CHINESE BORROWINGS IN THE LANGUAGE OF RUSSIAN EMIGRANTS IN THE FIRST HALF OF THE 20th CENTURY

The article analyzes Chinese borrowings in the language of Russian emigrants in Northeast China in the first half of the 20th century. The concept of borrowing and the reasons for the appearance of loan words are also described. In modern linguistics, there are several interpretations of the concept ‘borrowing’. Diffe­rent definitions were given by many linguists. According to the definition that appears to be the most complete and commonly used one, ‘borrowing’ is an element of a foreign language (word, morpheme, syntactic construction, etc.) transferred from one language to another as a result of language contacts, as well as the process of transition of elements of one language into another. Lexical borrowing as a process is determined by a combination of internal (linguistic) and external (extralinguistic) factors. The main reason for borrowing to occur is the absence of the corresponding concept in the accepting language. The emergence of Chinese borrowings was closely related to historical events – Russia’s gaining the right to build the Chinese Eastern Railway (CER) through the territory of Manchuria. In the article, the main borrowing methods – transcription and calquing – are considered based on the analysis of Chinese borrowings used by N. I. Ilyina in her memoirs Destiny, Roads and Return. Furthermore, the article proposes a classification of the borrowed words by lexical-thematic groups: the names of geographical objects, personal names, names of parties, natural objects, household items (food, housing, monetary units, games, etc.) and interjections; grammatical and semantic analysis of these words is also provided. Borrowing is one of the natural ways to enrich vocabulary of any language. Loan words play an important role in the lexical system of the accepting language. These words can serve as reflection of another culture, its mentality, traditions and customs

Sulfotanshinone Sodium Injection for Unstable Angina Pectoris: A Systematic Review of Randomized Controlled Trials

Objective. To assess the effect of sulfotanshinone sodium injection for unstable angina. Methods. We searched for published and unpublished studies up to June 2011. We included randomized controlled trials that confoundedly addressed the effect of sulfotanshinone sodium injection in the treatment of unstable angina. Results. Twenty-five studies involving 2,377 people were included. There was no evidence that sulfotanshinone sodium alone had better or worse effects to routine western medicine treatments in improving clinical symptoms (RR 1.00, 95% CI 0.90 to 1.11) and ECG (RR 0.97, 95% CI 0.87 to 1.09). However, there was evidence that sulfotanshinone sodium combined with western medications was a better treatment option than western medications alone in improving clinical symptoms (RR 1.28, 95% CI 1.23 to 1.3), ECG (RR 1.26, 95% CI 1.18 to 1.35), C-reaction protein (mean difference 2.10, 95% CI 1.63 to 2.58), and IL-6 (mean difference −3.85, 95% CI −4.10 to −3.60). There was no difference between sulfotanshinone sodium plus western medications and western medications alone affecting mortality (RR 0.50, 95% CI 0.02 to 12.13). Conclusion. Compared with western medications alone, sulfotanshinone sodium combined with western medications may provide more benefits for patients with unstable angina. Further large-scale high-quality trials are warranted

RHCO: A Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning for Large-scale Graphs

Heterogeneous graph neural networks (HGNNs) have been widely applied in heterogeneous information network tasks, while most HGNNs suffer from poor scalability or weak representation when they are applied to large-scale heterogeneous graphs. To address these problems, we propose a novel Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning (RHCO) for large-scale heterogeneous graph representation learning. Unlike traditional heterogeneous graph neural networks, we adopt the contrastive learning mechanism to deal with the complex heterogeneity of large-scale heterogeneous graphs. We first learn relation-aware node embeddings under the network schema view. Then we propose a novel positive sample selection strategy to choose meaningful positive samples. After learning node embeddings under the positive sample graph view, we perform a cross-view contrastive learning to obtain the final node representations. Moreover, we adopt the label smoothing technique to boost the performance of RHCO. Extensive experiments on three large-scale academic heterogeneous graph datasets show that RHCO achieves best performance over the state-of-the-art models

Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction

Accurate citation count prediction of newly published papers could help editors and readers rapidly figure out the influential papers in the future. Though many approaches are proposed to predict a paper's future citation, most ignore the dynamic heterogeneous graph structure or node importance in academic networks. To cope with this problem, we propose a Dynamic heterogeneous Graph and Node Importance network (DGNI) learning framework, which fully leverages the dynamic heterogeneous graph and node importance information to predict future citation trends of newly published papers. First, a dynamic heterogeneous network embedding module is provided to capture the dynamic evolutionary trends of the whole academic network. Then, a node importance embedding module is proposed to capture the global consistency relationship to figure out each paper's node importance. Finally, the dynamic evolutionary trend embeddings and node importance embeddings calculated above are combined to jointly predict the future citation counts of each paper, by a log-normal distribution model according to multi-faced paper node representations. Extensive experiments on two large-scale datasets demonstrate that our model significantly improves all indicators compared to the SOTA models.Comment: Accepted by CIKM'202

High-fat diets enhance and delay ursodeoxycholic acid absorption but elevate circulating hydrophobic bile salts

Background: Ursodeoxycholic acid (UDCA) is a natural drug essential for the treatment of cholestatic liver diseases. The food effects on the absorption of UDCA and the disposition of circulating bile salts remain unclear despite its widespread global uses. This study aims to investigate the effects of high-fat (HF) diets on the pharmacokinetics of UDCA and disclose how the circulated bile salts were simultaneously perturbed.Methods: After an overnight fast, a cohort of 36 healthy subjects received a single oral dose (500 mg) of UDCA capsules, and another cohort of 31 healthy subjects received the same dose after consuming a 900 kcal HF meal. Blood samples were collected from 48 h pre-dose up to 72 h post-dose for pharmacokinetic assessment and bile acid profiling analysis.Results: The HF diets significantly delayed the absorption of UDCA, with the Tmax of UDCA and its major metabolite, glycoursodeoxycholic acid (GUDCA), changing from 3.3 h and 8.0 h in the fasting study to 4.5 h and 10.0 h in the fed study, respectively. The HF diets did not alter the Cmax of UDCA and GUDCA but immediately led to a sharp increase in the plasma levels of endogenous bile salts including those hydrophobic ones. The AUC0–72h of UDCA significantly increased from 25.4 μg h/mL in the fasting study to 30.8 μg h/mL in the fed study, while the AUC0–72h of GUDCA showed no difference in both studies. As a result, the Cmax of total UDCA (the sum of UDCA, GUDCA, and TUDCA) showed a significant elevation, while the AUC0–72h of total UDCA showed a slight increase without significance in the fed study compared to the fasting study.Conclusion: The HF diets delay UDCA absorption due to the extension of gastric empty time. Although UDCA absorption was slightly enhanced by the HF diets, the beneficial effect may be limited in consideration of the simultaneous elevation of circulating hydrophobic bile salts

Research advances in cell models of hepatitis B virus

Hepatitis B virus (HBV) infection has become the main cause of hepatocellular carcinoma. A series of cell models for HBV infection are established to lay a good foundation for the research on the pathogenesis and treatment of HBV. In this review, we summarize culture models for a single type of cells, co-culture models for multiple types of cells, and other animal models, which are mainly for HBV transfection and infection. We also discuss the methods of cell model construction for HBV infection and their virological characteristics. It provides reliable evidence of models for scientific interpretation of advantages of traditional Chinese medicine in the prevention and treatment of chronic hepatitis B

An Implicit Difference Scheme for the Fourth-Order Nonlinear Evolution Equation with Multi-Term Riemann–Liouvile Fractional Integral Kernels

In this paper, an implicit difference scheme is proposed and analyzed for a class of nonlinear fourth-order equations with the multi-term Riemann–Liouvile (R–L) fractional integral kernels. For the nonlinear convection term, we handle implicitly and attain a system of nonlinear algebraic equations by using the Galerkin method based on piecewise linear test functions. The Riemann–Liouvile fractional integral terms are treated by convolution quadrature. In order to obtain a fully discrete method, the standard central difference approximation is used to discretize the spatial derivative. The stability and convergence are rigorously proved by the discrete energy method. In addition, the existence and uniqueness of numerical solutions for nonlinear systems are proved strictly. Additionally, we introduce and compare the Besse relaxation algorithm, the Newton iterative method, and the linearized iterative algorithm for solving the nonlinear systems. Numerical results confirm the theoretical analysis and show the effectiveness of the method

Study on the mechanism of soy protein isolate to improve quality of reduced-salt Hypophthalmichthys molitrix surimi gel: Focus on gel quality, protein structure, and in vitro digestibility

Excessive intake of sodium chloride may bring a series of diseases; as a result, reduced-salt surimi gels have gained growing popularity for sodium reduction. This paper studied soy protein isolate (SPI, 2.0%, 4.0%, and 6.0%, w/w) as a gel enhancer for reduced-salt silver carp surimi. Compared with the control (2.0% NaCl), the addition of SPI significantly increased (P < 0.05) the total SH content, hydrophobic interaction force, disulfide bond, hardness, gel strength, and water-holding capacity of the gels. During the thermal denaturation process, SPI and myofibrillar protein jointly participated in the formation of the gel network, resulting in a G′ value increase at 90 °C, forming a denser/more stable gel network structure. In vitro pepsin digestion results showed the digestibility of the reduced-salt gel with SPI was higher than that of the control. Therefore, appropriate SPI addition can improve the gel performance of reduced-salt surimi gel without affecting digestion and absorption