Here, for the first time, it is reported that some Mn oxides after a few hours convert to a nanolayered Mn oxide when the compounds are used as water-oxidizing catalysts in a water electrolysis device at near neutral pH and in the presence of LiClO4. The new nanolayered Mn oxide is more active than other Mn oxides toward water oxidation. This result is very important for artificial photosynthetic systems that use Mn oxides as water-oxidizing catalysts.

Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach (MM-RBM), which has the capability to connect the information about the multiple modalities, can be applied to the problem of drug repurposing. The present study utilized MM-RBM to combine two types of data, including the chemical structures data of small molecules and differentially expressed genes as well as small molecules perturbations. In the proposed method, two separate RBMs were applied to find out the features and the specific probability distribution of each datum (modality). Besides, RBM was used to integrate the discovered features, resulting in the identification of the probability distribution of the combined data. The results demonstrated the significance of the clusters acquired by our model. These clusters were used to discover the medicines which were remarkably similar to the proposed medications to treat COVID-19. Moreover, the chemical structures of some small molecules as well as dysregulated genes' effect led us to suggest using these molecules to treat COVID-19. The results also showed that the proposed method might prove useful in detecting the highly promising remedies for COVID-19 with minimum side effects. All the source codes are accessible using https ://githu b.com/LBBSo ft/Multi modal-Drug-Repur posin g.git

Nanolayered Mn oxide/poly(4-vinylpyridine) as a model for Mn cluster in photosystem II was synthesized and characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR) and UV-Visible spectroscopy (UV-Vis). The compound is a very efficient water oxidizing catalyst, and sizable oxygen evolution was detected at 50 mV overpotential at near neutral pH. The number is as low as the overpotential is used by nature in photosystem II of cyanobacteria, algae and green plants for similar reactions.

In this paper, new findings for the water-oxidizing activity of [(L)Cu(II)(NO3)], (L = (E)-3-(pyridin-2-yldiazenyl)naphthalen-2-ol (HL)) under both electro-water oxidation conditions and in the presence of cerium(iv) ammonium nitrate are reported.

Background: Despite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known. Finding the patterns and mapping the complex interactions between different genes help us to find the possible biomarkers and treatment targets. Methods: Herein, weighted gene co-expression network analysis (WGCNA) was employed to construct a co-expression network among genes identified by microarray analysis of the pediatric influenza-infected samples. Results: Three of the 38 modules were found as the most related modules to influenza infection. At a functional level, we found that the genes in these modules regulate the immune responses, protein targeting, and defense to virus. Moreover, the analysis of differentially expressed genes disclosed 719 DEGs between the normal and infected subjects. The comprehensive investigation of genes in the module involved in immune system and viral defense (yellow module) revealed that SP110, HERC5, SAMD9L, RTP4, C19orf66, HELZ2, EPSTI1, and PHF11 which were also identified as DEGs (except C19orf66) have the potential to be as the biomarkers and also drug targeting for the treatment of pediatric influenza. Conclusions: The WGCN analysis revealed co-expressed genes which were involved in the innate immune system and defense to virus. The differentially expressed genes in the identified modules can be considered for designing drug targets. Moreover, modules can help to find pathogenesis routes in the future.