Real-time tracking of hydrogen peroxide secreted by live cells using MnO2 nanoparticles intercalated layered doubled hydroxide nanohybrids

We report a facile and green method for the fabrication of new type of electrocatalysts based on MnO₂ nanoparticles incorporated on MgAl LDH P-type semiconductive channel and explore its practical applications as high-performance electrode materials for electrochemical biosensor. A series of MgAl layered doubled hydroxide (LDH) nanohybrids with fixed Mg/Al (M²⁺/M³⁺ atomic ratio of 3) and varied amount of MnCl₂.4H₂O are fabricated by a facile co-precipitation method. This approach demonstrates the combination of distinct properties including excellent intercalation features of LDH for entrapping nanoparticles and high loading of MnO₂ nanoparticles in the host layers of LDH. Among all samples, Mn5–MgAl with 0.04% loaded manganese has a good crystalline morphology. A well-dispersed MnO₂ nanoparticles encapsulated into the host matrix of hydrotalcite exhibit enhanced electrocatalytic activity towards the reduction of H₂O₂ as well as excellent stability, selectivity and reproducibility due to synergistic effect of good catalytic ability of MnO₂ and conductive MgAl LDH. Glass carbon electrode (GCE) modified with Mn5–MgAl possesses a wide linear range of 0.05–78 mM, lowest detection limit 5 μM (S/N = 3) and detection sensitivity of 0.9352 μAmM⁻¹. This outstanding performance enables it to be used for real-time tracking of H₂O₂ secreted by live HeLa cells. This work may provide new insight in clinical diagnosis, on-site environmental analysis and point of care testing devices.     

On molecular topological properties of hex‐derived networks

Topological indices are numerical parameters of a molecular graph, which characterize its topology and are usually graph invariant. In quantitative structure–activity relationship/quantitative structure–property relationship study, physico‐chemical properties and topological indices such as Randić, atom–bond connectivity (ABC), and geometric–arithmetic (GA) index are used to predict the bioactivity of chemical compounds. Graph theory has found a considerable use in this area of research. In this paper, we study hex‐derived networks HDN1(n) and HDN2(n), which are generated by hexagonal network of dimension n and derive analytical closed results of general Randić index R_α(G) for different values of α, for these networks of dimension n. We also compute the general first Zagreb, ABC, GA, ABC₄, and GA₅ indices for these hex‐derived networks for the first time and give closed formulae of these degree‐based indices for hex‐derived networks. Copyright © 2016 John Wiley & Sons, Ltd.     

Efficiency analysis of thermosyphon solar flat plate collector with low mass concentrations of ND–Co3O4 hybrid nanofluids: an experimental study

Journal of Thermal Analysis and Calorimetry - In the present study, the thermal efficiency, convective heat transfer and friction factor analysis are investigated for a flat plate solar collector...     

Metal-free and azide-free synthesis of 1,2,3-triazoles derivatives

1,2,3-Triazoles, significant five-membered ring N-heterocycles, are main structural moieties in well-designed materials, pharmaceutical agents, bioactive products, and synthetic intermediates. In the research of life sciences and pharmaceuticals, by seeing the spacious applications of 1,2,3-triazoles, the progress of metal-free method is exceedingly desirable to evade the heterocyclic product metal contamination. Moreover, on a larger scale, the toxicity and explosiveness of azides makes azides discommode and hard to hold, to synthesize 1,2,3-triazoles. The need to steer the development of the synthesis of 1,2,3-triazoles toward more maintainable synthesis is a pressing issue. There are rare methods to construct 1,2,3-triazoles under azide-free and metal-free environments. These rare methods are compiled in this review. The afford of the collection and compilation of azide-free and metal-free synthesis methodologies of 1,2,3-triazole in single podium is supportive and crucial for synthetic chemist to extend the diversity of the synthesis of 1,2,3-trizoles through green protocol.     

On Some Topological Indices Defined via the Modified Sombor Matrix

Let G be a simple graph with the vertex set V={v1,…,vn} and denote by dvi the degree of the vertex vi. The modified Sombor index of G is the addition of the numbers (dvi2+dvj2)−1/2 over all of the edges vivj of G. The modified Sombor matrix AMS(G) of G is the n by n matrix such that its (i,j)-entry is equal to (dvi2+dvj2)−1/2 when vi and vj are adjacent and 0 otherwise. The modified Sombor spectral radius of G is the largest number among all of the eigenvalues of AMS(G). The sum of the absolute eigenvalues of AMS(G) is known as the modified Sombor energy of G. Two graphs with the same modified Sombor energy are referred to as modified Sombor equienergetic graphs. In this article, several bounds for the modified Sombor index, the modified Sombor spectral radius, and the modified Sombor energy are found, and the corresponding extremal graphs are characterized. By using computer programs (Mathematica and AutographiX), it is found that there exists only one pair of the modified Sombor equienergetic chemical graphs of an order of at most seven. It is proven that the modified Sombor energy of every regular, complete multipartite graph is 2; this result gives a large class of the modified Sombor equienergetic graphs. The (linear, logarithmic, and quadratic) regression analyses of the modified Sombor index and the modified Sombor energy together with their classical versions are also performed for the boiling points of the chemical graphs of an order of at most seven.     

DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

Alzheimer’s Disease (AD) is a neurological brain disorder that causes dementia and neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a kind of Artificial Intelligence (AI), has paved the way for new AD detection and automation methods. The DL model’s prediction accuracy depends on the dataset’s size. The DL models lose their accuracy when the dataset has an imbalanced class problem. This study aims to use the deep Convolutional Neural Network (CNN) to develop a reliable and efficient method for identifying Alzheimer’s disease using MRI. In this study, we offer a new CNN architecture for diagnosing Alzheimer’s disease with a modest number of parameters, making it perfect for training a smaller dataset. This proposed model correctly separates the early stages of Alzheimer’s disease and displays class activation patterns on the brain as a heat map. The proposed Detection of Alzheimer’s Disease Network (DAD-Net) is developed from scratch to correctly classify the phases of Alzheimer’s disease while reducing parameters and computation costs. The Kaggle MRI image dataset has a severe problem with class imbalance. Therefore, we used a synthetic oversampling technique to distribute the image throughout the classes and avoid the problem. Precision, recall, F1-score, Area Under the Curve (AUC), and loss are all used to compare the proposed DAD-Net against DEMENET and CNN Model. For accuracy, AUC, F1-score, precision, and recall, the DAD-Net achieved the following values for evaluation metrics: 99.22%, 99.91%, 99.19%, 99.30%, and 99.14%, respectively. The presented DAD-Net outperforms other state-of-the-art models in all evaluation metrics, according to the simulation results.     

Psidium guajava L. An Incalculable but Underexplored Food Crop: Its Phytochemistry,Ethnopharmacology, and Industrial Applications

Psidium guajava L. (guava) is a small tree known for its fruit flavor that is cultivated almost around the globe in tropical areas. Its fruit is amazingly rich in antioxidants, vitamin C, potassium, and dietary fiber. In different parts of the world, this plant holds a special place with respect to fruit and nutritional items. Pharmacological research has shown that this plant has more potential than just a fruit source; it also has beneficial effects against a variety of chronic diseases due to its rich nutritional and phytochemical profile. The primary goal of this document is to provide an updated overview of Psidium guajava L. and its bioactive secondary metabolites, as well as their availability for further study, with a focus on the health benefits and potential industrial applications. There have been several studies conducted on Psidium guajava L. in relation to its use in the pharmaceutical industry. However, its clinical efficacy and applications are still debatable. Therefore, in this review a detailed study with respect to phytochemistry of the plant through modern instruments such as GC and LC-MS has been discussed. The biological activities of secondary metabolites isolated from this plant have been extensively discussed. In order to perform long-term clinical trials to learn more about their effectiveness as drugs and applications for various health benefits, a structure activity relationship has been established. Based on the literature, it is concluded that this plant has a wide variety of biopharmaceutical applications. As a whole, this article calls for long-term clinical trials to obtain a greater understanding of how it can be used to treat different diseases.     

Applications of Nanomaterials in Microbial Fuel Cells: A Review

Microbial fuel cells (MFCs) are an environmentally friendly technology and a source of renewable energy. It is used to generate electrical energy from organic waste using bacteria, which is an effective technology in wastewater treatment. The anode and the cathode electrodes and proton exchange membranes (PEM) are important components affecting the performance and operation of MFC. Conventional materials used in the manufacture of electrodes and membranes are insufficient to improve the efficiency of MFC. The use of nanomaterials in the manufacture of the anode had a prominent effect in improving the performance in terms of increasing the surface area, increasing the transfer of electrons from the anode to the cathode, biocompatibility, and biofilm formation and improving the oxidation reactions of organic waste using bacteria. The use of nanomaterials in the manufacture of the cathode also showed the improvement of cathode reactions or oxygen reduction reactions (ORR). The PEM has a prominent role in separating the anode and the cathode in the MFC, transferring protons from the anode chamber to the cathode chamber while preventing the transfer of oxygen. Nanomaterials have been used in the manufacture of membrane components, which led to improving the chemical and physical properties of the membranes and increasing the transfer rates of protons, thus improving the performance and efficiency of MFC in generating electrical energy and improving wastewater treatment.     

Synthesis of Starch-Grafted Polymethyl Methacrylate via Free Radical Polymerization Reaction and Its Application for the Uptake of Methylene Blue

In this research, a new biodegradable and eco-friendly adsorbent, starch-grafted polymethyl methacrylate (St-g-PMMA) was synthesized. The St-g-PMMA was synthesized by a free radical polymerization reaction in which methyl methacrylate (MMA) was grafted onto a starch polymer chain. The reaction was performed in water in the presence of a potassium persulfate (KPS) initiator. The structure and different properties of the St-g-PMMA was explored by FT-IR, 1H NMR, TGA, SEM and XRD. After characterization, the St-g-PMMA was used for the removal of MB dye. Different adsorption parameters, such as effect of adsorbent dose, effect of pH, effect of initial concentration of dye solution, effect of contact time and comparative adsorption study were investigated. The St-g-PMMA showed a maximum removal percentage (R%) of 97% towards MB. The other parameters, such as the isothermal and kinetic models, were fitted to the experimental data. The results showed that the Langmuir adsorption and pseudo second order kinetic models were best fitted to experimental data with a regression coefficient of R² = 0.93 and 0.99, respectively.