In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

Complex Networks Approach for Analyzing the Correlation of Traditional Chinese Medicine Syndrome Evolvement and Cardiovascular Events in Patients with Stable Coronary Heart Disease

This is a multicenter prospective cohort study to analyze the correlation of traditional Chinese medicine (TCM) syndrome evolvement and cardiovascular events in patients with stable coronary heart disease (CHD). The impact of syndrome evolvement on cardiovascular events during the 6-month and 12-month follow-up was analyzed using complex networks approach. Results of verification using Chi-square test showed that the occurrence of cardiovascular events was positively correlated with syndrome evolvement when it evolved from toxic syndrome to Qi deficiency, blood stasis, or sustained toxic syndrome, when it evolved from Qi deficiency to blood stasis, toxic syndrome, or sustained Qi deficiency, and when it evolved from blood stasis to Qi deficiency. Blood stasis, Qi deficiency, and toxic syndrome are important syndrome factors for stable CHD. There are positive correlations between cardiovascular events and syndrome evolution from toxic syndrome to Qi deficiency or blood stasis, from Qi deficiency to blood stasis, or toxic syndrome and from blood stasis to Qi deficiency. These results indicate that stable CHD patients with pathogenesis of toxin consuming Qi, toxin leading to blood stasis, and mutual transformation of Qi deficiency and blood stasis are prone to recurrent cardiovascular events

Treating Chronic Wounds Using Photoactive Metabolites: Data Mining the Chinese Pharmacopoeia for Potential Lead Species (#)

Efficient wound treatment that addresses associated infections and inflammation remains one of the big unmet needs, especially in low- and middle-income countries. One strategy for securing better healthcare can be using medicinal plants if sufficient evidence on their safety and therapeutic benefits can be ascertained. A unique novel opportunity could be photo-enhanced wound treatment with a combination of light-sensitive plant preparations and local exposure to daylight. Data mining strategies using existing resources offer an excellent basis for developing such an approach with many potential plant candidates. In the present analysis, we researched the 535 botanical drugs included in the Chinese pharmacopeia and identified 183 medicinal plant species, 82 for treating open wounds caused by trauma and 101 for inflammatory skin conditions. After further screening for reports on the presence of known photoactive compounds, we determined a core group of 10 scientifically lesser-known botanical species that may potentially be developed into more widely used topical preparations for photodynamic treatment of infected wounds. Our predictive approach may contribute to developing a more evidence-based use of herbal medicines

A Computational Drug-Target Network for Yuanhu Zhitong Prescription

Yuanhu Zhitong prescription (YZP) is a typical and relatively simple traditional Chinese medicine (TCM), widely used in the clinical treatment of headache, gastralgia, and dysmenorrhea. However, the underlying molecular mechanism of action of YZP is not clear. In this study, based on the previous chemical and metabolite analysis, a complex approach including the prediction of the structure of metabolite, high-throughput in silico screening, and network reconstruction and analysis was developed to obtain a computational drug-target network for YZP. This was followed by a functional and pathway analysis by ClueGO to determine some of the pharmacologic activities. Further, two new pharmacologic actions, antidepressant and antianxiety, of YZP were validated by animal experiments using zebrafish and mice models. The forced swimming test and the tail suspension test demonstrated that YZP at the doses of 4 mg/kg and 8 mg/kg had better antidepressive activity when compared with the control group. The anxiolytic activity experiment showed that YZP at the doses of 100 mg/L, 150 mg/L, and 200 mg/L had significant decrease in diving compared to controls. These results not only shed light on the better understanding of the molecular mechanisms of YZP for curing diseases, but also provide some evidence for exploring the classic TCM formulas for new clinical application

Economic-Social Interaction in China

This paper analyzes economic-social interaction in China in connection with the country’s change of economic system. I define an economic system in terms of a multidimensional vector of broad institutional characteristics, and I emphasize that important features of the social development are closely related to specific changes in these various dimensions. I classify China’s options for future social improvements into three broad categories: policies that improve the stability and distribution of factor income; government-created wedges between factor income and disposable income; and improvements in the quantity, quality and distribution of human services, such as education and health care.China, economic transition, typology of economic systems, social reforms

Sentiment analysis applied to tourism: exploring the tourist generated content in the case of a wellness tourism destination

Sentiment analysis applied to tourist-generated content through social media is one of the many sources of information for travellers in the case of a wellness tourism destination. The objectives of exploring tourist-generated content are to analyse the sentiments expressed on social media, in this research about wellness tourism destinations, based on destination reviews, and to identify the motivations that lead tourists to look for this kind of services in the Algarve destination The analysis of the hotel reviews exposes the tourist's opinion of the wellness destination and the grading of the infrastructural facilities and the acclaimed services in the categories of the tourist wellness destination. In attaining the objectives, quantitative approach methods were used to review 1,294 comments manually extracted from TripAdvisor and apply text mining algorithms to assess the sentiment expressed in the comments. The result shows that the three key extracted words frequently used by all categories of the component in the Algarve wellness destination are “bird”, “day”, “experience”, “Faro”, “fish”, “great”, “horse”, “love”, “market”, “massage”, “nice”, “old”, “park”, “Pinetree”, “place”, “relax”, “ride”, “spa”, “time”, “town”, “visit” and “walk”, also revealed some categories of a hotel into the services of spas and massage in the tourist wellness destination mainly satisfy the desire of the tourist. Exploring generated content with sentiment analysis helped to stimulate opinion on destinations with wellness facilities, revealing how the wellness of individuals at tourism destinations are generally satisfied based on keywords that illustrated opinions, shows diverse opinion, which shows that expectations are being met from the comments in TripAdvisor. It also widens the destination management organisation's (DMO) knowledge of the sustainability of destination infrastructures due to tourist views and opinions on destinations. However, generated review content which may be changed due to implicit factors, sometimes gives a psychological time frame view of the individual reviewer.A análise de sentimentos efetuada aos conteúdos gerados pelo turista nas redes sociais é uma das muitas fontes de informação consultadas pelos viajantes, permite visualizar os testemunhos de outros turistas que já visitaram os mesmos destinos. Através de avaliações efetuadas nas plataformas de social mídia, sobre infraestruturas existentes nos destinos turísticos, como no caso de um destino de saúde e bem-estar, permite estudar os principais motivos pelos quais estas regiões suscitam um sentimento mais positivo que outros, associado à experiência turística, com ou sem valor acrescentado pelos gestores do destino. A diversidade de opiniões, que por vezes é em função das expectativas que estão a ser satisfeitas, ou não, expressas através dos comentários gerados no TripAdvisor, podem contribuir para a sustentabilidade de infraestruturas de apoio ao turismo, que inclui, entre outras, instalações culturais tangíveis e intangíveis. Face ao exposto, os objetivos da presente dissertação são: (i) analisar o sentimento expresso nos conteúdos turísticos gerados pelos viajantes nas redes sociais sobre o destino turístico de saúde e bem-estar, (ii) avaliar o sentimento do turista sobre as componentes que caracterizam este tipo de destino e (iii) identificar as motivações que levam os viajantes a optar pelo Algarve, como um destino de turismo de saúde e bem-estar, que compreende dezasseis municípios com atrações e especificidades únicas. Para analisar o sentimento expresso nos comentários, foi necessário recorrer a uma metodologia própria de mineração de texto, cujo processo envolveu a recolha de dados, pré-processamento, extração de características, aplicação do algoritmo de análise de sentimento e por fim avaliação dos resultados. As avaliações foram extraídas manualmente e categorizadas em Número da Entidade (ID), Nome (Nome), Cidade onde está localizada (Cidade), País (País), Categoria (Categoria) Número de estrelas (Estrela) e número de avaliações (Número de avaliações). No conjunto de entidades foram considerados hotéis e infraestruturas selecionados pelas suas características: classificação e serviços turísticos adicionais prestados na área. De acordo com a revisão da literatura, as componentes consideradas e analisadas no que se refere a um destino de saúde e bem-estar foram dez, nomeadamente: Termas, Spas, Cuidados de corpo e mente, Turismo Médico, Ambiente Natural, Espiritualidade, Cultura, Enogastronomia, Desporto e Eventos. Neste contexto, foram identificados os hotéis e infraestruturas considerados como representativos de cada tipo de instalação que caracteriza este tipo de turismo e em seguida foram extraídos comentários do TripAdvisor. A seleção recaiu sobre as seguintes instalações: Caldas de Monchique (Monchique), Zensation - Body & Soul (Albufeira), Mercado de Loulé (Loulé), Moinhos Velhos Juice Detox & Yoga Retreat (Lagos), Old Town Faro (Faro), Pinetrees Horse Riding (Almancil), Ria Formosa Natural Park (Olhão), Swan Day Spa (Alvor) e Zoomarine Algarve (Albufeira). O pré-processamento envolveu a limpeza de elementos indesejados, transformação, tokenização, normalização e filtragem de texto. Na avaliação do resultado, a análise de sentimento foi também aplicada a duas dimensões (palavras extraídas e associadas em cada categoria), que foram comparadas com o comentário correspondente para determinar qual o sentimento associado a cada entidade considerada na investigação. Para atingir os objetivos, foram utilizados métodos de abordagem quantitativa para rever 1,294 comentários extraídos manualmente do TripAdvisor e nos quais foram aplicados algoritmos de mineração de texto para avaliar o sentimento expresso nos mesmos. O resultado destacou como as palavras-chave de comentários positivos: “bird”, “day”, “experience”, “Faro”, “fish”, “great”, “horse”, “love”, “market”, “massage”, “nice”, “old”, “park”, “Pinetree”, “place”, “relax”, “ride”, “spa”, “time”, “town”, “visit” e “walk”, Também, evidenciou que o sentimento associado a “spas”, “luxo”, “massage” e “sauna” obtiveram os valores mais elevados, no que se refere ao sentimento positivo. Os resultados expressaram de forma clara a aceitabilidade e popularidade perante os turistas, do Algarve como destino de saúde e bem-estar, onde se destacaram os termos “spas” e “cuidados de corpo e mente”, “ambiente natural” e “desporto” com desvio padrão de 0.4 e 0.3, com média de 4.7 par cada termo. Mostra que destinos de saúde e bem-estar com desporto (golfe), natureza e paisagem são características positivas neste tipo de destino. Além disso, as avaliações geradas durante os meses de inverno: janeiro, fevereiro, março, novembro e dezembro apresentaram valores mais altos. O estudo revelou, ainda, que algumas das categorias associadas ao destino de bem-estar turístico satisfazem o desejo do turista, principalmente, no que refere aos serviços de spas e massagem oferecidos pelos hotéis. A extração de comentários manualmente, apesar de ser uma limitação, concedeu ao investigador a possibilidade de confirmar questões relacionadas com a inclusão de taxas escondidas, com o tempo gasto no acesso à área de destino e às instalações turísticas, as atitudes do staff, prestação seletiva de serviços sem regras padrão, sem correlação entre o serviço anunciado e o prestado. A exploração de conteúdos gerados pelos turistas, em conjunto com análise de sentimentos, permitiu adquirir conhecimento sobre a perceção dos turistas sobre o destino, assim como revelou que o bem-estar dos mesmos nos destinos turísticos é geralmente satisfatório e expresso através de comentários diversos nas redes sociais que manifestam sentimentos, o que mostra que as expectativas foram satisfeitas. Para além disso, também permitem à organização de gestão de destinos (DMO) conhecer as potencialidades e desafios identificados pelos turistas. As categorias de instalações associadas a um destino de saúde e bem-estar, podem ajudar a melhorar a sua viabilidade económica através da gestão do sector turístico, contribuindo para o PIB, bem como permite identificar áreas que necessitam de especial atenção por parte dos governantes, como os eventos e o turismo médico. Contudo, o conteúdo gerado pelos turistas pode ser alterado devido a fatores implícitos, como a visão psicológica do estado do revisor individual ou o tempo que caracteriza o destino no momento. Assim, para futuros estudos, o processo de mineração de texto deverá ser efetuado de forma automática e em diversas fontes de informação, de modo que inclua mais instalações e constituído por mais comentários, especialmente no turismo médico que não foram analisados, uma vez que não existiam

An Effective Traditional Chinese Medicine Syndrome Model based on Proportional Odds Model and Similarity

This paper discusses proportional odds model and similarity on the construction of Traditional Chinese Medicine (TCM) chronic gastritis syndrome model. The syndromes explain the true relationships among a set of symptoms, which can be characterized by marginal probabilities and conditional probabilities. The former represents the distribution of levels of the syndrome across the symptoms. The latter describes the probabilities of an individual in a certain syndrome being at a particular level of the symptom, so it enables us to characterize the nature of the syndromes and the essence of the symptoms. A graph model for TCM syndromes gives intuitive mathematical insight into its use and computation. Similarity among syndromes explains that the model we construct is altogether fitting and proper

Traditional medicine-inspired approaches to drug discovery: can Ayurveda show the way forward?

Drug discovery strategies based on natural products and traditional medicines are re-emerging as attractive options. We suggest that drug discovery and development need not always be confined to new molecular entities. Rationally designed, carefully standardized, synergistic traditional herbal formulations and botanical drug products with robust scientific evidence can also be alternatives. A reverse pharmacology approach, inspired by traditional medicine and Ayurveda, can offer a smart strategy for new drug candidates to facilitate discovery process and also for the development of rational synergistic botanical formulations

Baicalin Downregulates RLRs Signaling Pathway to Control Influenza A Virus Infection and Improve the Prognosis

The objective of this study is to investigate the effects of baicalin on controlling the pulmonary infection and improving the prognosis in influenza A virus (IAV) infection. PCR and western blot were used to measure the changes of some key factors in RLRs signaling pathway. MSD electrochemiluminescence was used to measure the expression of pulmonary inflammatory cytokines including IFN-γ, TNF-α, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p70, and KC/GRO. Flow cytometry was used to detect the proportion of Th1, Th2, Th17, and Treg. The results showed that IAV infection led to low body weight and high viral load and high expression of RIG-I, IRF3, IRF7, and NF-κB mRNA, as well as RIG-I and NF-κB p65 protein. However, baicalin reduced the rate of body weight loss, inhibited virus replication, and downregulated the key factors of the RLRs signaling pathway. Besides, baicalin reduced the high expression inflammatory cytokines in lung and decreased the ratios of Th1/Th2 and Th17/Treg to arouse a brief but not overviolent inflammatory response. Therefore, baicalin activated a balanced host inflammatory response to limit immunopathologic injury, which was helpful to the improvement of clinical and survival outcomes