Density-driven higher-order topological phase transitions in amorphous solids

Amorphous topological states, which are independent of the specific spatial distribution of microscopic constructions, have gained much attention. Recently, higher-order topological insulators, which are a new class of topological phases of matter, have been proposed in amorphous systems. Here, we propose a density-driven higher-order topological phase transition in a two-dimensional amorphous system. We demonstrate that the amorphous system hosts a topological trivial phase at low density. With an increase in the density of lattice sites, the topological trivial phase converts to a higher-order topological phase characterized by a quantized quadrupole moment and the existence of topological corner states. Furthermore, we confirm that the density-driven higher-order topological phase transition is size dependent. In addition, our results should be general and equally applicable to three-dimensional amorphous systems. Our findings may greatly enrich the study of higher-order topological states in amorphous systems

Network pharmacology-based elucidation of the molecular mechanism underlying the anti-migraine effect of Asari Radix et Rhizoma

Purpose: To determine the molecular mechanism involved in the anti-migraine effect of Asari Radix et Rhizoma (ARR) using network pharmacology. Methods: The compounds present in ARR were identified through information retrieval from literature and public databases, and were screened based on absorption, distribution, metabolism, excretion and toxicity. Target genes related to the selected compounds and migraine were identified or predicted from public databases. Hub genes in ARR against migraine were identified through analysis of interactions in overlapping genes between compounds and migraine target genes, based on STRING database. Gene enrichment analysis of overlapping genes was performed using Database for Annotation, Visualization and Integrated Discovery. Results: A total of 138 compounds were selected as potential bioactive compounds in ARR. Target genes related to the selected compounds (611 genes) and migraine (278 genes) were obtained, including 71 overlapping genes. The hub genes in the anti-migraine effect of ARR were BDNF, IL6, COMT, APP and TNF. Gene enrichment analysis showed the top 10 biological processes or pathways involved in the mechanism of anti-migraine action of ARR. The tissue source of the overlapping genes was not limited to the brain. The results from gene enrichment analysis revealed that the effect of ARR on migraine was holistic, which is characteristic of traditional Chinese medicines. Conclusion: Network pharmacology has been used to decipher the molecular mechanism involved in the action of ARR against migraine. The results provide a scientific basis for the clinical effect of ARR on migraine

MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans

Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression. Identification of miRNAs is an important requirement for understanding the mechanisms of post-transcriptional regulation. Hundreds of miRNAs have been identified by direct cloning and computational approaches in several species. However, there are still many miRNAs that remain to be identified due to lack of either sequence features or robust algorithms to efficiently identify them. Results: We have evaluated features valuable for pre-miRNA prediction, such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins. We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs. Utilizing these features and combining some improvements of the current premiRNA prediction methods, we implemented a computational learning method SVM (support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder. The tool was designed for genome-wise, pair-wise sequences from two related species. The method built into the tool consisted of two major steps: 1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method. Results from applying the tool for chicken/human and D. melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions. Conclusion: The MiRFinder can be a good alternative to current miRNA discovery software. This tool is available at http://www.bioinformatics.org/mirfinder/

The Individual and Combined Effects of Deoxynivalenol and Aflatoxin B1 on Primary Hepatocytes of Cyprinus Carpio

Aflatoxin B1 (AFB1) and deoxynivalenol (DON) are important food-borne mycotoxins that have been implicated in animal and human health. In this study, individual and combinative effects of AFB1 and DON were tested in primary hepatocytes of Cyprinus carpio. The results indicated that the combinative effects of AFB1 and DON (0.01 μg/mL AFB1 and 0.25 μg/mL DON; 0.02 μg/mL AFB1 and 0.25 μg/mL DON; 0.02 μg/mL AFB1 and 0.5 μg/mL DON) were higher than that of individual mycotoxin (P < 0.05). The activity of AST, ALT and LDH in cell supernatant was higher than that of control group (P < 0.05) when the mycotoxins were exposed to primary hepatocytes for 4 h. The decreased cell number was observed in tested group by inverted light microscopy. The mitochondrial swelling, endoplasmic reticulum dilation and a lot of lipid droplets were observed in primary hepatocytes by transmission electron microscope. Therefore, this combination was classified as an additive response of the two mycotoxins