Preventive treatment for diseases: A practice model. a challenge for hospital management in the field of integrative medicine

The concept of preventive treatment for diseases in the Chinese context originated in an ancient Chinese medical text called The Yellow Emperor's Inner Canon or The Inner Canon of Huangdi. This concept is that of taking treatment measures in order to prevent recurrence of diseases and consequent deterioration in health and well-being. There are three aspects of preventive treatment: 1) preventive measures before the onset of the illness; 2) measures taken against deterioration during the illness; and 3) measures taken against relapse after recovery.1 The authors introduced a Tradtional Chinese Medicine (TCM) model of preventive treatment for diseases into the clinical health care practice at Guangdong Women's and Children's Hospital (GDWCH). TCM principles and methodologies were applied along with modern medical practices of diagnosis and treatment. The study found that the new model of integrative medicine applied at GDWCH presented a wide range of possibilities for both social benefits and good medical prognosis

Solving kk-means on High-dimensional Big Data

In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement. For the $k$-means problem, this has led to the development of several $(1+\varepsilon)$-approximations (under the assumption that $k$ is a constant), but also to the design of algorithms that are extremely fast in practice and compute solutions of high accuracy. However, when not only the length of the stream is high but also the dimensionality of the input points, then current methods reach their limits. We propose two algorithms, piecy and piecy-mr that are based on the recently developed data stream algorithm BICO that can process high dimensional data in one pass and output a solution of high quality. While piecy is suited for high dimensional data with a medium number of points, piecy-mr is meant for high dimensional data that comes in a very long stream. We provide an extensive experimental study to evaluate piecy and piecy-mr that shows the strength of the new algorithms.Comment: 23 pages, 9 figures, published at the 14th International Symposium on Experimental Algorithms - SEA 201

Observer design for a class of nonlinear systems combining dissipativity with interconnection and damping assignment

A nonlinear observer design approach is proposed that exploits and combines port-Hamiltonian systems and dissipativity theory. First, a passivity-based observer design using interconnection and damping assignment for time variant state affine systems is presented by applying output injection to the system such that the observer error dynamics takes a port-Hamiltonian structure. The stability of the observer error system is assured by exploiting its passivity properties. Second, this setup is extended to develop an observer design approach for a class of systems with a time varying state affine forward and a nonlinear feedback contribution. For a class of nonlinear systems, the theory of dissipative observers is adapted and combined with the results for the passivity-based observer design using interconnection and damping assignment. The convergence of the compound observer design is determined by a linear matrix inequality. The performance of both observer approaches is analyzed in simulation examples

Effects of Edge Functional Groups on Water Transport in Graphene Oxide Membranes

Graphene oxide (GO) membranes assembled by GO nanosheets exhibit high water flux because of the unique water channels formed by their functionalized layer-by-layer structure. Although water transport in the GO membrane is in principle influenced by the functional groups at the edges of GO nanosheets, this is yet to be fully understood. To fill this knowledge gap, molecular dynamics simulation was employed in this work to gain insights into the influences of three typical edge functional groups of GO nanosheets: Carboxyl (COOH), hydroxyl (OH), and hydrogen (H). A well-controlled numerical analysis with complete isolation of the functional groups at the edges was undertaken. The results reveal that the COOH group has a negative impact on water transport because of its relatively large steric geometric structure, which resists water flow. By contrast, the OH group promotes water transport by uniquely "pulling" water molecules across the nanosheet layer because of its relatively stronger interaction with water. The H atom promotes water transport as well, mainly because of its low-resistance steric structure. Moreover, the size of the inter-edge hub has an apparent impact on the influence of these functional groups on water transport. The results suggest that in the design of high water flux GO membranes, it would be strategic to remove COOH edge functional groups while maintaining a mixture of OH and H edge functional groups

An Assessment Of Traditional Uighur Medicine In Current Xinjiang Region (China)

Background: The main objectives of this study were to assess the current research and development of traditional Uighur medicine in Xinjiang (China), and to evaluate the promising pharmacological products of traditional Uighur medicine for further studies.Materials and Methods: Traditional Uighur medicine data of medicine registry, patent, and academic publications was collected and analyzed.Results: Data showed that, among the registered and studied traditional Uighur medicine, the main therapeutic areas of traditional Uighur medicine focused on skin disease, urogenital disease, rheumatism and digestive system disease. The representative traditional Uighur patent medicine included the following: BaixuanXiatare Tablets, Kaliziran Tincture and Vernoniaanthelmintica Injection (Psoriasis and vitiligo); Xi-payimazibiziLiquid (prostatitis); KursiKaknaq (urinary tract infection); Tongzhisurunjiang Capsules (anti-rheumatism medicine); HuganBuzure Granules (digestive system disease). Moreover, ten Uighur herbs were widely used, including: ResinaScammoniae, Folium FumicisDentati, HerbaDracocephali, Semen AmygdaliDulcis, HerbaChamomillae, FructusPimpinellaeanisi, Cortex Foeniculi, FructusVernoniae, FructusApii, and Radix AnacycliPyrethri.Conclusion: This study concluded by indicating that traditional Uighur medicine with excellent curative effect should be screened in details for their phytochemical properties and pharmacological activity to discover new bioactive constituents.Key words: Traditional Uighur medicine, Traditional Uighur patent medicine, Uighur her

Fyn Kinase regulates GluN2B subunit-dominant NMDA receptors in human induced pluripotent stem cell-derived neurons

NMDA receptor (NMDAR)-mediated fast excitatory neurotransmission is implicated in a broad range of physiological and pathological processes in the mammalian central nervous system. The function and regulation of NMDARs have been extensively studied in neurons from rodents and other non-human species, and in recombinant expression systems. Here, we investigated human NMDARs in situ by using neurons produced by directed differentiation of human induced pluripotent stem cells (iPSCs). The resultant cells showed electrophysiological characteristics demonstrating that they are bona fide neurons. In particular, human iPSC-derived neurons expressed functional ligand-gated ion channels, including NMDARs, AMPA receptors, GABAA receptors, as well as glycine receptors. Pharmacological and electrophysiological properties of NMDAR-mediated currents indicated that these were dominated by receptors containing GluN2B subunits. The NMDAR currents were suppressed by genistein, a broad-spectrum tyrosine kinase inhibitor. The NMDAR currents were also inhibited by a Fyn-interfering peptide, Fyn(39-57), but not a Src-interfering peptide, Src(40-58). Together, these findings are the first evidence that tyrosine phosphorylation regulates the function of NMDARs in human iPSC-derived neurons. Our findings provide a basis for utilizing human iPSC-derived neurons in screening for drugs targeting NMDARs in neurological disorders

Increased expression of cyclooxygenase-2 in first-degree relatives of gastric cancer patients

Aim: To study the expression of cyclooxygenase-2 (COX-2) in human gastric cancer tissues and their paired adjacent mucosa, as well as mucosa from gastric antrum and corpus of the first-degree relatives of the recruited cancer patients. Methods: The expression of COX-2 mRNA in 38 patients with gastric cancer and their 29 first-degree relatives and 18 healthy controls was assessed by the real time RT-PCR. The expression of COX-2 protein was determined by Western blot. Results: A marked increase in COX-2 mRNA expression was found in 20 of 37 (54%) cancerous tissues compared to their respective paired normal mucosa (P<0.001). Interestingly, increased COX-2 mRNA expression was also found in mucosa of the corpus (6/29) and antrum (13/29) of their first-degree relatives. Increased COX-2 mRNA expression was more frequently observed in the antrum biopsies from cancer patients than in the antrum biopsies from healthy controls (P<0.05). In addition, 3 of 23 (13%) patients with atrophic mucosa and 6 of 35 (17%) patients with intestinal metaplasia showed increased COX-2 mRNA expression. Furthermore, COX-2 expression increased in H pylori-positive tissues, especially in antrum mucosa. Conclusion: Increased COX-2 expression is involved in gastric carcinogenesis, and may be necessary for maintenance of the malignant phenotype and contribute to Helicobacter pylori-associated malignant transformation. © 2005 The WJG Press and Elsevier Inc. All rights reserved.published_or_final_versio

Articulatory-feature based sequence kernel for high-level speaker verification

Research has shown that articulatory feature-based phonetic-class pronunciation models (AFCPMs) can capture the pronunciation characteristics of speakers. However, the scoring method used in AFCPMs does not explicitly use the discriminative information available in the training data. To harness this information, this paper proposes converting speaker models to supervectors by stacking the discrete densities in AFCPMs. An AF-kernel is constructed from the supervectors of target speakers, background speakers, and claimants. An AF-kernel based SVM is then trained to classify the super-vectors. Results show that AF-kernel scoring is complementary to likelihood-ratio scoring, leading to better performance when the two scoring methods are combined.Department of Electronic and Information EngineeringRefereed conference pape