Jikei University School of Medicine

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,

Rhinosinusitis is a significant and increasing health problem which results in a large financial burden on society. This evidence based position paper describes what is known about rhinosinusitis and nasal polyps, offers evidence based recommendations on diagnosis and treatment, and considers how we can make progress with research in this area. Rhinitis and sinusitis usually coexist and are concurrent in most individuals; thus, the correct terminology is now rhinosinusitis. Rhinosinusitis (including nasal polyps) is defined as inflammation of the nose and the paranasal sinuses characterised by two or more symptoms, one of which should be either nasal blockage/obstruction/congestion or nasal discharge (anterior/posterior nasal drip), +/- facial pain/pressure, +/- reduction or loss of smell; and either endoscopic signs of polyps and/or mucopurulent discharge primarily from middle meatus and/or; oedema/mucosal obstruction primarily in middle meatus, and/or CT changes showing mucosal changes within the ostiomeatal complex and/or sinuses. The paper gives different definitions for epidemiology, first line and second line treatment and for research. Furthermore the paper describes the anatomy and (patho)physiology, epidemiology and predisposing factors, inflammatory mechanisms, evidence based diagnosis, medical and surgical treatment in acute and chronic rhinosinusitis and nasal polyposis in adults and children. Evidence based schemes for diagnosis and treatment are given for the first and second line clinicians. Moreover attention is given to complications and socio-economic cost of chronic rhinosinusitis and nasal polyps. Last but not least the relation to the lower airways is discussed.

The International League Against Epilepsy (ILAE) presents a revised operational classification of seizure types. The purpose of such a revision is to recognize that some seizure types can have either a focal or generalized onset, to allow classification when the onset is unobserved, to include some missing seizure types, and to adopt more transparent names. Because current knowledge is insufficient to form a scientifically based classification, the 2017 Classification is operational (practical) and based on the 1981 Classification, extended in 2010. Changes include the following: (1) "partial" becomes "focal"; (2) awareness is used as a classifier of focal seizures; (3) the terms dyscognitive, simple partial, complex partial, psychic, and secondarily generalized are eliminated; (4) new focal seizure types include automatisms, behavior arrest, hyperkinetic, autonomic, cognitive, and emotional; (5) atonic, clonic, epileptic spasms, myoclonic, and tonic seizures can be of either focal or generalized onset; (6) focal to bilateral tonic-clonic seizure replaces secondarily generalized seizure; (7) new generalized seizure types are absence with eyelid myoclonia, myoclonic absence, myoclonic-atonic, myoclonic-tonic-clonic; and (8) seizures of unknown onset may have features that can still be classified. The new classification does not represent a fundamental change, but allows greater flexibility and transparency in naming seizure types.

Publicado também em: https://repositorio.unifesp.br/handle/11600/53933

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.

<b>Objectives</b>&nbsp;To assess the overall effect of vitamin D supplementation on risk of acute respiratory tract infection, and to identify factors modifying this effect. <b>Design</b>&nbsp;Systematic review and meta-analysis of individual participant data (IPD) from randomised controlled trials. <b>Data sources</b>&nbsp;Medline, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, ClinicalTrials.gov, and the International Standard Randomised Controlled Trials Number registry from inception to December 2015. <b>Eligibility criteria for study selection</b>&nbsp;Randomised, double blind, placebo controlled trials of supplementation with vitamin D₃ or vitamin D₂ of any duration were eligible for inclusion if they had been approved by a research ethics committee and if data on incidence of acute respiratory tract infection were collected prospectively and prespecified as an efficacy outcome. <b>Results</b>&nbsp;25 eligible randomised controlled trials (total 11 321 participants, aged 0 to 95 years) were identified. IPD were obtained for 10 933 (96.6%) participants. Vitamin D supplementation reduced the risk of acute respiratory tract infection among all participants (adjusted odds ratio 0.88, 95% confidence interval 0.81 to 0.96; P for heterogeneity &lt;0.001). In subgroup analysis, protective effects were seen in those receiving daily or weekly vitamin D without additional bolus doses (adjusted odds ratio 0.81, 0.72 to 0.91) but not in those receiving one or more bolus doses (adjusted odds ratio 0.97, 0.86 to 1.10; P for interaction=0.05). Among those receiving daily or weekly vitamin D, protective effects were stronger in those with baseline 25-hydroxyvitamin D levels &lt;25 nmol/L (adjusted odds ratio 0.30, 0.17 to 0.53) than in those with baseline 25-hydroxyvitamin D levels ≥25 nmol/L (adjusted odds ratio 0.75, 0.60 to 0.95; P for interaction=0.006). Vitamin D did not influence the proportion of participants experiencing at least one serious adverse event (adjusted odds ratio 0.98, 0.80 to 1.20, P=0.83). The body of evidence contributing to these analyses was assessed as being of high quality. <b>Conclusions</b>&nbsp;Vitamin D supplementation was safe and it protected against acute respiratory tract infection overall. Patients who were very vitamin D deficient and those not receiving bolus doses experienced the most benefit. <b>Systematic review registration</b>&nbsp;PROSPERO CRD42014013953.

The growing worldwide prevalence of type 2 diabetes mellitus in the young, as underlined by an earlier International Diabetes Federation (IDF) Consensus Statement 1, has highlighted a significant shortfall of data on the epidemiology of the disorder and the identification and treatment of children and adolescents at risk of progression to this disease. Urbanization, unhealthy diets, and increasingly sedentary lifestyles have contributed to increase the prevalence of childhood obesity, particularly in developing countries 2. Current treatment initiatives include school-based programs addressing physical activity and diet, which have been conducted with mixed success in reducing adiposity. There are limited safety data supporting the use of drugs for the treatment of obesity and related conditions such as type 2 diabetes in children and adolescents, and non-compliance in this population suggests that pharmacotherapy is unlikely to be effective long term 1. Although criteria have now been developed for bariatric surgery in teenagers 3, there are few evidence-based data available to support the increasing use of this modality in adolescents. Governments and society in general must be made more aware of the problems associated with obesity and the likelihood of progression to the metabolic syndrome in children and adolescents. Obesity, particularly in the central (abdominal) region, has been determined as a key factor in the etiology of type 2 diabetes 2. The prediction of health risks associated with obesity in youth is improved by the additional inclusion of waist circumference (WC) measure to the body mass index (BMI) percentile 4, 5. Such observations reinforce the importance of including WC in the assessment of childhood obesity to identify those at increased metabolic risk as a result of excess abdominal fat 5. The role of obesity can clearly be demonstrated in Japan, where a parallel increase in type 2 diabetes and obesity in children has occurred over the past few decades 6. Central (abdominal) obesity is also a key component in the IDF definition of metabolic syndrome in adults 2. The link between obesity, metabolic syndrome, and type 2 diabetes has already been characterized in adult populations 2. At present, 50–80% of almost 250 million adults worldwide with diabetes 7 are at risk of death from cardiovascular disease. Those with the metabolic syndrome are also at increased risk being twice as likely to die from, and three times as likely to have, cardiovascular complications as compared with those without the syndrome 8, 9. In addition, adults with the metabolic syndrome have a fivefold greater risk of developing type 2 diabetes 10. Already, one-quarter of the world’s adult population have metabolic syndrome 11, 12, and this condition is appearing with increasing frequency in children and adolescents, driven by the growing obesity epidemic in this young population 13-15. In 2004, the World Health Organization (WHO) reported that an estimated 22 million children younger than 5 yr of age and 10% of school-aged children, between 5 and 17 yr, were overweight or obese 16. WHO predicts that the prevalence of childhood obesity in developed and developing countries will continue to increase as has been seen in recent years. For example, from 1985 to 1997, in young Australians, the prevalence of overweight and obesity combined doubled and that of obesity trebled 17. In Thailand, the prevalence of obesity in those aged 5–12 yr increased from 12.2 to 15.6% in just 2 yr 18. In 2003–2004, 17.1% of children aged 2–19 yr in the USA were obese 19. Obesity is associated with an increase in cardiovascular risk factors (also indicators of metabolic syndrome) 20, and the persistence of these indicators from childhood and adolescence to young adulthood has been shown in several studies, including the Quebec Family Study 21, 22. Recently, the IDF released its guidelines for defining and diagnosing the metabolic syndrome in adults 2. The intention was to rationalize the existing multiple definitions of the syndrome and to avoid the confusion that arose as a result of conflicting opinions on the value of each set of criteria. The use of a single unified definition makes it possible to estimate the global prevalence of metabolic syndrome and make valid comparisons between nations. However, to date, there has not been a unified definition that can be used to assess risk in children and adolescents, and existing adult-based definitions of the metabolic syndrome may not be appropriate to address the problem in this age group. A study of adolescents using modified National Cholesterol Education Program (NCEP) [Adult Treatment Panel III (ATP III)] criteria 23 identified that 12% of the study group had the metabolic syndrome 24. When the ≥95th percentile of BMI was used as a cutoff point in the same study group, 31.3% were identified as having the syndrome, more than double of those previously found to be at risk. Duncan et al. 25 studied 991 adolescents (aged 12–19 yr) from National Health and Nutrition Examination Study (NHANES) 1999–2000 and used the ATP III definition modified for age. The overall prevalence of a metabolic syndrome phenotype among US adolescents increased from 4.2% in NHANES III (1988–1992) to 6.4% in NHANES 1999–2000. Based on population-weighted estimates, they estimated that more than 2 million US adolescents currently have a metabolic syndrome phenotype. In a population-based study of a Canadian Qji-Cree community involving 236 children aged 10–19 yr, Retnakaran et al. reported that 18.6% of the children met the criteria for the metabolic syndrome based on a pediatric metabolic syndrome definition based on the ATP III definition, and they used the ATP III definition modified for age and gender 26. Goodman et al. reported on a school-based, cross-sectional study of 1513 black, white, and Hispanic teenagers 27. Overall, the prevalence of ATP III-defined metabolic syndrome was 4.2% and that of the WHO-defined metabolic syndrome was 8.4%. The metabolic syndrome was found almost exclusively among obese teenagers in whom prevalence of the ATP III-defined metabolic syndrome was 19.5% and prevalence of WHO-defined metabolic syndrome 28 was 38.9%. No race or sex differences were present for ATP III definition. However, non-white teenagers were more likely to have metabolic syndrome by WHO criteria, and it was more common among girls if the WHO definition was used. Chi et al. have recently undertaken a literature review on definitions of the metabolic syndrome in children and adolescents published in the past decade 29. They noted that the prevalence of metabolic syndrome in pre-adolescent girls varies widely because of disagreement among proposed definitions of metabolic syndrome in pediatrics. They called for a consensus definition for the metabolic syndrome in children, which would allow researchers to make better temporal, biological, environmental, and social comparisons between data sets. The American College of Endocrinology definition 30 is not ideal in pediatric subjects as WC is rarely measured in children, and nomograms have only recently become available 31 for some ethnic groups but are not available for all. A recent paper has suggested yet another set of criteria with age- and gender-specific cutoff points 32. The variety of cutoff points used for the different components in this paper underlines the need for a single consistent definition with easily measurable components. Therefore, to date, no formal definition for the diagnosis of the metabolic syndrome in children and adolescents has been developed. The rapid increase in obesity highlights the urgency for a definition that could be used to further understand who is at high risk and to distinguish them from those with ‘simple’ uncomplicated obesity. The metabolic syndrome in adults is defined as a cluster of cardiovascular and diabetes risk factors including abdominal obesity, dyslipidemia, glucose intolerance, and hypertension 2. While the danger associated with clustering of components of the metabolic syndrome has been demonstrated in adults, where the presence of three or more components significantly increases the risk for coronary heart disease death/non-fatal myocardial infarction and the onset of new diabetes 33, few, if any, outcome data in children exist. While one definition, although with gender- and ethnicity-specific cutoff points, is suitable for use in the at-risk adult population 2, transposing a single definition to children and adolescents is problematic. Blood pressure, lipid levels, and anthropometric variables change with age and pubertal development. Puberty impacts on fat distribution and is known to cause a decrease both in insulin sensitivity, of approximately 30% with a complementary increase in insulin secretion 34, and in adiponectin levels 35. Therefore, single cutoff points cannot be used to define abnormalities in children. Instead, values above the 90th, 95th, or 97th percentile for gender and age are used. However, there has not been universal agreement as to which level to use for the criteria for the metabolic syndrome. The importance of the early identification of children at risk of developing the metabolic syndrome and subsequently progressing to type 2 diabetes and cardiovascular disease in later life must not be underestimated. From birth and before, circumstances can predispose a child to conditions such as obesity or dysglycemia. The presence of maternal gestational diabetes 36, low birth weight 37, infant feeding practices 38, early adiposity rebound 39, and genetic factors may all contribute to a child’s future level of risk. Being raised in an ‘obesogenic’ environment can also have a strong impact, as can the influence of socioeconomic factors 40, with weight gain often being observed as a positive correlate to affluence in developing countries. Longitudinal outcome studies and further research on the progression and etiology of the metabolic syndrome are urgently required to ascertain the long-term outcomes of abdominal obesity and clustering of the components of metabolic syndrome in at-risk children and to help improve future definitions of the syndrome. This new IDF definition of metabolic syndrome in children and adolescents was developed during a consensus workshop that brought together experts in the field of the metabolic syndrome and pediatrics. The purpose of the new definition of metabolic syndrome in children and adolescents is to expand on the IDF recommendations for managing type 2 diabetes in the young 1 and to provide a useful and unified tool for identifying those at risk. A clinically accessible diagnostic tool, avoiding measurements that may only be available in research settings, is needed to identify the metabolic syndrome in children and adolescents globally. This need has prompted the IDF to develop a definition that has used the limited data available from existing studies in youth. As with the adult criteria, we look on these new criteria as a starting point. As new information emerges, they can be modified. Inspired, in part, by the IDF worldwide definition of metabolic syndrome in adults 2, this new definition builds on previous studies investigating the prevalence of metabolic syndrome in children and adolescents, which have used modified adult criteria with varying cutoff points 12-14, 41, 42 (Table 1). The wide variety of cutoff points used has emphasized the need for a single consistent set of criteria, which is easily measurable and can be used as the basis for future work 29. Because of the developmental challenges presented by the age-related differences in children and adolescents, the new IDF definition of metabolic syndrome has been divided according to the following age groups: 6 to <10, 10 to <16, and ≥16 yr (Table 2). In all the three age groups, abdominal obesity is the ‘sine qua non’. We suggest that below the age of 10 yr, the metabolic syndrome as an entity is not diagnosed, although a strong message for weight reduction will be made for these children. At the age of 10 yr and more, a diagnosis of metabolic syndrome can be made. It requires the presence of abdominal obesity plus the presence of two or more of the other components (elevated triglycerides, low high-density lipoprotein (HDL)-cholesterol, high blood pressure, and elevated plasma glucose). The IDF adult criteria 2 can be used for adolescents aged ≥16 yr, while a modified version of these criteria will be applied to those aged 10 to <16 yr (use 90th percentile cutoff point for waist and <40 mg/dL of HDL for both sexes). On the basis of emerging new data, these criteria may change in the future. In adults, insulin resistance and abdominal obesity are considered to be significant causative factors in the development of the metabolic syndrome 9, 43, 44. The link between obesity, insulin resistance, and the risk of developing the metabolic syndrome has also been described in children 22, 27. With measurement of insulin resistance considered to be impractical for clinical use, abdominal adiposity was positioned as the ‘sine qua non’ in the IDF definition of metabolic syndrome in adults 2 and is recognized to be an independent risk factor for the development of cardiovascular disease in adults 45. Abdominal obesity can be easily assessed using the simple measure of WC, which is known to correlate more strongly with visceral adipose tissue (VAT) than BMI in adults 46 and is a strong predictor of cardiovascular disease risk factors in children 47. The correlation between WC and VAT has also been more recently demonstrated in children 48, further strengthening the existing evidence that WC is an effective measure of abdominal obesity 49 in the youth population. In children and adolescents, a number of studies have demonstrated a similar link between childhood obesity and elevated cardiovascular risk in later life. The Bogalusa Heart study showed that childhood overweight is related to the development of adverse risk factors (BMI, lipids, insulin, diabetes mellitus, and blood pressure) in adulthood and is attributable to the strong persistence of weight status from childhood to adulthood 50. Of the overweight children in the Bogalusa Heart study (BMI ≥95th percentile), 77% remained obese in adulthood. Furthermore, the Muscatine study demonstrated that in young adults, excess weight was the earliest predictor of coronary artery calcification 51. The ATP III definition, applied to a cohort of individuals aged 12–19 yr (NHANES III), identified that 4% of those studied were found to have the metabolic syndrome, with 80% of those meeting the criteria of being overweight 13. Using a modified version of the ATP III definition, metabolic syndrome in adolescents has also been linked to high levels of C-reactive protein, a pro-inflammatory marker. Of the five components of metabolic syndrome, C-reactive protein was higher only among those with abdominal obesity 41. Waist circumference in children is an independent predictor of insulin resistance, lipid levels, and blood pressure 4, 52-54– all components of metabolic syndrome. Moreover, in obese youth with similar BMI, insulin sensitivity is lower in those with high VAT and high waist/hip ratio 53, 54. Furthermore, insulin sensitivity decreases and insulin levels increase with increasing WC percentiles 3. These data, combined with the unequivocal evidence of the dangers of abdominal obesity in adulthood, support the use of abdominal obesity as the ‘sine qua non’ for the diagnosis of metabolic syndrome in children and adolescents. Percentiles rather than absolute values of WC have been used in the new criteria to compensate for varying degrees of development and ethnicity in the youth population. WC percentile data are becoming increasingly available worldwide 31, 55-58. Children with a WC >90th percentile are more likely to have multiple risk factors than those with a WC below this level 59. Several studies attempting to estimate the prevalence of metabolic syndrome in children and adolescents have already used the 90th percentile as a cutoff point for WC 13, 14, 41. We have also chosen to use the 90th percentile as a cutoff point for WC based on this existing evidence and aim to reassess criteria and cutoff points in 5 yr and modify the guidelines, if necessary, based on the new outcome data. Previous studies investigating the metabolic syndrome in children and adolescents have used a range of cutoff points primarily based on ATP III criteria for categorizing additional components of the syndrome, i.e., triglycerides, HDL-cholesterol, blood pressure, and fasting glucose (Table 1) 12-14, 41, 42. Other definitive sources include the National High Blood Pressure Education Program, which recommends blood pressure cutoff points of >90th or >95th percentile adjusted for height, age, and gender to identify ‘high normal’ blood pressure or prehypertension and high blood pressure or hypertension in children and adolescents 60. Cutoff points for impaired fasting glucose have previously followed recommendations by the American Diabetes Association (ADA) [100–125 mg/dL (≥5.6–6.9 mmol/L)] 61 and the NCEP/ATP III in adults [≥110 mg/dL (6.1 mmol/L)] 23, although the latter has recently changed to the lower ADA recommended levels 62. Criteria for defining lipid (triglyceride and HDL-cholesterol) imbalances are even less consistent in the youth population, with recommendations by the NCEP/ATP III (age specific), NHANES III (age and gender specific), and the National Growth and Health Study (age, gender, and ethnic specific), employing either absolute value or percentile cutoff points. In view of this lack of consistency, we believe that use of the adult levels for the present is wise until further information is available. We recommend the following topics as priorities for future research: Develop a better understanding of the relationship between body fat and its distribution in children and adolescents, e.g., dual energy X-ray absorptiometry (DEXA), WC, BMI, and height and weight percentiles; a) Explore whether early growth patterns predict future adiposity and features of the metabolic syndrome, diabetes, and cardiovascular disease and b) explore whether low birth weight predicts future metabolic syndrome, diabetes, and cardiovascular disease; Perform factor analysis in children and adolescents to establish grouping of metabolic characteristics – adiposity, dyslipidemia, hyperinsulinemia, hypoadiponectinemia, and insulin resistance; Investigate how should obesity in children could be better defined, e.g., weight/height, WC etc.; Develop ethnic-specific normal ranges for WC, ideally based on healthy values; Perform ethnic-specific studies of WC etc. vs. abdominal (truncal) fat based on magnetic resonance imaging and DEXA; Support studies of adiponectin, leptin, etc. in children and adolescents to determine if they may be predictors of metabolic syndrome in adulthood; Initiate long-term studies of multi-ethnic cohorts followed into adulthood to determine the natural history and effectiveness of intervention strategies, particularly lifestyle. In conclusion, to combat any conflict that could arise from these multiple interpretations of the metabolic syndrome in children and adolescents, the IDF consensus group has aimed primarily at developing a simple, easy-to-apply definition to begin using in the clinical setting. In the absence of definitive research findings at this time, the proposed IDF definition of the metabolic syndrome in children and adolescents (Table 2) adheres to the absolute values presented in the adult definition 2, with the exception of WC. As described previously, until such time that outcome data from studies in children and adolescents indicate otherwise, WC percentiles are recommended for use. Early detection, followed by treatment in the form of lifestyle intervention and possibly pharmacotherapy, if its safety has been clearly demonstrated, is vital in halting the progression of this syndrome pathway in the adolescent population. It is likely that this will reduce morbidity and mortality in adulthood, as well as minimize the global socioeconomic burden of cardiovascular disease and type 2 diabetes. The workshop was sponsored by an unrestricted educational grant to the IDF Task Force on Epidemiology and Prevention from sanofi-aventis.

BACKGROUND: Interleukin-17A is considered to be central to the pathogenesis of psoriasis. We evaluated secukinumab, a fully human anti-interleukin-17A monoclonal antibody, in patients with moderate-to-severe plaque psoriasis. METHODS: In two phase 3, double-blind, 52-week trials, ERASURE (Efficacy of Response and Safety of Two Fixed Secukinumab Regimens in Psoriasis) and FIXTURE (Full Year Investigative Examination of Secukinumab vs. Etanercept Using Two Dosing Regimens to Determine Efficacy in Psoriasis), we randomly assigned 738 patients (in the ERASURE study) and 1306 patients (in the FIXTURE study) to subcutaneous secukinumab at a dose of 300 mg or 150 mg (administered once weekly for 5 weeks, then every 4 weeks), placebo, or (in the FIXTURE study only) etanercept at a dose of 50 mg (administered twice weekly for 12 weeks, then once weekly). The objective of each study was to show the superiority of secukinumab over placebo at week 12 with respect to the proportion of patients who had a reduction of 75% or more from baseline in the psoriasis area-and-severity index score (PASI 75) and a score of 0 (clear) or 1 (almost clear) on a 5-point modified investigator's global assessment (coprimary end points). RESULTS: The proportion of patients who met the criterion for PASI 75 at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 81.6% with 300 mg of secukinumab, 71.6% with 150 mg of secukinumab, and 4.5% with placebo; in the FIXTURE study, the rates were 77.1% with 300 mg of secukinumab, 67.0% with 150 mg of secukinumab, 44.0% with etanercept, and 4.9% with placebo (P<0.001 for each secukinumab dose vs. comparators). The proportion of patients with a response of 0 or 1 on the modified investigator's global assessment at week 12 was higher with each secukinumab dose than with placebo or etanercept: in the ERASURE study, the rates were 65.3% with 300 mg of secukinumab, 51.2% with 150 mg of secukinumab, and 2.4% with placebo; in the FIXTURE study, the rates were 62.5% with 300 mg of secukinumab, 51.1% with 150 mg of secukinumab, 27.2% with etanercept, and 2.8% with placebo (P<0.001 for each secukinumab dose vs. comparators). The rates of infection were higher with secukinumab than with placebo in both studies and were similar to those with etanercept. CONCLUSIONS: Secukinumab was effective for psoriasis in two randomized trials, validating interleukin-17A as a therapeutic target. (Funded by Novartis Pharmaceuticals; ERASURE and FIXTURE ClinicalTrials.gov numbers, NCT01365455 and NCT01358578, respectively.).

Tight junctions are well-developed between adjacent endothelial cells of blood vessels in the central nervous system, and play a central role in establishing the blood-brain barrier (BBB). Claudin-5 is a major cell adhesion molecule of tight junctions in brain endothelial cells. To examine its possible involvement in the BBB, claudin-5-deficient mice were generated. In the brains of these mice, the development and morphology of blood vessels were not altered, showing no bleeding or edema. However, tracer experiments and magnetic resonance imaging revealed that in these mice, the BBB against small molecules (<800 D), but not larger molecules, was selectively affected. This unexpected finding (i.e., the size-selective loosening of the BBB) not only provides new insight into the basic molecular physiology of BBB but also opens a new way to deliver potential drugs across the BBB into the central nervous system.

UNLABELLED: Diagnosis of autoimmune hepatitis (AIH) may be challenging. However, early diagnosis is important because immunosuppression is life-saving. Diagnostic criteria of the International Autoimmune Hepatitis Group (IAIHG) were complex and purely meant for scientific purposes. This study of the IAIHG aims to define simplified diagnostic criteria for routine clinical practice. Candidate criteria included sex, age, autoantibodies, immunoglobulins, absence of viral hepatitis, and histology. The training set included 250 AIH patients and 193 controls from 11 centers worldwide. Scores were built from variables showing predictive ability in univariate analysis. Diagnostic value of each score was assessed by the area under the receiver operating characteristic (ROC) curve. The best score was validated using data of an additional 109 AIH patients and 284 controls. This score included autoantibodies, immunoglobulin G, histology, and exclusion of viral hepatitis. The area under the curve for prediction of AIH was 0.946 in the training set and 0.91 in the validation set. Based on the ROC curves, two cutoff points were chosen. The score was found to have 88% sensitivity and 97% specificity (cutoff > or =6) and 81% sensitivity and 99% specificity (cutoff > or =7) in the validation set. CONCLUSION: A reliable diagnosis of AIH can be made using a very simple diagnostic score. We propose the diagnosis of probable AIH at a cutoff point greater than 6 points and definite AIH 7 points or higher.

Concept of Diabetes Mellitus: Diabetes mellitus is a group of diseases associated with various metabolic disorders, the main feature of which is chronic hyperglycemia due to insufficient insulin action. Its pathogenesis involves both genetic and environmental factors. The long-term persistence of metabolic disorders can cause susceptibility to specific complications and also foster arteriosclerosis. Diabetes mellitus is associated with a broad range of clinical presentations, from being asymptomatic to ketoacidosis or coma, depending on the degree of metabolic disorder. Classification (Tables 1 and 2, and Figure 1): Table 1. Etiological classification of diabetes mellitus and glucose metabolism disorders I. Type 1 (destruction of pancreatic β-cells, usually leading to absolute insulin deficiency) A. Autoimmune B. Idiopathic II. Type 2 (ranging from predominantly insulin secretory defect, to predominantly insulin resistance with varying degrees of insulin secretory defect) III. Due to other specific mechanisms or diseases (see Table 2 for details) A. Those in which specific mutations have been identified as a cause of genetic susceptibility (1) Genetic abnormalities of pancreatic β-cell function (2) Genetic abnormalities of insulin action B. Those associated with other diseases or conditions (1) Diseases of exocrine pancreas (2) Endocrine diseases (3) Liver disease (4) Drug- or chemical-induced (5) Infections (6) Rare forms of immune-mediated diabetes (7) Various genetic syndromes often associated with diabetes IV. Gestational diabetes mellitus Note: Those that cannot at present be classified as any of the above are called unclassifiable. The occurrence of diabetes-specific complications has not been confirmed in some of these conditions. Table 2. Diabetes mellitus and glucose metabolism disorders due to other specific mechanisms and diseases A. Those in which specific mutations have been identified as a cause of genetic susceptibility B. Those associated with other diseases or conditions (1) Genetic abnormalities of pancreatic β-cell functionInsulin gene (abnormal insulinemia, abnormal proinsulinemia, neonatal diabetes mellitus) HNF 4α gene (MODY1) Glucokinase gene (MODY2) HNF 1α gene (MODY3) IPF-1 gene (MODY4) HNF 1β gene (MODY5) Mitochondria DNA (MIDD) NeuroD1 gene (MODY6) Kir6.2 gene (neonatal diabetes mellitus) SUR1 gene (neonatal diabetes mellitus) AmylinOthers(2) Genetic abnormalities of insulin actionInsulin receptor gene (type A insulin resistance, leprechaunism, Rabson–Mendenhall syndrome etc.) Others (1) Diseases of exocrine pancreasPancreatitisTrauma/pancreatectomyNeoplasmHemochromatosisOthers(2) Endocrine diseasesCushing’s syndromeAcromegalyPheochromocytomaGlucagonomaAldosteronismHyperthyroidismSomatostatinomaOthers(3) Liver diseaseChronic hepatitisLiver cirrhosis Others(4) Drug- or chemical-inducedGlucocorticoidsInterferonOthers(5) InfectionsCongenital rubellaCytomegalovirusOthers(6) Rare forms of immune-mediated diabetesAnti-insulin receptor antibodiesStiffman syndromeInsulin autoimmune syndromeOthers(7) Various genetic syndromes often associated with diabetesDown syndromePrader-Willi syndromeTurner syndromeKlinefelter syndromeWerner syndromeWolfram syndromeCeruloplasmin deficiencyLipoatrophic diabetes mellitusMyotonic dystrophyFriedreich ataxiaLaurence-Moon-Biedl syndromeOthers The occurrence of diabetes-specific complications has not been confirmed in some of these conditions. Figure 1Open in figure viewerPowerPoint A scheme of the relationship between etiology (mechanism) and patho-physiological stages (states) of diabetes mellitus. Arrows pointing right represent worsening of glucose metabolism disorders (including onset of diabetes mellitus). Among the arrow lines, indicates the condition classified as ‘diabetes mellitus’. Arrows pointing left represent improvement in the glucose metabolism disorder. The broken lines indicate events of low frequency. For example, in type 2 diabetes mellitus, infection can lead to ketoacidosis and require temporary insulin treatment for survival. Also, once diabetes mellitus has developed, it is treated as diabetes mellitus regardless of improvement in glucose metabolism, therefore, the arrow lines pointing left are filled in black. In such cases, a broken line is used, because complete normalization of glucose metabolism is rare. The classification of glucose metabolism disorders is principally derived from etiology, and includes staging of pathophysiology based on the degree of deficiency of insulin action. These disorders are classified into four groups: (i) type 1 diabetes mellitus; (ii) type 2 diabetes mellitus; (iii) diabetes mellitus due to other specific mechanisms or diseases; and (iv) gestational diabetes mellitus. Type 1 diabetes is characterized by destruction of pancreatic β-cells. Type 2 diabetes is characterized by combinations of decreased insulin secretion and decreased insulin sensitivity (insulin resistance). Glucose metabolism disorders in category (iii) are divided into two subgroups; subgroup A is diabetes in which a genetic abnormality has been identified, and subgroup B is diabetes associated with other pathologic disorders or clinical conditions. The staging of glucose metabolism includes normal, borderline and diabetic stages depending on the degree of hyperglycemia occurring as a result of the lack of insulin action or clinical condition. The diabetic stage is then subdivided into three substages: non-insulin- requiring, insulin-requiring for glycemic control, and insulin-dependent for survival. The two former conditions are called non-insulin-dependent diabetes and the latter is known as insulin-dependent diabetes. In each individual, these stages may vary according to the deterioration or the improvement of the metabolic state, either spontaneously or by treatment. Diagnosis (Tables 3–7 and Figure 2): Table 3. Criteria of fasting plasma glucose levels and 75 g oral glucose tolerance test 2-h value Normal range Diabetic range Fasting value <110 mg/dL (6.1 mmol/L) ≥126 mg/dL (7.0 mmol/L) 75 g OGTT 2-h value <140 mg/dL (7.8 mmol/L) ≥200 mg/dL (11.1 mmol/L) Evaluation of OGTT Normal type: If both values belong to normal range *Diabetic type: If any of the two values falls into diabetic range Borderline typeNeither normal nor diabetic types *Casual plasma glucose ≥200 mg/dL (≥11.1 mmol/L) and HbA1c≥6.5% are also regarded as to indicate diabetic type. Even for normal type, if 1-h value is 180 mg/dL (10.0 mmol/L), the risk of progression to diabetes mellitus is greater than for <180 mg/dL (10.0 mmol/L) and should be treated as with borderline type (follow-up observation, etc.). Fasting plasma glucose level of 100–109 mg/dL (5.5–6.0 mmol/L) is called ‘high-normal’: within the range of normal fasting plasma glucose. Plasma glucose level after glucose load in oral glucose tolerance test (OGTT) is not included in casual plasma glucose levels. The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%). Table 4. Procedures for diagnosing diabetes mellitus Clinical diagnosis (1) At initial examination, a ‘diabetic type’ is diagnosed if any of the following criteria are met: (i) fasting plasma glucose level ≥126 mg/dL (7.0 mmol/L), (ii) 75 g OGTT 2-h value ≥200 mg/dL (11.1 mmol/L), (iii) casual plasma glucose level ≥200 mg/dL (11.1 mmol/L) or (iv) *HbA1c≥6.5%. Re-examination is carried out at another date and diabetes mellitus is diagnosed if ‘diabetic type’ is confirmed again**. However, diagnosis cannot be made on the basis of a repeated HbA1c test alone. If the same blood sample is confirmed to be diabetic type by both plasma glucose and HbA1c levels (any of [i] to [iii] plus [iv]), then diabetes mellitus can be diagnosed from the initial test (2) If plasma glucose level shows diabetic type (any of [i] to [iii]) and either of the following conditions exists, diabetes mellitus can be diagnosed immediately at the initial examination• The presence of typical symptoms of diabetes mellitus (thirst, polydipsia, polyuria, weight loss)• The presence of definite diabetic retinopathy (3) If it can be confirmed that either of the above conditions 1 or 2 existed in the past, diabetes mellitus must be diagnosed or suspected even if present test values do not meet the above conditions (4) If diabetes mellitus is suspected but the diagnosis cannot be made by the above (1) to (3), the patient should be followed-up (5) The following points should be kept in mind when selecting the method of determination in initial examination and re-examination• If HbA1c is used at initial examination, another method of determination is required for diagnosis at re-examination. As a rule, both plasma glucose level and HbA1c should be measured• If casual plasma glucose level is ≥200 mg/dL (11.1 mmol/L) at the initial test, a different test method is desirable for re-examination• In the case of disorders and conditions in which HbA1c may be inappropriately low, plasma glucose level should be used for diagnosis (Table 5) Epidemiological study For the purpose of estimating the frequency of diabetes mellitus, determination of ‘diabetic type’ from a single test can be considered to represent ‘diabetes mellitus’. Whenever possible, the criteria to be used are HbA1c≥6.5% or OGTT 2-h value ≥200 mg/dL (11.1 mmol/L) Health screening It is important to detect diabetes mellitus and identify high risk groups without overlooking anyone. Therefore, besides measuring plasma glucose and HbA1c, clinical information such as family history and obesity should be referred *The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%). **Hyperglycemia must be confirmed in a non-stressful condition. OGTT, oral glucose tolerance test. Table 5. Disorders and conditions associated with low HbA1c values Anemia Liver disease Dialysis Major hemorrhage Blood transfusion Chronic malaria Hemoglobinopathy Others Table 6. Situations where a 75-g oral glucose tolerance test is recommended Strongly recommended (suspicion of present diabetes mellitus cannot be ruled out) Fasting plasma glucose level is 110–125 mg/dL (6.1–6.9 mmol/L) Casual plasma glucose level is 140–199 mg/dL (7.8–11.0 mmol/L) *HbA1c is 6.0–6.4% (excluding those having overt symptoms of diabetes mellitus) Testing is desirable (high risk of developing diabetes mellitus in the future;Testing is especially advisable for patients with risk factors for arteriosclerosis such as hypertension, dyslipidemia and obesity.) Fasting plasma glucose level is 100–109 mg/dL (5.5–6.0 mmol/L) *HbA1c is 5.6–5.9% Strong family history of diabetes mellitus or present obesity regardless of above criteria *The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%). Table 7. Definition and diagnostic criteria of gestational diabetes mellitus Definition of gestational diabetes mellitus Glucose metabolism disorder with first recognition or onset during pregnancy, but that has not developed into diabetes mellitus Diagnostic criteria of gestational diabetes mellitus Diagnosed if one or more of the following criteria is met in a 75 g OGTT Fasting plasma glucose ≥92 mg/dL (5.1 mmol/L) 1-h value ≥180 mg/dL (10.0 mmol/L) 2-h value ≥153 mg/dL (8.5 mmol/L) However, diabetes mellitus that is diagnosed according to ‘Clinical diagnosis’ outlined in Table 4 is excluded from gestational diabetes mellitus (IADPSG Consensus Panel, Reference 42, partly modified with permission of Diabetes Care). Figure 2Open in figure viewerPowerPoint Flow chart outlining steps in the clinical diagnosis of diabetes mellitus. *The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%). Categories of the State of Glycemia: Confirmation of chronic hyperglycemia is essential for the diagnosis of diabetes mellitus. When plasma glucose levels are used to determine the categories of glycemia, patients are classified as having a diabetic type if they meet one of the following criteria: (i) fasting plasma glucose level of ≥126 mg/dL (≥7.0 mmol/L); (ii) 2-h value of ≥200 mg/dL (≥11.1 mmol/L) in 75 g oral glucose tolerance test (OGTT); or (iii) casual plasma glucose level of ≥200 mg/dL (≥11.1 mmol/L). Normal type is defined as fasting plasma glucose level of <110 mg/dL (<6.1 mmol/L) and 2-h value of <140 mg/dL (<7.8 mmol/L) in OGTT. Borderline type (neither diabetic nor normal type) is defined as falling between the diabetic and normal values. According to the current revision, in addition to the earlier listed plasma glucose values, hemoglobin A1c (HbA1c) has been given a more prominent position as one of the diagnostic criteria. That is, (iv) HbA1c≥6.5% is now also considered to indicate diabetic type. The value of HbA1c, which is equivalent to the internationally used HbA1c (%) (HbA1c [NGSP]) defined by the NGSP (National Glycohemoglobin Standardization Program), is expressed by adding 0.4% to the HbA1c (JDS) (%) defined by the Japan Diabetes Society (JDS). Subjects with borderline type have a high rate of developing diabetes mellitus, and correspond to the combination of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) noted by the American Diabetes Association (ADA) and WHO. Although borderline cases show few of the specific complications of diabetes mellitus, the risk of arteriosclerosis is higher than those of normal type. When HbA1c is 6.0–6.4%, suspected diabetes mellitus cannot be excluded, and when HbA1c of 5.6–5.9% is included, it forms a group with a high risk for developing diabetes mellitus in the future, even if they do not have it currently. Clinical Diagnosis: 1 If any of the criteria for diabetic type (i) through to (iv) is observed at the initial examination, the patient is judged to be ‘diabetic type’. Re-examination is conducted on another day, and if ‘diabetic type’ is reconfirmed, diabetes mellitus is diagnosed. However, a diagnosis cannot be made only by the re-examination of HbA1c alone. Moreover, if the plasma glucose values (any of criteria [i], [ii], or [iii]) and the HbA1c (criterion [iv]) in the same blood sample both indicate diabetic type, diabetes mellitus is diagnosed based on the initial examination alone. If HbA1c is used, it is essential that the plasma glucose level (criteria [i], [ii] or [iii]) also indicates diabetic type for a diagnosis of diabetes mellitus. When diabetes mellitus is suspected, HbA1c should be measured at the same time as examination for plasma glucose. 2 If the plasma glucose level indicates diabetic type (any of [i], [ii], or [iii]) and either of the following conditions exists, diabetes mellitus can be diagnosed immediately at the initial examination. • The presence of typical symptoms of diabetes mellitus (thirst, polydipsia, polyuria, weight loss) • The presence of definite diabetic retinopathy 3 If it can be confirmed that the above conditions 1 or 2 existed in the past, diabetes mellitus can be diagnosed or suspected regardless of the current test results. 4 If the diagnosis of diabetes cannot be established by these procedures, the patient is followed up and re-examined after an appropriate interval. 5 The physician should assess not only the presence or absence of diabetes, but also its etiology and glycemic stage, and the presence and absence of diabetic complications or associated conditions. Epidemiological Study: For the purpose of estimating the frequency of diabetes mellitus, ‘diabetes mellitus’ can be substituted for the determination of ‘diabetic type’ from a single examination. In this case, HbA1c≥6.5% alone can be defined as ‘diabetes mellitus’. Health Screening: It is important not to misdiagnose diabetes mellitus, and thus clinical information such as family history and obesity should be referred to at the time of screening in addition to an index for plasma glucose level. Gestational Diabetes Mellitus: There are two hyperglycemic disorders in pregnancy: (i) gestational diabetes mellitus (GDM); and (ii) diabetes mellitus. GDM is diagnosed if one or more of the following criteria is met in a 75 g OGTT during pregnancy: 1 Fasting plasma glucose level of ≥92 mg/dL (5.1 mmol/L) 2 1-h value of ≥180 mg/dL (10.0 mmol/L) 3 2-h value of ≥153 mg/dL (8.5 mmol/L) However, diabetes mellitus that is diagnosed by the clinical diagnosis of diabetes mellitus defined earlier is excluded from GDM. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2010.00074.x, 2010)

There is accumulating evidence that T-cell-mediated dominant control of self-reactive T-cells contributes to the maintenance of immunologic self-tolerance and its alteration can cause autoimmune disease. Efforts to delineate such a regulatory T-cell population have revealed that CD25+ cells in the CD4+ population in normal naive animals bear the ability to prevent autoimmune disease in vivo and, upon antigenic stimulation, suppress the activation/proliferation of other T cells in vitro. The CD25+ CD4+ regulatory T cells, which are naturally anergic and suppressive, appear to be produced by the normal thymus as a functionally distinct subpopulation of T cells. They play critical roles not only in preventing autoimmunity but also in controlling tumor immunity and transplantation tolerance.

Catheter ablation of AF is a very commonly performed procedure in hospitals throughout the world. Surgical ablation of AF, although less widely available than catheter-based AF ablation, is also an important therapeutic option for patients with AF at many major medical centers. This document provides an up-to-date review of the indications, techniques, and outcomes of catheter and surgical ablation of AF. Areas for which a consensus can be reached concerning AF ablation are identified, and a series of consensus definitions have been developed for use in future clinical trials of AF ablation. Also included within this document are recommendations concerning indications for AF ablation, technical performance of this procedure, and training. It is our hope to improve patient care by providing a foundation for those involved with care of patients with AF as well as those who perform AF ablation. It is recognized that this field continues to evolve rapidly and that this document will need to be updated. Successful AF ablation programs optimally should consist of a cooperative team of cardiologists, electrophysiologists, and surgeons to ensure appropriate indications, procedure selection, and follow-up.

This companion paper to the introduction of the International League Against Epilepsy (ILAE) 2017 classification of seizure types provides guidance on how to employ the classification. Illustration of the classification is enacted by tables, a glossary of relevant terms, mapping of old to new terms, suggested abbreviations, and examples. Basic and extended versions of the classification are available, depending on the desired degree of detail. Key signs and symptoms of seizures (semiology) are used as a basis for categories of seizures that are focal or generalized from onset or with unknown onset. Any focal seizure can further be optionally characterized by whether awareness is retained or impaired. Impaired awareness during any segment of the seizure renders it a focal impaired awareness seizure. Focal seizures are further optionally characterized by motor onset signs and symptoms: atonic, automatisms, clonic, epileptic spasms, or hyperkinetic, myoclonic, or tonic activity. Nonmotor-onset seizures can manifest as autonomic, behavior arrest, cognitive, emotional, or sensory dysfunction. The earliest prominent manifestation defines the seizure type, which might then progress to other signs and symptoms. Focal seizures can become bilateral tonic-clonic. Generalized seizures engage bilateral networks from onset. Generalized motor seizure characteristics comprise atonic, clonic, epileptic spasms, myoclonic, myoclonic-atonic, myoclonic-tonic-clonic, tonic, or tonic-clonic. Nonmotor (absence) seizures are typical or atypical, or seizures that present prominent myoclonic activity or eyelid myoclonia. Seizures of unknown onset may have features that can still be classified as motor, nonmotor, tonic-clonic, epileptic spasms, or behavior arrest. This "users' manual" for the ILAE 2017 seizure classification will assist the adoption of the new system.

Three integral membrane proteins, clau- din-1, -2, and occludin, are known to be components of tight junction (TJ) strands. To examine their ability to form TJ strands, their cDNAs were introduced into mouse L fibroblasts lacking TJs. Immunofluorescence microscopy revealed that both FLAG-tagged claudin-1 and -2 were highly concentrated at cell contact sites as planes through a homophilic interaction. In freeze-fracture replicas of these contact sites, well-developed networks of strands were identified that were similar to TJ strand networks in situ and were specifically labeled with anti-FLAG mAb. In glutaraldehyde-fixed samples, claudin-1-induced strands were largely associated with the protoplasmic (P) face as mostly continuous structures, whereas claudin-2-induced strands were discontinuous at the P face with complementary grooves at the extracellular (E) face which were occupied by chains of particles. Although occludin was also concentrated at cell contact sites as dots through its homophilic interaction, freeze-fracture replicas identified only a small number of short strands that were labeled with anti-occludin mAb. However, when occludin was cotransfected with claudin-1, it was concentrated at cell contact sites as planes to be incorporated into well- developed claudin-1-based strands. These findings suggested that claudin-1 and -2 are mainly responsible for TJ strand formation, and that occludin is an accessory protein in some function of TJ strands.

BACKGROUND: Data are limited regarding the use of poly(adenosine diphosphate [ADP]-ribose) polymerase inhibitors, such as veliparib, in combination with chemotherapy followed by maintenance as initial treatment in patients with high-grade serous ovarian carcinoma. METHODS: -mutation cohort), and the intention-to-treat population. RESULTS: -mutation cohort, the median progression-free survival was 34.7 months in the veliparib-throughout group and 22.0 months in the control group (hazard ratio for progression or death, 0.44; 95% confidence interval [CI], 0.28 to 0.68; P<0.001); in the HRD cohort, it was 31.9 months and 20.5 months, respectively (hazard ratio, 0.57; 95 CI, 0.43 to 0.76; P<0.001); and in the intention-to-treat population, it was 23.5 months and 17.3 months (hazard ratio, 0.68; 95% CI, 0.56 to 0.83; P<0.001). Veliparib led to a higher incidence of anemia and thrombocytopenia when combined with chemotherapy as well as of nausea and fatigue overall. CONCLUSIONS: Across all trial populations, a regimen of carboplatin, paclitaxel, and veliparib induction therapy followed by veliparib maintenance therapy led to significantly longer progression-free survival than carboplatin plus paclitaxel induction therapy alone. The independent value of adding veliparib during induction therapy without veliparib maintenance was less clear. (Funded by AbbVie; VELIA/GOG-3005 ClinicalTrials.gov number, NCT02470585.).

I. EXECUTIVE SUMMARY: BACKGROUND: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR-RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR-RS-2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence-based findings of the document. METHODS: ICAR-RS presents over 180 topics in the forms of evidence-based reviews with recommendations (EBRRs), evidence-based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. RESULTS: ICAR-RS-2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence-based management algorithm is provided. CONCLUSION: This ICAR-RS-2021 executive summary provides a compilation of the evidence-based recommendations for medical and surgical treatment of the most common forms of RS.

Tight junctions (TJs) in endothelial cells are thought to determine vascular permeability. Recently, claudin-1 to -15 were identified as major components of TJ strands. Among these, claudin-5 (also called transmembrane protein deleted in velo-cardio-facial syndrome [TMVCF]) was expressed ubiquitously, even in organs lacking epithelial tissues, suggesting the possible involvement of this claudin species in endothelial TJs. We then obtained a claudin-6-specific polyclonal antibody and a polyclonal antibody that recognized both claudin-5/TMVCF and claudin-6. In the brain and lung, immunofluorescence microscopy with these polyclonal antibodies showed that claudin-5/TMVCF was exclusively concentrated at cell-cell borders of endothelial cells of all segments of blood vessels, but not at those of epithelial cells. Immunoreplica electron microscopy revealed that claudin-5/TMVCF was a component of TJ strands. In contrast, in the kidney, the claudin-5/TMVCF signal was restricted to endothelial cells of arteries, but was undetectable in those of veins and capillaries. In addition, in all other tissues we examined, claudin-5/TMVCF was specifically detected in endothelial cells of some segments of blood vessels, but not in epithelial cells. Furthermore, when claudin-5/TMVCF cDNA was introduced into mouse L fibroblasts, TJ strands were reconstituted that resembled those in endothelial cells in vivo, i.e., the extracellular face-associated TJs. These findings indicated that claudin-5/TMVCF is an endothelial cell-specific component of TJ strands.

For epithelia to function as barriers, the intercellular space must be sealed. Sealing two adjacent cells at bicellular tight junctions (bTJs) is well described with the discovery of the claudins. Yet, there are still barrier weak points at tricellular contacts, where three cells join together. In this study, we identify tricellulin, the first integral membrane protein that is concentrated at the vertically oriented TJ strands of tricellular contacts. When tricellulin expression was suppressed with RNA interference, the epithelial barrier was compromised, and tricellular contacts and bTJs were disorganized. These findings indicate the critical function of tricellulin for formation of the epithelial barrier.

Abstract Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3–6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.