Mine Wastewater Treatment with Upflow Anaerobic Fixed Film Reactors

Mine Water and the Environment - Microbial bioremediation of metals in wastewater by sulfate-reducing bacteria (SRB) has received much attention due to its high efficiency, eco-friendly techniques,...     

Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

This study is designed to develop Artificial Intelligence (AI) based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays (CXRs). The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of CXRs. In this study, AI-based analysis tools were developed that can precisely classify COVID-19 lung infection. Publicly available datasets of COVID-19 (N = 1525), non-COVID-19 normal (N = 1525), viral pneumonia (N = 1342) and bacterial pneumonia (N = 2521) from the Italian Society of Medical and Interventional Radiology (SIRM), Radiopaedia, The Cancer Imaging Archive (TCIA) and Kaggle repositories were taken. A multi-approach utilizing deep learning ResNet101 with and without hyperparameters optimization was employed. Additionally, the features extracted from the average pooling layer of ResNet101 were used as input to machine learning (ML) algorithms, which twice trained the learning algorithms. The ResNet101 with optimized parameters yielded improved performance to default parameters. The extracted features from ResNet101 are fed to the k-nearest neighbor (KNN) and support vector machine (SVM) yielded the highest 3-class classification performance of 99.86% and 99.46%, respectively. The results indicate that the proposed approach can be better utilized for improving the accuracy and diagnostic efficiency of CXRs. The proposed deep learning model has the potential to improve further the efficiency of the healthcare systems for proper diagnosis and prognosis of COVID-19 lung infection.     

Toxicological effects of the chemical and green ZnO NPs on Cyprinus carpio L. observed under light and scanning electron microscopy

Nanoparticles in aquatic bodies cause serious harm to the aquatic organisms when accumulated in high amounts. However, green nanoparticles synthesized using plants can be less toxic as compared to chemical nanoparticles. Hence, we designed our study to investigate the toxicological effects of chemical and green zinc oxide nanoparticles (ZnO NPs) on the biological activity of juvenile Cyprinus carpio. The green ZnO NPs were synthesized from Solieria robusta, and chemical ZnO NPs were synthesized using zinc chloride solution and ammonium hydroxide. Characterization was done by using light microscopy, scanning electron microscope (SEM), Fourier transmission infrared radiation, and X-ray diffraction (XRD) techniques. The highest absorbance of nanoparticles was observed at 360 which confirmed the synthesis of ZnO. The SEM analysis showed that green nanoparticles were hexagonal while the chemical nanoparticles were spherical to cubic in shape. Definite peaks were observed in XRD of green and chemical NPs at 2θ angles 45.84° and 32.18°, respectively. Oxidative stress was determined by chemical analysis of catalase, glutathione S-transferase (GST), glutathione (GSH), and lipid peroxidation (LPO) activities. The toxicological effects of chemical ZnO NPs on the catalase, LPO, GST, and GSH activities were more than green ZnO NPs. The histopathological investigation proved that the effect of chemical nanoparticles was worse than green ZnO NPs. More tissue damage was found in chemical nanoparticles than green synthesized nanoparticles. It was concluded that chemical nanoparticles can be replaced by green nanoparticles, as green nanoparticles are eco-friendly with less toxicological effects. This replacement can limit the toxic effect of nanoparticles when they get accumulated in high amounts in water bodies.     

Touch location and force sensing interactive system for upper limb motor rehabilitation

Multimedia Tools and Applications - The development of an interactive low-cost system for executing tailored upper limb rehabilitation exercises based on game-based Virtual Environments (VEs) is...     

Pancreatic Cancer and Therapy: Role and Regulation of Cancer Stem Cells

Despite significant improvements in clinical management, pancreatic cancer (PC) remains one of the deadliest cancer types, as it is prone to late detection with extreme metastatic properties. The recent findings that pancreatic cancer stem cells (PaCSCs) contribute to the tumorigenesis, progression, and chemoresistance have offered significant insight into the cancer malignancy and development of precise therapies. However, the heterogeneity of cancer and signaling pathways that regulate PC have posed limitations in the effective targeting of the PaCSCs. In this regard, the role for K-RAS, TP53, Transforming Growth Factor-β, hedgehog, Wnt and Notch and other signaling pathways in PC progression is well documented. In this review, we discuss the role of PaCSCs, the underlying molecular and signaling pathways that help promote pancreatic cancer development and metastasis with a specific focus on the regulation of PaCSCs. We also discuss the therapeutic approaches that target different PaCSCs, intricate mechanisms, and therapeutic opportunities to eliminate heterogeneous PaCSCs populations in pancreatic cancer.     

Multicomponent Syntheses based upon Copper‐Catalyzed Alkyne‐Azide Cycloaddition

The copper‐catalyzed alkyne‐azide cycloaddition (CuAAC) is a highly versatile, regioselective synthesis of 1,4‐disubstituted 1,2,3‐triazoles under mild reaction conditions and has found numerous applications in medicinal, bioorganic, and materials chemistry in the past one and a half decades. By virtue of the enormous tolerance for functional groups and the mild reaction conditions, CuAAC has become increasingly important in combination with multicomponent reactions (MCR), either in a domino or in a consecutive fashion. While the majority of CuAAC‐based MCR are founded on the in situ or en route generation of azides, one‐pot generation of alkynes and the concatenation with other MCR are rapidly catching up and novel sequences for efficient one‐pot syntheses of triazole‐based structures in a multicomponent fashion are constantly evolving. This review summarizes important contributions of CuAAC‐based MCR including MCR‐type applications in polymer science.