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Beijing, China
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Tan Y.,Chinese Academy of Sciences | Jia D.,Science Press | Lin Z.,Shanghai University | Guo B.,Hong Kong Baptist University | And 12 more authors.
International Journal of Molecular Sciences | Year: 2016

Determining sensitive biomarkers in the peripheral blood to identify interstitial lung abnormalities (ILAs) is essential for the simple early diagnosis of ILAs. This study aimed to determine serum metabolic biomarkers of ILAs and the corresponding pathogenesis. Three groups of subjects undergoing health screening, including healthy subjects, subjects with ILAs, and subjects who were healthy initially and with ILAs one year later (Healthy→ILAs), were recruited for this study. The metabolic profiles of all of the subjects’ serum were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry. The metabolic characteristics of the ILAs subjects were discovered, and the corresponding biomarkers were predicted. The metabolomic data from the Healthy→ILAs subjects were collected for further verification. The results indicated that five serum metabolite alterations (up-regulated phosphatidylcholine, phosphatidic acid, betaine aldehyde and phosphatidylethanolamine, as well as down-regulated 1-acylglycerophosphocholine) were sensitive and reliable biomarkers for identifying ILAs. Perturbation of the corresponding biological pathways (RhoA signaling, mTOR/P70S6K signaling and phospholipase C signaling) might be at least partially responsible for the pathogenesis of ILAs. This study may provide a good template for determining the early diagnostic markers of subclinical disease status and for obtaining a better understanding of their pathogenesis. © 2016 by the authors; licensee MDPI, Basel, Switzerland.


Wang P.,Peking University | Wang P.,CAS Guangzhou Institute of Geochemistry | Wang Y.,Science Press | Yang Y.-F.,Chengdu Center
Ore Geology Reviews | Year: 2016

The Tangjiaping Mo deposit is located in the Dabie Shan in eastern China. Molybdenum (Mo) mineralization mainly occurs as veinlets in the Tangjiaping granite porphyry, which is featured by the development of potassic-silicic-, phyllic- and propylitic alterations. The Mo-mineralized granite porphyry yields a zircon UPb age of 118.1±0.8Ma (MSWD=1.6, 2σ, n=24), and may have formed under post-collision extensional tectonics after the Yangtze-North China collision. The Tangjiaping granite porphyry is characterized by the enrichments of LILEs and LREEs, depletions of Ba, Nb, Ta, Sr, P, Ti and HREEs, and negative Eu anomaly. Zircons from the granite porphyry yield negative εHf(t) of -15.3 to -9.9, with TDM2(Hf) ages of 1.80 to 2.14Ga. The 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb of the granite porphyry and its K-feldspar are 16.842-17.342, 15.388-15.439 and 37.706-38.260, respectively, while those of the sulfides are 17.090-17.832, 15.420-15.510, and 37.550-38.026, respectively. The δ34S of these sulfides exhibit a relatively narrow range of 3.2-4.9‰, with an average of 4.0‰. The HfPbS isotopic signatures indicate that the granite porphyry and the ore-forming materials at Tangjiaping were mainly derived from the partial melting of both the Southern Dabie Complex and the Precambrian basement of the North China Craton. © 2016 Elsevier B.V.


PubMed | Chinese Academy of Sciences, Hong Kong Baptist University, Science Press, Chinese Institute of Clinical Medicine and Shanghai University
Type: Journal Article | Journal: International journal of molecular sciences | Year: 2016

Determining sensitive biomarkers in the peripheral blood to identify interstitial lung abnormalities (ILAs) is essential for the simple early diagnosis of ILAs. This study aimed to determine serum metabolic biomarkers of ILAs and the corresponding pathogenesis. Three groups of subjects undergoing health screening, including healthy subjects, subjects with ILAs, and subjects who were healthy initially and with ILAs one year later (HealthyILAs), were recruited for this study. The metabolic profiles of all of the subjects serum were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry. The metabolic characteristics of the ILAs subjects were discovered, and the corresponding biomarkers were predicted. The metabolomic data from the HealthyILAs subjects were collected for further verification. The results indicated that five serum metabolite alterations (up-regulated phosphatidylcholine, phosphatidic acid, betaine aldehyde and phosphatidylethanolamine, as well as down-regulated 1-acylglycerophosphocholine) were sensitive and reliable biomarkers for identifying ILAs. Perturbation of the corresponding biological pathways (RhoA signaling, mTOR/P70S6K signaling and phospholipase C signaling) might be at least partially responsible for the pathogenesis of ILAs. This study may provide a good template for determining the early diagnostic markers of subclinical disease status and for obtaining a better understanding of their pathogenesis.


News Article | February 15, 2017
Site: www.eurekalert.org

The American Association for the Advancement of Science (AAAS) and the Bill & Melinda Gates Foundation have formed a partnership to advance scientific communication and open access publishing. The partnership will also ensure open access to research funded by the Gates Foundation and published in the Science family of journals. This collaboration is a natural extension of AAAS' mission. AAAS seeks to advance science, engineering and innovation throughout the world for the benefit of all people. As part of fulfilling that mission, the Association works to enhance communication among scientists, engineers and the public, and fosters education in science and technology for everyone. AAAS has supported green OA for more than a decade and has offered gold open access options via the Science Advances journal since 2015. As a result of this partnership, AAAS will allow authors funded by the Gates Foundation to publish their research under a Creative Commons Attribution license (CC BY) in Science, Science Translational Medicine, Science Signaling, Science Advances, Science Immunology or Science Robotics. This means that the final published version of any article from a Foundation-funded author submitted to one of the AAAS journals after January 1, 2017, will be immediately available to read, download and reuse. The Gates Foundation seeks to ensure that all of the research it funds is published on full open access terms - be it in Science or any of the other 24,000 journals now offering similar options. Effective in 2017, support for open access publishing is built into every grant made by the Gates Foundation across program areas. The foundation has also invested in a new publishing service, Chronos, which easily connects grantees with journals offering open access options. This collaboration will provide an opportunity for AAAS and the Gates Foundation to explore opportunities to broaden access to scientific research and to advance scientific collaboration and communication. The two organizations are in discussion about potential activities such as webinars, initiatives to engage younger researchers and women, and outreach to researchers in developing countries. The partnership agreement has been established for calendar year 2017 and a renewal option will be evaluated in late 2017. A public report on the results of the partnership will be released in 2018. In a joint statement about the partnership, Bill Moran, Science Publisher, and Leigh Morgan, Chief Operating Officer at the Bill and Melinda Gates Foundation, said: "The robust exchange of scientific information will play a crucial role in solving the big challenges of the 21st century, from the spread of infectious disease to climate shocks and food security. All of us involved - producers of scientific knowledge as well as funders, publishers and researchers - have a stake in ensuring the continued integrity of global scientific exchange." For more information about the partnership, see our Frequently Asked Questions or contact Meagan Phelan, Science Press Package Executive Director, at mphelan@aaas.org. Media inquiries for the Gates Foundation can be directed to media@gatesfoundation.org.


Zhou G.,Hunan Normal University | He Y.,Hunan Normal University | Tang C.,Hunan Normal University | Yu T.,Science Press | And 2 more authors.
Journal of Geographical Sciences | Year: 2013

This paper provides a detailed analysis of the factors influencing the evolution of rural settlements, including natural environmental constraints, infrastructure, regional cultural inheritance and integration, urbanization and rural industrial transformation, land use reformation and innovation, rural household behavior conversion, macro-control policy factors, and so on. Based on differences between the ways and degree of effect on rural settlement evolution, these factors are classified into basic factors, new-type factors and mutation factors. The drive of basic factors mainly focuses on the traditional inheritance of rural settlements, the new-type factors mainly affect rural settlement transition, and the mutation factors may bring about sudden changes. All these factors constitute a "three-wheel" driving mechanism for the evolution of rural settlements, and shape three typical driver paths: slow smooth path under the basic factors, new path to rapid development under the new-type factors, and the sudden change path under the mutation factors. The paper also investigates the overall situation of rural settlement evolution in the aspects of settlement system, settlement scale, settlement morphology, settlement function, settlement culture, settlement environment, etc. The general process of rural settlement evolution is divided into four stages: initial, transitional, developmental, and mature stages. © 2013 Science Press and Springer-Verlag Berlin Heidelberg.


Zhou G.,Hunan Normal University | He Y.,Hunan Normal University | Tang C.,Hunan Normal University | Yu T.,Science Press | Xiao G.,Hunan Normal University
Acta Geographica Sinica | Year: 2011

This paper makes a deep analysis of the influencing factors in rural settlements evolution, including natural environment constraints, infrastructure, regional cultural inheritance and integration, urbanization and rural industry transformation, land use reformation and innovation, rural household behavior conversion, macro-control policy factors, and so on. Based on the differences between their effective way and degree to rural settlements evolution, these factors are classified into base factors, new-type factors and mutation factors. The driving of base factors is mainly focused on traditional inheritance of rural settlements, the new-type factors mainly have effect on rural settlements transition, and the mutation factors may bring about sudden change. All these factors constitute "three-wheel" driving mechanism of rural settlements evolution, and shape three typical driver paths, which are slow smooth path under the base factors, new path to rapid development under the new-type factors, sudden change path under the mutation factors. The paper also investigates the overall situation of rural settlements evolution in the aspects of the settlement system, settlements scale, settlements morphology, settlements function, settlements culture, settlements environment, and so on. And the general process of rural settlements evolution is divided into four stages, i.e., initial stage, transitional stage, development stage and mature stage.


Wang S.,Shanxi University | Wang S.,Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education | Li D.,Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education | Li D.,Shanxi University | And 3 more authors.
Expert Systems with Applications | Year: 2011

Owing to its openness, virtualization and sharing criterion, the Internet has been rapidly becoming a platform for people to express their opinion, attitude, feeling and emotion. As the subjectivity texts are often too many for people to go through, how to automatically classify them into different sentiment orientation categories (e.g. positive/negative) has become an important research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for subjectivity text sentiment classification. In order to validate the proposed method, we compared it with the method based on Information Gain while Support Vector Machine is adopted as the classifier. Two experiments are conducted by combining different feature selection methods with two kinds of candidate feature sets. Under 2739 subjectivity documents of COAE2008s and 1006 car-related subjectivity documents, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance respectively with accuracy 86.61% and 82.80% under two corpus while the candidate features are the words which appear in both positive and negative texts. © 2011 Elsevier Ltd. All rights reserved.


Wang S.,Shanxi University | Li D.,Shanxi University | Wei Y.,Science Press
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2011

Facing with promptly increasing reviews on the Web, it has been great challenge for information science and technology that how people effectively organize and process document data hiding large amounts of information to meet with particular needs. Text sentiment classification aims at developing some new theories and methods to automatically explore the sentiment orientation of a text by mining and analyzing subjective information in texts such as standpoint, view, attitude, mood, and so on. A method of text sentiment classification based on weighted rough membership is proposed in this paper. In the method, the model of text expression is established based on two-tuples attribute (feature, feature orientation intensity), by introducing feature orientation intensity into the method of vector space representation. An attribute discretization method is proposed based on the sentiment orientation sequence for feature selection unifying the discretization processing to depress data dimension. To utilize the feature orientation intensity, a weighted rough membership is defined for classifying new sentiment text. Compared with SVM classifier, on the reality car review corpus, the proposed method based on rough membership for text sentiment classification has the best performance after data being compressed in a certainty extent for text sentiment classification.

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