Shandong University
UniversityJinan, Shandong, China
Research output, citation impact, and the most-cited recent papers from Shandong University (China). Aggregated across the NobleBlocks index of 300M+ scholarly works.
Top-cited papers from Shandong University
BACKGROUND: Antiplatelet agents are the mainstay for secondary prevention of non-cardioembolic stroke. This systematic review examined the safety and efficacy of short-, middle-, and long-term aspirin in combination with clopidogrel as secondary prevention of stroke or transient ischemic attack (TIA) of presumed arterial origin. METHODS: PubMed, EmBase, and CENTRAL were searched up to May 2014. Randomized controlled trials (RCTs) that compared aspirin plus clopidogrel versus aspirin or clopidogrel as secondary prevention of stroke or TIA of arterial origin were included. The analyses were stratified into short-term (≤3 months), middle-term (>3 months and <1 year), and long-term (≥1 year). Outcomes were compared using risk ratio (RR) and 95% confidence interval (95% CI). RESULTS: Eight RCTs (20,728 patients) were included in the overall analysis. Compared with aspirin or clopidogrel alone, the complete analysis of all the data indicated that the combination therapy significantly reduced the risk of stroke recurrence (RR, 0.82; 95% CI 0.70-0.96, p = 0.01) and major vascular events (RR, 0.84; 95% CI 0.73-0.96, p < 0.01). But the risk of hemorrhagic stroke (RR, 1.59; 95% CI 1.08-2.33, p = 0.02) and major bleeding (RR, 1.83; 95% CI 1.37-2.45, p < 0.01) was increased. No RCT studied middle-term combination therapy. The analyses were therefore stratified into only two subgroups, short- and long-term treatment. Stratified analysis of short-term treatment showed that relative to monotherapy, the drug combination reduced the risk of stroke recurrence (RR, 0.69; 95% CI 0.59-0.81, p < 0.01) and did not increase the risk of hemorrhagic stroke (RR, 1.23; 95% CI 0.50-3.04, p = 0.65) and major bleeding events (RR, 2.17; 95% CI 0.18-25.71, p = 0.54). Short-term combination therapy was associated with a significantly lower risk of major vascular events (RR, 0.70; 95% CI 0.69 to 0.82, p < 0.01). Stratified analysis of long-term treatment revealed that the combination treatment did not decrease the risk of stroke recurrence (RR, 0.92; 95% CI 0.83-1.03, p = 0.15), but was associated with a significantly higher risk of hemorrhagic stroke (RR, 1.67; 95% CI 1.10-2.56, p = 0.02) and major bleeding events (RR, 1.90; 95% CI 1.46-2.48, p < 0.01). Long-term combination therapy failed to reduce the risk of major vascular events (RR, 0.92; 95% CI 0.84-1.03, p = 0.09). CONCLUSIONS: Compared with monotherapy, short-term aspirin in combination with clopidogrel is more effective as secondary prevention of stroke or TIA without increasing the risk of hemorrhagic stroke and major bleeding events. Long-term combination therapy does not reduce the risk of stroke recurrence, and is associated with increased major bleeding events. The clinical applicability of the findings of this systematic review, however, needs to be confirmed in future clinical trials.
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation --- collaborative filtering --- on the basis of implicit feedback.
AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425, \nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981, \nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826, \nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376, \nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294, \nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198, \nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544, \nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107, \nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756, \nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6, \nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58, \nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007, \nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591, \nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930, \nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794, \nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727, \nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986, \nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409, \nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368, \nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884, \nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239, \nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997, \nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798, \nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909, \nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336, \nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419, \nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490, \nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401, \nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880, \nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913, \nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381, \nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112, \nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812, \nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287, \nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308, \nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901, \nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141, \nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374, \nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822, \nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480, \nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171, \nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789, \nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217, \nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24, \nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700, \nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983, \nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002, \nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318, \nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462, \nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884, \nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996, \nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628, \nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003, \nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434, \nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783, \nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514, \nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172, \nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113, \nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135, \nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702, \nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703, \nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308, \nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290, \nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105, \nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563, \nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936, \nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657, \nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254, \nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694, \nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781, \nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533, \nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829, \nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395, \nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566, \nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767, \nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301, \nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919, \nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576, \nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572, \nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940, \nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340, \nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254, \nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604, \nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182, \nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775, \nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,
In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
Author(s): Collaboration, The ATLAS; Aad, G; Abat, E; Abdallah, J; Abdelalim, AA; Abdesselam, A; Abdinov, O; Abi, BA; Abolins, M; Abramowicz, H; Acerbi, E; Acharya, BS; Achenbach, R; Ackers, M; Adams, DL; Adamyan, F; Addy, TN; Aderholz, M; Adorisio, C; Adragna, P; Aharrouche, M; Ahlen, SP; Ahles, F; Ahmad, A; Ahmed, H; Aielli, G; Åkesson, PF; Åkesson, TPA; Akimov, AV; Alam, SM; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, IN; Aleppo, M; Alessandria, F; Alexa, C; Alexander, G; Alexopoulos, T; Alimonti, G; Aliyev, M; Allport, PP; Allwood-Spiers, SE; Aloisio, A; Alonso, J; Alves, R; Alviggi, MG; Amako, K; Amaral, P; Amaral, SP; Ambrosini, G; Ambrosio, G; Amelung, C; Ammosov, VV; Amorim, A; Amram, N; Anastopoulos, C; Anderson, B; Anderson, KJ; Anderssen, EC; Andreazza, A; Andrei, V; Andricek, L; Andrieux, M-L; Anduaga, XS; Anghinolfi, F; Antonaki, A; Antonelli, M; Antonelli, S; Apsimon, R; Arabidze, G; Aracena, I; Arai, Y; Arce, ATH; Archambault, JP; Arguin, J-F; Arik, E; Arik, M; Arms, KE; Armstrong, SR; Arnaud, M; Arnault, C; Artamonov, A; Asai, S; Ask, S
Conductometric semiconducting metal oxide gas sensors have been widely used and investigated in the detection of gases. Investigations have indicated that the gas sensing process is strongly related to surface reactions, so one of the important parameters of gas sensors, the sensitivity of the metal oxide based materials, will change with the factors influencing the surface reactions, such as chemical components, surface-modification and microstructures of sensing layers, temperature and humidity. In this brief review, attention will be focused on changes of sensitivity of conductometric semiconducting metal oxide gas sensors due to the five factors mentioned above.
autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
Water electrolysis is considered as the most promising technology for hydrogen production. Much research has been devoted to developing efficient electrocatalysts for hydrogen production via the hydrogen evolution reaction (HER) and oxygen production via the oxygen evolution reaction (OER). The optimum electrocatalysts can drive down the energy costs needed for water splitting via lowering the overpotential. A number of cobalt (Co)-based materials have been developed over past years as non-noble-metal heterogeneous electrocatalysts for HER and OER. Recent progress in this field is summarized here, especially highlighting several important bifunctional catalysts. Various approaches to improve or optimize the electrocatalysts are introduced. Finally, the current existing challenges and the future working directions for enhancing the performance of Co-implicated electrocatalysts are proposed.
We are concerned with different properties of backward stochastic differential equations and their applications to finance. These equations, first introduced by Pardoux and Peng (1990), are useful for the theory of contingent claim valuation, especially cases with constraints and for the theory of recursive utilities, introduced by Duffie and Epstein (1992a, 1992b).
Exosomes are 40-100 nm nano-sized vesicles that are released from many cell types into the extracellular space. Such vesicles are widely distributed in various body fluids. Recently, mRNAs and microRNAs (miRNAs) have been identified in exosomes, which can be taken up by neighboring or distant cells and subsequently modulate recipient cells. This suggests an active sorting mechanism of exosomal miRNAs, since the miRNA profiles of exosomes may differ from those of the parent cells. Exosomal miRNAs play an important role in disease progression, and can stimulate angiogenesis and facilitate metastasis in cancers. In this review, we will introduce the origin and the trafficking of exosomes between cells, display current research on the sorting mechanism of exosomal miRNAs, and briefly describe how exosomes and their miRNAs function in recipient cells. Finally, we will discuss the potential applications of these miRNA-containing vesicles in clinical settings.
The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also discussed.
The Daya Bay Reactor Neutrino Experiment has measured a nonzero value for the neutrino mixing angle ${\ensuremath{\theta}}_{13}$ with a significance of 5.2 standard deviations. Antineutrinos from six 2.9 $\mathrm{G}{\mathrm{W}}_{\mathrm{th}}$ reactors were detected in six antineutrino detectors deployed in two near (flux-weighted baseline 470 m and 576 m) and one far (1648 m) underground experimental halls. With a $43\text{ }000\text{ }\text{ }\mathrm{ton}--\mathrm{G}{\mathrm{W}}_{\mathrm{th}}--\mathrm{day}$ live-time exposure in 55 days, 10 416 (80 376) electron-antineutrino candidates were detected at the far hall (near halls). The ratio of the observed to expected number of antineutrinos at the far hall is $R=0.940\ifmmode\pm\else\textpm\fi{}\phantom{\rule{0ex}{0ex}}0.011(\mathrm{stat}.)\ifmmode\pm\else\textpm\fi{}0.004(\mathrm{syst}.)$. A rate-only analysis finds ${sin}^{2}2{\ensuremath{\theta}}_{13}=0.092\ifmmode\pm\else\textpm\fi{}0.016(\mathrm{stat}.)\ifmmode\pm\else\textpm\fi{}0.005(\mathrm{syst}.)$ in a three-neutrino framework.
Abstract The ever‐growing demands for electrical energy storage have stimulated the pursuit of alternative advanced batteries. Zn‐ion batteries (ZIBs) are receiving increased attentions due to the low cost, high safety, and high eco‐efficiency. However, it is still a big challenge to develop suitable cathode materials for intercalation of Zn ions. This review provides a timely access for researchers to the recent activities regarding ZIBs. First, cathode materials including various manganese oxides, vanadium compounds, and Prussian blue analogs are summarized with details in crystal structures and Zn ion storage mechanisms. Then, the electrolytes and their influences on the electrochemical processes are discussed. Finally, opinions on the current challenge of ZIBs and perspective to future research directions are provided.
Visual attention has been successfully applied in structural prediction tasks such as visual captioning and question answering. Existing visual attention models are generally spatial, i.e., the attention is modeled as spatial probabilities that re-weight the last conv-layer feature map of a CNN encoding an input image. However, we argue that such spatial attention does not necessarily conform to the attention mechanism - a dynamic feature extractor that combines contextual fixations over time, as CNN features are naturally spatial, channel-wise and multi-layer. In this paper, we introduce a novel convolutional neural network dubbed SCA-CNN that incorporates Spatial and Channel-wise Attentions in a CNN. In the task of image captioning, SCA-CNN dynamically modulates the sentence generation context in multi-layer feature maps, encoding where (i.e., attentive spatial locations at multiple layers) and what (i.e., attentive channels) the visual attention is. We evaluate the proposed SCA-CNN architecture on three benchmark image captioning datasets: Flickr8K, Flickr30K, and MSCOCO. It is consistently observed that SCA-CNN significantly outperforms state-of-the-art visual attention-based image captioning methods.
To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account. Traditional methods like factorization machine (FM) cast it as a supervised learning problem, which assumes each interaction as an independent instance with side information encoded. Due to the overlook of the relations among instances or items (e.g., the director of a movie is also an actor of another movie), these methods are insufficient to distill the collaborative signal from the collective behaviors of users. In this work, we investigate the utility of knowledge graph (KG), which breaks down the independent interaction assumption by linking items with their attributes. We argue that in such a hybrid structure of KG and user-item graph, high-order relations --- which connect two items with one or multiple linked attributes --- are an essential factor for successful recommendation. We propose a new method named Knowledge Graph Attention Network (KGAT) which explicitly models the high-order connectivities in KG in an end-to-end fashion. It recursively propagates the embeddings from a node's neighbors (which can be users, items, or attributes) to refine the node's embedding, and employs an attention mechanism to discriminate the importance of the neighbors. Our KGAT is conceptually advantageous to existing KG-based recommendation methods, which either exploit high-order relations by extracting paths or implicitly modeling them with regularization. Empirical results on three public benchmarks show that KGAT significantly outperforms state-of-the-art methods like Neural FM and RippleNet. Further studies verify the efficacy of embedding propagation for high-order relation modeling and the interpretability benefits brought by the attention mechanism. We release the codes and datasets at https://github.com/xiangwang1223/knowledge_graph_attention_network.
Transition metal carbides and nitrides (MXenes), a family of two-dimensional (2D) inorganic compounds, are materials composed of a few atomic layers of transition metal carbides, nitrides, or carbonitrides. Ti3C2, the first 2D layered MXene, was isolated in 2011. This material, which is a layered bulk material analogous to graphite, was derived from its 3D phase, Ti3AlC2 MAX. Since then, material scientists have either determined or predicted the stable phases of >200 different MXenes based on combinations of various transition metals such as Ti, Mo, V, Cr, and their alloys with C and N. Extensive experimental and theoretical studies have shown their exciting potential for energy conversion and electrochemical storage. To this end, we comprehensively summarize the current advances in MXene research. We begin by reviewing the structure types and morphologies and their fabrication routes. The review then discusses the mechanical, electrical, optical, and electrochemical properties of MXenes. The focus then turns to their exciting potential in energy storage and conversion. Energy storage applications include electrodes in rechargeable lithium- and sodium-ion batteries, lithium-sulfur batteries, and supercapacitors. In terms of energy conversion, photocatalytic fuel production, such as hydrogen evolution from water splitting, and carbon dioxide reduction are presented. The potential of MXenes for the photocatalytic degradation of organic pollutants in water, such as dye waste, is also addressed, along with their promise as catalysts for ammonium synthesis from nitrogen. Finally, their application potential is summarized.
Although the respiratory and immune systems are the major targets of Coronavirus Disease 2019 (COVID-19), acute kidney injury and proteinuria have also been observed. Currently, detailed pathologic examination of kidney damage in critically ill patients with COVID-19 has been lacking. To help define this we analyzed kidney abnormalities in 26 autopsies of patients with COVID-19 by light microscopy, ultrastructural observation and immunostaining. Patients were on average 69 years (19 male and 7 female) with respiratory failure associated with multiple organ dysfunction syndrome as the cause of death. Nine of the 26 showed clinical signs of kidney injury that included increased serum creatinine and/or new-onset proteinuria. By light microscopy, diffuse proximal tubule injury with the loss of brush border, non-isometric vacuolar degeneration, and even frank necrosis was observed. Occasional hemosiderin granules and pigmented casts were identified. There were prominent erythrocyte aggregates obstructing the lumen of capillaries without platelet or fibrinoid material. Evidence of vasculitis, interstitial inflammation or hemorrhage was absent. Electron microscopic examination showed clusters of coronavirus-like particles with distinctive spikes in the tubular epithelium and podocytes. Furthermore, the receptor of SARS-CoV-2, ACE2 was found to be upregulated in patients with COVID-19, and immunostaining with SARS-CoV nucleoprotein antibody was positive in tubules. In addition to the direct virulence of SARS-CoV-2, factors contributing to acute kidney injury included systemic hypoxia, abnormal coagulation, and possible drug or hyperventilation-relevant rhabdomyolysis. Thus, our studies provide direct evidence of the invasion of SARSCoV-2 into kidney tissue. These findings will greatly add to the current understanding of SARS-CoV-2 infection. Although the respiratory and immune systems are the major targets of Coronavirus Disease 2019 (COVID-19), acute kidney injury and proteinuria have also been observed. Currently, detailed pathologic examination of kidney damage in critically ill patients with COVID-19 has been lacking. To help define this we analyzed kidney abnormalities in 26 autopsies of patients with COVID-19 by light microscopy, ultrastructural observation and immunostaining. Patients were on average 69 years (19 male and 7 female) with respiratory failure associated with multiple organ dysfunction syndrome as the cause of death. Nine of the 26 showed clinical signs of kidney injury that included increased serum creatinine and/or new-onset proteinuria. By light microscopy, diffuse proximal tubule injury with the loss of brush border, non-isometric vacuolar degeneration, and even frank necrosis was observed. Occasional hemosiderin granules and pigmented casts were identified. There were prominent erythrocyte aggregates obstructing the lumen of capillaries without platelet or fibrinoid material. Evidence of vasculitis, interstitial inflammation or hemorrhage was absent. Electron microscopic examination showed clusters of coronavirus-like particles with distinctive spikes in the tubular epithelium and podocytes. Furthermore, the receptor of SARS-CoV-2, ACE2 was found to be upregulated in patients with COVID-19, and immunostaining with SARS-CoV nucleoprotein antibody was positive in tubules. In addition to the direct virulence of SARS-CoV-2, factors contributing to acute kidney injury included systemic hypoxia, abnormal coagulation, and possible drug or hyperventilation-relevant rhabdomyolysis. Thus, our studies provide direct evidence of the invasion of SARSCoV-2 into kidney tissue. These findings will greatly add to the current understanding of SARS-CoV-2 infection. Editor’s NoteThe Editors recommend that the readers also view the letter to the editor by Kissling et al. (see page 228) reporting a case of COVID-19–associated collapsing glomerulopathy featuring cytoplasmic vacuoles containing numerous spherical particles. The nature of those intracellular organelles as viral particles is questioned in 2 letters to the editor, Nadasdy et al. (see page 233) and Miller and Brealey (see page 231), that provide important information when examining viral-like electron microscopy structures in the kidney. The Editors recommend that the readers also view the letter to the editor by Kissling et al. (see page 228) reporting a case of COVID-19–associated collapsing glomerulopathy featuring cytoplasmic vacuoles containing numerous spherical particles. The nature of those intracellular organelles as viral particles is questioned in 2 letters to the editor, Nadasdy et al. (see page 233) and Miller and Brealey (see page 231), that provide important information when examining viral-like electron microscopy structures in the kidney. In December 2019, a cluster of patients with pneumonia of unknown etiology was reported in Wuhan, Hubei Province, China. On January 9, 2020, the Chinese Center for Disease Control and Prevention identified the causative agent as a novel coronavirus, which now is officially termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).1Lu R. Zhao X. Li J. et al.Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.Lancet. 2020; 395: 565-574Abstract Full Text Full Text PDF PubMed Scopus (7711) Google Scholar The illness caused by SARS-CoV-2, coronavirus disease 2019 (COVID-19), mainly manifests with fever, dry cough, dyspnea, myalgia, and diarrhea. However, COVID-19 presentations can range from asymptomatic infection, self-limited influenza-type symptoms, and acute pneumonia to severe respiratory failure with high mortality. Currently, the epidemic in China is being gradually controlled with major domestic efforts and international support. However, the global epidemic has now become a pandemic. Without knowing the detailed mechanisms of COVID-19, specific management is lacking. The reported mortality in different countries varies according to extent of testing performed, ranging from 0.3% to 10%. The respiratory, immune, and coagulation systems are the major targets of this pandemic disease.2Guan W.J. Ni Z.Y. Hu Y. et al.Clinical characteristics of coronavirus disease 2019 in China.N Engl J Med. 2020; 382: 1708-1720Crossref PubMed Scopus (19246) Google Scholar Kidney injury has appeared relatively less with COVID-19 than with Middle East respiratory syndrome or hantavirus infections, perhaps due to the different underlying mechanisms and ensuing pathologic manifestations. Clinically, the incidence of acute kidney injury (AKI) in COVID-19 varied from 0.9% to 29% in different centers. New onset proteinuria was also reported by several institutions.3Alsaad K.O. Hajeer A.H. Al Balwi M. et al.Histopathology of Middle East respiratory syndrome coronavirus (MERS-CoV) infection—clinicopathological and ultrastructural study.Histopathology. 2018; 72: 516-524Crossref PubMed Scopus (215) Google Scholar Currently, the pathologic investigation has primarily focused on respiratory, hematopoietic, and immune systems, whereas morphologic data of kidney injury are lacking. In this study, we report on our experience of kidney findings at autopsy in patients with severe COVID-19. The 26 patients with COVID-19 included 19 males and 7 females, with an average age of 69 years (range, 39–87 years). All 26 cases had positive results for SARS-CoV-2 by nucleic acid testing and characteristic radiologic alterations in lungs. Eleven patients had history of hypertension or diabetes or both. Data on angiotensin-converting enzyme (ACE) inhibitors or angiotensin-receptor blockers for hypertension or diabetes or both before the terminal hospitalization were not available. Patients were treated with calcium-channel blockers if needed for hypertension during the terminal hospitalization, without ACE inhibitors or angiotensin-receptor blockers or both, due to uncertainty regarding possible effects. Six patients had history of tumor. The clinical information is summarized in Tables 1 and 2.Table 1Clinical information of 26 patients with COVID-19IDSexAge (y)History of HT, DM, CKD or tumorHypotension/vasopressorBUN (mmol/l)Cr (μmol/l)UrineHb (g/l)WBC (g/l)LY (g/l)LY%PLT (T/l)D-dimer (μg/ml)ALT (U/l)AST (U/l)TBIL (μmol/l)CK (U/l)PROBLDWBC1M77NY22.52239.8N/AN/AN/AN/A25.10.371.5033>8.006071N/AN/A2F60NNN/AN/A−2+1+11217.870.824.601032.35N/AN/AN/AN/A3M51Pancreas CaY18.9671.3Trace−−9631.870.752.40385.61102126110.23284M87DM, HT, CKDY42.45229.8N/AN/AN/A7013.630.261.902191.0813169.5995M39Gastric CaN7.1831N/AN/AN/A9811.40.443.902736.1151823.9876M66Liver CaY41.84161.4N/AN/AN/A8912.520.241.90570.918415049.110017M77Skin CaY24.14460.2N/AN/AN/A9323.590.813.401055.32214813.63128F87DM, HT, CKDYN/AN/A3+3+1+1018.980.485.40110>8.00N/AN/AN/AN/A9M70Lung CaN12.86207.3N/AN/AN/A1125.760.8114.102152.8536784014.9245910F84HTN14.28114.7N/AN/AN/A607.690.536.80752.86293016.15411F83HTY21.54108N/AN/AN/A692.280.177.30302.087179546.549512M63HTY7.345.9−±−10241.480.531.301791.02107448.515813M52NY7.5158.72+−±7311.190.665.903422.69975218.919414M61HTY13.9994.21+1+±8015.670.644.10802.3887741.325915F70HT, Lung CaY5.7944.1N/AN/AN/A10218.891.216.40106>8.00543526.13716M64HTY20.42137.3N/AN/AN/A933.350.5616.80237.69213818.96417M66HTY3.2457.92+3+1+810.260.0829.90154.953491573.2N/A18F62NY11.8661.8N/AN/AN/A889.140.697.60763.42191814.22319M55DM, HTY9.2443.72+1+3+781.280.086.20182.05599119957.73420M83N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A21F86N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A22M78N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A23M62N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A24M51N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A25M72N/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/AN/A26M86HTY4.3663.61+−−9745.440.380.801553.77153524.5213ALT, alanine aminotransferase; AST, aspartate aminotransferase; BLD, blood; BUN, blood urea nitrogen; Ca, cancer; CK, creatine kinase; CKD, chronic kidney disease; Cr, creatinine; DM, diabetes; F, female; Hb, hemoglobin; HT, hypertension; ID, identification number; LY, lymphocytes; M, male; N, no; N/A, not available; PLT, platelet; PRO, proteinuria; TBIL, total bilirubin; WBC, white blood cell; Y, yes.The cause of death in all patients was respiratory failure. In addition, patients 1, 5, 14, 15, 16, 25, and 26 had multiorgan failure. Open table in a new tab Table 2Treatment historyIDExposure to nephrotoxic drugRenal replacement therapyAntiviralsSteroid1NNArbidolY2YCRRTArbidolY3NNRibavirinN4NNRibavirin, arbidolN5NNArbidolY6NNArbidolY7NCRRTArbidolY8NNArbidolN9NNNN10NCRRTArbidolY11NNArbidolY12NNArbidolY13YNLopinavir/ritonavirY14YNNY15NNLopinavir/ritonavirY16NNLopinavir/ritonavirY17YNNY18NCRRTNY19NCRRTLopinavir/ritonavirY20N/AN/AN/AN/A21N/AN/AN/AN/A22N/AN/AN/AN/A23N/AN/AN/AN/A24N/AN/AN/AN/A25N/AN/AN/AN/A26NNLopinavir/ritonavirYCRRT, continuous renal replacement therapy; ID, identification number; N, no; N/A, not available; Y, yes. Open table in a new tab ALT, alanine aminotransferase; AST, aspartate aminotransferase; BLD, blood; BUN, blood urea nitrogen; Ca, cancer; CK, creatine kinase; CKD, chronic kidney disease; Cr, creatinine; DM, diabetes; F, female; Hb, hemoglobin; HT, hypertension; ID, identification number; LY, lymphocytes; M, male; N, no; N/A, not available; PLT, platelet; PRO, proteinuria; TBIL, total bilirubin; WBC, white blood cell; Y, yes. The cause of death in all patients was respiratory failure. In addition, patients 1, 5, 14, 15, 16, 25, and 26 had multiorgan failure. CRRT, continuous renal replacement therapy; ID, identification number; N, no; N/A, not available; Y, yes. All tissue samples were well preserved without autolysis. There was prominent proximal acute tubule injury (ATI) manifested as the loss of brush border, vacuolar degeneration, dilatation of the tubular lumen with cellular debris, and occasionally even frank necrosis and detachment of epithelium with bare tubular basement membrane noted (the latter observed in 4 cases). The majority of the vacuoles in cytoplasm were variable in size; however, focal isometric fine vacuolization was uncommonly present and is associated with, for example, mannitol or i.v. Ig therapy (Figure 1a and b). In 2 patients, consistent with corresponding pathologic findings in their lungs, acute pyelonephritis was observed with multiple foci of bacteria and diffuse polymorphonuclear casts in the lumen of tubules. In 1 of these 2 patients, an arcuate artery was infiltrated with numerous inflammatory cells (Figure 1c and d), likely representing reaction to bacterial infection. Diffuse erythrocyte aggregation and obstruction were present in peritubular and glomerular capillary loops without distinct fragmentation of erythrocytes or platelets or fibrin thrombi. Occasional hemosiderin granules in tubular epithelium were identified in 4 patients with hematuria by dipstick (Figure 1e). In 3 cases, pigmented casts were found with high levels of creatine phosphokinase, possibly representing rhabdomyolysis (Figure 1f). Distal tubules and collecting ducts showed only occasional cellular swelling and edematous expansion of the interstitial space without significant inflammation. Lymphocytic infiltrates were present in areas of nonspecific fibrosis including subcapsular areas. Glomeruli showed varied degrees of underlying morphologic changes, such as nodular mesangial expanding and hyalinosis of arterioles, which constituted evidence of diabetic nephropathy in 2 of the patients with diabetes, and arteriosclerosis of medium-size arteries with ischemic glomeruli in 11 of the patients with hypertension. Focal obsolescent glomeruli were detected proportional to the age in this population. Endothelial cell swelling with variable foamy degeneration was present in 5 of the patients with COVID-19, and they were usually older and had hypertensive or diabetic histories. In 3 cases, a few areas of segmental fibrin thrombus in glomerular capillary loops were identified associated with severe injury of the endothelium (Figure 1g). Occasional podocyte vacuolation and even detachment from the glomerular basement membrane was noted. Focal segmental glomerulosclerosis was observed in 2 patients with overt proteinuria as well as history of diabetes. Ischemic changes with shrinkage of capillary loops with accumulation of plasma in Bowman’s space was present in 7 cases, occasionally with pseudocrescent appearance (Figure 1h). Crescents and hypercellular or inflammatory lesions of glomeruli were not present. The pathologic findings are summarized in Table 3.Table 3The pathologic abnormalities of kidney in 26 cases of deceased patients with COVID-19IDLMEMIFTubule interstitiumGlomeruliATIMultiple foci of bacteriaPigmented castsArteriosclerosisSegmental fibrin thrombusFSGSCoronavirus-like particlesDense depositsSubendothelial lucent expansionIgGIgASARS-CoV NP1SevereNNMild to moderateNNN/AN/AN/AN/AN/AN/A2ModerateNNMildNNYNNN/AN/AN/A3Mild to moderateNYMildNNYNYN/AN/AN/A4SevereNNSevereNYYNYN/AN/AN/A5MildNNMildNNN/AN/AN/AN/AN/AN/A6Mild to moderateNYMildNNN/AN/AN/AN/AN/AN/A7SevereNNMild to moderateNNN/AN/AN/AN/AN/AN/A8ModerateNNSevereFocalYN/AN/AN/AN/AN/AN/A9ModerateNYModerateNNN/AN/AN/AN/AN/AN/A10ModerateNNModerate to severeNNN/AN/AN/AN/AN/AN/A11Moderate to severeNNModerate to severeFocalNN/AN/AN/AN/AN/AN/A12Moderate to severeNNModerateNNYNYN/AN/AN/A13Mild to moderateNNMildNNN/AN/AN/AN/AN/AN/A14SevereMultiple focalNModerateDiffuseNN/AN/AN/AN/AN/AN/A15Mild to moderateNNModerate to severeNNN/AN/AN/AN/AN/AN/A16SevereMultiple focalNModerate to severeNNN/AN/AN/AN/AN/AN/A17ModerateNNModerateNNN/AN/AN/AN/AN/AN/A18ModerateNNMildNNN/AN/AN/AN/AN/AN/A19MildNNModerate to to to to to severeNNModerate to to acute tubular COVID-19, coronavirus disease electron focal segmental ID, identification number; light N, not N/A, not available; severe acute syndrome Y, Open table in a new tab acute tubular COVID-19, coronavirus disease electron focal segmental ID, identification number; light N, not N/A, not available; severe acute syndrome Y, particles were identified in the cytoplasm of renal proximal tubular epithelium as well as in the and less in tubules. The of particles varied from to with distinctive to in a of this coronavirus included membrane with to the viral and the of the particles (Figure In 1 and with segmental mesangial and increased were present (Figure and were noted in were These 2 patients not have evidence of bacterial at autopsy in or In 2 of 3 patients with diabetes, characteristic changes of diabetic nephropathy were present by electron microscopy including increased of the glomerular basement membrane without mesangial expansion and segmental and erythrocytes were observed obstructing peritubular capillary with of endothelium (Figure or fibrin were not detected in with this of erythrocytes in segmental glomerular capillary loops was without inflammation or In glomerular capillary a varied extent of injury was including lucent and without The ultrastructural findings are summarized in Table for inflammatory cells not specific accumulation of these with of and cells in areas of nonspecific with and present in the obstruction was of for showed in the significant platelet and for cells showed of peritubular capillary (Figure In an of a was and without COVID-19, for ACE of proximal tubules without glomerular was which is consistent with was observed in the kidney (Figure ACE2 was also in 5 of the patients ACE2 in 3 of these ACE2 was prominent in proximal tubular in areas with severe In addition, focal cells was as well as occasional podocyte (Figure or was from in cases, and nonspecific and were present. showed segmental capillary however, without the capillary with by case showed in mesangial as well as capillary associated with corresponding mesangial and by By an the of SARS-CoV nucleoprotein was analyzed in the cases, and 3 showed positive in a or cytoplasm in tubular epithelium (Figure and positive showed The immunostaining findings are summarized in Table In the present study, we report the kidney and immunostaining findings from autopsies of 26 patients from respiratory failure due to COVID-19. is the report of kidney pathologic presentations in patients with SARS-CoV-2 infection. autopsy the range of abnormalities present and the specific kidney cells likely with the and provide important information for studies in less ill patients with COVID-19 and kidney observed significant the of mainly by erythrocytes with ensuing as well as glomerular and changes of underlying diabetic or hypertensive of these findings are in with mechanisms for in kidney. also findings that distinct mechanisms of this novel coronavirus infection, direct kidney and likely Thus, these pathologic provide a for understanding of COVID-19. observed diffuse acute proximal tubular injury with loss of brush and which be caused by the direct virulence of SARS-CoV-2, by our ultrastructural and immunostaining The tubular cytoplasmic vacuoles were variable in However, in a few patients, focal isometric fine vacuolization was present and is likely to with or such as i.v. 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The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases.The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease.
BACKGROUND: China has a large population of older people, but has not yet undertaken a comprehensive study on the prevalence, risk factors, and management of both dementia and mild cognitive impairment (MCI). METHODS: For this national cross-sectional study, 46 011 adults aged 60 years or older were recruited between March 10, 2015, and Dec 26, 2018, using a multistage, stratified, cluster-sampling method, which considered geographical region, degree of urbanisation, economic development status, and sex and age distribution. 96 sites were randomly selected in 12 provinces and municipalities representative of all socioeconomic and geographical regions in China. Participants were interviewed to obtain data on sociodemographic characteristics, lifestyle, medical history, current medications, and family history, and then completed a neuropsychological testing battery administered by a psychological evaluator. The prevalence of dementia (Alzheimer's disease, vascular dementia, and other dementias) and MCI were calculated and the risk factors for different groups were examined using multivariable-adjusted analyses. FINDINGS: Overall age-adjusted and sex-adjusted prevalence was estimated to be 6·0% (95% CI 5·8-6·3) for dementia, 3·9% (3·8-4·1) for Alzheimer's disease, 1·6% (1·5-1·7) for vascular dementia, and 0·5% (0·5-0·6) for other dementias. We estimated that 15·07 million (95% CI 14·53-15·62) people aged 60 years or older in China have dementia: 9·83 million (9·39-10·29) with Alzheimer's disease, 3·92 million (3·64-4·22) with vascular dementia, and 1·32 million (1·16-1·50) with other dementias. Overall MCI prevalence was estimated to be 15·5% (15·2-15·9), representing 38·77 million (37·95-39·62) people in China. Dementia and MCI shared similar risk factors including old age (dementia: odds ratios ranging from 2·69 [95% CI 2·43-2·98] to 6·60 [5·24-8·32]; MCI: from 1·89 [1·77-2·00] to 4·70 [3·77-5·87]); female sex (dementia: 1·43 [1·31-1·56]; MCI: 1·51 [1·43-1·59]); parental history of dementia (dementia: 7·20 [5·68-9·12]; MCI: 1·91 [1·48-2·46]); rural residence (dementia: 1·16 [1·06-1·27]; MCI: 1·45 [1·38-1·54]); fewer years of education (dementia: from 1·17 [1·06-1·29] to 1·55 [1·38-1·73]; MCI: from 1·48 [1·39-1·58] to 3·48 [3·25-3·73]); being widowed, divorced, or living alone (dementia: from 2·59 [2·30-2·90] to 2·66 [2·29-3·10]; MCI: from 1·58 [1·44-1·73] to 1·74 [1·56-1·95]); smoking (dementia: 1·85 [1·67-2·04]; MCI: 1·27 [1·19-1·36]), hypertension (dementia: 1·86 [1·70-2·03]; MCI: 1·62 [1·54-1·71] for MCI), hyperlipidaemia (dementia: 1·87 [1·71-2·05]; MCI: 1·29 [1·21-1·37]), diabetes (dementia: 2·14 [1·96-2·34]; MCI: 1·44 [1·35-1·53]), heart disease (dementia: 1·98 [1·73-2·26]; MCI: 1·17 [1·06-1·30]), and cerebrovascular disease (dementia: 5·44 [4·95-5·97]; MCI: 1·49 [1·36-1·62]). Nine of these risk factors are modifiable. INTERPRETATION: Dementia and MCI are highly prevalent in China and share similar risk factors. A prevention strategy should be developed to target the identified risk factors in the MCI population to thwart or slow down disease progression. It is also crucial to optimise the management of dementia and MCI as an important part of China's public health system. FUNDING: Key Project of the National Natural Science Foundation of China, National Key Scientific Instrument and Equipment Development Project, Mission Program of Beijing Municipal Administration of Hospitals, Beijing Scholars Program, Beijing Brain Initiative from Beijing Municipal Science & Technology Commission, Project for Outstanding Doctor with Combined Ability of Western and Chinese Medicine, and Beijing Municipal Commission of Health and Family Planning.
Abstract Objective To assess the prevalence of diabetes and its risk factors. Design Population based, cross sectional study. Setting 31 provinces in mainland China with nationally representative cross sectional data from 2015 to 2017. Participants 75 880 participants aged 18 and older—a nationally representative sample of the mainland Chinese population. Main outcome measures Prevalence of diabetes among adults living in China, and the prevalence by sex, regions, and ethnic groups, estimated by the 2018 American Diabetes Association (ADA) and the World Health Organization diagnostic criteria. Demographic characteristics, lifestyle, and history of disease were recorded by participants on a questionnaire. Anthropometric and clinical assessments were made of serum concentrations of fasting plasma glucose (one measurement), two hour plasma glucose, and glycated haemoglobin (HbA 1c ). Results The weighted prevalence of total diabetes (n=9772), self-reported diabetes (n=4464), newly diagnosed diabetes (n=5308), and prediabetes (n=27 230) diagnosed by the ADA criteria were 12.8% (95% confidence interval 12.0% to 13.6%), 6.0% (5.4% to 6.7%), 6.8% (6.1% to 7.4%), and 35.2% (33.5% to 37.0%), respectively, among adults living in China. The weighted prevalence of total diabetes was higher among adults aged 50 and older and among men. The prevalence of total diabetes in 31 provinces ranged from 6.2% in Guizhou to 19.9% in Inner Mongolia. Han ethnicity had the highest prevalence of diabetes (12.8%) and Hui ethnicity had the lowest (6.3%) among five investigated ethnicities. The weighted prevalence of total diabetes (n=8385) using the WHO criteria was 11.2% (95% confidence interval 10.5% to 11.9%). Conclusion The prevalence of diabetes has increased slightly from 2007 to 2017 among adults living in China. The findings indicate that diabetes is an important public health problem in China.