The gut microbiota is composed of a large number of microbes, usually regarded as commensal bacteria. It has become gradually clear that gastrointestinal microbiota affects not only gut pathophysiology but also the central nervous system (CNS) function by modulating the signaling pathways of the gut-microbiota-brain axis. This bidirectional gut-microbiota-brain axis communication primarily acts through neuroendocrine, neuroimmune, and autonomic nervous systems (ANS) mechanisms. Accumulating evidence reveals that gastrointestinal microbiota interacts with the host brain, and its modulation may play a critical role in the pathology of neuropsychiatric disorders. Recently, neuroscience research has established the significance of gut microbiota in the development of brain systems that are essential to stress-related behaviors, including depression and anxiety. Application of modulators of the microbiota-gut-brain axis, such as psychobiotics (e.g., probiotics), prebiotics, and specific diets, may be a promising therapeutic strategy for neuropsychiatric disorders. The presented review article primarily focuses on the relevant features of the disturbances of the gut-microbiota-brain axis in the pathophysiology of neuropsychiatric disorders and its potential therapeutic target in neuropsychiatric disorders, including depression and anxiety.
Objectives: To explore and validate the differential expression of circRNAs in the myocardium of congenital ventricular septal defect (VSD) and to explore a new avenue of research regarding the pathological mechanisms of VSD.Methods: We detected circRNAs expression profiles in heart tissues taken from six aborted fetuses with VSD and normal group using circRNA microarray. Some differentially expressed circRNAs were studied by bioinformatics analysis. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm these results.Results: This study found abundant circRNAs in the myocardium taken from individuals in the normal group and the VSD group. After that, totally 6234 differentially expressed circRNAs between the normal group and the VSD group were confirmed (Fold change ≥ 2.0; p < 0.05). Then, this research carried out bioinformatics analysis and predicted the potential biological functions of circRNAs. Finally, the over-expression of hsa_circRNA_002086 and under-expression of hsa_circRNA_007878, hsa_circRNA_100709, hsa_circRNA_101965, hsa_circRNA_402565 were further validated by qRT-PCR.Conclusions: There is a significant difference in expression of the circRNA in cardiac tissue from VSD group compared to the normal group. Combined with the microarray results and previous researches, circRNAs may contribute to the occurrence of VSD by acting as miRNA sponges or by binding proteins, these possible roles for circRNAs in VSD require elucidation in additional studies.
The bird's nest on the transmission line tower has a bad impact on the transmission equipment, and even threaten the safe and stable operation of the power grid. In recent years, the number of bird pest in transmission line is increasing year by year, resulting in increasing economic losses. The traditional bird's nest identification method of transmission line is time-consuming and labor-intensive, and its security level is low. Therefore, this paper proposes an automatic detection method of bird's nest on transmission line tower based on Faster_RCNN convolution neural network. This method can automatically identify the location of the bird's nest on the transmission line tower by using the image collected by unmanned aerial vehicle (UAV). The problem of insufficient training samples and overfitting of neural network classifier is solved by enlarging the bird's nest image. The experimental results show that this method can effectively detect bird's nest targets in complex environment, and the highest recall rate can reach 95.38%, the highest F1 score can reach 96.87%, and the detection time of each image can reach 0.154s. Compared with the traditional nest detection method, this method has stronger applicability and generalization ability. It provides technical support for analyzing bird activities and taking effective preventive measures.
Many long non-coding RNAs (lncRNAs) are species specific and seem to be less conserved than protein-coding genes. Some of them are involved in the development of the lateral mesoderm in the heart and in the differentiation of cardiomyocytes. The purpose of the study was to investigate the expression profiles of lncRNAs during the differentiation of P19 cells into cardiomyocytes, with a view to studying the biological function of lncRNAs and their involvement in the mechanism of heart development. First, we observed the morphology of P19 cells during differentiation using an inverted microscope. Then, cardiac troponin T (cTnT) expression was detected to validate that the cells had successfully differentiated into cardiac myocytes by real-time reverse transcriptase polymerase chain reaction (real-time RT-PCR) and western blotting. Lastly, the expression profile of lncRNA genes was obtained using an lncRNA microarray and real-time RT-PCR analyses. The microarray results showed that 40 lncRNAs were differentially expressed, of which 28 were upregulated and 12 were downregulated in differentiated cardiomyocytes. The differentially expressed lncRNAs were further validated. Our results illustrated a critical role of lncRNAs during the differentiation of P19 cells into cardiac myocytes, which will provide the foundation for further study of the biological functions of lncRNAs and the mechanism of heart development.
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