Diabetes-related molecular signatures in infrared spectra of human saliva

WOS: 000290261500001PubMed ID: 20630088Background: There is an ongoing need for improvements in non-invasive, point-of-care tools for the diagnosis and prognosis of diabetes mellitus. Ideally, such technologies would allow for community screening. Methods: In this study, we employed infrared spectroscopy as a novel diagnostic tool in the prediction of diabetic status by analyzing the molecular and sub-molecular spectral signatures of saliva collected from subjects with diabetes (n = 39) and healthy controls (n = 22). Results: Spectral analysis revealed differences in several major metabolic components - lipid, proteins, glucose, thiocyanate and carboxylate - that clearly demarcate healthy and diseased saliva. The overall accuracy for the diagnosis of diabetes based on infrared spectroscopy was 100% on the training set and 88.2% on the validation set. Therefore, we have established that infrared spectroscopy can be used to generate complex biochemical profiles in saliva and identify several potential diabetes-associated spectral features. Conclusions: Infrared spectroscopy may represent an appropriate tool with which to identify novel diseases mechanisms, risk factors for diabetic complications and markers of therapeutic efficacy. Further study into the potential utility of infrared spectroscopy as diagnostic and prognostic tool for diabetes is warranted

Web-based guided insulin self-titration in patients with type 2 diabetes: the Di@log study. Design of a cluster randomised controlled trial [TC1316]

<p>Abstract</p> <p>Background</p> <p>Many patients with type 2 diabetes (T2DM) are not able to reach the glycaemic target level of HbA1c < 7.0%, and therefore are at increased risk of developing severe complications. Transition to insulin therapy is one of the obstacles in diabetes management, because of barriers of both patient and health care providers. Patient empowerment, a patient-centred approach, is vital for improving diabetes management. We developed a web-based self-management programme for insulin titration in T2DM patients. The aim of our study is to investigate if this internet programme helps to improve glycaemic control more effectively than usual care.</p> <p>Methods/Design</p> <p>T2DM patients (n = 248), aged 35–75 years, with an HbA1c ≥ 7.0%, eligible for treatment with insulin and able to use the internet will be selected from general practices in two different regions in the Netherlands. Cluster randomisation will be performed at the level of general practices. Patients in the intervention group will use a self-developed internet programme to assist them in self-titrating insulin. The control group will receive usual care.</p> <p>Primary outcome is the difference in change in HbA1c between intervention and control group. Secondary outcome measures are quality of life, treatment satisfaction, diabetes self-efficacy and frequency of hypoglycaemic episodes. Results will be analysed according to the intention-to-treat principle.</p> <p>Discussion</p> <p>An internet intervention supporting self-titration of insulin therapy in T2DM patients is an innovative patient-centred intervention. The programme provides guided self-monitoring and evaluation of health and self-care behaviours through tailored feedback on input of glucose values. This is expected to result in a better performance of self-titration of insulin and consequently in the improvement of glycaemic control. The patient will be enabled to 'discover and use his or her own ability to gain mastery over his/her diabetes' and therefore patient empowerment will increase. Based on the self-regulation theory of Leventhal, we hypothesize that additional benefits will be achieved in terms of increases in treatment satisfaction, quality of life and self-efficacy.</p> <p>Trial registration</p> <p>Dutch Trial Register TC1316.</p

An ethnographic investigation of maternity healthcare experience of immigrants in rural and urban Alberta, Canada

Background: Canada is among the top immigrant-receiving nations in the world. Immigrant populations may face structural and individual barriers in the access to and navigation of healthcare services in a new country. The aims of the study were to (1) generate new understanding of the processes that perpetuate immigrant disadvantages in maternity healthcare, and (2) devise potential interventions that might improve maternity experiences and outcomes for immigrant women in Canada. Methods: The study utilized a qualitative research approach that focused on ethnographic research design and data analysis contextualized within theories of organizational behaviour and critical realism. Data were collected over 2.5 years using focus groups and in-depth semistructured interviews with immigrant women (n = 34), healthcare providers (n = 29), and social service providers (n = 23) in a Canadian province. Purposive samples of each subgroup were generated, and recruitment and data collection – including interpretation and verification of translations – were facilitated through the hiring of community researchers and collaborations with key informants. Results: The findings indicate that (a) communication difficulties, (b) lack of information, (c) lack of social support (isolation), (d) cultural beliefs, e) inadequate healthcare services, and (f) cost of medicine/services represent potential barriers to the access to and navigation of maternity services by immigrant women in Canada. Having successfully accessed and navigated services, immigrant women often face additional challenges that influence their level of satisfaction and quality of care, such as lack of understanding of the informed consent process, lack of regard by professionals for confidential patient information, short consultation times, short hospital stays, perceived discrimination/stereotyping, and culture shock. Conclusions: Although health service organizations and policies strive for universality and equality in service provision, personal and organizational barriers can limit care access, adequacy, and acceptability for immigrant women. A holistic healthcare approach must include health informational packages available in different languages/media. Health care professionals who care for diverse populations must be provided with training in cultural competence, and monitoring and evaluation programs to ameliorate personal and systemic discrimination

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

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.; 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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

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Experiment Simulation Configurations Approximating DUNE TDR

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community