First Affiliated Hospital of Anhui Medical University

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,

Abstract Objective To assess the prevalence of diabetes and its risk factors. Design Population based, cross sectional study. Setting 31 provinces in mainland China with nationally representative cross sectional data from 2015 to 2017. Participants 75 880 participants aged 18 and older—a nationally representative sample of the mainland Chinese population. Main outcome measures Prevalence of diabetes among adults living in China, and the prevalence by sex, regions, and ethnic groups, estimated by the 2018 American Diabetes Association (ADA) and the World Health Organization diagnostic criteria. Demographic characteristics, lifestyle, and history of disease were recorded by participants on a questionnaire. Anthropometric and clinical assessments were made of serum concentrations of fasting plasma glucose (one measurement), two hour plasma glucose, and glycated haemoglobin (HbA 1c ). Results The weighted prevalence of total diabetes (n=9772), self-reported diabetes (n=4464), newly diagnosed diabetes (n=5308), and prediabetes (n=27 230) diagnosed by the ADA criteria were 12.8% (95% confidence interval 12.0% to 13.6%), 6.0% (5.4% to 6.7%), 6.8% (6.1% to 7.4%), and 35.2% (33.5% to 37.0%), respectively, among adults living in China. The weighted prevalence of total diabetes was higher among adults aged 50 and older and among men. The prevalence of total diabetes in 31 provinces ranged from 6.2% in Guizhou to 19.9% in Inner Mongolia. Han ethnicity had the highest prevalence of diabetes (12.8%) and Hui ethnicity had the lowest (6.3%) among five investigated ethnicities. The weighted prevalence of total diabetes (n=8385) using the WHO criteria was 11.2% (95% confidence interval 10.5% to 11.9%). Conclusion The prevalence of diabetes has increased slightly from 2007 to 2017 among adults living in China. The findings indicate that diabetes is an important public health problem in China.

The role of clinical laboratory data in the differential diagnosis of the severe forms of COVID-19 has not been definitely established. The aim of this study was to look for the warning index in severe COVID-19 patients. We investigated 43 adult patients with COVID-19. The patients were classified into mild group (28 patients) and severe group (15 patients). A comparison of the hematological parameters between the mild and severe groups showed significant differences in interleukin-6 (IL-6), d-dimer (d-D), glucose, thrombin time, fibrinogen, and C-reactive protein (P < .05). The optimal threshold and area under the receiver operator characteristic curve (ROC) of IL-6 were 24.3 and 0.795 µg/L, respectively, while those of d-D were 0.28 and 0.750 µg/L, respectively. The area under the ROC curve of IL-6 combined with d-D was 0.840. The specificity of predicting the severity of COVID-19 during IL-6 and d-D tandem testing was up to 93.3%, while the sensitivity of IL-6 and d-D by parallel test in the severe COVID-19 was 96.4%. IL-6 and d-D were closely related to the occurrence of severe COVID-19 in the adult patients, and their combined detection had the highest specificity and sensitivity for early prediction of the severity of COVID-19 patients, which has important clinical value.

BACKGROUND: In acute ischemic stroke, there is uncertainty regarding the benefit and risk of administering intravenous alteplase before endovascular thrombectomy. METHODS: We conducted a trial at 41 academic tertiary care centers in China to evaluate endovascular thrombectomy with or without intravenous alteplase in patients with acute ischemic stroke. Patients with acute ischemic stroke from large-vessel occlusion in the anterior circulation were randomly assigned in a 1:1 ratio to undergo endovascular thrombectomy alone (thrombectomy-alone group) or endovascular thrombectomy preceded by intravenous alteplase, at a dose of 0.9 mg per kilogram of body weight, administered within 4.5 hours after symptom onset (combination-therapy group). The primary analysis for noninferiority assessed the between-group difference in the distribution of the modified Rankin scale scores (range, 0 [no symptoms] to 6 [death]) at 90 days on the basis of a lower boundary of the 95% confidence interval of the adjusted common odds ratio equal to or larger than 0.8. We assessed various secondary outcomes, including death and reperfusion of the ischemic area. RESULTS: Of 1586 patients screened, 656 were enrolled, with 327 patients assigned to the thrombectomy-alone group and 329 assigned to the combination-therapy group. Endovascular thrombectomy alone was noninferior to combined intravenous alteplase and endovascular thrombectomy with regard to the primary outcome (adjusted common odds ratio, 1.07; 95% confidence interval, 0.81 to 1.40; P = 0.04 for noninferiority) but was associated with lower percentages of patients with successful reperfusion before thrombectomy (2.4% vs. 7.0%) and overall successful reperfusion (79.4% vs. 84.5%). Mortality at 90 days was 17.7% in the thrombectomy-alone group and 18.8% in the combination-therapy group. CONCLUSIONS: In Chinese patients with acute ischemic stroke from large-vessel occlusion, endovascular thrombectomy alone was noninferior with regard to functional outcome, within a 20% margin of confidence, to endovascular thrombectomy preceded by intravenous alteplase administered within 4.5 hours after symptom onset. (Funded by the Stroke Prevention Project of the National Health Commission of the People's Republic of China and the Wu Jieping Medical Foundation; DIRECT-MT ClinicalTrials.gov number, NCT03469206.).

BACKGROUND: The transfer of fresh embryos is generally preferred over the transfer of frozen embryos for in vitro fertilization (IVF), but some evidence suggests that frozen-embryo transfer may improve the live-birth rate and lower the rates of the ovarian hyperstimulation syndrome and pregnancy complications in women with the polycystic ovary syndrome. METHODS: In this multicenter trial, we randomly assigned 1508 infertile women with the polycystic ovary syndrome who were undergoing their first IVF cycle to undergo either fresh-embryo transfer or embryo cryopreservation followed by frozen-embryo transfer. After 3 days of embryo development, women underwent the transfer of up to two fresh or frozen embryos. The primary outcome was a live birth after the first embryo transfer. RESULTS: Frozen-embryo transfer resulted in a higher frequency of live birth after the first transfer than did fresh-embryo transfer (49.3% vs. 42.0%), for a rate ratio of 1.17 (95% confidence interval [CI], 1.05 to 1.31; P=0.004). Women who underwent frozen-embryo transfer also had a lower frequency of pregnancy loss (22.0% vs. 32.7%), for a rate ratio of 0.67 (95% CI, 0.54 to 0.83; P<0.001), and of the ovarian hyperstimulation syndrome (1.3% vs. 7.1%), for a rate ratio of 0.19 (95% CI, 0.10 to 0.37; P<0.001), but a higher frequency of preeclampsia (4.4% vs. 1.4%), for a rate ratio of 3.12 (95% CI, 1.26 to 7.73; P=0.009). There were no significant between-group differences in rates of other pregnancy and neonatal complications. There were five neonatal deaths in the frozen-embryo group and none in the fresh-embryo group (P=0.06). CONCLUSIONS: Among infertile women with the polycystic ovary syndrome, frozen-embryo transfer was associated with a higher rate of live birth, a lower risk of the ovarian hyperstimulation syndrome, and a higher risk of preeclampsia after the first transfer than was fresh-embryo transfer. (Funded by the National Basic Research Program of China and others; ClinicalTrials.gov number, NCT01841528.).

Importance: Standard first-line therapy for advanced or metastatic esophageal carcinoma is chemotherapy, but the prognosis remains poor. Camrelizumab (an anti-programmed death receptor 1 [PD-1] antibody) showed antitumor activity in previously treated advanced or metastatic esophageal squamous cell carcinoma. Objective: To evaluate the efficacy and adverse events of camrelizumab plus chemotherapy vs placebo plus chemotherapy as a first-line treatment in advanced or metastatic esophageal squamous cell carcinoma. Design, Setting, and Participants: This randomized, double-blind, placebo-controlled, multicenter, phase 3 trial (ESCORT-1st study) enrolled patients from 60 hospitals in China between December 3, 2018, and May 12, 2020 (final follow-up, October 30, 2020). A total of 751 patients were screened and 596 eligible patients with untreated advanced or metastatic esophageal squamous cell carcinoma were randomized. Interventions: Patients were randomized 1:1 to receive either camrelizumab 200 mg (n = 298) or placebo (n = 298), combined with up to 6 cycles of paclitaxel (175 mg/m2) and cisplatin (75 mg/m2). All treatments were given intravenously every 3 weeks. Main Outcomes and Measures: Coprimary end points were overall survival (significance threshold, 1-sided P < .02) and progression-free survival (significance threshold, 1-sided P < .005). Results: Of the 596 patients randomized (median age, 62 years [interquartile range, 56-67 years]; 523 men [87.8%]), 1 patient in the placebo-chemotherapy group did not receive planned treatment. A total of 490 patients (82.2%) had discontinued the study treatment. The median follow-up was 10.8 months. The overall survival for the camrelizumab-chemotherapy group was a median of 15.3 months (95% CI, 12.8-17.3; 135 deaths) vs a median of 12.0 months (95% CI, 11.0-13.3; 174 deaths) for the placebo-chemotherapy group (hazard ratio [HR] for death, 0.70 [95% CI, 0.56-0.88]; 1-sided P = .001). Progression-free survival for camrelizumab plus chemotherapy was a median of 6.9 months (95% CI, 5.8-7.4; 199 progression or deaths) vs 5.6 months (95% CI, 5.5-5.7; 229 progression or deaths) for the placebo-chemotherapy group (HR for progression or death, 0.56 [95% CI, 0.46-0.68]; 1-sided P < .001). Treatment-related adverse events of grade 3 or higher occurred in 189 patients (63.4%) in the camrelizumab-chemotherapy group and 201 (67.7%) in the placebo-chemotherapy group, including treatment-related deaths among 9 patients (3.0%) and 11 patients (3.7%), respectively. Conclusions and Relevance: Among patients with advanced or metastatic esophageal squamous cell carcinoma, the addition of camrelizumab to chemotherapy, compared with placebo and chemotherapy, significantly improved overall survival and progression-free survival. Trial Registration: ClinicalTrials.gov Identifier: NCT03691090.

IMPORTANCE: Uncertainty remains about the efficacy of folic acid therapy for the primary prevention of stroke because of limited and inconsistent data. OBJECTIVE: To test the primary hypothesis that therapy with enalapril and folic acid is more effective in reducing first stroke than enalapril alone among Chinese adults with hypertension. DESIGN, SETTING, AND PARTICIPANTS: The China Stroke Primary Prevention Trial, a randomized, double-blind clinical trial conducted from May 19, 2008, to August 24, 2013, in 32 communities in Jiangsu and Anhui provinces in China. A total of 20,702 adults with hypertension without history of stroke or myocardial infarction (MI) participated in the study. INTERVENTIONS: Eligible participants, stratified by MTHFR C677T genotypes (CC, CT, and TT), were randomly assigned to receive double-blind daily treatment with a single-pill combination containing enalapril, 10 mg, and folic acid, 0.8 mg (n = 10,348) or a tablet containing enalapril, 10 mg, alone (n = 10,354). MAIN OUTCOMES AND MEASURES: The primary outcome was first stroke. Secondary outcomes included first ischemic stroke; first hemorrhagic stroke; MI; a composite of cardiovascular events consisting of cardiovascular death, MI, and stroke; and all-cause death. RESULTS: During a median treatment duration of 4.5 years, compared with the enalapril alone group, the enalapril-folic acid group had a significant risk reduction in first stroke (2.7% of participants in the enalapril-folic acid group vs 3.4% in the enalapril alone group; hazard ratio [HR], 0.79; 95% CI, 0.68-0.93), first ischemic stroke (2.2% with enalapril-folic acid vs 2.8% with enalapril alone; HR, 0.76; 95% CI, 0.64-0.91), and composite cardiovascular events consisting of cardiovascular death, MI, and stroke (3.1% with enalapril-folic acid vs 3.9% with enalapril alone; HR, 0.80; 95% CI, 0.69-0.92). The risks of hemorrhagic stroke (HR, 0.93; 95% CI, 0.65-1.34), MI (HR, 1.04; 95% CI, 0.60-1.82), and all-cause deaths (HR, 0.94; 95% CI, 0.81-1.10) did not differ significantly between the 2 treatment groups. There were no significant differences between the 2 treatment groups in the frequencies of adverse events. CONCLUSIONS AND RELEVANCE: Among adults with hypertension in China without a history of stroke or MI, the combined use of enalapril and folic acid, compared with enalapril alone, significantly reduced the risk of first stroke. These findings are consistent with benefits from folate use among adults with hypertension and low baseline folate levels. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00794885.

Transforming growth factor-beta1 (TGF-β1), a key member in the TGF-β superfamily, plays a critical role in the development of hepatic fibrosis. Its expression is consistently elevated in affected organs, which correlates with increased extracellular matrix deposition. SMAD proteins have been studied extensively as pivotal intracellular effectors of TGF-β1, acting as transcription factors. In the context of hepatic fibrosis, SMAD3 and SMAD4 are pro-fibrotic, whereas SMAD2 and SMAD7 are protective. Deletion of SMAD3 inhibits type I collagen expression and blocks epithelial-myofibroblast transition. In contrast, disruption of SMAD2 upregulates type I collagen expression. SMAD4 plays an essential role in fibrosis disease by enhancing SMAD3 responsive promoter activity, whereas SMAD7 negatively mediates SMAD3-induced fibrogenesis. Accumulating evidence suggests that divergent miRNAs participate in the liver fibrotic process, which partially regulates members of the TGF-β/SMAD signaling pathway. In this review, we focus on the TGF-β/SMAD and other relative signaling pathways, and discussed the role and molecular mechanisms of TGF-β/SMAD in the pathogenesis of hepatic fibrosis. Moreover, we address the possibility of novel therapeutic approaches to hepatic fibrosis by targeting to TGF-β/SMAD signaling.

BACKGROUND: With the advent of second-generation sequencing, the expression of gene transcripts can be digitally measured with high accuracy. The purpose of this study was to systematically profile the expression of both mRNA and miRNA genes in clear cell renal cell carcinoma (ccRCC) using massively parallel sequencing technology. METHODOLOGY: The expression of mRNAs and miRNAs were analyzed in tumor tissues and matched normal adjacent tissues obtained from 10 ccRCC patients without distant metastases. In a prevalence screen, some of the most interesting results were validated in a large cohort of ccRCC patients. PRINCIPAL FINDINGS: A total of 404 miRNAs and 9,799 mRNAs were detected to be differentially expressed in the 10 ccRCC patients. We also identified 56 novel miRNA candidates in at least two samples. In addition to confirming that canonical cancer genes and miRNAs (including VEGFA, DUSP9 and ERBB4; miR-210, miR-184 and miR-206) play pivotal roles in ccRCC development, promising novel candidates (such as PNCK and miR-122) without previous annotation in ccRCC carcinogenesis were also discovered in this study. Pathways controlling cell fates (e.g., cell cycle and apoptosis pathways) and cell communication (e.g., focal adhesion and ECM-receptor interaction) were found to be significantly more likely to be disrupted in ccRCC. Additionally, the results of the prevalence screen revealed that the expression of a miRNA gene cluster located on Xq27.3 was consistently downregulated in at least 76.7% of ∼50 ccRCC patients. CONCLUSIONS: Our study provided a two-dimensional map of the mRNA and miRNA expression profiles of ccRCC using deep sequencing technology. Our results indicate that the phenotypic status of ccRCC is characterized by a loss of normal renal function, downregulation of metabolic genes, and upregulation of many signal transduction genes in key pathways. Furthermore, it can be concluded that downregulation of miRNA genes clustered on Xq27.3 is associated with ccRCC.

PURPOSE: We assessed the efficacy and safety of camrelizumab [an anti-programmed death (PD-1) mAb] plus apatinib (a VEGFR-2 tyrosine kinase inhibitor) in patients with advanced hepatocellular carcinoma (HCC). PATIENTS AND METHODS: This nonrandomized, open-label, multicenter, phase II study enrolled patients with advanced HCC who were treatment-naïve or refractory/intolerant to first-line targeted therapy. Patients received intravenous camrelizumab 200 mg (for bodyweight ≥50 kg) or 3 mg/kg (for bodyweight <50 kg) every 2 weeks plus oral apatinib 250 mg daily. The primary endpoint was objective response rate (ORR) assessed by an independent review committee (IRC) per RECIST v1.1. RESULTS: Seventy patients in the first-line setting and 120 patients in the second-line setting were enrolled. As of January 10, 2020, the ORR was 34.3% [24/70; 95% confidence interval (CI), 23.3-46.6] in the first-line and 22.5% (27/120; 95% CI, 15.4-31.0) in the second-line cohort per IRC. Median progression-free survival in both cohorts was 5.7 months (95% CI, 5.4-7.4) and 5.5 months (95% CI, 3.7-5.6), respectively. The 12-month survival rate was 74.7% (95% CI, 62.5-83.5) and 68.2% (95% CI, 59.0-75.7), respectively. Grade ≥3 treatment-related adverse events (TRAE) were reported in 147 (77.4%) of 190 patients, with the most common being hypertension (34.2%). Serious TRAEs occurred in 55 (28.9%) patients. Two (1.1%) treatment-related deaths occurred. CONCLUSIONS: .

Abstract Hypoxia of solid tumor compromises the therapeutic outcome of photodynamic therapy (PDT) that relies on localized O 2 molecules to produce highly cytotoxic singlet oxygen ( 1 O 2 ) species. Herein, we present a safe and versatile self-assembled PDT nanoagent, i.e., OxgeMCC-r single-atom enzyme (SAE), consisting of single-atom ruthenium as the active catalytic site anchored in a metal-organic framework Mn 3 [Co(CN) 6 ] 2 with encapsulated chlorin e6 (Ce6), which serves as a catalase-like nanozyme for oxygen generation. Coordination-driven self-assembly of organic linkers and metal ions in the presence of a biocompatible polymer generates a nanoscale network that adaptively encapsulates Ce6. The resulted OxgeMCC-r SAE possesses well-defined morphology, uniform size distribution and high loading capacity. When conducting the in situ O 2 generation through the reaction between endogenous H 2 O 2 and single-atom Ru species of OxgeMCC-r SAE, the hypoxia in tumor microenvironment is relieved. Our study demonstrates a promising self-assembled nanozyme with highly efficient single-atom catalytic sites for cancer treatment.

IMPORTANCE: The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. OBJECTIVE: To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. DATA SOURCES: Genomewide association studies (GWAS) published up to January 15, 2015. STUDY SELECTION: GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. DATA EXTRACTION AND SYNTHESIS: Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. MAIN OUTCOMES AND MEASURES: Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. RESULTS: Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]). CONCLUSIONS AND RELEVANCE: It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented setback for global economy and health. Vaccination is one of the most effective interventions to substantially reduce severe disease and death due to SARS-CoV-2 infection. Vaccination programmes are being rolled out globally, but most of these vaccines have been approved without extensive studies on their side-effects and efficacy. Recently, new-onset autoimmune phenomena after COVID-19 vaccination have been reported increasingly (e.g. immune thrombotic thrombocytopenia, autoimmune liver diseases, Guillain-Barré syndrome, IgA nephropathy, rheumatoid arthritis and systemic lupus erythematosus). Molecular mimicry, the production of particular autoantibodies and the role of certain vaccine adjuvants seem to be substantial contributors to autoimmune phenomena. However, whether the association between COVID-19 vaccine and autoimmune manifestations is coincidental or causal remains to be elucidated. Here, we summarize the emerging evidence about autoimmune manifestations occurring in response to certain COVID-19 vaccines. Although information pertaining to the risk of autoimmune disease as a consequence of vaccination is controversial, we merely propose our current understanding of autoimmune manifestations associated with COVID-19 vaccine. In fact, we do not aim to disavow the overwhelming benefits of mass COVID-19 vaccination in preventing COVID-19 morbidity and mortality. These reports could help guide clinical assessment and management of autoimmune manifestations after COVID-19 vaccination.

Zhiming Cai and colleagues report whole-genome and whole-exome sequencing of 99 paired tumor-normal samples of transitional cell carcinoma of the bladder. They find that 32% of tumors harbor alterations in genes involved in sister chromatid cohesion, including STAG2, ESPL1, NIPBL, SMC1A and SMC3. Bladder cancer is one of the most common cancers worldwide, with transitional cell carcinoma (TCC) being the predominant form. Here we report a genomic analysis of TCC by both whole-genome and whole-exome sequencing of 99 individuals with TCC. Beyond confirming recurrent mutations in genes previously identified as being mutated in TCC, we identified additional altered genes and pathways that were implicated in TCC. Notably, we discovered frequent alterations in STAG2 and ESPL1, two genes involved in the sister chromatid cohesion and segregation (SCCS) process. Furthermore, we also detected a recurrent fusion involving FGFR3 and TACC3, another component of SCCS, by transcriptome sequencing of 42 DNA-sequenced tumors. Overall, 32 of the 99 tumors (32%) harbored genetic alterations in the SCCS process. Our analysis provides evidence that genetic alterations affecting the SCCS process may be involved in bladder tumorigenesis and identifies a new therapeutic possibility for bladder cancer.

Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with worse prognosis for early prevention and medical resource optimisation is important. Here, we proposed a fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis by routinely used computed tomography.We retrospectively collected 5372 patients with computed tomography images from seven cities or provinces. Firstly, 4106 patients with computed tomography images were used to pre-train the deep learning system, making it learn lung features. Following this, 1266 patients (924 with COVID-19 (471 had follow-up for >5 days) and 342 with other pneumonia) from six cities or provinces were enrolled to train and externally validate the performance of the deep learning system.In the four external validation sets, the deep learning system achieved good performance in identifying COVID-19 from other pneumonia (AUC 0.87 and 0.88, respectively) and viral pneumonia (AUC 0.86). Moreover, the deep learning system succeeded to stratify patients into high- and low-risk groups whose hospital-stay time had significant difference (p=0.013 and p=0.014, respectively). Without human assistance, the deep learning system automatically focused on abnormal areas that showed consistent characteristics with reported radiological findings.Deep learning provides a convenient tool for fast screening of COVID-19 and identifying potential high-risk patients, which may be helpful for medical resource optimisation and early prevention before patients show severe symptoms.

Abstract The dysregulation of NLRP3 inflammasome can cause uncontrolled inflammation and drive the development of a wide variety of human diseases, but the medications targeting NLRP3 inflammasome are not available in clinic. Here, we show that tranilast (TR), an old anti‐allergic clinical drug, is a direct NLRP3 inhibitor. TR inhibits NLRP3 inflammasome activation in macrophages, but has no effects on AIM2 or NLRC4 inflammasome activation. Mechanismly, TR directly binds to the NACHT domain of NLRP3 and suppresses the assembly of NLRP3 inflammasome by blocking NLRP3 oligomerization. In vivo experiments show that TR has remarkable preventive or therapeutic effects on the mouse models of NLRP3 inflammasome‐related human diseases, including gouty arthritis, cryopyrin‐associated autoinflammatory syndromes, and type 2 diabetes. Furthermore, TR is active ex vivo for synovial fluid mononuclear cells from patients with gout. Thus, our study identifies the old drug TR as a direct NLRP3 inhibitor and provides a potentially practical pharmacological approach for treating NLRP3‐driven diseases.

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

Currently, detecting SARS-CoV-2 RNAs is a standard approach for COVID-19 diagnosis. However, there is an urgent need for reliable and rapid serological diagnostic methods to screen SARS-CoV-2infected people including those who do not have overt symptoms. ]

BACKGROUND: The majority of the prostatic cancers are adenocarcinomas characterized by glandular formation and the expression of luminal differentiation markers androgen receptor (AR) and prostate-specific antigen (PSA). Most adenocarcinomas are indolent and androgen-dependent. Hormonal therapy that inhibits AR signaling produces symptomatic relief in patients with advanced and metastatic adenocarcinomas. Prostatic small cell neuroendocrine carcinoma (SCNC) is a variant form of prostate cancer (PC). In contrast to adenocarcinoma, the tumor cells of SCNC do not form glands and are negative for AR and PSA. SCNC is extremely aggressive and does not respond to hormonal therapy. The purpose of this study was to compare the important and relevant features of two most commonly used PC cell lines, LNCaP and PC3, with prostatic adenocarcinoma and SCNC. METHODS: Xenograft tumors of LNCaP and PC3 were prepared and compared with human prostatic adenocarcinoma and SCNC for the expression of key signaling molecules by immunohistochemistry and Western blot analysis. RESULTS: LNCaP cells express AR and PSA and their growth is inhibited by androgen withdrawal, similar to human prostatic adenocarcinoma. PC3 cells do not express AR and PSA and their proliferation is independent of androgen, similar to SCNC. Adenocarcinoma cells and LNCaP cells are negative for neuroendocrine markers and stem cell-associated marker CD44 while SCNC and PC3 cells are positive. LNCaP cells have identical cytokeratin profiles to adenocarcinoma while PC3 cells have cytokeratin profiles similar to SCNC. CONCLUSION: LNCaP cells share common features with adenocarcinoma while PC3 cells are characteristic of SCNC.

Long noncoding RNAs (lncRNAs) are RNAs longer than 200 nt in length that are characterized by low levels of sequence conservation and expression; lncRNAs modulate various biological functions at epigenetic, transcriptional and post-transcriptional levels, or directly regulate protein activity. As a family of small and evolutionarily conserved noncoding RNAs, microRNAs (miRNAs) are capable of regulating physiological and pathological processes via inhibiting target mRNA translation or promoting mRNA degradation. A number of studies have confirmed that both lncRNAs and miRNAs are closely associated with the development of cardiovascular diseases (CVDs), such as cardiac remodelling, heart failure, myocardial injury and arrhythmia, and that they act as biomarkers, potential therapeutic targets or strong indicators of prognosis; however, the underlying molecular mechanism has not been elucidated. Recently, emerging evidence showed that the novel regulatory mechanism underlying the crosstalk among lncRNAs, miRNAs and mRNAs plays a pivotal role in the pathophysiological processes of CVDs in response to stress stimuli. In this review, I comprehensively summarized the regulatory relationship of lncRNAs, miRNAs and mRNAs and highlighted the important role of the lncRNA-miRNA-mRNA axis in CVDs.