774,903 results match your criteria Computer aided surgery : official journal of the International Society for Computer Aided Surgery[Journal]


Chronic recording and electrochemical performance of amorphous silicon carbide-coated Utah electrode arrays implanted in rat motor cortex.

J Neural Eng 2019 Apr 23. Epub 2019 Apr 23.

Department of Bioengineering, The University of Texas at Dallas, Richardson, Texas, UNITED STATES.

Clinical applications of implantable microelectrode arrays are currently limited by device failure due to, in part, mechanical and electrochemical failure modes. To overcome this challenge, there is significant research interest in the exploration of novel array architectures and encapsulation materials. Amorphous silicon carbide (a-SiC) is biocompatible and corrosion resistant, and has recently been employed as a coating on biomedical devices including planar microelectrode arrays. Read More

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http://dx.doi.org/10.1088/1741-2552/ab1bc8DOI Listing

Using Surgeon Hand Motions to Predict Surgical Maneuvers.

Hum Factors 2019 Apr 23:18720819838901. Epub 2019 Apr 23.

University of Wisconsin-Madison, USA.

Objective: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical benchtop simulations.

Background: Automatic computer vision recognition of surgical maneuvers (suturing, tying, and transition) could expedite video review and objective assessment of surgeries.

Method: We recorded hand movements of 37 clinicians performing simple and running subcuticular suturing benchtop simulations, and applied three machine learning techniques (decision trees, random forests, and hidden Markov models) to classify surgical maneuvers every 2 s (60 frames) of video. Read More

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http://dx.doi.org/10.1177/0018720819838901DOI Listing

Mathematical predictions of oxygen availability in micro- and macro-encapsulated human and porcine pancreatic islets.

J Biomed Mater Res B Appl Biomater 2019 Apr 23. Epub 2019 Apr 23.

Department of Surgery, University of California, Irvine, Orange, California.

Optimal function of immunoisolated islets requires adequate supply of oxygen to metabolically active insulin producing beta-cells. Using mathematical modeling, we investigated the influence of the pO on islet insulin secretory capacity and evaluated conditions that could lead to the development of tissue anoxia, modeled for a 300 μm islet in a 500 μm microcapsule or a 500 μm planar, slab-shaped macrocapsule. The pO was used to assess the part of islets that contributed to insulin secretion. Read More

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http://dx.doi.org/10.1002/jbm.b.34393DOI Listing

Deep convolutional models improve predictions of macaque V1 responses to natural images.

PLoS Comput Biol 2019 Apr 23;15(4):e1006897. Epub 2019 Apr 23.

Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany.

Despite great efforts over several decades, our best models of primary visual cortex (V1) still predict spiking activity quite poorly when probed with natural stimuli, highlighting our limited understanding of the nonlinear computations in V1. Recently, two approaches based on deep learning have emerged for modeling these nonlinear computations: transfer learning from artificial neural networks trained on object recognition and data-driven convolutional neural network models trained end-to-end on large populations of neurons. Here, we test the ability of both approaches to predict spiking activity in response to natural images in V1 of awake monkeys. Read More

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http://dx.plos.org/10.1371/journal.pcbi.1006897
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http://dx.doi.org/10.1371/journal.pcbi.1006897DOI Listing
April 2019
1 Read

Effects of spatial dimensionality and steric interactions on microtubule-motor self-organization.

Phys Biol 2019 Apr 23;16(4):046004. Epub 2019 Apr 23.

The Francis Crick Institute, 1 Midland Road, London NW1 1AT, United Kingdom. Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London WC1 6BT, United Kingdom.

Active networks composed of filaments and motor proteins can self-organize into a variety of architectures. Computer simulations in two or three spatial dimensions and including or omitting steric interactions between filaments can be used to model active networks. Here we examine how these modelling choices affect the state space of network self-organization. Read More

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http://dx.doi.org/10.1088/1478-3975/ab0fb1DOI Listing

Methodological Characteristics of Clinical Trials: Impact of Mandatory Trial Registration.

J Pharm Pharm Sci 2019 ;22(1):131-141

Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.

Purpose: Numerous studies across multiple specialties have evaluated the impact of trial registration on quality of study reports and found significant improvements over several domains. However, the impact of mandatory trial registration on the quality of clinical trial protocols remains hitherto unexplored.

Methods: We carried out a retrospective cohort study of clinical trial applications submitted to drug regulatory authority of India for initial review with the objective of comparing methodological characteristics of their protocols. Read More

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http://dx.doi.org/10.18433/jpps30360DOI Listing
January 2019

Trends in Sedentary Behavior Among the US Population, 2001-2016.

JAMA 2019 Apr;321(16):1587-1597

Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, Missouri.

Importance: Prolonged sitting, particularly watching television or videos, has been associated with increased risk of multiple diseases and mortality. However, changes in sedentary behaviors over time have not been well described in the United States.

Objective: To evaluate patterns and temporal trends in sedentary behaviors and sociodemographic and lifestyle correlates in the US population. Read More

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http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.20
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http://dx.doi.org/10.1001/jama.2019.3636DOI Listing
April 2019
4 Reads

The Potential of Game-Based Digital Biomarkers for Modeling Mental Health.

JMIR Ment Health 2019 Apr 23;6(4):e13485. Epub 2019 Apr 23.

Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.

Background: Assessment for mental health is performed by experts using interview techniques, questionnaires, and test batteries and following standardized manuals; however, there would be myriad benefits if behavioral correlates could predict mental health and be used for population screening or prevalence estimations. A variety of digital sources of data (eg, online search data and social media posts) have been previously proposed as candidates for digital biomarkers in the context of mental health. Playing games on computers, gaming consoles, or mobile devices (ie, digital gaming) has become a leading leisure activity of choice and yields rich data from a variety of sources. Read More

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http://mental.jmir.org/2019/4/e13485/
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http://dx.doi.org/10.2196/13485DOI Listing
April 2019
6 Reads

The Use of Cancer-Specific Patient-Centered Technologies Among Underserved Populations in the United States: Systematic Review.

J Med Internet Res 2019 Apr 23;21(4):e10256. Epub 2019 Apr 23.

VA Health Services Research and Development, Center for Health Information & Communication, Richard L Roudebush VA Medical Center, Indianapolis, IN, United States.

Background: In the United States, more than 1.6 million new cases of cancer are estimated to be diagnosed each year. However, the burden of cancer among the US population is not shared equally, with racial and ethnic minorities and lower-income populations having a higher cancer burden compared with their counterparts. Read More

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http://dx.doi.org/10.2196/10256DOI Listing

Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue.

AJR Am J Roentgenol 2019 Apr 23:1-9. Epub 2019 Apr 23.

1 The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287.

The objective of our study was to determine the utility of radiomics features in differentiating CT cases of pancreatic ductal adenocarcinoma (PDAC) from normal pancreas. In this retrospective case-control study, 190 patients with PDAC (97 men, 93 women; mean age ± SD, 66 ± 9 years) from 2012 to 2017 and 190 healthy potential renal donors (96 men, 94 women; mean age ± SD, 52 ± 8 years) without known pancreatic disease from 2005 to 2009 were identified from radiology and pathology databases. The 3D volume of the pancreas was manually segmented from the preoperative CT scans by four trained researchers and verified by three abdominal radiologists. Read More

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http://dx.doi.org/10.2214/AJR.18.20901DOI Listing

A Predictive-Reactive Approach with Genetic Programming and Cooperative Co-evolution for Uncertain Capacitated Arc Routing Problem.

Evol Comput 2019 Apr 23:1-25. Epub 2019 Apr 23.

College of Computer & Information Science, Southwest University, Chongqing 400715, China; School of Information Technology, Deakin University, Locked Bag 20000, Geelong VIC 3220, Australia

The uncertain capacitated arc routing problem is of great significance for its wide applications in the real world. In uncertain capacitated arc routing problem, variables such as task demands and travel costs are realised in real time. This may cause the predefined solution to become ineffective and/or infeasible. Read More

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https://www.mitpressjournals.org/doi/abs/10.1162/evco_a_0025
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http://dx.doi.org/10.1162/evco_a_00256DOI Listing
April 2019
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Parameterized Analysis of Multi-objective Evolutionary Algorithms and the Weighted Vertex Cover Problem.

Evol Comput 2019 Apr 23:1-17. Epub 2019 Apr 23.

Optimisation and Logistics, The University of Adelaide, Adelaide, SA 5005, Australia

Evolutionary multi-objective optimization for the classical vertex cover problem has been analysed in [12] in the context of parameterized complexity analysis. This paper extends the analysis to the weighted vertex cover problem in which integer weights are assigned to the vertices and the goal is to find a vertex cover of minimum weight. Using an alternative mutation operator introduced in [12], we provide a fixed parameter evolutionary algorithm with respect to , the cost of an optimal solution for the problem. Read More

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http://dx.doi.org/10.1162/evco_a_00255DOI Listing

Observation of Two Resonances in the Λ_{b}^{0}π^{±} Systems and Precise Measurement of Σ_{b}^{±} and Σ_{b}^{*±} Properties.

Authors:
R Aaij C Abellán Beteta B Adeva M Adinolfi C A Aidala Z Ajaltouni S Akar P Albicocco J Albrecht F Alessio M Alexander A Alfonso Albero G Alkhazov P Alvarez Cartelle A A Alves S Amato S Amerio Y Amhis L An L Anderlini G Andreassi M Andreotti J E Andrews R B Appleby F Archilli J Arnau Romeu A Artamonov M Artuso K Arzymatov E Aslanides M Atzeni B Audurier S Bachmann J J Back S Baker V Balagura W Baldini A Baranov R J Barlow S Barsuk W Barter F Baryshnikov V Batozskaya B Batsukh V Battista A Bay J Beddow F Bedeschi I Bediaga A Beiter L J Bel S Belin N Beliy V Bellee N Belloli K Belous I Belyaev G Bencivenni E Ben-Haim S Benson S Beranek A Berezhnoy R Bernet D Berninghoff E Bertholet A Bertolin C Betancourt F Betti M O Bettler Ia Bezshyiko S Bhasin J Bhom S Bifani P Billoir A Birnkraut A Bizzeti M Bjørn M P Blago T Blake F Blanc S Blusk D Bobulska V Bocci O Boente Garcia T Boettcher A Bondar N Bondar S Borghi M Borisyak M Borsato F Bossu M Boubdir T J V Bowcock C Bozzi S Braun M Brodski J Brodzicka A Brossa Gonzalo D Brundu E Buchanan A Buonaura C Burr A Bursche J Buytaert W Byczynski S Cadeddu H Cai R Calabrese R Calladine M Calvi M Calvo Gomez A Camboni P Campana D H Campora Perez L Capriotti A Carbone G Carboni R Cardinale A Cardini P Carniti L Carson K Carvalho Akiba G Casse L Cassina M Cattaneo G Cavallero R Cenci D Chamont M G Chapman M Charles Ph Charpentier G Chatzikonstantinidis M Chefdeville V Chekalina C Chen S Chen S-G Chitic V Chobanova M Chrzaszcz A Chubykin P Ciambrone X Cid Vidal G Ciezarek F Cindolo P E L Clarke M Clemencic H V Cliff J Closier V Coco J A B Coelho J Cogan E Cogneras L Cojocariu P Collins T Colombo A Comerma-Montells A Contu G Coombs S Coquereau G Corti M Corvo C M Costa Sobral B Couturier G A Cowan D C Craik A Crocombe M Cruz Torres R Currie F Da Cunha Marinho C L Da Silva E Dall'Occo J Dalseno C D'Ambrosio A Danilina P d'Argent A Davis O De Aguiar Francisco K De Bruyn S De Capua M De Cian J M De Miranda L De Paula M De Serio P De Simone J A de Vries C T Dean D Decamp L Del Buono B Delaney H-P Dembinski M Demmer A Dendek D Derkach O Deschamps F Desse F Dettori B Dey A Di Canto P Di Nezza S Didenko H Dijkstra F Dordei M Dorigo A C Dos Reis A Dosil Suárez L Douglas A Dovbnya K Dreimanis L Dufour G Dujany P Durante J M Durham D Dutta R Dzhelyadin M Dziewiecki A Dziurda A Dzyuba S Easo U Egede V Egorychev S Eidelman S Eisenhardt U Eitschberger R Ekelhof L Eklund S Ely A Ene S Escher S Esen T Evans A Falabella C Färber N Farley S Farry D Fazzini L Federici M Féo P Fernandez Declara A Fernandez Prieto F Ferrari L Ferreira Lopes F Ferreira Rodrigues M Ferro-Luzzi S Filippov R A Fini M Fiorini M Firlej C Fitzpatrick T Fiutowski F Fleuret M Fontana F Fontanelli R Forty V Franco Lima M Frank C Frei J Fu W Funk E Gabriel A Gallas Torreira D Galli S Gallorini S Gambetta Y Gan M Gandelman P Gandini Y Gao L M Garcia Martin J García Pardiñas B Garcia Plana J Garra Tico L Garrido D Gascon C Gaspar L Gavardi G Gazzoni D Gerick E Gersabeck M Gersabeck T Gershon D Gerstel Ph Ghez S Gianì V Gibson O G Girard L Giubega K Gizdov V V Gligorov C Göbel D Golubkov A Golutvin A Gomes I V Gorelov C Gotti E Govorkova J P Grabowski R Graciani Diaz L A Granado Cardoso E Graugés E Graverini G Graziani A Grecu R Greim P Griffith L Grillo L Gruber B R Gruberg Cazon O Grünberg C Gu E Gushchin Yu Guz T Gys T Hadavizadeh C Hadjivasiliou G Haefeli C Haen S C Haines B Hamilton X Han T H Hancock S Hansmann-Menzemer N Harnew S T Harnew T Harrison C Hasse M Hatch J He M Hecker K Heinicke A Heister K Hennessy L Henry M Heß A Hicheur R Hidalgo Charman D Hill M Hilton P H Hopchev W Hu W Huang Z C Huard W Hulsbergen T Humair M Hushchyn D Hutchcroft D Hynds P Ibis M Idzik P Ilten A Inyakin K Ivshin R Jacobsson J Jalocha E Jans B K Jashal A Jawahery F Jiang M John D Johnson C R Jones C Joram B Jost N Jurik S Kandybei M Karacson J M Kariuki S Karodia N Kazeev M Kecke F Keizer M Kelsey M Kenzie T Ketel E Khairullin B Khanji C Khurewathanakul K E Kim T Kirn S Klaver K Klimaszewski T Klimkovich S Koliiev M Kolpin R Kopecna P Koppenburg I Kostiuk S Kotriakhova M Kozeiha L Kravchuk M Kreps F Kress P Krokovny W Krupa W Krzemien W Kucewicz M Kucharczyk V Kudryavtsev A K Kuonen T Kvaratskheliya D Lacarrere G Lafferty A Lai D Lancierini G Lanfranchi C Langenbruch T Latham C Lazzeroni R Le Gac R Lefèvre A Leflat J Lefrançois F Lemaitre O Leroy T Lesiak B Leverington P-R Li T Li Z Li X Liang T Likhomanenko R Lindner F Lionetto V Lisovskyi X Liu D Loh A Loi I Longstaff J H Lopes G H Lovell D Lucchesi M Lucio Martinez A Lupato E Luppi O Lupton A Lusiani X Lyu F Machefert F Maciuc V Macko P Mackowiak S Maddrell-Mander O Maev K Maguire D Maisuzenko M W Majewski S Malde B Malecki A Malinin T Maltsev G Manca G Mancinelli D Marangotto J Maratas J F Marchand U Marconi C Marin Benito M Marinangeli P Marino J Marks P J Marshall G Martellotti M Martin M Martinelli D Martinez Santos F Martinez Vidal A Massafferri M Materok R Matev A Mathad Z Mathe C Matteuzzi A Mauri E Maurice B Maurin A Mazurov M McCann A McNab R McNulty J V Mead B Meadows C Meaux F Meier N Meinert D Melnychuk M Merk A Merli E Michielin D A Milanes E Millard M-N Minard L Minzoni D S Mitzel A Mödden A Mogini J Molina Rodriguez T Mombächer I A Monroy S Monteil M Morandin G Morello M J Morello O Morgunova J Moron A B Morris R Mountain F Muheim M Mulder D Müller J Müller K Müller V Müller C H Murphy D Murray P Naik T Nakada R Nandakumar A Nandi T Nanut I Nasteva M Needham N Neri S Neubert N Neufeld M Neuner R Newcombe T D Nguyen C Nguyen-Mau S Nieswand R Niet N Nikitin A Nogay N S Nolte A Oblakowska-Mucha V Obraztsov S Ogilvy D P O'Hanlon R Oldeman C J G Onderwater A Ossowska J M Otalora Goicochea P Owen A Oyanguren P R Pais T Pajero A Palano M Palutan G Panshin A Papanestis M Pappagallo L L Pappalardo W Parker C Parkes G Passaleva A Pastore M Patel C Patrignani A Pearce A Pellegrino G Penso M Pepe Altarelli S Perazzini D Pereima P Perret L Pescatore K Petridis A Petrolini A Petrov S Petrucci M Petruzzo B Pietrzyk G Pietrzyk M Pikies M Pili D Pinci J Pinzino F Pisani A Piucci V Placinta S Playfer J Plews M Plo Casasus F Polci M Poli Lener A Poluektov N Polukhina I Polyakov E Polycarpo G J Pomery S Ponce A Popov D Popov S Poslavskii C Potterat E Price J Prisciandaro C Prouve V Pugatch A Puig Navarro H Pullen G Punzi W Qian J Qin R Quagliani B Quintana N V Raab B Rachwal J H Rademacker M Rama M Ramos Pernas M S Rangel F Ratnikov G Raven M Ravonel Salzgeber M Reboud F Redi S Reichert F Reiss C Remon Alepuz Z Ren V Renaudin S Ricciardi S Richards K Rinnert P Robbe A Robert A B Rodrigues E Rodrigues J A Rodriguez Lopez M Roehrken S Roiser A Rollings V Romanovskiy A Romero Vidal M Rotondo M S Rudolph T Ruf J Ruiz Vidal J J Saborido Silva N Sagidova B Saitta V Salustino Guimaraes C Sanchez Gras C Sanchez Mayordomo B Sanmartin Sedes R Santacesaria C Santamarina Rios M Santimaria E Santovetti G Sarpis A Sarti C Satriano A Satta M Saur D Savrina S Schael M Schellenberg M Schiller H Schindler M Schmelling T Schmelzer B Schmidt O Schneider A Schopper H F Schreiner M Schubiger M H Schune R Schwemmer B Sciascia A Sciubba A Semennikov E S Sepulveda A Sergi N Serra J Serrano L Sestini A Seuthe P Seyfert M Shapkin Y Shcheglov T Shears L Shekhtman V Shevchenko E Shmanin B G Siddi R Silva Coutinho L Silva de Oliveira G Simi S Simone I Skiba N Skidmore T Skwarnicki M W Slater J G Smeaton E Smith I T Smith M Smith M Soares L Soares Lavra M D Sokoloff F J P Soler B Souza De Paula B Spaan E Spadaro Norella P Spradlin F Stagni M Stahl S Stahl P Stefko S Stefkova O Steinkamp S Stemmle O Stenyakin M Stepanova H Stevens A Stocchi S Stone B Storaci S Stracka M E Stramaglia M Straticiuc U Straumann S Strokov J Sun L Sun K Swientek T Szumlak M Szymanski Z Tang A Tayduganov T Tekampe G Tellarini F Teubert E Thomas M J Tilley V Tisserand S T'Jampens M Tobin S Tolk L Tomassetti D Tonelli D Y Tou R Tourinho Jadallah Aoude E Tournefier M Traill M T Tran A Trisovic A Tsaregorodtsev G Tuci A Tully N Tuning A Ukleja A Usachov A Ustyuzhanin U Uwer A Vagner V Vagnoni A Valassi S Valat G Valenti M van Beuzekom E van Herwijnen J van Tilburg M van Veghel R Vazquez Gomez P Vazquez Regueiro C Vázquez Sierra S Vecchi J J Velthuis M Veltri G Veneziano A Venkateswaran T A Verlage M Vernet M Veronesi M Vesterinen J V Viana Barbosa D Vieira M Vieites Diaz H Viemann X Vilasis-Cardona A Vitkovskiy M Vitti V Volkov A Vollhardt D Vom Bruch B Voneki A Vorobyev V Vorobyev N Voropaev R Waldi J Walsh J Wang M Wang Y Wang Z Wang D R Ward H M Wark N K Watson D Websdale A Weiden C Weisser M Whitehead J Wicht G Wilkinson M Wilkinson I Williams M Williams M R J Williams T Williams F F Wilson J Wimberley M Winn J Wishahi W Wislicki M Witek G Wormser S A Wotton K Wyllie D Xiao Y Xie A Xu M Xu Q Xu Z Xu Z Xu Z Yang Z Yang Y Yao L E Yeomans H Yin J Yu X Yuan O Yushchenko K A Zarebski M Zavertyaev D Zhang L Zhang W C Zhang Y Zhang A Zhelezov Y Zheng X Zhu V Zhukov J B Zonneveld S Zucchelli

Phys Rev Lett 2019 Jan;122(1):012001

INFN Sezione di Bologna, Bologna, Italy.

The first observation of two structures consistent with resonances in the final states Λ_{b}^{0}π^{-} and Λ_{b}^{0}π^{+} is reported using samples of pp collision data collected by the LHCb experiment at sqrt[s]=7 and 8 TeV, corresponding to an integrated luminosity of 3  fb^{-1}. The ground states Σ_{b}^{±} and Σ_{b}^{*±} are also confirmed and their masses and widths are precisely measured. Read More

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http://dx.doi.org/10.1103/PhysRevLett.122.012001DOI Listing
January 2019

Measurement of the Charm-Mixing Parameter y_{CP}.

Authors:
R Aaij C Abellán Beteta B Adeva M Adinolfi C A Aidala Z Ajaltouni S Akar P Albicocco J Albrecht F Alessio M Alexander A Alfonso Albero G Alkhazov P Alvarez Cartelle A A Alves S Amato S Amerio Y Amhis L An L Anderlini G Andreassi M Andreotti J E Andrews F Archilli P d'Argent J Arnau Romeu A Artamonov M Artuso K Arzymatov E Aslanides M Atzeni B Audurier S Bachmann J J Back S Baker V Balagura W Baldini A Baranov R J Barlow G C Barrand S Barsuk W Barter M Bartolini F Baryshnikov V Batozskaya B Batsukh A Battig V Battista A Bay J Beddow F Bedeschi I Bediaga A Beiter L J Bel S Belin N Beliy V Bellee N Belloli K Belous I Belyaev E Ben-Haim G Bencivenni S Benson S Beranek A Berezhnoy R Bernet D Berninghoff E Bertholet A Bertolin C Betancourt F Betti M O Bettler M van Beuzekom Ia Bezshyiko S Bhasin J Bhom S Bifani P Billoir A Birnkraut A Bizzeti M Bjørn M P Blago T Blake F Blanc S Blusk D Bobulska V Bocci O Boente Garcia T Boettcher A Bondar N Bondar S Borghi M Borisyak M Borsato F Bossu M Boubdir T J V Bowcock C Bozzi S Braun M Brodski J Brodzicka A Brossa Gonzalo D Brundu E Buchanan A Buonaura C Burr A Bursche J Buytaert W Byczynski S Cadeddu H Cai R Calabrese R Calladine M Calvi M Calvo Gomez A Camboni P Campana D H Campora Perez L Capriotti A Carbone G Carboni R Cardinale A Cardini P Carniti L Carson K Carvalho Akiba G Casse L Cassina M Cattaneo G Cavallero R Cenci D Chamont M G Chapman M Charles Ph Charpentier G Chatzikonstantinidis M Chefdeville V Chekalina C Chen S Chen S-G Chitic V Chobanova M Chrzaszcz A Chubykin P Ciambrone X Cid Vidal G Ciezarek P E L Clarke M Clemencic H V Cliff J Closier V Coco J A B Coelho J Cogan E Cogneras L Cojocariu P Collins T Colombo A Comerma-Montells A Contu G Coombs S Coquereau G Corti M Corvo C M Costa Sobral B Couturier G A Cowan D C Craik A Crocombe M Cruz Torres R Currie C D'Ambrosio F Da Cunha Marinho C L Da Silva E Dall'Occo J Dalseno A Danilina A Davis O De Aguiar Francisco K De Bruyn S De Capua M De Cian J M De Miranda L De Paula M De Serio P De Simone C T Dean D Decamp L Del Buono B Delaney H-P Dembinski M Demmer A Dendek D Derkach O Deschamps F Desse F Dettori B Dey A Di Canto P Di Nezza S Didenko H Dijkstra F Dordei M Dorigo A Dosil Suárez L Douglas A Dovbnya K Dreimanis L Dufour G Dujany P Durante J M Durham D Dutta R Dzhelyadin M Dziewiecki A Dziurda A Dzyuba S Easo U Egede V Egorychev S Eidelman S Eisenhardt U Eitschberger R Ekelhof L Eklund S Ely A Ene S Escher S Esen T Evans A Falabella N Farley S Farry D Fazzini L Federici P Fernandez Declara A Fernandez Prieto F Ferrari L Ferreira Lopes F Ferreira Rodrigues M Ferro-Luzzi S Filippov R A Fini M Fiorini M Firlej C Fitzpatrick T Fiutowski F Fleuret M Fontana F Fontanelli R Forty V Franco Lima M Frank C Frei J Fu W Funk C Färber M Féo E Gabriel A Gallas Torreira D Galli S Gallorini S Gambetta Y Gan M Gandelman P Gandini Y Gao L M Garcia Martin B Garcia Plana J García Pardiñas J Garra Tico L Garrido D Gascon C Gaspar L Gavardi G Gazzoni D Gerick E Gersabeck M Gersabeck T Gershon D Gerstel Ph Ghez V Gibson O G Girard P Gironella Gironell L Giubega K Gizdov V V Gligorov D Golubkov A Golutvin A Gomes I V Gorelov C Gotti E Govorkova J P Grabowski R Graciani Diaz L A Granado Cardoso E Graugés E Graverini G Graziani A Grecu R Greim P Griffith L Grillo L Gruber B R Gruberg Cazon O Grünberg C Gu E Gushchin A Guth Yu Guz T Gys C Göbel T Hadavizadeh C Hadjivasiliou G Haefeli C Haen S C Haines B Hamilton X Han T H Hancock S Hansmann-Menzemer N Harnew S T Harnew T Harrison C Hasse M Hatch J He M Hecker K Heinicke A Heister K Hennessy L Henry E van Herwijnen J Heuel M Heß A Hicheur R Hidalgo Charman D Hill M Hilton P H Hopchev J Hu W Hu W Huang Z C Huard W Hulsbergen T Humair M Hushchyn D Hutchcroft D Hynds P Ibis M Idzik P Ilten K Ivshin R Jacobsson J Jalocha E Jans A Jawahery F Jiang M John D Johnson C R Jones C Joram B Jost N Jurik S Kandybei M Karacson J M Kariuki S Karodia N Kazeev M Kecke F Keizer M Kelsey M Kenzie T Ketel E Khairullin B Khanji C Khurewathanakul K E Kim T Kirn S Klaver K Klimaszewski T Klimkovich S Koliiev M Kolpin R Kopecna P Koppenburg I Kostiuk S Kotriakhova M Kozeiha L Kravchuk M Kreps F Kress P Krokovny W Krupa W Krzemien W Kucewicz M Kucharczyk V Kudryavtsev A K Kuonen T Kvaratskheliya D Lacarrere G Lafferty A Lai D Lancierini G Lanfranchi C Langenbruch T Latham C Lazzeroni R Le Gac A Leflat J Lefrançois R Lefèvre F Lemaitre O Leroy T Lesiak B Leverington P-R Li Y Li Z Li X Liang T Likhomanenko R Lindner F Lionetto V Lisovskyi G Liu X Liu D Loh A Loi I Longstaff J H Lopes G H Lovell D Lucchesi M Lucio Martinez A Lupato E Luppi O Lupton A Lusiani X Lyu F Machefert F Maciuc V Macko P Mackowiak S Maddrell-Mander O Maev K Maguire D Maisuzenko M W Majewski S Malde B Malecki A Malinin T Maltsev G Manca G Mancinelli D Marangotto J Maratas J F Marchand U Marconi C Marin Benito M Marinangeli P Marino J Marks P J Marshall G Martellotti M Martin M Martinelli D Martinez Santos F Martinez Vidal A Massafferri M Materok R Matev A Mathad Z Mathe C Matteuzzi A Mauri E Maurice B Maurin A Mazurov M McCann A McNab R McNulty J V Mead B Meadows C Meaux N Meinert D Melnychuk M Merk A Merli E Michielin D A Milanes E Millard M-N Minard L Minzoni D S Mitzel A Mogini R D Moise T Mombächer I A Monroy S Monteil M Morandin G Morello M J Morello O Morgunova J Moron A B Morris R Mountain F Muheim M Mulder C H Murphy D Murray A Mödden D Müller J Müller K Müller V Müller P Naik T Nakada R Nandakumar A Nandi T Nanut I Nasteva M Needham N Neri S Neubert N Neufeld M Neuner R Newcombe T D Nguyen C Nguyen-Mau S Nieswand R Niet N Nikitin A Nogay N S Nolte D P O'Hanlon A Oblakowska-Mucha V Obraztsov S Ogilvy R Oldeman C J G Onderwater A Ossowska J M Otalora Goicochea T Ovsiannikova P Owen A Oyanguren P R Pais T Pajero A Palano M Palutan G Panshin A Papanestis M Pappagallo L L Pappalardo W Parker C Parkes G Passaleva A Pastore M Patel C Patrignani A Pearce A Pellegrino G Penso M Pepe Altarelli S Perazzini D Pereima P Perret L Pescatore K Petridis A Petrolini A Petrov S Petrucci M Petruzzo B Pietrzyk G Pietrzyk M Pikies M Pili D Pinci J Pinzino F Pisani A Piucci V Placinta S Playfer J Plews M Plo Casasus F Polci M Poli Lener A Poluektov N Polukhina I Polyakov E Polycarpo G J Pomery S Ponce A Popov D Popov S Poslavskii C Potterat E Price J Prisciandaro C Prouve V Pugatch A Puig Navarro H Pullen G Punzi W Qian J Qin R Quagliani B Quintana B Rachwal J H Rademacker M Rama M Ramos Pernas M S Rangel F Ratnikov G Raven M Ravonel Salzgeber M Reboud F Redi S Reichert A C Dos Reis F Reiss C Remon Alepuz Z Ren V Renaudin S Ricciardi S Richards K Rinnert P Robbe A Robert A B Rodrigues E Rodrigues J A Rodriguez Lopez M Roehrken S Roiser A Rollings V Romanovskiy A Romero Vidal M Rotondo M S Rudolph T Ruf J Ruiz Vidal J J Saborido Silva N Sagidova B Saitta V Salustino Guimaraes C Sanchez Gras C Sanchez Mayordomo B Sanmartin Sedes R Santacesaria C Santamarina Rios M Santimaria E Santovetti G Sarpis A Sarti C Satriano A Satta M Saur D Savrina S Schael M Schellenberg M Schiller H Schindler M Schmelling T Schmelzer B Schmidt O Schneider A Schopper H F Schreiner M Schubiger M H Schune R Schwemmer B Sciascia A Sciubba A Semennikov E S Sepulveda A Sergi N Serra J Serrano L Sestini A Seuthe P Seyfert M Shapkin Y Shcheglov T Shears L Shekhtman V Shevchenko E Shmanin B G Siddi R Silva Coutinho L Silva de Oliveira G Simi S Simone I Skiba N Skidmore T Skwarnicki M W Slater J G Smeaton E Smith I T Smith M Smith M Soares L Soares Lavra M D Sokoloff F J P Soler B Souza De Paula B Spaan E Spadaro Norella P Spradlin F Stagni M Stahl S Stahl P Stefko S Stefkova O Steinkamp S Stemmle O Stenyakin M Stepanova H Stevens A Stocchi S Stone B Storaci S Stracka M E Stramaglia M Straticiuc U Straumann S Strokov J Sun L Sun K Swientek A Szabelski T Szumlak M Szymanski S T'Jampens Z Tang A Tayduganov T Tekampe G Tellarini F Teubert E Thomas J van Tilburg M J Tilley V Tisserand M Tobin S Tolk L Tomassetti D Tonelli D Y Tou R Tourinho Jadallah Aoude E Tournefier M Traill M T Tran A Trisovic A Tsaregorodtsev G Tuci A Tully N Tuning A Ukleja A Usachov A Ustyuzhanin U Uwer A Vagner V Vagnoni A Valassi S Valat G Valenti R Vazquez Gomez P Vazquez Regueiro S Vecchi M van Veghel J J Velthuis M Veltri G Veneziano A Venkateswaran M Vernet M Veronesi N V Veronika M Vesterinen J V Viana Barbosa D Vieira M Vieites Diaz H Viemann X Vilasis-Cardona A Vitkovskiy M Vitti V Volkov A Vollhardt D Vom Bruch B Voneki A Vorobyev V Vorobyev J A de Vries C Vázquez Sierra R Waldi J Walsh J Wang M Wang Y Wang Z Wang D R Ward H M Wark N K Watson D Websdale A Weiden C Weisser M Whitehead J Wicht G Wilkinson M Wilkinson I Williams M R J Williams M Williams T Williams F F Wilson M Winn W Wislicki M Witek G Wormser S A Wotton K Wyllie D Xiao Y Xie A Xu M Xu Q Xu Z Xu Z Xu Z Yang Z Yang Y Yao L E Yeomans H Yin J Yu X Yuan O Yushchenko K A Zarebski M Zavertyaev D Zhang L Zhang W C Zhang Y Zhang A Zhelezov Y Zheng X Zhu V Zhukov J B Zonneveld S Zucchelli

Phys Rev Lett 2019 Jan;122(1):011802

INFN Sezione di Bologna, Bologna, Italy.

A measurement of the charm-mixing parameter y_{CP} using D^{0}→K^{+}K^{-}, D^{0}→π^{+}π^{-}, and D^{0}→K^{-}π^{+} decays is reported. The D^{0} mesons are required to originate from semimuonic decays of B^{-} and B[over ¯]^{0} mesons. These decays are partially reconstructed in a data set of proton-proton collisions at center-of-mass energies of 7 and 8 TeV collected with the LHCb experiment and corresponding to an integrated luminosity of 3  fb^{-1}. Read More

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January 2019
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Cluster Synchronization in Multilayer Networks: A Fully Analog Experiment with LC Oscillators with Physically Dissimilar Coupling.

Phys Rev Lett 2019 Jan;122(1):014101

Department of Mechanical Engineering, University of New Mexico, Albuquerque, New Mexico 87131, USA.

We investigate cluster synchronization in experiments with a multilayer network of electronic Colpitts oscillators, specifically a network with two interaction layers. We observe and analytically characterize the appearance of several cluster states as we change coupling in the layers. In this study, we innovatively combine bifurcation analysis and the computation of transverse Lyapunov exponents. Read More

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January 2019

First Measurement of Charm Production in its Fixed-Target Configuration at the LHC.

Authors:
R Aaij B Adeva M Adinolfi C A Aidala Z Ajaltouni S Akar P Albicocco J Albrecht F Alessio M Alexander A Alfonso Albero S Ali G Alkhazov P Alvarez Cartelle A A Alves S Amato S Amerio Y Amhis L An L Anderlini G Andreassi M Andreotti J E Andrews R B Appleby F Archilli P d'Argent J Arnau Romeu A Artamonov M Artuso K Arzymatov E Aslanides M Atzeni B Audurier S Bachmann J J Back S Baker V Balagura W Baldini A Baranov R J Barlow S Barsuk W Barter F Baryshnikov V Batozskaya B Batsukh V Battista A Bay J Beddow F Bedeschi I Bediaga A Beiter L J Bel S Belin N Beliy V Bellee N Belloli K Belous I Belyaev E Ben-Haim G Bencivenni S Benson S Beranek A Berezhnoy R Bernet D Berninghoff E Bertholet A Bertolin C Betancourt F Betti M O Bettler M van Beuzekom Ia Bezshyiko S Bhasin J Bhom S Bifani P Billoir A Birnkraut A Bizzeti M Bjørn M P Blago T Blake F Blanc S Blusk D Bobulska V Bocci O Boente Garcia T Boettcher A Bondar N Bondar S Borghi M Borisyak M Borsato F Bossu M Boubdir T J V Bowcock C Bozzi S Braun M Brodski J Brodzicka A Brossa Gonzalo D Brundu E Buchanan A Buonaura C Burr A Bursche J Buytaert W Byczynski S Cadeddu H Cai R Calabrese R Calladine M Calvi M Calvo Gomez A Camboni P Campana D H Campora Perez L Capriotti A Carbone G Carboni R Cardinale A Cardini P Carniti L Carson K Carvalho Akiba G Casse L Cassina M Cattaneo G Cavallero R Cenci D Chamont M G Chapman M Charles Ph Charpentier G Chatzikonstantinidis M Chefdeville V Chekalina C Chen S Chen S-G Chitic V Chobanova M Chrzaszcz A Chubykin P Ciambrone X Cid Vidal G Ciezarek P E L Clarke M Clemencic H V Cliff J Closier V Coco J A B Coelho J Cogan E Cogneras L Cojocariu P Collins T Colombo A Comerma-Montells A Contu G Coombs S Coquereau G Corti M Corvo C M Costa Sobral B Couturier G A Cowan D C Craik A Crocombe M Cruz Torres R Currie C D'Ambrosio F Da Cunha Marinho C L Da Silva E Dall'Occo J Dalseno A Danilina A Davis O De Aguiar Francisco K De Bruyn S De Capua M De Cian J M De Miranda L De Paula M De Serio P De Simone C T Dean D Decamp L Del Buono B Delaney H-P Dembinski M Demmer A Dendek D Derkach O Deschamps F Desse F Dettori B Dey A Di Canto P Di Nezza S Didenko H Dijkstra F Dordei M Dorigo A Dosil Suárez L Douglas A Dovbnya K Dreimanis L Dufour G Dujany P Durante J M Durham D Dutta R Dzhelyadin M Dziewiecki A Dziurda A Dzyuba S Easo U Egede V Egorychev S Eidelman S Eisenhardt U Eitschberger R Ekelhof L Eklund S Ely A Ene S Escher S Esen T Evans A Falabella N Farley S Farry D Fazzini L Federici P Fernandez Declara A Fernandez Prieto F Ferrari L Ferreira Lopes F Ferreira Rodrigues M Ferro-Luzzi S Filippov R A Fini M Fiorini M Firlej C Fitzpatrick T Fiutowski F Fleuret M Fontana F Fontanelli R Forty V Franco Lima M Frank C Frei J Fu W Funk C Färber M Féo E Gabriel A Gallas Torreira D Galli S Gallorini S Gambetta Y Gan M Gandelman P Gandini Y Gao L M Garcia Martin B Garcia Plana J García Pardiñas J Garra Tico L Garrido D Gascon C Gaspar L Gavardi G Gazzoni D Gerick E Gersabeck M Gersabeck T Gershon D Gerstel Ph Ghez S Gianì V Gibson O G Girard L Giubega K Gizdov V V Gligorov D Golubkov A Golutvin A Gomes I V Gorelov C Gotti E Govorkova J P Grabowski R Graciani Diaz L A Granado Cardoso E Graugés E Graverini G Graziani A Grecu R Greim P Griffith L Grillo L Gruber B R Gruberg Cazon O Grünberg C Gu E Gushchin Yu Guz T Gys C Göbel T Hadavizadeh C Hadjivasiliou G Haefeli C Haen S C Haines B Hamilton X Han T H Hancock S Hansmann-Menzemer N Harnew S T Harnew T Harrison C Hasse M Hatch J He M Hecker K Heinicke A Heister K Hennessy L Henry E van Herwijnen M Heß A Hicheur R Hidalgo Charman D Hill M Hilton P H Hopchev W Hu W Huang Z C Huard W Hulsbergen T Humair M Hushchyn D Hutchcroft D Hynds P Ibis M Idzik P Ilten K Ivshin R Jacobsson J Jalocha E Jans A Jawahery F Jiang M John D Johnson C R Jones C Joram B Jost N Jurik S Kandybei M Karacson J M Kariuki S Karodia N Kazeev M Kecke F Keizer M Kelsey M Kenzie T Ketel E Khairullin B Khanji C Khurewathanakul K E Kim T Kirn S Klaver K Klimaszewski T Klimkovich S Koliiev M Kolpin R Kopecna P Koppenburg I Kostiuk S Kotriakhova M Kozeiha L Kravchuk M Kreps F Kress P Krokovny W Krupa W Krzemien W Kucewicz M Kucharczyk V Kudryavtsev A K Kuonen T Kvaratskheliya D Lacarrere G Lafferty A Lai D Lancierini G Lanfranchi C Langenbruch T Latham C Lazzeroni R Le Gac A Leflat J Lefrançois R Lefèvre F Lemaitre O Leroy T Lesiak B Leverington P-R Li T Li Z Li X Liang T Likhomanenko R Lindner F Lionetto V Lisovskyi X Liu D Loh A Loi I Longstaff J H Lopes G H Lovell D Lucchesi M Lucio Martinez A Lupato E Luppi O Lupton A Lusiani X Lyu F Machefert F Maciuc V Macko P Mackowiak S Maddrell-Mander O Maev K Maguire D Maisuzenko M W Majewski S Malde B Malecki A Malinin T Maltsev G Manca G Mancinelli D Marangotto J Maratas J F Marchand U Marconi C Marin Benito M Marinangeli P Marino J Marks P J Marshall G Martellotti M Martin M Martinelli D Martinez Santos F Martinez Vidal A Massafferri M Materok R Matev A Mathad Z Mathe C Matteuzzi A Mauri E Maurice B Maurin A Mazurov M McCann A McNab R McNulty J V Mead B Meadows C Meaux F Meier N Meinert D Melnychuk M Merk A Merli E Michielin D A Milanes E Millard M-N Minard L Minzoni D S Mitzel A Mogini J Molina Rodriguez T Mombächer I A Monroy S Monteil M Morandin G Morello M J Morello O Morgunova J Moron A B Morris R Mountain F Muheim M Mulder C H Murphy D Murray A Mödden D Müller J Müller K Müller V Müller P Naik T Nakada R Nandakumar A Nandi T Nanut I Nasteva M Needham N Neri S Neubert N Neufeld M Neuner T D Nguyen C Nguyen-Mau S Nieswand R Niet N Nikitin A Nogay N S Nolte D P O'Hanlon A Oblakowska-Mucha V Obraztsov S Ogilvy R Oldeman C J G Onderwater A Ossowska J M Otalora Goicochea P Owen A Oyanguren P R Pais T Pajero A Palano M Palutan G Panshin A Papanestis M Pappagallo L L Pappalardo W Parker C Parkes G Passaleva A Pastore M Patel C Patrignani A Pearce A Pellegrino G Penso M Pepe Altarelli S Perazzini D Pereima P Perret L Pescatore K Petridis A Petrolini A Petrov S Petrucci M Petruzzo B Pietrzyk G Pietrzyk M Pikies M Pili D Pinci J Pinzino F Pisani A Piucci V Placinta S Playfer J Plews M Plo Casasus F Polci M Poli Lener A Poluektov N Polukhina I Polyakov E Polycarpo G J Pomery S Ponce A Popov D Popov S Poslavskii C Potterat E Price J Prisciandaro C Prouve V Pugatch A Puig Navarro H Pullen G Punzi W Qian J Qin R Quagliani B Quintana B Rachwal J H Rademacker M Rama M Ramos Pernas M S Rangel F Ratnikov G Raven M Ravonel Salzgeber M Reboud F Redi S Reichert A C Dos Reis F Reiss C Remon Alepuz Z Ren V Renaudin S Ricciardi S Richards K Rinnert P Robbe A Robert A B Rodrigues E Rodrigues J A Rodriguez Lopez M Roehrken A Rogozhnikov S Roiser A Rollings V Romanovskiy A Romero Vidal M Rotondo M S Rudolph T Ruf J Ruiz Vidal J J Saborido Silva N Sagidova B Saitta V Salustino Guimaraes C Sanchez Gras C Sanchez Mayordomo B Sanmartin Sedes R Santacesaria C Santamarina Rios M Santimaria E Santovetti G Sarpis A Sarti C Satriano A Satta M Saur D Savrina S Schael M Schellenberg M Schiller H Schindler M Schmelling T Schmelzer B Schmidt O Schneider A Schopper H F Schreiner M Schubiger M H Schune R Schwemmer B Sciascia A Sciubba A Semennikov E S Sepulveda A Sergi N Serra J Serrano L Sestini A Seuthe P Seyfert M Shapkin Y Shcheglov T Shears L Shekhtman V Shevchenko E Shmanin B G Siddi R Silva Coutinho L Silva de Oliveira G Simi S Simone N Skidmore T Skwarnicki J G Smeaton E Smith I T Smith M Smith M Soares L Soares Lavra M D Sokoloff F J P Soler B Souza De Paula B Spaan P Spradlin F Stagni M Stahl S Stahl P Stefko S Stefkova O Steinkamp S Stemmle O Stenyakin M Stepanova H Stevens A Stocchi S Stone B Storaci S Stracka M E Stramaglia M Straticiuc U Straumann S Strokov J Sun L Sun K Swientek V Syropoulos T Szumlak M Szymanski S T'Jampens Z Tang A Tayduganov T Tekampe G Tellarini F Teubert E Thomas J van Tilburg M J Tilley V Tisserand M Tobin S Tolk L Tomassetti D Tonelli D Y Tou R Tourinho Jadallah Aoude E Tournefier M Traill M T Tran A Trisovic A Tsaregorodtsev G Tuci A Tully N Tuning A Ukleja A Usachov A Ustyuzhanin U Uwer A Vagner V Vagnoni A Valassi S Valat G Valenti R Vazquez Gomez P Vazquez Regueiro S Vecchi M van Veghel J J Velthuis M Veltri G Veneziano A Venkateswaran T A Verlage M Vernet M Veronesi N V Veronika M Vesterinen J V Viana Barbosa D Vieira M Vieites Diaz H Viemann X Vilasis-Cardona A Vitkovskiy M Vitti V Volkov A Vollhardt B Voneki A Vorobyev V Vorobyev J A de Vries C Vázquez Sierra R Waldi J Walsh J Wang M Wang Y Wang Z Wang D R Ward H M Wark N K Watson D Websdale A Weiden C Weisser M Whitehead J Wicht G Wilkinson M Wilkinson I Williams M R J Williams M Williams T Williams F F Wilson J Wimberley M Winn J Wishahi W Wislicki M Witek G Wormser S A Wotton K Wyllie D Xiao Y Xie A Xu M Xu Q Xu Z Xu Z Xu Z Yang Z Yang Y Yao L E Yeomans H Yin J Yu X Yuan O Yushchenko K A Zarebski M Zavertyaev D Zhang L Zhang W C Zhang Y Zhang A Zhelezov Y Zheng X Zhu V Zhukov J B Zonneveld S Zucchelli

Phys Rev Lett 2019 Apr;122(13):132002

INFN Sezione di Bologna, Bologna, Italy.

The first measurement of heavy-flavor production by the LHCb experiment in its fixed-target mode is presented. The production of J/ψ and D^{0} mesons is studied with beams of protons of different energies colliding with gaseous targets of helium and argon with nucleon-nucleon center-of-mass energies of sqrt[s_{NN}]=86.6 and 110. Read More

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April 2019
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Accelerating Kidney Allocation: Simultaneously Expiring Offers.

Am J Transplant 2019 Apr 23. Epub 2019 Apr 23.

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Placing non-ideal kidneys quickly might reduce discard. We studied changing kidney allocation to eliminate sequential offers, instead making offers to multiple centers for all non-locally allocated kidneys, so that multiple centers must accept or decline within the same one hour. If more than one center accepted an offer, the kidney would go to the highest-priority accepting candidate. Read More

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http://dx.doi.org/10.1111/ajt.15396DOI Listing

Validation of a rhinologic virtual surgical simulator for performing a Draf 3 endoscopic frontal sinusotomy.

Int Forum Allergy Rhinol 2019 Apr 23. Epub 2019 Apr 23.

Department of Otolaryngology-Head & Neck Surgery, Stanford University, Stanford, CA.

Background: We recently introduced a patient-specific rhinologic virtual surgical environment (VSE) that has shown potential for surgical rehearsal of various skull base lesions. Our aim in this study was to validate the usefulness of the rhinology VSE in performing the Draf 3 procedure.

Methods: An outside-in Draf 3 procedure was performed on 4 cadaver heads. Read More

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http://dx.doi.org/10.1002/alr.22333DOI Listing

Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine Learning Approach with Multi-Trial Replication.

Clin Pharmacol Ther 2019 Apr 23. Epub 2019 Apr 23.

Dept. of Psychiatry & Psychology, Mayo Clinic, Jacksonville, FL.

We set out to determine whether machine learning-based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 Caucasian MDD outpatients treated with citalopram/escitalopram in the PGRN-AMPS (n = 398), STAR*D (n = 467), and ISPC (n = 165) trials. GWAS for PGRN-AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified SNPs in DEFB1, ERICH3, AHR, and TSPAN5 that we tested as predictors. Read More

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http://dx.doi.org/10.1002/cpt.1482DOI Listing

Conformal prediction of HDAC inhibitors.

SAR QSAR Environ Res 2019 Apr;30(4):265-277

c Department of Pharmacy, School of Chemistry , Universidad Nacional Autónoma de México , Mexico City , Mexico.

The growing interest in epigenetic probes and drug discovery, as revealed by several epigenetic drugs in clinical use or in the lineup of the drug development pipeline, is boosting the generation of screening data. In order to maximize the use of structure-activity relationships there is a clear need to develop robust and accurate models to understand the underlying structure-activity relationship. Similarly, accurate models should be able to guide the rational screening of compound libraries. Read More

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http://dx.doi.org/10.1080/1062936X.2019.1591503DOI Listing

Probing demyelination and remyelination of the cuprizone mouse model using multimodality MRI.

J Magn Reson Imaging 2019 Apr 22. Epub 2019 Apr 22.

Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.

Background: Various studies by MRI exhibit that the corpus callosum (CC) is the most vulnerable to cuprizone administration, detecting the demyelination and remyelination process using different MRI parameters are, however, lacking.

Purpose: To investigate the sensitivity of multiparametric MRI both in vivo and ex vivo for demyelination and remyelination.

Study Type: Prospective. Read More

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https://onlinelibrary.wiley.com/doi/abs/10.1002/jmri.26758
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April 2019
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Cyanobacterial biodiversity of semiarid public drinking water supply reservoirs assessed via next-generation DNA sequencing technology.

J Microbiol 2019 Apr 22. Epub 2019 Apr 22.

Laboratory of Cyanobacteria, Department of Biological Sciences, Luiz de Queiroz College of Agriculture, University of São Paulo (USP), Piracicaba, SP, Brazil.

Next-generation DNA sequencing technology was applied to generate molecular data from semiarid reservoirs during well-defined seasons. Target sequences of 16S-23S rRNA ITS and cpcBA-IGS were used to reveal the taxonomic groups of cyanobacteria present in the samples, and genes coding for cyanotoxins such as microcystins (mcyE), saxitoxins (sxtA), and cylindrospermopsins (cyrJ) were investigated. The presence of saxitoxins in the environmental samples was evaluated using ELISA kit. Read More

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http://dx.doi.org/10.1007/s12275-019-8349-7DOI Listing

The Thrill Is Gone: Burdensome Electronic Documentation Takes Its Toll on Physicians' Time and Attention.

J Gen Intern Med 2019 Apr 22. Epub 2019 Apr 22.

VA HSR&D Center for Health Information and Communication, Roudebush VAMC, 1481 W. 10th Street, Indianapolis, IN, 46202, USA.

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http://dx.doi.org/10.1007/s11606-019-04898-8DOI Listing

Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography.

J Digit Imaging 2019 Apr 22. Epub 2019 Apr 22.

Memorial Sloan Kettering Cancer Center, 300 East 66th Street, New York, NY, 10065, USA.

To determine whether cmAssist™, an artificial intelligence-based computer-aided detection (AI-CAD) algorithm, can be used to improve radiologists' sensitivity in breast cancer screening and detection. A blinded retrospective study was performed with a panel of seven radiologists using a cancer-enriched data set from 122 patients that included 90 false-negative mammograms obtained up to 5.8 years prior to diagnosis and 32 BIRADS 1 and 2 patients with a 2-year follow-up of negative diagnosis. Read More

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http://dx.doi.org/10.1007/s10278-019-00192-5DOI Listing

A Region-Based Deep Level Set Formulation for Vertebral Bone Segmentation of Osteoporotic Fractures.

J Digit Imaging 2019 Apr 22. Epub 2019 Apr 22.

POF's Hospital, Wah Cantt, Pakistan.

Accurate segmentation of the vertebrae from medical images plays an important role in computer-aided diagnoses (CADs). It provides an initial and early diagnosis of various vertebral abnormalities to doctors and radiologists. Vertebrae segmentation is very important but difficult task in medical imaging due to low-contrast imaging and noise. Read More

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http://dx.doi.org/10.1007/s10278-019-00216-0DOI Listing

Discovering and characterizing dynamic functional brain networks in task FMRI.

Brain Imaging Behav 2019 Apr 22. Epub 2019 Apr 22.

Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.

Many existing studies for the mapping of function brain networks impose an implicit assumption that the networks' spatial distributions are constant over time. However, the latest research reports reveal that functional brain networks are dynamical and have time-varying spatial patterns. Furthermore, how these functional networks evolve over time has not been elaborated and explained in sufficient details yet. Read More

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http://dx.doi.org/10.1007/s11682-019-00096-6DOI Listing

A computer aided diagnosis system for measurement of mandibular cortical thickness on dental panoramic radiographs in prediction of women with low bone mineral density.

J Med Syst 2019 Apr 22;43(6):148. Epub 2019 Apr 22.

Department of Chemistry, C. Kandasamy Naidu college for women, Cuddalore, 607 001, India.

Osteoporosis detection at earlier stages can enhance the life span of an elderly individual. The aim of the study is to perform semi-automated measurement of mandibular cortical thickness (MCT) on a dental panoramic radiograph (DPR) and thereby to predict the risk of low BMD among the studied population. The study involved 76 women (mean age: 57. Read More

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http://dx.doi.org/10.1007/s10916-019-1268-7DOI Listing

Treatment of actinic cheilitis: a systematic review.

Clin Oral Investig 2019 Apr 23. Epub 2019 Apr 23.

Oral Pathology Department, Universidade Federal do Rio Grande do Sul, Ramiro Barcelos 2492, Room 503, Porto Alegre, RS, 90035-003, Brazil.

Objectives: Actinic cheilitis is a potentially malignant disorder caused by excessive sun exposure. It affects the lower lip of individuals, mostly those with light skin color. Different treatments have been proposed for AC; however, no consensus has been reached on the best option available. Read More

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http://link.springer.com/10.1007/s00784-019-02895-z
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http://dx.doi.org/10.1007/s00784-019-02895-zDOI Listing
April 2019
1 Read

Analysis of Breast Thermograms Using Asymmetry in Infra-Mammary Curves.

J Med Syst 2019 Apr 22;43(6):146. Epub 2019 Apr 22.

Department of Computer Science and Engineering, Easwari Engineering College, Chennai, Tamilnadu, India.

The objective of this research is to propose a methodology to analyse breast thermograms in order to detect breast abnormalities, including cancer. This research work mainly target to segmented ROI that show significant increase in temperature as compared to the neighbouring areas and contralateral sides in breast thermograms. The captured frontal thermograms from each patient is initially smoothed using a Gaussian filter with a standard deviation σ = 1. Read More

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http://dx.doi.org/10.1007/s10916-019-1267-8DOI Listing

Network mapping of the conformational heterogeneity of SOD1 by deploying statistical cluster analysis of FTIR spectra.

Cell Mol Life Sci 2019 Apr 22. Epub 2019 Apr 22.

Protein Folding and Dynamics Laboratory, Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, 700032, India.

A crucial contribution to the heterogeneity of the conformational landscape of a protein comes from the way an intermediate relates to another intermediate state in its journey from the unfolded to folded or misfolded form. Unfortunately, it is extremely hard to decode this relatedness in a quantifiable manner. Here, we developed an application of statistical cluster analyses to explore the conformational heterogeneity of a metalloenzyme, human cytosolic copper-zinc superoxide dismutase (SOD1), using the inputs from infrared spectroscopy. Read More

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http://dx.doi.org/10.1007/s00018-019-03108-2DOI Listing

Aggregation dynamics of active rotating particles in dense passive media.

Soft Matter 2019 Apr 23. Epub 2019 Apr 23.

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Active matter systems are able to exhibit emergent non-equilibrium behavior due to activity-induced effective interactions between the active particles. Here we study the aggregation and dynamical behavior of active rotating particles, spinners, embedded in 2D passive colloidal monolayers. Using both experiments and simulations we observe aggregation of active particles or spinners whose behavior resembles classical 2D Cahn-Hilliard coarsening. Read More

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http://dx.doi.org/10.1039/c8sm02207kDOI Listing

Active microrheology in two-dimensional magnetic networks.

Soft Matter 2019 Apr 23. Epub 2019 Apr 23.

Institut für Theoretische Physik II, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany.

We study active microrheology in two-dimensional (2D) magnetic networks. To this end, we use Langevin dynamics computer simulations where single non-magnetic or magnetic tracer particles are pulled through the network structures via a constant force f. Structural changes in the network around the pulled tracer particle are characterized in terms of pair correlation functions. Read More

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http://dx.doi.org/10.1039/c9sm00085bDOI Listing

Machine Learning Methods Uncover Radiomorphologic Dose Patterns in Salivary Glands that Predict Xerostomia in Patients with Head and Neck Cancer.

Adv Radiat Oncol 2019 Apr-Jun;4(2):401-412. Epub 2018 Nov 29.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Purpose: Patients with head-and-neck cancer (HNC) may experience xerostomia after radiation therapy (RT), which leads to compromised quality of life. The purpose of this study is to explore how the spatial pattern of radiation dose (radiomorphology) in the major salivary glands influences xerostomia in patients with HNC.

Methods And Materials: A data-driven approach using spatially explicit dosimetric predictors, voxel dose (ie, actual radiation dose in voxels in parotid glands [PG] and submandibular glands [SMG]) was used to predict whether patients would develop xerostomia 3 months after RT. Read More

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http://dx.doi.org/10.1016/j.adro.2018.11.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6460328PMC
November 2018

Data on changes in flexural strength and elastic modulus of dental CAD/CAM composites after deterioration tests.

Data Brief 2019 Jun 3;24:103889. Epub 2019 Apr 3.

Division of Biomaterials, Department of Oral Functions, Kyushu Dental University, Fukuoka 803-8580, Japan.

Mechanical properties of dental restorative materials are important for clinical success in prosthodontic care. However, open data on the mechanical properties of these materials are limited. This article provides data on the flexural strength and elastic modulus of dental composites in practical use for design/computer-aided manufacturing (CAD/CAM) systems. Read More

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http://dx.doi.org/10.1016/j.dib.2019.103889DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461697PMC

Evaluation of a re-useable bronchoscopy biosimulator with ventilated lungs.

ERJ Open Res 2019 Apr 15;5(2). Epub 2019 Apr 15.

Royal Brompton Hospital, London, UK.

Background: Restrictions on respiratory trainee time and access to procedures reduce the opportunities to acquire necessary skills in bronchoscopy. Simulation, not subject to such impediments, is a useful supplementary aid to teaching bronchoscopic techniques in a safe environment but there is a limited choice of simulators that are sufficiently realistic and not prohibitively expensive. This study evaluated a low-cost device that simulates an intubated and ventilated patient, employing re-useable, inflatable, BioFlex-preserved, porcine lungs. Read More

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http://dx.doi.org/10.1183/23120541.00035-2019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469070PMC

In Silico Exploration of Aryl Halides Analogues as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and ADMET Screening.

Adv Pharm Bull 2019 Feb 21;9(1):84-92. Epub 2019 Feb 21.

Faculty of Science, Moulay Ismail University, Meknes, Morocco.

In this review, a set of aryl halides analogs were identified as potent checkpoint kinase 1 (Chk1) inhibitors through a series of computer-aided drug design processes, to develop models with good predictive ability, highlight the important interactions between the ligand and the Chk1 receptor protein and determine properties of the new proposed drugs as Chk1 inhibitors agents. Three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking and absorption, distribution, metabolism, excretion and toxicity (ADMET) approaches are used to determine structure activity relationship and confirm the stable conformation on the receptor pocket. The statistical analysis results of comparative -molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models that employed for a training set of 24 compounds gives reliable values of Q (0. Read More

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https://apb.tbzmed.ac.ir/Abstract/apb-19609
Publisher Site
http://dx.doi.org/10.15171/apb.2019.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468235PMC
February 2019
2 Reads

Recursive Motif Analyses Identify Brain Epigenetic Transcription Regulatory Modules.

Comput Struct Biotechnol J 2019 9;17:507-515. Epub 2019 Apr 9.

Biocomplexity Institute of Virginia Tech, Blacksburg, VA 24061, USA.

DNA methylation is an epigenetic modification modulating the structure of DNA molecule and the interactions with its binding proteins. Accumulating large-scale methylation data motivates the development of analytic tools to facilitate methylome data mining. One critical phenomenon associated with dynamic DNA methylation is the altered DNA binding affinity of transcription factors, which plays key roles in gene expression regulation. Read More

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http://dx.doi.org/10.1016/j.csbj.2019.04.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462766PMC

Application of artificial intelligence in gastroenterology.

World J Gastroenterol 2019 Apr;25(14):1666-1683

Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Gangwon-do 24253, South Korea.

Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization of AI to efficiently deal with these data, which have become fundamental resources for a machine to learn by itself. Among several DL models, the convolutional neural network showed outstanding performance in image analysis. Read More

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http://dx.doi.org/10.3748/wjg.v25.i14.1666DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465941PMC

Capturing the dynamics of genome replication on individual ultra-long nanopore sequence reads.

Nat Methods 2019 Apr 22. Epub 2019 Apr 22.

Sir William Dunn School of Pathology, University of Oxford, Oxford, UK.

Replication of eukaryotic genomes is highly stochastic, making it difficult to determine the replication dynamics of individual molecules with existing methods. We report a sequencing method for the measurement of replication fork movement on single molecules by detecting nucleotide analog signal currents on extremely long nanopore traces (D-NAscent). Using this method, we detect 5-bromodeoxyuridine (BrdU) incorporated by Saccharomyces cerevisiae to reveal, at a genomic scale and on single molecules, the DNA sequences replicated during a pulse-labeling period. Read More

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http://dx.doi.org/10.1038/s41592-019-0394-yDOI Listing

Chiral twisted van der Waals nanowires.

Nature 2019 Apr 22. Epub 2019 Apr 22.

Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA.

Van der Waals heterostructures with small misalignment between adjacent layers ('interlayer twist') are of interest because of electronic structure and correlation phenomena (such as superconductivity) that are determined by both the atomic lattice and long-range superlattice potentials arising in interlayer moiré patterns. Previously, such twisted heterostructures have involved a single planar interface between layers isolated by exfoliation and micromechanically stacked in the desired relative orientation. Here we demonstrate a class of materials-van der Waals nanowires of layered crystals-in which a tunable interlayer twist evolves naturally during synthesis. Read More

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http://dx.doi.org/10.1038/s41586-019-1147-xDOI Listing

Autonomous dynamic control of DNA nanostructure self-assembly.

Nat Chem 2019 Apr 22. Epub 2019 Apr 22.

Mechanical Engineering, University of California, Riverside, CA, USA.

Biological cells routinely reconfigure their shape using dynamic signalling and regulatory networks that direct self-assembly processes in time and space, through molecular components that sense, process and transmit information from the environment. A similar strategy could be used to enable life-like behaviours in synthetic materials. Nucleic acid nanotechnology offers a promising route towards this goal through a variety of sensors, logic and dynamic components and self-assembling structures. Read More

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http://dx.doi.org/10.1038/s41557-019-0251-8DOI Listing

U2AF1 mutations induce oncogenic IRAK4 isoforms and activate innate immune pathways in myeloid malignancies.

Nat Cell Biol 2019 Apr 22. Epub 2019 Apr 22.

Division of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

Spliceosome mutations are common in myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML), but the oncogenic changes due to these mutations have not been identified. Here a global analysis of exon usage in AML samples revealed distinct molecular subsets containing alternative spliced isoforms of inflammatory and immune genes. Interleukin-1 receptor-associated kinase 4 (IRAK4) was the dominant alternatively spliced isoform in MDS and AML and is characterized by a longer isoform that retains exon 4, which encodes IRAK4-long (IRAK4-L), a protein that assembles with the myddosome, results in maximal activation of nuclear factor kappa-light-chain-enhancer of B cells (NF-κB) and is essential for leukaemic cell function. Read More

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http://dx.doi.org/10.1038/s41556-019-0314-5DOI Listing

Economic Potential for Distributed Manufacturing of Adaptive Aids for Arthritis Patients in the U.S.

Geriatrics (Basel) 2018 Dec 6;3(4). Epub 2018 Dec 6.

Department of Materials Science & Engineering, Michigan Technological University, Houghton, MI 49931, USA.

By 2040, more than a quarter of the U.S. population will have diagnosed arthritic conditions. Read More

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http://dx.doi.org/10.3390/geriatrics3040089DOI Listing
December 2018

Naturalistic Driving: A Framework and Advances in Using Big Data.

Geriatrics (Basel) 2018 Mar 29;3(2). Epub 2018 Mar 29.

Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8L6, Canada.

Driving is an activity that facilitates physical, cognitive, and social stimulation in older adults, ultimately leading to better physical and cognitive health. However, aging is associated with declines in vision, physical health, and cognitive health, all of which can affect driving ability. One way of assessing driving ability is with the use of sensors in the older adult's own vehicle. Read More

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http://www.mdpi.com/2308-3417/3/2/16
Publisher Site
http://dx.doi.org/10.3390/geriatrics3020016DOI Listing
March 2018
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Lean Methods Applied to CAD/CAM Pedagogy in the Dental Simulation Laboratory.

J Dent Educ 2019 Apr 22. Epub 2019 Apr 22.

Sharon C. Siegel, DDS, MS, MBA, is Professor, Department of Prosthodontics, College of Dental Medicine, Nova Southeastern University; Steven B. Kramer, MS, PhD, is Associate Professor, Department of Decision Sciences, H. Wayne Huizenga College of Business and Entrepreneurship, Nova Southeastern University; and Kimberly M. Deranek, MS, PhD, is Associate Professor, Department of Decision Sciences, H. Wayne Huizenga College of Business and Entrepreneurship, Nova Southeastern University.

Dental education is incorporating computer-assisted design/computer-assisted manufacturing (CAD/CAM) into patient care delivery. The aim of this study was to determine if lean production methods applied to the preclinical phase of dental education would reduce the students' time (efficiency) to complete CAD/CAM indirect restorations (CAD/CAM IR) without compromising the desired quality of the CAD/CAM tooth preparations (effectiveness). In 2016, all third-year students at one U. Read More

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http://dx.doi.org/10.21815/JDE.019.100DOI Listing

Effectiveness of Using a Mobile App to Improve Dental Students' Ability to Identify Endodontic Complications from Periapical Radiographs.

J Dent Educ 2019 Apr 22. Epub 2019 Apr 22.

Manuela Lima Barros de Oliveira is a master's student in Health Applied Sciences, Federal University of Juiz de Fora, Campus GV, Governador Valadares, Minas Gerais, Brazil; Francielle Silvestre Verner is Professor, Department of Dentistry, Division of Oral Diagnosis, Federal University of Juiz de Fora, Campus GV, Governador Valadares, Minas Gerais, Brazil; Kıvanç Kamburoğlu is Professor, Dentomaxillofacial Radiology Department, Ankara University Faculty of Dentistry, Ankara, Turkey; Jesca Neftali Nogueira Silva is a PhD student, Department of Radiology, School of Medicine, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; and Rafael Binato Junqueira is Professor, Department of Dentistry, Division of Endodontics, Federal University of Juiz de Fora, Campus GV, Governador Valadares, Minas Gerais, Brazil.

The aim of this study was to evaluate the feasibility and effectiveness of a mobile application as a supplementary tool in the radiographic diagnosis of endodontic complications by dental students. Radiographic images of the following endodontic conditions were selected: 1) absence of endodontic treatment (ET) without periapical lesion (PL); 2) absence of ET with PL; 3) satisfactory ET without PL; 4) satisfactory ET with PL; 5) unsatisfactory ET without PL; 6) unsatisfactory ET with PL; 7) fractured instrument; 8) deviated cast post; 9) root fracture; and 10) root resorption. In 2018, images were evaluated by 20 students at a dental school in Brazil who had been divided into experimental and control groups. Read More

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http://dx.doi.org/10.21815/JDE.019.099DOI Listing

Prevalence of antenatal depression in South Asia: a systematic review and meta-analysis.

J Epidemiol Community Health 2019 Apr 22. Epub 2019 Apr 22.

Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka.

Objective: To estimate the prevalence of antenatal depression in South Asia and to examine variations by country and study characteristics to inform policy, practice and future research.

Methods: We conducted a comprehensive search of 13 databases including international databases and databases covering scientific literature from South Asian countries in addition to Google Scholar and grey sources from 1 January 2007 to 31 May 2018. Studies reporting prevalence estimates of antenatal depression using a validated diagnostic/screening tool were identified, screened, selected and appraised. Read More

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http://dx.doi.org/10.1136/jech-2018-211819DOI Listing

PROMIS physical function underperforms psychometrically relative to American Shoulder and Elbow Surgeons score in patients undergoing anatomic total shoulder arthroplasty.

J Shoulder Elbow Surg 2019 Apr 19. Epub 2019 Apr 19.

Sports Medicine and Shoulder Service, Hospital for Special Surgery, New York, NY, USA.

Background: The purpose of this study was to evaluate the psychometric properties of the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function computer adaptive test (PF-CAT) relative to the American Shoulder and Elbow Surgeons (ASES) score in patients with glenohumeral osteoarthritis undergoing primary anatomic total shoulder arthroplasty (TSA).

Methods: A retrospective study of an institutional TSA registry was performed. Preoperative PROMIS PF-CAT and ASES scores were collected. Read More

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http://dx.doi.org/10.1016/j.jse.2019.02.011DOI Listing

Three-dimensional skeletal and dental patterns obtained from cone-beam computer tomography of patients diagnosed as malocclusion class I.

Int Orthod 2019 Apr 20. Epub 2019 Apr 20.

University of Alberta, Department of Dentistry, Edmonton, Canada. Electronic address:

The purpose of this study was to locate the landmarks both in traditionally-used two-dimensional (2D) lateral cephalogram images and newly suggested landmarks in three-dimensional (3D) cone-beam computer tomography (CBCT) images to determine possible relationships between them and determine if they could be used to classify patients of malocclusion Class I.

Material And Methods: CBCT images from 30 patients with malocclusion Class I were selected from the university of Alberta Graduate Orthodontic Program database. The images were then reconstructed using the AVIZO software platform to visualize and locate landmarks. Read More

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http://dx.doi.org/10.1016/j.ortho.2019.03.012DOI Listing

Vertical sleeve gastrectomy in adolescents reduces the appetitive reward value of a sweet and fatty reinforcer in a progressive ratio task.

Surg Obes Relat Dis 2019 Feb 22;15(2):194-199. Epub 2018 Nov 22.

Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, United Kingdom; Diabetes Complications Research Centre, Conway Institute, University College Dublin, Dublin, Ireland; Gastrosurgical laboratory, University of Gothenburg, Gothenburg, Sweden.

Background: Adolescent obesity is challenging to treat even if good multidisciplinary approaches are started early. Vertical sleeve gastrectomy (VSG) is an effective intervention for long-term weight loss, but the underlying mechanisms that result in reduced calorie intake are controversial. Anecdotal evidence from the clinic and evidence in rodents after VSG suggest a decrease in the reward value of high-calorie dense foods. Read More

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http://dx.doi.org/10.1016/j.soard.2018.10.033DOI Listing
February 2019
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