1
|
Huot F, Claveau S, Bunel A, Warner D, Santschi DE, Gervais R, Paquet ER. Predicting subacute ruminal acidosis from milk mid-infrared estimated fatty acids and machine learning on Canadian commercial dairy herds. J Dairy Sci 2024:S0022-0302(24)00984-6. [PMID: 38971559 DOI: 10.3168/jds.2024-25034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 06/08/2024] [Indexed: 07/08/2024]
Abstract
Our objective was to validate the possibility of detecting SARA from milk Fourier transform mid-infrared spectroscopy estimated fatty acids (FA) and machine learning. Subacute ruminal acidosis is a common condition in modern commercial dairy herds for which the diagnostic remains challenging due to its symptoms often being subtle, nonexclusive, and not immediately apparent. This observational study aimed at evaluating the possibility of predicting SARA by developing machine learning models to be applied to farm data and to provide an estimated portrait of SARA prevalence in commercial dairy herds. A first data set composed of 488 milk samples of 67 cows (initial DIM = 8.5 ± 6.18; mean ± SD) from 7 commercial dairy farms and their corresponding SARA classification (SARA+ if rumen pH <6.0 for 300 min, else SARA-) was used for the development of machine learning models. Three sets of predictive variables: i) milk major components (MMC), ii) milk FA (MFA), and iii) MMC combined with MFA (MMCFA) were submitted to 3 different algorithms, namely Elastic net (EN), Extreme gradient boosting (XGB), and Partial least squares (PLS), and evaluated using 3 different scenarios of cross-validation. Accuracy, sensitivity, and specificity of the resulting 27 models were analyzed using a linear mixed model. Model performance was not significantly affected by the choice of algorithm. Model performance was improved by including fatty acids estimations (MFA and MMCFA as opposed to MMC alone). Based on these results, one model was selected (algorithm: EN; predictive variables: MMCFA; 60.4, 65.4, and 55.3% of accuracy, sensitivity, and specificity, respectively) and applied to a large data set comprising the first test-day record (milk major components and FA within the first 70 DIM of 211,972 Holstein cows (219,503 samples) collected from 3001 commercial dairy herds. Based on this analysis, the within-herd SARA prevalence of commercial farms was estimated at 6.6 ± 5.29% ranging from 0 to 38.3%. A subsequent linear mixed model was built to investigate the herd-level factors associated to higher within-herd SARA prevalence. Milking system, proportion of primiparous cows, herd size and seasons were all herd-level factors affecting SARA prevalence. Furthermore, milk production was positively, and milk fat yield negatively associated with SARA prevalence. Due to their moderate levels of accuracy, the SARA prediction models developed in our study, using data from continuous pH measurements on commercial farms, are not suitable for diagnostic purpose. However, these models can provide valuable information at the herd level.
Collapse
|
2
|
Abratenko P, Aduszkiewicz A, Akbar F, Pons MA, Asaadi J, Aslin M, Babicz M, Badgett WF, Bagby LF, Baibussinov B, Behera B, Bellini V, Beltramello O, Benocci R, Berger J, Berkman S, Bertolucci S, Bertoni R, Betancourt M, Bettini M, Biagi S, Biery K, Bitter O, Bonesini M, Boone T, Bottino B, Braggiotti A, Brailsford D, Bremer J, Brice SJ, Brio V, Brizzolari C, Brown J, Budd HS, Calaon F, Campani A, Carber D, Carneiro M, Terrazas IC, Carranza H, Casazza D, Castellani L, Castro A, Centro S, Cerati G, Chalifour M, Chambouvet P, Chatterjee A, Cherdack D, Cherubini S, Chithirasreemadam N, Cicerchia M, Cicero V, Coan T, Cocco AG, Convery MR, Copello S, Cristaldo E, Dange AA, de Icaza Astiz I, De Roeck A, Di Domizio S, Di Noto L, Di Stefano C, Di Ferdinando D, Diwan M, Dolan S, Domine L, Donati S, Doubnik R, Drielsma F, Dyer J, Dytman S, Fabre C, Fabris F, Falcone A, Farnese C, Fava A, Ferguson H, Ferrari A, Ferraro F, Gallice N, Garcia FG, Geynisman M, Giarin M, Gibin D, Gigli SG, Gioiosa A, Gu W, Guerzoni M, Guglielmi A, Gurung G, Hahn S, Hardin K, Hausner H, Heggestuen A, Hilgenberg C, Hogan M, Howard B, Howell R, Hrivnak J, Iliescu M, Ingratta G, James C, Jang W, Jung M, Jwa YJ, Kashur L, Ketchum W, Kim JS, Koh DH, Kose U, Larkin J, Laurenti G, Lukhanin G, Marchini S, Marshall CM, Martynenko S, Mauri N, Mazzacane A, McFarland KS, Méndez DP, Menegolli A, Meng G, Miranda OG, Mladenov D, Mogan A, Moggi N, Montagna E, Montanari C, Montanari A, Mooney M, Moreno-Granados G, Mueller J, Naples D, Nebot-Guinot M, Nessi M, Nichols T, Nicoletto M, Norris B, Palestini S, Pallavicini M, Paolone V, Papaleo R, Pasqualini L, Patrizii L, Peghin R, Petrillo G, Petta C, Pia V, Pietropaolo F, Poirot J, Poppi F, Pozzato M, Prata MC, Prosser A, Putnam G, Qian X, Rampazzo G, Rappoldi A, Raselli GL, Rechenmacher R, Resnati F, Ricci AM, Riccobene G, Rice L, Richards E, Rigamonti A, Rosenberg M, Rossella M, Rubbia C, Sala P, Sapienza P, Savage G, Scaramelli A, Scarpelli A, Schmitz D, Schukraft A, Sergiampietri F, Sirri G, Smedley JS, Soha AK, Spanu M, Stanco L, Stewart J, Suarez NB, Sutera C, Tanaka HA, Tenti M, Terao K, Terranova F, Togo V, Torretta D, Torti M, Tortorici F, Tosi N, Tsai YT, Tufanli S, Turcato M, Usher T, Varanini F, Ventura S, Vercellati F, Vicenzi M, Vignoli C, Viren B, Warner D, Williams Z, Wilson RJ, Wilson P, Wolfs J, Wongjirad T, Wood A, Worcester E, Worcester M, Wospakrik M, Yu H, Yu J, Zani A, Zatti PG, Zennamo J, Zettlemoyer JC, Zhang C, Zucchelli S, Zuckerbrot M. ICARUS at the Fermilab Short-Baseline Neutrino program: initial operation. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2023; 83:467. [PMID: 37303462 PMCID: PMC10239613 DOI: 10.1140/epjc/s10052-023-11610-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/12/2023] [Indexed: 06/13/2023]
Abstract
The ICARUS collaboration employed the 760-ton T600 detector in a successful 3-year physics run at the underground LNGS laboratory, performing a sensitive search for LSND-like anomalous ν e appearance in the CERN Neutrino to Gran Sasso beam, which contributed to the constraints on the allowed neutrino oscillation parameters to a narrow region around 1 eV2 . After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 the cryogenic commissioning began with detector cool down, liquid argon filling and recirculation. ICARUS then started its operations collecting the first neutrino events from the booster neutrino beam (BNB) and the Neutrinos at the Main Injector (NuMI) beam off-axis, which were used to test the ICARUS event selection, reconstruction and analysis algorithms. ICARUS successfully completed its commissioning phase in June 2022. The first goal of the ICARUS data taking will be a study to either confirm or refute the claim by Neutrino-4 short-baseline reactor experiment. ICARUS will also perform measurement of neutrino cross sections with the NuMI beam and several Beyond Standard Model searches. After the first year of operations, ICARUS will search for evidence of sterile neutrinos jointly with the Short-Baseline Near Detector, within the Short-Baseline Neutrino program. In this paper, the main activities carried out during the overhauling and installation phases are highlighted. Preliminary technical results from the ICARUS commissioning data with the BNB and NuMI beams are presented both in terms of performance of all ICARUS subsystems and of capability to select and reconstruct neutrino events.
Collapse
|
3
|
Dallago G, Mauyenova N, Warner D, Cue R, Vasseur E. Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data. Animal 2022; 16:100641. [DOI: 10.1016/j.animal.2022.100641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 08/30/2022] [Accepted: 09/01/2022] [Indexed: 11/27/2022] Open
|
4
|
Warner D, Dallago GM, Dovoedo OW, Lacroix R, Delgado HA, Cue RI, Wade KM, Dubuc J, Pellerin D, Vasseur E. Keeping profitable cows in the herd: A lifetime cost-benefit assessment to support culling decisions. Animal 2022; 16:100628. [PMID: 36108456 DOI: 10.1016/j.animal.2022.100628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 07/29/2022] [Accepted: 08/08/2022] [Indexed: 11/01/2022] Open
Abstract
Increasing the productive lifespan of dairy cows is important to achieve a sustainable dairy industry, but making strategic culling decisions based on cow profitability is challenging for farmers. The objective of this study was to carry out a lifetime cost-benefit analysis based on production and health records and to explore different culling decisions among farmers. The cost-benefit analysis was conducted for 22 747 dairy cows across 114 herds in Quebec, Canada for which feed costs and the occurrence of diseases were reported. Costs and revenues related to productive lifespan were compared among cohorts of cows that left their respective herd at the end of their last completed lactation or stayed for a complete additional lactation. Hierarchical clustering analysis was carried out based on costs and revenues to explore different culling decisions among farmers. Our results showed that the knowledge of lifetime cumulative costs and revenues was of great importance to identify low-profitable cows at an earlier lactation, while only focusing on current lactation costs and revenues can lead to an erroneous assessment of profitability. While culling decisions were mostly based on current lactation costs and revenues and disregarded the occurrence of costly events on previous lactations, there was variation among farmers as we identified three different culling decision clusters. Monitoring cumulative costs and revenues would help farmers to identify low-profitable cows at an earlier lactation and make the decision to increase herd productive lifespan and farm profitability by keeping the most profitable cows.
Collapse
|
5
|
Abud AA, Abi B, Acciarri R, Acero MA, Adames MR, Adamov G, Adamowski M, Adams D, Adinolfi M, Aduszkiewicz A, Aguilar J, Ahmad Z, Ahmed J, Aimard B, Ali-Mohammadzadeh B, Alion T, Allison K, Monsalve SA, AlRashed M, Alt C, Alton A, Alvarez R, Amedo P, Anderson J, Andreopoulos C, Andreotti M, Andrews M, Andrianala F, Andringa S, Anfimov N, Ankowski A, Antoniassi M, Antonova M, Antoshkin A, Antusch S, Aranda-Fernandez A, Arellano L, Arnold LO, Arroyave MA, Asaadi J, Asquith L, Aurisano A, Aushev V, Autiero D, Lara VA, Ayala-Torres M, Azfar F, Back A, Back H, Back JJ, Backhouse C, Bagaturia I, Bagby L, Balashov N, Balasubramanian S, Baldi P, Baller B, Bambah B, Barao F, Barenboim G, Alzas PB, Barker G, Barkhouse W, Barnes C, Barr G, Monarca JB, Barros A, Barros N, Barrow JL, Basharina-Freshville A, Bashyal A, Basque V, Batchelor C, Chagas EBD, Battat JBR, Battisti F, Bay F, Bazetto MCQ, Alba JLLB, Beacom JF, Bechetoille E, Behera B, Beigbeder C, Bellantoni L, Bellettini G, Bellini V, Beltramello O, Benekos N, Montiel CB, Neves FB, Berger J, Berkman S, Bernardini P, Berner RM, Bersani A, Bertolucci S, Betancourt M, Rodríguez AB, Bevan A, Bezawada Y, Bezerra TJC, Bhardwaj A, Bhatnagar V, Bhattacharjee M, Bhattarai D, Bhuller S, Bhuyan B, Biagi S, Bian J, Biassoni M, Biery K, Bilki B, Bishai M, Bitadze A, Blake A, Blaszczyk F, Blazey GC, Blucher E, Boissevain J, Bolognesi S, Bolton T, Bomben L, Bonesini M, Bongrand M, Bonilla-Diaz C, Bonini F, Booth A, Boran F, Bordoni S, Borkum A, Bostan N, Bour P, Bourgeois C, Boyden D, Bracinik J, Braga D, Brailsford D, Branca A, Brandt A, Bremer J, Breton D, Brew C, Brice SJ, Brizzolari C, Bromberg C, Brooke J, Bross A, Brunetti G, Brunetti M, Buchanan N, Budd H, Butorov I, Cagnoli I, Cai T, Caiulo D, Calabrese R, Calafiura P, Calcutt J, Calin M, Calvez S, Calvo E, Caminata A, Campanelli M, Caratelli D, Carber D, Carceller JC, Carini G, Carlus B, Carneiro MF, Carniti P, Terrazas IC, Carranza H, Carroll T, Forero JFC, Castillo A, Castromonte C, Catano-Mur E, Cattadori C, Cavalier F, Cavallaro G, Cavanna F, Centro S, Cerati G, Cervelli A, Villanueva AC, Chalifour M, Chappell A, Chardonnet E, Charitonidis N, Chatterjee A, Chattopadhyay S, Neyra MSSC, Chen H, Chen M, Chen Y, Chen Z, Chen-Wishart Z, Cheon Y, Cherdack D, Chi C, Childress S, Chirco R, Chiriacescu A, Chisnall G, Cho K, Choate S, Chokheli D, Chong PS, Christensen A, Christian D, Christodoulou G, Chukanov A, Chung M, Church E, Cicero V, Clarke P, Cline G, Coan TE, Cocco AG, Coelho JAB, Colton N, Conley E, Conley R, Conrad J, Convery M, Copello S, Cova P, Cremaldi L, Cremonesi L, Crespo-Anadón JI, Crisler M, Cristaldo E, Crnkovic J, Cross R, Cudd A, Cuesta C, Cui Y, Cussans D, Dalager O, da Motta H, Da Silva Peres L, David C, David Q, Davies GS, Davini S, Dawson J, De K, De S, Debbins P, De Bonis I, Decowski MP, De Gouvêa A, De Holanda PC, De Icaza Astiz IL, Deisting A, De Jong P, Delbart A, Delepine D, Delgado M, Dell’Acqua A, Delmonte N, De Lurgio P, de Mello Neto JRT, DeMuth DM, Dennis S, Densham C, Deptuch GW, De Roeck A, De Romeri V, De Souza G, Devi R, Dharmapalan R, Dias M, Diaz F, Díaz JS, Domizio SD, Giulio LD, Ding P, Noto LD, Dirkx G, Distefano C, Diurba R, Diwan M, Djurcic Z, Doering D, Dolan S, Dolek F, Dolinski M, Domine L, Donon Y, Douglas D, Douillet D, Dragone A, Drake G, Drielsma F, Duarte L, Duchesneau D, Duffy K, Dunne P, Dutta B, Duyang H, Dvornikov O, Dwyer D, Dyshkant A, Eads M, Earle A, Edmunds D, Eisch J, Emberger L, Emery S, Englezos P, Ereditato A, Erjavec T, Escobar C, Eurin G, Evans JJ, Ewart E, Ezeribe AC, Fahey K, Falcone A, Fani’ M, Farnese C, Farzan Y, Fedoseev D, Felix J, Feng Y, Fernandez-Martinez E, Menendez PF, Morales MF, Ferraro F, Fields L, Filip P, Filthaut F, Fiorini M, Fischer V, Fitzpatrick RS, Flanagan W, Fleming B, Flight R, Fogarty S, Foreman W, Fowler J, Fox W, Franc J, Francis K, Franco D, Freeman J, Freestone J, Fried J, Friedland A, Robayo FF, Fuess S, Furic IK, Furman K, Furmanski AP, Gabrielli A, Gago A, Gallagher H, Gallas A, Gallego-Ros A, Gallice N, Galymov V, Gamberini E, Gamble T, Ganacim F, Gandhi R, Gandrajula R, Gao F, Gao S, Garcia-Gamez D, García-Peris MÁ, Gardiner S, Gastler D, Gauvreau J, Ge G, Geffroy N, Gelli B, Gendotti A, Gent S, Ghorbani-Moghaddam Z, Giammaria P, Giammaria T, Giangiacomi N, Gibin D, Gil-Botella I, Gilligan S, Girerd C, Giri AK, Gnani D, Gogota O, Gold M, Gollapinni S, Gollwitzer K, Gomes RA, Bermeo LVG, Fajardo LSG, Gonnella F, Gonzalez-Diaz D, Gonzalez-Lopez M, Goodman MC, Goodwin O, Goswami S, Gotti C, Goudzovski E, Grace C, Gran R, Granados E, Granger P, Grant A, Grant C, Gratieri D, Green P, Greenler L, Greer J, Grenard J, Griffith WC, Groh M, Grudzinski J, Grzelak K, Gu W, Guardincerri E, Guarino V, Guarise M, Guenette R, Guerard E, Guerzoni M, Guffanti D, Guglielmi A, Guo B, Gupta A, Gupta V, Guthikonda KK, Gutierrez R, Guzowski P, Guzzo MM, Gwon S, Ha C, Haaf K, Habig A, Hadavand H, Haenni R, Hahn A, Haiston J, Hamacher-Baumann P, Hamernik T, Hamilton P, Han J, Harris DA, Hartnell J, Hartnett T, Harton J, Hasegawa T, Hasnip C, Hatcher R, Hatfield KW, Hatzikoutelis A, Hayes C, Hayrapetyan K, Hays J, Hazen E, He M, Heavey A, Heeger KM, Heise J, Henry S, Morquecho MAH, Herner K, Hewes J, Hilgenberg C, Hill T, Hillier SJ, Himmel A, Hinkle E, Hirsch LR, Ho J, Hoff J, Holin A, Hoppe E, Horton-Smith GA, Hostert M, Hourlier A, Howard B, Howell R, Hoyos J, Hristova I, Hronek MS, Huang J, Hulcher Z, Iles G, Ilic N, Iliescu AM, Illingworth R, Ingratta G, Ioannisian A, Irwin B, Isenhower L, Itay R, Jackson CM, Jain V, James E, Jang W, Jargowsky B, Jediny F, Jena D, Jeong YS, Jesús-Valls C, Ji X, Jiang L, Jiménez S, Jipa A, Johnson R, Johnson W, Johnston N, Jones B, Jones S, Judah M, Jung CK, Junk T, Jwa Y, Kabirnezhad M, Kaboth A, Kadenko I, Kakorin I, Kalitkina A, Kalra D, Kamiya F, Kaneshige N, Kaplan DM, Karagiorgi G, Karaman G, Karcher A, Karolak M, Karyotakis Y, Kasai S, Kasetti SP, Kashur L, Kazaryan N, Kearns E, Keener P, Kelly KJ, Kemp E, Kemularia O, Ketchum W, Kettell SH, Khabibullin M, Khotjantsev A, Khvedelidze A, Kim D, King B, Kirby B, Kirby M, Klein J, Klustova A, Kobilarcik T, Koehler K, Koerner LW, Koh DH, Kohn S, Koller PP, Kolupaeva L, Korablev D, Kordosky M, Kosc T, Kose U, Kostelecký VA, Kothekar K, Kralik R, Kreczko L, Krennrich F, Kreslo I, Kropp W, Kroupova T, Kubota S, Kudenko Y, Kudryavtsev VA, Kulagin S, Kumar J, Kumar P, Kunze P, Kurita N, Kuruppu C, Kus V, Kutter T, Kvasnicka J, Kwak D, Lambert A, Land B, Lane CE, Lang K, Langford T, Langstaff M, Larkin J, Lasorak P, Last D, Laundrie A, Laurenti G, Lawrence A, Lazanu I, LaZur R, Lazzaroni M, Le T, Leardini S, Learned J, LeBrun P, LeCompte T, Lee C, Lee SY, Miotto GL, Lehnert R, de Oliveira MAL, Leitner M, Lepin LM, Li SW, Li Y, Liao H, Lin CS, Lin Q, Lin S, Lineros RA, Ling J, Lister A, Littlejohn BR, Liu J, Liu Y, Lockwitz S, Loew T, Lokajicek M, Lomidze I, Long K, Lord T, LoSecco JM, Louis WC, Lu XG, Luk KB, Lunday B, Luo X, Luppi E, Lux T, Luzio VP, Maalmi J, MacFarlane D, Machado AA, Machado P, Macias CT, Macier JR, Maddalena A, Madera A, Madigan P, Magill S, Mahn K, Maio A, Major A, Maloney JA, Mandrioli G, Mandujano RC, Maneira J, Manenti L, Manly S, Mann A, Manolopoulos K, Plata MM, Manyam VN, Manzanillas L, Marchan M, Marchionni A, Marciano W, Marfatia D, Mariani C, Maricic J, Marie R, Marinho F, Marino AD, Marsden D, Marshak M, Marshall C, Marshall J, Marteau J, Martín-Albo J, Martinez N, Caicedo DAM, Miravé PM, Martynenko S, Mascagna V, Mason K, Mastbaum A, Matichard F, Matsuno S, Matthews J, Mauger C, Mauri N, Mavrokoridis K, Mawby I, Mazza R, Mazzacane A, Mazzucato E, McAskill T, McCluskey E, McConkey N, McFarland KS, McGrew C, McNab A, Mefodiev A, Mehta P, Melas P, Mena O, Mendez H, Mendez P, Méndez DP, Menegolli A, Meng G, Messier MD, Metcalf W, Mettler T, Mewes M, Meyer H, Miao T, Michna G, Miedema T, Mikola V, Milincic R, Miller G, Miller W, Mills J, Mineev O, Minotti A, Miranda OG, Miryala S, Mishra CS, Mishra SR, Mislivec A, Mitchell M, Mladenov D, Mocioiu I, Moffat K, Moggi N, Mohanta R, Mohayai TA, Mokhov N, Molina J, Bueno LM, Montagna E, Montanari A, Montanari C, Montanari D, Zetina LMM, Moon SH, Mooney M, Moor AF, Moreno D, Moretti D, Morris C, Mossey C, Mote M, Motuk E, Moura CA, Mousseau J, Mouster G, Mu W, Mualem L, Mueller J, Muether M, Mufson S, Muheim F, Muir A, Mulhearn M, Munford D, Muramatsu H, Murphy S, Musser J, Nachtman J, Nagu S, Nalbandyan M, Nandakumar R, Naples D, Narita S, Nath A, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Negishi K, Nelson JK, Nesbit J, Nessi M, Newbold D, Newcomer M, Newton H, Nichol R, Nicolas-Arnaldos F, Nikolica A, Niner E, Nishimura K, Norman A, Norrick A, Northrop R, Novella P, Nowak JA, Oberling M, Ochoa-Ricoux J, Olivier A, Olshevskiy A, Onel Y, Onishchuk Y, Ott J, Pagani L, Palacio G, Palamara O, Palestini S, Paley JM, Pallavicini M, Palomares C, Vazquez WP, Pantic E, Paolone V, Papadimitriou V, Papaleo R, Papanestis A, Paramesvaran S, Parke S, Parozzi E, Parsa Z, Parvu M, Pascoli S, Pasqualini L, Pasternak J, Pater J, Patrick C, Patrizii L, Patterson RB, Patton SJ, Patzak T, Paudel A, Paulos B, Paulucci L, Pavlovic Z, Pawloski G, Payne D, Pec V, Peeters SJM, Perez AP, Pennacchio E, Penzo A, Peres OLG, Perry J, Pershey D, Pessina G, Petrillo G, Petta C, Petti R, Pia V, Piastra F, Pickering L, Pietropaolo F, Pimentel VL, Pinaroli G, Plows K, Plunkett R, Poling R, Pompa F, Pons X, Poonthottathil N, Poppi F, Pordes S, Porter J, Potekhin M, Potenza R, Potukuchi BVKS, Pozimski J, Pozzato M, Prakash S, Prakash T, Prest M, Prince S, Psihas F, Pugnere D, Qian X, Raaf JL, Radeka V, Rademacker J, Radics B, Rafique A, Raguzin E, Rai M, Rajaoalisoa M, Rakhno I, Rakotonandrasana A, Rakotondravohitra L, Rameika R, Delgado MAR, Ramson B, Rappoldi A, Raselli G, Ratoff P, Raut S, Razakamiandra RF, Rea EM, Real JS, Rebel B, Rechenmacher R, Reggiani-Guzzo M, Reichenbacher J, Reitzner SD, Sfar HR, Renshaw A, Rescia S, Resnati F, Ribas M, Riboldi S, Riccio C, Riccobene G, Rice LCJ, Ricol JS, Rigamonti A, Rigaut Y, Rincón EV, Ritchie-Yates H, Rivera D, Robert A, Rochester L, Roda M, Rodrigues P, Alonso MJR, Bonilla ER, Rondon JR, Rosauro-Alcaraz S, Rosenberg M, Rosier P, Roskovec B, Rossella M, Rossi M, Rout J, Roy P, Rubbia A, Rubbia C, Russell B, Ruterbories D, Rybnikov A, Saa-Hernandez A, Saakyan R, Sacerdoti S, Safford T, Sahu N, Sakashita K, Sala P, Samios N, Samoylov O, Sanchez MC, Sandberg V, Sanders DA, 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, Schefke T, Schellman H, Schifano S, Schlabach P, Schmitz D, Schneider AW, Scholberg K, Schukraft A, Segreto E, Selyunin A, Senise CR, Sensenig J, Sergi A, Sgalaberna D, Shaevitz MH, Shafaq S, Shaker F, Shamma M, Sharankova R, Sharma HR, Sharma R, Sharma RK, Shaw T, Shchablo K, Shepherd-Themistocleous C, Sheshukov A, Shin S, Shoemaker I, Shooltz D, Shrock R, Siegel H, Simard L, Sinclair J, Sinev G, Singh J, Singh J, Singh L, Singh P, Singh V, Sipos R, Sippach FW, Sirri G, Sitraka A, Siyeon K, Skarpaas K, Smith A, Smith E, Smith P, Smolik J, Smy M, Snider E, Snopok P, Snowden-Ifft D, Nunes MS, Sobel H, Soderberg M, Sokolov S, Salinas CJS, Söldner-Rembold S, Soleti SR, Solomey N, Solovov V, Sondheim WE, Sorel M, Sotnikov A, Soto-Oton J, Ugaldi FAS, Sousa A, Soustruznik K, Spagliardi F, Spanu M, Spitz J, Spooner NJC, Spurgeon K, Stancari M, Stanco L, Stanford C, Stein R, Steiner HM, Lisbôa AFS, Stewart J, Stillwell B, Stock J, Stocker F, Stokes T, Strait M, Strauss T, Strigari L, Stuart A, Suarez JG, Sunción JMS, Sullivan H, Summers D, Surdo A, Susic V, Suter L, Sutera CM, Svoboda R, Szczerbinska B, Szelc AM, Tanaka H, Tang S, Tapia A, Oregui BT, Tapper A, Tariq S, Tarpara E, Tata N, Tatar E, Tayloe R, Teklu AM, Tennessen P, Tenti M, Terao K, Ternes CA, Terranova F, Testera G, Thakore T, Thea A, Thompson JL, Thorn C, Timm SC, Tishchenko V, Tomassetti L, Tonazzo A, Torbunov D, Torti M, Tortola M, Tortorici F, Tosi N, Totani D, Toups M, Touramanis C, Travaglini R, Trevor J, Trilov S, Trzaska WH, Tsai Y, Tsai YT, Tsamalaidze Z, Tsang KV, Tsverava N, Tufanli S, Tull C, Tyley E, Tzanov M, Uboldi L, Uchida MA, Urheim J, Usher T, Uzunyan S, Vagins MR, Vahle P, Valder S, Valdiviesso GDA, Valencia E, Valentim R, Vallari Z, Vallazza E, Valle JWF, Vallecorsa S, Berg RV, de Water RGV, Forero DV, Vannerom D, Varanini F, Oliva DV, Varner G, Vasel J, Vasina S, Vasseur G, Vaughan N, Vaziri K, Ventura S, Verdugo A, Vergani S, Vermeulen MA, Verzocchi M, Vicenzi M, de Souza HV, Vignoli C, Vilela C, Viren B, Vrba T, Wachala T, Waldron AV, Wallbank M, Wallis C, Wang H, Wang J, Wang L, Wang MHLS, Wang X, Wang Y, Wang Y, Warburton K, Warner D, Wascko MO, Waters D, Watson A, Wawrowska K, Weatherly P, Weber A, Weber M, Wei H, Weinstein A, Wenman D, Wetstein M, White A, Whitehead LH, Whittington D, Wilking MJ, Wilkinson A, Wilkinson C, Williams Z, Wilson F, Wilson RJ, Wisniewski W, Wolcott J, Wongjirad T, Wood A, Wood K, Worcester E, Worcester M, Wresilo K, Wret C, Wu W, Wu W, Xiao Y, Xie F, Yaeggy B, Yandel E, Yang G, Yang K, Yang T, Yankelevich A, Yershov N, Yonehara K, Yoon YS, Young T, Yu B, Yu H, Yu H, Yu J, Yu Y, Yuan W, Zaki R, Zalesak J, Zambelli L, Zamorano B, Zani A, Zazueta L, Zeller GP, Zennamo J, Zeug K, Zhang C, Zhang S, Zhang Y, Zhao M, Zhivun E, Zhu G, Zimmerman ED, Zucchelli S, Zuklin J, Zutshi V, Zwaska R. Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2022; 82:618. [PMID: 35859696 PMCID: PMC9288420 DOI: 10.1140/epjc/s10052-022-10549-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
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.
Collapse
|
6
|
Vu L, Koroukian S, Debanne S, Warner D, Gairola R, Schiltz N, Rose J, Cullen J, Owusu C, Sajatovic M, Douglas S. Cancer Patients in Nursing Homes: Survival and Multimorbidity Phenotypes Across Gradients of Cognitive Impairment. J Geriatr Oncol 2021. [DOI: 10.1016/s1879-4068(21)00385-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
7
|
Abi B, Acciarri R, Acero MA, Adamov G, Adams D, Adinolfi M, Ahmad Z, Ahmed J, Alion T, Monsalve SA, Alt C, Anderson J, Andreopoulos C, Andrews MP, Andrianala F, Andringa S, Ankowski A, Antonova M, Antusch S, Aranda-Fernandez A, Ariga A, Arnold LO, Arroyave MA, Asaadi J, Aurisano A, Aushev V, Autiero D, Azfar F, Back H, Back JJ, Backhouse C, Baesso P, Bagby L, Bajou R, Balasubramanian S, Baldi P, Bambah B, Barao F, Barenboim G, Barker GJ, Barkhouse W, Barnes C, Barr G, Monarca JB, Barros N, Barrow JL, Bashyal A, Basque V, Bay F, Alba JLB, Beacom JF, Bechetoille E, Behera B, Bellantoni L, Bellettini G, Bellini V, Beltramello O, Belver D, Benekos N, Neves FB, Berger J, Berkman S, Bernardini P, Berner RM, 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 BB, Blaszczyk FDM, Blazey GC, 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 SB, Boyden D, Bracinik J, Braga D, Brailsford D, Brandt A, Bremer J, Brew C, Brianne E, Brice SJ, 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 IC, Carranza H, Castillo A, Castromonte C, Cattadori C, Cavalier F, Cavanna F, Centro S, Cerati G, Cervelli A, Villanueva AC, 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 TE, Cocco AG, Coelho JAB, Conley E, Conrad JM, Convery M, Corwin L, Cotte P, Cremaldi L, Cremonesi L, Crespo-Anadón JI, Cristaldo E, Cross R, Cuesta C, Cui Y, Cussans D, Dabrowski M, da Motta H, Peres LDS, David C, David Q, Davies GS, Davini S, Dawson J, De K, De Almeida RM, Debbins P, De Bonis I, Decowski MP, de Gouvêa A, De Holanda PC, De Icaza Astiz IL, Deisting A, De Jong P, Delbart A, Delepine D, Delgado M, Dell’Acqua A, De Lurgio P, de Mello Neto JRT, DeMuth DM, Dennis S, Densham C, Deptuch G, De Roeck A, De Romeri V, De Vries JJ, Dharmapalan R, Dias M, Diaz F, Díaz JS, Di Domizio S, Di Giulio L, Ding P, Di Noto L, Distefano C, Diurba R, Diwan M, Djurcic Z, Dokania N, Dolinski MJ, Domine L, Douglas D, Drielsma F, Duchesneau D, Duffy K, Dunne P, Durkin T, Duyang H, Dvornikov O, Dwyer DA, Dyshkant AS, Eads M, Edmunds D, Eisch J, Emery S, Ereditato A, Escobar CO, Sanchez LE, Evans JJ, Ewart E, Ezeribe AC, Fahey K, Falcone A, Farnese C, Farzan Y, Felix J, Fernandez-Martinez E, Fernandez Menendez P, Ferraro F, Fields L, Filkins A, Filthaut F, Fitzpatrick RS, 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 AP, Gago A, Gallagher H, Gallego-Ros A, Gallice N, Galymov V, Gamberini E, Gamble T, Gandhi R, Gandrajula R, Gao S, Garcia-Gamez D, García-Peris MÁ, Gardiner S, Gastler D, Ge G, Gelli B, Gendotti A, Gent S, Ghorbani-Moghaddam Z, Gibin D, Gil-Botella I, Girerd C, Giri AK, Gnani D, Gogota O, Gold M, Gollapinni S, Gollwitzer K, Gomes RA, Bermeo LVG, Fajardo LSG, Gonnella F, Gonzalez-Cuevas JA, Goodman MC, 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 WC, Groh M, Grudzinski J, Grzelak K, Gu W, Guarino V, Guenette R, Guglielmi A, Guo B, Guthikonda KK, Gutierrez R, Guzowski P, Guzzo MM, 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 DA, Hartnell J, Hasegawa T, Hatcher R, Hazen E, Heavey A, Heeger KM, Heise J, Hennessy K, Henry S, Morquecho MAH, Herner K, Hertel L, Hesam AS, Hewes J, Higuera A, Hill T, Hillier SJ, Himmel A, Hoff J, Hohl C, Holin A, Hoppe E, Horton-Smith GA, Hostert M, Hourlier A, Howard B, Howell R, Huang J, Huang J, Hugon J, Iles G, Ilic N, Iliescu AM, Illingworth R, Ioannisian A, Itay R, Izmaylov A, James E, Jargowsky B, Jediny F, Jesùs-Valls C, Ji X, Jiang L, Jiménez S, Jipa A, Joglekar A, Johnson C, Johnson R, Jones B, Jones S, Jung CK, Junk T, Jwa Y, Kabirnezhad M, Kaboth A, Kadenko I, Kamiya F, Karagiorgi G, Karcher A, Karolak M, Karyotakis Y, Kasai S, Kasetti SP, Kashur L, Kazaryan N, Kearns E, Keener P, Kelly KJ, Kemp E, Ketchum W, Kettell SH, Khabibullin M, Khotjantsev A, Khvedelidze A, Kim D, King B, Kirby B, Kirby M, Klein J, Koehler K, Koerner LW, Kohn S, Koller PP, Kordosky M, Kosc T, Kose U, Kostelecký VA, Kothekar K, Krennrich F, Kreslo I, Kudenko Y, Kudryavtsev VA, Kulagin S, Kumar J, Kumar R, Kuruppu C, Kus V, Kutter T, Lambert A, Lande K, Lane CE, 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 GL, Lehnert R, de Oliveira MAL, Leitner M, Leyton M, Li L, Li S, Li SW, Li T, Li Y, Liao H, Lin CS, Lin S, Lister A, Littlejohn BR, Liu J, Lockwitz S, Loew T, Lokajicek M, Lomidze I, Long K, Loo K, Lorca D, Lord T, LoSecco JM, Louis WC, Luk KB, Luo X, Lurkin N, Lux T, Luzio VP, MacFarland D, Machado AA, Machado P, Macias CT, Macier JR, Maddalena A, Madigan P, Magill S, Mahn K, Maio A, Maloney JA, Mandrioli G, Maneira J, Manenti L, Manly S, Mann A, Manolopoulos K, Plata MM, Marchionni A, Marciano W, Marfatia D, Mariani C, Maricic J, Marinho F, Marino AD, Marshak M, Marshall C, Marshall J, Marteau J, Martin-Albo J, Martinez N, Caicedo DAM, 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 KS, McGrew C, McNab A, Mefodiev A, Mehta P, Melas P, Mellinato M, Mena O, Menary S, Mendez H, Menegolli A, Meng G, Messier MD, 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 OG, Miryala S, Mishra CS, Mishra SR, Mislivec A, Mladenov D, Mocioiu I, Moffat K, Moggi N, Mohanta R, Mohayai TA, Mokhov N, Molina J, Bueno LM, Montanari A, Montanari C, Montanari D, Zetina LMM, Moon J, Mooney M, Moor A, Moreno D, Morgan B, Morris C, Mossey C, Motuk E, Moura CA, 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-Nicolás D, Nayak N, Nebot-Guinot M, Necib L, Negishi K, Nelson JK, Nesbit J, Nessi M, Newbold D, Newcomer M, Newhart D, Nichol R, Niner E, Nishimura K, Norman A, Norrick A, Northrop R, Novella P, Nowak JA, Oberling M, Del Campo AO, Olivier A, Onel Y, Onishchuk Y, Ott J, Pagani L, Pakvasa S, Palamara O, Palestini S, Paley JM, Pallavicini M, Palomares C, Pantic E, Paolone V, Papadimitriou V, Papaleo R, Papanestis A, Paramesvaran S, Park JC, Parke S, Parsa Z, Parvu M, Pascoli S, Pasqualini L, Pasternak J, Pater J, Patrick C, Patrizii L, Patterson RB, Patton SJ, Patzak T, Paudel A, Paulos B, Paulucci L, Pavlovic Z, Pawloski G, Payne D, Pec V, Peeters SJM, Penichot Y, Pennacchio E, Penzo A, Peres OLG, Perry J, Pershey D, Pessina G, Petrillo G, Petta C, Petti R, Piastra F, Pickering L, Pietropaolo F, Pillow J, Pinzino J, Plunkett R, Poling R, Pons X, Poonthottathil N, Pordes S, Potekhin M, Potenza R, Potukuchi BVKS, Pozimski J, Pozzato M, Prakash S, Prakash T, Prince S, Prior G, Pugnere D, Qi K, Qian X, Raaf JL, Raboanary R, Radeka V, Rademacker J, Radics B, Rafique A, Raguzin E, Rai M, Rajaoalisoa M, Rakhno I, Rakotondramanana HT, Rakotondravohitra L, Ramachers YA, Rameika R, Delgado MAR, Ramson B, Rappoldi A, Raselli G, Ratoff P, Ravat S, Razafinime H, Real JS, Rebel B, Redondo D, Reggiani-Guzzo M, Rehak T, Reichenbacher J, Reitzner SD, Renshaw A, Rescia S, Resnati F, Reynolds A, Riccobene G, Rice LCJ, Rielage K, Rigaut Y, Rivera D, Rochester L, Roda M, Rodrigues P, Alonso MJR, Rondon JR, Roeth AJ, 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 MC, Sanders DA, 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 MH, Shafaq S, Shamma M, Sharma HR, Sharma R, Shaw T, Shepherd-Themistocleous C, Shin S, Shooltz D, Shrock R, Simard L, Simos N, Sinclair J, Sinev G, Singh J, Singh J, Singh V, Sipos R, Sippach FW, Sirri G, Sitraka A, Siyeon K, Smargianaki D, Smith A, Smith A, Smith E, Smith P, Smolik J, Smy M, Snopok P, Nunes MS, Sobel H, Soderberg M, Salinas CJS, Söldner-Rembold S, Solomey N, Solovov V, Sondheim WE, Sorel M, Soto-Oton J, Sousa A, Soustruznik K, Spagliardi F, Spanu M, Spitz J, Spooner NJC, Spurgeon K, Staley R, Stancari M, Stanco L, Steiner HM, Stewart J, Stillwell B, Stock J, Stocker F, Stocks D, Stokes T, Strait M, Strauss T, Striganov S, Stuart A, Summers D, Surdo A, Susic V, Suter L, Sutera CM, Svoboda R, Szczerbinska B, Szelc AM, Talaga R, Tanaka HA, Oregui BT, Tapper A, Tariq S, Tatar E, Tayloe R, Teklu AM, Tenti M, Terao K, Ternes CA, Terranova F, Testera G, Thea A, Thompson JL, Thorn C, Timm SC, Todd J, Tonazzo A, Torti M, Tortola M, Tortorici F, Totani D, Toups M, Touramanis C, Trevor J, Trzaska WH, Tsai YT, Tsamalaidze Z, Tsang KV, Tsverava N, Tufanli S, Tull C, Tyley E, Tzanov M, Uchida MA, Urheim J, Usher T, Vagins MR, Vahle P, Valdiviesso GA, Valencia E, Vallari Z, Valle JWF, Vallecorsa S, Berg RV, de Water RGV, Forero DV, Varanini F, Vargas D, Varner G, Vasel J, Vasseur G, Vaziri K, Ventura S, Verdugo A, Vergani S, Vermeulen MA, Verzocchi M, de Souza HV, Vignoli C, Vilela C, Viren B, Vrba T, Wachala T, Waldron AV, 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 MR, White A, Whitehead LH, Whittington D, Wilking MJ, Wilkinson C, Williams Z, Wilson F, Wilson RJ, 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, Zaki R, Zalesak J, Zambelli L, Zamorano B, Zani A, Zazueta L, Zeller GP, Zennamo J, Zeug K, Zhang C, Zhao M, Zhao Y, Zhivun E, Zhu G, Zimmerman ED, Zito M, Zucchelli S, Zuklin J, Zutshi V, Zwaska R. Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment: DUNE Collaboration. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2021; 81:322. [PMID: 34720713 PMCID: PMC8550327 DOI: 10.1140/epjc/s10052-021-09007-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 02/23/2021] [Indexed: 06/13/2023]
Abstract
The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE's sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.
Collapse
Grants
- MR/T019530/1 Medical Research Council
- MR/T041323/1 Medical Research Council
- MSMT, Czech Republic
- NRF, South Korea
- Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- SERI, Switzerland
- Fundação de Amparo à Pesquisa do Estado de São Paulo
- U.S. Department of Energy
- CERN
- Türkiye Bilimsel ve Teknolojik Arastirma Kurumu
- The Royal Society, United Kingdom
- Canada Foundation for Innovation
- U.S. NSF
- FCT, Portugal
- CEA, France
- CNRS/IN2P3, France
- European Regional Development Fund
- Science and Technology Facilities Council
- H2020-EU, European Union
- IPP, Canada
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
- CAM, Spain
- MSCA, European Union
- Instituto Nazionale di Fisica Nucleare
- Fundacção de Amparo à Pesquisa do Estado de Goiás
- Ministerio de Ciencia e Innovación
- Fundacion “La Caixa” Spain
Collapse
|
8
|
Puerto MA, Shepley E, Cue RI, Warner D, Dubuc J, Vasseur E. The hidden cost of disease: I. Impact of the first incidence of mastitis on production and economic indicators of primiparous dairy cows. J Dairy Sci 2021; 104:7932-7943. [PMID: 33865582 DOI: 10.3168/jds.2020-19584] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 03/01/2021] [Indexed: 11/19/2022]
Abstract
Mastitis is a highly prevalent disease, which negatively affects cow performance, profitability, welfare, and longevity. The objectives of this study were (1) to quantify the impact of the first instance of mastitis, at different stages of lactation, on production and economic performance, and (2) to further quantify the impact of the first instance of mastitis when only cows that remain in the herd for at least 100 d in milk (DIM) and those that remain for 305 DIM are included in the analysis. A retrospective longitudinal study was conducted using data from existing animal health record files and Dairy Herd Improvement records. After editing based on selected inclusion criteria and completeness of health records, data consisted of records from first-lactation Holstein cows, from 120 herds, that calved for the first time between 2003 and 2014, inclusive. Mastitic cows were assigned to 1 of 4 groups based on when in the lactation the first event of mastitis occurred: transition (1-21 DIM), early lactation (22-100 DIM), mid lactation (101-200 DIM), or late lactation (201+ DIM). Mid-lactation and late-lactation mastitic cows were also stratified by cumulative milk yield before the mastitis event. Healthy cows (i.e., no recorded mastitis event) were randomly assigned for each lactation stage, with mid-lactation healthy and late-lactation healthy cows similarly stratified. Production performance (cumulative milk, fat, and protein yield) and economic performance [milk value, margin over feed cost (MOFC), and gross profit] were analyzed using a mixed model with herd as a random effect. Significant losses in cumulative milk yield (-382 to -989 kg) and correspondingly lower fat and protein yields were found in mastitic cows, with transition and late-lactation mastitic cows having the highest losses. Drops in production translated to significant reductions in cumulative milk value (-Can$287 to -Can$591; -US$228 to -US$470), MOFC (-Can$243 to -Can$540; -US$193 to -US$429), and gross profit (-Can$649 to -Can$908; -US$516 to -US$722) for mastitic cows at all stages. Differences between mastitic and healthy cows in the early lactation and transition stages remained for all variables in the 100-DIM analysis, but, aside from gross profit, were nonsignificant in the 305-DIM analysis. Gross profit accounted for all costs associated with mastitis and thus continued to be lower for mastitic cows at all stages, even in the 305-DIM analysis in which culled cows were omitted (-Can$485 to -Can$979; -US$386 to -US$779). The research reflects the performance implications of mastitis, providing more information upon which the producer can make informed culling decisions and maximize both herd profitability and cow longevity.
Collapse
|
9
|
Puerto MA, Shepley E, Cue RI, Warner D, Dubuc J, Vasseur E. The hidden cost of disease: II. Impact of the first incidence of lameness on production and economic indicators of primiparous dairy cows. J Dairy Sci 2021; 104:7944-7955. [PMID: 33865579 DOI: 10.3168/jds.2020-19585] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 03/01/2021] [Indexed: 11/19/2022]
Abstract
Lameness is a persistent and underreported health and welfare problem in the dairy industry, resulting in reduced cow performance and profitability as well as early culling. The study objectives were (1) to quantify the impact of the first instance of lameness, at different stages of lactation, on production and economic performance, and (2) to further quantify the impacts of the first instance of lameness when only cows that remain in the herd for at least 100 d in milk (DIM) and those that remain for 305 DIM are included in the analysis. A retrospective longitudinal study was conducted using pre-existing data from animal health records and Dairy Herd Improvement Association records. Data were edited based on selected inclusion criteria, yielding a data set containing records from 15,159 first-lactation Holstein cows from 120 herds with year of first calving between 2003 and 2014. Lame cows were assigned to 1 of 4 groups based on when in the lactation the first event of lameness occurred: transition (1-21 DIM), early lactation (22-100 DIM), mid-lactation (101-200 DIM), or late lactation (201+ DIM). Mid- and late-lactation lame cows were also stratified by cumulative milk yield before the lameness event. Healthy cows (i.e., no recorded lameness event) were randomly assigned for each lactation stage, with mid-lactation healthy and late-lactation healthy cows similarly stratified. Production performance (cumulative milk, fat, and protein yield) and economic performance [milk value, margin over feed cost (MOFC), and gross profit] were analyzed using a mixed model with herd as a random effect. Cumulative milk yields were 811 to 1,290 kg lower for lame cows than for healthy cows, with milk component yields undergoing similar reductions. Reductions in milk yield contributed to losses in milk value (-Can$527 to -Can$1,083; -US$419 to -US$862) and MOFC (-Can$510 to -Can$774; -US$406 to -US$616). Higher losses were reported using gross profit (-Can$753 to -Can$1,052; -US$599 to -US$837), which includes all lameness-related costs. Production and performance losses were smaller when 100 DIM and 305 DIM thresholds were applied (i.e., exclusion of cows culled before 100 and 305 DIM, respectively), however, mid- and late-lactation lame cows maintained high levels of significant losses for all 6 variables analyzed. Lameness also led to higher levels of culling, masking losses for transition and early-lactation lame cows in the 305-DIM analysis. Increasing producer understanding of the costs associated with lameness not only serves to provide insight to producers for more informed culling decisions, but may also help producers weigh the costs of adopting new methods and technologies targeted at reducing on-farm lameness.
Collapse
|
10
|
Jain AV, Ross PF, Carlson MP, Barger T, Barr C, Booth M, Brown W, Buckley C, Coatuey C, Colvin B, Everson R, Holt K, Kinker J, Landgraf W, Lecrone E, Medlin M, Ross S, Rumbler P, Sanchez D, Short A, Shockley M, Tahara J, Warner D, Weiband L. Screening Nitrate in Forages with a Test Strip: Collaborative Study. J AOAC Int 2020. [DOI: 10.1093/jaoac/82.1.9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
A collaborative study was conducted for screening nitrate in forages with a commercially available test strip. The method involves extracting a finely ground sample with deionized water. The test strip is dipped in the sample extract. The color of the reaction zone on the test strip changes from white to pink or purple depending on the nitrate concentration in sample extract. The nitrate present in the extract is determined by comparing the color of the test strip to the color scale on the test strip container. Six blind quintuplicates of forage samples were analyzed by 20 collaborators. Nitrate concentrations in forage samples tested ranged from <1000 ppm nitrate to >10 000 ppm nitrate on dry matter basis. Each collaborator was asked to assign each sample to one of the 4 following nitrate concentration ranges: (1) <1000 ppm, (2) 1000 to 5000 ppm, (3)>5000 ppm to 10 000 ppm, and (4) >10 000 ppm. Nineteen of 20 collaborators reported results. Results from 2 laboratories were rejected as outliers by inspection and χ2 test. Sensitivity rates (p+) ranged from 0.965 to 0.998, with standard errors of 0.006 to 0.16. Specificity rates (p−) ranged from 0.991 to 0.997 for the 4 ranges, with standard errors of 0.003 to 0.006. False-positive rates (pf+) ranged from 0.006 to 0.046, with standard errors of 0.006 to 0.025. False-negative rates (pf−) ranged from 0.003 to 0.007, with standard errors of 0.003 to 0.006. Screening nitrate in forages with a test strip has been adopted first action by AOAC INTERNATIONAL.
Collapse
|
11
|
Macome FM, Pellikaan WF, Hendriks WH, Warner D, Schonewille JT, Cone JW. In vitro gas and methane production in rumen fluid from dairy cows fed grass silages differing in plant maturity, compared to in vivo data. J Anim Physiol Anim Nutr (Berl) 2018; 102:843-852. [PMID: 29655256 DOI: 10.1111/jpn.12898] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 03/11/2018] [Indexed: 11/29/2022]
Abstract
The relationship between in vitro rumen CH4 production of grass silages, using the gas production technique, and in vivo data obtained with the same cows and rations in respiration chambers was investigated. Silages were made from grass harvested in 2013 on May 6th, May 25th, July 1st and July 8th. The grass silages were used to formulate four different rations which were fed to 24 cows in early and late lactation, resulting in a slightly different dry matter intake (DMI; 16.5 kg/day vs. 15.4 kg/day). The experimental rations consisted of 70% grass silage, 10% maize silage, and 20% concentrates on a dry matter basis. Cows were adapted to the rations for 17 days before rumen fluid was collected via oesophageal tubing, and in vitro gas and CH4 production were analysed. In vitro total gas and CH4 production of the (ensiled) grass expressed as ml/g OM decreased with advancing maturity of the grass. The in vitro CH4 production after 48 hr of incubation expressed in ml/g OM did not correlate with the in vivo CH4 production expressed in g/kg organic matter intake or g/kg DMI (R2 = .00-.18, p ≥ .287). The differences in CH4 emission per unit of intake observed in vivo were rather small between the different rations, which also contributed to the observed poor relationship. Utilizing stepwise multiple regression improved the correlation only slightly. In vitro gas and CH4 production varied based on whether donor cows were previously adapted to the respective ration or not, suggesting that careful adaption to the experimental diet should be envisaged in in vitro gas and CH4 production experiments.
Collapse
|
12
|
Warner D, Bannink A, Hatew B, van Laar H, Dijkstra J. Effects of grass silage quality and level of feed intake on enteric methane production in lactating dairy cows. J Anim Sci 2018; 95:3687-3700. [PMID: 28805897 DOI: 10.2527/jas.2017.1459] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The objective of this study was to determine the effect of level of feed intake and quality of ryegrass silage as well as their interaction on enteric methane (CH) emission from dairy cows. In a randomized block design, 56 lactating dairy cows received a diet of grass silage, corn silage, and a compound feed meal (70:10:20 on DM basis). Treatments consisted of 4 grass silage qualities prepared from grass harvested from leafy through late heading stage, and offered to dairy cows at 96 ± 2.4 (mean ± SEM) days in milk (namely, high intake) and 217 ± 2.4 d in milk (namely, low intake). Grass silage CP content varied between 124 and 286 g/kg of DM, and NDF content between 365 and 546 g/kg of DM. After 12 d of adaptation, enteric CH production of cows was measured in open-circuit climate-controlled respiration chambers for 5 d. No interaction between DMI and grass quality on CH emission, or on milk production, diet digestibility, and energy, and N retention was found ( ≥ 0.17). Cows had a greater DMI (16.6 vs. 15.5 kg/d; SEM 0.46) and greater fat- and protein-corrected milk (FPCM) yield (29.9 vs. 25.4 kg/d; SEM 1.24) at high than low intake (both ≤ 0.001). Apparent total-tract nutrient digestibility was not affected ( ≥ 0.08) by DMI level. Total enteric CH production (346 ± 10.9 g/d) was not affected ( = 0.15) by DMI level. A small, significant ( = 0.025) decrease at high compared with low intake occurred for CH yield (21.8 ± 0.59 g/kg of DMI; -4%). Methane emission intensity (12.8 ± 0.56 g/kg of FPCM; -12%) was considerably smaller ( ≤ 0.001) at high intake as a result of greater milk yields realized in early lactation. As grass quality decreased from leafy through late heading stage, FPCM yield and apparent total-tract OM digestibility declined (-12%; ≤ 0.015), whereas total CH production (+13%), CH yield (+21%), and CH emission intensity (+28%) increased ( ≤ 0.001). Our results suggest that improving grass silage quality by cutting grass at an earlier stage considerably reduces enteric CH emissions from dairy cows, independent of DMI. In contrast, losses of N in manure increased for the earlier cut grass silage treatments. The small increase in DMI at high intake was associated with a small to moderate reduction in CH emission per unit of DMI and GE intake. This study confirmed that enteric CH emissions from dairy cows at distinct levels of feed intake depend on the nutritive value and chemical composition of the grass silage.
Collapse
|
13
|
Warner D, Bannink A, Hatew B, van Laar H, Dijkstra J. Effects of grass silage quality and level of feed intake on enteric methane production in lactating dairy cows. J Anim Sci 2017. [DOI: 10.2527/jas2017.1459] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
14
|
Benchaar C, Hassanat F, Warner D, Petit H. 1457 Enteric methane emissions from dairy cows fed a corn silage–based diet supplemented with increasing amounts of linseed oil. J Anim Sci 2016. [DOI: 10.2527/jam2016-1457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
15
|
Lipton A, Stopeck A, Body JJ, Von Moos R, De Boer R, Paiva Gadelha Guimaraes A, Tonkin K, Fujiwara Y, Zhu L, Warner D. Abstract P3-07-45: Bone turnover marker levels and clinical outcomes in patients with breast cancer and bone metastases treated with bone antiresorptive therapies. Cancer Res 2016. [DOI: 10.1158/1538-7445.sabcs15-p3-07-45] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
INTRODUCTION AND OBJECTIVES: Patients with advanced breast cancer (BC) and metastatic bone disease typically have elevated serum levels of bone turnover markers (BTMs). Potent antiresorptive agents, such as denosumab and zoledronic acid, can significantly reduce BTM levels (Stopeck et al. J Clin Oncol 2010). Prior studies have provided evidence that higher BTM baseline levels may be associated with worse clinical outcomes (Ali et al. Ann Oncol 2004). In this analysis, we assessed the association between BTM levels after treatment with antiresorptive agents and overall survival (OS), disease progression (DP) and disease progression in the bone (DPB) in patients with advanced BC and bone metastases.
METHODS: This post-hoc analysis included data from patients with BC and bone metastases enrolled in an international, blinded phase 3 trial who were randomized to receive either denosumab (120 mg SC) or zoledronic acid (4 mg IV, adjusted for creatinine clearance). The BTMs urinary N-telopeptide (uNTx) and bone-specific alkaline phosphatase (BSAP) were measured at study entry and at study month 3. The clinical outcomes of OS, DP, and DPB were compared in patients with BTMs above or below median levels at month 3 of antiresorptive therapy. These covariate analyses were based on Cox models stratified by treatment, prior SRE before month 3, prior bisphosphonate use, chemotherapy at randomization, and region (Japan or other countries).
RESULTS: A total of 1705 patients were measured for uNTx serum levels, with 895 patients ≥ and 810 < the median of 10.40 nmol/mmol at month 3. Similarly, BSAP levels were measured in a total of 1708 patients, with 855 patients ≥ and 853 < the median BSAP level of 10.89 ng/mL at month 3. Patients with uNTx levels ≥ the median at month 3 had a significantly reduced OS (by 54%) and a greater risk of both DP (by 21%) and DPB (by 23%) than patients with uNTx levels < median (see Table). Similarly, patients with BSAP levels ≥ the median level at month 3 had an increased risk for reduced OS (by 197%), DP (by 67%) and DPB (by 56%) compared with patients whose BSAP levels < median. After adjusting for risk factors suggestive of more advanced disease such as visceral metastases or > 2 bone metastases, the correlation between elevated BTMs and reduced OS and greater risk of DP and DPB was maintained.
CONCLUSIONS: Patients with BTM levels ≥ median at month 3 of antiresorptive therapy had generally worse clinical outcomes than patients whose BTM levels were < median. Assessment of uNTx and BSAP serum levels after treatment with antiresorptive therapy can add to our understanding of which patients with breast cancer and bone metastases are most at risk for decreased OS, or increased DP or DPB.
Month 3*Covariate Analysis Results: Risk of Decreased OS or Increased DP or DPBClinical OutcomeHazard Ratio (95% Confidence Interval)P-valueDecrease in OSuNTXa1.539 (1.270, 1.866)<0.0001BSAPb2.966 (2.422, 3.633)<0.0001Increase in DPuNTXa1.214 (1.071, 1.377)=0.0024BSAPb1.666 (1.470, 1.888)<0.0001Increase of DPBuNTXa1.231 (1.054, 1.437)=0.0087BSAPb1.563 (1.342, 1.821)<0.0001*Comparing ≥ median to < median. aMedian uNTx levels=10.40 nmol/mmol. bMedian BSAP level=10.89 ng/mL.
Citation Format: Lipton A, Stopeck A, Body J-J, Von Moos R, De Boer R, Paiva Gadelha Guimaraes A, Tonkin K, Fujiwara Y, Zhu L, Warner D. Bone turnover marker levels and clinical outcomes in patients with breast cancer and bone metastases treated with bone antiresorptive therapies. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-45.
Collapse
|
16
|
Bannink A, Warner D, Hatew B, Ellis JL, Dijkstra J. Quantifying effects of grassland management on enteric methane emission. ANIMAL PRODUCTION SCIENCE 2016. [DOI: 10.1071/an15594] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Data on the effect of grassland management on the nutritional characteristics of fresh and conserved grass, and on enteric methane (CH4) emission in dairy cattle, are sparse. In the present study, an extant mechanistic model of enteric fermentation was evaluated against observations on the effect of grassland management on CH4 emission in three trials conducted in climate-controlled respiration chambers. Treatments were nitrogen fertilisation rate, stage of maturity of grass and level of feed intake, and mean data of a total of 18 treatments were used (4 grass herbage treatments and 14 grass silage treatments). There was a wide range of observed organic matter (OM) digestibility (from 68% to 84%) and CH4 emission intensity (from 5.6% to 7.3% of gross energy intake; from 27.4 to 36.9 g CH4/kg digested OM; from 19.7 to 24.6 g CH4/kg dry matter) among treatment means. The model predicted crude protein, fibre and OM digestibility with reasonable accuracy (root of mean square prediction errors as % of observed mean, RMSPE, 6.8%, 7.5% and 3.9%, respectively). For grass silages only, the model-predicted CH4 correlated well (Pearson correlation coefficient 0.73) with the observed CH4 (which varied from 5.7% to 7.2% of gross energy intake), after predicted CH4 was corrected for nitrate consumed with grass silage, acting as hydrogen sink in the rumen. After nitrate correction, there was a systematic under-prediction of 18%, which reduced to 9% when correcting the erroneously predicted rumen volatile fatty acid (VFA) profile (RMSPE 15%). Although a small over-prediction of 3% was obtained for the grass herbages, this increased to 14% when correcting VFA profile. The model predictions showed a systematic difference in CH4 emission from grass herbages and grass silages, which was not supported by the observed data. This is possibly related to the very high content of soluble carbohydrates in grass herbage (an extra 170 g/kg dry matter compared with grass silages) and an erroneous prediction of its fate and contribution to CH4 in the rumen. Erroneous prediction of the VFA profile is likely to be due to different types of diets included in the empirical database used to parameterise VFA yield in the model from those evaluated here. Model representations of feed digestion and VFA profile are key elements to predict enteric CH4 accurately, and with further evaluations, the latter aspect should be emphasised in particular.
Collapse
|
17
|
Dijkstra J, van Gastelen S, Antunes-Fernandes EC, Warner D, Hatew B, Klop G, Podesta SC, van Lingen HJ, Hettinga KA, Bannink A. Relationships between milk fatty acid profiles and enteric methane production in dairy cattle fed grass- or grass silage-based diets. ANIMAL PRODUCTION SCIENCE 2016. [DOI: 10.1071/an15509] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
We quantified relationships between methane production and milk fatty acid (FA) profile in dairy cattle fed grass- or grass silage-based diets, and determined whether recent prediction equations for methane, based on a wide variety of diets, are applicable to grass- and grass silage-based diets. Data from three studies were used, encompassing four grass herbage and 14 grass silage treatments and 132 individual cow observations. Methane production was measured using respiration chambers and milk fatty acids (FAs) analysed using gas chromatography. The proportion of grass or grass silage (dry matter (DM) basis) was 0.80 ± 0.037. Methane yield averaged 22.3 ± 2.10 g/kg DM intake (DMI) and 14.2 ± 2.90 g/kg fat- and protein-corrected milk (FPCM). Mixed model univariate regression including a random study effect on intercept was applied to predict methane yield, with individual milk FA concentrations (g/100 g FA) as fixed effects. Of the 42 milk FAs identified, no single FA had a strong positive correlation (r; strong correlation defined as |r| ≥ 0.50) with methane yield (g/kg DMI), and cis-12 C18:1 and cis-9,12,15 C18:3 had a strong negative correlation with methane yield (g/kg DMI). C14:0 iso, C15:0, C15:0 iso, C15:0 anteiso, C16:0, C20:0, cis-11,14 C20:2, cis-5,8,11,14 C20:4, C22:0, cis-7,10,13,16,19 C22:5 and C24:0 had a strong positive correlation with methane yield (g/kg FPCM), and trans-15+cis-11 C18:1, cis-9 C18:1, and cis-11 C20:1 had a strong negative correlation with methane yield (g/kg FPCM). Observed methane yield was compared with methane yield predicted by the equations of van Lingen et al. (2014; Journal of Dairy Science 97, 7115–7132). These equations did not accurately predict methane yield as grams per kilogram DMI (concordance correlation coefficient (CCC) = 0.13) or as grams per kilogram FPCM (CCC = 0.22), in particular related to large differences in standard deviation between predicted and observed values. In conclusion, quantitative relationships between milk FA profile and methane yield in cattle fed grass- or grass silage-based diets differ from those determined for other types of diets.
Collapse
|
18
|
Creagh O, Torres H, Rivera K, Morales-Franqui M, Altieri-Acevedo G, Warner D. Previous Exposure to Anesthesia and Autism Spectrum Disorder (ASD): A Puerto Rican Population-Based Sibling Cohort Study. BOLETIN DE LA ASOCIACION MEDICA DE PUERTO RICO 2016; 108:73-80. [PMID: 29172370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) is characterized by impaired social interaction and communication, and by restricted and repetitive behavior, that begins usually before a child is three years old.(1) Researchers have shown that prevalence rates in the U.S. may be as high as 1 in 68.(52) A number of studies have examined the effects of early exposure to anesthesia on brain development and subsequent impairment in neurocognitive function; yet, little is known about the possible effects of anesthetic agents on social-behavioral functioning. The association between exposure to anesthesia either in uterus, during the first years of life, or later and development of Autistic Spectrum Disorder (ASD) or its severity was determined in a retrospective population based cohort study. OBJECTIVES Identify if children who had previous exposure to anesthesia either in uterus, first years of life during their developing brain years, or later, are at risk of developing ASD and its severe form of the disease. METHODS Data was obtained from structured interviews administered to a sample of 515 parents/guardians distributed in two groups: ASD = 262 children diagnosed with this condition and Non-ASD: 253 children (siblings of ASD group) without diagnosis (95% confidence interval) that freely decided to participate and agreed to a consent form. Variables studied include: demographics, diagnosis and severity of ASD, exposure to anesthesia, method of childbirth, and age of exposure Children less than 2 years of age were considered into have developing brain period. Data was analyzed using Chi-square or Fisher exact test. RESULTS In contrast to non-ASD group, most of the children within ASD group were male, 76% (p=0.0001). With regards to methods of childbirth, 64% of the ASD population were vaginal delivery (VD; Non-anesthesia exposure group) and 36% cesarean delivery (CD) compared to non-autistic population with 71% VD and 29% CD, which demonstrates no statistical difference between both groups (p=0.1113). Out of the 36% of ASD population that underwent CD, 7% were performed using general anesthesia and 93% regional anesthesia, while the 29% of the CD of non-ASD, 5% were performed using general anesthesia and 95% regional anesthesia. This reveals no statistical significance (p=0.7569) with the development of ASD and the type of anesthesia used when comparing ASD with non-ASD patients. In view of severity of autism, in VD, 56% of ASD population had mild form of the disorder, 34% moderate, and 10% severe; while CD had a 54% mild form of the disorder, 33% moderate, and 13% severe. This shows no statistical association (p=0.8069) when comparing exposure to anesthesia in uterus to subsequent severe form of ASD. Of the 262 ASD patients, 99 had exposure to anesthetics before their diagnosis, while in Non-ASD population, 110 had exposure to anesthesia, demonstrating no statistically significant association between both groups (p=0.2091). Out of 99 ASD patients exposed to anesthesia prior to their diagnosis, 72 were exposed before age 2. When compared to the 110 Non-ASD patients exposed to anesthesia, 86 had exposure during this developing brain period, which indicates no statistically significant association (p=0.4207). In addition, most of the ASD children exposed to anesthesia during developing brain were diagnosed with mild degree of the disorder when compared to ASD children without any previous exposure to anesthesia (p=0.9700) during the same period. When the exposure occurred after age 2, ASD children developed mild form of the disorder as compared with ASD children without any previous exposure to anesthesia (p=0.1699) in that period. CONCLUSIONS Children under early exposure to anesthesia in uterus, first 2 years of life, or later are not more likely to develop neither ASD nor severe form of the disorder.
Collapse
|
19
|
Creagh O, Torres H, Rivera K, Morales-Franqui M, Altieri-Acevedo G, Warner D. Previous Exposure to Anesthesia and Autism Spectrum Disorder (ASD): A Puerto Rican Population-Based Sibling Cohort Study. BOLETIN DE LA ASOCIACION MEDICA DE PUERTO RICO 2015; 107:29-37. [PMID: 26742193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) is characterized by impaired social interaction and communication, and by restricted and repetitive behavior, that begins usually before a child is three years old.1 Researchers have shown that prevalence rates in the U.S. may be as high as 1 in 68.52 A number of studies have examined the effects of early exposure to anesthesia on brain development and subsequent impairment in neurocognitive function; yet, little is known about the possible effects of anesthetic agents on social-behavioral functioning. The association between exposure to anesthesia either in uterus, during the first years of life, or later and development of Autistic Spectrum Disorder (ASD) or its severity was determined in a retrospective population based cohort study. OBJECTIVES Identify if children who had previous exposure to anesthesia either in uterus, first years of life during their developing brain years, or later, are at risk of developing ASD and its severe form of the disease. METHODS Data was obtained from structured interviews administered to a sample of 515 parents/guardians distributed in two groups: ASD = 262 children diagnosed with this condition and Non-ASD: 253 children (siblings of ASD group) without diagnosis (p = 0.8069) when comparing exposure to anesthesia in uterus to subsequent severe form of ASD. Of the 262 ASD patients, 99 had exposure to anesthetics before their diagnosis, while in Non-ASD population, 110 had exposure to anesthesia, demonstrating no statistically significant association between both groups (p = 0.2091). Out of 99 ASD patients exposed to anesthesia prior to their diagnosis, 72 were exposed before age 2. When compared to the 110 Non-ASD patients exposed to anesthesia, 86 had exposure during this developing brain period, which indicates no statistically significant association (p = 0.4207). In addition, most of the ASD children exposed to anesthesia during developing brain were diagnosed with mild degree of the disorder when compared to ASD children without any previous exposure to anesthesia (p = 0.9700) during the same period. When the exposure occurred after age 2, ASD children developed mild form of the disorder as compared with ASD children without any previous exposure to anesthesia (p = 0.1699) in that period. CONCLUSIONS Children under early exposure to anesthesia in uterus, first 2 years of life, or later are not more likely to develop neither ASD nor severe form of the disorder. INDEX WORDS: Anesthesia, Autism Spectrum Disorder, Puerto Rico. (95% confidence interval) that freely decided to participate and agreed to a consent form. Variables studied, include: demographics, diagnosis and severity of ASD, exposure to anesthesia, method of childbirth, and age of exposure. Children less than 2 years of age were considered into have developing brain period. Data was analyzed using Chi-square or Fisher exact test. RESULTS In contrast to non-ASD group, most of the children within ASD group were male, 76% (p = 0.0001). With regards to methods of childbirth, 64% of the ASD population were vaginal delivery (VD; Non-anesthesia exposure group) and 36% cesarean delivery (CD) compared to non-autistic population with 71% VD and 29% CD, which demonstrates no statistical difference between both groups (p = 0.1113). Out of the 36% of ASD population that underwent CD, 7% were performed using general anesthesia and 93% regional anesthesia, while the 29% of the CD of non-ASD, 5% were performed using general anesthesia and 95% regional anesthesia. This reveals no statistical significance (p = 0.7569) with the development of ASD and the type of anesthesia used when comparing ASD with non-ASD patients. In view of severity of autism, in VD, 56% of ASD population had mild form of the disorder, 34% moderate, and 10% severe; while CD had a 54% mild form of the disorder, 33% moderate, and 13% severe. This shows no statistical association.
Collapse
|
20
|
Warner D, Podesta S, Hatew B, Klop G, van Laar H, Bannink A, Dijkstra J. Effect of nitrogen fertilization rate and regrowth interval of grass herbage on methane emission of zero-grazing lactating dairy cows. J Dairy Sci 2015; 98:3383-93. [DOI: 10.3168/jds.2014-9068] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Accepted: 01/31/2015] [Indexed: 12/19/2022]
|
21
|
Vergote I, Oaknin A, Baurain JF, Ananda S, Wong S, Su X, Wu B, Zhong Z, Warner D, Casado A. A phase 1b, open-label study of trebananib in combination with paclitaxel and carboplatin in patients with ovarian cancer receiving interval or primary debulking surgery. Eur J Cancer 2014; 50:2408-16. [PMID: 25037684 DOI: 10.1016/j.ejca.2014.06.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2014] [Revised: 06/10/2014] [Accepted: 06/13/2014] [Indexed: 01/29/2023]
Abstract
AIM To evaluate the tolerability, pharmacokinetics and tumour response of first-line trebananib plus paclitaxel and carboplatin followed by trebananib maintenance in high-risk or advanced ovarian cancer. METHODS In this open-label phase 1b study, patients received intravenous (IV) trebananib 15 mg/kg administered weekly (QW) plus paclitaxel 175 mg/m(2) once every 3 weeks (Q3W) and carboplatin 6 mg/mL · min Q3W followed by trebananib 15 mg/kg QW monotherapy for 18 months. End-points were dose-limiting toxicities (DLTs; primary); treatment-emergent adverse events (AEs), anti-trebananib antibodies, pharmacokinetics and tumour response (secondary). RESULTS Twenty seven patients (interval debulking surgery [IDS], n=13) were enrolled. No DLTs occurred. During the combination therapy phase, AEs (>50%) in patients with IDS were nausea, diarrhoea, fatigue, decreased appetite and thrombocytopenia. In patients with primary debulking surgery (PDS), they were nausea, diarrhoea, fatigue and localised oedema. Grade 4 AEs were neutropenia (IDS, PDS; all n=3) and thrombocytopenia (IDS, PDS; all n=1). No deaths occurred. Toxicity results pertaining to trebananib maintenance were immature. The treatment combination did not markedly affect the pharmacokinetics across agents. In patients with IDS (n=14 after one patient was reassigned from PDS to IDS), 12 patients had a partial response (PR), two patients had stable disease. In patients with PDS (n=4), three patients had a complete response, one patient had a PR. CONCLUSIONS In women with ovarian cancer receiving IDS or PDS, IV trebananib 15 mg/kg QW plus paclitaxel and carboplatin appears tolerable. Results suggest that the treatment combination followed by trebananib 15 mg/kg monotherapy is associated with antitumour activity.
Collapse
|
22
|
Heeren JAH, Podesta SC, Hatew B, Klop G, van Laar H, Bannink A, Warner D, de Jonge LH, Dijkstra J. Rumen degradation characteristics of ryegrass herbage and ryegrass silage are affected by interactions between stage of maturity and nitrogen fertilisation rate. ANIMAL PRODUCTION SCIENCE 2014. [DOI: 10.1071/an14259] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The objective of this experiment was to evaluate interaction effects between stage of maturity and nitrogen (N) fertilisation rate on rumen degradation characteristics determined with nylon bag incubations of ryegrass herbages and ryegrass silage. Grass herbage (n = 4) was cut after 3 or 5 weeks of regrowth and received a low (20 kg N/ha) or a high (90 kg N/ha) fertilisation rate. Grass silage (n = 6) received a low (65 kg N/ha) or high (150 kg N/ha) fertilisation rate and was harvested at early (~2000 kg DM/ha), mid (harvested 13 days later), or late (harvested 34 days later) maturity stage and ensiled in big bales. All grasses were incubated in the rumen of three lactating rumen-cannulated Holstein Friesian cows. Rumen degradation characteristics of organic matter (OM), N and neutral detergent fibre (NDF) and the extent of effective degradation (ED) were evaluated. In grass herbage, NDF content varied between 390 and 454 g/kg DM and N content between 12.1 and 25.8 g/kg DM. In grass silage, NDF content varied between 438 and 593 g/kg DM and N content between 13.4 and 34.8 g/kg DM. In general, rumen degradation of grass herbage and grass silage decreased with increased maturity, and increased with increased fertilisation rate. Significant interaction between maturity and fertilisation rate was observed for ED of OM, N and NDF, except for ED of N in grass herbage. These results indicate that the effect of the rate of N fertilisation on degradation of nutrients in the rumen of dairy cattle and on nutritional value depends on the grass maturity stage.
Collapse
|
23
|
Daniel JB, Van Laar H, Warner D, Dijkstra J, Navarro-Villa A, Pellikaan WF. Passage kinetics of dry matter and neutral detergent fibre through the gastro-intestinal tract of growing beef heifers fed a high-concentrate diet measured with internal δ13C and external markers. ANIMAL PRODUCTION SCIENCE 2014. [DOI: 10.1071/an14354] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Fractional rumen passage rates (K1) are fundamental in feed evaluation systems for ruminants to predict the extent of nutrient degradation. Data on passage kinetics of growing beef cattle fed high-concentrate diets are scarce and mainly rely on external passage markers which do not provide nutrient-specific K1 estimates. The present study describes the use of carbon stable isotopes (δ13C) as an internal marker to estimate K1 of dry matter (DM) and neutral detergent fibre (NDF) fractions of a compound feed in a high-concentrate diet, and compares them to the external markers ytterbium (Yb)-actetate and chromium mordanted fibre (Cr-NDF). Four rumen-fistulated Holstein heifers received four times per day a basal diet consisting of barley straw and pelleted compound feed offered separately (ratio 10 : 90, DM basis). Compound feed in the basal diet was mainly based on wheat of low natural 13C enrichment (−28.4 δ13C), which was exchanged with a single dose of a maize-based compound feed of higher natural 13C enrichment (−18.9 δ13C). This difference in natural 13C abundance was used to determine K1 values from faecal 13C excretion patterns. At the same time Yb-Acetate and Cr-NDF were introduced into the rumen to determine K1 values from faecal excretions. Faeces were collected over 90 h after pulse dosing. The K1 of δ13C-marked DM (0.062/h) did not differ (P = 0.745) from δ13C-marked NDF (0.060/h). The δ13C-based K1 values also did not differ from Cr-NDF (0.056/h; P = 0.315). These results indicate similar passage behaviour of these fractions in the rumen of beef heifers fed a high-concentrate diet.
Collapse
|
24
|
Warner D, Dijkstra J, Hendriks W, Pellikaan W. Passage of stable isotope-labeled grass silage fiber and fiber-bound protein through the gastrointestinal tract of dairy cows. J Dairy Sci 2013; 96:7904-17. [DOI: 10.3168/jds.2013-7168] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Accepted: 08/18/2013] [Indexed: 11/19/2022]
|
25
|
Boyer J, Byrne P, Cassman K, Cooper M, Delmer D, Greene T, Gruis F, Habben J, Hausmann N, Kenny N, Lafitte R, Paszkiewicz S, Porter D, Schlegel A, Schussler J, Setter T, Shanahan J, Sharp R, Vyn T, Warner D, Gaffney J. The U.S. drought of 2012 in perspective: A call to action. GLOBAL FOOD SECURITY-AGRICULTURE POLICY ECONOMICS AND ENVIRONMENT 2013. [DOI: 10.1016/j.gfs.2013.08.002] [Citation(s) in RCA: 83] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
|