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Urbain J, Dinahet T, Martin O, Lukaszewicz AC, Mojallal AA, Lherm M. [Local administration of amphotericin B by VAC instillation: Therapeutic aid in the treatment of mucormycosis]. ANN CHIR PLAST ESTH 2024; 69:222-227. [PMID: 37596143 DOI: 10.1016/j.anplas.2023.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/20/2023]
Abstract
Mucormycosis is a rare and serious fungal infection, occurring mainly in immunocompromised, diabetic, polytrauma or burn patients. Current standard treatments include iterative carcinological surgical trimming, systemic treatment with liposomal amphotericin B and second-line Posaconazole or Isavuconazole. We report the case of a 37-year-old female patient with no previous medical history who developed a disseminated mucormycosis, with an estimated 25 % loss of skin substance and major decay of the chest wall. In addition to standard treatment, local instillations of amphotericin B using the VAC Veraflow® system were performed. We believe that local instillations of amphotericin B by VAC could improve the functional prognosis of patients with skin involvement.
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Affiliation(s)
- J Urbain
- Service de chirurgie des brûlés, plastique, reconstructrice et esthétique, hôpital de la Croix-Rousse, hospices civils de Lyon, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France.
| | - T Dinahet
- Service de chirurgie des brûlés, plastique, reconstructrice et esthétique, hôpital de la Croix-Rousse, hospices civils de Lyon, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France
| | - O Martin
- Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France; Service d'anesthésie réanimation, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France
| | - A C Lukaszewicz
- Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France; Service d'anesthésie réanimation, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France
| | - A-A Mojallal
- Service de chirurgie des brûlés, plastique, reconstructrice et esthétique, hôpital de la Croix-Rousse, hospices civils de Lyon, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France
| | - M Lherm
- Service de chirurgie des brûlés, plastique, reconstructrice et esthétique, hôpital de la Croix-Rousse, hospices civils de Lyon, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Centre de traitement des brûlés de Lyon Pierre-Colson, hôpital Edouard-Herriot, hospices civils de Lyon, 5, place d'Arsonval, 69003 Lyon, France
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2
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Affiliation(s)
- E Rosenberg
- Google Research, Mountain View, CA, USA
- Department of Physics, Cornell University, Ithaca, NY, USA
| | | | - R Samajdar
- Department of Physics, Princeton University, Princeton, NJ, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, USA
| | | | - J C Hoke
- Department of Physics, Stanford University, Stanford, CA, USA
| | - D Abanin
- Google Research, Mountain View, CA, USA
| | | | - I K Drozdov
- Google Research, Mountain View, CA, USA
- Department of Physics, University of Connecticut, Storrs, CT, USA
| | | | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - A Morvan
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - R Allen
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - A Bilmes
- Google Research, Mountain View, CA, USA
| | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - J Campero
- Google Research, Mountain View, CA, USA
| | - H-S Chang
- Google Research, Mountain View, CA, USA
| | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | - C Earle
- Google Research, Mountain View, CA, USA
| | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - G Garcia
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | - G Hill
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- QSI, Faculty of Engineering & Information Technology, University of Technology Sydney, Ultimo, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - S Mandrà
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | - S Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | - S Meeks
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - S Omonije
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - V Sivak
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | | | - R D Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - D Thor
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | | | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - V Khemani
- Department of Physics, Stanford University, Stanford, CA, USA
| | | | - T Prosen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - P Roushan
- Google Research, Mountain View, CA, USA
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3
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Affiliation(s)
- X Mi
- Google Research, Mountain View, CA, USA
| | - A A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - S Shabani
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | - J Lloyd
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | | | - R Acharya
- Google Research, Mountain View, CA, USA
| | - I Aleiner
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - C Chou
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | - A G Dau
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | | | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Software and Information (QSI), Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | | | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | | | | | - A Morvan
- Google Research, Mountain View, CA, USA
| | | | | | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | | | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Google Research, Mountain View, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - R Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z J Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | - P Roushan
- Google Research, Mountain View, CA, USA
| | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
- Department of Physics, Princeton University, Princeton, NJ, USA
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4
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Hoke JC, Ippoliti M, Rosenberg E, Abanin D, Acharya R, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Eppens D, Erickson C, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Miao KC, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Mi X, Khemani V, Roushan P. Measurement-induced entanglement and teleportation on a noisy quantum processor. Nature 2023; 622:481-486. [PMID: 37853150 PMCID: PMC10584681 DOI: 10.1038/s41586-023-06505-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/01/2023] [Indexed: 10/20/2023]
Abstract
Measurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the 'arrow of time' that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time3-10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11-13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15-17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.
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5
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Taghipoor M, Pastell M, Martin O, Nguyen Ba H, van Milgen J, Doeschl-Wilson A, Loncke C, Friggens NC, Puillet L, Muñoz-Tamayo R. Animal board invited review: Quantification of resilience in farm animals. Animal 2023; 17:100925. [PMID: 37690272 DOI: 10.1016/j.animal.2023.100925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/17/2023] [Accepted: 07/20/2023] [Indexed: 09/12/2023] Open
Abstract
Resilience, when defined as the capacity of an animal to respond to short-term environmental challenges and to return to the prechallenge status, is a dynamic and complex trait. Resilient animals can reinforce the capacity of the herd to cope with often fluctuating and unpredictable environmental conditions. The ability of modern technologies to simultaneously record multiple performance measures of individual animals over time is a huge step forward to evaluate the resilience of farm animals. However, resilience is not directly measurable and requires mathematical models with biologically meaningful parameters to obtain quantitative resilience indicators. Furthermore, interpretive models may also be needed to determine the periods of perturbation as perceived by the animal. These applications do not require explicit knowledge of the origin of the perturbations and are developed based on real-time information obtained in the data during and outside the perturbation period. The main objective of this paper was to review and illustrate with examples, different modelling approaches applied to this new generation of data (i.e., with high-frequency recording) to detect and quantify animal responses to perturbations. Case studies were developed to illustrate alternative approaches to real-time and post-treatment of data. In addition, perspectives on the use of hybrid models for better understanding and predicting animal resilience are presented. Quantification of resilience at the individual level makes possible the inclusion of this trait into future breeding programmes. This would allow improvement of the capacity of animals to adapt to a changing environment, and therefore potentially reduce the impact of disease and other environmental stressors on animal welfare. Moreover, such quantification allows the farmer to tailor the management strategy to help individual animals to cope with the perturbation, hence reducing the use of pharmaceuticals, and decreasing the level of pain of the animal.
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Affiliation(s)
- M Taghipoor
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France.
| | - M Pastell
- Natural Resources Institute Finland (Luke), Production Systems, Helsinki, Finland
| | - O Martin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France
| | - H Nguyen Ba
- Univ Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 SaintGenes Champanelle, France
| | | | - A Doeschl-Wilson
- The Roslin Institute, University of Edinburgh, Easter Bush EH25 9RG, UK
| | - C Loncke
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France
| | - N C Friggens
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France
| | - L Puillet
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France
| | - R Muñoz-Tamayo
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 91120 Palaiseau, France
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6
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Andersen TI, Lensky YD, Kechedzhi K, Drozdov IK, Bengtsson A, Hong S, Morvan A, Mi X, Opremcak A, Acharya R, Allen R, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Babbush R, Bacon D, Bardin JC, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hilton J, Hoffmann MR, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Lucero E, Malone FD, Martin O, McClean JR, McCourt T, McEwen M, Miao KC, Mieszala A, Mohseni M, Montazeri S, Mount E, Movassagh R, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O’Brien TE, Omonije S, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Kim EA, Aleiner I, Roushan P. Non-Abelian braiding of graph vertices in a superconducting processor. Nature 2023; 618:264-269. [PMID: 37169834 DOI: 10.1038/s41586-023-05954-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/14/2023] [Indexed: 06/09/2023]
Abstract
Indistinguishability of particles is a fundamental principle of quantum mechanics1. For all elementary and quasiparticles observed to date-including fermions, bosons and Abelian anyons-this principle guarantees that the braiding of identical particles leaves the system unchanged2,3. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions4-8. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well-developed mathematical description of non-Abelian anyons and numerous theoretical proposals9-22, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. Whereas efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasiparticles, superconducting quantum processors allow for directly manipulating the many-body wavefunction by means of unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons9,10, we implement a generalized stabilizer code and unitary protocol23 to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of using the anyons for quantum computation and use braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and, through the future inclusion of error correction to achieve topological protection, could open a path towards fault-tolerant quantum computing.
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7
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Kolluri M, Martin O, Naziris F, D'Agata E, Gillemot F, Brumovsky M, Ulbricht A, Autio JM, Shugailo O, Horvath A. Structural MATerias research on parameters influencing the material properties of RPV steels for safe long-term operation of PWR NPPs. Nuclear Engineering and Design 2023. [DOI: 10.1016/j.nucengdes.2023.112236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
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8
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Morvan A, Andersen TI, Mi X, Neill C, Petukhov A, Kechedzhi K, Abanin DA, Michailidis A, Acharya R, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Del Toro Barba A, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores Burgos L, Forati E, Fowler AG, Foxen B, Giang W, Gidney C, Gilboa D, Giustina M, Grajales Dau A, Gross JA, Habegger S, Hamilton MC, Harrigan MP, Harrington SD, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lester BJ, Lill AT, Liu W, Locharla A, Malone F, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Nersisyan A, Newman M, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Olenewa R, Opremcak A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shvarts V, Skruzny J, Smith WC, Strain D, Sterling G, Su Y, Szalay M, Torres A, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Xing C, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Aleiner I, Ioffe LB, Roushan P. Formation of robust bound states of interacting microwave photons. Nature 2022; 612:240-245. [PMID: 36477133 PMCID: PMC9729104 DOI: 10.1038/s41586-022-05348-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/14/2022] [Indexed: 12/12/2022]
Abstract
Systems of correlated particles appear in many fields of modern science and represent some of the most intractable computational problems in nature. The computational challenge in these systems arises when interactions become comparable to other energy scales, which makes the state of each particle depend on all other particles1. The lack of general solutions for the three-body problem and acceptable theory for strongly correlated electrons shows that our understanding of correlated systems fades when the particle number or the interaction strength increases. One of the hallmarks of interacting systems is the formation of multiparticle bound states2-9. Here we develop a high-fidelity parameterizable fSim gate and implement the periodic quantum circuit of the spin-½ XXZ model in a ring of 24 superconducting qubits. We study the propagation of these excitations and observe their bound nature for up to five photons. We devise a phase-sensitive method for constructing the few-body spectrum of the bound states and extract their pseudo-charge by introducing a synthetic flux. By introducing interactions between the ring and additional qubits, we observe an unexpected resilience of the bound states to integrability breaking. This finding goes against the idea that bound states in non-integrable systems are unstable when their energies overlap with the continuum spectrum. Our work provides experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.
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Affiliation(s)
- A Morvan
- Google Research, Mountain View, CA, USA
| | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J Basso
- Google Research, Mountain View, CA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | - D Eppens
- Google Research, Mountain View, CA, USA
| | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Computation and Communication Technology, Centre for Quantum Software and Information, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Y Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - F Malone
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | - K C Miao
- Google Research, Mountain View, CA, USA
| | - M Mohseni
- Google Research, Mountain View, CA, USA
| | | | - E Mount
- Google Research, Mountain View, CA, USA
| | | | - O Naaman
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - R Olenewa
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | | | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - D Strain
- Google Research, Mountain View, CA, USA
| | | | - Y Su
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - I Aleiner
- Google Research, Mountain View, CA, USA.
| | - L B Ioffe
- Google Research, Mountain View, CA, USA.
| | - P Roushan
- Google Research, Mountain View, CA, USA.
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9
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Mi X, Sonner M, Niu MY, Lee KW, Foxen B, Acharya R, Aleiner I, Andersen TI, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Basso J, Bengtsson A, Bortoli G, Bourassa A, Brill L, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chen Z, Chiaro B, Collins R, Conner P, Courtney W, Crook AL, Debroy DM, Demura S, Dunsworth A, Eppens D, Erickson C, Faoro L, Farhi E, Fatemi R, Flores L, Forati E, Fowler AG, Giang W, Gidney C, Gilboa D, Giustina M, Dau AG, Gross JA, Habegger S, Harrigan MP, Hoffmann M, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Kafri D, Kechedzhi K, Khattar T, Kim S, Kitaev AY, Klimov PV, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Lee J, Laws L, Liu W, Locharla A, Martin O, McClean JR, McEwen M, Meurer Costa B, Miao KC, Mohseni M, Montazeri S, Morvan A, Mount E, Mruczkiewicz W, Naaman O, Neeley M, Neill C, Newman M, O’Brien TE, Opremcak A, Petukhov A, Potter R, Quintana C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schuster C, Shearn MJ, Shvarts V, Strain D, Su Y, Szalay M, Vidal G, Villalonga B, Vollgraff-Heidweiller C, White T, Yao Z, Yeh P, Yoo J, Zalcman A, Zhang Y, Zhu N, Neven H, Bacon D, Hilton J, Lucero E, Babbush R, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Abanin DA, Roushan P. Noise-resilient edge modes on a chain of superconducting qubits. Science 2022; 378:785-790. [DOI: 10.1126/science.abq5769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model, which exhibits nonlocal Majorana edge modes (MEMs) with
ℤ
2
parity symmetry. We find that any multiqubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.
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Affiliation(s)
- X. Mi
- Google Research, Mountain View, CA, USA
| | - M. Sonner
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - M. Y. Niu
- Google Research, Mountain View, CA, USA
| | - K. W. Lee
- Google Research, Mountain View, CA, USA
| | - B. Foxen
- Google Research, Mountain View, CA, USA
| | | | | | | | - F. Arute
- Google Research, Mountain View, CA, USA
| | - K. Arya
- Google Research, Mountain View, CA, USA
| | - A. Asfaw
- Google Research, Mountain View, CA, USA
| | | | - J. C. Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - J. Basso
- Google Research, Mountain View, CA, USA
| | | | | | | | - L. Brill
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Chen
- Google Research, Mountain View, CA, USA
| | - B. Chiaro
- Google Research, Mountain View, CA, USA
| | | | - P. Conner
- Google Research, Mountain View, CA, USA
| | | | | | | | - S. Demura
- Google Research, Mountain View, CA, USA
| | | | - D. Eppens
- Google Research, Mountain View, CA, USA
| | | | - L. Faoro
- Google Research, Mountain View, CA, USA
| | - E. Farhi
- Google Research, Mountain View, CA, USA
| | - R. Fatemi
- Google Research, Mountain View, CA, USA
| | - L. Flores
- Google Research, Mountain View, CA, USA
| | - E. Forati
- Google Research, Mountain View, CA, USA
| | | | - W. Giang
- Google Research, Mountain View, CA, USA
| | - C. Gidney
- Google Research, Mountain View, CA, USA
| | - D. Gilboa
- Google Research, Mountain View, CA, USA
| | | | - A. G. Dau
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - S. Hong
- Google Research, Mountain View, CA, USA
| | - T. Huang
- Google Research, Mountain View, CA, USA
| | - A. Huff
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - Z. Jiang
- Google Research, Mountain View, CA, USA
| | - C. Jones
- Google Research, Mountain View, CA, USA
| | - D. Kafri
- Google Research, Mountain View, CA, USA
| | | | | | - S. Kim
- Google Research, Mountain View, CA, USA
| | - A. Y. Kitaev
- Google Research, Mountain View, CA, USA
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA
| | | | | | - A. N. Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P. Laptev
- Google Research, Mountain View, CA, USA
| | - K.-M. Lau
- Google Research, Mountain View, CA, USA
| | - J. Lee
- Google Research, Mountain View, CA, USA
| | - L. Laws
- Google Research, Mountain View, CA, USA
| | - W. Liu
- Google Research, Mountain View, CA, USA
| | | | - O. Martin
- Google Research, Mountain View, CA, USA
| | | | - M. McEwen
- Google Research, Mountain View, CA, USA
- Department of Physics, University of California, Santa Barbara, CA, USA
| | | | | | | | | | - A. Morvan
- Google Research, Mountain View, CA, USA
| | - E. Mount
- Google Research, Mountain View, CA, USA
| | | | - O. Naaman
- Google Research, Mountain View, CA, USA
| | - M. Neeley
- Google Research, Mountain View, CA, USA
| | - C. Neill
- Google Research, Mountain View, CA, USA
| | - M. Newman
- Google Research, Mountain View, CA, USA
| | | | | | | | - R. Potter
- Google Research, Mountain View, CA, USA
| | | | | | - N. Saei
- Google Research, Mountain View, CA, USA
| | - D. Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - D. Strain
- Google Research, Mountain View, CA, USA
| | - Y. Su
- Google Research, Mountain View, CA, USA
| | - M. Szalay
- Google Research, Mountain View, CA, USA
| | - G. Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T. White
- Google Research, Mountain View, CA, USA
| | - Z. Yao
- Google Research, Mountain View, CA, USA
| | - P. Yeh
- Google Research, Mountain View, CA, USA
| | - J. Yoo
- Google Research, Mountain View, CA, USA
| | | | - Y. Zhang
- Google Research, Mountain View, CA, USA
| | - N. Zhu
- Google Research, Mountain View, CA, USA
| | - H. Neven
- Google Research, Mountain View, CA, USA
| | - D. Bacon
- Google Research, Mountain View, CA, USA
| | - J. Hilton
- Google Research, Mountain View, CA, USA
| | - E. Lucero
- Google Research, Mountain View, CA, USA
| | | | - S. Boixo
- Google Research, Mountain View, CA, USA
| | | | - Y. Chen
- Google Research, Mountain View, CA, USA
| | - J. Kelly
- Google Research, Mountain View, CA, USA
| | | | - D. A. Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
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10
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Djonov V, Fernandez-Palomo C, Trappetti V, Fazzari J, Martin O. FLASH Modalities Track (Oral Presentations) SYNCHROTRON MICROBEAM RADIATION: FLASH AND SPATIAL FRACTIONATION, THE BEST OF BOTH WORLDS. Phys Med 2022. [DOI: 10.1016/s1120-1797(22)01493-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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11
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Fernandez-Palomo C, Pellicioli P, Fazzari J, Trappetti V, Mothersill C, Seymour C, Martin O, Djonov V. INCREASE IN THE SIZE OF THE SURVIVAL CURVE SHOULDER WITH INCREASING DOSE-RATES: FLASH EFFECT ON CELL SURVIVAL. Phys Med 2022. [DOI: 10.1016/s1120-1797(22)01659-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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12
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Satzinger KJ, Liu YJ, Smith A, Knapp C, Newman M, Jones C, Chen Z, Quintana C, Mi X, Dunsworth A, Gidney C, Aleiner I, Arute F, Arya K, Atalaya J, Babbush R, Bardin JC, Barends R, Basso J, Bengtsson A, Bilmes A, Broughton M, Buckley BB, Buell DA, Burkett B, Bushnell N, Chiaro B, Collins R, Courtney W, Demura S, Derk AR, Eppens D, Erickson C, Faoro L, Farhi E, Fowler AG, Foxen B, Giustina M, Greene A, Gross JA, Harrigan MP, Harrington SD, Hilton J, Hong S, Huang T, Huggins WJ, Ioffe LB, Isakov SV, Jeffrey E, Jiang Z, Kafri D, Kechedzhi K, Khattar T, Kim S, Klimov PV, Korotkov AN, Kostritsa F, Landhuis D, Laptev P, Locharla A, Lucero E, Martin O, McClean JR, McEwen M, Miao KC, Mohseni M, Montazeri S, Mruczkiewicz W, Mutus J, Naaman O, Neeley M, Neill C, Niu MY, O'Brien TE, Opremcak A, Pató B, Petukhov A, Rubin NC, Sank D, Shvarts V, Strain D, Szalay M, Villalonga B, White TC, Yao Z, Yeh P, Yoo J, Zalcman A, Neven H, Boixo S, Megrant A, Chen Y, Kelly J, Smelyanskiy V, Kitaev A, Knap M, Pollmann F, Roushan P. Realizing topologically ordered states on a quantum processor. Science 2021; 374:1237-1241. [PMID: 34855491 DOI: 10.1126/science.abi8378] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
[Figure: see text].
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Affiliation(s)
| | - Y-J Liu
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany
| | - A Smith
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, UK.,Centre for the Mathematics and Theoretical Physics of Quantum Non-Equilibrium Systems, University of Nottingham, Nottingham NG7 2RD, UK
| | - C Knapp
- Department of Physics and Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA.,Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, USA
| | - M Newman
- Google Quantum AI, Mountain View, CA, USA
| | - C Jones
- Google Quantum AI, Mountain View, CA, USA
| | - Z Chen
- Google Quantum AI, Mountain View, CA, USA
| | - C Quintana
- Google Quantum AI, Mountain View, CA, USA
| | - X Mi
- Google Quantum AI, Mountain View, CA, USA
| | | | - C Gidney
- Google Quantum AI, Mountain View, CA, USA
| | - I Aleiner
- Google Quantum AI, Mountain View, CA, USA
| | - F Arute
- Google Quantum AI, Mountain View, CA, USA
| | - K Arya
- Google Quantum AI, Mountain View, CA, USA
| | - J Atalaya
- Google Quantum AI, Mountain View, CA, USA
| | - R Babbush
- Google Quantum AI, Mountain View, CA, USA
| | - J C Bardin
- Google Quantum AI, Mountain View, CA, USA.,Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - R Barends
- Google Quantum AI, Mountain View, CA, USA
| | - J Basso
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Bilmes
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Quantum AI, Mountain View, CA, USA
| | - B Burkett
- Google Quantum AI, Mountain View, CA, USA
| | - N Bushnell
- Google Quantum AI, Mountain View, CA, USA
| | - B Chiaro
- Google Quantum AI, Mountain View, CA, USA
| | - R Collins
- Google Quantum AI, Mountain View, CA, USA
| | - W Courtney
- Google Quantum AI, Mountain View, CA, USA
| | - S Demura
- Google Quantum AI, Mountain View, CA, USA
| | - A R Derk
- Google Quantum AI, Mountain View, CA, USA
| | - D Eppens
- Google Quantum AI, Mountain View, CA, USA
| | - C Erickson
- Google Quantum AI, Mountain View, CA, USA
| | - L Faoro
- Laboratoire de Physique Theorique et Hautes Energies, Sorbonne Université, 75005 Paris, France
| | - E Farhi
- Google Quantum AI, Mountain View, CA, USA
| | - A G Fowler
- Google Quantum AI, Mountain View, CA, USA
| | - B Foxen
- Google Quantum AI, Mountain View, CA, USA
| | - M Giustina
- Google Quantum AI, Mountain View, CA, USA
| | - A Greene
- Google Quantum AI, Mountain View, CA, USA.,Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - J A Gross
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - J Hilton
- Google Quantum AI, Mountain View, CA, USA
| | - S Hong
- Google Quantum AI, Mountain View, CA, USA
| | - T Huang
- Google Quantum AI, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Quantum AI, Mountain View, CA, USA
| | - S V Isakov
- Google Quantum AI, Mountain View, CA, USA
| | - E Jeffrey
- Google Quantum AI, Mountain View, CA, USA
| | - Z Jiang
- Google Quantum AI, Mountain View, CA, USA
| | - D Kafri
- Google Quantum AI, Mountain View, CA, USA
| | | | - T Khattar
- Google Quantum AI, Mountain View, CA, USA
| | - S Kim
- Google Quantum AI, Mountain View, CA, USA
| | - P V Klimov
- Google Quantum AI, Mountain View, CA, USA
| | - A N Korotkov
- Google Quantum AI, Mountain View, CA, USA.,Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | - D Landhuis
- Google Quantum AI, Mountain View, CA, USA
| | - P Laptev
- Google Quantum AI, Mountain View, CA, USA
| | - A Locharla
- Google Quantum AI, Mountain View, CA, USA
| | - E Lucero
- Google Quantum AI, Mountain View, CA, USA
| | - O Martin
- Google Quantum AI, Mountain View, CA, USA
| | | | - M McEwen
- Google Quantum AI, Mountain View, CA, USA.,Department of Physics, University of California, Santa Barbara, CA, USA
| | - K C Miao
- Google Quantum AI, Mountain View, CA, USA
| | - M Mohseni
- Google Quantum AI, Mountain View, CA, USA
| | | | | | - J Mutus
- Google Quantum AI, Mountain View, CA, USA
| | - O Naaman
- Google Quantum AI, Mountain View, CA, USA
| | - M Neeley
- Google Quantum AI, Mountain View, CA, USA
| | - C Neill
- Google Quantum AI, Mountain View, CA, USA
| | - M Y Niu
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Opremcak
- Google Quantum AI, Mountain View, CA, USA
| | - B Pató
- Google Quantum AI, Mountain View, CA, USA
| | - A Petukhov
- Google Quantum AI, Mountain View, CA, USA
| | - N C Rubin
- Google Quantum AI, Mountain View, CA, USA
| | - D Sank
- Google Quantum AI, Mountain View, CA, USA
| | - V Shvarts
- Google Quantum AI, Mountain View, CA, USA
| | - D Strain
- Google Quantum AI, Mountain View, CA, USA
| | - M Szalay
- Google Quantum AI, Mountain View, CA, USA
| | | | - T C White
- Google Quantum AI, Mountain View, CA, USA
| | - Z Yao
- Google Quantum AI, Mountain View, CA, USA
| | - P Yeh
- Google Quantum AI, Mountain View, CA, USA
| | - J Yoo
- Google Quantum AI, Mountain View, CA, USA
| | - A Zalcman
- Google Quantum AI, Mountain View, CA, USA
| | - H Neven
- Google Quantum AI, Mountain View, CA, USA
| | - S Boixo
- Google Quantum AI, Mountain View, CA, USA
| | - A Megrant
- Google Quantum AI, Mountain View, CA, USA
| | - Y Chen
- Google Quantum AI, Mountain View, CA, USA
| | - J Kelly
- Google Quantum AI, Mountain View, CA, USA
| | | | - A Kitaev
- Google Quantum AI, Mountain View, CA, USA.,Department of Physics and Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA, USA.,Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, USA
| | - M Knap
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany.,Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany
| | - F Pollmann
- Department of Physics, Technical University of Munich, 85748 Garching, Germany.,Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, 80799 München, Germany
| | - P Roushan
- Google Quantum AI, Mountain View, CA, USA
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13
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Fernandez C, Trappetti V, Fazzari J, Martin O, Djonov V. OC-0064 Microbeam radiosurgery enhances drug delivery across the vascular wall: results from 2 animal models. Radiother Oncol 2021. [DOI: 10.1016/s0167-8140(21)06758-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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14
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Djonov V, Fernandez C, Trappetti V, Fazzari J, Martin O. OC-0507 Microbeams excellent tumour control and high normal tissue tolerance: limitations and perspectives. Radiother Oncol 2021. [DOI: 10.1016/s0167-8140(21)06933-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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15
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Tandjaoui-Lambiotte Y, Gonzalez F, Boubaya M, Freynet O, Clec H C, Bonnet N, Van Der Meersch G, Oziel J, Huang C, Uzunhan Y, Brillet PY, Poirson F, Martin O, Ahmed P, Ebstein N, Karoubi P, Gaudry S, Nunes H, Cohen Y. Two-year follow-up of 196 interstitial lung disease patients after ICU stay. Int J Tuberc Lung Dis 2021; 25:199-205. [PMID: 33688808 DOI: 10.5588/ijtld.20.0706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE: Interstitial lung diseases (ILDs) are associated with poor prognosis in the intensive care unit (ICU). We aimed to assess factors associated with hospital mortality in ILD patients admitted to the ICU and to investigate long-term outcome.MATERIAL AND METHODS: This was a retrospective study in a teaching hospital specialised in ILD management. Patients with ILD who were hospitalised in the ICU between 2000 and 2014 were included. Independent predictors of hospital mortality were identified using logistic regression.RESULTS: A total of 196 ILD patients were admitted to the ICU during the study period. Overall hospital mortality was 55%. Two years after ICU admission, 70 (36%) patients were still alive. Of the 196 patients, 108 (55%) required invasive mechanical ventilation, of whom 21 (20%) were discharged alive from hospital. Acute exacerbation of ILD and multi-organ failure were highly associated with hospital mortality (OR 5.4, 95% CI 1.9-15.5 and OR 12.6, 95% CI 4.9-32.5, respectively).CONCLUSION: Hospital mortality among ILD patients hospitalised in the ICU was high, but even where invasive mechanical ventilation was required, a substantial number of patients were discharged alive from hospital. Multi-organ failure could lead to major ethical concerns.
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Affiliation(s)
- Y Tandjaoui-Lambiotte
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Institut national de la santé et de la recherche médicale (INSERM) Hypoxie & Poumon, Bobigny
| | - F Gonzalez
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - M Boubaya
- Unité de Recherche Clinique, Hôpital Avicenne, Bobigny
| | - O Freynet
- Service de Pneumologie, Hôpital Avicenne, Bobigny
| | - C Clec H
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - N Bonnet
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris
| | - G Van Der Meersch
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - J Oziel
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - C Huang
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - Y Uzunhan
- Institut national de la santé et de la recherche médicale (INSERM) Hypoxie & Poumon, Bobigny, Service de Pneumologie, Hôpital Avicenne, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris
| | - P-Y Brillet
- Université Paris XIII, Sorbonne Paris Cité, Paris, Service de Radiologie, Hôpital Avicenne, Bobigny
| | - F Poirson
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - O Martin
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris
| | - P Ahmed
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - N Ebstein
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris
| | - P Karoubi
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny
| | - S Gaudry
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris, Unité mixte de Recherche S1155, Remodeling and Repair of Renal Tissue, INSERM, Hôpital Tenon, F-75020, Paris
| | - H Nunes
- Institut national de la santé et de la recherche médicale (INSERM) Hypoxie & Poumon, Bobigny, Service de Pneumologie, Hôpital Avicenne, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris
| | - Y Cohen
- Service de Réanimation Médico-Chirurgicale, Hôpital Avicenne, Assistance Publique-Hôpitaux de Paris, Bobigny, Université Paris XIII, Sorbonne Paris Cité, Paris, Unité 942, F-75010, INSERM, Paris, France
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16
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Dubowitz JA, Cata JP, De Silva AP, Braat S, Shan D, Yee K, Hollande F, Martin O, Sloan EK, Riedel B. Volatile anaesthesia and peri-operative outcomes related to cancer: a feasibility and pilot study for a large randomised control trial. Anaesthesia 2021; 76:1198-1206. [PMID: 33440019 DOI: 10.1111/anae.15354] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2020] [Indexed: 12/14/2022]
Abstract
Published data suggest that the type of general anaesthesia used during surgical resection for cancer may impact on patient long-term outcome. However, robust prospective clinical evidence is essential to guide a change in clinical practice. We explored the feasibility of conducting a randomised controlled trial to investigate the impact of total intravenous anaesthesia with propofol vs. inhalational volatile anaesthesia on postoperative outcomes of patients undergoing major cancer surgery. We undertook a randomised, double-blind feasibility and pilot study of propofol total intravenous anaesthesia or volatile-based maintenance anaesthesia during cancer resection surgery at three tertiary hospitals in Australia and the USA. Patients were randomly allocated to receive propofol total intravenous anaesthesia or volatile-based maintenance anaesthesia. Primary outcomes for this study were successful recruitment to the study and successful delivery of the assigned anaesthetic treatment as per randomisation arm. Of the 217 eligible patients approached, 146 were recruited, a recruitment rate of 67.3% (95%CI 60.6-73.5%). One hundred and forty-five patients adhered to the randomised treatment arm, 99.3% (95%CI 96.2-100%). Intra-operative patient characteristics and postoperative complications were comparable between the two intervention groups. This feasibility and pilot study supports the viability of the protocol for a large, randomised controlled trial to investigate the effect of anaesthesia technique on postoperative cancer outcomes. The volatile anaesthesia and peri-operative outcomes related to cancer (VAPOR-C) study that is planned to follow this feasibility study is an international, multicentre trial with the aim of providing evidence-based guidelines for the anaesthetic management of patients undergoing major cancer surgery.
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Affiliation(s)
- J A Dubowitz
- Department of Anaesthesia, Peri-operative and Pain Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - J P Cata
- Department of Anesthesiology and Peri-operative Medicine, Division of Anesthesiology and Critical Care, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - A P De Silva
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Melbourne, Australia
| | - S Braat
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Melbourne, Australia
| | - D Shan
- Department of Anaesthesia, Peri-operative and Pain Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - K Yee
- Department of Anaesthesia, Peri-operative and Pain Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - F Hollande
- Department of Clinical Pathology and University of Melbourne Centre for Cancer Research, Melbourne, Australia
| | - O Martin
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - E K Sloan
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Parkville, Australia
| | - B Riedel
- Department of Anaesthesia, Peri-operative and Pain Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia
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Ben Abdelkrim A, Puillet L, Gomes P, Martin O. Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming. Animal 2020; 15:100074. [PMID: 33515999 DOI: 10.1016/j.animal.2020.100074] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 09/01/2020] [Accepted: 09/08/2020] [Indexed: 11/29/2022] Open
Abstract
In the context of dairy farming, ruminant females often face challenges inducing perturbations that affect their performance and welfare. A key issue is how to assess the effect of perturbations and provide metrics to quantify how animals cope with their environment. Milk production dynamics are good candidates to address this issue: i) they are easily accessible, ii) overall dynamics throughout lactation process are well described and iii) perturbations are visible through milk losses. In this study, a perturbed lactation model (PLM) with explicit representation of perturbations was developed. The model combines two components: i) the unperturbed lactation model that describes a theoretical lactation curve, assumed to reflect female production potential and ii) the perturbation model that describes all the deviations from the unperturbed lactation model with four parameters: starting date, intensity and shape (collapse and recovery). To illustrate the use of the PLM as a phenotyping tool, it was fitted on a data set of 319 complete lactations from 181 individual dairy goats. A total of 2 354 perturbations were detected, with an average of 7.40 perturbations per lactation. Loss of milk production for the whole lactation due to perturbations varied between 2 and 19% of the milk production predicted by the unperturbed lactation model. The number of perturbations was not the major factor explaining the loss of milk production, suggesting that there are different types of animal response to challenges. By incorporating explicit representation of perturbations in a lactation model, it was possible to determine for each female the potential milk production, characteristics of each perturbation and milk losses induced by perturbations. Further, it was possible to compare animals and analyze individual variability. The indicators produced by the PLM are likely to be useful to move from raw data to decision support tools in dairy production.
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Affiliation(s)
- A Ben Abdelkrim
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 75005 Paris, France; Université Paris-Saclay, INRAE, AgroParisTech, UMRGABI, 78350 Jouy-en-Josas, France.
| | - L Puillet
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 75005 Paris, France
| | - P Gomes
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 75005 Paris, France; NEOVIA, 56250 Saint-Nolff, France
| | - O Martin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR Modélisation Systémique Appliquée aux Ruminants, 75005 Paris, France
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18
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Ben Abdelkrim A, Tribout T, Martin O, Boichard D, Ducrocq V, Friggens NC. Exploring simultaneous perturbation profiles in milk yield and body weight reveals a diversity of animal responses and new opportunities to identify resilience proxies. J Dairy Sci 2020; 104:459-470. [PMID: 33162073 DOI: 10.3168/jds.2020-18537] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 08/27/2020] [Indexed: 12/12/2022]
Abstract
Livestock husbandry aims to manage the environment in which animals are reared to enable them to express their production potential. However, animals are often confronted with perturbations that affect their performance. Evaluating effects of these perturbations on animal performance could provide metrics to quantify and understand how animals cope with their environment, and therefore to better manage them. Body weight (BW) and milk yield (MY) dynamics over lactation may be used for this purpose. The goal of this study was to estimate an unperturbed performance trajectory using a differential smoothing approach on both MY and BW time series, and then to identify the perturbations and extract their phenotypic features. Daily MY and BW records from 490 primiparous Holstein cows from 33 commercial French herds were used. From the fitting procedure, estimated unperturbed performance trajectories of BW and MY were clustered into 3 groups. After the fitting procedure, 1,754 deviations were detected in the MY time series and 964 were detected in the BW time series across all cows. Overall, 425 of these deviations were detected during the same period (±10 d) in both MY and BW time series, 76 of which started at the same time. Results suggest that combining various individual dynamic measures and revealing the relationship that exists between them could be of great value in obtaining reliable estimates of resilience components in large populations.
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Affiliation(s)
- A Ben Abdelkrim
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France; Université Paris-Saclay, INRAE, AgroParisTech, UMR MoSAR, 75005 Paris, France.
| | - T Tribout
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France
| | - O Martin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR MoSAR, 75005 Paris, France
| | - D Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France
| | - V Ducrocq
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France
| | - N C Friggens
- Université Paris-Saclay, INRAE, AgroParisTech, UMR MoSAR, 75005 Paris, France
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Khanafer N, Bennia S, Martin-Gaujard G, Juillard L, Rimmelé T, Argaud L, Martin O, Cassier P, Vandenesh F, Vanhems P. Facteurs associés à la colonisation asymptomatique par Clostridioides difficile à l’admission : étude de cohorte prospective dans un centre hospitalo-universitaire. Med Mal Infect 2020. [DOI: 10.1016/j.medmal.2020.06.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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20
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Denis C, Lebarbier E, Lévy‐Leduc C, Martin O, Sansonnet L. A novel regularized approach for functional data clustering: an application to milking kinetics in dairy goats. J R Stat Soc Ser C Appl Stat 2020. [DOI: 10.1111/rssc.12404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- C. Denis
- AgroParisTech Institut National de la Recherche Agronomique Paris France
- Université Paris‐Saclay Paris France
- Université Paris‐Est Champs‐sur‐Marne France
| | - E. Lebarbier
- AgroParisTech Institut National de la Recherche Agronomique Paris France
- Université Paris‐Saclay Paris France
| | - C. Lévy‐Leduc
- AgroParisTech Institut National de la Recherche Agronomique Paris France
- Université Paris‐Saclay Paris France
| | - O. Martin
- AgroParisTech Institut National de la Recherche Agronomique Paris France
- Université Paris‐Saclay Paris France
| | - L. Sansonnet
- AgroParisTech Institut National de la Recherche Agronomique Paris France
- Université Paris‐Saclay Paris France
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21
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Hall AR, Blakeman JT, Eissa AM, Chapman P, Morales-García AL, Stennett L, Martin O, Giraud E, Dockrell DH, Cameron NR, Wiese M, Yakob L, Rogers ME, Geoghegan M. Glycan–glycan interactions determine Leishmania attachment to the midgut of permissive sand fly vectors. Chem Sci 2020. [DOI: 10.1039/d0sc03298k] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Force spectroscopy was used to measure the adhesion of Leishmania to synthetic mimics of galectins on the sand fly midgut.
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22
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Ullrich T, Arsov C, Quentin M, Laqua N, Klingebiel M, Martin O, Hiester A, Blondin D, Rabenalt R, Albers P, Antoch G, Schimmöller L. Analysis of PI-RADS 4 cases: Management recommendations for negatively biopsied patients. Eur J Radiol 2019; 113:1-6. [PMID: 30927932 DOI: 10.1016/j.ejrad.2019.01.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Revised: 01/23/2019] [Accepted: 01/28/2019] [Indexed: 01/21/2023]
Abstract
PURPOSE To evaluate if subgroups of patients assigned to MRI category PI-RADS 4 regarding clinical and MRI imaging aspects have distinct risks of prostate cancer (PCa) to facilitate adequate clinical management of this population, especially after negative targeted biopsy. METHODS This prospective, IRB approved single center cross-sectional study includes 931 consecutive patients after mp-MRI at 3 T for PCa detection. 193 patients with PI-RADS assessment category 4 received subsequent combined targeted MRI/US fusion-guided and systematic 12-core TRUS-guided biopsy as reference standard and were finally analyzed. The primary endpoint was PCa detection of PI-RADS 4 with MRI subgroup analyses. Secondary endpoints were analyses of clinical data, location of PCa, and detection of targeted biopsy cores. RESULTS PCa was detected in 119 of 193 patients (62%) including clinically significant PCa (csPCa; Gleason score ≥3 + 4 = 7) in 92 patients (48%). MRI subgroup analysis revealed 95% PCa (73% csPCa) in unambiguous PI-RADS 4 index lesions without additional, interfering signs of prostatitis in the peripheral zone or overlaying signs of severe stromal hyperplasia in the transition zone according to PI-RADS v2. Transition zone confined PI-RADS-4-lesions with overlaying signs of stromal hyperplasia showed PCa only in 11% (4% csPCa). Targeted biopsy cores missed the csPCa index lesion in 7% of the patients. PSA density (PSAD) was significantly higher in PCa patients. CONCLUSIONS Small csPCa can reliably be detected with mp-MRI by experienced readers, but can be missed by targeted MR/US fusion biopsy alone. Targeted re-biopsy of unambiguous (peripheral) PI-RADS-4-lesions is recommended; whereas transition zone confined PI-RADS-4-lesions with overlaying signs of stromal hyperplasia might be followed-up by re-MRI primarily.
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Affiliation(s)
- T Ullrich
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - C Arsov
- Department of Urology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - M Quentin
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - N Laqua
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - M Klingebiel
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - O Martin
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - A Hiester
- Department of Urology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - D Blondin
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - R Rabenalt
- Department of Urology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - P Albers
- Department of Urology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - G Antoch
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
| | - L Schimmöller
- Department of Diagnostic and Interventional Radiology, Univ Dusseldorf, Medical Faculty, Moorenstr. 5, D-40225 Dusseldorf, Germany.
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23
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Giraud E, Martin O, Yakob L, Rogers M. Quantifying Leishmania Metacyclic Promastigotes from Individual Sandfly Bites Reveals the Efficiency of Vector Transmission. Commun Biol 2019; 2:84. [PMID: 30854476 PMCID: PMC6395631 DOI: 10.1038/s42003-019-0323-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 01/22/2019] [Indexed: 01/12/2023] Open
Abstract
Predicting how Leishmania will respond to control efforts requires an understanding of their transmission strategy. Using real-time quantitative PCR to quantify infectious metacyclic and non-metacyclic forms in mouse skin from single sandfly bites we show that most transmissions were highly enriched for infectious parasites. However, a quarter of sandflies were capable of transmitting high doses containing more non-infectious promastigotes from the vector's midgut. Mouse infections replicating "high" to "low" quality, low-dose transmissions confirmed clear differences in the pathology of the infection and their onward transmissibility back to sandflies. Borrowing methods originally developed to account for exposure heterogeneity among hosts, we show how these high-dose, low-quality transmitters act as super-spreading vectors, capable of inflating Leishmania transmission potential by as much as six-fold. These results highlight the hidden potential of transmission of mixed Leishmania promastigote stages on disease prevalence and the role of dose heterogeneity as an underlying strategy for efficient transmission.
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Affiliation(s)
- Emilie Giraud
- Department of Immunology and Infection, Faculty of Infectious Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Institut Pasteur, 25-28 rue du Dr Roux 75015, Paris, France
| | - Oihane Martin
- Department of Disease Control, Faculty of Infectious Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Laith Yakob
- Department of Disease Control, Faculty of Infectious Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Matthew Rogers
- Department of Disease Control, Faculty of Infectious Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
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24
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Martin O, Bolzli N, Puértolas B, Pérez-Ramírez J, Riedlberger P. Preparation of highly active phosphated TiO 2catalysts viacontinuous sol–gel synthesis in a microreactor. Catal Sci Technol 2019. [DOI: 10.1039/c8cy02574f] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Highly efficient TiO2based catalysts for biomass conversion were obtained through optimised and well-controlled sol–gel synthesis in a multi-mixer microreactor.
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Affiliation(s)
- O. Martin
- Research Group Chemical Engineering
- Institute of Chemistry and Biotechnology
- ZHAW Zurich University of Applied Sciences
- 8820 Wädenswil
- Switzerland
| | - N. Bolzli
- Research Group Chemical Engineering
- Institute of Chemistry and Biotechnology
- ZHAW Zurich University of Applied Sciences
- 8820 Wädenswil
- Switzerland
| | - B. Puértolas
- Institute for Chemical and Bioengineering
- Department of Chemistry and Applied Biosciences
- ETH Zurich
- 8093 Zurich
- Switzerland
| | - J. Pérez-Ramírez
- Institute for Chemical and Bioengineering
- Department of Chemistry and Applied Biosciences
- ETH Zurich
- 8093 Zurich
- Switzerland
| | - P. Riedlberger
- Research Group Chemical Engineering
- Institute of Chemistry and Biotechnology
- ZHAW Zurich University of Applied Sciences
- 8820 Wädenswil
- Switzerland
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25
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Puillet L, Martin O. A dynamic model as a tool to describe the variability of lifetime body weight trajectories in livestock females. J Anim Sci 2018; 95:4846-4856. [PMID: 29293698 DOI: 10.2527/jas2017.1803] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Until now, the development of precision livestock farming has been largely based on data acquisition automation. The future challenge is to develop interpretative tools to capitalize on high-throughput raw data and to generate benchmarks for phenotypic traits. We developed a dynamic model of female BW that converts BW time series into a vector of biologically meaningful parameters. The model is based on a first submodel that split a female's weight into elementary mass changes related to biological functions: growth (G component), reserves balance (R component), uterine load (U component), and maternal investment (M component). These elementary weight components are linked to the second submodel, which represents the litter developmental stages (oocyte, fetus, neonate, and juvenile) that drive elementary components of dam weight over each reproductive cycle. The so-called GRUM model is based on ordinary differential equations and laws of mass action. Input data are BW measures, age, and litter weight at birth for each parturition. Outputs of the fitting procedure are a vector of parameters related to each GRUM component and indexed by reproductive cycle. We illustrated the potential application of the model with a case study including growth and successive lactations ( = 202) from 45 dairy goats from the Alpine ( = 27) and Saanen ( = 18) breeds. The fitting procedure converged for all individuals, including goats that went through extended lactations. We analyzed the fitted parameters to quantify breed and parity effects over 4 reproductive cycles. We found significant differences between breeds regarding gestation components (fetal growth and reserves balance). We also found significant differences among reproductive cycles for reserves balance. Although these findings are based on a small sample, they illustrate how use the model can be to adapt herd management and implement grouping strategies to account for individual variability.
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26
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Walters L, Martin O, Price J, Sula MM. Expression of receptor tyrosine kinase targets PDGFR-β, VEGFR2 and KIT in canine transitional cell carcinoma. Vet Comp Oncol 2017; 16:E117-E122. [PMID: 28884928 DOI: 10.1111/vco.12344] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 07/10/2017] [Accepted: 08/01/2017] [Indexed: 01/05/2023]
Abstract
Transitional cell carcinoma (TCC) is the most common neoplasia of the canine urinary tract. It tends to be locally invasive and has a moderate metastatic rate. Receptor tyrosine kinases (RTKs) play an important role in promoting cell growth, differentiation and regulation of cell function. RTK inhibitor toceranib phosphate has been used anecdotally to treat TCC. The goal of this study was to evaluate archived normal urinary bladder, TCC and cystitis bladder samples for expression of toceranib phosphate targets: VEGFR2, PDGFR-β and stem cell factor receptor (KIT). A significant number of TCC samples expressed PDGFR-β compared with cystitis and normal bladder samples (P<.0001). While all the tumour samples stained positively for VEGFR2, there was no significant difference between tumour, cystitis and normal bladder samples in intensity scores or staining distribution. Minimal positive staining for KIT was noted in the tumour samples. Based on this proof of target study, further investigation is warranted to determine clinical response of TCC to toceranib phosphate.
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Affiliation(s)
- L Walters
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee
| | - O Martin
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee
| | - J Price
- Knoxville School of Information Sciences, University of Tennessee, Knoxville, Tennessee
| | - M M Sula
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee
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Schröder SL, Martin O, Mlinarić M, Richter M. „Das liegt an jedem selbst“ – Eine qualitative Studie zu Versorgungsungleichheiten aus Patientensicht. Das Gesundheitswesen 2017. [DOI: 10.1055/s-0037-1605762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- SL Schröder
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - O Martin
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - M Mlinarić
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - M Richter
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
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28
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Schröder SL, Fink A, Hoffmann L, Schumann N, Martin O, Richter M. Sozioökonomische Unterschiede in den Wegen zur Diagnostik der koronaren Herzkrankheit – einequalitative Studie aus Patientensicht. Das Gesundheitswesen 2017. [DOI: 10.1055/s-0037-1605663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- SL Schröder
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - A Fink
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - L Hoffmann
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - N Schumann
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - O Martin
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
| | - M Richter
- Martin-Luther-Universität Halle-Wittenberg, Medizinische Fakultät, Institut für Medizinische Soziologie, Halle (Saale)
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29
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Phuong HN, Friggens NC, Martin O, Blavy P, Hayes BJ, Wales WJ, Pryce JE. Evaluating the ability of a lifetime nutrient-partitioning model for simulating the performance of Australian Holstein dairy cows. Anim Prod Sci 2017. [DOI: 10.1071/an16452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The present study determined the ability of a lifetime nutrient-partitioning model to simulate individual genetic potentials of Australian Holstein cows. The model was initially developed in France and has been shown to be able to accurately simulate performance of individual cows from various breeds. Generally, it assumes that the curves of cow performance differ only in terms of scaling, but the dynamic shape is universal. In other words, simulations of genetic variability in performance between cow genotypes can be performed using scaling parameters to simply scale the performance curves up or down. Validation of the model used performance data from 63 lactations of Australian Holstein cows offered lucerne cubes plus grain-based supplement. Individual cow records were used to derive genetic scaling parameters for each animal by calibrating the model to minimise root mean-square errors between observed and fitted values, cow by cow. The model was able to accurately fit the curves of bodyweight, milk fat concentration, milk protein concentration and milk lactose concentration with a high degree of accuracy (relative prediction errors <5%). Daily milk yield and weekly body condition score were satisfactorily predicted, although slight under-predictions of milk yield were identified during the last stage of lactation (relative prediction errors ≈11.1–15.6%). The prediction of feed intake was promising, with the value of relative prediction error of 18.1%. The results also suggest that the current recommendation of energy required for maintenance of pasture-based cows might be under-estimated. In conclusion, this model can be used to simulate genetic variability in the production potential of Australian cows. Thus, it can be used for simulation of consequences of future genetic-selection strategies on lifetime performance and efficiency of individual cows.
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Bibault JE, Pernet A, Mollo V, Gourdon L, Martin O, Giraud P. Empowering patients for radiation therapy safety: Results of the EMPATHY study. Cancer Radiother 2016; 20:790-793. [DOI: 10.1016/j.canrad.2016.06.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 05/26/2016] [Accepted: 06/10/2016] [Indexed: 11/25/2022]
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García-Aparicio L, Blázquez-Gómez E, Vila Santandreu A, Camacho Diaz J, Vila-Cots J, Ramos Cebrian M, de Haro I, Martin O, Tarrado X. Routine delayed voiding cystourethography after initial successful endoscopic treatment with Dextranomer/Hialuronic Acid Copolimer (Dx/HA) of vesicoureteral reflux (VUR). Is it necessary? Actas Urol Esp 2016; 40:635-639. [PMID: 27161091 DOI: 10.1016/j.acuro.2016.02.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Revised: 02/24/2016] [Accepted: 02/25/2016] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Some guidelines recommend an early voiding cystourethrography (VCUG) after endoscopic treatment of vesicoureteral reflux (VUR), but there's no consensus if it's necessary a long-term follow-up in these patients. The aim of our study is analyze if it's necessary a delayed VCUG after initial successful treatment with Dx/HA. MATERIAL AND METHOD We have reviewed all medical charts of patients that underwent Dx/HA treatment from 2006 to 2010. We have selected patients with initial successful treatment and more than 3 years of radiological and clinical follow-up. We have analyzed late clinical and radiological outcomes. RESULTS One hundred and sixty children with 228 refluxing ureters underwent Dx/HA endoscopic treatment with a mean follow-up of 52.13 months. Early VCUG was performed in 215 ureters with an initial successful rate of 84.1%. The group of study was 94/215 ureters with more than 3 years of follow-up with a delayed VCUG. VUR was still resolved in 79,8% of the ureters. Clinical success rate was 91.7%. The incidence of febrile urinary tract infection in those patients with cured VUR and those with a relapsed VUR was 8 and 15%, respectively; but there were no significant differences. We have not found any variable related with relapsed VUR except those ureters that initially received 2 injections (P<.05). CONCLUSION If our objective in the treatment of VUR is to reduce the incidence of febrile urinary tract infection it is not necessary to perform a delayed VCUG even though the long-term radiological outcomes is worse than clinical outcome.
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Gaillard C, Martin O, Blavy P, Friggens N, Sehested J, Phuong H. Prediction of the lifetime productive and reproductive performance of Holstein cows managed for different lactation durations, using a model of lifetime nutrient partitioning. J Dairy Sci 2016; 99:9126-9135. [DOI: 10.3168/jds.2016-11051] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 07/14/2016] [Indexed: 11/19/2022]
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Blavy P, Derks M, Martin O, Höglund J, Friggens N. Overview of progesterone profiles in dairy cows. Theriogenology 2016; 86:1061-1071. [DOI: 10.1016/j.theriogenology.2016.03.037] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Revised: 03/19/2016] [Accepted: 03/23/2016] [Indexed: 10/22/2022]
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Martin O, Rockenbauch K, Kleinert E, Stöbel-Richter Y. [Effectively communicate active listening : Comparison of two concepts]. Nervenarzt 2016; 88:1026-1035. [PMID: 27448178 DOI: 10.1007/s00115-016-0178-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Communication between physicians and patients has a great influence on patient adherence, patient satisfaction and the success of treatment. In this context, patient centered care and emotional support have a high positive impact; however, it is unclear how physicians can be motivated to communicate with patients in an appreciative and empathetic way. The implementation of such behavior requires a multitude of communicative skills. One of them is active listening, which is very important in two respects. On the one hand active listening provides the basis for several conversational contexts as a special communication technique and on the other hand active listening is presented in current textbooks in different ways: as an attitude or as a technique. In light of this, the question arises how active listening should be taught in order to be not only applicable in concrete conversations but also to lead to the highest possible level of patient satisfaction. The aim of this pilot study was to examine some variations in simulated doctor-patient conversations, which are the result of the different approaches to active listening. For this purpose three groups of first semester medical students were recruited, two of which were schooled in active listening in different ways (two groups of six students), i.e. attitude versus technique oriented. The third group (seven students) acted as the control group. In a pre-post design interviews with standardized simulation patients were conducted and subsequently evaluated. The analysis of these interviews was considered from the perspectives of participants and observers as well as the quantitative aspects. This study revealed some interesting tendencies despite its status as a pilot study: in general, the two interventional groups performed significantly better than the control group in which no relevant changes occurred. In a direct comparison, the group in which active listening was taught from an attitude approach achieved better results than the group in which the focus was on the technical aspects of active listening. In the group with active listening schooled as an attitude, the response to the feelings of the standardized simulation patients was significantly better from the perspectives of both participants and observers.
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Affiliation(s)
- O Martin
- Institut für medizinische Soziologie, Martin-Luther-Universität Halle-Wittenberg, Magdeburger Str. 8, 06112, Halle, Deutschland.
| | - K Rockenbauch
- Abteilung für Medizinische Psychologie und Medizinische Soziologie, Department für Psychische Gesundheit, Universitätsklinikum Leipzig AöR, Ph.-Rosenthal-Str. 55, 04103, Leipzig, Deutschland
| | - E Kleinert
- Abteilung für Medizinische Psychologie und Medizinische Soziologie, Department für Psychische Gesundheit, Universitätsklinikum Leipzig AöR, Ph.-Rosenthal-Str. 55, 04103, Leipzig, Deutschland
| | - Y Stöbel-Richter
- Fakultät Management- und Kulturwissenschaften, Hochschule Zittau/Görlitz, Furtstraße 3, 02826, Görlitz, Deutschland
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Abstract
As valpromide is a prodrug of valproic acid (valproate), the clinical presentation of overdoses with either valpromide or valproate sodium is generally considered similar. Whereas plasma peak levels and signs of central nervous system depression occur within a few hours after the acute ingestion of regular-release forms of valproate sodium, delayed toxicity and time to peak levels following valpromide ingestion can be seen as shown by the three reported cases. They were initially considered as mild because patients presented with no or only moderate symptoms and serum valproate levels were below or at therapeutic levels on admission more than 3 hours post-ingestion in two of the three patients. Serum valproate levels were not monitored until marked deterioration more than 10 hours after ingestion. At the time of deterioration, serum valproate was at toxic level in the three reported cases. Therefore, large intake of valpromide should be closely monitored because no or moderate symptoms together with low plasma levels in the first few hours after ingestion do not exclude a subsequent severe intoxication. Despite the usual favourable outcome and the poor correlation between plasma levels and toxic symptoms, patients should not be discharged until plasma levels are documented to remain at low levels for at least 10 hours after the ingestion of valpromide and the patient asymptomatic.
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Affiliation(s)
- C Payen
- Centre Antipoison, 162 Avenue Lacassagne, 69424 Lyon cedex 03, France.
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Lee-Jones L, Wang Q, Bohan S, Martin O, Linton P. Anti-cancer properties of secondary metabolites derived from marine bacteria. Eur J Cancer 2016. [DOI: 10.1016/s0959-8049(16)61517-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Llanes-Acevedo IP, Arcones C, Gálvez R, Martin O, Checa R, Montoya A, Chicharro C, Cruz S, Miró G, Cruz I. DNA sequence analysis suggests that cytb-nd1 PCR-RFLP may not be applicable to sandfly species identification throughout the Mediterranean region. Parasitol Res 2016; 115:1287-95. [PMID: 26755361 PMCID: PMC4759228 DOI: 10.1007/s00436-015-4865-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Accepted: 11/30/2015] [Indexed: 12/04/2022]
Abstract
Molecular methods are increasingly used for both species identification of sandflies and assessment of their population structure. In general, they are based on DNA sequence analysis of targets previously amplified by PCR. However, this approach requires access to DNA sequence facilities, and in some circumstances, it is time-consuming. Though DNA sequencing provides the most reliable information, other downstream PCR applications are explored to assist in species identification. Thus, it has been recently proposed that the amplification of a DNA region encompassing partially both the cytochrome-B (cytb) and the NADH dehydrogenase 1 (nd1) genes followed by RFLP analysis with the restriction enzyme Ase I allows the rapid identification of the most prevalent species of phlebotomine sandflies in the Mediterranean region. In order to confirm the suitability of this method, we collected, processed, and molecularly analyzed a total of 155 sandflies belonging to four species including Phlebotomus ariasi, P. papatasi, P. perniciosus, and Sergentomyia minuta from different regions in Spain. This data set was completed with DNA sequences available at the GenBank for species prevalent in the Mediterranean basin and the Middle East. Additionally, DNA sequences from 13 different phlebotomine species (P. ariasi, P. balcanicus, P. caucasicus, P. chabaudi, P. chadlii, P. longicuspis, P. neglectus, P. papatasi, P. perfiliewi, P. perniciosus, P. riouxi, P. sergenti, and S. minuta), from 19 countries, were added to the data set. Overall, our molecular data revealed that this PCR-RFLP method does not provide a unique and specific profile for each phlebotomine species tested. Intraspecific variability and similar RFLP patterns were frequently observed among the species tested. Our data suggest that this method may not be applicable throughout the Mediterranean region as previously proposed. Other molecular approaches like DNA barcoding or phylogenetic analyses would allow a more precise molecular species identification.
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Affiliation(s)
- Ivonne Pamela Llanes-Acevedo
- Servicio de Parasitología, Centro Nacional de Microbiología, Instituto de Salud Carlos III, World Health Organization Collaborating Center for Leishmaniasis, Ctra. Majadahonda-Pozuelo Km2, Majadahonda, 28220, Madrid, Spain.
| | - Carolina Arcones
- Servicio de Parasitología, Centro Nacional de Microbiología, Instituto de Salud Carlos III, World Health Organization Collaborating Center for Leishmaniasis, Ctra. Majadahonda-Pozuelo Km2, Majadahonda, 28220, Madrid, Spain.
| | - Rosa Gálvez
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040, Madrid, Spain.
| | - Oihane Martin
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040, Madrid, Spain.
| | - Rocío Checa
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040, Madrid, Spain.
| | - Ana Montoya
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040, Madrid, Spain.
| | - Carmen Chicharro
- Servicio de Parasitología, Centro Nacional de Microbiología, Instituto de Salud Carlos III, World Health Organization Collaborating Center for Leishmaniasis, Ctra. Majadahonda-Pozuelo Km2, Majadahonda, 28220, Madrid, Spain.
| | - Susana Cruz
- Servicio de Parasitología, Centro Nacional de Microbiología, Instituto de Salud Carlos III, World Health Organization Collaborating Center for Leishmaniasis, Ctra. Majadahonda-Pozuelo Km2, Majadahonda, 28220, Madrid, Spain.
| | - Guadalupe Miró
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro s/n, 28040, Madrid, Spain.
| | - Israel Cruz
- Neglected Tropical Diseases Programme, Foundation for Innovative New Diagnostics-FIND, Chemin des Mines 9, Campus Biotech, 1202, Geneva, Switzerland.
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Martin O, Rathmann K. Präferenzen und Kompetenzen älterer, multimorbider Patienten (PräKäP) in der Arzt-Patienten-Interaktion: Eine qualitative Untersuchung. Gesundheitswesen 2015. [DOI: 10.1055/s-0035-1563301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Martin O, Fink A. Kommunikative Fertigkeiten mit E-Learning? Gesundheitswesen 2015. [DOI: 10.1055/s-0035-1563122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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García-Aparicio L, Blázquez-Gómez E, Martin O, Krauel L, de Haro I, Rodó J. Bacterial characteristics and clinical significance of ureteral double-J stents in children. Actas Urol Esp 2015; 39:53-6. [PMID: 24954842 DOI: 10.1016/j.acuro.2014.04.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Accepted: 04/14/2014] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To determine the incidence of urinary tract infection in those patients that we have used an ureteral double-J stent as internal diversion after urological procedures. MATERIAL AND METHODS We reviewed all the medical records of patients who had a ureteral double-J stent after a urological procedure from August 2007 to May 2013. We have analyzed the following data: age, gender, type of prophylaxis, incidence of urinary tract infection (UTI), days of internal diversion with double-J stent, surgical procedure, bacterial characteristics, bacterial sensibility to antibiotics and UTI treatment. RESULTS We have used 73 double-J stents as ureteral internal diversion in 67 patients with a mean age of 44.73±57.23. Surgical procedures were 50 laparoscopic Anderson-Hynes pyeloplasties in 49 patients, and 20 high-pressure balloon dilatation of the ureterovesical junction to treat primary obstructive megaureter in 15 patients; and 3 patients with ureterovesical obstruction after endoscopic treatment of vesicoureteral reflux. Forty three stents showed a bacterial colonization in cultures. Pseudomona aeruginosa was present in 9 (20.9%) stents. Only in 12 stents, bacterial colonization was sensible to antibiotic prophylaxis. Stent colonization was higher in boys and younger patients. Four patients had a febrile UTI. Incidence of UTI in younger patients that underwent HBPD of UVJ is higher. CONCLUSION Bacterial colonization is frequent in double-J stents but the incidence of UTI is low. Double-J colonization is higher in younger patients. Patients that underwent HPBD have a higher risk of UTI related with ureteral double J stent.
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Affiliation(s)
- L García-Aparicio
- Sección de Urología Pediátrica, Servicio de Cirugía Pediátrica, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, España.
| | - E Blázquez-Gómez
- Hospital Universitario Virgen Macarena, Universidad de Sevilla, Sevilla, España
| | - O Martin
- Sección de Urología Pediátrica, Servicio de Cirugía Pediátrica, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, España
| | - L Krauel
- Servicio de Cirugía Pediátrica, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, España
| | - I de Haro
- Servicio de Cirugía Pediátrica, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, España
| | - J Rodó
- Sección de Urología Pediátrica, Servicio de Cirugía Pediátrica, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, España
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Phuong H, Martin O, de Boer I, Ingvartsen K, Schmidely P, Friggens N. Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning. J Dairy Sci 2015; 98:618-32. [DOI: 10.3168/jds.2014-8250] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2014] [Accepted: 10/01/2014] [Indexed: 11/19/2022]
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Tabbabi A, Rhim A, Ghrab J, Martin O, Aoun K, Bouratbine A, Ready PD. Phlebotomus (Paraphlebotomus) riouxi: a synonym of Phlebotomus chabaudi without any proven vectorial role in Tunisia and Algeria. Med Vet Entomol 2014; 28 Suppl 1:51-59. [PMID: 25171607 DOI: 10.1111/mve.12067] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Revised: 01/27/2014] [Accepted: 01/30/2014] [Indexed: 06/03/2023]
Abstract
Phlebotomus (Paraphlebotomus) riouxi Depaquit, Léger & Killick-Kendrick (Diptera: Psychodidae) was described as a typological species based on a few morphological characters distinguishing it from Phlebotomus (Paraphlebotomus) chabaudi Croset, Abonnenc & Rioux. The naming of P. riouxi coincided with its incrimination as a rural vector of Leishmania tropica Wright (junior synonym: Leishmania killicki Rioux, Lanotte & Pratlong) in Tataouine governorate, an arid region of southern Tunisia. The current report finds insufficient evidence to incriminate either phlebotomine sandfly as a vector of L. tropica in North Africa. Phlebotomus riouxi was found not to have the characteristics of a phylogenetic or biological species, and therefore it is synonymized with P. chabaudi. Both taxa were recorded together for the first time in Tunisia, in Tataouine, where three of 12 males showed intermediate morphology and both sexes of each taxon were not characterized by specific lineages of the nuclear gene elongation factor-1α or the mitochondrial gene cytochrome b, for which a long 3' terminal fragment is recommended for phlebotomine phylogenetics. This case study indicates that the eco-epidemiology of leishmaniasis should focus more on identifying key components of vectorial transmission that are susceptible to interventions for disease control, rather than on defining sibling species of vectors.
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Affiliation(s)
- A Tabbabi
- Laboratoire de Recherche LR 11-IPT-06 (Parasitoses Médicales, Biotechnologies et Biomolécules), Institut Pasteur de Tunis, Tunis, Tunisia
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Le Bars E, Chaptal T, Martin O, Miravete V, El Kaim Y, Bonafé A, Menjot de Champfleur N. Mise en place d’une plateforme de recherche dans un service hospitalier d’imagerie. J Neuroradiol 2014. [DOI: 10.1016/j.neurad.2014.01.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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García-Aparicio L, Blázquez-Gómez E, Martin O, Palazón P, Manzanares A, García-Smith N, Bejarano M, de Haro I, Ribó JM. Use of high-pressure balloon dilatation of the ureterovesical junction instead of ureteral reimplantation to treat primary obstructive megaureter: is it justified? J Pediatr Urol 2013; 9:1229-33. [PMID: 23796389 DOI: 10.1016/j.jpurol.2013.05.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2012] [Accepted: 05/19/2013] [Indexed: 10/26/2022]
Abstract
OBJECTIVE To compare outcomes between high-pressure balloon dilatation of the ureterovesical junction (UVJ) and ureteral reimplantation with ureteral tapering to treat primary obstructive megaureter (POM). PATIENTS AND METHODS Retrospective review of clinical data from patients who underwent surgical treatment of POM from 2005 to 2010. Patients were divided into two groups: endoscopic treatment (ET) with UVJ dilatation and ureteral reimplantation (UR) with Cohen's or Leadbetter-Politano neoureterocystostomy and Hendren's tapering. Preoperative studies included ultrasound scan (US), voiding cystourethrography, and diuretic isotopic renogram. Outcome parameters were US, differential renal function (DRF), presence of postoperative vesicoureteral reflux, need for secondary reimplantation and complications. RESULTS ET 13 patients with a median age of 7 (4-24) months; UR: 12 patients with a median age of 14 (7-84) months, with no statistical differences in age and gender between groups. Preoperative US parameters were similar. ET: mean diameter of renal pelvis, calices and ureter was 23.5 mm, 13.46 mm and 15.77 mm respectively. UR: mean diameter of renal pelvis, calices and ureter was 22.25 mm, 11.75 mm, and 19.08 mm, respectively. Preoperative DRF was 45.62% and 39.33% for ET and UR, respectively (p > 0.05). Significant improvement of hydroureteronephrosis was observed in 11/13 patients of ET and 11/12 patients of UR (p > 0.05). Postoperative DRF was 42% and 48% for ET and UR, respectively (p > 0.05). Postoperative vesicoureteral reflux was observed in 2 patients of ET and 1 of UR (p > 0.05). Secondary ureteral reimplantation was needed in 3 patients of ET and 2 of UR (p > 0.05). CONCLUSION Endoscopic treatment of POM is as effective as ureteral reimplantation but further randomized clinical trials are needed to support these results.
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Affiliation(s)
- L García-Aparicio
- Pediatric Urology, Pediatric Surgery Dept, Hospital Sant Joan de Déu, University of Barcelona, Spain.
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Douhard F, Friggens N, Tessier J, Martin O, Tichit M, Sauvant D. Characterization of a changing relationship between milk production and liveweight for dairy goats undergoing extended lactation. J Dairy Sci 2013; 96:5698-711. [DOI: 10.3168/jds.2012-6374] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2012] [Accepted: 06/03/2013] [Indexed: 11/19/2022]
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Moutet F, Delon-Martin C, Martin O, Sirigu A, Delaquaize F, Benali H, Masquelet AC. [Functional magnetic resonance imaging. What are the benefits expected in hand surgery?]. ACTA ACUST UNITED AC 2013; 32:121-8. [PMID: 23731670 DOI: 10.1016/j.main.2013.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2013] [Accepted: 04/20/2013] [Indexed: 10/26/2022]
Abstract
Functional MRI (fMRI) allowed considerable advances upon understanding of cerebral functioning. Cortical plasticity, which allows the voluntary command of a restored function by a transferred muscle remains to be investigated in its intimacy. The authors present here the round table held at the 48th annual meeting of the French Society for Surgery of the Hand on December 22nd, 2012. It tries to review the analysis of the phenomenon observed during multiple tendinous transfers for restoration of proximal radial nerve palsy. Were successively approached: 1) Methods of acquisition and analysis of the signals (C. D-M.); 2) Movement reorganization (O.M.); 3) Motor plasticity after hand allograft (A. S.); 4) The potential interest of the fMRI in hand rehabilitation (F. D.); 5) The analysis of cerebral plasticity in general (H. B.). A rather philosophical conclusion opens other fields to f MRI (A.M.).
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Affiliation(s)
- F Moutet
- Clinique de chirurgie plastique de la main et des brûlés, hôpital Albert-Michallon, université Joseph-Fourier (Grenoble I), CHU de Grenoble, 38000 Grenoble, France.
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MacManus M, Jacobs D, Do H, Ball D, Ivashkevich A, Dobrovic A, Martin R, Martin O. Significant Numbers of Irradiated Tumor Cells Enter the Circulation Early During a Course of Fractionated Radiation Therapy for Non-small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2012. [DOI: 10.1016/j.ijrobp.2012.07.1536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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García-Aparicio L, Rodo J, Krauel L, Palazon P, Martin O, Ribó JM. High pressure balloon dilation of the ureterovesical junction--first line approach to treat primary obstructive megaureter? J Urol 2012; 187:1834-8. [PMID: 22425047 DOI: 10.1016/j.juro.2011.12.098] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2011] [Indexed: 11/17/2022]
Abstract
PURPOSE We describe the efficacy of dilation of the ureterovesical junction to treat primary obstructive megaureter. MATERIALS AND METHODS A total of 13 patients with primary obstructive megaureter were treated from May 2008 to December 2010. Of these patients 8 were diagnosed prenatally and the others were diagnosed after a urinary tract infection. Preoperative studies included ultrasonography, voiding cystourethrography despite vesicoureteral reflux and diuretic isotopic renogram (mercaptoacetyltriglycine). With the patient under general anesthesia, high pressure balloon dilation of the ureterovesical junction was performed under direct and fluoroscopic vision until the disappearance of the narrowed ring. A Double-J(®) catheter was positioned, and 2 months later it was withdrawn and the ureterovesical junction was reviewed. A secondary treatment was performed in those in whom the ureterovesical junction was still narrow. Followup was performed with ultrasonography, cystourethrography and isotopic diuretic renography. RESULTS A total of 18 procedures were performed in 13 patients (median age 7 months, range 4 to 24). Median diameter of the distal ureter was 14 mm (range 10 to 26), and median diameter of the renal pelvis and calyx was 27 mm (range 10 to 47) and 12 mm (range 9 to 26), respectively. Significant postoperative improvement of hydroureteronephrosis was observed in 11 of 13 patients and vesicoureteral reflux was found in 2. Only 3 patients needed ureteral reimplantation after endoscopic treatment due to hydroureteronephrosis in 2 and high grade vesicoureteral reflux in 1. CONCLUSIONS High pressure balloon dilation of the ureterovesical junction is effective in treating primary obstructive megaureter, but long-term followup is needed.
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Affiliation(s)
- L García-Aparicio
- Pediatric Urology Unit, Pediatric Surgery Department, Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain.
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Gascuel JD, Payno H, Schmerber S, Martin O. Immersive virtual environment for visuo-vestibular therapy: preliminary results. Stud Health Technol Inform 2012; 181:187-191. [PMID: 22954853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The sense of equilibrium aggregates several interacting cues. On vestibular areflexic patients, vision plays a major role. We developed an immersive therapeutic platform, based on 3D opto-kinetic stimulation that enables to tune the difficulty of the balance task by managing the type of optic flow and its speed. The balance adjustments are recorded by a force plate, quantified by the length of the center of pressure trajectory and detection of disequilibrium corrections (leans, compensation step). Preliminary analysis shows that (i) patients report a strong immersion feeling in the motion flow, triggering intense motor response to "fight against fall"; (ii) the ANOVA factorial design shows a significant effect of flow speed, session number and gaze anchor impact. In conclusion, this study shows that 3D immersive stimulation removes essential limits of traditional opto-kinetic stimulators (limited 2D motions and remaining fixed background cues). Moreover, the immersive optic flow stimulation is an efficient tool to induce balance adaptive reactions in vestibular patients. Hence, such a platform appears to be a powerful therapeutic tool for training and relearning of balance control processes.
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Martin O, Rockenbauch K, Stöbel-Richter Y. Vermittlung von Gesprächsführung im Medizinstudium – Haltungs- oder technikorientiert. Gesundheitswesen 2011. [DOI: 10.1055/s-0031-1283540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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