In-Situ Growth of One-Dimensional Blocking Layer to Mitigate Deficient Surface of Single-Crystal Perovskites.

Organic-inorganic halide perovskite (OIHP) single crystals are promising for optoelectronic application, but their high surface trap density and associated ion migration hinders device performance and stability. Herein, a one-dimensional (1D) perovskites are designed and proposed as blocking layer at the crystal/electrode interface to mitigate the surface issues. As a model system, the interface ion migration in CsFAPbI (FA=formamidinium) single-crystal perovskite solar cells (PSCs) is obviously suppressed, leading to increase of T lifetime from 260 to 1000 hours, five times better than previously reported results.

Facile Solvothermal Synthesis of Hollow BiOBr Submicrospheres with Enhanced Visible-Light-Responsive Photocatalytic Performance.

In this work, hierarchical hollow BiOBr submicrospheres (HBSMs) were successfully prepared a facile yet efficient solvothermal strategy. Remarkable effects of solvents upon the crystallinities, morphologies, and microstructures of the BiOBr products were systematically investigated, which revealed that the glycerol/isopropanol volumetric ratio played a significant role in the formation of hollow architecture. Accordingly, the underlying formation mechanism of the hollow submicrospheres was tentatively put forward here.

RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction.

Based on advancements in deep sequencing technology and microbiology, increasing evidence indicates that microbes inhabiting humans modulate various host physiological phenomena, thus participating in various disease pathogeneses. Owing to increasing availability of biological data, further studies on the establishment of efficient computational models for predicting potential associations are required. In particular, computational approaches can also reduce the discovery cycle of novel microbe-disease associations and further facilitate disease treatment, drug design, and other scientific activities.

Integrating random walk and binary regression to identify novel miRNA-disease association.

Background: In the last few decades, cumulative experimental researches have witnessed and verified the important roles of microRNAs (miRNAs) in the development of human complex diseases. Benefitting from the rapid growth both in the availability of miRNA-related data and the development of various analysis methodologies, up until recently, some computational models have been developed to predict human disease related miRNAs, efficiently and quickly.

Results: In this work, we proposed a computational model of Random Walk and Binary Regression-based MiRNA-Disease Association prediction (RWBRMDA).

Maximal entropy random walk on heterogenous network for MIRNA-disease Association prediction.

The last few decades have verified the vital roles of microRNAs in the development of human diseases and witnessed the increasing interest in the prediction of potential disease-miRNA associations. Owning to the open access of many miRNA-related databases, up until recently, kinds of feasible in silico models have been proposed. In this work, we developed a computational model of Maximal Entropy Random Walk on heterogenous network for MiRNA-disease Association prediction (MERWMDA).

Combination of Phospholipid Complex and Submicron Emulsion Techniques for Improving Oral Bioavailability and Therapeutic Efficacy of Water-Insoluble Drug.

Water-insoluble drugs cannot be absorbed effectively through the gastrointestinal tract due to insufficient solubility and often face the problems of low bioavailability and poor therapeutic efficacy. To overcome these biopharmaceutical challenges, lipid-based formulations were suggested and have been researched in recent years. In this study, we used atorvastatin as a model drug to prepare a phospholipid complex prodrug system to upgrade its lipophilicity and further developed a drug loaded submicron emulsion to improve its in vivo bioavailability.

MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.

Background: Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases. Especially, constructing computational methods to predict potential miRNA-disease associations is worthy of more studies because of the feasibility and effectivity.

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm.

Formulation and Drug Loading Features of Nano-Erythrocytes.

Nano erythrocyte ghosts have recently been used as drug carriers of water-soluble APIs due to inherit biological characteristics of good compatibility, low toxicity, and small side-effect. In this study, we developed a novel drug delivery system based on nano erythrocyte ghosts (STS-Nano-RBCs) to transport Sodium Tanshinone IIA sulfonate (STS) for intravenous use in rat. STS-Nano-RBCs were prepared by hypotonic lysis and by extrusion methods, and its biological properties were investigated compared with STS injection.