Human enteroids: Preclinical models of non-inflammatory diarrhea

Researchers need an available and easy-to-use model of the human intestine to better understand human intestinal physiology and pathophysiology of diseases, and to offer an enhanced platform for developing drug therapy. Our work employs human enteroids derived from each of the major intestinal sections to advance understanding of several diarrheal diseases, including those caused by cholera, rotavirus and enterohemorrhagic Escherichia coli. An enteroid bank is being established to facilitate comparison of segmental, developmental, and regulatory differences in transport proteins that can influence therapy efficacy. Basic characterization of major ion transport protein expression, localization and function in the human enteroid model sets the stage to study the effects of enteric infection at the transport level, as well as to monitor potential responses to pharmacological intervention

JUNO Conceptual Design Report

The Jiangmen Underground Neutrino Observatory (JUNO) is proposed to determine the neutrino mass hierarchy using an underground liquid scintillator detector. It is located 53 km away from both Yangjiang and Taishan Nuclear Power Plants in Guangdong, China. The experimental hall, spanning more than 50 meters, is under a granite mountain of over 700 m overburden. Within six years of running, the detection of reactor antineutrinos can resolve the neutrino mass hierarchy at a confidence level of 3-4$\sigma$, and determine neutrino oscillation parameters $\sin^2\theta_{12}$, $\Delta m^2_{21}$, and $|\Delta m^2_{ee}|$ to an accuracy of better than 1%. The JUNO detector can be also used to study terrestrial and extra-terrestrial neutrinos and new physics beyond the Standard Model. The central detector contains 20,000 tons liquid scintillator with an acrylic sphere of 35 m in diameter. $\sim$17,000 508-mm diameter PMTs with high quantum efficiency provide $\sim$75% optical coverage. The current choice of the liquid scintillator is: linear alkyl benzene (LAB) as the solvent, plus PPO as the scintillation fluor and a wavelength-shifter (Bis-MSB). The number of detected photoelectrons per MeV is larger than 1,100 and the energy resolution is expected to be 3% at 1 MeV. The calibration system is designed to deploy multiple sources to cover the entire energy range of reactor antineutrinos, and to achieve a full-volume position coverage inside the detector. The veto system is used for muon detection, muon induced background study and reduction. It consists of a Water Cherenkov detector and a Top Tracker system. The readout system, the detector control system and the offline system insure efficient and stable data acquisition and processing.Comment: 328 pages, 211 figure

Radioactivity control strategy for the JUNO detector

602siopenJUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV. [Figure not available: see fulltext.]openAbusleme A.; Adam T.; Ahmad S.; Ahmed R.; Aiello S.; Akram M.; An F.; An Q.; Andronico G.; Anfimov N.; Antonelli V.; Antoshkina T.; Asavapibhop B.; de Andre J.P.A.M.; Auguste D.; Babic A.; Baldini W.; Barresi A.; Basilico D.; Baussan E.; Bellato M.; Bergnoli A.; Birkenfeld T.; Blin S.; Blum D.; Blyth S.; Bolshakova A.; Bongrand M.; Bordereau C.; Breton D.; Brigatti A.; Brugnera R.; Bruno R.; Budano A.; Buscemi M.; Busto J.; Butorov I.; Cabrera A.; Cai H.; Cai X.; Cai Y.; Cai Z.; Cammi A.; Campeny A.; Cao C.; Cao G.; Cao J.; Caruso R.; Cerna C.; Chang J.; Chang Y.; Chen P.; Chen P.-A.; Chen S.; Chen X.; Chen Y.-W.; Chen Y.; Chen Y.; Chen Z.; Cheng J.; Cheng Y.; Chetverikov A.; Chiesa D.; Chimenti P.; Chukanov A.; Claverie G.; Clementi C.; Clerbaux B.; Conforti Di Lorenzo S.; Corti D.; Cremonesi O.; Dal Corso F.; Dalager O.; De La Taille C.; Deng J.; Deng Z.; Deng Z.; Depnering W.; Diaz M.; Ding X.; Ding Y.; Dirgantara B.; Dmitrievsky S.; Dohnal T.; Dolzhikov D.; Donchenko G.; Dong J.; Doroshkevich E.; Dracos M.; Druillole F.; Du S.; Dusini S.; Dvorak M.; Enqvist T.; Enzmann H.; Fabbri A.; Fajt L.; Fan D.; Fan L.; Fang J.; Fang W.; Fargetta M.; Fedoseev D.; Fekete V.; Feng L.-C.; Feng Q.; Ford R.; Formozov A.; Fournier A.; Gan H.; Gao F.; Garfagnini A.; Giammarchi M.; Giaz A.; Giudice N.; Gonchar M.; Gong G.; Gong H.; Gornushkin Y.; Gottel A.; Grassi M.; Grewing C.; Gromov V.; Gu M.; Gu X.; Gu Y.; Guan M.; Guardone N.; Gul M.; Guo C.; Guo J.; Guo W.; Guo X.; Guo Y.; Hackspacher P.; Hagner C.; Han R.; Han Y.; Hassan M.S.; He M.; He W.; Heinz T.; Hellmuth P.; Heng Y.; Herrera R.; Hor Y.K.; Hou S.; Hsiung Y.; Hu B.-Z.; Hu H.; Hu J.; Hu J.; Hu S.; Hu T.; Hu Z.; Huang C.; Huang G.; Huang H.; Huang W.; Huang X.; Huang X.; Huang Y.; Hui J.; Huo L.; Huo W.; Huss C.; Hussain S.; Ioannisian A.; Isocrate R.; Jelmini B.; Jen K.-L.; Jeria I.; Ji X.; Ji X.; Jia H.; Jia J.; Jian S.; Jiang D.; Jiang X.; Jin R.; Jing X.; Jollet C.; Joutsenvaara J.; Jungthawan S.; Kalousis L.; Kampmann P.; Kang L.; Karaparambil R.; Kazarian N.; Khan W.; Khosonthongkee K.; Korablev D.; Kouzakov K.; Krasnoperov A.; Kruth A.; Kutovskiy N.; Kuusiniemi P.; Lachenmaier T.; Landini C.; Leblanc S.; Lebrin V.; Lefevre F.; Lei R.; Leitner R.; Leung J.; Li D.; Li F.; Li F.; Li H.; Li H.; Li J.; Li M.; Li M.; Li N.; Li N.; Li Q.; Li R.; Li S.; Li T.; Li W.; Li W.; Li X.; Li X.; Li X.; Li Y.; Li Y.; Li Z.; Li Z.; Li Z.; Liang H.; Liang H.; Liao J.; Liebau D.; Limphirat A.; Limpijumnong S.; Lin G.-L.; Lin S.; Lin T.; Ling J.; Lippi I.; Liu F.; Liu H.; Liu H.; Liu H.; Liu H.; Liu H.; Liu J.; Liu J.; Liu M.; Liu Q.; Liu Q.; Liu R.; Liu S.; Liu S.; Liu S.; Liu X.; Liu X.; Liu Y.; Liu Y.; Lokhov A.; Lombardi P.; Lombardo C.; Loo K.; Lu C.; Lu H.; Lu J.; Lu J.; Lu S.; Lu X.; Lubsandorzhiev B.; Lubsandorzhiev S.; Ludhova L.; Luo F.; Luo G.; Luo P.; Luo S.; Luo W.; Lyashuk V.; Ma B.; Ma Q.; Ma S.; Ma X.; Ma X.; Maalmi J.; Malyshkin Y.; Mantovani F.; Manzali F.; Mao X.; Mao Y.; Mari S.M.; Marini F.; Marium S.; Martellini C.; Martin-Chassard G.; Martini A.; Mayer M.; Mayilyan D.; Mednieks I.; Meng Y.; Meregaglia A.; Meroni E.; Meyhofer D.; Mezzetto M.; Miller J.; Miramonti L.; Montini P.; Montuschi M.; Muller A.; Nastasi M.; Naumov D.V.; Naumova E.; Navas-Nicolas D.; Nemchenok I.; Nguyen Thi M.T.; Ning F.; Ning Z.; Nunokawa H.; Oberauer L.; Ochoa-Ricoux J.P.; Olshevskiy A.; Orestano D.; Ortica F.; Othegraven R.; Pan H.-R.; Paoloni A.; Parmeggiano S.; Pei Y.; Pelliccia N.; Peng A.; Peng H.; Perrot F.; Petitjean P.-A.; Petrucci F.; Pilarczyk O.; Pineres Rico L.F.; Popov A.; Poussot P.; Pratumwan W.; Previtali E.; Qi F.; Qi M.; Qian S.; Qian X.; Qian Z.; Qiao H.; Qin Z.; Qiu S.; Rajput M.U.; Ranucci G.; Raper N.; Re A.; Rebber H.; Rebii A.; Ren B.; Ren J.; Ricci B.; Robens M.; Roche M.; Rodphai N.; Romani A.; Roskovec B.; Roth C.; Ruan X.; Ruan X.; Rujirawat S.; Rybnikov A.; Sadovsky A.; Saggese P.; Sanfilippo S.; Sangka A.; Sanguansak N.; Sawangwit U.; Sawatzki J.; Sawy F.; Schever M.; Schwab C.; Schweizer K.; Selyunin A.; Serafini A.; Settanta G.; Settimo M.; Shao Z.; Sharov V.; Shaydurova A.; Shi J.; Shi Y.; Shutov V.; Sidorenkov A.; Simkovic F.; Sirignano C.; Siripak J.; Sisti M.; Slupecki M.; Smirnov M.; Smirnov O.; Sogo-Bezerra T.; Sokolov S.; Songwadhana J.; Soonthornthum B.; Sotnikov A.; Sramek O.; Sreethawong W.; Stahl A.; Stanco L.; Stankevich K.; Stefanik D.; Steiger H.; Steinmann J.; Sterr T.; Stock M.R.; Strati V.; Studenikin A.; Sun S.; Sun X.; Sun Y.; Sun Y.; Suwonjandee N.; Szelezniak M.; Tang J.; Tang Q.; Tang Q.; Tang X.; Tietzsch A.; Tkachev I.; Tmej T.; Treskov K.; Triossi A.; Troni G.; Trzaska W.; Tuve C.; Ushakov N.; van den Boom J.; van Waasen S.; Vanroyen G.; Vassilopoulos N.; Vedin V.; Verde G.; Vialkov M.; Viaud B.; Vollbrecht M.C.; Volpe C.; Vorobel V.; Voronin D.; Votano L.; Walker P.; Wang C.; Wang C.-H.; Wang E.; Wang G.; Wang J.; Wang J.; Wang K.; Wang L.; Wang M.; Wang M.; Wang M.; Wang R.; Wang S.; Wang W.; Wang W.; Wang W.; Wang X.; Wang X.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Z.; Wang Z.; Wang Z.; Wang Z.; Waqas M.; Watcharangkool A.; Wei L.; Wei W.; Wei W.; Wei Y.; Wen L.; Wiebusch C.; Wong S.C.-F.; Wonsak B.; Wu D.; Wu F.; Wu Q.; Wu Z.; Wurm M.; Wurtz J.; Wysotzki C.; Xi Y.; Xia D.; Xie X.; Xie Y.; Xie Z.; Xing Z.; Xu B.; Xu C.; Xu D.; Xu F.; Xu H.; Xu J.; Xu J.; Xu M.; Xu Y.; Xu Y.; Yan B.; Yan T.; Yan W.; Yan X.; Yan Y.; Yang A.; Yang C.; Yang C.; Yang H.; Yang J.; Yang L.; Yang X.; Yang Y.; Yang Y.; Yao H.; Yasin Z.; Ye J.; Ye M.; Ye Z.; Yegin U.; Yermia F.; Yi P.; Yin N.; Yin X.; You Z.; Yu B.; Yu C.; Yu C.; Yu H.; Yu M.; Yu X.; Yu Z.; Yu Z.; Yuan C.; Yuan Y.; Yuan Z.; Yuan Z.; Yue B.; Zafar N.; Zambanini A.; Zavadskyi V.; Zeng S.; Zeng T.; Zeng Y.; Zhan L.; Zhang A.; Zhang F.; Zhang G.; Zhang H.; Zhang H.; Zhang J.; Zhang J.; Zhang J.; Zhang J.; Zhang J.; Zhang P.; Zhang Q.; Zhang S.; Zhang S.; Zhang T.; Zhang X.; Zhang X.; Zhang X.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Y.; Zhang Z.; Zhang Z.; Zhao F.; Zhao J.; Zhao R.; Zhao S.; Zhao T.; Zheng D.; Zheng H.; Zheng M.; Zheng Y.; Zhong W.; Zhou J.; Zhou L.; Zhou N.; Zhou S.; Zhou T.; Zhou X.; Zhu J.; Zhu K.; Zhu K.; Zhu Z.; Zhuang B.; Zhuang H.; Zong L.; Zou J.Abusleme, A.; Adam, T.; Ahmad, S.; Ahmed, R.; Aiello, S.; Akram, M.; An, F.; An, Q.; Andronico, G.; Anfimov, N.; Antonelli, V.; Antoshkina, T.; Asavapibhop, B.; de Andre, J. P. A. M.; Auguste, D.; Babic, A.; Baldini, W.; Barresi, A.; Basilico, D.; Baussan, E.; Bellato, M.; Bergnoli, A.; Birkenfeld, T.; Blin, S.; Blum, D.; Blyth, S.; Bolshakova, A.; Bongrand, M.; Bordereau, C.; Breton, D.; Brigatti, A.; Brugnera, R.; Bruno, R.; Budano, A.; Buscemi, M.; Busto, J.; Butorov, I.; Cabrera, A.; Cai, H.; Cai, X.; Cai, Y.; Cai, Z.; Cammi, A.; Campeny, A.; Cao, C.; Cao, G.; Cao, J.; Caruso, R.; Cerna, C.; Chang, J.; Chang, Y.; Chen, P.; Chen, P. -A.; Chen, S.; Chen, X.; Chen, Y. -W.; Chen, Y.; Chen, Y.; Chen, Z.; Cheng, J.; Cheng, Y.; Chetverikov, A.; Chiesa, D.; Chimenti, P.; Chukanov, A.; Claverie, G.; Clementi, C.; Clerbaux, B.; Conforti Di Lorenzo, S.; Corti, D.; Cremonesi, O.; Dal Corso, F.; Dalager, O.; De La Taille, C.; Deng, J.; Deng, Z.; Deng, Z.; Depnering, W.; Diaz, M.; Ding, X.; Ding, Y.; Dirgantara, B.; Dmitrievsky, S.; Dohnal, T.; Dolzhikov, D.; Donchenko, G.; Dong, J.; Doroshkevich, E.; Dracos, M.; Druillole, F.; Du, S.; Dusini, S.; Dvorak, M.; Enqvist, T.; Enzmann, H.; Fabbri, A.; Fajt, L.; Fan, D.; Fan, L.; Fang, J.; Fang, W.; Fargetta, M.; Fedoseev, D.; Fekete, V.; Feng, L. -C.; Feng, Q.; Ford, R.; Formozov, A.; Fournier, A.; Gan, H.; Gao, F.; Garfagnini, A.; Giammarchi, M.; Giaz, A.; Giudice, N.; Gonchar, M.; Gong, G.; Gong, H.; Gornushkin, Y.; Gottel, A.; Grassi, M.; Grewing, C.; Gromov, V.; Gu, M.; Gu, X.; Gu, Y.; Guan, M.; Guardone, N.; Gul, M.; Guo, C.; Guo, J.; Guo, W.; Guo, X.; Guo, Y.; Hackspacher, P.; Hagner, C.; Han, R.; Han, Y.; Hassan, M. S.; He, M.; He, W.; Heinz, T.; Hellmuth, P.; Heng, Y.; Herrera, R.; Hor, Y. K.; Hou, S.; Hsiung, Y.; Hu, B. -Z.; Hu, H.; Hu, J.; Hu, J.; Hu, S.; Hu, T.; Hu, Z.; Huang, C.; Huang, G.; Huang, H.; Huang, W.; Huang, X.; Huang, X.; Huang, Y.; Hui, J.; Huo, L.; Huo, W.; Huss, C.; Hussain, S.; Ioannisian, A.; Isocrate, R.; Jelmini, B.; Jen, K. -L.; Jeria, I.; Ji, X.; Ji, X.; Jia, H.; Jia, J.; Jian, S.; Jiang, D.; Jiang, X.; Jin, R.; Jing, X.; Jollet, C.; Joutsenvaara, J.; Jungthawan, S.; Kalousis, L.; Kampmann, P.; Kang, L.; Karaparambil, R.; Kazarian, N.; Khan, W.; Khosonthongkee, K.; Korablev, D.; Kouzakov, K.; Krasnoperov, A.; Kruth, A.; Kutovskiy, N.; Kuusiniemi, P.; Lachenmaier, T.; Landini, C.; Leblanc, S.; Lebrin, V.; Lefevre, F.; Lei, R.; Leitner, R.; Leung, J.; Li, D.; Li, F.; Li, F.; Li, H.; Li, H.; Li, J.; Li, M.; Li, M.; Li, N.; Li, N.; Li, Q.; Li, R.; Li, S.; Li, T.; Li, W.; Li, W.; Li, X.; Li, X.; Li, X.; Li, Y.; Li, Y.; Li, Z.; Li, Z.; Li, Z.; Liang, H.; Liang, H.; Liao, J.; Liebau, D.; Limphirat, A.; Limpijumnong, S.; Lin, G. -L.; Lin, S.; Lin, T.; Ling, J.; Lippi, I.; Liu, F.; Liu, H.; Liu, H.; Liu, H.; Liu, H.; Liu, H.; Liu, J.; Liu, J.; Liu, M.; Liu, Q.; Liu, Q.; Liu, R.; Liu, S.; Liu, S.; Liu, S.; Liu, X.; Liu, X.; Liu, Y.; Liu, Y.; Lokhov, A.; Lombardi, P.; Lombardo, C.; Loo, K.; Lu, C.; Lu, H.; Lu, J.; Lu, J.; Lu, S.; Lu, X.; Lubsandorzhiev, B.; Lubsandorzhiev, S.; Ludhova, L.; Luo, F.; Luo, G.; Luo, P.; Luo, S.; Luo, W.; Lyashuk, V.; Ma, B.; Ma, Q.; Ma, S.; Ma, X.; Ma, X.; Maalmi, J.; Malyshkin, Y.; Mantovani, F.; Manzali, F.; Mao, X.; Mao, Y.; Mari, S. M.; Marini, F.; Marium, S.; Martellini, C.; Martin-Chassard, G.; Martini, A.; Mayer, M.; Mayilyan, D.; Mednieks, I.; Meng, Y.; Meregaglia, A.; Meroni, E.; Meyhofer, D.; Mezzetto, M.; Miller, J.; Miramonti, L.; Montini, P.; Montuschi, M.; Muller, A.; Nastasi, M.; Naumov, D. V.; Naumova, E.; Navas-Nicolas, D.; Nemchenok, I.; Nguyen Thi, M. T.; Ning, F.; Ning, Z.; Nunokawa, H.; Oberauer, L.; Ochoa-Ricoux, J. P.; Olshevskiy, A.; Orestano, D.; Ortica, F.; Othegraven, R.; Pan, H. -R.; Paoloni, A.; Parmeggiano, S.; Pei, Y.; Pelliccia, N.; Peng, A.; Peng, H.; Perrot, F.; Petitjean, P. -A.; Petrucci, F.; Pilarczyk, O.; Pineres Rico, L. F.; Popov, A.; Poussot, P.; Pratumwan, W.; Previtali, E.; Qi, F.; Qi, M.; Qian, S.; Qian, X.; Qian, Z.; Qiao, H.; Qin, Z.; Qiu, S.; Rajput, M. U.; Ranucci, G.; Raper, N.; Re, A.; Rebber, H.; Rebii, A.; Ren, B.; Ren, J.; Ricci, B.; Robens, M.; Roche, M.; Rodphai, N.; Romani, A.; Roskovec, B.; Roth, C.; Ruan, X.; Ruan, X.; Rujirawat, S.; Rybnikov, A.; Sadovsky, A.; Saggese, P.; Sanfilippo, S.; Sangka, A.; Sanguansak, N.; Sawangwit, U.; Sawatzki, J.; Sawy, F.; Schever, M.; Schwab, C.; Schweizer, K.; Selyunin, A.; Serafini, A.; Settanta, G.; Settimo, M.; Shao, Z.; Sharov, V.; Shaydurova, A.; Shi, J.; Shi, Y.; Shutov, V.; Sidorenkov, A.; Simkovic, F.; Sirignano, C.; Siripak, J.; Sisti, M.; Slupecki, M.; Smirnov, M.; Smirnov, O.; Sogo-Bezerra, T.; Sokolov, S.; Songwadhana, J.; Soonthornthum, B.; Sotnikov, A.; Sramek, O.; Sreethawong, W.; Stahl, A.; Stanco, L.; Stankevich, K.; Stefanik, D.; Steiger, H.; Steinmann, J.; Sterr, T.; Stock, M. R.; Strati, V.; Studenikin, A.; Sun, S.; Sun, X.; Sun, Y.; Sun, Y.; Suwonjandee, N.; Szelezniak, M.; Tang, J.; Tang, Q.; Tang, Q.; Tang, X.; Tietzsch, A.; Tkachev, I.; Tmej, T.; Treskov, K.; Triossi, A.; Troni, G.; Trzaska, W.; Tuve, C.; Ushakov, N.; van den Boom, J.; van Waasen, S.; Vanroyen, G.; Vassilopoulos, N.; Vedin, V.; Verde, G.; Vialkov, M.; Viaud, B.; Vollbrecht, M. C.; Volpe, C.; Vorobel, V.; Voronin, D.; Votano, L.; Walker, P.; Wang, C.; Wang, C. -H.; Wang, E.; Wang, G.; Wang, J.; Wang, J.; Wang, K.; Wang, L.; Wang, M.; Wang, M.; Wang, M.; Wang, R.; Wang, S.; Wang, W.; Wang, W.; Wang, W.; Wang, X.; Wang, X.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Y.; Wang, Z.; Wang, Z.; Wang, Z.; Wang, Z.; Waqas, M.; Watcharangkool, A.; Wei, L.; Wei, W.; Wei, W.; Wei, Y.; Wen, L.; Wiebusch, C.; Wong, S. C. -F.; Wonsak, B.; Wu, D.; Wu, F.; Wu, Q.; Wu, Z.; Wurm, M.; Wurtz, J.; Wysotzki, C.; Xi, Y.; Xia, D.; Xie, X.; Xie, Y.; Xie, Z.; Xing, Z.; Xu, B.; Xu, C.; Xu, D.; Xu, F.; Xu, H.; Xu, J.; Xu, J.; Xu, M.; Xu, Y.; Xu, Y.; Yan, B.; Yan, T.; Yan, W.; Yan, X.; Yan, Y.; Yang, A.; Yang, C.; Yang, C.; Yang, H.; Yang, J.; Yang, L.; Yang, X.; Yang, Y.; Yang, Y.; Yao, H.; Yasin, Z.; Ye, J.; Ye, M.; Ye, Z.; Yegin, U.; Yermia, F.; Yi, P.; Yin, N.; Yin, X.; You, Z.; Yu, B.; Yu, C.; Yu, C.; Yu, H.; Yu, M.; Yu, X.; Yu, Z.; Yu, Z.; Yuan, C.; Yuan, Y.; Yuan, Z.; Yuan, Z.; Yue, B.; Zafar, N.; Zambanini, A.; Zavadskyi, V.; Zeng, S.; Zeng, T.; Zeng, Y.; Zhan, L.; Zhang, A.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, H.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, J.; Zhang, P.; Zhang, Q.; Zhang, S.; Zhang, S.; Zhang, T.; Zhang, X.; Zhang, X.; Zhang, X.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Y.; Zhang, Z.; Zhang, Z.; Zhao, F.; Zhao, J.; Zhao, R.; Zhao, S.; Zhao, T.; Zheng, D.; Zheng, H.; Zheng, M.; Zheng, Y.; Zhong, W.; Zhou, J.; Zhou, L.; Zhou, N.; Zhou, S.; Zhou, T.; Zhou, X.; Zhu, J.; Zhu, K.; Zhu, K.; Zhu, Z.; Zhuang, B.; Zhuang, H.; Zong, L.; Zou, J

Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Blood transfusion is one of the most common transmission pathways of hepatitis C virus (HCV). This paper aims to provide a comprehensive and reliable tabulation of available data on the epidemiological characteristics and risk factors for HCV infection among blood donors in Chinese mainland, so as to help make prevention strategies and guide further research.</p> <p>Methods</p> <p>A systematic review was constructed based on the computerized literature database. Infection rates and 95% confidence intervals (95% CI) were calculated using the approximate normal distribution model. Odds ratios and 95% CI were calculated by fixed or random effects models. Data manipulation and statistical analyses were performed using STATA 10.0 and ArcGIS 9.3 was used for map construction.</p> <p>Results</p> <p>Two hundred and sixty-five studies met our inclusion criteria. The pooled prevalence of HCV infection among blood donors in Chinese mainland was 8.68% (95% CI: 8.01%-9.39%), and the epidemic was severer in North and Central China, especially in Henan and Hebei. While a significant lower rate was found in Yunnan. Notably, before 1998 the pooled prevalence of HCV infection was 12.87% (95%CI: 11.25%-14.56%) among blood donors, but decreased to 1.71% (95%CI: 1.43%-1.99%) after 1998. No significant difference was found in HCV infection rates between male and female blood donors, or among different blood type donors. The prevalence of HCV infection was found to increase with age. During 1994-1995, the prevalence rate reached the highest with a percentage of 15.78% (95%CI: 12.21%-19.75%), and showed a decreasing trend in the following years. A significant difference was found among groups with different blood donation types, Plasma donors had a relatively higher prevalence than whole blood donors of HCV infection (33.95% <it>vs </it>7.9%).</p> <p>Conclusions</p> <p>The prevalence of HCV infection has rapidly decreased since 1998 and kept a low level in recent years, but some provinces showed relatively higher prevalence than the general population. It is urgent to make efficient measures to prevent HCV secondary transmission and control chronic progress, and the key to reduce the HCV incidence among blood donors is to encourage true voluntary blood donors, strictly implement blood donation law, and avoid cross-infection.</p

Measurements of long-range azimuthal anisotropies and associated Fourier coefficients for pp collisions at √s=5.02 and 13 TeV and p+Pb collisions at √sNN=5.02 TeV with the ATLAS detector

ATLAS measurements of two-particle correlations are presented for √s=5.02 and 13 TeV ppcollisions and for √sNN=5.02 TeV p+Pb collisions at the LHC. The correlation functions are measured as a function of relative azimuthal angle Δϕ, and pseudorapidity separation Δη, using charged particles detected within the pseudorapidity interval |η|2, is studied using a template fitting procedure to remove a “back-to-back” contribution to the correlation function that primarily arises from hard-scattering processes. In addition to the elliptic, cos (2Δϕ), modulation observed in a previous measurement, the pp correlation functions exhibit significant cos (3Δϕ) and cos (4Δϕ) modulation. The Fourier coefficients vn, n associated with the cos (nΔϕ) modulation of the correlation functions for n=2–4 are measured as a function of charged-particle multiplicity and charged-particle transverse momentum. The Fourier coefficients are observed to be compatible with cos (nϕ) modulation of per-event single-particle azimuthal angle distributions. The single-particle Fourier coefficients vn are measured as a function of charged-particle multiplicity, and charged-particle transverse momentum for n=2–4. The integrated luminosities used in this analysis are, 64nb−1 for the √s=13 TeV pp data, 170 nb−1 for the √ s = 5.02 TeV pp data, and 28 nb−1 for the √sNN = 5.02 TeV p+Pb data

Probing the W tb vertex structure in t-channel single-top-quark production and decay in pp collisions at s√=8 TeV with the ATLAS detector

To probe the W tb vertex structure, top-quark and W -boson polarisation observables are measured from t-channel single-top-quark events produced in proton-proton collisions at a centre-of-mass energy of 8 TeV. The dataset corresponds to an integrated luminosity of 20.2 fb−1, recorded with the ATLAS detector at the LHC. Selected events contain one isolated electron or muon, large missing transverse momentum and exactly two jets, with one of them identified as likely to contain a b-hadron. Stringent selection requirements are applied to discriminate t-channel single-top-quark events from background. The polarisation observables are extracted from asymmetries in angular distributions measured with respect to spin quantisation axes appropriately chosen for the top quark and the W boson. The asymmetry measurements are performed at parton level by correcting the observed angular distributions for detector effects and hadronisation after subtracting the background contributions. The measured top-quark and W -boson polarisation values are in agreement with the Standard Model predictions. Limits on the imaginary part of the anomalous coupling gR are also set from model-independent measurements.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; SRNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex and Idex, ANR, Region Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom.The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resoinfo:eu-repo/semantics/publishedVersio

Performance of the ATLAS trigger system in 2015

During 2015 the ATLAS experiment recorded 3.8fb−1 of proton–proton collision data at a centre-of-mass energy of 13TeV. The ATLAS trigger system is a crucial component of the experiment, responsible for selecting events of interest at a recording rate of approximately 1 kHz from up to 40 MHz of collisions. This paper presents a short overview of the changes to the trigger and data acquisition systems during the first long shutdown of the LHC and shows the performance of the trigger system and its components based on the 2015 proton–proton collision data

Search for additional heavy neutral Higgs and gauge bosons in the ditau final state produced in 36 fb−1 of pp collisions at √s=13 TeV with the ATLAS detector

A search for heavy neutral Higgs bosons and Z′ bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb−1 from proton-proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to τ+τ− with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for Z′ bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude tan β > 1.0 for mA= 0.25 TeV and tan β > 42 for mA=1.5 TeV at the 95% confidence level. For the Sequential Standard Model, ZSSM′ with mZ′< 2.42 TeV is excluded at 95% confidence level, while Z NU′ with mZ ′ < 2.25 TeV is excluded for the non-universal G(221) model that exhibits enhanced couplings to third-generation fermions

Top-quark mass measurement in the all-hadronic tt¯ decay channel at √s=8 TeV with the ATLAS detector

The top-quark mass is measured in the all-hadronic top-antitop quark decay channel using proton-proton collisions at a centre-of-mass energy of √s=8 TeV with the ATLAS detector at the CERN Large Hadron Collider. The data set used in the analysis corresponds to an integrated luminosity of 20.2 fb−1. The large multi-jet background is modelled using a data-driven method. The top-quark mass is obtained from template fits to the ratio of the three-jet to the dijet mass. The three-jet mass is obtained from the three jets assigned to the top quark decay. From these three jets the dijet mass is obtained using the two jets assigned to the W boson decay. The top-quark mass is measured to be 173.72 ± 0.55 (stat.) ± 1.01 (syst.) GeV