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1.
Sci Total Environ ; 698: 133999, 2020 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-31499345

RESUMO

When water and solutes enter the plant root through the epidermis, organic contaminants in solution either cross the root membranes and transport through the vascular pathways to the aerial tissues or accumulate in the plant roots. The accumulation of contaminants in plant roots and edible tissues is measured by root concentration factor (RCF) and fruit concentration factor (FCF). In this paper, 1) a neural network (NN) was applied to model RCF based on physicochemical properties of organic compounds, 2) correlation and significance of physicochemical properties were assessed using statistical analysis, 3) fuzzy logic was used to examine the simultaneous impacts of significant compound properties on RCF and FCF, 4) a clustering algorithm (k-means) was used to identify unique groups and discover hidden relationships within contaminants in various parts of the plants. The physicochemical cutoffs achieved by fuzzy logic for the RCF and the FCF were compared versus the cutoffs for compounds that crossed the plant root membranes and found their way into transpiration stream (measured by transpiration stream concentration factor, TSCF). The NN predicted the RCF with improved accuracy compared to mechanistic models. The analysis indicated that log Kow, molecular weight, and rotatable bonds are the most important properties for predicting the RCF. These significant compound properties are positively correlated with RCF while they are negatively correlated with TSCF. Comparing the relationships between compound properties in various plant tissues showed that compounds detected in the edible parts have physicochemical cutoffs that are more like the compounds crossing the plant root membranes (into xylem tissues) than the compounds accumulating in the plant roots, with clear relationships to food security. The cluster analysis placed the contaminants into three meaningful groups that were in agreement with the results of fuzzy logic.


Assuntos
Abastecimento de Alimentos , Aprendizado de Máquina , Plantas/metabolismo , Poluentes do Solo/metabolismo , Análise por Conglomerados , Lógica Fuzzy , Xilema
2.
J Agric Food Chem ; 67(46): 12927-12935, 2019 Nov 20.
Artigo em Inglês | MEDLINE | ID: mdl-31657558

RESUMO

Emerging and fugitive contaminants (EFCs) released to our biosphere have caused a legacy and continuing threat to human and ecological health, contaminating air, water, and soil. Polluted media are closely linked to food security through plants, especially agricultural crops. However, measuring EFCs in plant tissues remains difficult, and high-throughput screening is a greater challenge. A novel rapid freeze-thaw/centrifugation extraction followed by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis was developed for high-throughput quantification of 11 EFCs with diverse chemical properties, including estriol, codeine, oxazepam, 2,4-dinitrotoluene, 1,3,5-trinitroperhydro-1,3,5-triazine, bisphenol A, triclosan, caffeine, carbamazepine, lincomycin, and DEET, in three representative crops, corn, tomato, and wheat. The internal aqueous solution, i.e., sap, is liberated via a freeze/thaw cycle, and separated from macromolecules utilizing molecular weight cutoff membrane centrifugal filtration. Detection limits ranged from 0.01 µg L-1 to 2.0 µg L-1. Recoveries of spiked analytes in three species ranged from 83.7% to 109%. Developed methods can rapidly screen EFCs in agriculture crops and can assess pollutant distribution at contaminated sites and gain insight on EFCs transport in plants to assess transmembrane migration in vascular organisms. The findings contribute significantly to environmental research, food security, and human health, as it assesses the first step of potential entry into the food chain, that being transmembrane migration and plant uptake, the primary barrier between polluted waters or soils and our food.


Assuntos
Cromatografia Líquida de Alta Pressão/métodos , Poluentes Ambientais/química , Lycopersicon esculentum/química , Extratos Vegetais/química , Espectrometria de Massas em Tandem/métodos , Triticum/química , Zea mays/química , Centrifugação , Poluentes Ambientais/isolamento & purificação , Filtração , Contaminação de Alimentos/análise , Química Verde/métodos , Ensaios de Triagem em Larga Escala/métodos , Extratos Vegetais/isolamento & purificação
3.
Environ Pollut ; 246: 381-389, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30577006

RESUMO

Heavy metals and emerging engineered nanoparticles (ENPs) are two current environmental concerns that have attracted considerable attention. Cerium oxide nanoparticles (CeO2NPs) are now used in a plethora of industrial products, while cadmium (Cd) is a great environmental concern because of its toxicity to animals and humans. Up to now, the interactions between heavy metals, nanoparticles and plants have not been extensively studied. The main objectives of this study were (i) to determine the synergistic effects of Cd and CeO2NPs on the physiological parameters of Brassica and their accumulation in plant tissues and (ii) to explore the underlying physiological/phenotypical effects that drive these specific changes in plant accumulation using Artificial Neural Network (ANN) as an alternative methodology to modeling and simulating plant uptake of Ce and Cd. The combinations of three cadmium levels (0 [control] and 0.25 and 1 mg/kg of dry soil) and two CeO2NPs concentrations (0 [control] and 500 mg/kg of dry soil) were investigated. The results showed high interactions of co-existing CeO2NPs and Cd on plant uptake of these metal elements and their interactive effects on plant physiology. ANN also identified key physiological factors affecting plant uptake of co-occurring Cd and CeO2NPs. Specifically, the results showed that root fresh weight and the net photosynthesis rate are parameters governing Ce uptake in plant leaves and roots while root fresh weight and Fv/Fm ratio are parameters affecting Cd uptake in leaves and roots. Overall, ANN is a capable approach to model plant uptake of co-occurring CeO2NPs and Cd.


Assuntos
Brassica napus/fisiologia , Cádmio/metabolismo , Cério/metabolismo , Poluentes do Solo/metabolismo , Brassica napus/efeitos dos fármacos , Brassica napus/metabolismo , Cádmio/farmacologia , Cério/farmacologia , Humanos , Nanopartículas/metabolismo , Nanopartículas/toxicidade , Fotossíntese/fisiologia , Raízes de Plantas/efeitos dos fármacos , Raízes de Plantas/metabolismo , Raízes de Plantas/fisiologia , Solo/química , Poluentes do Solo/farmacologia
4.
Sci Total Environ ; 651(Pt 1): 561-569, 2019 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-30245412

RESUMO

Uptake of contaminants from the groundwater is one pathway of interest, and efforts have been made to relate root exposure to transloation throughout the plant, termed the transpiration stream concentration factor (TSCF). This work utilized machine learning techniques and statistcal analysis to improve the understanding of plant uptake and translocation of emerging contaminants. Neural network (NN) was used to develop a reliable model for predicting TSCF using physicochemical properties of compounds. Fuzzy logic was as a technique to examine the simultaneous impact of properties on TSCF, and interactions between compound properties. The significant and effective compound properties were determined using stepwise and forward regression as two widely used statiscal techniques. Clustering was used for detecting the hidden structures in the plant uptake data set. The NN predicted the TSCF with improved accuracy compared to mechanistic models. We also delivered new insight to compound properteis and their importance in transmembrane migration. The sensitivity analysis indicated that log Kow, molecular weight, hydrogen bond donor, and rotatable bonds are the most important properties. The results of fuzzy logic demonstrated that the relationship between molecular weight and log Kow with TSCF are both bell-shape and sigmoidal. The employed clustering algorithms all discovered two major distinct clusters in the data set.


Assuntos
Monitoramento Ambiental/métodos , Poluentes Ambientais/metabolismo , Plantas/metabolismo , Algoritmos , Transporte Biológico , Análise por Conglomerados , Lógica Fuzzy
5.
Bioresour Technol ; 258: 318-334, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29548641

RESUMO

The current research was an effort to critically review all approaches used for membrane fouling control in the membrane bioreactors treating water and wastewater. The first generation of antifouling methods tried to optimize operational conditions, or used chemical agents to control membrane fouling. Despite their positive impacts on the fouling mitigation, these methods did not provide a sustainable solution for the problem. Moreover, chemical agents may affect microorganisms in bioreactors and has some environmental drawbacks. The improved knowledge of membrane fouling mechanism and effective factors has directed the attention of researchers to novel methods that focus on disrupting fouling mechanism through affecting fouling causing bacteria. Employing nanomaterials, cell entrapment, biologically- and electrically-based methods are the latest efforts. The results of this review indicate that sustainable control of membrane fouling requires employing more than one single approach. Large scale application of fouling mitigation strategies should be the focus of future studies.


Assuntos
Reatores Biológicos , Eliminação de Resíduos Líquidos , Membranas Artificiais , Águas Residuárias , Água , Purificação da Água
6.
Arch Iran Med ; 20(11 Suppl. 1): S95-S98, 2017 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-29481139

RESUMO

INTRODUCTION: This research aims to determine the mental health status of population aged 15 and over in the province of Qom in 2015. METHODS: The statistical population of this cross-sectional field survey consisted of residents of urban and rural areas of Qom in Iran. An estimated sample size of 600 people was chosen using systematic random cluster sampling. The access was provided by the contribution of Geographical Post Office of Qom city. The General Health Questionnaire-28 (GHQ-28) was used as the screening tool for mental disorders. Data analysis in the current study was carried out using the SPSS-18 computer software. RESULTS: Using GHQ traditional scoring method, 16.2% of the subjects were shown to be at risk of mental disorders (19.7% of females and 12.6% of males). Urban areas (17%) were more at risk of mental disorders compared with rural residents (6.5%). Anxiety and somatization symptoms were more frequent than depression and social dysfunction among respondents. The obtained data revealed that the prevalence of mental disorders increased with age. Such disorders were more common in females, age group of 65 and above, people living in rural areas, divorced and widowed, illiterate, retired and unemployed individuals compared with the other groups. CONCLUSION: The results of this study showed that a sixth of the people in the province were suspected to have mental disorders. Therefore, it is mandatory for the provincial public health authorities to take the needed steps to ensure that necessary requirements encompassing prevention and promotion of mental health are implemented. .


Assuntos
Previsões , Nível de Saúde , Transtornos Mentais/epidemiologia , Saúde Mental , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Feminino , Inquéritos Epidemiológicos , Humanos , Irã (Geográfico)/epidemiologia , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , População Rural/estatística & dados numéricos , Amostragem , Distribuição por Sexo , População Urbana/estatística & dados numéricos , Adulto Jovem
7.
J Curr Ophthalmol ; 28(4): 206-211, 2016 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-27830205

RESUMO

PURPOSE: The aim of the present study was to investigate the effect of subthreshold diode laser micropulse (SDM) in comparison with conventional laser photocoagulation in the treatment of the diabetic macular edema (DME). METHODS: Sixty-eight eyes from 68 patients with clinically significant DME were divided randomly into two equal groups. In the first group, SDM photocoagulation was employed, while conventional laser photocoagulation was performed on the eyes of the second group. Central macular thickness (CMT), central macular volume (CMV), and best corrected visual acuity (BCVA) were measured before, 2, and 4 months after intervention, and the results were compared. RESULTS: The mean CMT was 357.3 and 354.8 microns before the treatment in Groups 1 and 2, respectively (P = 0.85), and decreased significantly to 344.3 and 349.8 after 4 months, respectively (P = 0.012 and P = 0.049). The changes in the central macular thickness was statistically higher in the first group (P = 0.001). The mean CMV significantly decreased in Group 1 (P = 0.003), but it was similar to pretreatment in Group 2 after 4 months (P = 0.31). The BCVA improved significantly in Group 1 (P < 0.001), but it remained unchanged in Group 2 (P = 0.38). CONCLUSIONS: In this study, SDM was more effective than conventional laser photocoagulation in reducing CMT and CMV and improving visual acuity in patients with DME.

8.
Artigo em Inglês | MEDLINE | ID: mdl-25883788

RESUMO

[This retracts the article DOI: 10.1186/s40201-014-0153-z.].

9.
Artigo em Inglês | MEDLINE | ID: mdl-25798288

RESUMO

Treatment process models are efficient tools to assure proper operation and better control of wastewater treatment systems. The current research was an effort to evaluate performance of a submerged membrane bioreactor (SMBR) treating combined municipal and industrial wastewater and to simulate effluent quality parameters of the SMBR using a radial basis function artificial neural network (RBFANN). The results showed that the treatment efficiencies increase and hydraulic retention time (HRT) decreases for combined wastewater compared with municipal and industrial wastewaters. The BOD, COD, [Formula: see text] and total phosphorous (TP) removal efficiencies for combined wastewater at HRT of 7 hours were 96.9%, 96%, 96.7% and 92%, respectively. As desirable criteria for treating wastewater, the TBOD/TP ratio increased, the BOD and COD concentrations decreased to 700 and 1000 mg/L, respectively and the BOD/COD ratio was about 0.5 for combined wastewater. The training procedures of the RBFANN models were successful for all predicted components. The train and test models showed an almost perfect match between the experimental and predicted values of effluent BOD, COD, [Formula: see text] and TP. The coefficient of determination (R(2)) values were higher than 0.98 and root mean squared error (RMSE) values did not exceed 7% for train and test models.

10.
J Environ Health Sci Eng ; 12(1): 153, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25649059

RESUMO

High flood occurrences with large environmental damages have a growing trend in Iran. Dynamic movements of water during a flood cause different environmental damages in geographical areas with different characteristics such as topographic conditions. In general, environmental effects and damages caused by a flood in an area can be investigated from different points of view. The current essay is aiming at detecting environmental effects of flood occurrences in Halilrood catchment area of Kerman province in Iran using flood zone mapping techniques. The intended flood zone map was introduced in four steps. Steps 1 to 3 pave the way to calculate and estimate flood zone map in the understudy area while step 4 determines the estimation of environmental effects of flood occurrence. Based on our studies, wide range of accuracy for estimating the environmental effects of flood occurrence was introduced by using of flood zone mapping techniques. Moreover, it was identified that the existence of Jiroft dam in the study area can decrease flood zone from 260 hectares to 225 hectares and also it can decrease 20% of flood peak intensity. As a result, 14% of flood zone in the study area can be saved environmentally.

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