose- and a lactose-specific lectin. No evidence for the presence of alpha-D-mannose-, alpha-D-galactose- or of alpha-L-fucose-specific lectins could be obtained. The two lectins, identified in T. pyriformis, are associated with the kinetids. During cell division the lectins disappear or become masked in the fission furrow. Therefore, we assume that these lectins are involved in the organization of the distribution pattern of the kinetids during cell division perhaps due to lec…

CiliateCell divisionbiologyTetrahymena pyriformisLectinCell BiologyGeneral Medicinebiology.organism_classificationCell biologyMicroscopy FluorescenceAlbuminsLectinsDistribution patternTetrahymena pyriformisbiology.proteinAnimalsIdentification (biology)GlycoconjugatesCell DivisionFluorescein-5-isothiocyanateCell Biology International
researchProduct

Induction of digoxin-like material production, and the digoxin binding in the unicellular organism Tetrahymena by digitoxin.

1998

Thin layer chromatographic, and laser-confocal microscopic analyses with a monoclonal antibody to digoxin also displaying high affinity to digoxigenin, were used to determine the presence and localization of cardioactive glycosides. Tetrahymena pyriformis was found to possess digitoxigenin-like material, but digoxin, digitoxin, digoxigenin, gitoxin and lanatoside C were not detected. Digitoxin treatment elicited the appearance of a digoxin-like material in the progeny generations. Digoxin was taken up by untreated Tetrahymena, especially strongly 24 h after digitoxin treatment. While the cardenolide was localized in vesicles of the cell body in untreated Tetrahymena, the engulfed digoxin ap…

DigoxinDigoxinDigitoxinBiologychemistry.chemical_compoundDigitoxinpolycyclic compoundsmedicineCardenolideDigoxigeninAnimalscardiovascular diseasesChromatography High Pressure Liquidchemistry.chemical_classificationBinding SitesMicroscopy ConfocalTetrahymena pyriformisdigestive oral and skin physiologyCell MembraneLanatoside CTetrahymenaDigitalis GlycosidesBiological TransportCell BiologyGeneral Medicinebiology.organism_classificationImmunohistochemistrycarbohydrates (lipids)EnzymechemistryBiochemistryTetrahymena pyriformiscirculatory and respiratory physiologymedicine.drugCell biology international
researchProduct

Prediction of Aquatic Toxicity of Benzene Derivatives to Tetrahymena pyriformis According to OECD Principles

2016

Background: Many QSAR studies have been developed to predict acute toxicity over several biomarkers like Pimephales promelas, Daphnia magna and Tetrahymena pyriformis. Regardless of the progress made in this field there are still some gaps to be resolved such as the prediction of aquatic toxicity over the protozoan T. pyriformis still lack a QSAR study focused in accomplish the OECD principles. Methods: Atom-based quadratic indices are used to obtain quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. Our models agree with the principles required by the OECD for QSAR models to regulatory purposes. The database employed consists of 392 substitut…

PharmacologyQuantitative structure–activity relationshipTetrahymena pyriformisAntiprotozoal AgentsQuantitative Structure-Activity Relationship010501 environmental sciencesBiology01 natural sciencesAcute toxicity0104 chemical sciencesAquatic toxicologyToxicology010404 medicinal & biomolecular chemistryParasitic Sensitivity TestsTest setDrug DiscoveryBenzene derivativesLinear regressionTetrahymena pyriformisBenzene DerivativesBiological systemMonte Carlo MethodAlgorithmsBootstrapping (statistics)0105 earth and related environmental sciencesCurrent Pharmaceutical Design
researchProduct

Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

2017

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector…

Quantitative structure–activity relationshipAntiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringModes of toxic action010501 environmental sciencesMachine learningcomputer.software_genre01 natural sciencesMachine Learningchemistry.chemical_compoundPhenolsMolecular descriptorDrug DiscoveryPhenols0105 earth and related environmental sciencesCiliated protozoanArtificial neural networkbusiness.industryTetrahymena pyriformisGeneral Medicine0104 chemical sciencesSupport vector machine010404 medicinal & biomolecular chemistrychemistryTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerbusinesscomputerSAR and QSAR in environmental research
researchProduct

Prediction of acute toxicity of phenol derivatives using multiple linear regression approach for Tetrahymena pyriformis contaminant identification in…

2016

In this article, the modeling of inhibitory grown activity against Tetrahymena pyriformis is described. The 0-2D Dragon descriptors based on structural aspects to gain some knowledge of factors influencing aquatic toxicity are mainly used. Besides, it is done by some enlarged data of phenol derivatives described for the first time and composed of 358 chemicals. It overcomes the previous datasets with about one hundred compounds. Moreover, the results of the model evaluation by the parameters in the training, prediction and validation give adequate results comparable with those of the previous works. The more influential descriptors included in the model are: X3A, MWC02, MWC10 and piPC03 wit…

Quantitative structure–activity relationshipEnvironmental EngineeringDatabases FactualHealth Toxicology and Mutagenesis0211 other engineering and technologiesQuantitative Structure-Activity Relationship02 engineering and technology010501 environmental sciencesBiologycomputer.software_genre01 natural sciencesAquatic toxicologyPhenolsLinear regressionEnvironmental Chemistry0105 earth and related environmental sciences021110 strategic defence & security studiesDatabaseTetrahymena pyriformisPublic Health Environmental and Occupational HealthLinear modelGeneral MedicineGeneral ChemistryModels TheoreticalchEMBLPollutionAcute toxicityTetrahymena pyriformisLinear ModelscomputerChemical databaseChemosphere
researchProduct

A novel approach to predict aquatic toxicity from molecular structure

2008

The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity using atom-based non-stochastic and stochastic linear indices. The used dataset consist of 392 benzene derivatives, separated into training and test sets, for which toxicity data to the ciliate Tetrahymena pyriformis were available. Using multiple linear regression, two statistically significant QSAR models were obtained with non-stochastic (R2=0.791 and s=0.344) and stochastic (R2=0.799 and s=0.343) linear indices. A leave-one-out (LOO) cross-validation procedure was carried out achieving values of q2=0.781 (scv=0.348) and q2=0.786 (scv=0.350), respecti…

Quantitative structure–activity relationshipEnvironmental EngineeringToxicity dataMolecular StructureLooHealth Toxicology and MutagenesisPublic Health Environmental and Occupational HealthGeneral MedicineGeneral ChemistryPollutionAquatic toxicologyToxicologyStructure-Activity RelationshipToxicity TestsBenzene derivativesTetrahymena pyriformisLinear regressionEnvironmental ChemistryBiological systemMathematicsChemosphere
researchProduct

Atom-Based Quadratic Indices to Predict Aquatic Toxicity of Benzene Derivatives to <i>Tetrahymena pyriformis</i>

2009

The non-stochastic and stochastic atom-based quadratic indices are applied to develop quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. The used dataset, consisting of 392 benzene derivatives for which toxicity data to the ciliate Tetrahymena pyriformis were available, is divided into training and test sets. The obtained multiple linear regression models are statistically significant (R2 = 0.787 and s = 0.347, R2 = 0.806 and s = 0.329, for non-stochastic and stochastic quadratic indices, respectively) and show rather good stability in a cross-validation experiment (q2 = 0.769 and scv = 0.357, q2 = 0.791 and scv = 0.337, correspondingly). In a…

Quantitative structure–activity relationshipQuadratic equationTest setToxicityLinear regressionTetrahymena pyriformisBiological systemStability (probability)MathematicsAquatic toxicologyProceedings of The 13th International Electronic Conference on Synthetic Organic Chemistry
researchProduct

Physiological, morphological and metabolic changes in Tetrahymena pyriformis for the in vivo cytotoxicity assessment of metallic pollution: Impact on…

2007

Abstract The individual cytotoxicity of cadmium chloride, iron sulphate and chromium nitrate has been investigated by using the freshwater ciliate Tetrahymena pyriformis. The metabolic enzymes and antioxidant defense biomarkers were assessed. The results obtained reveal that their metal salts have perturbed the physiology and morphology of T. pyriformis. Also, the biomarkers assessed were sensitive to the presence of metal salts and this sensitivity was metal salt and dose dependant. To estimate the impact of their metal salts on mitochondria, we studied their effects in vivo and in vitro on the d -β-hydroxybutyrate dehydrogenase (BDH) (EC 1.1.1.30) inner mitochondrial membrane enzyme. The …

chemistry.chemical_classificationEcologyGeneral Decision SciencesDehydrogenaseMitochondrionCadmium chlorideBiologychemistry.chemical_compoundEnzymechemistryBiochemistryIn vivoTetrahymena pyriformisInner mitochondrial membraneCytotoxicityEcology Evolution Behavior and SystematicsEcological Indicators
researchProduct