A circRNA-miRNA-mRNA network analysis underlying pathogenesis of human heart failure.

BACKGROUND: The molecular mechanisms of heart failure (HF) are still poorly understood. Circular RNA (circRNA) has been discovered in the heart in increasing numbers of studies. The goal of this research is to learn more about the potential roles of circRNAs in HF. METHODS & RESULTS: We used RNA sequencing data to identify the characteristics of circRNAs expressed in the heart and discovered that the majority of circRNAs screened were less than 2000 nt. Additionally, chromosomes One and Y had the most and least number of circRNAs, respectively. After excluding duplicate host genes and intergenic circRNAs, a total of 238 differentially expressed circRNAs (DECs) and 203 host genes were discovered. However, only four of the 203 host genes of DECs were examined in HF differentially expressed genes. Another study used Gene Oncology analysis of DECs host genes to elucidate the underlying pathogenesis of HF, and it found that binding and catalytic activity accounted for a large portion of DECs. Immune system, metabolism, and signal transduction pathways were significantly enriched. Furthermore, 1052 potentially regulated miRNAs from the top 40 DECs were collected to build a circRNA-miRNA network, and it was discovered that 470 miRNAs can be regulated by multiple circRNAs, while others are regulated by a single circRNA. In addition, a comparison of the top 10 mRNAs in HF and their targeted miRNAs revealed that DDX3Y and UTY were regulated by the most and least circRNA, respectively. CONCLUSION: These findings demonstrated circRNAs have species and tissue specific expression patterns; while circRNA expression is independent on host genes, the same types of genes in DECs and DEGs worked in HF. Our findings would contribute to a better understanding of the critical roles of circRNAs and lay the groundwork for future studies of HF molecular functions.

[Visual analysis of research on traditional Chinese medicine treatment of Alzheimer's disease in recent ten years].

This study employed bibliometrics tools to review the studies of traditional Chinese medicine(TCM) treatment of Alzheimer's disease(AD) in recent ten years, aiming to explore the research status, hotspots, and future trends in this field at home and abroad. The relevant literature published from January 1, 2012 to August 15, 2022 was retrieved from Web of Science and CNKI. CiteSpace 6.1R2 and VOSviewer 1.6.15 were used for the visual analysis of authors, countries, institutions, keywords, journals, etc. A total of 2 254 Chinese articles and 545 English articles were included. The annual number of articles published showed a rising trend with fluctuations. The country with the largest number of relevant articles published and the largest centrality was China. SUN Guo-jie and WANG Qi were the authors publishing the most Chinese articles and English articles, respectively. Hubei University of Chinese Medicine and Beijing University of Chinese Medicine published the most articles in Chinese and English, respectively. Journal of Ethnopharmacology and Neuroscience Letters published the articles with the highest cited frequency and the highest centrality. According to the keywords, the research on TCM treatment of AD mainly focused on the mechanism of action and treatment methods. Metabolomics, intestinal flora, oxidative stress, tau hyperphosphorylation, ß-amyloid(Aß), inflammatory cytokines, and autophagy were the focuses of the research on mechanism of action. Acupuncture, clinical effect, kidney deficiency and phlegm stasis, and dredging governor vessel to revitalize mind were the hotspots of clinical research. This research field is still in the stage of exploration and development. Exchanges and cooperation among institutions should be encouraged to carry out more high-quality basic research on TCM treatment of AD, obtain high-level evidence, and clarify the pathogenesis and prescription mechanism.

Canonical versus noncanonical equilibration dynamics of open quantum systems.

In statistical mechanics, any quantum system in equilibrium with its weakly coupled reservoir is described by a canonical state at the same temperature as the reservoir. Here, by studying the equilibration dynamics of a harmonic oscillator interacting with a reservoir, we evaluate microscopically the condition under which the equilibration to a canonical state is valid. It is revealed that the non-Markovian effect and the availability of a stationary state of the total system play a profound role in the equilibration. In the Markovian limit, the conventional canonical state can be recovered. In the non-Markovian regime, when the stationary state is absent, the system equilibrates to a generalized canonical state at an effective temperature; whenever the stationary state is present, the equilibrium state of the system cannot be described by any canonical state anymore. Our finding of the physical condition on such noncanonical equilibration might have significant impact on statistical physics. A physical scheme based on circuit QED is proposed to test our results.

[The online measurement for pulp Kappa number based on near infrared spectroscopy and support vector machine].

A new method for online measurement of pulp Kappa number by means of near infrared diffuse reflectance spectroscopy and support vector machine (SVM) modeling has been developed in this paper. The near infrared diffuse reflectance spectroscopy of 45 Chinese red pine wood pulp samples was acquired. Selecting the absorption rates in 15 vibration absorption peaks of each sample and using dynamic independent component analysis (DICA) to distill the characters of input sample data, the pulp Kappa number predictive model based on SVM was built. From the whole 45 samples, 35 samples was selected to be the calibration set, and the predictive set consisted of the other 10 samples was used to validate the the pulp Kappa number predictive model. The external validation standard deviation is 0.26 for pulp Kappa number predictive model based on SVM, and the determining factor is 0.93 for the model. The internal cross validation standard deviation is 0.22 for pulp Kappa number predictive model based on SVM, and the determining factor is 0.96 for the model. To analyze the effectiveness of SVM method used to build the pulp Kappa number predictive model, the pulp Kappa number predictive model based on linear regression (LR) was also established. The external validation standard deviation is 0.45 for the model based on linear regression (LR), and the determining factor is 0.81 for the model. The internal cross validation standard deviation is 0.41 for the model based on linear regression (LR), and the determining factor is 0.85 for the model. For the 10 test samples, the pulp Kappa number predictive model based on Linear regression (LR) and the model based on SVM all have certain predictive accuracy, but the later higher. The experiment results not only show the feasibility and effectiveness of the near infrared measurement method for pulp Kappa number, but also validate that the pulp Kappa number predictive model based on SVM is more accurate and robust than linear regression model.