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Background: Small extracellular vesicles (sEVs) obtained from human umbilical cord mesenchymal stromal cells (MSCs) have shown cardioprotective efficacy in doxorubicin-induced cardiotoxicity (DIC). However, their clinical application is limited due to the low yield and high consumption. This study aims to achieve large-scale production of sEVs using a three-dimensional (3D) bioreactor system. In addition, sEVs were developed to deliver Ginsenoside Rg1 (Rg1), a compound derived from traditional Chinese medicine, Ginseng, that has cardioprotective properties but limited bioavailability, to enhance the treatment of DIC. Methods: The 3D bioreactor system with spinner flasks was used to expand human umbilical cord MSCs and collect MSC-conditioned medium. Subsequently, sEVs were isolated from the conditioned medium using differential ultra-centrifugation (dUC). The sEVs were loaded with Ginsenoside Rg1 by electroporation and evaluated for cardioprotective efficacy using Cell Counting Kit-8 (CCK-8) analysis, Annexin V/PI staining and live cell count of H9c2 cells under DIC. Results: Using the 3D bioreactor system with spinner flasks, the expansion of MSCs reached ~600 million, and the production of sEVs was up to 2.2 × 1012 particles in five days with significantly reduced bench work compared to traditional 2D flasks. With the optimized protocol, the Ginsenoside Rg1 loading efficiency of sEVs by electroporation was ~21%, higher than sonication or co-incubation. Moreover, Rg1-loaded sEVs had attenuated DOX-induced cardiotoxicity with reduced apoptosis compared to free Ginsenoside Rg1 or sEVs. Conclusions: The 3D culture system scaled up the production of sEVs, which facilitated the Rg1 delivery and attenuated cardiomyocyte apoptosis, suggesting a potential treatment of DOX-induced cardiotoxicity. [ABSTRACT FROM AUTHOR]

Background: Embelin is an active compound identified as a novel X-linked inhibitor of apoptosis protein (XIAP) inhibitor from the Embelia ribes that exhibits various medicinal effects including anti-inflammatory and anticancer activities. However, the therapeutic effect of Embelin to human osteosarcoma is not yet determined.Objectives: In this study, we evaluated the sensitizing potential of Embelin on promoting apoptosis to cause osteosarcoma cell death and inhibiting its invasion.Methods: We uesd 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to detect the survival rates of osteosarcoma cells, Western blot to detect the expression of proteins in U-2 OS and MG63 cells, and fluorescence microscope to observe the morphology of apoptotic cells.Results: The survival of osteosarcoma cells decreased, When Embelin was used. Obvious condensed and flared fluorescence was observed, when used high-dose Embelin. There was an increase of caspase-3, cleaved caspase-3, caspase-8, and caspase-9 in Embelin group, while PI3K, AKt, p-AKt, X-linked inhibitor of apoptosis protein, and MMP-9 were downregulated. The invasion of Embelin application was significantly lower than that of the control application.Conclusion: Embelin promoted apoptosis via XIAP and PI3K/Akt signaling pathway. XIAP inhibitor Embelin inducing apoptosis could cause osteosarcoma cell death and inhibit its invasion. [ABSTRACT FROM AUTHOR]

Montmorillonite has been refined to overcome uncertainties originating from different sources, which offers opportunities for addressing various health issues, e.g., cosmetics, wound dressings, and antidiarrheal medicines. Herein, three commercial montmorillonite samples were obtained from different sources and labeled M1, M2, and M3 for Ca-montmorillonite, magnesium-enriched Ca-montmorillonite, and silicon-enriched Na-montmorillonite, respectively. Commercial montmorillonite was refined via ultrasonic scission-differential centrifugation and labeled S, M, or L according to the particle sizes (small, medium, or large, respectively). The size distribution decreased from 2000 nm to 250 nm with increasing centrifugation rates from 3000 rpm to 12,000 rpm. Toxicological evaluations with human colon-associated cells and human skin-associated cells indicated that side effects were correlated with excess dosages and silica sand. These side effects were more obvious with human colon-associated cells. The microscopic interactions between micro/nanosized montmorillonite and human colon-associated cells or human skin-associated cells indicated that those interactions were correlated with the size distributions. The interactions of the M1 series with the human cells were attributed to size effects because montmorillonite with a broad size distribution was stored in the M1 series. The M2 series interactions with human cells did not seem to be correlated with size effects because large montmorillonite particles were retained after refining. The M3 series interactions with human cells were attributed to size effects because small montmorillonite particles were retained after refining. This illustrates that toxicological evaluations with refined montmorillonite must be performed in accordance with clinical medical practices. [ABSTRACT FROM AUTHOR]

The increasing use of computer numerical control (CNC) machines requires better prediction of the reliability of their servo control systems. A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. It can overcome the disadvantages of conventional methods, which are time consuming and resource intensive. The major influences on the reliability of servo system include torque, temperature, current, and complexity. An improved algorithm for predicting the mean time between failure (MTBF) of servo systems based on a particle swarm optimization (PSO) and an RBF neural network algorithm is proposed. Two common problem of the PSO: local minimization and slow convergence were solved by the IPSO. "Zero failure" data preprocessing, data normalization, and small-sample data enhancement were performed on the original data. A homogenized sampling method is proposed to extract training and testing samples. Experimental results show that the improved PSO-based RBF neural network is superior to back propagation (BP) and RBF networks in terms of accuracy in servo system reliability prediction. [ABSTRACT FROM AUTHOR]