Search results for "TOXICITY"

showing 10 items of 2261 documents

Quantitative structure-activity relationships for the toxicity of organophosphorus and carbamate pesticides to the Rainbow trout Onchorhyncus mykiss.

2006

This study has investigated the development of quantitative structure-activity relationships (QSARs) for the toxicity to rainbow trout Onchorhyncus mykiss Walbaum of 75 organophosphorus and carbamate pesticides. The toxicity data were obtained from an openly available toxicological database and were selected to be representative of a single endpoint. A large number of physicochemical and structural descriptors were calculated for the pesticides. QSAR models were developed using multiple linear regression and partial least-squares analyses. Following the removal of a small number of outliers, predictive QSARs were developed on small numbers of mechanistically relevant descriptors. Applying m…

Quantitative structure–activity relationshipCarbamatemedicine.medical_treatmentQuantitative Structure-Activity RelationshipRisk AssessmentToxicologyOrganophosphorus CompoundsmedicineAnimalsPesticidesToxicity dataChemistryQuantitative structureGeneral MedicinePesticideCarbamate pesticidesInsect ScienceEnvironmental chemistryOncorhynchus mykissToxicityMultivariate AnalysisLinear ModelsRainbow troutCarbamatesCholinesterase InhibitorsAgronomy and Crop SciencePest management science
researchProduct

Modelling bioconcentration of pesticides in fish using biopartitioning micellar chromatography.

2005

Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the bioconcentration factor (BCF) of pesticides in fish is proposed. A heterogeneous set of 85 pesticides from six chemical families was used. For pesticides exhibiting bioconcentration in fish (experimental log BCF > 2), a quantitative retention-activity relationships (QRAR) model is able to perform precise log BCF estimations of new pesticides. Considering the present data, the results based on log k seem to be more reliable than those from availabl…

Quantitative structure–activity relationshipChromatographyThreshold limit valueChemistryOrganic ChemistryFishesChromatography liquidQuantitative Structure-Activity RelationshipBioconcentrationGeneral MedicinePesticideBiochemistryHigh-performance liquid chromatographyAnalytical ChemistryEnvironmental chemistryFish <Actinopterygii>AnimalsEcotoxicityPesticidesChromatography LiquidJournal of chromatography. A
researchProduct

Chromatographic evaluation of the toxicity in fish of pesticides

2004

Abstract Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the toxicity in fish of pesticides (acute toxicity levels as pLC50) is proposed. A heterogeneous data set of 85 pesticides from six chemical families with available experimental fish toxicity data (ECOTOX database from U.S. Environmental Protection Agency (EPA)) was used. For pesticides exhibiting non-polar narcosis mechanism in fish (non-specific toxicity), more reliable models and precise pLC50 estimations are obtained from log k (quantitat…

Quantitative structure–activity relationshipChromatographyToxicity dataChemistryClinical BiochemistryFishesQuantitative Structure-Activity RelationshipCell BiologyGeneral MedicinePesticideBiochemistryAcute toxicityAnalytical ChemistryEnvironmental chemistryToxicityAnimalsFish <Actinopterygii>Spectrophotometry UltravioletPesticidesEcotoxicityChromatography LiquidJournal of Chromatography B
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 &lt;i&gt;Tetrahymena pyriformis&lt;/i&gt;

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

Prediction of potential environmental toxicity of chemicals in &lt;em&gt;Lactuca sativa&lt;/em&gt; seed germination using computational tools

2019

The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of phytotoxicity effects of chemical compounds on the Lactuca sativa seeds germination. A database of 73 compounds, assayed against L. sativa and Dragon’s molecular descriptors are used to obtain a QSAR model for the prediction of the phytotoxicity. The model is carried out with QSARINS software and validated according to OECD principles. The best model showed good value for the determination coefficient (R2 = 0.917) and others parameters appropriate for fitting (s = 0.256 and RMSEtr= 0.236). The validation results confirmed that the model has good robustness and stability …

Quantitative structure–activity relationshipbiologyGerminationMolecular descriptorEnvironmental toxicologyPhytotoxicityLactucaBiological systembiology.organism_classificationMathematicsProceedings of MOL2NET 2019, International Conference on Multidisciplinary Sciences, 5th edition
researchProduct

Assessment in vitro of radioprotective efficacy of curcumin and resveratrol

2011

Abstract Many natural substances have been studied in recent past to be used as radioprotectors to mitigate ionizing radiation-induced damage in mammalian systems due to its effectiveness given both pre- and post-irradiation and for long time with out drug-related toxicity. Curcumin and trans -resveratrol are both natural occurring polyphenols, obtained from the root of Curcuma longa and from grapes and other berries, respectively. These compounds have shown antioxidant, anti-inflammatory, immunostimulant and anti-carcinogenic properties. Our aim was to evaluate the radioprotective efficacy, in vitro , of curcumin and trans -resveratrol separately against radiation-induced chromosomal aberr…

RadiationAntioxidantbiologyChemistrymedicine.drug_classmedicine.medical_treatmentResveratrolbiology.organism_classificationImmunostimulantIn vitrochemistry.chemical_compoundBiochemistryPolyphenolToxicitymedicineCurcuminCurcumaInstrumentationRadiation Measurements
researchProduct

The radiosensitization effect of titanate nanotubes as a new tool in radiation therapy for glioblastoma: A proof-of-concept

2013

Abstract Background and purpose One of the new challenges to improve radiotherapy is to increase the ionizing effect by using nanoparticles. The interest of titanate nanotubes (TiONts) associated with radiotherapy was evaluated in two human glioblastoma cell lines (SNB-19 and U87MG). Materials and methods Titanate nanotubes were synthetized by the hydrothermal treatment of titanium dioxide powder in a strongly basic NaOH solution. The cytotoxicity of TiONts was evaluated on SNB-19 and U87MG cell lines by cell proliferation assay. The internalization of TiONts was studied using Transmission Electron Microscopy (TEM). Finally, the effect of TiONts on cell radiosensitivity was evaluated using …

Radiation-Sensitizing AgentsCell SurvivalDNA repairCellApoptosisFlow cytometryCell Line TumormedicineHumansRadiology Nuclear Medicine and imagingRadiosensitivityClonogenic assayCytotoxicityTitaniumNanotubesmedicine.diagnostic_testBrain NeoplasmsChemistryCell growthCell CycleHematologyCell cyclemedicine.anatomical_structureOncologyBiophysicsGlioblastomaReactive Oxygen SpeciesDNA DamageRadiotherapy and Oncology
researchProduct

AGuIX® from bench to bedside-Transfer of an ultrasmall theranostic gadolinium-based nanoparticle to clinical medicine.

2019

International audience; AGuIX® are sub-5 nm nanoparticles made of a polysiloxane matrix and gadolinium chelates. This nanoparticle has been recently accepted in clinical trials in association with radiotherapy. This review will summarize the principal preclinical results that have led to first in man administration. No evidence of toxicity has been observed during regulatory toxicity tests on two animal species (rodents and monkeys). Biodistributions on different animal models have shown passive uptake in tumours due to enhanced permeability and retention effect combined with renal elimination of the nanoparticles after intravenous administration. High radiosensitizing effect has been obser…

Radiation-Sensitizing AgentsGadoliniummedicine.medical_treatmentGadolinium02 engineering and technologyReview ArticlePharmacologyTheranostic NanomedicineMice0302 clinical medicineMelanomaBrain NeoplasmsMelanomaGeneral Medicine[CHIM.MATE]Chemical Sciences/Material chemistry[SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences021001 nanoscience & nanotechnology3. Good health[SDV.SP] Life Sciences [q-bio]/Pharmaceutical sciencesNuclear Medicine & Medical ImagingRadiology Nuclear Medicine and imagingHead and Neck Neoplasms030220 oncology & carcinogenesisToxicity/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being[SDV.IB]Life Sciences [q-bio]/Bioengineering0210 nano-technologyClinical Scienceschemistry.chemical_element[SDV.CAN]Life Sciences [q-bio]/CancerEnhanced permeability and retention effect03 medical and health sciences/dk/atira/pure/subjectarea/asjc/2700/2741SDG 3 - Good Health and Well-being[SDV.CAN] Life Sciences [q-bio]/CancerIn vivo[CHIM.ANAL]Chemical Sciences/Analytical chemistrymedicineAnimalsHumansRadiology Nuclear Medicine and imaging[SDV.IB] Life Sciences [q-bio]/Bioengineeringbusiness.industryCancermedicine.diseaseRadiation therapyClinical trialchemistryNanoparticlesbusinessForecasting
researchProduct