Expression of CDX2 and Hepatocyte Antigen in Benign and Malignant Lesions of Gallbladder and Its Correlation with Histopathologic Type and Clinical Outcome

Recent studies have shown that both CDX2 and Hepatocyte antigen (Hep) are detected in different types of cancer and associated with clinical prognosis. However, fever studies have examined gallbladder cancer specimens, and little is known about the clinicopathological significance of both CDX2 and Hep expression in gallbladder adenocarcinomas. In present study, we examined the expression frequencies of CDX2 and Hepatocyte antigen (Hep), and explored their clinicopathologic significances in gallbladder adenocarcinoma. Immunohistochemistry was used to detect and compare the frequencies of CDX2 and Hep expression in 108 samples of gallbladder adenocarcinoma, 46 peri-tumor tissues and 35 chronic cholecystitis. The expression frequencies for CDX2 and Hep were 49/108 (45.4%) and 45/108 (41.7%) in gallbladder carcinoma; 13/46 (28.3%) and 11/46 (23.9) in peri-tumor tissues; 5/35 (14.3%) and 2/35 (5.7%) in chronic cholecystitis. The positive staining of CDX2 or Hep in gallbladder adenocarcinoma was significantly higher than that in peritumoral tissues (both, P < 0.05), and chronic cholecystits (both, P < 0.01). The expression of CDX2 or Hep was negatively correlated to grade of differentiation, tumor size and lymph node metastasis (P < 0.01 or P < 0.05). Elevated expression frequency of CDX2 or Hep was associated with increased overall survival (P = 0.003 or P = 0.002). Multivariate Cox regression analysis showed that CDX2 (P = 0.014) or Hep (P = 0.026) expression was an independent prognostic predictor in gallbladder adenocarcinoma. CDX2 and Hep might function as important biological markers in the development and prognosis of gallbladder adenocarcinoma

Frequency fluctuations in silicon nanoresonators

Frequency stability is key to performance of nanoresonators. This stability is thought to reach a limit with the resonator's ability to resolve thermally-induced vibrations. Although measurements and predictions of resonator stability usually disregard fluctuations in the mechanical frequency response, these fluctuations have recently attracted considerable theoretical interest. However, their existence is very difficult to demonstrate experimentally. Here, through a literature review, we show that all studies of frequency stability report values several orders of magnitude larger than the limit imposed by thermomechanical noise. We studied a monocrystalline silicon nanoresonator at room temperature, and found a similar discrepancy. We propose a new method to show this was due to the presence of frequency fluctuations, of unexpected level. The fluctuations were not due to the instrumentation system, or to any other of the known sources investigated. These results challenge our current understanding of frequency fluctuations and call for a change in practices

Use of green solvents as pre-treatment of dissolving pulp to decrease CS2 consumption from viscose production

Choline chloride-based deep eutectic solvents are widely used in biomass processing. In this work, four different green solvent mixtures were used as pre-treatment of acid sulphite dissolving pulp with the hypothesis of increasing the possibilities to produce viscose fibres and decreasing the use of the harmful and toxic carbon disulphide in the process. The experiments were performed at two different pulp to solvent mass ratios. Pulp quality parameters were also measured to determine the suitability of the pretreatment: a-cellulose, viscosity, lignin and pentosan content. In addition, X-ray diffraction analysis of pulps at the best solid to liquid ratio was performed to obtain the influence of the crystallinity index. Best results were obtained with the use of lactic acid, with reactivity values close to 94%, giving a reduction of CS2 usage of 15.83%. Furthermore, a linear relationship between the crystallinity index calculated by the XRD and reactivity with a regression factor of 0.87 was found

Assessment of regional best‐fit probability density function of annual maximum rainfall using CFSR precipitation data

The upper Cross River basin (UCRB) fits a true description of a data scarce watershed in respect of climatic data. This paper seeks to determine the best‐fit probability density function (PDF) of annual maximum rainfall for the UCRB using the Climate Forecast System Reanalysis (CFSR) precipitation data. Also, to evaluate the performance of the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Inter‐comparison Project (CMIP3) Fourth Assessment Report (AR4) Global Circulation Models (GCMs) in simulating the monthly precipitation in the UCRB considering 1979–2014 data. For the determination of the best‐fit PDF, the models under review included the generalized extreme value (GEV), normal, gamma, Weibull and log‐normal (LN) distributions. Twenty‐four weather station datasets were obtained and subjected to frequency distribution analysis on per station basis, and subsequently fitted to the respective PDFs. Also, simulated monthly precipitation data obtained from 16 AR4 GCMs, for weather station p6191, were subjected to frequency distribution analysis. The results showed the percentages of best‐fit to worst‐fit PDFs, considering the total number of stations, as follows: 54.17%, 45.83%, 37.50%, 45.83%, and 50%/50%. These percentages corresponded to GEV, Weibull, gamma, gamma, and LN/normal, respectively. The comparison of the predicted and observed values using the Chi‐square goodness‐of‐fit test revealed that the GEV PDF is the best‐fit model for the UCRB. The correlation coefficient values further corroborated the correctness of the test. The PDF of the observed data (weather station p6191) and the simulations of the 16 GCMs computed using monthly rainfall datasets were compared using a mean square error (MSE) dependent skill score. The result from this study suggested that the CGCM3.1 (T47) and MRI‐CGCM2.3.2 provide the best representations of precipitation, considering about 36 years trend for station p6191. The results have no influence on how well the models perform in other geographical locations

Preconditioning-induced ischemic tolerance: a window into endogenous gearing for cerebroprotection

Ischemic tolerance defines transient resistance to lethal ischemia gained by a prior sublethal noxious stimulus (i.e., preconditioning). This adaptive response is thought to be an evolutionarily conserved defense mechanism, observed in a wide variety of species. Preconditioning confers ischemic tolerance if not in all, in most organ systems, including the heart, kidney, liver, and small intestine. Since the first landmark experimental demonstration of ischemic tolerance in the gerbil brain in early 1990's, basic scientific knowledge on the mechanisms of cerebral ischemic tolerance increased substantially. Various noxious stimuli can precondition the brain, presumably through a common mechanism, genomic reprogramming. Ischemic tolerance occurs in two temporally distinct windows. Early tolerance can be achieved within minutes, but wanes also rapidly, within hours. Delayed tolerance develops in hours and lasts for days. The main mechanism involved in early tolerance is adaptation of membrane receptors, whereas gene activation with subsequent de novo protein synthesis dominates delayed tolerance. Ischemic preconditioning is associated with robust cerebroprotection in animals. In humans, transient ischemic attacks may be the clinical correlate of preconditioning leading to ischemic tolerance. Mimicking the mechanisms of this unique endogenous protection process is therefore a potential strategy for stroke prevention. Perhaps new remedies for stroke are very close, right in our cells

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

Volume III. DUNE far detector technical coordination

open966siAcknowledgments This document was prepared by the DUNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. The DUNE collaboration also acknowledges the international, national, and regional funding agencies supporting the institutions who have contributed to completing this Technical Design Report.The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay-these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- A nd dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module.openAbi B.; Acciarri R.; Acero M.A.; Adamov G.; Adams D.; Adinolfi M.; Ahmad Z.; Ahmed J.; Alion T.; Monsalve S.A.; Alt C.; Anderson J.; Andreopoulos C.; Andrews M.; Andrianala F.; Andringa S.; Ankowski A.; Antonova M.; Antusch S.; Aranda-Fernandez A.; Ariga A.; Arnold L.O.; Arroyave M.A.; Asaadi J.; Aurisano A.; Aushev V.; Autiero D.; Azfar F.; Back H.; Back J.J.; Backhouse C.; Baesso P.; Bagby L.; Bajou R.; Balasubramanian S.; Baldi P.; Bambah B.; Barao F.; Barenboim G.; Barker G.; Barkhouse W.; Barnes C.; Barr G.; Monarca J.B.; Barros N.; Barrow J.L.; Bashyal A.; Basque V.; Bay F.; Alba J.B.; Beacom J.F.; Bechetoille E.; Behera B.; Bellantoni L.; Bellettini G.; Bellini V.; Beltramello O.; Belver D.; Benekos N.; Neves F.B.; Berger J.; Berkman S.; Bernardini P.; Berner R.M.; Berns H.; Bertolucci S.; Betancourt M.; Bezawada Y.; Bhattacharjee M.; Bhuyan B.; Biagi S.; Bian J.; Biassoni M.; Biery K.; Bilki B.; Bishai M.; Bitadze A.; Blake A.; Siffert B.B.; Blaszczyk F.; Blazey G.; Blucher E.; Boissevain J.; Bolognesi S.; Bolton T.; Bonesini M.; Bongrand M.; Bonini F.; Booth A.; Booth C.; Bordoni S.; Borkum A.; Boschi T.; Bostan N.; Bour P.; Boyd S.; Boyden D.; Bracinik J.; Braga D.; Brailsford D.; Brandt A.; Bremer J.; Brew C.; Brianne E.; Brice S.J.; Brizzolari C.; Bromberg C.; Brooijmans G.; Brooke J.; Bross A.; Brunetti G.; Buchanan N.; Budd H.; Caiulo D.; Calafiura P.; Calcutt J.; Calin M.; Calvez S.; Calvo E.; Camilleri L.; Caminata A.; Campanelli M.; Caratelli D.; Carini G.; Carlus B.; Carniti P.; Terrazas I.C.; Carranza H.; Castillo A.; Castromonte C.; Cattadori C.; Cavalier F.; Cavanna F.; Centro S.; Cerati G.; Cervelli A.; Villanueva A.C.; Chalifour M.; Chang C.; Chardonnet E.; Chatterjee A.; Chattopadhyay S.; Chaves J.; Chen H.; Chen M.; Chen Y.; Cherdack D.; Chi C.; Childress S.; Chiriacescu A.; Cho K.; Choubey S.; Christensen A.; Christian D.; Christodoulou G.; Church E.; Clarke P.; Coan T.E.; Cocco A.G.; Coelho J.; Conley E.; Conrad J.; Convery M.; Corwin L.; Cotte P.; Cremaldi L.; Cremonesi L.; Crespo-Anadon J.I.; Cristaldo E.; Cross R.; Cuesta C.; Cui Y.; Cussans D.; Dabrowski M.; Motta H.D.; Peres L.D.S.; David Q.; Davies G.S.; Davini S.; Dawson J.; De K.; Almeida R.M.D.; Debbins P.; Bonis I.D.; Decowski M.; Gouvea A.D.; Holanda P.C.D.; Astiz I.L.D.I.; Deisting A.; Jong P.D.; Delbart A.; Delepine D.; Delgado M.; Dell'acqua A.; Lurgio P.D.; Neto J.R.D.M.; Demuth D.M.; Dennis S.; Densham C.; Deptuch G.; Roeck A.D.; Romeri V.D.; Vries J.D.; Dharmapalan R.; Dias M.; Diaz F.; Diaz J.; Domizio S.D.; Giulio L.D.; Ding P.; Noto L.D.; Distefano C.; Diurba R.; Diwan M.; Djurcic Z.; Dokania N.; Dolinski M.; Domine L.; Douglas D.; Drielsma F.; Duchesneau D.; Duffy K.; Dunne P.; Durkin T.; Duyang H.; Dvornikov O.; Dwyer D.; Dyshkant A.; Eads M.; Edmunds D.; Eisch J.; Emery S.; Ereditato A.; Escobar C.; Sanchez L.E.; Evans J.J.; Ewart E.; Ezeribe A.C.; Fahey K.; Falcone A.; Farnese C.; Farzan Y.; Felix J.; Fernandez-Martinez E.; Menendez P.F.; Ferraro F.; Fields L.; Filkins A.; Filthaut F.; Fitzpatrick R.S.; Flanagan W.; Fleming B.; Flight R.; Fowler J.; Fox W.; Franc J.; Francis K.; Franco D.; Freeman J.; Freestone J.; Fried J.; Friedland A.; Fuess S.; Furic I.; Furmanski A.P.; Gago A.; Gallagher H.; Gallego-Ros A.; Gallice N.; Galymov V.; Gamberini E.; Gamble T.; Gandhi R.; Gandrajula R.; Gao S.; Garcia-Gamez D.; Garcia-Peris M.A.; Gardiner S.; Gastler D.; Ge G.; Gelli B.; Gendotti A.; Gent S.; Ghorbani-Moghaddam Z.; Gibin D.; Gil-Botella I.; Girerd C.; Giri A.; Gnani D.; Gogota O.; Gold M.; Gollapinni S.; Gollwitzer K.; Gomes R.A.; Bermeo L.G.; Fajardo L.S.G.; Gonnella F.; Gonzalez-Cuevas J.; Goodman M.C.; Goodwin O.; Goswami S.; Gotti C.; Goudzovski E.; Grace C.; Graham M.; Gramellini E.; Gran R.; Granados E.; Grant A.; Grant C.; Gratieri D.; Green P.; Green S.; Greenler L.; Greenwood M.; Greer J.; Griffith C.; Groh M.; Grudzinski J.; Grzelak K.; Gu W.; Guarino V.; Guenette R.; Guglielmi A.; Guo B.; Guthikonda K.; Gutierrez R.; Guzowski P.; Guzzo M.M.; Gwon S.; Habig A.; Hackenburg A.; Hadavand H.; Haenni R.; Hahn A.; Haigh J.; Haiston J.; Hamernik T.; Hamilton P.; Han J.; Harder K.; Harris D.A.; Hartnell J.; Hasegawa T.; Hatcher R.; Hazen E.; Heavey A.; Heeger K.M.; Hennessy K.; Henry S.; Morquecho M.H.; Herner K.; Hertel L.; Hesam A.S.; Hewes J.; Pichardo A.H.; Hill T.; Hillier S.J.; Himmel A.; Hoff J.; Hohl C.; Holin A.; Hoppe E.; Horton-Smith G.A.; Hostert M.; Hourlier A.; Howard B.; Howell R.; Huang J.; Huang J.; Hugon J.; Iles G.; Iliescu A.M.; Illingworth R.; Ioannisian A.; Itay R.; Izmaylov A.; James E.; Jargowsky B.; Jediny F.; Jesus-Valls C.; Ji X.; Jiang L.; Jimenez S.; Jipa A.; Joglekar A.; Johnson C.; Johnson R.; Jones B.; Jones S.; Jung C.; Junk T.; Jwa Y.; Kabirnezhad M.; Kaboth A.; Kadenko I.; Kamiya F.; Karagiorgi G.; Karcher A.; Karolak M.; Karyotakis Y.; Kasai S.; Kasetti S.P.; Kashur L.; Kazaryan N.; Kearns E.; Keener P.; Kelly K.J.; Kemp E.; Ketchum W.; Kettell S.; Khabibullin M.; Khotjantsev A.; Khvedelidze A.; Kim D.; King B.; Kirby B.; Kirby M.; Klein J.; Koehler K.; Koerner L.W.; Kohn S.; Koller P.P.; Kordosky M.; Kosc T.; Kose U.; Kostelecky V.; Kothekar K.; Krennrich F.; Kreslo I.; Kudenko Y.; Kudryavtsev V.; Kulagin S.; Kumar J.; Kumar R.; Kuruppu C.; Kus V.; Kutter T.; Lambert A.; Lande K.; Lane C.E.; Lang K.; Langford T.; Lasorak P.; Last D.; Lastoria C.; Laundrie A.; Lawrence A.; Lazanu I.; Lazur R.; Le T.; Learned J.; Lebrun P.; Miotto G.L.; Lehnert R.; De Oliveira M.L.; Leitner M.; Leyton M.; Li L.; Li S.; Li S.; Li T.; Li Y.; Liao H.; Lin C.; Lin S.; Lister A.; Littlejohn B.R.; Liu J.; Lockwitz S.; Loew T.; Lokajicek M.; Lomidze I.; Long K.; Loo K.; Lorca D.; Lord T.; Losecco J.; Louis W.C.; Luk K.; Luo X.; Lurkin N.; Lux T.; Luzio V.P.; MacFarland D.; MacHado A.; MacHado P.; MacIas C.; MacIer J.; Maddalena A.; Madigan P.; Magill S.; Mahn K.; Maio A.; Maloney J.A.; Mandrioli G.; Maneira J.C.; Manenti L.; Manly S.; Mann A.; Manolopoulos K.; Plata M.M.; Marchionni A.; Marciano W.; Marfatia D.; Mariani C.; Maricic J.; Marinho F.; Marino A.D.; Marshak M.; Marshall C.; Marshall J.; Marteau J.; Martin-Albo J.; Martinez N.; Caicedo D.A.M.; Martynenko S.; Mason K.; Mastbaum A.; Masud M.; Matsuno S.; Matthews J.; Mauger C.; Mauri N.; Mavrokoridis K.; Mazza R.; Mazzacane A.; Mazzucato E.; McCluskey E.; McConkey N.; McFarland K.S.; McGrew C.; McNab A.; Mefodiev A.; Mehta P.; Melas P.; Mellinato M.; Mena O.; Menary S.; Mendez H.; Menegolli A.; Meng G.; Messier M.; Metcalf W.; Mewes M.; Meyer H.; Miao T.; Michna G.; Miedema T.; Migenda J.; Milincic R.; Miller W.; Mills J.; Milne C.; Mineev O.; Miranda O.G.; Miryala S.; Mishra C.; Mishra S.; Mislivec A.; Mladenov D.; Mocioiu I.; Moffat K.; Moggi N.; Mohanta R.; Mohayai T.A.; Mokhov N.; Molina J.A.; Bueno L.M.; Montanari A.; Montanari C.; Montanari D.; Zetina L.M.M.; Moon J.; Mooney M.; Moor A.; Moreno D.; Morgan B.; Morris C.; Mossey C.; Motuk E.; Moura C.A.; Mousseau J.; Mu W.; Mualem L.; Mueller J.; Muether M.; Mufson S.; Muheim F.; Muir A.; Mulhearn M.; Muramatsu H.; Murphy S.; Musser J.; Nachtman J.; Nagu S.; Nalbandyan M.; Nandakumar R.; Naples D.; Narita S.; Navas-Nicolas D.; Nayak N.; Nebot-Guinot M.; Necib L.; Negishi K.; Nelson J.K.; Nesbit J.; Nessi M.; Newbold D.; Newcomer M.; Newhart D.; Nichol R.; Niner E.; Nishimura K.; Norman A.; Northrop R.; Novella P.; Nowak J.A.; Oberling M.; Campo A.O.D.; Olivier A.; Onel Y.; Onishchuk Y.; Ott J.; Pagani L.; Pakvasa S.; Palamara O.; Palestini S.; Paley J.M.; Pallavicini M.; Palomares C.; Pantic E.; Paolone V.; Papadimitriou V.; Papaleo R.; Papanestis A.; Paramesvaran S.; Parke S.; Parsa Z.; Parvu M.; Pascoli S.; Pasqualini L.; Pasternak J.; Pater J.; Patrick C.; Patrizii L.; Patterson R.B.; Patton S.; Patzak T.; Paudel A.; Paulos B.; Paulucci L.; Pavlovic Z.; Pawloski G.; Payne D.; Pec V.; Peeters S.J.; Penichot Y.; Pennacchio E.; Penzo A.; Peres O.L.; Perry J.; Pershey D.; Pessina G.; Petrillo G.; Petta C.; Petti R.; Piastra F.; Pickering L.; Pietropaolo F.; Pillow J.; Plunkett R.; Poling R.; Pons X.; Poonthottathil N.; Pordes S.; Potekhin M.; Potenza R.; Potukuchi B.V.; Pozimski J.; Pozzato M.; Prakash S.; Prakash T.; Prince S.; Prior G.; Pugnere D.; Qi K.; Qian X.; Raaf J.; Raboanary R.; Radeka V.; Rademacker J.; Radics B.; Rafique A.; Raguzin E.; Rai M.; Rajaoalisoa M.; Rakhno I.; Rakotondramanana H.; Rakotondravohitra L.; Ramachers Y.; Rameika R.; Delgado M.R.; Ramson B.; Rappoldi A.; Raselli G.; Ratoff P.; Ravat S.; Razafinime H.; Real J.; Rebel B.; Redondo D.; Reggiani-Guzzo M.; Rehak T.; Reichenbacher J.; Reitzner S.D.; Renshaw A.; Rescia S.; Resnati F.; Reynolds A.; Riccobene G.; Rice L.C.; Rielage K.; Rigaut Y.; Rivera D.; Rochester L.; Roda M.; Rodrigues P.; Alonso M.R.; Rondon J.R.; Roeth A.; Rogers H.; Rosauro-Alcaraz S.; Rossella M.; Rout J.; Roy S.; Rubbia A.; Rubbia C.; Russell B.; Russell J.; Ruterbories D.; Saakyan R.; Sacerdoti S.; Safford T.; Sahu N.; Sala P.; Samios N.; Sanchez M.; Sanders D.A.; Sankey D.; Santana S.; Santos-Maldonado M.; Saoulidou N.; Sapienza P.; Sarasty C.; Sarcevic I.; Savage G.; Savinov V.; Scaramelli A.; Scarff A.; Scarpelli A.; Schaffer T.; Schellman H.; Schlabach P.; Schmitz D.; Scholberg K.; Schukraft A.; Segreto E.; Sensenig J.; Seong I.; Sergi A.; Sergiampietri F.; Sgalaberna D.; Shaevitz M.; Shafaq S.; Shamma M.; Sharma H.R.; Sharma R.; Shaw T.; Shepherd-Themistocleous C.; Shin S.; Shooltz D.; Shrock R.; Simard L.; Simos N.; Sinclair J.; Sinev G.; Singh J.; Singh V.; Sipos R.; Sippach F.; Sirri G.; Sitraka A.; Siyeon K.; Smargianaki D.; Smith A.; Smith A.; Smith E.; Smith P.; Smolik J.; Smy M.; Snopok P.; Nunes M.S.; Sobel H.; Soderberg M.; Salinas C.J.S.; Soldner-Rembold S.; Solomey N.; Solovov V.; Sondheim W.E.; Sorel M.; Soto-Oton J.; Sousa A.; Soustruznik K.; Spagliardi F.; Spanu M.; Spitz J.; Spooner N.J.; Spurgeon K.; Staley R.; Stancari M.; Stanco L.; Steiner H.; Stewart J.; Stillwell B.; Stock J.; Stocker F.; Stokes T.; Strait M.; Strauss T.; Striganov S.; Stuart A.; Summers D.; Surdo A.; Susic V.; Suter L.; Sutera C.; Svoboda R.; Szczerbinska B.; Szelc A.; Talaga R.; Tanaka H.; Oregui B.T.; Tapper A.; Tariq S.; Tatar E.; Tayloe R.; Teklu A.; Tenti M.; Terao K.; Ternes C.A.; Terranova F.; Testera G.; Thea A.; Thompson J.L.; Thorn C.; Timm S.; Tonazzo A.; Torti M.; Tortola M.; Tortorici F.; Totani D.; Toups M.; Touramanis C.; Trevor J.; Trzaska W.H.; Tsai Y.T.; Tsamalaidze Z.; Tsang K.; Tsverava N.; Tufanli S.; Tull C.; Tyley E.; Tzanov M.; Uchida M.A.; Urheim J.; Usher T.; Vagins M.; Vahle P.; Valdiviesso G.; Valencia E.; Vallari Z.; Valle J.W.; Vallecorsa S.; Berg R.V.; De Water R.G.V.; Forero D.V.; Varanini F.; Vargas D.; Varner G.; Vasel J.; Vasseur G.; Vaziri K.; Ventura S.; Verdugo A.; Vergani S.; Vermeulen M.A.; Verzocchi M.; De Souza H.V.; Vignoli C.; Vilela C.; Viren B.; Vrba T.; Wachala T.; Waldron A.V.; Wallbank M.; Wang H.; Wang J.; Wang Y.; Wang Y.; Warburton K.; Warner D.; Wascko M.; Waters D.; Watson A.; Weatherly P.; Weber A.; Weber M.; Wei H.; Weinstein A.; Wenman D.; Wetstein M.; While M.R.; White A.; Whitehead L.H.; Whittington D.; Wilking M.J.; Wilkinson C.; Williams Z.; Wilson F.; Wilson R.J.; Wolcott J.; Wongjirad T.; Wood K.; Wood L.; Worcester E.; Worcester M.; Wret C.; Wu W.; Wu W.; Xiao Y.; Yang G.; Yang T.; Yershov N.; Yonehara K.; Young T.; Yu B.; Yu J.; Zalesak J.; Zambelli L.; Zamorano B.; Zani A.; Zazueta L.; Zeller G.; Zennamo J.; Zeug K.; Zhang C.; Zhao M.; Zhivun E.; Zhu G.; Zimmerman E.D.; Zito M.; Zucchelli S.; Zuklin J.; Zutshi V.; Zwaska R.Abi B.; Acciarri R.; Acero M.A.; Adamov G.; Adams D.; Adinolfi M.; Ahmad Z.; Ahmed J.; Alion T.; Monsalve S.A.; Alt C.; Anderson J.; Andreopoulos C.; Andrews M.; Andrianala F.; Andringa S.; Ankowski A.; Antonova M.; Antusch S.; Aranda-Fernandez A.; Ariga A.; Arnold L.O.; Arroyave M.A.; Asaadi J.; Aurisano A.; Aushev V.; Autiero D.; Azfar F.; Back H.; Back J.J.; Backhouse C.; Baesso P.; Bagby L.; Bajou R.; Balasubramanian S.; Baldi P.; Bambah B.; Barao F.; Barenboim G.; Barker G.; Barkhouse W.; Barnes C.; Barr G.; Monarca J.B.; Barros N.; Barrow J.L.; Bashyal A.; Basque V.; Bay F.; Alba J.B.; Beacom J.F.; Bechetoille E.; Behera B.; Bellantoni L.; Bellettini G.; Bellini V.; Beltramello O.; Belver D.; Benekos N.; Neves F.B.; Berger J.; Berkman S.; Bernardini P.; Berner R.M.; Berns H.; Bertolucci S.; Betancourt M.; Bezawada Y.; Bhattacharjee M.; Bhuyan B.; Biagi S.; Bian J.; Biassoni M.; Biery K.; Bilki B.; Bishai M.; Bitadze A.; Blake A.; Siffert B.B.; Blaszczyk F.; Blazey G.; Blucher E.; Boissevain J.; Bolognesi S.; Bolton T.; Bonesini M.; Bongrand M.; Bonini F.; Booth A.; Booth C.; Bordoni S.; Borkum A.; Boschi T.; Bostan N.; Bour P.; Boyd S.; Boyden D.; Bracinik J.; Braga D.; Brailsford D.; Brandt A.; Bremer J.; Brew C.; Brianne E.; Brice S.J.; Brizzolari C.; Bromberg C.; Brooijmans G.; Brooke J.; Bross A.; Brunetti G.; Buchanan N.; Budd H.; Caiulo D.; Calafiura P.; Calcutt J.; Calin M.; Calvez S.; Calvo E.; Camilleri L.; Caminata A.; Campanelli M.; Caratelli D.; Carini G.; Carlus B.; Carniti P.; Terrazas I.C.; Carranza H.; Castillo A.; Castromonte C.; Cattadori C.; Cavalier F.; Cavanna F.; Centro S.; Cerati G.; Cervelli A.; Villanueva A.C.; Chalifour M.; Chang C.; Chardonnet E.; Chatterjee A.; Chattopadhyay S.; Chaves J.; Chen H.; Chen M.; Chen Y.; Cherdack D.; Chi C.; Childress S.; Chiriacescu A.; Cho K.; Choubey S.; Christensen A.; Christian D.; Christodoulou G.; Church E.; Clarke P.; Coan T.E.; Cocco A.G.; Coelho J.; Conley E.; Conrad J.; Convery M.; Corwin L.; Cotte P.; Cremaldi L.; Cremonesi L.; Crespo-Anadon J.I.; Cristaldo E.; Cross R.; Cuesta C.; Cui Y.; Cussans D.; Dabrowski M.; Motta H.D.; Peres L.D.S.; David Q.; Davies G.S.; Davini S.; Dawson J.; De K.; Almeida R.M.D.; Debbins P.; Bonis I.D.; Decowski M.; Gouvea A.D.; Holanda P.C.D.; Astiz I.L.D.I.; Deisting A.; Jong P.D.; Delbart A.; Delepine D.; Delgado M.; Dell'acqua A.; Lurgio P.D.; Neto J.R.D.M.; Demuth D.M.; Dennis S.; Densham C.; Deptuch G.; Roeck A.D.; Romeri V.D.; Vries J.D.; Dharmapalan R.; Dias M.; Diaz F.; Diaz J.; Domizio S.D.; Giulio L.D.; Ding P.; Noto L.D.; Distefano C.; Diurba R.; Diwan M.; Djurcic Z.; Dokania N.; Dolinski M.; Domine L.; Douglas D.; Drielsma F.; Duchesneau D.; Duffy K.; Dunne P.; Durkin T.; Duyang H.; Dvornikov O.; Dwyer D.; Dyshkant A.; Eads M.; Edmunds D.; Eisch J.; Emery S.; Ereditato A.; Escobar C.; Sanchez L.E.; Evans J.J.; Ewart E.; Ezeribe A.C.; Fahey K.; Falcone A.; Farnese C.; Farzan Y.; Felix J.; Fernandez-Martinez E.; Menendez P.F.; Ferraro F.; Fields L.; Filkins A.; Filthaut F.; Fitzpatrick R.S.; Flanagan W.; Fleming B.; Flight R.; Fowler J.; Fox W.; Franc J.; Francis K.; Franco D.; Freeman J.; Freestone J.; Fried J.; Friedland A.; Fuess S.; Furic I.; Furmanski A.P.; Gago A.; Gallagher H.; Gallego-Ros A.; Gallice N.; Galymov V.; Gamberini E.; Gamble T.; Gandhi R.; Gandrajula R.; Gao S.; Garcia-Gamez D.; Garcia-Peris M.A.; Gardiner S.; Gastler D.; Ge G.; Gelli B.; Gendotti A.; Gent S.; Ghorbani-Moghaddam Z.; Gibin D.; Gil-Botella I.; Girerd C.; Giri A.; Gnani D.; Gogota O.; Gold M.; Gollapinni S.; Gollwitzer K.; Gomes R.A.; Bermeo L.G.; Fajardo L.S.G.; Gonnella F.; Gonzalez-Cuevas J.; Goodman M.C.; Goodwin O.; Goswami S.; Gotti C.; Goudzovski E.; Grace C.; Graham M.; Gramellini E.; Gran R.; Granados E.; Grant A.; Grant C.; Gratieri D.; Green P.; Green S.; Greenler L.; Greenwood M.; Greer J.; Griffith C.; Groh M.; Grudzinski J.; Grzelak K.; Gu W.; Guarino V.; Guenette R.; Guglielmi A.; Guo B.; Guthikonda K.; Gutierrez R.; Guzowski P.; Guzzo M.M.; Gwon S.; Habig A.; Hackenburg A.; Hadavand H.; Haenni R.; Hahn A.; Haigh J.; Haiston J.; Hamernik T.; Hamilton P.; Han J.; Harder K.; Harris D.A.; Hartnell J.; Hasegawa T.; Hatcher R.; Hazen E.; Heavey A.; Heeger K.M.; Hennessy K.; Henry S.; Morquecho M.H.; Herner K.; Hertel L.; Hesam A.S.; Hewes J.; Pichardo A.H.; Hill T.; Hillier S.J.; Himmel A.; Hoff J.; Hohl C.; Holin A.; Hoppe E.; Horton-Smith G.A.; Hostert M.; Hourlier A.; Howard B.; Howell R.; Huang J.; Huang J.; Hugon J.; Iles G.; Iliescu A.M.; Illingworth R.; Ioannisian A.; Itay R.; Izmaylov A.; James E.; Jargowsky B.; Jediny F.; Jesus-Valls C.; Ji X.; Jiang L.; Jimenez S.; Jipa A.; Joglekar A.; Johnson C.; Johnson R.; Jones B.; Jones S.; Jung C.; Junk T.; Jwa Y.; Kabirnezhad M.; Kaboth A.; Kadenko I.; Kamiya F.; Karagiorgi G.; Karcher A.; Karolak M.; Karyotakis Y.; Kasai S.; Kasetti S.P.; Kashur L.; Kazaryan N.; Kearns E.; Keener P.; Kelly K.J.; Kemp E.; Ketchum W.; Kettell S.; Khabibullin M.; Khotjantsev A.; Khvedelidze A.; Kim D.; King B.; Kirby B.; Kirby M.; Klein J.; Koehler K.; Koerner L.W.; Kohn S.; Koller P.P.; Kordosky M.; Kosc T.; Kose U.; Kostelecky V.; Kothekar K.; Krennrich F.; Kreslo I.; Kudenko Y.; Kudryavtsev V.; Kulagin S.; Kumar J.; Kumar R.; Kuruppu C.; Kus V.; Kutter T.; Lambert A.; Lande K.; Lane C.E.; Lang K.; Langford T.; Lasorak P.; Last D.; Lastoria C.; Laundrie A.; Lawrence A.; Lazanu I.; Lazur R.; Le T.; Learned J.; Lebrun P.; Miotto G.L.; Lehnert R.; De Oliveira M.L.; Leitner M.; Leyton M.; Li L.; Li S.; Li S.; Li T.; Li Y.; Liao H.; Lin C.; Lin S.; Lister A.; Littlejohn B.R.; Liu J.; Lockwitz S.; Loew T.; Lokajicek M.; Lomidze I.; Long K.; Loo K.; Lorca D.; Lord T.; Losecco J.; Louis W.C.; Luk K.; Luo X.; Lurkin N.; Lux T.; Luzio V.P.; MacFarland D.; MacHado A.; MacHado P.; MacIas C.; MacIer J.; Maddalena A.; Madigan P.; Magill S.; Mahn K.; Maio A.; Maloney J.A.; Mandrioli G.; Maneira J.C.; Manenti L.; Manly S.; Mann A.; Manolopoulos K.; Plata M.M.; Marchionni A.; Marciano W.; Marfatia D.; Mariani C.; Maricic J.; Marinho F.; Marino A.D.; Marshak M.; Marshall C.; Marshall J.; Marteau J.; Martin-Albo J.; Martinez N.; Caicedo D.A.M.; Martynenko S.; Mason K.; Mastbaum A.; Masud M.; Matsuno S.; Matthews J.; Mauger C.; Mauri N.; Mavrokoridis K.; Mazza R.; Mazzacane A.; Mazzucato E.; McCluskey E.; McConkey N.; McFarland K.S.; McGrew C.; McNab A.; Mefodiev A.; Mehta P.; Melas P.; Mellinato M.; Mena O.; Menary S.; Mendez H.; Menegolli A.; Meng G.; Messier M.; Metcalf W.; Mewes M.; Meyer H.; Miao T.; Michna G.; Miedema T.; Migenda J.; Milincic R.; Miller W.; Mills J.; Milne C.; Mineev O.; Miranda O.G.; Miryala S.; Mishra C.; Mishra S.; Mislivec A.; Mladenov D.; Mocioiu I.; Moffat K.; Moggi N.; Mohanta R.; Mohayai T.A.; Mokhov N.; Molina J.A.; Bueno L.M.; Montanari A.; Montanari C.; Montanari D.; Zetina L.M.M.; Moon J.; Mooney M.; Moor A.; Moreno D.; Morgan B.; Morris C.; Mossey C.; Motuk E.; Moura C.A.; Mousseau J.; Mu W.; Mualem L.; Mueller J.; Muether M.; Mufson S.; Muheim F.; Muir A.; Mulhearn M.; Muramatsu H.; Murphy S.; Musser J.; Nachtman J.; Nagu S.; Nalbandyan M.; Nandakumar R.; Naples D.; Narita S.; Navas-Nicolas D.; Nayak N.; Nebot-Guinot M.; Necib L.; Negishi K.; Nelson J.K.; Nesbit J.; Nessi M.; Newbold D.; Newcomer M.; Newhart D.; Nichol R.; Niner E.; Nishimura K.; Norman A.; Northrop R.; Novella P.; Nowak J.A.; 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Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide 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

Supernova neutrino burst detection with the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the νe spectral parameters of the neutrino burst will be considered

Salmonella bongori provides insights into the evolution of the Salmonellae.

The genus Salmonella contains two species, S. bongori and S. enterica. Compared to the well-studied S. enterica there is a marked lack of information regarding the genetic makeup and diversity of S. bongori. S. bongori has been found predominantly associated with cold-blooded animals, but it can infect humans. To define the phylogeny of this species, and compare it to S. enterica, we have sequenced 28 isolates representing most of the known diversity of S. bongori. This cross-species analysis allowed us to confidently differentiate ancestral functions from those acquired following speciation, which include both metabolic and virulence-associated capacities. We show that, although S. bongori inherited a basic set of Salmonella common virulence functions, it has subsequently elaborated on this in a different direction to S. enterica. It is an established feature of S. enterica evolution that the acquisition of the type III secretion systems (T3SS-1 and T3SS-2) has been followed by the sequential acquisition of genes encoding secreted targets, termed effectors proteins. We show that this is also true of S. bongori, which has acquired an array of novel effector proteins (sboA-L). All but two of these effectors have no significant S. enterica homologues and instead are highly similar to those found in enteropathogenic Escherichia coli (EPEC). Remarkably, SboH is found to be a chimeric effector protein, encoded by a fusion of the T3SS-1 effector gene sopA and a gene highly similar to the EPEC effector nleH from enteropathogenic E. coli. We demonstrate that representatives of these new effectors are translocated and that SboH, similarly to NleH, blocks intrinsic apoptotic pathways while being targeted to the mitochondria by the SopA part of the fusion. This work suggests that S. bongori has inherited the ancestral Salmonella virulence gene set, but has adapted by incorporating virulence determinants that resemble those employed by EPEC.We thank the core sequencing and informatics teams at the Sanger Institute for their assistance and The Wellcome Trust for its support of the Sanger Institute Pathogen Genomics and Biology groups and the MRC for their support of GF, KSR and GNS. MCF, GCL, TRC, HSS, GSV, MS, NKP, RAK, JP, GD and NRT were supported by Wellcome Trust grant 076964 and MICROME, an EU Framework Programme 7 Collaborative Project, Grant Agreement Number 222886-2. Work was also supported by Grant ADI-08/2006 from Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) and The World Bank, and grant 1100092 from Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT). CJB was supported by fellowships from CONICYT (21080373 and AT-24091015)