The association of chromosome 8p deletion and tumor metastasis in human hepatocellular carcinoma

Program no. 686postprin

Seasonal variations in carbon, nitrogen and phosphorus concentrations and C:N:P stoichiometry in different organs of a Larix principis-rupprechtii Mayr. plantation in the Qinling Mountains, China

Understanding how concentrations of elements and their stoichiometry change with plant growth and age is critical for predicting plant community responses to environmental change. Weusedlong-term field experiments to explore how the leaf, stem and root carbon (C), nitrogen (N) and phosphorous (P) concentrations and their stoichiometry changed with growth and stand age in a L.principis-rupprechtii Mayr. plantation from 2012–2015 in the Qinling Mountains, China. Our results showed that the C, N and P concentrations and stoichiometric ratios in different tissues of larch stands were affected by stand age, organ type andsampling month and displayed multiple correlations with increased stand age in different growing seasons. Generally, leaf C and N concentrations were greatest in the fast-growing season, but leaf P concentrations were greatest in the early growing season. However, no clear seasonal tendencies in the stem and root C, N and P concentrations were observed with growth. In contrast to N and P, few differences were found in organ-specific C concentrations. Leaf N:P was greatest in the fast-growing season, while C:N and C:P were greatest in the late-growing season. No clear variations were observed in stem and root C:N, C:P andN:Pthroughout the entire growing season, but leaf N:P was less than 14, suggesting that the growth of larch stands was limited by N in our study region. Compared to global plant element concentrations and stoichiometry, the leaves of larch stands had higher C, P, C:NandC:PbutlowerNandN:P,andtherootshadgreater PandC:NbutlowerN,C:Pand N:P. Our study provides baseline information for describing the changes in nutritional elements with plant growth, which will facilitates plantation forest management and restoration, and makes avaluable contribution to the global data pool on leaf nutrition and stoichiometry

Quality Grade Evaluation of Niuhuang Qingwei Pills Based on UPLC and TCM Reference Drug—A Novel Principle of Analysis of Multiple Components in Ready-Made Chinese Herbal Medicine

Ready-made Chinese herbal medicine (RMCHM) is one of the most common types of synergistic herbal medicine used worldwide. It is based on composite herbal formulae (CHF), which makes quality control of this kind of traditional Chinese medicine (TCM) difficult, let alone distinguishing the good from the bad. Taking Niuhuang Qingwei Pills (NHQWP) as an example, this study reported the development of a novel principle of analysis of multiple components in RMCHM. Experimental procedures involved the selection of high-quality Chinese materia medica (CMM, individual medicinal plant parts used in the NHQWP) to prepare three batches of TCM reference drugs (TCMRD). Pure compounds of the active ingredients identified in the herbal formula including berberine hydrochloride, geniposide, forsythiaside A, 3,5-O-dicaffeoyl quinic acid, hesperidin, baicalin, glycyrrhizic acid, and chrysophanol in the three TCMRDs were analyzed as well as those in 49 batches of commercial products from 18 manufacturers by ultra-performance liquid chromatography (UPLC) method combined with wavelength switching. Using the TCMRD as the scientific ruler, quality grade specifications of NHQWP were proposed by comprehensive analysis of multiple components. Accordingly, 13, 28, and 8 batches of samples were primarily rated as first-grade, second-grade, and unqualified, respectively

Dual cloud point extraction coupled with hydrodynamic-electrokinetic two-step injection followed by micellar electrokinetic chromatography for simultaneous determination of trace phenolic estrogens in water samples

A dual cloud point extraction (dCPE) off-line enrichment procedure coupled with a hydrodynamic-electrokinetic two-step injection online enrichment technique was successfully developed for simultaneous preconcentration of trace phenolic estrogens (hexestrol, dienestrol, and diethylstilbestrol) in water samples followed by micellar electrokinetic chromatography (MEKC) analysis. Several parameters affecting the extraction and online injection conditions were optimized. Under optimal dCPE-two-step injection-MEKC conditions, detection limits of 7.9-8.9 ng/mL and good linearity in the range from 0.05 to 5 mu g/mL with correlation coefficients R (2) a parts per thousand yenaEuro parts per thousand 0.9990 were achieved. Satisfactory recoveries ranging from 83 to 108 % were obtained with lake and tap water spiked at 0.1 and 0.5 mu g/mL, respectively, with relative standard deviations (n = 6) of 1.3-3.1 %. This method was demonstrated to be convenient, rapid, cost-effective, and environmentally benign, and could be used as an alternative to existing methods for analyzing trace residues of phenolic estrogens in water samples.A dual cloud point extraction (dCPE) off-line enrichment procedure coupled with a hydrodynamic-electrokinetic two-step injection online enrichment technique was successfully developed for simultaneous preconcentration of trace phenolic estrogens (hexestrol, dienestrol, and diethylstilbestrol) in water samples followed by micellar electrokinetic chromatography (MEKC) analysis. Several parameters affecting the extraction and online injection conditions were optimized. Under optimal dCPE-two-step injection-MEKC conditions, detection limits of 7.9-8.9 ng/mL and good linearity in the range from 0.05 to 5 mu g/mL with correlation coefficients R (2) a parts per thousand yenaEuro parts per thousand 0.9990 were achieved. Satisfactory recoveries ranging from 83 to 108 % were obtained with lake and tap water spiked at 0.1 and 0.5 mu g/mL, respectively, with relative standard deviations (n = 6) of 1.3-3.1 %. This method was demonstrated to be convenient, rapid, cost-effective, and environmentally benign, and could be used as an alternative to existing methods for analyzing trace residues of phenolic estrogens in water samples

A comparative study on different parallel solvers for nonlinear analysis of complex structures

The parallelization of 2D/3D software SAPTIS is discussed for nonlinear analysis of complex structures. A comparative study is made on different parallel solvers. The numerical models are presented, including hydration models, water cooling models, modulus models, creep model, and autogenous deformation models. A finite element simulation is made for the whole process of excavation and pouring of dams using these models. The numerical results show a good agreement with the measured ones. To achieve a better computing efficiency, four parallel solvers utilizing parallelization techniques are employed: (1) a parallel preconditioned conjugate gradient (PCG) solver based on OpenMP, (2) a parallel preconditioned Krylov subspace solver based on MPI, (3) a parallel sparse equation solver based on OpenMP, and (4) a parallel GPU equation solver. The parallel solvers run either in a shared memory environment OpenMP or in a distributed memory environment MPI. A comparative study on these parallel solvers is made, and the results show that the parallelization makes SAPTIS more efficient, powerful, and adaptable

Accreting Black Holes

This chapter provides a general overview of the theory and observations of black holes in the Universe and on their interpretation. We briefly review the black hole classes, accretion disk models, spectral state classification, the AGN classification, and the leading techniques for measuring black hole spins. We also introduce quasi-periodic oscillations, the shadow of black holes, and the observations and the theoretical models of jets.Comment: 41 pages, 18 figures. To appear in "Tutorial Guide to X-ray and Gamma-ray Astronomy: Data Reduction and Analysis" (Ed. C. Bambi, Springer Singapore, 2020). v3: fixed some typos and updated some parts. arXiv admin note: substantial text overlap with arXiv:1711.1025

Ecological Footprint Model Using the Support Vector Machine Technique

The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance

Perspectives on the Trypanosoma cruzi-host cell receptor interaction

Chagas disease is caused by the parasite Trypanosoma cruzi. The critical initial event is the interaction of the trypomastigote form of the parasite with host receptors. This review highlights recent observations concerning these interactions. Some of the key receptors considered are those for thromboxane, bradykinin, and for the nerve growth factor TrKA. Other important receptors such as galectin-3, thrombospondin, and laminin are also discussed. Investigation into the molecular biology and cell biology of host receptors for T. cruzi may provide novel therapeutic targets

Lean manufacturing, culture and their role on sustainability: A case study in the Chinese automotive industry

This paper focuses on lean manufacturing and culture and how they influence the sustainability initiatives of an Automotive company in China. The principle of lean manufacturing is widely applied in the automotive industry worldwide. The last few decades have witnessed the accelerating pace of China’s continued emergence as a major industrial power. With the globalisation of multinational corporations and the development of domestic automotive enterprises, there is an increasing number of cross-cultural motor manufacturing companies starting their business in China. In these companies, cultural diversity is an important factor that affects the management strategies. Using a case study approach, this paper shows the relevant themes on the role of lean manufacturing and culture on the sustainability initiatives taken by the company