Transmission electron microscopy assessment of a novel method for isolating pure exosomes from serum.

Serum exosomes frequently are used for liquid biopsy. Serum exosomes normally are isolated using ultracentrifugation; however, ultracentrifugation is time-consuming, labor intensive and requires a high-speed centrifuge. Many commercial kits use a precipitation-based method; however, this process can result in substantial contamination. We developed a new method to isolate pure serum exosomes. We isolated serum exosomes using precipitation, extracted them using acetone, then isolated them again by precipitation. We used transmission electron microscopy (TEM) to examine the morphology of serum exosomes. TEM indicated that our isolated exosomes were pure with typical morphology and with a size ranging from 40 to 150 nm. Flow cytometry revealed expression of exosome markers, CD63, CA81 and CD9. Our double precipitation method enables ready extraction of pure exosomes from serum. Our double precipitation method simplifies detection of serum exosomal biomarkers for diagnosis and prognosis of disease.

Assessment of dynamic drought-induced ecosystem risk: Integrating time-varying hazard frequency, exposure and vulnerability.

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization.

Do Rural-Urban Identities Affect Individuals' Health? Evidence From China.

We study the relationship between household registration status (Hukou) and the state of individuals' health to find out whether inequality in health between urban and rural population exists in China. We have used the probit model to regress the state of health on household registration using the individual-level data of the 2018 CFPS survey. We find that inequality in health between urban and rural population does exist in China. Individuals with rural Hukou have a higher probability by 1.4% to be admitted to hospital than individuals with urban Hukou. While, individuals with rural Hukou tend to over-estimate the state of their health as the probability for them to assess themselves healthy is higher by 1.7% than individuals with urban Hukou. The findings suggest that policy makers should recognize the issue of rural-urban health inequalities and take measures, such as controlling pollution in rural areas and providing high quality routine health checks for rural population to deal with the problem.

Cooperative Output Regulation Quadratic Control for Discrete-Time Heterogeneous Multiagent Markov Jump Systems.

This article investigates the cooperative output regulation problem for discrete-time heterogeneous multiagent Markov jump systems. Two cases are studied: 1) output regulation quadratic control in the case where the exosystem is accessible to all agents and 2) cooperative output regulation quadratic control in the case where only a part of agents can directly communicate with the exosystem. The hidden Markov models are employed to describe the asynchronous modes of the agents and their corresponding controllers. Via the jumping regulator equation, asynchronous control laws are constructed and the algorithms to obtain control parameters are presented in terms of linear matrix inequalities. For the first case, the optimal synchronous/mode-dependent control law, which is a special case of the asynchronous control protocol, is also given via the stochastic dynamic programming approach. Finally, an example is given to illustrate the effectiveness of the proposed approaches.

A Novel Fixed-Time Converging Neurodynamic Approach to Mixed Variational Inequalities and Applications.

This article proposes a novel fixed-time converging forward-backward-forward neurodynamic network (FXFNN) to deal with mixed variational inequalities (MVIs). A distinctive feature of the FXFNN is its fast and fixed-time convergence, in contrast to conventional forward-backward-forward neurodynamic network and projected neurodynamic network. It is shown that the solution of the proposed FXFNN exists uniquely and converges to the unique solution of the corresponding MVIs in fixed time under some mild conditions. It is also shown that the fixed-time convergence result obtained for the FXFNN is independent of initial conditions, unlike most of the existing asymptotical and exponential convergence results. Furthermore, the proposed FXFNN is applied in solving sparse recovery problems, variational inequalities, nonlinear complementarity problems, and min-max problems. Finally, numerical and experimental examples are presented to validate the effectiveness of the proposed neurodynamic network.

The global significance of biodiversity science in China: an overview.

Biodiversity science in China has seen rapid growth over recent decades, ranging from baseline biodiversity studies to understanding the processes behind evolution across dynamic regions such as the Qinghai-Tibetan Plateau. We review research, including species catalogues; biodiversity monitoring; the origins, distributions, maintenance and threats to biodiversity; biodiversity-related ecosystem function and services; and species and ecosystems' responses to global change. Next, we identify priority topics and offer suggestions and priorities for future biodiversity research in China. These priorities include (i) the ecology and biogeography of the Qinghai-Tibetan Plateau and surrounding mountains, and that of subtropical and tropical forests across China; (ii) marine and inland aquatic biodiversity; and (iii) effective conservation and management to identify and maintain synergies between biodiversity and socio-economic development to fulfil China's vision for becoming an ecological civilization. In addition, we propose three future strategies: (i) translate advanced biodiversity science into practice for biodiversity conservation; (ii) strengthen capacity building and application of advanced technologies, including high-throughput sequencing, genomics and remote sensing; and (iii) strengthen and expand international collaborations. Based on the recent rapid progress of biodiversity research, China is well positioned to become a global leader in biodiversity research in the near future.

A proximal neurodynamic model for solving inverse mixed variational inequalities.

This paper proposes a proximal neurodynamic model (PNDM) for solving inverse mixed variational inequalities (IMVIs) based on the proximal operator. It is shown that the PNDM has a unique continuous solution under the condition of Lipschitz continuity (L-continuity). It is also shown that the equilibrium point of the proposed PNDM is asymptotically stable or exponentially stable under some mild conditions. Finally, three numerical examples are presented to illustrate effectiveness of the proposed PNDM.

A birdstrike risk assessment model and its application at Ordos Airport, China.

Birdstrikes are an important threat to aviation safety. A standardized, scientific process for assessing birdstrike risk could prevent accidents, thereby improving the flight safety and reducing economic losses. However, China currently lacks a unified birdstrike risk assessment system. Here, we propose and validate a new model for assessing birdstrike risk in order to fill that need. The model consists of two elements. First, empirical data are collected on the occurrence of birds at the airport and in a surrounding 8 km buffer. Second, each species is evaluated with a risk assessment matrix that takes into account the number of birds, weight, flight altitude, a tendency to cluster, and range of activity. These five factors allow each species to be divided into one of three risk levels: high danger (level 3), moderate danger (level 2) and low danger (level 1). We propose corresponding birdstrike prevention measures for each level. We apply this method to the civil aviation airport in Ordos, China. We found that 20 of the 118 species of birds in and around the airport were high danger birds (level 3). To validate this process, we compared these species with records of birdstrike accidents in a database maintained by the Civil Aviation Administration of China (CAAC) for 2007-2016. We found that 42% of the species we identified as high risk had been involved in at least one birdstrike accident, and that the remaining 58% belonged to families that appeared in the database. The high degree of overlap gives us high confidence in the practicality of our risk assessment model, which is based on the risk management concept of ISO 31000. Critically, this new model and method for predicting bird strike risk can be replicated at other airports around the world, even where no extensive records have been kept of past birdstrikes.

Randomized, self-controlled, prospective assessment of the efficacy of mometasone furoate local application in reducing acute radiation dermatitis in patients with head and neck squamous cell carcinomas.

BACKGROUND: Acute radiation dermatitis (ARD) is a common adverse effect in patients undergoing radiotherapy. Mometasone furoate cream (MMF) was reported to significantly reduce ARD, especially in breast cancer. Clinically, ARD is more critical and more difficult to prevent in patients with head and neck squamous cell carcinoma (HNSCC) than in those with breast cancer, because a higher dose of radiotherapy is required in HNSCC cases. The aim of this study was to evaluate the effect of MMF local application on radiation dermatitis in patients with HNSCC. METHODS: HNSCC patients scheduled for bilateral radical radiotherapy to the neck with identical radiation doses were enrolled. One side of the neck skin (test groups) of the patients were randomized to apply a thin layer of MMF once a day from the date of first radiotherapy until either 2 weeks after end of radiotherapy or until the test side skin developed ARD lesions, while the other side of neck (control groups) didn't apply any medication. The severity of ARD was evaluated weekly by using the modified radiation therapy oncology group score, pain intensity, and itch stages. RESULTS: Forty-one patients (82 targets) were analyzed. There was a significant difference between the ARD scores on the test side and the control side. MMF reduced the stages of ARD when the radiotherapy dose was <6000 cGY (P = .01) but showed no improvement when the dose was ≥6000 cGY (P = .699). Compared to the control side, local application of MMF significantly reduced the itch and pain scores of the test side skin regardless of the radiotherapy dose and ARD stage (P < .001) during radiotherapy. CONCLUSIONS: This study showed that MMF inunction after high-dose radiotherapy (>50 Gy) can prevent ARD, especially when the radiation dose is <6000 cGY.

The establishment and biological assessment of a whole tissue-engineered intervertebral disc with PBST fibers and a chitosan hydrogel in vitro and in vivo.

Intervertebral disc (IVD) degeneration (IDD) is the main cause of low back pain in the clinic. In the advanced stage of IDD, both cell transplantation and gene therapy have obvious limitations. At this stage, tissue-engineered IVDs (TE-IVDs) provide new hope for the treatment of this disease. We aimed to construct a TE-IVD with a relatively complete structure. The inner annulus fibrosus (AF) was constructed using poly (butylene succinate-co-terephthalate) copolyester (PBST) electrospun fibers, and the outer AF consisted of solid PBST. The nucleus pulposus (NP) scaffold was constructed using a chitosan hydrogel, as reported in our previous research. The three components were assembled in vitro, and the mechanical properties were analyzed. AF and NP cells were implanted on the corresponding scaffolds. Then, the cell-seeded scaffolds were implanted subcutaneously in nude mice and cultured for 4 weeks; then they were removed and implanted into New Zealand white rabbits. After 4 weeks, their properties were analyzed. The PBST outer AF provided mechanical support for the whole TE-IVD. The electrospun film and chitosan hydrogel simulated the natural structure of the IVD well. Its mechanical property could meet the requirement of the normal IVD. Four weeks later, X-ray and MR imaging examination results suggested that the height of the intervertebral space was retained. The cells on the TE-IVD expressed extracellular matrix, which indicated that the cells maintained their biological function. Therefore, we conclude that the whole TE-IVD has biological and biomechanical properties to some extent, which is a promising candidate for IVD replacement therapies. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 2305-2316, 2019.

Use of low-dose computed tomography to assess pulmonary tuberculosis among healthcare workers in a tuberculosis hospital.

BACKGROUND: According to the World Health Organization, China is one of 22 countries with serious tuberculosis (TB) infections and one of the 27 countries with serious multidrug-resistant TB strains. Despite the decline of tuberculosis in the overall population, healthcare workers (HCWs) are still at a high risk of infection. Compared with high-income countries, the TB prevalence among HCWs is higher in low- and middle-income countries. Low-dose computed tomography (LDCT) is becoming more popular due to its superior sensitivity and lower radiation dose. However, there have been no reports about active pulmonary tuberculosis (PTB) among HCWs as assessed with LDCT. The purposes of this study were to examine PTB statuses in HCWs in hospitals specializing in TB treatment and explore the significance of the application of LDCT to these workers. METHODS: This study retrospectively analysed the physical examination data of healthcare workers in the Beijing Chest Hospital from September 2012 to December 2015. Low-dose lung CT examinations were performed in all cases. The comparisons between active and inactive PTB according to the CT findings were made using the Pearson chi-square test or the Fisher's exact test. Comparisons between the incidences of active PTB in high-risk areas and non-high-risk areas were performed using the Pearson chi-square test. Analyses of active PTB were performed according to different ages, numbers of years on the job, and the risks of the working areas. Active PTB as diagnosed by the LDCT examinations alone was compared with the final comprehensive diagnoses, and the sensitivity and positive predictive value were calculated. RESULTS: A total of 1 012 participants were included in this study. During the 4-year period of medical examinations, active PTB was found in 19 cases, and inactive PTB was found in 109 cases. The prevalence of active PTB in the participants was 1.24%, 0.67%, 0.81%, and 0.53% for years 2012 to 2015. The corresponding incidences of active PTB among the tuberculosis hospital participants were 0.86%, 0.41%, 0.54%, and 0.26%. Most HCWs with active TB (78.9%, 15/19) worked in the high-risk areas of the hospital. There was a significant difference in the incidences of active PTB between the HCWs who worked in the high-risk and non-high-risk areas (odds ratio [OR], 14.415; 95% confidence interval (CI): 4.733 - 43.896). Comparisons of the CT signs between the active and inactive groups via chi-square tests revealed that the tree-in-bud, cavity, fibrous shadow, and calcification signs exhibited significant differences (P = 0.000, 0.021, 0.001, and 0.024, respectively). Tree-in-bud and cavity opacities suggest active pulmonary tuberculosis, whereas fibrous shadow and calcification opacities are the main features of inactive pulmonary tuberculosis. Comparison with the final comprehensive diagnoses revealed that the sensitivity and positive predictive value of the diagnoses of active PTB based on LDCT alone were 100% and 86.4%, respectively. CONCLUSIONS: Healthcare workers in tuberculosis hospitals are a high-risk group for active PTB. Yearly LDCT examinations of such high-risk groups are feasible and necessary.

Opportunities in systems biology to discover mechanisms and repurpose drugs for CNS diseases.

Therapies for central nervous system (CNS) diseases remain an unmet medical need. This is largely due to multiple unknown disease-modifying genes and pathways. Systems biology through network modeling has shown promise in discovering novel therapeutic targets, deciphering disease mechanisms, and suggesting drug repurposing opportunities. In this article we cover current progress in systems biology and its role, applications, and challenges in the pharmaceutical industry. We also outline a practical strategy to infer drug repositioning candidates for rare CNS diseases by describing Multiple Level Network Modeling (MLNM) analysis.

A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints.

This paper presents a novel recurrent neural network for solving nonlinear optimization problems with inequality constraints. Under the condition that the Hessian matrix of the associated Lagrangian function is positive semidefinite, it is shown that the proposed neural network is stable at a Karush-Kuhn-Tucker point in the sense of Lyapunov and its output trajectory is globally convergent to a minimum solution. Compared with variety of the existing projection neural networks, including their extensions and modification, for solving such nonlinearly constrained optimization problems, it is shown that the proposed neural network can solve constrained convex optimization problems and a class of constrained nonconvex optimization problems and there is no restriction on the initial point. Simulation results show the effectiveness of the proposed neural network in solving nonlinearly constrained optimization problems.