Shanghai Tenth People's Hospital

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,

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.

Hydrogel is a type of versatile platform with various biomedical applications after rational structure and functional design that leverages on material engineering to modulate its physicochemical properties (e.g., stiffness, pore size, viscoelasticity, microarchitecture, degradability, ligand presentation, stimulus-responsive properties, etc.) and influence cell signaling cascades and fate. In the past few decades, a plethora of pioneering studies have been implemented to explore the cell-hydrogel matrix interactions and figure out the underlying mechanisms, paving the way to the lab-to-clinic translation of hydrogel-based therapies. In this review, we first introduced the physicochemical properties of hydrogels and their fabrication approaches concisely. Subsequently, the comprehensive description and deep discussion were elucidated, wherein the influences of different hydrogels properties on cell behaviors and cellular signaling events were highlighted. These behaviors or events included integrin clustering, focal adhesion (FA) complex accumulation and activation, cytoskeleton rearrangement, protein cyto-nuclei shuttling and activation (e.g., Yes-associated protein (YAP), catenin, etc.), cellular compartment reorganization, gene expression, and further cell biology modulation (e.g., spreading, migration, proliferation, lineage commitment, etc.). Based on them, current in vitro and in vivo hydrogel applications that mainly covered diseases models, various cell delivery protocols for tissue regeneration and disease therapy, smart drug carrier, bioimaging, biosensor, and conductive wearable/implantable biodevices, etc. were further summarized and discussed. More significantly, the clinical translation potential and trials of hydrogels were presented, accompanied with which the remaining challenges and future perspectives in this field were emphasized. Collectively, the comprehensive and deep insights in this review will shed light on the design principles of new biomedical hydrogels to understand and modulate cellular processes, which are available for providing significant indications for future hydrogel design and serving for a broad range of biomedical applications.

Abstract Innate lymphoid cells (ILCs) and CD4 + T cells produce IL-22, which is critical for intestinal immunity. The microbiota is central to IL-22 production in the intestines; however, the factors that regulate IL-22 production by CD4 + T cells and ILCs are not clear. Here, we show that microbiota-derived short-chain fatty acids (SCFAs) promote IL-22 production by CD4 + T cells and ILCs through G-protein receptor 41 (GPR41) and inhibiting histone deacetylase (HDAC). SCFAs upregulate IL-22 production by promoting aryl hydrocarbon receptor (AhR) and hypoxia-inducible factor 1α (HIF1α) expression, which are differentially regulated by mTOR and Stat3. HIF1α binds directly to the Il22 promoter, and SCFAs increase HIF1α binding to the Il22 promoter through histone modification. SCFA supplementation enhances IL-22 production, which protects intestines from inflammation. SCFAs promote human CD4 + T cell IL-22 production. These findings establish the roles of SCFAs in inducing IL-22 production in CD4 + T cells and ILCs to maintain intestinal homeostasis.

With modern technologies such as microarray, deep sequencing, and liquid chromatography-mass spectrometry (LC-MS), it is possible to measure the expression levels of thousands of genes/proteins simultaneously to unravel important biological processes. A very first step towards elucidating hidden patterns and understanding the massive data is the application of clustering techniques. Nonlinear relations, which were mostly unutilized in contrast to linear correlations, are prevalent in high-throughput data. In many cases, nonlinear relations can model the biological relationship more precisely and reflect critical patterns in the biological systems. Using the general dependency measure, Distance Based on Conditional Ordered List (DCOL) that we introduced before, we designed the nonlinear K-profiles clustering method, which can be seen as the nonlinear counterpart of the K-means clustering algorithm. The method has a built-in statistical testing procedure that ensures genes not belonging to any cluster do not impact the estimation of cluster profiles. Results from extensive simulation studies showed that K-profiles clustering not only outperformed traditional linear K-means algorithm, but also presented significantly better performance over our previous General Dependency Hierarchical Clustering (GDHC) algorithm. We further analyzed a gene expression dataset, on which K-profile clustering generated biologically meaningful results.

BACKGROUND: A patient's infectivity is determined by the presence of the virus in different body fluids, secretions, and excreta. The persistence and clearance of viral RNA from different specimens of patients with 2019 novel coronavirus disease (COVID-19) remain unclear. This study analyzed the clearance time and factors influencing 2019 novel coronavirus (2019-nCoV) RNA in different samples from patients with COVID-19, providing further evidence to improve the management of patients during convalescence. METHODS: The clinical data and laboratory test results of convalescent patients with COVID-19 who were admitted to from January 20, 2020 to February 10, 2020 were collected retrospectively. The reverse transcription polymerase chain reaction (RT-PCR) results for patients' oropharyngeal swab, stool, urine, and serum samples were collected and analyzed. Convalescent patients refer to recovered non-febrile patients without respiratory symptoms who had two successive (minimum 24 h sampling interval) negative RT-PCR results for viral RNA from oropharyngeal swabs. The effects of cluster of differentiation 4 (CD4)+ T lymphocytes, inflammatory indicators, and glucocorticoid treatment on viral nucleic acid clearance were analyzed. RESULTS: In the 292 confirmed cases, 66 patients recovered after treatment and were included in our study. In total, 28 (42.4%) women and 38 men (57.6%) with a median age of 44.0 (34.0-62.0) years were analyzed. After in-hospital treatment, patients' inflammatory indicators decreased with improved clinical condition. The median time from the onset of symptoms to first negative RT-PCR results for oropharyngeal swabs in convalescent patients was 9.5 (6.0-11.0) days. By February 10, 2020, 11 convalescent patients (16.7%) still tested positive for viral RNA from stool specimens and the other 55 patients' stool specimens were negative for 2019-nCoV following a median duration of 11.0 (9.0-16.0) days after symptom onset. Among these 55 patients, 43 had a longer duration until stool specimens were negative for viral RNA than for throat swabs, with a median delay of 2.0 (1.0-4.0) days. Results for only four (6.9%) urine samples were positive for viral nucleic acid out of 58 cases; viral RNA was still present in three patients' urine specimens after throat swabs were negative. Using a multiple linear regression model (F = 2.669, P = 0.044, and adjusted R = 0.122), the analysis showed that the CD4+ T lymphocyte count may help predict the duration of viral RNA detection in patients' stools (t = -2.699, P = 0.010). The duration of viral RNA detection from oropharyngeal swabs and fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (15 days vs. 8.0 days, respectively; t = 2.550, P = 0.013) and the duration of viral RNA detection in fecal samples in the glucocorticoid treatment group was longer than that in the non-glucocorticoid treatment group (20 days vs. 11 days, respectively; t = 4.631, P < 0.001). There was no statistically significant difference in inflammatory indicators between patients with positive fecal viral RNA test results and those with negative results (P > 0.05). CONCLUSIONS: In brief, as the clearance of viral RNA in patients' stools was delayed compared to that in oropharyngeal swabs, it is important to identify viral RNA in feces during convalescence. Because of the delayed clearance of viral RNA in the glucocorticoid treatment group, glucocorticoids are not recommended in the treatment of COVID-19, especially for mild disease. The duration of RNA detection may relate to host cell immunity.

Ubiquitination, an important type of protein posttranslational modification (PTM), plays a crucial role in controlling substrate degradation and subsequently mediates the "quantity" and "quality" of various proteins, serving to ensure cell homeostasis and guarantee life activities. The regulation of ubiquitination is multifaceted and works not only at the transcriptional and posttranslational levels (phosphorylation, acetylation, methylation, etc.) but also at the protein level (activators or repressors). When regulatory mechanisms are aberrant, the altered biological processes may subsequently induce serious human diseases, especially various types of cancer. In tumorigenesis, the altered biological processes involve tumor metabolism, the immunological tumor microenvironment (TME), cancer stem cell (CSC) stemness and so on. With regard to tumor metabolism, the ubiquitination of some key proteins such as RagA, mTOR, PTEN, AKT, c-Myc and P53 significantly regulates the activity of the mTORC1, AMPK and PTEN-AKT signaling pathways. In addition, ubiquitination in the TLR, RLR and STING-dependent signaling pathways also modulates the TME. Moreover, the ubiquitination of core stem cell regulator triplets (Nanog, Oct4 and Sox2) and members of the Wnt and Hippo-YAP signaling pathways participates in the maintenance of CSC stemness. Based on the altered components, including the proteasome, E3 ligases, E1, E2 and deubiquitinases (DUBs), many molecular targeted drugs have been developed to combat cancer. Among them, small molecule inhibitors targeting the proteasome, such as bortezomib, carfilzomib, oprozomib and ixazomib, have achieved tangible success. In addition, MLN7243 and MLN4924 (targeting the E1 enzyme), Leucettamol A and CC0651 (targeting the E2 enzyme), nutlin and MI-219 (targeting the E3 enzyme), and compounds G5 and F6 (targeting DUB activity) have also shown potential in preclinical cancer treatment. In this review, we summarize the latest progress in understanding the substrates for ubiquitination and their special functions in tumor metabolism regulation, TME modulation and CSC stemness maintenance. Moreover, potential therapeutic targets for cancer are reviewed, as are the therapeutic effects of targeted drugs.

BACKGROUND: The aim of this study was to evaluate the ability of dual acridine orange/ethidium bromide (AO/EB) staining to detect tumor cell apoptosis. According to apoptosis-associated changes of cell membranes during the process of apoptosis, a clear distinction is made between normal cells, early and late apoptotic cells, and necrotic cells. MATERIAL AND METHODS: We cultured human osteosarcoma cells with 30, 60, and 120 µg/ml kappa-selenocarrageenan. To assess the rates of cell proliferation and apoptosis, cells were fluorescently stained with acridine orange/ethidium bromide (AO/EB) or stained with propidium iodide (PI) and analyzed by flow cytometry. All experiments were repeated at least 3 times. RESULTS: Normal tumor cells, early and late apoptotic cells, and necrotic cells were examined using fluorescent microscopy. Early-stage apoptotic cells were marked by crescent-shaped or granular yellow-green acridine orange nuclear staining. Late-stage apoptotic cells were marked with concentrated and asymmetrically localized orange nuclear ethidium bromide staining. Necrotic cells increased in volume and showed uneven orange-red fluorescence at their periphery. Cells appeared to be in the process of disintegrating. The percentage of apoptotic osteosarcoma cells detected by dual acridine orange/ethidium bromide (AO/EB) staining was not significantly different from that detected using flow cytometry (P>0.05). CONCLUSIONS: Our results suggest that dual acridine orange/ethidium bromide staining is an economic and convenient method to detect apoptosis in tumor cells and to test tumor chemosensitivity compared with flow cytometry.

Liver cancer has become the sixth most diagnosed cancer and the fourth leading cause of cancer death worldwide. Hepatocellular carcinoma (HCC) is responsible for up to 75-85% of primary liver cancers, and sorafenib is the first targeted drug for advanced HCC treatment. However, sorafenib resistance is common because of the resultant enhancement of aerobic glycolysis and other molecular mechanisms. Aerobic glycolysis was firstly found in HCC, acts as a hallmark of liver cancer and is responsible for the regulation of proliferation, immune evasion, invasion, metastasis, angiogenesis, and drug resistance in HCC. The three rate-limiting enzymes in the glycolytic pathway, including hexokinase 2 (HK2), phosphofructokinase 1 (PFK1), and pyruvate kinases type M2 (PKM2) play an important role in the regulation of aerobic glycolysis in HCC and can be regulated by many mechanisms, such as the AMPK, PI3K/Akt pathway, HIF-1α, c-Myc and noncoding RNAs. Because of the importance of aerobic glycolysis in the progression of HCC, targeting key factors in its pathway such as the inhibition of HK2, PFK or PKM2, represent potential new therapeutic approaches for the treatment of HCC.

Lung cancer is one of the most common cancer in the world. In 2018, there were over 2 million new cases of lung cancer and over 1.7 million deaths were attributed to lung cancer. Targeted therapy has emerged as an important mean of the disease management for patients with non-small-cell lung cancer (NSCLC). Herein, we review and analyze recent literature, discuss the targeting pathways and ongoing clinical trials in lung cancer. Chemotherapy is no longer the best available treatment for all patients. Therapeutic decisions should be guided by an understanding of the molecular features of patient's tumor tissues. The future gains will likely emerge from finding optimal ways of combining targeted therapy, immunotherapy, and chemotherapy.

Abstract T-cells are crucial in maintanence of intestinal homeostasis, however, it is still unclear how microbiota metabolites regulate T-effector cells. Here we show gut microbiota-derived short-chain fatty acids (SCFAs) promote microbiota antigen-specific Th1 cell IL-10 production, mediated by G-protein coupled receptors 43 (GPR43). Microbiota antigen-specific Gpr43 −/− CBir1 transgenic (Tg) Th1 cells, specific for microbiota antigen CBir1 flagellin, induce more severe colitis compared with wide type (WT) CBir1 Tg Th1 cells in Rag −/− recipient mice. Treatment with SCFAs limits colitis induction by promoting IL-10 production, and administration of anti-IL-10R antibody promotes colitis development. Mechanistically, SCFAs activate Th1 cell STAT3 and mTOR, and consequently upregulate transcription factor B lymphocyte-induced maturation protein 1 (Blimp-1), which mediates SCFA-induction of IL-10. SCFA-treated Blimp1 −/− Th1 cells produce less IL-10 and induce more severe colitis compared to SCFA-treated WT Th1 cells. Our studies, thus, provide insight into how microbiota metabolites regulate Th1 cell functions to maintain intestinal homeostasis.

BACKGROUND: During primary percutaneous coronary intervention (PCI), manual thrombectomy may reduce distal embolization and thus improve microvascular perfusion. Small trials have suggested that thrombectomy improves surrogate and clinical outcomes, but a larger trial has reported conflicting results. METHODS: We randomly assigned 10,732 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary PCI to a strategy of routine upfront manual thrombectomy versus PCI alone. The primary outcome was a composite of death from cardiovascular causes, recurrent myocardial infarction, cardiogenic shock, or New York Heart Association (NYHA) class IV heart failure within 180 days. The key safety outcome was stroke within 30 days. RESULTS: The primary outcome occurred in 347 of 5033 patients (6.9%) in the thrombectomy group versus 351 of 5030 patients (7.0%) in the PCI-alone group (hazard ratio in the thrombectomy group, 0.99; 95% confidence interval [CI], 0.85 to 1.15; P=0.86). The rates of cardiovascular death (3.1% with thrombectomy vs. 3.5% with PCI alone; hazard ratio, 0.90; 95% CI, 0.73 to 1.12; P=0.34) and the primary outcome plus stent thrombosis or target-vessel revascularization (9.9% vs. 9.8%; hazard ratio, 1.00; 95% CI, 0.89 to 1.14; P=0.95) were also similar. Stroke within 30 days occurred in 33 patients (0.7%) in the thrombectomy group versus 16 patients (0.3%) in the PCI-alone group (hazard ratio, 2.06; 95% CI, 1.13 to 3.75; P=0.02). CONCLUSIONS: In patients with STEMI who were undergoing primary PCI, routine manual thrombectomy, as compared with PCI alone, did not reduce the risk of cardiovascular death, recurrent myocardial infarction, cardiogenic shock, or NYHA class IV heart failure within 180 days but was associated with an increased rate of stroke within 30 days. (Funded by Medtronic and the Canadian Institutes of Health Research; TOTAL ClinicalTrials.gov number, NCT01149044.).

BACKGROUND: Mounting evidence indicates that obesity may be associated with the risk of colorectal cancer (CRC). To conduct a systematic review of prospective studies assessing the association of obesity with the risk of CRC using meta-analysis. METHODOLOGY/PRINCIPAL FINDINGS: Relevant studies were identified by a search of MEDLINE and EMBASE databases before January 2012, with no restrictions. We also reviewed reference lists from retrieved articles. We included prospective studies that reported relative risk (RR) estimates with 95% confidence intervals (CIs) for the association between general obesity [measured using body mass index (BMI)] or central obesity [measured using waist circumference (WC)] and the risk of colorectal, colon, or rectal cancer. Approximately 9, 000, 000 participants from several countries were included in this analysis. 41 studies on general obesity and 13 studies on central obesity were included in the meta-analysis. The pooled RRs of CRC for the obese vs. normal category of BMI were 1.334 (95% CI, 1.253-1.420), and the highest vs. lowest category of WC were 1.455 (95% CI, 1.327-1.596). There was heterogeneity among studies of BMI (P<0.001) but not among studies of WC (P=0.323). CONCLUSIONS: Both of general and central obesity were positively associated with the risk of CRC in this meta-analysis.

Combined checkpoint blockade (e.g., PD1/PD-L1) with traditional clinical therapies can be hampered by side effects and low tumour-therapeutic outcome, hindering broad clinical translation. Here we report a combined tumour-therapeutic modality based on integrating nanosonosensitizers-augmented noninvasive sonodynamic therapy (SDT) with checkpoint-blockade immunotherapy. All components of the nanosonosensitizers (HMME/R837@Lip) are clinically approved, wherein liposomes act as carriers to co-encapsulate sonosensitizers (hematoporphyrin monomethyl ether (HMME)) and immune adjuvant (imiquimod (R837)). Using multiple tumour models, we demonstrate that combining nanosonosensitizers-augmented SDT with anti-PD-L1 induces an anti-tumour response, which not only arrests primary tumour progression, but also prevents lung metastasis. Furthermore, the combined treatment strategy offers a long-term immunological memory function, which can protect against tumour rechallenge after elimination of the initial tumours. Therefore, this work represents a proof-of-concept combinatorial tumour therapeutics based on noninvasive tumours-therapeutic modality with immunotherapy.

A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we present DeepCRISPR, a comprehensive computational platform to unify sgRNA on-target and off-target site prediction into one framework with deep learning, surpassing available state-of-the-art in silico tools. In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at http://www.deepcrispr.net/ .

-aggregates.

Abstract Purpose: Colorectal cancer is one of the most common malignancies worldwide. Recently, a novel circular RNA, ciRS-7, was proposed to be a potential miR-7 sponge. As miR-7, a putative tumor-suppressor, regulates the expression of several important drivers of colorectal cancer, we analyzed the clinical significance of ciRS-7 in colorectal cancer patients. Experimental Design: Initially, we evaluated the expression levels of ciRS-7 in a training cohort comprising of 153 primary colorectal cancer tissues and 44 matched normal mucosae. We subsequently confirmed its clinical relevance in an independent validation cohort (n = 165), and evaluated the effect of ciRS-7 on miR-7, and its target genes EGFR and RAF1. Functional analyses were performed in cell lines and an animal model to support clinical findings. Results: Our data revealed that ciRS-7 was significantly upregulated in colorectal cancer tissues compared with matched normal mucosae (P = 0.0018), and its overexpression was associated with poor patient survival (P = 0.0224 and 0.0061 in the training and validation cohorts, respectively). Multivariate survival analysis revealed that ciRS-7 emerged as an independent risk factor for overall survival (P = 0.0656 and 0.0324 in the training and validation cohorts, respectively). Overexpression of ciRS-7 in HCT116 and HT29 cells led to the blocking of miR-7 and resulted in a more aggressive oncogenic phenotype, and ciRS-7 overexpression permitted the inhibition of miR-7 and subsequent activation of EGFR and RAF1 oncogenes. Conclusions: CiRS-7 is a promising prognostic biomarker in colorectal cancer patients and may serve as a therapeutic target for reducing EGFR-RAF1 activity in colorectal cancer patients. Clin Cancer Res; 23(14); 3918–28. ©2017 AACR.

Initially, a set of guidelines for the use of ultrasound contrast agents was published in 2004 dealing only with liver applications. A second edition of the guidelines in 2008 reflected changes in the available contrast agents and updated the guidelines for the liver, as well as implementing some non-liver applications. Time has moved on, and the need for international guidelines on the use of CEUS in the liver has become apparent. The present document describes the third iteration of recommendations for the hepatic use of contrast enhanced ultrasound (CEUS) using contrast specific imaging techniques. This joint WFUMB-EFSUMB initiative has implicated experts from major leading ultrasound societies worldwide. These liver CEUS guidelines are simultaneously published in the official journals of both organizing federations (i.e., Ultrasound in Medicine and Biology for WFUMB and Ultraschall in der Medizin/European Journal of Ultrasound for EFSUMB). These guidelines and recommendations provide general advice on the use of all currently clinically available ultrasound contrast agents (UCA). They are intended to create standard protocols for the use and administration of UCA in liver applications on an international basis and improve the management of patients worldwide.

BACKGROUND: The vascular complications of diabetes mellitus are the major causes of morbidity and mortality among people with diabetes. Circular RNAs are a class of endogenous noncoding RNAs that regulate gene expression in eukaryotes. In this study, we investigated the role of circular RNA in retinal vascular dysfunction induced by diabetes mellitus. METHODS: Quantitative polymerase chain reactions, Sanger sequencing, and Northern blots were conducted to detect circular HIPK3 (circHIPK3) expression pattern on diabetes mellitus-related stresses. MTT (3-[4,5-dimethythiazol-2-yl]-2,5-diphenyl tetrazolium bromide) assays, EdU (5-ethynyl-2'-deoxyuridine) incorporation assays, Transwell migration assays, and Matrigel assays were conducted to detect the role of circHIPK3 in retinal endothelial cell function in vitro. Retinal trypsin digestion, vascular permeability assays, and ELISA assays were conducted to detect the role of circHIPK3 in retinal vascular dysfunction in vivo. Bioinformatics analysis, luciferase activity assays, RNA pull-down assays, and in vitro studies were conducted to reveal the mechanism of circHIPK3-mediated retinal vascular dysfunction. RESULTS: circHIPK3 expression was significantly upregulated in diabetic retinas and retinal endothelial cells following stressors related to diabetes mellitus. circHIPK3 silencing or overexpressing circHIPK3 changed retinal endothelial cell viability, proliferation, migration, and tube formation in vitro. circHIPK3 silencing in vivo alleviated retinal vascular dysfunction, as shown by decreased retinal acellular capillaries, vascular leakage, and inflammation. circHIPK3 acted as an endogenous miR-30a-3p sponge to sequester and inhibit miR-30a-3p activity, which led to increased vascular endothelial growth factor-C, FZD4, and WNT2 expression. Ectopic expression of miR-30a-3p mimicked the effect of circHIPK3 silencing on vascular endothelial phenotypes in vivo and in vitro. CONCLUSIONS: The circular RNA circHIPK3 plays a role in diabetic retinopathy by blocking miR-30a function, leading to increased endothelial proliferation and vascular dysfunction. These data suggest that circular RNA is a potential target to control diabetic proliferative retinopathy.

Importance: If we assume that women and men exhibit variations of the same fundamental vascular physiology, then conventional analyses of subclinical measures would suggest that women catch up to men by midlife in the extent of potentially important vascular disease. Alternatively, under the assumption that vascular physiology may fundamentally differ between women and men, a sex-specific analysis of existing data could offer new insights and augment our understanding of sex differences in cardiovascular diseases. Objective: To evaluate whether longitudinal patterns of blood pressure (BP) elevation differ between women and men during the life course when considering baseline BP levels as the reference. Design, Setting, and Participants: We conducted sex-specific analyses of longitudinal BP measures (144 599 observations) collected for a period of 43 years (1971 to 2014) in 4 community-based US cohort studies. The combined total included 32 833 participants (54% female) spanning ages 5 to 98 years. Data were analyzed between May 4, 2019, and August 5, 2019. Exposures: Age and serially assessed longitudinal BP measures: systolic BP, diastolic BP, mean arterial pressure (MAP), and pulse pressure (PP). Main Outcomes and Measures: Sex-specific change in each primary BP measure compared with baseline BP levels, derived from multilevel longitudinal models fitted over the age span, and new-onset cardiovascular disease events. Results: Of the 32 833 participants, 17 733 were women (54%). Women compared with men exhibited a steeper increase in BP that began as early as in the third decade and continued through the life course (likelihood ratio test χ2 = 531 for systolic BP; χ2 = 123 for diastolic BP; χ2 = 325 for MAP; and χ2 = 572 for PP; P for all <.001). After adjustment for multiple cardiovascular disease risk factors, these between-sex differences in all BP trajectories persisted (likelihood ratio test χ2 = 314 for systolic BP; χ2 = 31 for diastolic BP; χ2 = 129 for MAP; and χ2 = 485 for PP; P for all <.001). Conclusions and Relevance: In contrast with the notion that important vascular disease processes in women lag behind men by 10 to 20 years, sex-specific analyses indicate that BP measures actually progress more rapidly in women than in men, beginning early in life. This early-onset sexual dimorphism may set the stage for later-life cardiovascular diseases that tend to present differently, not simply later, in women compared with men.