Saint Louis University

Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome. The Human Microbiome Project Consortium reports the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome. The Human Microbiome Project (HMP), supported by the National Institutes of Health Common Fund, has the goal of characterizing the microbial communities that inhabit and interact with the human body in sickness and in health. In two Articles in this issue of Nature, the HMP Consortium presents the first population-scale details of the organismal and functional composition of the microbiota across five areas of the body. An associated News & Views discusses the initial results — which, along with those of a series of co-publications, already constitute the most extensive catalogue of organisms and genes related to the human microbiome yet published — and highlights some of the major questions that the project will tackle in the next few years.

Nonalcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis in the absence of a history of significant alcohol use or other known liver disease. Nonalcoholic steatohepatitis (NASH) is the progressive form of NAFLD. The Pathology Committee of the NASH Clinical Research Network designed and validated a histological feature scoring system that addresses the full spectrum of lesions of NAFLD and proposed a NAFLD activity score (NAS) for use in clinical trials. The scoring system comprised 14 histological features, 4 of which were evaluated semi-quantitatively: steatosis (0-3), lobular inflammation (0-2), hepatocellular ballooning (0-2), and fibrosis (0-4). Another nine features were recorded as present or absent. An anonymized study set of 50 cases (32 from adult hepatology services, 18 from pediatric hepatology services) was assembled, coded, and circulated. For the validation study, agreement on scoring and a diagnostic categorization ("NASH," "borderline," or "not NASH") were evaluated by using weighted kappa statistics. Inter-rater agreement on adult cases was: 0.84 for fibrosis, 0.79 for steatosis, 0.56 for injury, and 0.45 for lobular inflammation. Agreement on diagnostic category was 0.61. Using multiple logistic regression, five features were independently associated with the diagnosis of NASH in adult biopsies: steatosis (P = .009), hepatocellular ballooning (P = .0001), lobular inflammation (P = .0001), fibrosis (P = .0001), and the absence of lipogranulomas (P = .001). The proposed NAS is the unweighted sum of steatosis, lobular inflammation, and hepatocellular ballooning scores. In conclusion, we present a strong scoring system and NAS for NAFLD and NASH with reasonable inter-rater reproducibility that should be useful for studies of both adults and children with any degree of NAFLD. NAS of > or =5 correlated with a diagnosis of NASH, and biopsies with scores of less than 3 were diagnosed as "not NASH."

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,
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\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,
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\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
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\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,

OBJECTIVE: Steatohepatitis is a morphological pattern of liver injury that may be seen in alcoholic or nonalcoholic liver disease. This pattern may occur with obesity, diabetes, the use of certain drugs, or the cause may be idiopathic. The well-recognized histopathological features of nonalcoholic steatohepatitis (NASH) include hepatocellular steatosis and ballooning, mixed acute and chronic lobular inflammation, and zone 3 perisinusoidal fibrosis. Currently, there are no systems for grading necroinflammatory activity or for staging fibrosis as exist for various other forms of chronic liver disease. The purpose of this study was to develop such a grading and staging system and was based on review of liver biopsies from 51 patients with nonalcoholic steatohepatitis from Saint Louis University Health Sciences Center. METHODS: For determination of grade, 10 histological variables of activity were initially analyzed; an overall impression of mild, moderate, and severe was made and the variables considered to be most significant were used to develop the necroinflammatory grade. RESULTS: The histological lesions considered to be significant were: steatosis, ballooning, and intra-acinar and portal inflammation. A staging score was developed to reflect both location and extent of fibrosis. The fibrosis score was derived from the extent of zone 3 perisinusoidal fibrosis with possible additional portal/periportal fibrosis and architectural remodeling. Fibrosis stages are as follows: Stage 1, zone 3 perisinusoidal fibrosis; Stage 2, as above with portal fibrosis; Stage 3, as above with bridging fibrosis; and Stage 4, cirrhosis. CONCLUSION: We propose a grading and staging system that reflects the unique histological features of nonalcoholic steatohepatitis.

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies. The Human Microbiome Project Consortium has established a population-scale framework to study a variety of microbial communities that exist throughout the human body, enabling the generation of a range of quality-controlled data as well as community resources. The Human Microbiome Project (HMP), supported by the National Institutes of Health Common Fund, has the goal of characterizing the microbial communities that inhabit and interact with the human body in sickness and in health. In two Articles in this issue of Nature, the HMP Consortium presents the first population-scale details of the organismal and functional composition of the microbiota across five areas of the body. An associated News & Views discusses the initial results — which, along with those of a series of co-publications, already constitute the most extensive catalogue of organisms and genes related to the human microbiome yet published — and highlights some of the major questions that the project will tackle in the next few years.

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.

Abstract The Adaptive Poisson–Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson–Boltzmann analytical and a semi‐analytical solver, an optimized boundary element solver, a geometry‐based geometric flow solvation model, a graph theory‐based algorithm for determining p K a values, and an improved web‐based visualization tool for viewing electrostatics.

PREAMBLE The study of NAFLD has intensified significantly, with more than 1400 publications since 2018, when the last American Association for the Study of Liver Diseases (AASLD) Guidance document was published.1 This new AASLD Guidance document reflects many advances in the field pertinent to any practitioner caring for patients with NAFLD and emphasizes advances in noninvasive risk stratification and therapeutics. A separate guideline focused on the management of patients with NAFLD in the context of diabetes has been written jointly by the American Association of Clinical Endocrinology and AASLD.2 Given the significant growth in pediatric NAFLD, it will not be covered here to allow for a more robust discussion of the diagnosis and management of pediatric NAFLD in the upcoming AASLD Pediatric NAFLD Guidance. A “Guidance” differs from a “Guideline” in that it is not bound by the Grading of Recommendations, Assessment Development and Evaluation system. Thus, actionable statements rather than formal recommendations are provided herein. The highest available level of evidence was used to develop these statements, and, where high-level evidence was not available, expert opinion was used to develop guidance statements to inform clinical practice. Key points highlight important concepts relevant to understanding the disease and its management. The most profound advances in NAFLD relevant to clinical practice are in biomarkers and therapeutics. Biomarkers and noninvasive tests (NITs) can be used clinically to either exclude advanced diseases or identify those with a high probability of cirrhosis.3,4 NIT “cut points” vary with the populations studied, underlying disease severity, and clinical setting. Those proposed in this guidance are meant to aid decision-making in the clinic and are not meant to be interpreted in isolation. Identifying patients with “at-risk” NASH (biopsy-proven NASH with stage 2 or higher fibrosis) is a more recent area of interest. Although the definitive diagnosis and staging of NASH remain linked to histology, noninvasive tools can now be used to assess the likelihood of significant fibrosis, predict risk of disease progression and decompensation, make management decisions, and, to some degree, assess response to treatment. There is an ongoing debate over the nomenclature of fatty liver disease, which had not been finalized at the time this guidance was published. At the culmination of a rigorous consensus process, it is intended that any formal change in nomenclature will advance the field without a negative impact on disease awareness, clinical trial endpoints, or the drug development/approval process. Furthermore, it should allow for the emergence of newly recognized disease subtypes to address the impact of disease heterogeneity, including the role of alcohol, on disease progression and response to therapy. Input from patients has been central to all stages of the consensus process to ensure the minimization of nomenclature-related stigma. DEFINITIONS NAFLD is an overarching term that includes all disease grades and stages and refers to a population in which ≥5% of hepatocytes display macrovesicular steatosis in the absence of a readily identified alternative cause of steatosis (eg, medications, starvation, monogenic disorders) in individuals who drink little or no alcohol (defined as < 20 g/d for women and <30 g/d for men). The spectrum of disease includes NAFL, characterized by macrovesicular hepatic steatosis that may be accompanied by mild inflammation, and NASH, which is additionally characterized by the presence of inflammation and cellular injury (ballooning), with or without fibrosis, and finally cirrhosis, which is characterized by bands of fibrous septa leading to the formation of cirrhotic nodules, in which the earlier features of NASH may no longer be fully appreciated on a liver biopsy. UPDATE ON EPIDEMIOLOGY AND NATURAL HISTORY The prevalence of NAFLD and NASH is rising worldwide in parallel with increases in the prevalence of obesity and metabolic comorbid disease (insulin resistance, dyslipidemia, central obesity, and hypertension).5,6 The prevalence of NAFLD in adults is estimated to be 25%–30% in the general population7–9 and varies with the clinical setting, race/ethnicity, and geographic region studied but often remains undiagnosed.10–14 The associated economic burden attributable to NASH is substantial.15–17 The prevalence of NASH in the general population is challenging to determine with certainty; however, NASH was identified in 14% of asymptomatic patients undergoing colon cancer screening.14 This study also highlights that since the publication of a prior prospective prevalence study,18 the prevalence of clinically significant fibrosis (stage 2 or higher fibrosis) has increased >2-fold. This is supported by the projected rise in NAFLD prevalence by 2030, when patients with advanced hepatic fibrosis, defined as bridging fibrosis (F3) or compensated will the projected of the of hepatic decompensation, and to NASH are to to by Although to is the leading for liver in women and those of and is on with alcohol as the leading of disease progression from and that fibrosis and the presence of are the of disease The NASH and the fibrosis it it challenging to the of NASH to fibrosis and in Although fibrosis is the of increased and and are in patients with NAFLD in the absence of fibrosis on patients with NASH and at stage 2 fibrosis to as “at-risk” NASH, a higher risk of and progression is by many as the presence and of comorbid disease, and A of patients in NASH that or or may earlier of with a NAFLD fibrosis progression of stage in those with NASH for those with The diagnosis of cirrhosis, by or is important it clinical management. Those with for as as for and for or of patients with cirrhosis, progression to clinical from to Association disease stage and The most of in patients with NAFLD are disease and by liver The of liver fibrosis identified in patients with NAFLD has been linked to the of and fibrosis and are associated with an risk of and than earlier stages of a prospective study of in those with fibrosis stages was with in those with bridging fibrosis and in those with for hepatic was associated with has been associated with a in in clinical with NASH and fibrosis are at higher risk for and and are to “at-risk” The of fibrosis progression and hepatic vary on disease severity, and comorbid disease and are the most of in patients with NAFLD without advanced from liver disease in patients with advanced AND The presence and of and NASH are by that the and of fatty and and to and metabolic metabolic and in the of (eg, and the formation and of from There is in the role of patients with the of a role in the of NASH, with a higher risk associated with of NAFLD as of the that to the of NASH and its many of which can be are the many where may a role and where important as of fatty the and may also these A disease may be an of to that to without is which and the of NASH the of for patients with of that or NASH that (eg, (eg, (eg, A and fatty hepatic and and inflammation, and metabolic the with on the liver (eg, of growth growth and as that and is in patients with NAFLD and is in the and is characterized by increased of fatty from in the and with the progression of NAFLD to that the and of the of to an and that in response to in The and to in can be by and decisions, all of which in the of The of to the of NASH patients has the of tests and Although in some the and progression of NASH are by and resistance, in disease progression is by been associated with more advanced liver disease and the of in The of of in and in that a role in also been linked to the prevalence and of NAFLD, including 2 which may a role in and which in a that an that also to in been linked to NASH, fibrosis, and in a for of also been to be A of the of which is the of this to in disease and as to from the and hepatic may also to the NASH of of patients is to understanding of this disease and its The response of the liver to injury includes and of which to injury and as of a hepatic Although of been a in NASH, its role in the of NASH in remains of NASH an to the liver and and with in and disease inflammation, from to disease to the of NAFLD and disease NAFLD NAFLD is linked to and often the of metabolic (insulin resistance, dyslipidemia, central obesity, and metabolic an risk of progression of NASH and The NAFLD and metabolic may also the liver and (eg, the of that fatty and and The presence and of obesity are associated with NAFLD and disease is an important of the role of obesity in NAFLD characterized by increased and a higher risk of resistance, and hepatic fibrosis, of characterized by increased in the or to be which is more and than the of this more and is the of fatty leading to and of a with NAFLD recent and of NAFLD, or for alcohol including of and (eg, features of (eg, features of advanced liver disease (eg, tests with and and or to not as of liver or 2 diabetes 2 diabetes is the most risk for the of NAFLD, fibrosis and Given the central role that in the of and NAFLD, it is not that patients with a higher prevalence of NAFLD from to and a higher risk of NASH with Furthermore, the probability of advanced fibrosis increases with the of Although is for time and time these the and The NAFLD and is in in its NAFLD is associated with a in in the absence of The presence of NAFLD is associated with a to risk of and patients with NAFLD should be for the presence of Furthermore, as liver disease and diabetes more challenging to The role of in the progression of remains with 2 an and injury and liver not this Although NAFLD has also been in patients with its prevalence is than in and it is to metabolic risk (eg, higher is associated with There is a higher of in those with NAFLD the disease with of in disease to in those with The presence of is to metabolic with to the risk of and has been associated with fibrosis the of or the or are of underlying metabolic disease has not been with NAFLD are as to as those without and the are more in patients with NASH can to and and impact it is to this is by the of the patients to cirrhosis, to remain at high risk for the of and to hepatic of in NAFLD should the of to as on risk and risk of with as fatty or should be when with a not are in patients with NAFLD the disease including advanced liver disease, and to a in and in clinical are often patients with are also in the context of compensated and may on and are Although been used in patients with cirrhosis, the risk of be higher in this and more is patients with and high risk undergoing for liver can be with patients with NAFLD and (eg, or a of with fatty or should be used to 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for NAFLD, NASH, and advanced 2 to for of hepatic steatosis and Clinical and advanced fibrosis in steatosis on liver (eg, disease on liver disease with to macrovesicular steatosis or of of steatosis and of hepatic to steatosis of of or may not be of metabolic risk and injury injury to of of metabolic of of hepatic of alcohol can be an important to fatty liver disease progression and should be in all can be as mild to 20 and and or and alcohol increases the probability of advanced in patients with obesity or of and alcohol on liver disease and alcohol the risk of liver cirrhosis, and from liver alcohol liver injury and fibrosis progression and should be in patients with a of mild alcohol on the of but in a alcohol (defined as was associated with in steatosis and and of NASH with patients who not alcohol may the risk for and is in to liver with an of on the to impact disease at an The impact of alcohol and on the of patients with NAFLD, alcohol can be a for liver disease and should be on a with clinically significant hepatic fibrosis should from alcohol Key for those patients with alcohol may the of fibrosis progression and hepatic and in patients with to its with obesity and metabolic risk higher of NAFLD been in patients with growth and the role of in the of hepatic the NAFLD and in remains significant NAFLD and or was in a however, a study of patients for a of was associated with a higher of and the of its metabolic growth are important of and and cellular is associated with and increased and can in resistance, and a growth in patients with NAFLD and associated with obesity and cause of is associated with resistance, and dyslipidemia, with a an increased risk for NASH and of in with and NAFLD been and a study of adults with with and liver in NASH with and hepatic steatosis by patients with and NAFLD, a which and increases growth without liver the a in the and NAFLD is linked to in and resistance, but is not for all A of and and A that NAFLD was associated with in but higher in a by The and NAFLD is often by the presence of obesity and resistance, of which are to be associated with can also resistance, and to the of hepatic study in that a level was associated with NAFLD, and the was for and in study including with by and liver histology, the and steatosis when for and obesity, with no to the of liver or in resistance, and a more role of on metabolic risk for NAFLD in but it should be for as it may The role of and in NAFLD is associated with increased liver as as a higher prevalence of NAFLD and advanced The prevalence of NAFLD is higher in with that higher in women are associated with an increased risk of NAFLD Furthermore, is a likelihood of NAFLD in higher of as as an and the of on NAFLD, hepatic in study that to from and are in The associated increased to the and progression of NAFLD, has not been of in and population a to in the prevalence of NAFLD and an increased risk of women with that is the of disease in a study of women with NAFLD was associated with the of and advanced fibrosis for and this study not for resistance, which may the NAFLD is more in with but not of is as by clinical or this should be Key Although and may be associated with hepatic role on the and progression of and fibrosis remains to be can in women with which with obesity and can NAFLD and more disease in this NAFLD Although NAFLD is associated with obesity, it can also in or in are with or and the prevalence of NAFLD in individuals varies from in the to as high as in with with NAFLD increased metabolic and and in the may also to NAFLD in a significant role in this but the to NAFLD individuals with NAFLD are more of or which is in by a higher prevalence of the in the which to NASH and fibrosis but is more in individuals with NAFLD with patients who or had but is not as it not can also a role and should be in patients of NAFLD in patients without obesity can be clinically may not be for patients with NAFLD, but and in this may be of populations at increased risk for advanced liver disease is to identify and those with clinically significant fibrosis (stage in as those with obesity with metabolic a of or significant alcohol also separate discussion on the role of may identify those with asymptomatic but clinically significant of patients for that may hepatic of is important of with NASH a higher risk of advanced Furthermore, the risk of NAFLD and advanced fibrosis may be of risk and recommendations are in for advanced fibrosis in populations of advanced fibrosis, obesity NAFLD in context of alcohol of a with to 2 diabetes of advanced fibrosis in population should NAFLD be in and practice most NAFLD is asymptomatic or associated with often patients The prevalence of advanced disease is in than in and the to is context to NAFLD on the of metabolic risk or identified as fatty liver by in the absence of of hepatic steatosis disease, disease, alcohol should risk The of this risk is to identify patients who are not to advanced fibrosis to the negative of in in advanced fibrosis, patients in can be in patients with metabolic risk those with or should more risk with patients with and advanced hepatic fibrosis a from available clinical and may be and allow for the of as progression to or decompensation, the of may be robust in patients with more are available, it is that the for in patients with will for the of patients at risk for or with NAFLD practice with steatosis on or for is a clinical of NAFLD, as those with metabolic risk or in liver should with a prevalence of advanced fibrosis, as in the setting, the is on advanced fibrosis a with a high negative the is patients can be in the and without 2 diabetes and metabolic risk can be with or 2 or more metabolic risk are at higher risk for disease and more (eg, should be patients than a of should be has in those should be in those with increased metabolic risk or liver should not be used in patients with a should be or Liver or the for risk stratification in a to should be in those with to exclude of liver disease or when to the increased risk of clinically significant higher prevalence as risk with may be when noninvasive tests (NITs) are or is clinical of more advanced of should for and or may identify patients with “at-risk” NASH with NAFLD and fibrosis stage who may from a as is on clinical or management may be without a liver biopsy. Liver should be when significant fibrosis the presence of “at-risk” NASH (eg, or NIT is are or are that in patients with or advanced fibrosis, an is a of and is for this of in risk is on expert at all stages of disease should be on and those with fibrosis for as of are supported by evidence and are meant to clinical management to rather than be interpreted in isolation. who may a or high risk of advanced disease on should risk the setting, or as are over as to The Liver is for when advanced fibrosis is it can be for risk the of may be in some risk is with an or high risk of fibrosis, patients should be to for and those patients with advanced hepatic fibrosis or cirrhosis, or of of or may the of are often used clinically to identify patients with liver disease but can be in patients with NASH, and advanced hepatic Although are for the of with advanced fibrosis, and or or a of may the presence of liver are the provided by most clinical which is to the of of patients with for NAFLD from risk stratification in the and practice The in the is the of patients with “at-risk” NASH or advanced patients and may from tools as or can be used to risk patients in been or not of clinical Liver should be when is as may with or and or features a diagnosis of advanced or (eg, or when is in liver for NAFLD is not patients with hepatic steatosis or clinically NAFLD on the presence of obesity and metabolic risk should risk with as those with obesity, of cirrhosis, or more than mild alcohol should be for advanced patients with or 2 or more metabolic risk evidence of hepatic risk with should be with NASH are at the highest risk for and for and for with advanced NASH or should be to a for are in patients with advanced liver disease to NASH and should not be used in to exclude the presence of NASH with clinically significant of patients with NASH should be increased risk and for advanced hepatic Key with “at-risk” NASH with at stage 2 fibrosis) are at increased risk of and AND NAFLD Although liver remains the for the and staging of NASH, it has important to and liver for and staging of NASH are not in clinical practice and should be for clinical biomarkers are as tools for more an important of liver of noninvasive biomarkers in with the and of will the diagnosis of patients with clinically disease and response to without the for liver and of hepatic steatosis Although used in clinical for of in those with and a of steatosis The absence of steatosis on not exclude the presence of NASH or the presence of fibrosis, can be when cirrhotic liver is identified or it evidence of (eg, the of hepatic the in with a of hepatic steatosis but not or in liver is an and for liver that is used in clinical role in clinical practice is it is used in Although is to in the diagnosis as as the of liver this is by and the of not a of liver fibrosis in patients with or NAFLD Clinical and fibrosis biomarkers from clinical can of the presence of advanced fibrosis been (eg, NAFLD however, is the most is a and and in its to identify patients with a probability of advanced of and also been associated with and in a change in from risk to risk to high risk may be used to assess clinical Although is to fibrosis as the and to advanced fibrosis, is as a for general and on its and The is a of in of and of patients with NAFLD at increased risk of progression to and clinical The is for clinical as a in the and fibrosis tests may be as risk when is not available for the noninvasive of NAFLD to clinical context of of hepatic steatosis with steatosis can as advanced fibrosis for ≥5% spectrum of to assess of “at-risk” NASH in the of and patients with at stage 2 fibrosis with of advanced fibrosis not in and individuals who high probability not in with obesity 2 to a to a of points not points not with advanced fibrosis, of of or for and for cirrhosis, is associated with increased risk of hepatic patients with by is associated with cirrhosis, but for is by has a for diagnosis of and is also associated with increased risk of hepatic “at-risk” NASH is defined as NASH with stage area the clinical Liver liver in and liver from and NAFLD Liver is a of the liver that increases with fibrosis as as as inflammation, and (eg, is the most used to assess liver and can be used to exclude significant hepatic A recent that a liver can be used to advanced fibrosis, used by and may be associated with NASH, and is associated with a high likelihood of advanced fibrosis, the is in liver may also be in disease that an in liver of on either or may be associated with disease progression and clinical patients with cirrhosis, a with a and by had a of an will some patients with to of these of points to exclude advanced fibrosis and high points to identify advanced fibrosis may be used more points for and are but not been with the more on is more than in the of fibrosis stage and is to be the most of fibrosis in Although is not a to risk stratification in a with NAFLD, it can be an important clinical is a for or when are patients with cirrhosis, by risk of hepatic and The of that with the stage of fibrosis is by is of the Liver by may also be to assess the risk of of and associated with risk of hepatic or that the for by and are but the are provided of these with a of and that associated with and risk of over of a in liver is associated with a higher risk of as as Although more are NIT in patients with may be as for in response to study for the of “at-risk” NASH and biomarkers are study for the of NASH, but these not the level of clinical evidence for in clinical practice. of biomarkers including and and and and biomarkers are in for “at-risk” as may also be for the of “at-risk” an of the this in not been and over remains to be that clinical with liver that may be of are The is a from liver and by and for the of “at-risk” with study on and a with has been to be to A with has been linked to increased risk of hepatic decompensation, and a negative with has a negative for a risk of hepatic A from and is also to identify “at-risk” as a on and may be but of over the over to be and the of in on the context of Although can hepatic it is not as a to identify hepatic steatosis to the NAFLD as a may be used to identify can additionally is or may be used to exclude advanced Key liver and can predict an increased risk of hepatic and AND of NAFLD should of of and staging of fibrosis assess these with a should be at in but in and are also the spectrum of

Urine provides an alternative to blood plasma as a potential source of disease biomarkers. One urinary biomarker already exploited in clinical studies is aquaporin-2. However, it remains a mystery how aquaporin-2 (an integral membrane protein) and other apical transporters are delivered to the urine. Here we address the hypothesis that these proteins reach the urine through the secretion of exosomes [membrane vesicles that originate as internal vesicles of multivesicular bodies (MVBs)]. Low-density urinary membrane vesicles from normal human subjects were isolated by differential centrifugation. ImmunoGold electron microscopy using antibodies directed to cytoplasmic or anticytoplasmic epitopes revealed that the vesicles are oriented "cytoplasmic-side inward," consistent with the unique orientation of exosomes. The vesicles were small (<100 nm), consistent with studies of MVBs and exosomes from other tissues. Proteomic analysis of urinary vesicles through nanospray liquid chromatography-tandem mass spectrometry identified numerous protein components of MVBs and of the endosomal pathway in general. Full liquid chromatography-tandem MS analysis revealed 295 proteins, including multiple protein products of genes already known to be responsible for renal and systemic diseases, including autosomal dominant polycystic kidney disease, Gitelman syndrome, Bartter syndrome, autosomal recessive syndrome of osteopetrosis with renal tubular acidosis, and familial renal hypomagnesemia. The results indicate that exosome isolation may provide an efficient first step in biomarker discovery in urine.

Fatty liver disease that develops in the absence of alcohol abuse is recognized increasingly as a major health burden. This report summarizes the presentations and discussions at a Single Topic Conference held September 20-22, 2002, and sponsored by the American Association for the Study of Liver Diseases. The conference focused on fatty liver disorders. Estimates based on imaging and autopsy studies suggest that about 20% to 30% of adults in the United States and other Western countries have excess fat accumulation in the liver. About 10% of these individuals, or fully 2% to 3% of adults, are estimated to meet current diagnostic criteria for nonalcoholic steatohepatitis (NASH). Sustained liver injury leads to progressive fibrosis and cirrhosis in a fraction, possibly up to one third, of those with NASH, and NASH may be a cause of cryptogenic cirrhosis. NASH is now a significant health issue for obese children as well, leading to cirrhosis in some. The diagnostic criteria for NASH continue to evolve and rely on the histologic findings of steatosis, hepatocellular injury (ballooning, Mallory bodies), and the pattern of fibrosis. Generally recognized indications for biopsy include establishing the diagnosis and staging of the injury, but strict guidelines do not exist. Liver enzymes are insensitive and cannot be used reliably to confirm the diagnosis or stage the extent of fibrosis. Older age, obesity, and diabetes are predictive of fibrosis. The pathogenesis of NASH is multifactorial. Insulin resistance may be an important factor in the accumulation of hepatocellular fat, whereas excess intracellular fatty acids, oxidant stress, adenosine triphosphate (ATP) depletion, and mitochondrial dysfunction may be important causes of hepatocellular injury in the steatotic liver. Efforts are underway to refine the role of insulin resistance in NASH and determine whether improving insulin sensitivity pharmacologically is an effective treatment. An altered lifestyle may be a more effective means of improving insulin sensitivity. The research agenda for the future includes establishing the role of insulin resistance and abnormal lipoprotein metabolism in NASH, determining the pathogenesis of cellular injury, defining predisposing genetic abnormalities, identifying better noninvasive predictors of disease, and defining effective therapy.

The cardiovascular complications of acute coronavirus disease 2019 (COVID-19) are well described, but the post-acute cardiovascular manifestations of COVID-19 have not yet been comprehensively characterized. Here we used national healthcare databases from the US Department of Veterans Affairs to build a cohort of 153,760 individuals with COVID-19, as well as two sets of control cohorts with 5,637,647 (contemporary controls) and 5,859,411 (historical controls) individuals, to estimate risks and 1-year burdens of a set of pre-specified incident cardiovascular outcomes. We show that, beyond the first 30 d after infection, individuals with COVID-19 are at increased risk of incident cardiovascular disease spanning several categories, including cerebrovascular disorders, dysrhythmias, ischemic and non-ischemic heart disease, pericarditis, myocarditis, heart failure and thromboembolic disease. These risks and burdens were evident even among individuals who were not hospitalized during the acute phase of the infection and increased in a graded fashion according to the care setting during the acute phase (non-hospitalized, hospitalized and admitted to intensive care). Our results provide evidence that the risk and 1-year burden of cardiovascular disease in survivors of acute COVID-19 are substantial. Care pathways of those surviving the acute episode of COVID-19 should include attention to cardiovascular health and disease.

Cholinergic synapses are ubiquitous in the human central nervous system. Their high density in the thalamus, striatum, limbic system, and neocortex suggest that cholinergic transmission is likely to be critically important for memory, learning, attention and other higher brain functions. Several lines of research suggest additional roles for cholinergic systems in overall brain homeostasis and plasticity. As such, the brain's cholinergic system occupies a central role in ongoing research related to normal cognition and age-related cognitive decline, including dementias such as Alzheimer's disease. The cholinergic hypothesis of Alzheimer's disease centres on the progressive loss of limbic and neocortical cholinergic innervation. Neurofibrillary degeneration in the basal forebrain is believed to be the primary cause for the dysfunction and death of forebrain cholinergic neurons, giving rise to a widespread presynaptic cholinergic denervation. Cholinesterase inhibitors increase the availability of acetylcholine at synapses in the brain and are one of the few drug therapies that have been proven clinically useful in the treatment of Alzheimer's disease dementia, thus validating the cholinergic system as an important therapeutic target in the disease. This review includes an overview of the role of the cholinergic system in cognition and an updated understanding of how cholinergic deficits in Alzheimer's disease interact with other aspects of disease pathophysiology, including plaques composed of amyloid-β proteins. This review also documents the benefits of cholinergic therapies at various stages of Alzheimer's disease and during long-term follow-up as visualized in novel imaging studies. The weight of the evidence supports the continued value of cholinergic drugs as a standard, cornerstone pharmacological approach in Alzheimer's disease, particularly as we look ahead to future combination therapies that address symptoms as well as disease progression.

OBJECTIVES: The Mini-Cog, a composite of three-item recall and clock drawing, was developed as a brief test for discriminating demented from non-demented persons in a community sample of culturally, linguistically, and educationally heterogeneous older adults. SUBJECTS: All 129 who met criteria for probable dementia based on informant interviews and 120 with no history of cognitive decline were included; 124 were non-English speakers. METHODS: Sensitivity, specificity, and diagnostic value of the Mini-Cog were compared with those of the Mini-Mental State Exam (MMSE) and Cognitive Abilities Screening Instrument (CASI). RESULTS: The Mini-Cog had the highest sensitivity (99%) and correctly classified the greatest percentage (96%) of subjects. Moreover, its diagnostic value was not influenced by education or language, while that of the CASI was adversely influenced by low education, and both education and language compromised the diagnostic value of the MMSE. Administration time for the Mini-Cog was 3 minutes vs 7 minutes for the MMSE. CONCLUSIONS: The Mini-Cog required minimal language interpretation and training to administer, and no test forms of scoring modifications were needed to compensate for the extensive linguistic and educational heterogeneity of the sample. Validation in clinical and population-based samples is warranted, as its brevity and ease of administration suggest that the Mini-Cog might be readily incorporated into general practice and senior care settings as a routine 'cognitive vital signs' measure.

The design of clinical trials in hepatocellular carcinoma (HCC) is complex because many patients have concurrent liver disease, which can confound the assessment of clinical benefit. There is an urgent need for high-quality trials in this disease. An expert panel was convened by the American Association for the Study of Liver Diseases to develop guidelines that provide a common framework for designing trials to facilitate comparability of results. According to these guidelines, randomized phase 2 trials with a time-to-event primary endpoint, such as time to progression, are pivotal in clinical research on HCC. Survival remains the main endpoint to measure effectiveness in phase 3 studies, whereas time to recurrence is proposed as an appropriate endpoint in the adjuvant setting. Because progression-free survival and disease-free survival are composite endpoints, they are more vulnerable than others in HCC clinical studies and may not be able to capture clinical benefits. Selection of the target population should be based on the Barcelona Clinic Liver Cancer staging system. New drugs should be tested in patients with well-preserved liver function (Child-Pugh A class). Patients assigned to the control arm should receive standard-of-care therapy, that is, chemoembolization for patients with intermediate-stage disease and sorafenib for patients with advanced-stage disease. Further research is needed to incorporate biomarkers and molecular imaging into clinical research in HCC. These surrogate markers may help to enrich study populations and maximize the cost-benefit ratio of trial execution. Design and conduct of phase 3 trials should be coordinated by centers with appropriate expertise in HCC.

BACKGROUND: In patients with chronic infection with hepatitis C virus (HCV) genotype 1 who do not have a sustained response to therapy with peginterferon-ribavirin, outcomes after retreatment are suboptimal. Boceprevir, a protease inhibitor that binds to the HCV nonstructural 3 (NS3) active site, has been suggested as an additional treatment. METHODS: To assess the effect of the combination of boceprevir and peginterferon-ribavirin for retreatment of patients with chronic HCV genotype 1 infection, we randomly assigned patients (in a 1:2:2 ratio) to one of three groups. In all three groups, peginterferon alfa-2b and ribavirin were administered for 4 weeks (the lead-in period). Subsequently, group 1 (control group) received placebo plus peginterferon-ribavirin for 44 weeks; group 2 received boceprevir plus peginterferon-ribavirin for 32 weeks, and patients with a detectable HCV RNA level at week 8 received placebo plus peginterferon-ribavirin for an additional 12 weeks; and group 3 received boceprevir plus peginterferon-ribavirin for 44 weeks. RESULTS: A total of 403 patients were treated. The rate of sustained virologic response was significantly higher in the two boceprevir groups (group 2, 59%; group 3, 66%) than in the control group (21%, P<0.001). Among patients with an undetectable HCV RNA level at week 8, the rate of sustained virologic response was 86% after 32 weeks of triple therapy and 88% after 44 weeks of triple therapy. Among the 102 patients with a decrease in the HCV RNA level of less than 1 log(10) IU per milliliter at treatment week 4, the rates of sustained virologic response were 0%, 33%, and 34% in groups 1, 2, and 3, respectively. Anemia was significantly more common in the boceprevir groups than in the control group, and erythropoietin was administered in 41 to 46% of boceprevir-treated patients and 21% of controls. CONCLUSIONS: The addition of boceprevir to peginterferon-ribavirin resulted in significantly higher rates of sustained virologic response in previously treated patients with chronic HCV genotype 1 infection, as compared with peginterferon-ribavirin alone. (Funded by Schering-Plough [now Merck]; HCV RESPOND-2 ClinicalTrials.gov number, NCT00708500.).

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language processing, cybersecurity, and many others. This survey presents a brief survey on the advances that have occurred in the area of Deep Learning (DL), starting with the Deep Neural Network (DNN). The survey goes on to cover Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Auto-Encoder (AE), Deep Belief Network (DBN), Generative Adversarial Network (GAN), and Deep Reinforcement Learning (DRL). Additionally, we have discussed recent developments, such as advanced variant DL techniques based on these DL approaches. This work considers most of the papers published after 2012 from when the history of deep learning began. Furthermore, DL approaches that have been explored and evaluated in different application domains are also included in this survey. We also included recently developed frameworks, SDKs, and benchmark datasets that are used for implementing and evaluating deep learning approaches. There are some surveys that have been published on DL using neural networks and a survey on Reinforcement Learning (RL). However, those papers have not discussed individual advanced techniques for training large-scale deep learning models and the recently developed method of generative models.

Psychologists, economists, and advertising moguls have long known that human decision-making is strongly influenced by the behavior of others. A rapidly accumulating body of evidence suggests that the same is true in animals. Individuals can use information arising from cues inadvertently produced by the behavior of other individuals with similar requirements. Many of these cues provide public information about the quality of alternatives. The use of public information is taxonomically widespread and can enhance fitness. Public information can lead to cultural evolution, which we suggest may then affect biological evolution.

Nonhuman primates, our closest biological relatives, play important roles in the livelihoods, cultures, and religions of many societies and offer unique insights into human evolution, biology, behavior, and the threat of emerging diseases. They are an essential component of tropical biodiversity, contributing to forest regeneration and ecosystem health. Current information shows the existence of 504 species in 79 genera distributed in the Neotropics, mainland Africa, Madagascar, and Asia. Alarmingly, ~60% of primate species are now threatened with extinction and ~75% have declining populations. This situation is the result of escalating anthropogenic pressures on primates and their habitats-mainly global and local market demands, leading to extensive habitat loss through the expansion of industrial agriculture, large-scale cattle ranching, logging, oil and gas drilling, mining, dam building, and the construction of new road networks in primate range regions. Other important drivers are increased bushmeat hunting and the illegal trade of primates as pets and primate body parts, along with emerging threats, such as climate change and anthroponotic diseases. Often, these pressures act in synergy, exacerbating primate population declines. Given that primate range regions overlap extensively with a large, and rapidly growing, human population characterized by high levels of poverty, global attention is needed immediately to reverse the looming risk of primate extinctions and to attend to local human needs in sustainable ways. Raising global scientific and public awareness of the plight of the world's primates and the costs of their loss to ecosystem health and human society is imperative.

The last quarter century witnessed significant population growth, aging, and major changes in epidemiologic trends, which may have shaped the state of chronic kidney disease (CKD) epidemiology. Here, we used the Global Burden of Disease study data and methodologies to describe the change in burden of CKD from 1990 to 2016 involving incidence, prevalence, death, and disability-adjusted-life-years (DALYs). Globally, the incidence of CKD increased by 89% to 21,328,972 (uncertainty interval 19,100,079- 23,599,380), prevalence increased by 87% to 275,929,799 (uncertainty interval 252,442,316-300,414,224), death due to CKD increased by 98% to 1,186,561 (uncertainty interval 1,150,743-1,236,564), and DALYs increased by 62% to 35,032,384 (uncertainty interval 32,622,073-37,954,350). Measures of burden varied substantially by level of development and geography. Decomposition analyses showed that the increase in CKD DALYs was driven by population growth and aging. Globally and in most Global Burden of Disease study regions, age-standardized DALY rates decreased, except in High-income North America, Central Latin America, Oceania, Southern Sub-Saharan Africa, and Central Asia, where the increased burden of CKD due to diabetes and to a lesser extent CKD due to hypertension and other causes outpaced burden expected by demographic expansion. More of the CKD burden (63%) was in low and lower-middle-income countries. There was an inverse relationship between age-standardized CKD DALY rate and health care access and quality of care. Frontier analyses showed significant opportunities for improvement at all levels of the development spectrum. Thus, the global toll of CKD is significant, rising, and unevenly distributed; it is primarily driven by demographic expansion and in some regions a significant tide of diabetes. Opportunities exist to reduce CKD burden at all levels of development.