A Multi-objective Particle Swarm Optimization Algorithm Based on Reverse Learning

In order to solve the contradiction between population diversity and convergence in particle swarm optimization algorithm, in this paper, a particle swarm optimization algorithm with reverse learning is proposed. On this basis, the values of learning factor and constraint factor parameters are modified, and the linear decreasing weight strategy was adopted. By modifying the learning factor and the constraint factor, the algorithm improves the particle optimization ability. It balances the global search and local search of the particle, and the convergence speed is improved by using the inertia weight. When it is detected that the algorithm falls into the local optimal region, the position information of these poor particles is used to guide some particles to reverse learning at a faster flight speed, and the particles are quickly pulled out of the local optimal region. The reverse learning process can not only improve the diversity of particle population, but also ensure the global detection ability of the algorithm. Experimental results show that, compared with the basic MOPSO algorithm, this algorithm has fast convergence speed and high solution accuracy in function optimization

Exosomes derived from MSC as drug system in osteoarthritis therapy

Osteoarthritis (OA) is the most common degenerative disease of the joint with irreversible cartilage damage as the main pathological feature. With the development of regenerative medicine, mesenchymal stem cells (MSCs) have been found to have strong therapeutic potential. However, intraarticular MSCs injection therapy is limited by economic costs and ethics. Exosomes derived from MSC (MSC-Exos), as the important intercellular communication mode of MSCs, contain nucleic acid, proteins, lipids, microRNAs, and other biologically active substances. With excellent editability and specificity, MSC-Exos function as a targeted delivery system for OA treatment, modulating immunity, inhibiting apoptosis, and promoting regeneration. This article reviews the mechanism of action of MSC-Exos in the treatment of osteoarthritis, the current research status of the preparation of MSC-Exos and its application of drug delivery in OA therapy

Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease

Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients

The gut microbiome in atherosclerotic cardiovascular disease

The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease

Preparation of Si-C-N-O Amorphous Films from A Polysilazane by Heat Treatment at High-Temperatures

Abstract. Si-C-N-O amorphous films were fabricated at about 800°C by pyrolysis of poly-vinylsilazane precursor films in a vacuum oven under N2 flow. The polymer precursor films were prepared onto Si wafers by spinning from a solution of the polymer. The compositions of the as-prepared films were confirmed by X-ray diffraction, Fourier transformation infrared spectroscopy, and x-ray photoelectron spectroscopy. SEM analysis indicated that the films can be formed with thickness more than several micrometers, and very smooth surfaces. Such films will be promising in application of protecting equipments in high-temperature, corrosive and wear environments

Additional file 1: of Risk prediction model for epithelial ovarian cancer using molecular markers and clinical characteristics

Table S1. Prognostic molecular markers in published studies. Table S2. The relationship between molecular markers and clinicopathologic characteristics. Figure S1. Single immunostaining of 15 molecular markers in epithelial ovarian cancer. Figure S2. Kaplan-Meier overall survival analyses of 15 molecular markers inepithelial ovarian cancer. (ZIP 108 kb