Mechanistic Insights into the Stabilization of In Situ Formed γ-NiOOH Species on Ni60Nb40 Nanoglass for Effective Urea Electro-Oxidation.

The formation of NiOOH on the catalyst surface is widely considered to be the active species in electrochemical urea oxidation reactions (UOR). Though in situ-formed NiOOH species are reported to be more active than the synthesized ones, the mechanistic study of the actual active species remains a daunting task due to the possibility of different phases and instability of surface-formed NiOOH. Herein, mechanistic UOR aspects of electrochemically activated metallic Ni60Nb40 Nanoglass showing stability toward the γ-NiOOH phase are reported, probed via in situ Raman spectroscopy, supported by electron microscopy analysis and X-ray photoelectron spectroscopy in contrast with the ß-NiOOH formation favored on Ni foil. Detailed mechanistic study further reveals that γ-NiOOH predominantly follows a direct UOR mechanism while ß-NiOOH favors indirect UOR from time-dependent Raman study, and electrochemical impedance spectroscopy (EIS) analysis. The Nanoglass has shown outstanding UOR performance with a low Tafel slope of 16 mV dec-1 and stability for prolonged electrolysis (≈38 mA cm-2 for 70 h) that can be attributed to the nanostructured glassy interfaces facilitating more γ-NiOOH species formation and stabilization on the surface. The present study opens up a new direction for the development of inexpensive Ni-based UOR catalysts and sheds light on the UOR mechanism.

Unsupervised Feature Selection Using an Integrated Strategy of Hierarchical Clustering With Singular Value Decomposition: An Integrative Biomarker Discovery Method With Application to Acute Myeloid Leukemia.

In this article, we propose a novel unsupervised feature selection method by combining hierarchical feature clustering with singular value decomposition (SVD). The proposed algorithm first generates several feature clusters by adopting the hierarchical clustering on the feature space and then applies SVD to each of these feature clusters to find out the feature that contributes most to the SVD-entropy. The proposed feature selection method selects an optimal feature subset that not only minimizes the mutual dependency among the selected features but also maximizes the mutual dependency of the selected features against their nearest neighbor non-selected features to some extent. Each of the selected features also contributes the maximum SVD-entropy among all features of the same feature cluster. The experimental results demonstrate that the proposed algorithm performs well against several state-of-the-art methods of feature selection in terms of various evaluation criteria such as classification accuracy, redundancy rate, and representation entropy. The superiority of the proposed algorithm is demonstrated through analysis of Acute Myeloid Leukemia (AML) multi-omics data that consist of five datasets: gene expression, exon expression, methylation, microRNA, and pathway activity dataset (paradigm IPLs) from The Cancer Genome Atlas (TCGA). Our analysis pinpoints a candidate gene-marker, EREG for AML with an integrative omics evidence. EREG is targeted by two top ranked microRNAs, hsa-miR-1286 and hsa-miR-1976, here in the datasets. The method and results will be useful for biomarker discovery in the era of in precision medicine.

Extremely dilution of strychnos Nux vomica mitigates alcohol-induced reduction in enthalpies associated with free water molecules in a fish brain

Introduction: Alcohol intoxication affects aquaporins in the glial cells of brain resulting in oedema. Nux vomica, a homeopathic drug of plant origin, is known to counteract alcohol effect. The objective of this present study is to find out the level of free water molecules in the brain of a teleost fish under ethanol intoxication. The second objective is to determine whether Nux vomica could restore the level of free water in the alcohol treated fish. Materials and methods: One group of fish was exposed to 456 mM ethanol for 30 min, another exposed first to a solution of Nux vomica 200c for 20 min and then to 456 mM ethanol for 30 min. The third group served as an untreated control. The mid brain of each fish was kept in an aluminium sample pan and its free water level was assessed by differential scanning calorimetry (DSC). Results: All alcohol treated fish showed significant reduction in the level of free water molecules as compared to the untreated control. Treatment with Nux vomica increased the level of free water in the brain significantly as compared to the untreated alcoholic group. Conclusion: Alcohol intoxication reduces free water molecules in the fish brain. Nux vom might have acted on aquaporins in the glial cells thereby increasing the level of free water in the brain. (AU)