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Abstract Mitochondria are organelles highly dynamic in most types of cells, constantly changing morphology and forming dynamically continuous networks. Defects of mitochondrial dynamics are associated with various human diseases including neurodegenerative diseases and cardiovascular diseases. In the heart, mitochondria are rigidly organized between myofilaments into a crystal-like lattice pattern, the apparently limited mitochondrial movement raises the question of whether mitochondria communicate with each other dynamically. A large body of evidence reveals abnormal mitochondrial morphology in cardiac diseases and that deficiencies of mitochondrial dynamic related proteins lead to cardiac dysfunctions, indicating an essential role of mitochondrial dynamics in regulating the cardiac function. Here we will review mitochondrial dynamics in the heart with the focus on recent findings of the direct inter-mitochondrial communication in adult cardiomyocytes, and will discuss the possible regulating mechanisms. [ABSTRACT FROM AUTHOR]

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Monitoring (PARM) have been considered as a key paradigm for smart healthcare. Traditional methods for PARM focus on controlled environments with the aim of increasing the types of identifiable activity subjects complete and improving recognition accuracy and system robustness by means of novel body-worn sensors or advanced learning algorithms. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to open and connected uncontrolled environments by connecting heterogeneous cost-effective wearable devices and mobile apps. Little is currently known about whether traditional PARM technologies can tackle the new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand the use of IoT technologies in PARM studies, this paper will give a systematic review, critically examining PARM studies from a typical IoT layer-based perspective. It will firstly summarize the state-of-the-art in traditional PARM methodologies as used in the healthcare domain, including sensory, feature extraction and recognition techniques. The paper goes on to identify some new research trends and challenges of PARM studies in the IoT environments, and discusses some key enabling techniques for tackling them. Finally, this paper consider some of the successful case studies in the area and look at the possible future industrial applications of PARM in smart healthcare. [ABSTRACT FROM AUTHOR]

Background Systemic inflammation has been implicated in complications and heightened mortality of patients with secondary hyperparathyroidism. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are widely available surrogate markers of inflammation. This study sought to delineate the changes in NLR and PLR after parathyroidectomy. Methods A total of 213 patients undergoing initial parathyroidectomy from 2010 to 2015 for secondary hyperparathyroidism were identified from a prospectively maintained clinical database. Among 183 patients free of persistent or recurrent disease, follow-up NLR and PLR were available for analysis in 85 patients. Results In the whole study population, the baseline NLR was positively correlated with male sex, total white blood cell count, height, serum phosphorus, and calcium–phosphorus product levels. The baseline PLR was positively correlated with platelet count, serum phosphorus, and calcium–phosphorus product levels and negatively associated with patient age. Postoperative parathyroid hormone levels were positively correlated with NLR and PLR at follow-up. For patients who had successful parathyroidectomy, there was a decrease in NLR ( P = 0.0006), PLR ( P = 0.0003), and platelet count ( P = 0.033), whereas hemoglobin significantly increased ( P = 0.0002) after surgery. Those with persistent or recurrent hyperparathyroidism had no change in NLR, PLR, hemoglobin, total white blood cell, or platelet count. Conclusions Successful parathyroidectomy is associated with a decrease in NLR and PLR. The modulatory effects of parathyroidectomy on systemic inflammation may partially explain the benefits of surgery in secondary hyperparathyroidism. [ABSTRACT FROM AUTHOR]

This paper intend to investigate the effects of biodiesel fuel blends comprising of waste-cooking oil and butanol-diesel (B10W10–B10W40) under steady-state conditions. Both particulate organic carbon (OC) and PM including PM 2.5 and PM 10 significantly decreased with the increasing percentage of biodiesel fuel blends. The fuel blend of B10W40 also demonstrated the most effective function in reducing the emissions of PM 10 and PM 2.5 in the volume by 59.4% and 57.7%, respectively. Moreover, the emissions of nitrogen oxides decreased with the blending of B10W10-B10W40 (13.9–28.5%), while the brake specific fuel consumption was substantially increased (5.69–13.4%). The overall biological toxicity of PM 10 generated from the fuel tested in this study was determined according to Single Cell Gel Electrophoresis assay in human alveolar basal epithelial A549 cells and micronucleus assay in CHO-K1 cells. In addition, the volume of more than 20% waste-cooking oil (B10W20 and B10W40) significantly reduced diesel-induced genotoxicity in lung cells and micronucleus formation in CHO-K1 cells. Collectively, these results indicated that biodiesel fuel blends with the butanol could be a potential alternative fuels for diesel engines because of its substantial property with a significant reduction of the PM-related genotoxicity and the emissions of PM, particulate OC, and NO X . [ABSTRACT FROM AUTHOR]

The present study elucidated mechanisms through which sulforaphane (SFN) protects retinal pigment epithelial (RPE) cells from blue light–induced impairment. SFN could activate the nuclear translocation of nuclear factor erythroid 2-related factor 2 (Nrf2) and increase the expression of the heme oxygenease-1 (HO-1) gene and production of glutathione. SFN reduced blue light–induced oxidative stress, and effectively activated cytoprotective components including Nrf-2, HO-1, thioredoxin-1, and glutathione. The protective effect of SFN on blue light–induced injury was blocked by the Nrf2 inhibitor ML385, suggesting that the SFN-induced Nrf2 pathway is involved in the cytoprotective effect of SFN. SFN inhibited intercellular adhesion molecule-1 expression induced by TNF-α or blue light, suggesting the anti-inflammatory activity of SFN. The inhibitory effect of SFN was associated with the blocking of NF-κB p65 nuclear translocation in blue light–exposed RPE cells. SFN protected RPE cells from blue light–induced interruption of the mitochondrial membrane potential and reduction of the Bcl-2/Bax ratio and cleaved caspase-3 and PARP-1 expression, suggesting the antiapoptotic activity of SFN. SFN alone or together with blue light exposure increased the expression of the autophagy-related proteins LC3BII and p62. An autophagy inhibitor, 3-MA, inhibited the protective effect of SFN on blue light–induced cell damage. SFN increased sirtuin-1 (SIRT1) expression; however, treatment with blue light induced peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) expression. Our study results demonstrated that SFN exerts its protective effect under blue light exposure by maintaining the Nrf2-related redox state and upregulating SIRT1 and PGC-1α expression and autophagy. • SFN suppresses blue light-induced cell damage in RPE cells. • SFN decreases blue light-induced oxidative stress and promotes GSH production. • SFN inhibits blue light-induced ICAM-1 expression and p65 nuclear translocation. • SFN diminishes apoptosis and enhances SIRT1/PGC-1α expression. • SFN-increased autophagy protects cells against blue light exposure. [ABSTRACT FROM AUTHOR]

The recent outbreak of COVID-19 has infected millions of people around the world, which is leading to the global emergency. In the event of the virus outbreak, it is crucial to get the carriers of the virus timely and precisely, then the animal origins can be isolated for further infection. Traditional identifications rely on fields and laboratory researches that lag the responses to emerging epidemic prevention. With the development of machine learning, the efficiency of predicting the viral hosts has been demonstrated by recent researchers. However, the problems of the limited annotated virus data and imbalanced hosts information restrict these approaches to obtain a better result. To assure the high reliability of predicting the animal origins on COVID-19, we extend transfer learning and ensemble learning to present a hybrid transfer learning model. When predicting the hosts of newly discovered virus, our model provides a novel solution to utilize the related virus domain as auxiliary to help building a robust model for target virus domain. The simulation results on several UCI benchmarks and viral genome datasets demonstrate that our model outperforms the general classical methods under the condition of limited target training sets and class-imbalance problems. By setting the coronavirus as target domain and other related virus as source domain, the feasibility of our approach is evaluated. Finally, we show the animal reservoirs prediction of the COVID-19 for further analysing. [ABSTRACT FROM AUTHOR]

Laparoscopic liver surgery is challenging to perform because of compromised ability of the surgeon to localize subsurface anatomy due to minimal invasive visibility. While image guidance has the potential to address this barrier, intraoperative factors, such as insufflations and variable degrees of organ mobilization from supporting ligaments, may generate substantial deformation. The navigation ability in terms of searching and tagging within liver views has not been characterized, and current object detection methods do not account for the mechanics of how these features could be applied to the liver images. In this research, we have proposed spatial pyramid based searching and tagging of liver's intraoperative views using convolution neural network (SPST-CNN). By exploiting a hybrid combination of an image pyramid at input and spatial pyramid pooling layer at deeper stages of SPST-CNN, we reveal the gains of full-image representations for searching and tagging variable scaled liver live views. SPST-CNN provides pinpoint searching and tagging of intraoperative liver views to obtain up-to-date information about the location and shape of the area of interest. Downsampling input using image pyramid enables SPST-CNN framework to deploy input images with a diversity of resolutions for achieving scale-invariance feature. We have compared the proposed approach to the four recent state-of-the-art approaches and our method achieved better mAP up to 85.9%. [ABSTRACT FROM AUTHOR]

Graphical abstract Novel Au@CdSe heteroepitaxial nanorods were prepared via pre-growth of Ag 2 Se as an intermediate layer that favored the formation of a complete CdSe shell via a cation-exchange process. The as-obtained heterostructures with tunable shell thicknesses are expected to provide alternative substrates for various applications such as solar cells and biological detection. Abstract Synthesis of metal@semiconductor heteroepitaxial nanorods fully covered by a semiconductor shell remains challenging due to the large lattice mismatch between the two components. Here, we prepared Au@CdSe heteroepitaxial nanorods by employing pre-growth of Ag 2 Se as an intermediate layer that favored the formation of a complete CdSe shell via a cation-exchange process. The optical properties of these hybrid nanostructures can be tailored by changing the shell thickness with thicker shells resulting in a redshift of the longitudinal surface plasmon resonance. The resonance energy, intensity, and linewidth of the longitudinal surface plasmon resonance were measured by single-particle dark-field scattering spectroscopy, confirming significant electron transfer from the Au nanorod to the CdSe shell. In addition, we also studied the dependence of the catalytic reactivity on shell thickness in photocatalysis of methylene blue under UV illumination. These studies revealed that a thinner shell thickness resulted in higher photocatalytic activity. [ABSTRACT FROM AUTHOR]

Highlights: [•] We detected expression of miR-205 in breast cancer cell lines and tissue samples. [•] We suggest miR-205 is downregulated in human breast cancer tissues and MCF7 cells. [•] We suggest the lower expression of miR-205 play a role in breast cancer onset. [•] These data suggest that miR-205 directly targets HER3 in human breast cancer. [ABSTRACT FROM AUTHOR]

Abstract: A cDNA encoding hepatitis C virus NS5A protein was isolated from the serum of a patient with hepatocellular carcinoma. The NS5AHCC was localized in both the cytoplasmic and nuclear fractions of Huh-7 cells. Immunoprecipitation and electrophoresis experiments showed four major phosphorylated species of NS5AHCC, p58, p56, p53, and p50. Two mutants (NS5AHCC-NLSmt and NS5AHCC-TSmt) carrying mutations on the putative nuclear localization signal were engineered. NS5AHCC-NLSmt was localized exclusively in the cytoplasm, whereas some forms of NS5AHCC-TSmt can be transported into the nucleus. These NS5AHCC mutant proteins were capable of transactivating c-fos and SV40 promoters. However, the transactivation efficiency was not dependent on its capability of nuclear localization. Subsequently, interaction between NS5AHCC mutants and Grb2 was studied. While capable of transactivating oncogenic promoters, NS5AHCC-TSmt could not interact with Grb2. Our results suggested that other cytosolic pathways independent of Grb2-mediated mechanisms were involved in the transactivation activity of HCV NS5A. [Copyright &y& Elsevier]