Status of Total Antioxidant Capacity and Malondialdehyde Level in Methamphetamine Addicts: A Cross Sectional Study

Background: Methamphetamine (MA) is an illegal amphetamine-like which stimulate the central nervous system. In recent years, MA has been widely abused worldwide. Previous studies have suggested that oxidative stress (OS) plays an important role in MA-induced toxicity. From this view, antioxidant therapy could be considered as a potential drug therapy in MA abusers. Therefore, the objective of this study was to evaluate OS status in MA abusers.Methods: This was a cross-sectional study conducted on 21 MA abusers who referred to Iranian National Center for Addiction Studies and Congress 60 Humane Revivification Society, and 15 healthy males as a control group. The demographic data and peripheral blood sampling was obtained from both groups. The serum malondialdehyde (MDA) level as a marker of plasma lipid peroxidation and total antioxidant capacity (TAC) of plasma were analyzed.Results: Significant decrease in plasma TAC in case group was observed (101.85±12.5 vs. 130.7±16.12 mmol/L). No significant increase in MDA serum level was detected in case group in comparison with control (27.35±2.6 vs. 26.67±2.22 µmol/L, respectively). Neither the serum MDA levels nor the plasma TAC were significantly correlated with the duration and amount of MA abuse.Conclusion: It seems that, MA abuse is associated with prooxidant-antioxidant imbalance, which suggests evaluation the role of antioxidants administration for the prevention and treatment of MA-induced toxicity

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels

BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. METHODS: We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. RESULTS: The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. CONCLUSION: The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

Ergonomics factors influencing school education during the COVID-19 pandemic: A literature review

BACKGROUND: The school is one of the most critical social, educational, and training institutions and the main pillar of education in society. Education and, consequently, educational environments have the highest effect on the mentality, development, growth, welfare, concentration, performance, and learning efficiency of students. OBJECTIVES: The present study aimed to examine the effects of environmental ergonomics on the learning and cognition of pre-school students during the COVID-19 pandemic. METHODS: The study was carried out as a review article using some keywords, namely 'children', 'learning', 'pre-school', 'COVID-19', 'ergonomics', and 'environmental factors'. Scopus, PubMed, Science Direct and Web of Science were searched to find related articles. RESULTS: Factors like color, form, and layout of classrooms, lighting and ventilation, interior decoration, and educational equipment are effective in creating interest and motivation for students to learn. CONCLUSIONS: A review of these articles showed that the presence of ergonomics in educational spaces for children increases the quality of learning and reduces stress and anxiety, and by observing health protocols, a healthy and safe environment can be provided for students. © 2021 - IOS Press. All rights reserved

Optical-fiber thermal-wave-cavity technique to study thermal properties of silver/clay nanofluids

Thermal properties enhancement of nanofluids have varied strongly with synthesis technique, particle size and type, concentration and agglomeration with time. This study explores the possibility of changing the thermal wave signal of Ag/clay nanofluids into a thermal diffusivity measurement at well dispersion or aggregation of nanoparticles in the base fluid. Optical-Fiber Thermal-Wave-Cavity (OF-TWC) technique was achieved by using a small amount of nanofluid (only 0.2 mL) between fiber optic tip and the Pyroelectric detector and the cavity-length scan was performed. We established the accuracy and precision of this technique by comparing the thermal diffusivity of distilled water to values reported in the literature. Assuming a linear Pyroelectric signal response, the results show that adding clay reduced the thermal diffusivity of water, while increasing the Ag concentration from 1 to 5 wt.% increased the thermal diffusivity of the Ag nanofluid from 1.524×10−3 to 1.789×10−3 cm2/s. However, in particular, nanoparticles show the tendency to form aggregates over time that correlated with the performance change of thermal properties of nanofluid. Our results confirm the high sensitivity of OF-TWC technique raises the potential to be applied to measuring the optical and thermal properties of nanofluids. Furthermore, this technique allows the extraction of information not obtained using other traditional techniques

Metals – impact and implications

Impact of metal in vitro administration on rat tissue oxygen consumption is referred in the first part. Toxicological implications of in vivo metal administration to rats and the study of potential penetration of metal into the rat brain, which may eventually result in oxygen radical production are presented in second part

Genetic Variation in Base Excision Repair Pathway Genes, Pesticide Exposure, and Prostate Cancer Risk

Background: Previous research indicates increased prostate cancer risk for pesticide applicators and pesticide manufacturing workers. Although underlying mechanisms are unknown, evidence suggests a role of oxidative DNA damage

Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI

PURPOSE: We propose a fully automated method for detection and segmentation of the abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid- Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI). METHODS: The method is based on superpixel technique and classification of each superpixel. A number of novel image features including intensity-based, Gabor textons, fractal analysis and curvatures are calculated from each superpixel within the entire brain area in FLAIR MRI to ensure a robust classification. Extremely randomized trees (ERT) classifier is compared with support vector machine (SVM) to classify each superpixel into tumour and non-tumour. RESULTS: The proposed method is evaluated on two datasets: (1) Our own clinical dataset: 19 MRI FLAIR images of patients with gliomas of grade II to IV, and (2) BRATS 2012 dataset: 30 FLAIR images with 10 low-grade and 20 high-grade gliomas. The experimental results demonstrate the high detection and segmentation performance of the proposed method using ERT classifier. For our own cohort, the average detection sensitivity, balanced error rate and the Dice overlap measure for the segmented tumour against the ground truth are 89.48 %, 6 % and 0.91, respectively, while, for the BRATS dataset, the corresponding evaluation results are 88.09 %, 6 % and 0.88, respectively. CONCLUSIONS: This provides a close match to expert delineation across all grades of glioma, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

X‐ray CT reveals 4D root system development and lateral root responses to nitrate in soil

Abstract The spatial arrangement of the root system, termed root system architecture, is important for resource acquisition as it directly affects the soil zone explored. Methods for phenotyping roots are mostly destructive, which prevents analysis of roots over time as they grow. Here, we used X‐ray microcomputed tomography (μCT) to non‐invasively characterize wheat (Triticum aestivum L.) seedling root development across time under high and low nitrate nutrition. Roots were imaged multiple times with the 3D models co‐aligned and timestamped in the architectural plant model OpenSimRoot for subsequent root growth and nitrate uptake simulations. Through 4D imaging, we found that lateral root traits were highly responsive to nitrate limitation in soil with greater lateral root length under low N. The root growth model using all μCT root scans was comparable to a parameterized model using only the final root scan in the series. In a second μCT experiment, root growth and nitrate uptake simulations of candidate wheat genotypes found significant root growth and uptake differences between lines. A high nitrate uptake wheat line selected from field data had a greater lateral root count and length at seedling growth stage compared with a low uptake line