1
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Zhang ZY, Yang LT, Yue Q, Kang KJ, Li YJ, An HP, C G, Chang JP, Chen YH, Cheng JP, Dai WH, Deng Z, Fang CH, Geng XP, Gong H, Guo QJ, Guo T, Guo XY, He L, He SM, Hu JW, Huang HX, Huang TC, Jiang L, Karmakar S, Li HB, Li HY, Li JM, Li J, Li QY, Li RMJ, Li XQ, Li YL, Liang YF, Liao B, Lin FK, Lin ST, Liu JX, Liu SK, Liu YD, Liu Y, Liu YY, Ma H, Mao YC, Nie QY, Ning JH, Pan H, Qi NC, Ren J, Ruan XC, Singh MK, Sun TX, Tang CJ, Tian Y, Wang GF, Wang JZ, Wang L, Wang Q, Wang YF, Wang YX, Wong HT, Wu SY, Wu YC, Xing HY, Xu R, Xu Y, Xue T, Yan YL, Yi N, Yu CX, Yu HJ, Yue JF, Zeng M, Zeng Z, Zhang BT, Zhang FS, Zhang L, Zhang ZH, Zhao JZ, Zhao KK, Zhao MG, Zhou JF, Zhou ZY, Zhu JJ. Experimental Limits on Solar Reflected Dark Matter with a New Approach on Accelerated-Dark-Matter-Electron Analysis in Semiconductors. Phys Rev Lett 2024; 132:171001. [PMID: 38728703 DOI: 10.1103/physrevlett.132.171001] [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] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/22/2024] [Accepted: 03/19/2024] [Indexed: 05/12/2024]
Abstract
Recently a dark matter-electron (DM-electron) paradigm has drawn much attention. Models beyond the standard halo model describing DM accelerated by high energy celestial bodies are under intense examination as well. In this Letter, a velocity components analysis (VCA) method dedicated to swift analysis of accelerated DM-electron interactions via semiconductor detectors is proposed and the first HPGe detector-based accelerated DM-electron analysis is realized. Utilizing the method, the first germanium based constraint on sub-GeV solar reflected DM-electron interaction is presented with the 205.4 kg·day dataset from the CDEX-10 experiment. In the heavy mediator scenario, our result excels in the mass range of 5-15 keV/c^{2}, achieving a 3 orders of magnitude improvement comparing with previous semiconductor experiments. In the light mediator scenario, the strongest laboratory constraint for DM lighter than 0.1 MeV/c^{2} is presented. The result proves the feasibility and demonstrates the vast potential of the VCA technique in future accelerated DM-electron analyses with semiconductor detectors.
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Affiliation(s)
- Z Y Zhang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - L T Yang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Q Yue
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - K J Kang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y J Li
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - H P An
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
- Department of Physics, Tsinghua University, Beijing 100084
| | - Greeshma C
- Institute of Physics, Academia Sinica, Taipei 11529
| | | | - Y H Chen
- YaLong River Hydropower Development Company, Chengdu 610051
| | - J P Cheng
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - W H Dai
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Z Deng
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - C H Fang
- College of Physics, Sichuan University, Chengdu 610065
| | - X P Geng
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - H Gong
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Q J Guo
- School of Physics, Peking University, Beijing 100871
| | - T Guo
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - X Y Guo
- YaLong River Hydropower Development Company, Chengdu 610051
| | - L He
- NUCTECH Company, Beijing 100084
| | - S M He
- YaLong River Hydropower Development Company, Chengdu 610051
| | - J W Hu
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - H X Huang
- Department of Nuclear Physics, China Institute of Atomic Energy, Beijing 102413
| | - T C Huang
- Sino-French Institute of Nuclear and Technology, Sun Yat-sen University, Zhuhai 519082
| | - L Jiang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - S Karmakar
- Institute of Physics, Academia Sinica, Taipei 11529
| | - H B Li
- Institute of Physics, Academia Sinica, Taipei 11529
| | - H Y Li
- College of Physics, Sichuan University, Chengdu 610065
| | - J M Li
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - J Li
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Q Y Li
- College of Physics, Sichuan University, Chengdu 610065
| | - R M J Li
- College of Physics, Sichuan University, Chengdu 610065
| | - X Q Li
- School of Physics, Nankai University, Tianjin 300071
| | - Y L Li
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y F Liang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - B Liao
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - F K Lin
- Institute of Physics, Academia Sinica, Taipei 11529
| | - S T Lin
- College of Physics, Sichuan University, Chengdu 610065
| | - J X Liu
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - S K Liu
- College of Physics, Sichuan University, Chengdu 610065
| | - Y D Liu
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - Y Liu
- College of Physics, Sichuan University, Chengdu 610065
| | - Y Y Liu
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - H Ma
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y C Mao
- School of Physics, Peking University, Beijing 100871
| | - Q Y Nie
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - J H Ning
- YaLong River Hydropower Development Company, Chengdu 610051
| | - H Pan
- NUCTECH Company, Beijing 100084
| | - N C Qi
- YaLong River Hydropower Development Company, Chengdu 610051
| | - J Ren
- Department of Nuclear Physics, China Institute of Atomic Energy, Beijing 102413
| | - X C Ruan
- Department of Nuclear Physics, China Institute of Atomic Energy, Beijing 102413
| | - M K Singh
- Institute of Physics, Academia Sinica, Taipei 11529
- Department of Physics, Banaras Hindu University, Varanasi 221005
| | - T X Sun
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - C J Tang
- College of Physics, Sichuan University, Chengdu 610065
| | - Y Tian
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - G F Wang
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - J Z Wang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - L Wang
- Department of Physics, Beijing Normal University, Beijing 100875
| | - Q Wang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
- Department of Physics, Tsinghua University, Beijing 100084
| | - Y F Wang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y X Wang
- School of Physics, Peking University, Beijing 100871
| | - H T Wong
- Institute of Physics, Academia Sinica, Taipei 11529
| | - S Y Wu
- YaLong River Hydropower Development Company, Chengdu 610051
| | - Y C Wu
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - H Y Xing
- College of Physics, Sichuan University, Chengdu 610065
| | - R Xu
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y Xu
- School of Physics, Nankai University, Tianjin 300071
| | - T Xue
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Y L Yan
- College of Physics, Sichuan University, Chengdu 610065
| | - N Yi
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - C X Yu
- School of Physics, Nankai University, Tianjin 300071
| | - H J Yu
- NUCTECH Company, Beijing 100084
| | - J F Yue
- YaLong River Hydropower Development Company, Chengdu 610051
| | - M Zeng
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - Z Zeng
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - B T Zhang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - F S Zhang
- College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875
| | - L Zhang
- College of Physics, Sichuan University, Chengdu 610065
| | - Z H Zhang
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - J Z Zhao
- Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing 100084
| | - K K Zhao
- College of Physics, Sichuan University, Chengdu 610065
| | - M G Zhao
- School of Physics, Nankai University, Tianjin 300071
| | - J F Zhou
- YaLong River Hydropower Development Company, Chengdu 610051
| | - Z Y Zhou
- Department of Nuclear Physics, China Institute of Atomic Energy, Beijing 102413
| | - J J Zhu
- College of Physics, Sichuan University, Chengdu 610065
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Cao Y, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE. Phys Rev Lett 2024; 132:151801. [PMID: 38683006 DOI: 10.1103/physrevlett.132.151801] [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] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 01/04/2024] [Accepted: 03/13/2024] [Indexed: 05/01/2024]
Abstract
We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41} cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois, 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois, 60637, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- University of Chicago, Chicago, Illinois, 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois, 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois, 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | | | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois, 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois, 60637, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Liu HF, Feng QL, Huang RW, Yuan TY, Sui MZ, Li PL, Liu K, Li F, Li Y, Jiang L, Fu HM. [Clinical characteristics of hospitalized children with respiratory syncytial virus infection and risk prediction of severe illness during the post-COVID-19 era in Kunming]. Zhonghua Er Ke Za Zhi 2024; 62:323-330. [PMID: 38527502 DOI: 10.3760/cma.j.cn112140-20240219-00109] [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] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Objective: To compare the epidemiological and clinical characteristics of hospitalized children with respiratory syncytial virus (RSV) infection in Kunming among the pre-and post-COVID-19 era, and to establish a prediction model for severe RSV infection in children during the post-COVID-19 period. Methods: This was a retrospective study. Clinical and laboratory data were collected from 959 children hospitalized with RSV infection in the Department of Pulmonary and Critical Care Medicine at Kunming Children's Hospital during January to December 2019 and January to December 2023. Patients admitted in 2019 were defined as the pre-COVID-19 group, while those admitted in 2023 were classified as the post-COVID-19 group. Epidemiological and clinical characteristics were compared between the two groups. Subsequently, comparison of the clinical severity among the two groups was performed based on propensity score matching (PSM). Furthermore, the subjects in the post-COVID-19 group were divided into severe and non-severe groups based on clinical severity. Chi-square test and Mann-Whitney U test were used for pairwise comparison between groups, and multivariate Logistic regression was applied for the identification of independent risk factors and construction of the prediction model. The receiver operating characteristic (ROC) curve and calibration curve were employed to evaluate the predictive performance of this model. Results: Among the 959 children hospitalized with RSV infection, there were 555 males and 404 females, with an onset age of 15.4 (7.3, 28.5) months. Of which, there were 331 cases in the pre-COVID-19 group and 628 cases in the post-COVID-19 group. The peak period of RSV hospitalization in the post-COVID-19 group were from May to October 2023, and the monthly number of inpatients for each of these months were as follows: 72 cases (11.5%), 98 cases (15.6%), 128 cases (20.4%), 101 cases (16.1%), 65 cases (10.4%), and 61 cases (9.7%), respectively. After PSM for general data, 267 cases were matched in each group. The proportion of wheezing in the post-COVID-19 group was lower than that in the pre-COVID-19 group (109 cases (40.8%) vs. 161 cases (60.3%), χ2=20.26, P<0.001), while the incidences of fever, tachypnea, seizures, severe case, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein and interleukin-6 levels were all higher than those in the pre-COVID-19 group (146 cases (54.7%) vs. 119 cases (44.6%), 117 cases (43.8%) vs. 89 cases (33.3%), 37 cases (13.9%) vs. 14 cases (5.2%), 69 cases (25.8%) vs. 45 cases (16.9%), 3.6 (1.9, 6.4) vs. 2.3 (1.8, 4.6), 9.9 (7.1, 15.2) vs. 7.8 (4.5, 13.9) mg/L, 20.5 (15.7, 30.4) vs. 17.2 (11.0, 26.9) ng/L, χ2=5.46, 6.36, 11.47, 6.42, Z=4.13, 3.06, 2.96, all P<0.05). There were 252 cases and 107 cases with co-infection in the post-and pre-COVID-19 groups, respectively. The proportion of triple and quadruple infection in the post-COVID-19 group was higher than that in the pre-COVID-19 group (59 cases (23.4%) vs. 13 cases (12.1%), 30 cases (11.9%) vs. 5 cases (4.7%), χ2=5.94, 4.46, both P<0.05). Among the 252 cases with co-infection in post-COVID-19 group, the most prevalent pathogens involving in co-infections, in order, were Mycoplasma pneumoniae 56 cases (22.2%), Influenza A virus 53 cases (21.0%), Rhinovirus 48 cases (19.0%), Parainfluenza virus 35 cases (13.9%), and Adenovirus 28 cases (11.1%).The result of multivariate Logistic regression showed that age (OR=0.70, 95%CI 0.62-0.78, P<0.001), underlying diseases (OR=10.03, 95%CI 4.10-24.55, P<0.001), premature birth (OR=6.78, 95%CI 3.53-13.04, P<0.001), NLR (OR=1.85, 95%CI 1.09-3.15, P=0.023), and co-infection (OR=1.28, 95%CI 1.18-1.38, P<0.001) were independently associated with the development of severe RSV infection in the post-COVID-19 group. The ROC curve of the prediction model integrating the above five factors indicated an area under the curve of 0.85 (95%CI 0.80-0.89, P<0.001), with an optimal cutoff of 0.21, a sensitivity of 0.83 and a specificity of 0.80. The calibration curve showed that the predicted probability in this model did not differ significantly from the actual probability (P=0.319). Conclusions: In the post-COVID-19 era in Kunming, the peak in pediatric hospitalizations for RSV infection was from May to October, with declined incidence of wheezing and increased incidence of fever, tachypnea, seizures, severe cases, and rates of triple and quadruple co-infections. Age, underlying diseases, premature birth, NLR, and co-infection were identified as independent risk factors for severe RSV infection in the post-COVID-19 period. In this study, a risk prediction model for severe pediatric RSV infection was established, which had a good predictive performance.
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Affiliation(s)
- H F Liu
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - Q L Feng
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - R W Huang
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - T Y Yuan
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - M Z Sui
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - P L Li
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - K Liu
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - F Li
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - Y Li
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
| | - L Jiang
- Department of Laboratory Medicine, Kunming Children's Hospital, Kunming 650034, China
| | - H M Fu
- Department of Pulmonary and Critical Care Medicine, Kunming Children's Hospital, Yunnan Provincial Key Laboratory of Children's Major Diseases Research, Kunming 650034, China
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Yuan M, Jiang L, Sun C, Lu W, Tapu SR, Zhang H, Jing G, Weng H, Peng J. Diagnostic and prognostic value of parameters of erector spinae in patients with uremic sarcopenia. Clin Radiol 2024:S0009-9260(24)00140-5. [PMID: 38599949 DOI: 10.1016/j.crad.2024.03.001] [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: 11/09/2023] [Revised: 02/09/2024] [Accepted: 03/04/2024] [Indexed: 04/12/2024]
Abstract
AIM This study aimed to investigate whether computed tomography (CT)-measured erector spinae parameters (ESPs) have diagnostic, severity assessment, and prognostic predictive value in uremic sarcopenia (US). MATERIALS AND METHODS A total of 202 uremic patients were enrolled and divided into two groups: a control group and a sarcopenia group. Sarcopenia was classified into two types: severe and nonsevere. The area, volume, and density of the erector spinae (ES) were measured using chest CT images, and the relevant ESP, including the erector spinae index (ESI), total erector spinae volume (TESV), erector spinae density (ESD), and erector spinae gauge (ESG) were calculated. The occurrence of adverse events was followed-up for 36 months. The diagnostic value and severity of US were determined using the receiver operating characteristic (ROC) curve. Survival curves diagnosed using CT were plotted and compared with the curve drawn using the gold standard. Cox regression analysis was used to identify independent risk factors associated with survival in US. RESULTS With an area under the curve (AUC) of 0.840 and 0.739, the combined ESP has diagnostic value and the ability to assess the severity of US. There was no significant difference in the survival curve between the combined ESP for the diagnosis of US and the gold standard (P > 0.05). ESI is a standalone predictor of survival in patients with US. CONCLUSION ESP measured by CT has diagnostic values for US and its severity, as well as being a predictive value for the prognosis of US.
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Affiliation(s)
- M Yuan
- Department of Radiology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - L Jiang
- Department of Nephrology, Jiangdu People's Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - C Sun
- Department of Radiology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - W Lu
- Department of Neurology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - S R Tapu
- Department of Cardiology, Tongji University Affiliated East Hospital, Jimo Road 150, Pudong District, Shanghai 200120, PR China
| | - H Zhang
- Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, Dingjiaqiao 87, Gulou District, Nanjing 210009, PR China
| | - G Jing
- Department of Radiology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - H Weng
- Department of Radiology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China
| | - J Peng
- Department of Radiology, Jiangdu People' s Hospital of Yangzhou, Dongfanghong Road 9, Jiangdu District, Yangzhou 225200, PR China.
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Dai XM, Jiang L, Xu QY, Zhu Y, Lin Q, Shen YY, Li XZ. [A case of juvenile systemic lupus erythematosus with autoimmune hypophysitis]. Zhonghua Er Ke Za Zhi 2024; 62:177-179. [PMID: 38264820 DOI: 10.3760/cma.j.cn112140-20231020-00306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Affiliation(s)
- X M Dai
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - L Jiang
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Q Y Xu
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Y Zhu
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Q Lin
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - Y Y Shen
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
| | - X Z Li
- Department of Nephrology and Immunology, Children's Hospital of Soochow University, Suzhou 215000, China
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Jiang L, Li W, Gong XL, Wang GY, Zhao F, Han L. Curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by acute pulmonary embolism by regulating microRNA-145-5P/insulin receptor substrate 1 axis. J Physiol Pharmacol 2024; 75. [PMID: 38583436 DOI: 10.26402/jpp.2024.1.03] [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] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 02/29/2024] [Indexed: 04/09/2024]
Abstract
The treatment of patients with acute pulmonary embolism (APE) is extremely challenging due to the complex clinical presentation and prognosis of APE related to the patient's hemodynamic status and insufficient arterial blood flow and right ventricular overload. Protective efficacy against cardiovascular diseases of curcumin, a common natural polyphenolic compound, which has antithrombotic properties and reduces platelet accumulation in the circulation by inhibiting thromboxane synthesis has been demonstrated. However, the direct effect of curcumin on APE has rarely been studied. Therefore, the present study aimed to investigate the therapeutic potential of curcumin in APE and associated myocardial injury to provide new insights into curcumin as a promising competitive new target for the treatment of APE. A suspension of 12 mg/kg microspheres was injected intravenously into rats. An APE rat model was built. Before modeling, intragastric 100 mg/kg curcumin was given, and/or lentiviral plasmid vector targeting microRNA-145-5p or insulin receptor substrate 1 (IRS1) was injected. Pulmonary artery pressure was measured to assess right ventricular systolic pressure (RVSP). Hematoxylin and eosin (H&E) staining was performed on liver tissues and myocardial tissues of APE rats. TUNEL (terminal deoxynucleotidyl transferase biotin-dUTP nick end labeling) staining and immunohistochemical (IHC) staining were conducted to measure apoptosis and CyPA-CD147 expression in the myocardium, respectively. Inflammatory indices interleukin-1beta (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) were measured by ELISA in cardiac tissues. RT-qPCR and Western blot were performed to determine the expression levels of related genes. In addition, by dual luciferase reporter assay and RIP assay, the relationship between microRNA-145-5p and insulin receptor substrate 1 (IRS1) was confirmed. In results: curcumin improved APE-induced myocardial injury, reduced myocardial tissue edema, and thrombus volume. It attenuated APE-induced myocardial inflammation and apoptosis, as well as reduced lung injury and pulmonary artery pressure. Curcumin promoted microRNA-145-5p expression in APE rat myocardium. MicroRNA-145-5p overexpression protected against APE-induced myocardial injury, and microRNA-145-5p silencing abolished the beneficial effects of curcumin in APE-induced myocardial injury. IRS1 was targeted by microRNA-145-5p. IRS1 silencing attenuated APE-induced myocardial injury, and enhanced therapeutic effect of curcumin on myocardial injury in APE rats. In conclusion, curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by APE by regulating microRNA-145-5p/IRS1 axis.
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Affiliation(s)
- L Jiang
- Department of Pharmacy, Yantai Qishan Hospital, Yantai City, Shandong Province, China
| | - W Li
- Department of Pharmacy, Yantai Qishan Hospital, Yantai City, Shandong Province, China
| | - X L Gong
- Department of Pharmacy, Yantai Qishan Hospital, Yantai City, Shandong Province, China
| | - G Y Wang
- Department of Respiratory Medicine, Qingdao Municipal Hospital (Qingdao Geriatric Hospital), Qingdao City, China
| | - F Zhao
- Intravenous Drug Dispensing Center, Qingdao Central Hospital Affiliated to Qingdao University,Qingdao City, China
| | - L Han
- Department of Pharmacy, Qingdao Women and Children's Hospital, Qingdao University, Qingdao City, China.
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Deng RF, Long LY, Chen YW, Jiang ZY, Jiang L, Zou LJ, Zhang YL. [Clinical repair strategy for ischial tuberosity pressure ulcers based on the sinus tract condition and range of skin and soft tissue defects]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2024; 40:64-71. [PMID: 38296238 DOI: 10.3760/cma.j.cn501225-20231114-00194] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Objective: To investigate the clinical repair strategy for ischial tuberosity pressure ulcers based on the sinus tract condition and range of skin and soft tissue defects. Methods: The study was a retrospective observational study. From July 2017 to March 2023, 21 patients with stage Ⅲ or Ⅳ ischial tuberosity pressure ulcers who met the inclusion criteria were admitted to the First Affiliated Hospital of Nanchang University, including 13 males and 8 females, aged 14-84 years. There were 31 ischial tuberosity pressure ulcers, with an area of 1.5 cm×1.0 cm-8.0 cm×6.0 cm. After en bloc resection and debridement, the range of skin and soft tissue defect was 6.0 cm×3.0 cm-15.0 cm×8.0 cm. According to the depth and size of sinus tract and range of skin and soft tissue defects on the wound after debridement, the wounds were repaired according to the following three conditions. (1) When there was no sinus tract or the sinus tract was superficial, with a skin and soft tissue defect range of 6.0 cm×3.0 cm-8.5 cm×6.5 cm, the wound was repaired by direct suture, Z-plasty, transfer of buttock local flap, or V-Y advancement of the posterior femoral cutaneous nerve nutrient vessel flap. (2) When the sinus tract was deep and small, with a skin and soft tissue defect range of 8.5 cm×4.5 cm-11.0 cm×6.5 cm, the wound was repaired by the transfer and filling of gracilis muscle flap followed by direct suture, or Z-plasty, or combined with transfer of inferior gluteal artery perforator flap. (3) When the sinus tract was deep and large, with a skin and soft tissue defect range of 7.5 cm×5.5 cm-15.0 cm×8.0 cm, the wound was repaired by the transfer and filling of gracilis muscle flap and gluteus maximus muscle flap transfer, followed by direct suture, Z-plasty, or combined with transfer of buttock local flap; and transfer and filling of biceps femoris long head muscle flap combined with rotary transfer of the posterior femoral cutaneous nerve nutrient vessel flap; and filling of the inferior gluteal artery perforator adipofascial flap transfer combined with V-Y advancement of the posterior femoral cutaneous nerve nutrient vessel flap. A total of 7 buttock local flaps with incision area of 8.0 cm×6.0 cm-19.0 cm×16.0 cm, 21 gracilis muscle flaps with incision area of 18.0 cm×3.0 cm-24.0 cm×5.0 cm, 9 inferior gluteal artery perforator flaps or inferior gluteal artery perforator adipofascial flaps with incision area of 8.5 cm×6.0 cm-13.0 cm×7.5 cm, 10 gluteal maximus muscle flaps with incision area of 8.0 cm×5.0 cm-13.0 cm×7.0 cm, 2 biceps femoris long head muscle flaps with incision area of 17.0 cm×3.0 cm and 20.0 cm×5.0 cm, and 5 posterior femoral cutaneous nerve nutrient vessel flaps with incision area of 12.0 cm×6.5 cm-21.0 cm×10.0 cm were used. The donor area wounds were directly sutured. The survival of muscle flap, adipofascial flap, and flap, and wound healing in the donor area were observed after operation. The recovery of pressure ulcer and recurrence of patients were followed up. Results: After surgery, all the buttock local flaps, gracilis muscle flaps, gluteus maximus muscle flaps, inferior gluteal artery perforator adipofascial flaps, and biceps femoris long head muscle flaps survived well. In one case, the distal part of one posterior femoral cutaneous nerve nutrient vessel flap was partially necrotic, and the wound was healed after dressing changes. In another patient, bruises developed in the distal end of inferior gluteal artery perforator flap. It was somewhat relieved after removal of some sutures, but a small part of the necrosis was still present, and the wound was healed after bedside debridement and suture. The other posterior femoral cutaneous nerve nutrient vessel flaps and inferior gluteal artery perforator flaps survived well. In one patient, the wound at the donor site caused incision dehiscence due to postoperative bleeding in the donor area. The wound was healed after debridement+Z-plasty+dressing change. The wounds in the rest donor areas of patients were healed well. After 3 to 15 months of follow-up, all the pressure ulcers of patients were repaired well without recurrence. Conclusions: After debridement of ischial tuberosity pressure ulcer, if there is no sinus tract formation or sinus surface is superficial, direct suture, Z-plasty, buttock local flap, or V-Y advancement repair of posterior femoral cutaneous nerve nutrient vessel flap can be selected according to the range of skin and soft tissue defects. If the sinus tract of the wound is deep, the proper tissue flap can be selected to fill the sinus tract according to the size of sinus tract and range of the skin and soft tissue defects, and then the wound can be closed with individualized flap to obtain good repair effect.
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Affiliation(s)
- R F Deng
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - L Y Long
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Y W Chen
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Z Y Jiang
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - L Jiang
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - L J Zou
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Y L Zhang
- Medical Center of Burn Plastic and Wound Repair, the First Affiliated Hospital of Nanchang University, Nanchang 330006, China
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Fu R, Lin R, Fan ZP, Huang F, Xu N, Xuan L, Huang YF, Liu H, Zhao K, Wang ZX, Jiang L, Dai M, Sun J, Liu QF. [Metagenomic next-generation sequencing for the diagnosis of Pneumocystis jirovecii pneumonia after allogeneic hematopoietic stem cell transplantation]. Zhonghua Xue Ye Xue Za Zhi 2024; 45:62-67. [PMID: 38527840 DOI: 10.3760/cma.j.cn121090-20230928-00147] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Objectives: To investigate the value of metagenomic next-generation sequencing (mNGS) in the diagnosis of Pneumocystis jirovecii pneumonia (PJP) in patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) . Methods: The data of 98 patients with suspected pulmonary infection after allo-HSCT who underwent pathogen detection from bronchoalveolar lavage fluid between June 2016 and August 2023 at Nanfang Hospital were analyzed. The diagnostic performance of mNGS, conventional methods, and real-time quantitative polymerase chain reaction (qPCR) for PJP were compared. Results: A total of 12 patients were diagnosed with PJP, including 11 with a proven diagnosis and 1 with a probable diagnosis. Among the patients with a proven diagnosis, 1 was positive by both conventional methods and qPCR, and 10 were positive by qPCR only. Pneumocystis jirovecii was detected by mNGS in all 12 patients. The diagnostic sensitivity of mNGS for PJP was 100%, which was greater than that of conventional methods (8.3%, P=0.001) and similar to that of qPCR (91.6%, P=1.000) . A total of 75% of the patients developed mixed pulmonary infections, and cytomegalovirus and Epstein-Barr virus were the most common pathogens. Mixed infection was detected in eight patients by mNGS and in five patients by qPCR, but not by conventional methods (P=0.008) . Conclusions: mNGS had good sensitivity for diagnosing PJP after allo-HSCT and was advantageous for detecting mixed infectious pathogens; therefore, mNGS might be an effective supplement to regular detection methods and qPCR.
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Affiliation(s)
- R Fu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - R Lin
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - Z P Fan
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - F Huang
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - N Xu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - L Xuan
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - Y F Huang
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - H Liu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - K Zhao
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - Z X Wang
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - L Jiang
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - M Dai
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - J Sun
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
| | - Q F Liu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Clinical Medical Research Center of Hematological Diseases of Guangdong Province, Guangzhou 510515, China
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Gu LN, Yu JW, Jiang L, Liu TB, Xu Y. Serum squamous cell carcinoma antigen level and magnetic resonance imaging for the prognosis of locally advanced cervical cancer. Eur Rev Med Pharmacol Sci 2024; 28:668-678. [PMID: 38305609 DOI: 10.26355/eurrev_202401_35064] [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] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
OBJECTIVE Squamous cell carcinoma antigen (SCC-ag) and magnetic resonance imaging (MRI) were explored to serve as biomarkers to predict the prognosis of cervical cancer (CC) patients treated with neoadjuvant chemotherapy (NACT) prior to radical surgery, with the aim of identifying the subgroup that least benefits from the combined therapy. PATIENTS AND METHODS All patients were treated with NACT prior to radical surgery and received MRI and SCC-ag examinations before and after NACT. For these three cycles of NACT, patients were treated with intravenous paclitaxel at 150 mg/m2 over a period of 3 hours and carboplatin, with the area under the sera concentration-time curve of 5 over a period of 30 minutes on the first day of each cycle. Meanwhile, the blood pressure, ECG, and blood oxygen saturation of the patients were observed during the infusion. A discovery cohort and a validation cohort were applied to examine the prognostic performance of SCC-ag, MRI, and their combination. The endpoints of our study were overall survival (OS) and progression-free survival (PFS). RESULTS A total of 384 patients diagnosed between August 2006 and December 2010 were enrolled in our research, with 206 patients in the discovery cohort and 178 patients in the validation cohort. The high-risk group identified by MRI had a worse OS [hazard ratio (HR), 3.567; 95% confidence interval (CI), 1.466-8.677; log-rank p=0.0027) and PFS (HR, 4.062; 95% CI, 2.171-7.6; log-rank p<0.0001) than the low-risk group. Meanwhile, the SCC-RC could serve as a strong prognostic factor to predict OS (HR, 5.614; 95% CI, 2.473-12.744; log-rank p<0.0001) and PFS (HR, 7.481; 95% CI, 4.194-13.344; log-rank p<0.0001) for CC. In addition, the combined MRI and SCC-ag had greater prognostic efficiency and were used to divide the whole patient population into three groups. Compared with patients in the low-risk group, patients in the high-risk group had a worse OS (HR, 8.216; 95% CI, 2.98-22.651; log-rank p<0.0001) and PFS (HR, 11.757; 95% CI, 5.735-24.104; log-rank p<0.0001). Multivariate analyses revealed that MRI, SCC-ag, and their combination were independent prognostic factors. CONCLUSIONS SCC-ag and MRI, individually or in combination, were bound up with OS and PFS in CC. Additionally, the predictive efficiency improved when SCC-ag and MRI were combined in a risk model that predicted the OS and PFS of SCC compared with the predictive efficiency of either SCC-ag or MRI alone, revealing that the combination of these two biomarkers could help to ameliorate prognostic stratification and to guide personalized therapy for SCC patients.
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Affiliation(s)
- L-N Gu
- Department of Gynecology, Harbin Medical University Cancer Hospital, Harbin, China.
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Li X, Zheng J, Wei SB, Li HY, Jiang L, Dong L, Wang J, Tao CZ, Yan YH, Sun LH, Cui LB, Huang JH, Fang YX, Tang CX. [A multicenter study to test the reliability and validity of the frailty assessment scale for elderly patients with inguinal hernia and to evaluate the value of clinical application]. Zhonghua Wai Ke Za Zhi 2023; 61:1080-1085. [PMID: 37932144 DOI: 10.3760/cma.j.cn112139-20230131-00043] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Objectives: To verify the reliability and validity of the frailty assessment scale for elderly patients with inguinal hernia and to evaluate the value of its clinical application. Methods: A convenience sampling method was used to collect 129 geriatric patients who underwent inguinal hernia surgery from January 2018 to January 2023 in nine hospitals in Liaoning Province. There were 120 males and 9 females, of whom 89 patients were 60 to <75 years old, 33 patients were 75 to <85 years old and 7 patients were ≥85 years old. The 129 patients included 11 elderly patients with inguinal hernia who had recovered from preoperative infection with COVID-19. Statistical methods such as Cronbach's coefficient, Kaiser-Meyer-Olkin test, Bartlett's test, Pearson's correlation analysis, etc. were calculated to verify the reliability indexes such as feasibility, content validity, structural validity, criterion-related validity, internal consistency reliability, and re-test reliability. Taking the 5-item modified frailty index (5-mFI) as the gold standard, the area under the curve was used to analyze the ability of the two scales to predict the occurrence of postoperative acute urinary retention, postoperative delirium, poor incision healing, operative hematoma seroma, and postoperative complications. Results: The frailty assessment scale for elderly patients with inguinal hernia showed good reliability and validity (valid completion rate of 99.2%; item content validity index of 1.000, and the scale content validity index of 1.000; exploratory factor analysis extracted a total of 1 principal component, and factor loadings of each item of 0.565 to 0.873; the AUC for frailty diagnosis using 5-mFI as the gold standard of 0.795 (P<0.01) Cronbach's coefficient of 0.916, retest reliability coefficient of 0.926), it could effectively predict postoperative acute urinary retention, delirium, hematoma seroma in the operative area and total complications (AUC of 0.746, 0.870, 0.806, and 0.738, respectively; all P<0.05), and prediction efficiency was higher than that of 5-mFI (AUC of 0.694, 0.838, 0.626 and 0.641, P<0.05 for delirium only), but both scales were inaccurate in predicting poor incision healing (AUC of 0.519, P=0.913 for the frailty assessment scale and 0.455, P=0.791 for the 5-mFI). Conclusions: The frailty assessment scale for elderly patients with inguinal hernia is reliable and significantly predicts the occurrence of postoperative adverse events in elderly inguinal hernia patients. The scale can also be used for preoperative frailty assessment in elderly patients with inguinal hernia after rehabilitation from COVID-19 infection.
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Affiliation(s)
- X Li
- The Third Department of General Surgery, the Fourth Affiliated Hospital of China Medical University, Shenyang 110032, China
| | - J Zheng
- Department of Clinical Epidemiology, the Fourth Affiliated Hospital of China Medical University, Shenyang 110032, China
| | - S B Wei
- The Seventh Department of General Surgery, the Fourth Affiliated Hospital of China Medical University, Shenyang 110032, China
| | - H Y Li
- The Third Department of General Surgery, the Fourth Affiliated Hospital of China Medical University, Shenyang 110032, China
| | - L Jiang
- Department of General Surgery, the First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121000, China
| | - L Dong
- Department of General Surgery, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - J Wang
- Department of General Surgery, Liaoning Provincial Health Industry Group Fukuang General Hospital, Fushun 113012, China
| | - C Z Tao
- Department of General Surgery, Liaoning Provincial Health Industry Group Fukuang General Hospital, Fushun 113012, China
| | - Y H Yan
- Department of General Surgery, Dandong First Hospital, Dandong 118000, China
| | - L H Sun
- Department of General Surgery, the Third Affiliated Hospital of Jinzhou Medical University, Jinzhou 121001, China
| | - L B Cui
- Department of General Surgery, Dalian Pulandian Geriatric Hospital, Dalian 116200, China
| | - J H Huang
- Department of General Surgery, Yingkou Central Hospital, Yingkou 115003, China
| | - Y X Fang
- Department of General Surgery, Yingkou Central Hospital, Yingkou 115003, China
| | - C X Tang
- Department of General Surgery, Liaoyang Central Hospital, Liaoyang 111000, China
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Liu Q, Dai F, Zhu H, Yang H, Huang Y, Jiang L, Tang X, Deng L, Song L. Deep learning for the early identification of periodontitis: a retrospective, multicentre study. Clin Radiol 2023; 78:e985-e992. [PMID: 37734974 DOI: 10.1016/j.crad.2023.08.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 08/15/2023] [Accepted: 08/21/2023] [Indexed: 09/23/2023]
Abstract
AIM To develop a deep-learning model to help general dental practitioners diagnose periodontitis accurately and at an early stage. MATERIALS AND METHODS First, the panoramic radiographs (PARs) from the Second Affiliated Hospital of Nanchang University were input into the convolutional neural network (CNN) architecture to establish the PAR-CNN model for healthy controls and periodontitis patients. Then, the PARs from the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine were included in the second testing set to validate the effectiveness of the model with data from two centres. Heat maps were produced using a gradient-weighted class activation mapping method to visualise the regions of interest of the model. The accuracy and time required to read the PARs were compared between the model, periodontal experts, and general dental practitioners. Areas under the receiver operating characteristic curve (AUCs) were used to evaluate the performance of the model. RESULTS The AUC of the PAR-CNN model was 0.843, and the AUC of the second test set was 0.793. The heat map showed that the regions of interest predicted by the model were periodontitis bone lesions. The accuracy of the model, periodontal experts, and general dental practitioners was 0.800, 0.813, and 0.693, respectively. The time required to read each PAR by periodontal experts (6.042 ± 1.148 seconds) and general dental practitioners (13.105 ± 3.153 seconds), which was significantly longer than the time required by the model (0.027 ± 0.002 seconds). CONCLUSION The ability of the CNN model to diagnose periodontitis approached the level of periodontal experts. Deep-learning methods can assist general dental practitioners to diagnose periodontitis quickly and accurately.
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Affiliation(s)
- Q Liu
- Center of Stomatology, The Second Affiliated Hospital of Nanchang University, Nanchang, China; The Institute of Periodontal Disease, Nanchang University, Nanchang, China
| | - F Dai
- Center of Stomatology, The Second Affiliated Hospital of Nanchang University, Nanchang, China; The Institute of Periodontal Disease, Nanchang University, Nanchang, China
| | - H Zhu
- Center of Stomatology, The Second Affiliated Hospital of Nanchang University, Nanchang, China; The Institute of Periodontal Disease, Nanchang University, Nanchang, China
| | - H Yang
- The Second Clinical College, Medical College of Nanchang University, Nanchang, China
| | - Y Huang
- Center of Stomatology, The Second Affiliated Hospital of Nanchang University, Nanchang, China; The Institute of Periodontal Disease, Nanchang University, Nanchang, China
| | - L Jiang
- Department of Stomatology, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - X Tang
- College of Basic Medical Science, Nanchang University, Nanchang, China
| | - L Deng
- The Institute of Periodontal Disease, Nanchang University, Nanchang, China; School of Public Health, Nanchang University, Nanchang, China; Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, China.
| | - L Song
- Center of Stomatology, The Second Affiliated Hospital of Nanchang University, Nanchang, China; The Institute of Periodontal Disease, Nanchang University, Nanchang, China.
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Huang Y, Jiang L, Liu J, Xu Y, Mo F, Su J, Tao R. Investigating a Causal Relationship Between Diabetes Mellitus and Oropharyngeal Cancer: A Mendelian Randomization Study. Community Dent Health 2023; 40:212-220. [PMID: 37988677 DOI: 10.1922/cdh_00025huang09] [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] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 05/01/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVE Previous observational studies reported an association of diabetes mellitus (DM) with oropharyngeal cancer (OPC), however, the potential causality of the association between them remains unclear. METHODS To explore this causal relationship in individuals of European descent, a two-sample Mendelian randomization (MR) study was conducted. A genome-wide association study (GWAS) of DM was used to represent the exposure factor (T1DM: n = 24,840; T2DM: n = 215,654), and GWAS of OPC represented the outcome (n = 3,448). RESULTS Forty-one single nucleotide polymorphisms (SNPs) related to T1DM and fifty-four SNPs related to T2DM were identified as effective instrumental variables (IVs) in the two-sample MR analyses. In IVW estimates, neither T1DM nor T2DM significantly contributed to an increased risk of OPC [T1DM: OR 1.0322 (95% CI 0.9718, 1.0963), P = 0.3033; T2DM: OR 0.9998 (95% CI 0.9995, 1.0002), P = 0.2858]. Four other regression models produced similar results. MR-Egger regression results [Cochran's Q statistic was 47.1544 (P = 0.1466) in T1DM, and 35.5084 (P = 0.9512) in T2DM] suggested no horizontal pleiotropy between IVs and outcomes. CONCLUSION Our findings suggest little evidence to support the genetic role of diabetes mellitus in OPC development in the European population.
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Affiliation(s)
- Y Huang
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - L Jiang
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - J Liu
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - Y Xu
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - F Mo
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - J Su
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
| | - R Tao
- Department of Periodontics and Oral medicine, College of Stomatology, Guangxi Medical University, China
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Jiang L, Zhao BZ, Gao XY, Ge WY, Cui YF, Lyu FY, Han GP. [Intracranial Langerhans-cell histiocytosis that is not coocurring with Erdheim-Chester disease: report of a case]. Zhonghua Bing Li Xue Za Zhi 2023; 52:1171-1173. [PMID: 37899329 DOI: 10.3760/cma.j.cn112151-20230316-00201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Affiliation(s)
- L Jiang
- Department of Pathology, the Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
| | - B Z Zhao
- The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
| | - X Y Gao
- The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
| | - W Y Ge
- Department of Stomatology, Harbin Institute of Technology, Heilongjiang Provincial Hospital, Harbin 150036, China
| | - Y F Cui
- Department of Pathology, Harbin Medical University Cancer Hospital, Harbin 150040, China
| | - F Y Lyu
- The Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
| | - G P Han
- Department of Pathology, the Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
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Hu HF, Jiang N, Jiang L, Lu P, Xiao YQ, Zhang Y. Predictive values of cervix length measurement based on transvaginal ultrasonography combined with pathological examination of placenta for premature delivery and correlation between premature delivery and infection. Eur Rev Med Pharmacol Sci 2023; 27:10221-10232. [PMID: 37975346 DOI: 10.26355/eurrev_202311_34297] [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] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
OBJECTIVE The predictive values of cervix length (CL) measurement based on transvaginal ultrasonography (TVUS) and pathological examination of placenta for premature delivery (PTD) were investigated, and the correlation between PTD and infection was analyzed. PATIENTS AND METHODS A total of 120 pregnant women with PTD or high-risk factors for PTD admitted to Hengyang Maternal and Child Health Hospital, between February 2020 and March 2022 were included in this retrospective study. There were 36 subjects in the PTD group and 84 in the normal delivery group (control group). They underwent pathological examination of the placenta and TVUS for CL measurement. The final gestational age was set as the standard for the evaluation of the predictive values of pathological examination of the placenta and TVUS. Moreover, a pathological examination of the placenta was used to analyze the correlation between PTD and infection. RESULTS The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of joint inspection were remarkably superior to those of single CL or pathological examination of the placenta (p<0.05). The proportion of pregnant women with CL ≤30 mm and positive placental pathology was higher than that of pregnant women with CL >30 mm and negative placental pathology (p<0.05). In addition, the incidence of Ureaplasma urealyticum (UU), Chlamydia trachomatis (CT), and chorioamnionitis (CA) in the vaginal discharge of the PTD group was markedly superior to that of the control group (p<0.05). CONCLUSIONS The combination of CL ≤30 mm and positive placental pathology could effectively predict PTD, and placental infection was notably correlated with the occurrence of PTD.
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Affiliation(s)
- H-F Hu
- Affiliated Hospital, Hunan Vocational and Technical College of Environmental Biology, Hengyang, China.
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15
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Jiang L, Wang WP, Wu BY, Mao HJ. [Association between sarcopenia and abdominal aortic calcification in maintenance hemodialysis patients]. Zhonghua Yi Xue Za Zhi 2023; 103:3026-3032. [PMID: 37813653 DOI: 10.3760/cma.j.cn112137-20230615-01019] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
Objective: To investigate the relationship between sarcopenia and abdominal aortic calcification (AAC) in maintenance hemodialysis (MHD) patients. Methods: A cross-sectional study was conducted. MHD patients who underwent regular dialysis between January 2021 and January 2022 at hemodialysis center in Jiangdu People's Hospital Affiliated to Yangzhou University were enrolled. The incidence of sarcopenia in these patients was examined by measuring handgrip strength, gait speed and appendicular skeletal muscle mass index (ASMI) using bioelectrical impedance analysis. AAC score was measured by a lateral lumbar spinal radiograph. The general information of the patients was collected and the blood biochemical indexes were detected. These patients were divided into non-calcification group (n=104) and calcification group (n=127) according to the score of AAC. Multivariate logistic regression was used to analyze the related factors of AAC. Results: A total of 231 MHD patients (134 males and 97 females) were enrolled in the study, with the mean age of (57.1±11.4) years. Among 231 hemodialysis patients, the incidence of sarcopenia and AAC were 46.3% (107 cases) and 55.0% (127 cases), respectively. The age [(60.2±11.1) vs (53.4±12.2) years, P<0.001] and dialysis vintage [86 (46, 135) vs 57 (27, 109) months, P=0.005] in calcification group were longer than these in the non-calcification group. The level of 25(OH)D3 [17.7 (13.5, 24.3) vs 20.5 (15.1, 28.1) μg/L, P=0.008] and gait speed [(0.88±0.23) vs (1.01±0.20) m/s, P=0.024], handgrip strength [(17.9±9.1) vs (20.7±9.9) kg, P=0.013], ASMI [(6.65±2.24) vs (7.83±2.46) kg/m2, P<0.001] were lower. While, AAC score [12 (9, 19) vs 0 (0, 3), P<0.001] and the incidence of sarcopenia [58.3% (74/127) vs 31.7% (33/104), P<0.001] were higher in the calcification group than these in the non-calcification group. Multivariate logistic regression analysis indicated that sarcopenia (OR=1.928, 95%CI: 1.302-2.855, P=0.001), decrease of 25(OH)D3 level (OR=0.969, 95%CI: 0.940-1.000, P=0.047), age (OR=1.043, 95%CI: 1.015-1.072, P=0.002), and dialysis vintage (OR=1.009, 95%CI: 1.004-1.015, P=0.001) were related factors of AAC. Conclusions: Sarcopenia is associated with AAC in MHD patients. In clinical practice, attention should be paid to sarcopenia in MHD patients.
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Affiliation(s)
- L Jiang
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - W P Wang
- Department of Nephrology, Jiangdu People's Hospital Affiliated to Yangzhou University, Yangzhou 225200, China
| | - B Y Wu
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - H J Mao
- Department of Nephrology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
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Wu F, Tang X, Zhang Y, Wei L, Wang T, Lu Z, Wei J, Ma S, Jiang L, Gao T, Huang Q. The Role of Radiation Therapy for Metastatic Cervical Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e555. [PMID: 37785704 DOI: 10.1016/j.ijrobp.2023.06.1865] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Survival rates for women with metastatic cervical cancer (CC) are low, with limited management options. Radiation therapy (RT) for metastatic disease has led to prolonged survival in other malignancies, however, the data are scarce in CC. Herein, we evaluated the effect of RT for metastatic CC. MATERIALS/METHODS A total of 58 patients with metastatic CC between September 2019 and January 2023 were retrospectively analyzed. All the patients were treated with platinum-based chemotherapy combined with targeted therapy or immunotherapy followed with or without RT (NRT). The recent efficacy, survival status and prognostic factors were analyzed statistically. RESULTS Objective response rate (ORR) was 63.6% with one complete and twenty partial responses in RT group (n = 33) and 40.0% with two complete and eight partial responses in NRT group (n = 25), respectively (p = 0.074). Disease control rate (DCR) of the RT and NRT groups were 79.4% vs 80.0%, respectively (p = 0.861). Median follow-up time was 17 months (3-39months). In RT group, 11(33.3%) patients experienced local regional or distant failure and 9 (27.3%) patients were dead. In NRT group, 15(60%) patients had progression and 8 (32%) patients dead. There was no significant difference between the two groups in overall survival (OS); however, RT group displayed superior progression-free survival (PFS) (1-year OS: 72.7% vs. 68.0%, p = 0.460; 1-year PFS: 66.7% vs. 40.0%, p = 0.039). The multivariate analysis showed that RT, immunotherapy, lymph node metastasis only relevant predictor of superior PFS but not OS. In subgroup analysis, patients treated with RT appeared to have a better PFS in some specific cohorts, such as age>45 years (72.0% vs 36.4% P = 0.015), squamous carcinoma histology (71.0% vs 40.9% P = 0.017), metastatic at diagnosis (75.0% vs 47.6% P = 0.012), non-targeted therapy (72.4% vs 43.8% P = 0.040). No significant increase in treatment-related toxicity was observed in the RT group compared with the NRT group. CONCLUSION RT provided superior PFS in metastatic CC patients compared to NRT, and well tolerated. Moreover, RT, immunotherapy, lymph node metastasis only were independent significant prognostic factors for PFS. Subgroup analysis showed that combination of RT and chemotherapy obtained favorable PFS in metastatic CC patients with age>45 years, squamous carcinoma histology, metastatic at diagnosis, non-targeted therapy. Studies with a larger sample size and longer follow-up are warranted.
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Affiliation(s)
- F Wu
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - X Tang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China; Department of Radiation Oncology, Liuzhou People's Hospital, Liuzhou, Guangxi, China
| | - Y Zhang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - L Wei
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - T Wang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Z Lu
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - J Wei
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - S Ma
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - L Jiang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - T Gao
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Q Huang
- Department of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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Yu J, Jiang L, Zhao L, Wang X, Yang X, Yang D, Zhuo M, Chen H, Zhao YD, Zhou F, Li Q, Zhu Z, Chu L, Ma Z, Wang Q, Qu Y, Huang W, Zhang M, Gu T, Liu S, Yang Y, Yang J, Yu H, Yu R, Zhao J, Shi A. High Dose Hyperfractionated Thoracic Radiotherapy vs. Standard Dose for Limited Stage Small-Cell Lung Cancer: A Multicenter, Open-Label Randomized, Phase 3 Trial. Int J Radiat Oncol Biol Phys 2023; 117:S1. [PMID: 37784261 DOI: 10.1016/j.ijrobp.2023.06.205] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Limited stage small-cell lung cancer (LS-SCLC) is associated with poor prognosis. We aimed to assess the efficacy and safety of high-dose, hyperfractionated thoracic radiotherapy of 54 Gy in 30 fractions compared with standard dose (45 Gy in 30 fractions) as a first-line treatment for LS-SCLC. MATERIALS/METHODS The study was an open-label, randomized, phase 3 trial, done at 16 public hospitals in China. Key inclusion criteria were patients aged 18-70 years, with previously histologically or cytologically confirmed LS-SCLC, previously untreated or received 1-2 courses of intravenous cisplatin (75 mg/m²of body-surface area, on day 1 or divided into two days of each cycle) or carboplatin (area under the curve of 5 mg/mL per min, day 1 of each cycle)and intravenous etoposide (100 mg/m²of body-surface area, on days 1-3 of each cycle), and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1.Eligible patients were randomly assigned (1:1) to receive volumetric-modulated arc radiotherapy (VMAT) of 45 Gy in 30 fractions or the simultaneous integrated boost VMAT (SIB-VMAT) of 54 Gy in 30 fractions to the primary lung tumor and lymph node metastases starting 0-42 days after the first chemotherapy course. Both groups of patients received thoracic radiotherapy twice per day and 10 fractions per week. Prophylactic cranial radiation (PCI, 25 Gy in 10 fractions) was implemented to patients with responsive disease. The primary endpoint was overall survival. Safety was analyzed in the as-treated population. RESULTS Between June 30, 2017, and April 6, 2021, 224 eligible patients were enrolled and randomly assigned to 54 Gy (n = 108) or 45 Gy (n = 116). Median follow-up for the primary analysis was 45 months (IQR 41-48). Median overall survival was significantly improved in the 54 Gy group (62.4 months) compared with the 45 Gy group (43.1 months; p = 0.001). Median progression-free survival was significantly improved in the 54 Gy group (30.5 months) compared with the 45 Gy group (16.7 months; p = 0.044). The most common grade 3-4 adverse events were neutropenia (30 [28%] of 108 patients in the 54 Gy group vs 27 [23%] of 116 patients in the 45 Gy group), neutropenic infections (6 [6%] vs 2 [2%]), thrombocytopenia (13 [12%] vs 12 [10%]), anemia (6 [6%] vs 4 [3%]), and esophagitis (1 [1%] vs 3 [3%]). Treatment-related serious adverse events occurred in 9 [8%] patients in the 54 Gy group and 16 [14%] patients in the 45 Gy group. There were one treatment-related deaths in 54 Gy group (myocardial infarction). CONCLUSION Compared with standard thoracic radiotherapy dose of 45 Gy, the high dose of 54 Gy improved overall survival and progression-free survival without increasing toxicities in patients with LS-SCLC, supporting twice-daily hyperfractionated thoracic radiotherapy of 54 Gy with concurrent chemotherapy is an alternative treatment option for LS-SCLC. This study is complete and registered with ClinicalTrials.gov, NCT03214003.
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Affiliation(s)
- J Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - L Jiang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University. ty, Xi'an, China
| | - X Wang
- Department of Radiation Oncology, Anyang Cancer Hospital, Anyang, China
| | - X Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - D Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - M Zhuo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - H Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - Y D Zhao
- Department of Radiation Oncology, Anyang Tumor Hospital, Anyang, China
| | - F Zhou
- Yantai Yuhuangding Hospital, Yantai, China
| | - Q Li
- Ordos School of Clinical Medicine I.M.M.U, Ordos, China
| | - Z Zhu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - L Chu
- Fudan University Shanghai Cancer Center, Shanghai, China
| | - Z Ma
- Chifeng Affiliated Hospital, Chifeng, China
| | - Q Wang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Chengdu, China
| | - Y Qu
- Liaoning cancer hospital & institute, Shenyang, China
| | - W Huang
- Shandong Cancer Hospital & Institute, Jinan, Shandong, China
| | - M Zhang
- Department of Radiation Oncology, Peking University People's Hospital, Beijing, China; Department of Radiation Oncology, Peking University First Hospital, Peking University, Beijing, China
| | - T Gu
- The First Hospital of Qinhuangdao, Qinhuangdao, China
| | - S Liu
- Jilin Provincial Cancer Hospital, Changchun, China
| | - Y Yang
- Jilin Provincial Cancer Hospital, Changchun, China
| | - J Yang
- Department of Oncology, The first Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - H Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - R Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - J Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - A Shi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cohen EO, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector. Phys Rev Lett 2023; 131:101802. [PMID: 37739352 DOI: 10.1103/physrevlett.131.101802] [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] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/09/2023] [Accepted: 07/14/2023] [Indexed: 09/24/2023]
Abstract
We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - O Benevides Rodrigues
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
- Syracuse University, Syracuse, New York 13244, USA
| | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - E O Cohen
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Wang L, Zhang Y, Wang XQ, Yue ZD, Fan ZH, Wu YF, Liu FQ, Dong J, Zhang K, Jiang L, Ding HG, Zhang YN. [Evaluation of the efficacy of TIPS in 27 patients with hepatic sinus obstruction syndrome in the near and medium term]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:842-846. [PMID: 37723066 DOI: 10.3760/cma.j.cn501113-20221012-00493] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
Objective: intrahepatic portocaval shunt (TIPS) in the treatment of hepatic sinusoidal obstruction syndrome (HSOS). Methods: A retrospective analysis was performed on 27 patients with HSOS who were treated with TIPS in our center from July 2018 to July 2020. The changes of portal vein pressure (PVP), portal vein pressure gradient (PPG) and liver function were observed, so as to evaluate the efficacy. Paired t test was adopted to evaluate the quantitative parameters, while χ (2) test was used to analyze qualitative parameters, with P < 0.05 as statistical difference. Results: PVP decreased from (4.41 ± 0.18) kPa before shunt to (2.69 ± 0.11) kPa after shunt (t = 82.41, P < 0.001), PPG decreased from (3.23 ± 0.18) kPa before shunt to (1.46 ± 0.23) kPa after shunt (t = 32.41, P < 0.001). The liver function improved significantly after operation. After 24 months of follow-up, 3 patients developed stent restenosis and recanalized after balloon dilation. Three patients developed hepatic encephalopathy, which was improved after drug treatment. One patient underwent liver transplantation due to liver failure. Conclusion: TIPS is effective in the treatment of HSOS in the short and medium term, and can provide time for liver transplantation patients to wait for liver source.
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Affiliation(s)
- L Wang
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Y Zhang
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - X Q Wang
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Z D Yue
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Z H Fan
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - Y F Wu
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - F Q Liu
- Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - J Dong
- Department of Radiology Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - K Zhang
- Department of Surgery, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - L Jiang
- Department of Surgery, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - H G Ding
- Department of Gastroenterology, Beijing You'an Hospital, Capital Medical University, Beijing 100069, China
| | - Y N Zhang
- Department of Gastroenterology, Beijing You'an Hospital, Capital Medical University, Beijing 100069, China
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Jiang L, Piribauer M, Kostov T, Steidel S, Bizjak DA, Steinacker JM, Parr M, Diel P. Testing anabolic activity, potency and mechanisms of action of the phyto-derived beta 2 agonist higenamine. Toxicol Lett 2023; 385:21-28. [PMID: 37598871 DOI: 10.1016/j.toxlet.2023.08.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [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: 06/09/2023] [Revised: 08/07/2023] [Accepted: 08/16/2023] [Indexed: 08/22/2023]
Abstract
Higenamine (Hige), a plant derived alkaloid is classified as β2 agonist by the World Anti-Doping Agency (WADA). However, pharmacologic mechanisms of its performance-enhancing activity have not been investigated so far. Therefore, we investigate the anabolic activity and associated molecular mechanisms of Hige in C2C12 myotubes. In differentiated C2C12 cells dose-dependent effects of Hige on myotube size were analyzed. The mRNA expression of genes involved in hypertrophy was measured. For mechanistic studies, β2-adrenoceptor (ADRB2), androgen receptor (AR), and estrogen receptor (ER) inhibitors and dexamethasone (Dexa) were co-incubated and myotube diameter was evaluated. The interaction of Hige with the AR and ER was investigated. Hige treatment significantly increased myotube diameters and stimulated the mRNA expression of hypertrophy-involved genes. In contrast to the ADRB2 inhibitor (ICI 118551), the ER inhibitor ZK 191703, the AR inhibitor Flutamide (Flu), and treatment with Dexa were able to antagonize the Hige-induced increase of myotube diameter. Hige has antagonistic activity in the AR and ER yeast transactivation assay. Our results demonstrate that Hige induces anabolic effects in C2C12 cells but not via the ADRB2. There are indications for a cross talk between Hige and the AR and ER. Future studies are necessary to investigate the involved molecular mechanisms.
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Affiliation(s)
- L Jiang
- German Sports University Cologne, Department of Molecular and Cellular Sport Medicine, Cologne, Germany; Division of Sports and Rehabilitation Medicine, Center of Medicine, University Hospital Ulm, Ulm, Germany
| | - M Piribauer
- German Sports University Cologne, Department of Molecular and Cellular Sport Medicine, Cologne, Germany
| | - T Kostov
- German Sports University Cologne, Department of Molecular and Cellular Sport Medicine, Cologne, Germany
| | - S Steidel
- German Sports University Cologne, Department of Molecular and Cellular Sport Medicine, Cologne, Germany
| | - D A Bizjak
- Division of Sports and Rehabilitation Medicine, Center of Medicine, University Hospital Ulm, Ulm, Germany
| | - J M Steinacker
- Division of Sports and Rehabilitation Medicine, Center of Medicine, University Hospital Ulm, Ulm, Germany
| | - M Parr
- Institute of Pharmaceutical and Medicinal Chemistry, Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Germany
| | - P Diel
- German Sports University Cologne, Department of Molecular and Cellular Sport Medicine, Cologne, Germany.
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21
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Xu JJ, Chen J, Liu YX, Song Y, Jiang L, Yan SD, Guo WY, Yao Y, Jia SD, Yuan DS, Wang PZ, Li JX, Zhao XY, Liu ZY, Yuan JQ. [The impact of LDL-C/HDL-C ratio on severity of coronary artery disease and 2-year outcome in patients with premature coronary heart disease: results of a prospective, multicenter, observational cohort study]. Zhonghua Xin Xue Guan Bing Za Zhi 2023; 51:702-708. [PMID: 37460423 DOI: 10.3760/cma.j.cn112148-20230128-00043] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Objective: To explore the relationship between low density lipoprotein cholesterol (LDL-C)/high density lipoprotein cholesterol (HDL-C) ratio with the severity of coronary artery disease and 2-yeat outcome in patients with premature coronary heart disease. Methods: This prospective, multicenter, observational cohort study is originated from the PROMISE study. Eighteen thousand seven hundred and one patients with coronary heart disease (CHD) were screened from January 2015 to May 2019. Three thousand eight hundred and sixty-one patients with premature CHD were enrolled in the current study. According to the median LDL-C/HDL-C ratio (2.4), the patients were divided into two groups: low LDL-C/HDL-C group (LDL-C/HDL-C≤2.4, n=1 867) and high LDL-C/HDL-C group (LDL-C/HDL-C>2.4, n=1 994). Baseline data and 2-year major adverse cardiovascular and cerebrovascular events (MACCE) were collected and analyzed in order to find the differences between premature CHD patients at different LDL-C/HDL-C levels, and explore the correlation between LDL-C/HDL-C ratio with the severity of coronary artery disease and MACCE. Results: The average age of the low LDL-C/HDL-C ratio group was (48.5±6.5) years, 1 154 patients were males (61.8%); the average age of high LDL-C/HDL-C ratio group was (46.5±6.8) years, 1 523 were males (76.4%). The number of target lesions, the number of coronary artery lesions, the preoperative SNYTAX score and the proportion of three-vessel coronary artery disease in the high LDL-C/HDL-C group were significantly higher than those in the low LDL-C/HDL-C group (1.04±0.74 vs. 0.97±0.80, P=0.002; 2.04±0.84 vs. 1.85±0.84, P<0.001; 13.81±8.87 vs. 11.70±8.05, P<0.001; 36.2% vs. 27.4%, respectively, P<0.001). Correlation analysis showed that there was a significant positive correlation between LDL-C/HDL-C ratio and preoperative SYNTAX score, the number of coronary artery lesions, the number of target lesions and whether it was a three-vessel coronary artery disease (all P<0.05). The 2-year follow-up results showed that the incidence of MACCE was significantly higher in the high LDL-C/HDL-C group than that in the low LDL-C/HDL-C group (6.9% vs. 9.1%, P=0.011). There was no significant difference in the incidence of all-cause death, cardiac death, myocardial infarction, stroke, revascularization and bleeding between the two groups. Cox multivariate regression analysis showed that the LDL-C/HDL-C ratio has no correlation with 2-year MACCE, death, myocardial infarction, revascularization, stroke and bleeding events above BARC2 in patients with premature CHD. Conclusion: High LDL-C/HDL-C ratio is positively correlated with the severity of coronary artery disease in patients with premature CHD. The incidence of MACCE of patients with high LDL-C/HDL-C ratio is significantly higher during 2 years follow-up; LDL-C/HDL-C ratio may be an indicator for evaluating the severity of coronary artery disease and long-term prognosis in patients with premature CHD.
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Affiliation(s)
- J J Xu
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - J Chen
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen 518057, China
| | - Y X Liu
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Y Song
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - L Jiang
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - S D Yan
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen 518057, China
| | - W Y Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen 518057, China
| | - Y Yao
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - S D Jia
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - D S Yuan
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - P Z Wang
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - J X Li
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - X Y Zhao
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Z Y Liu
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - J Q Yuan
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
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22
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Winiarski B, Gheysen J, Pyka G, Hannard F, Arseenko M, Villanova J, Brinek A, Chirazi A, Jiang L, Simar A. Correlative Microscopy Discovers Self-Healing of AM-Build Al-Mg Alloy. Microsc Microanal 2023; 29:1981-1982. [PMID: 37612913 DOI: 10.1093/micmic/ozad067.1026] [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] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- B Winiarski
- Thermo Fisher Scientific, Brno, Czech Republic
| | - J Gheysen
- Université Catholique de Louvain, Louvain-la-Neuve, Belgique
| | - G Pyka
- Université Catholique de Louvain, Louvain-la-Neuve, Belgique
| | - F Hannard
- Université Catholique de Louvain, Louvain-la-Neuve, Belgique
| | - M Arseenko
- Université Catholique de Louvain, Louvain-la-Neuve, Belgique
| | - J Villanova
- ESRF - The European Synchrotron Radiation Facility, Grenoble, France
| | - A Brinek
- CEITEC - Central European Institute of Technology, Brno, Czech Republic
| | - A Chirazi
- Thermo Fisher Scientific, Bordeaux, France
| | - L Jiang
- Thermo Fisher Scientific, Hillsboro, Oregon, USA
| | - A Simar
- Université Catholique de Louvain, Louvain-la-Neuve, Belgique
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23
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Zhang S, He CF, Cai XZ, Jiang L, Wu XW, Jin Y, Mei LY. [Comparative study of surgical effects on patients with mixed deafness and otosclerosis with different air bone conduction differences]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:666-671. [PMID: 37455111 DOI: 10.3760/cma.j.cn115330-20230616-00283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Objective: To analyze the surgical efficacy of patients with mixed hearing loss and otosclerosis with different air bone gap (ABG) before surgery, and to provide reference for the prognosis evaluation of otosclerosis surgery. Methods: The clinical data of 108 cases(116 ears) of otosclerosis who had undergone stapes fenestration technique artificial stapes implantation in Xiangya Hospital of Central South University from November 2013 to May 2020 and had mixed hearing loss before surgery were collected, including 71 women(76 ears)and 37 men (40 ears), with an average age of 38.5 years. According to preoperative pure tone audiometry ABG, they were divided into three groups: group S, 15 dB≤ABG<31 dB, a total of 39 ears; group M, 31 dB≤ABG<46 dB, a total of 58 ears; and group L, ABG≥46 dB, 19 ears in total. The hearing outcomes of three groups of patients at 6-12 months after surgery were compared and analyzed using SPSS 24.0 statistical software. Results: A total of 3 patients (group S: 2 cases; group L: 1 case) experienced severe sensorineural hearing loss after surgery and were not included in the statistical analysis. After surgery, the pure tone hearing threshold of patients with otosclerosis in each group was significantly improved compared to before surgery, with an average air conduction threshold improvement of(21.6±13.4) dB. The difference between before and after surgery was statistically significant(t=17.13, P<0.01). The average bone conduction threshold improved by(3.7±7.6) dB, and the difference was statistically significant before and after surgery(t=5.20, P<0.01). The postoperative ABG was(18.3±9.3) dB, which was significantly reduced compared to preoperative(36.2±8.6)dB. Among the three groups of patients, the L group had the highest improvement in air conduction threshold[(29.9±10.8)dB], while the S group had the lowest improvement[(15.7±11.4)dB]. There was no statistically significant difference in post operative pure tone hearing thresholds between the three groups(P>0.05). The postoperative ABG in group S was the smallest[(16.5±9.0)dB], while in group L, the postoperative ABG was the largest[(20.5±10.0)dB]. Compared with group S, group M and group L still had a large residual ABG at 2 000 Hz after surgery. The bone conduction threshold of both S and M groups improved to some extent after surgery compared to before (P<0.01). Conclusions: Surgery can benefit patients with mixed hearing loss and otosclerosis with different preoperative ABG. Patients with small preoperative ABG have better surgical results and ideal ABG closure at all frequencies after surgery. Patients with large preoperative ABG can significantly increase the gas conduction threshold during surgery, but certain frequencies of ABG may still be left behind after surgery. The improvement effect of surgery on bone conduction threshold is not significant. Patients should be informed of treatment methods such as hearing aids based on their actual situation for selection.
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Affiliation(s)
- S Zhang
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - C F He
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - X Z Cai
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - L Jiang
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - X W Wu
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - Y Jin
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
| | - L Y Mei
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central SouthUniversity, Key Laboratory of Otorhinolaryngology, Hunan Province, Changsha 410008, China
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Liu T, Jiang L, Bai Q, Wu S, Yu X, Wu T, Wang J, Zhang X, Li H, Zhao K, Wang L. CLDN6 Suppresses Migration and Invasion of MCF-7 and SKBR-3 Breast Cancer Cells by Blocking the SMAD/Snail/MMP-2/9 Axis. Bull Exp Biol Med 2023; 175:376-381. [PMID: 37566248 DOI: 10.1007/s10517-023-05871-6] [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: 09/23/2022] [Indexed: 08/12/2023]
Abstract
The study examined the mechanisms of action of signal protein claudin 6 (CLDN6) on migration and invasion of breast cancer cell lines MCF-7 and SKBR-3. To this end, the signal proteins SMAD were blocked with their inhibitor SB431542, the genes CLDN6 and SNAIL were knocked down with short hairpin RNAs, and MMP2 and MMP9 were inhibited with TIMP-1. Expressions of MMP2 and MMP9 mRNAs were evaluated by reverse transcription PCR, Expressions of MMP-2, MMP-9, E-cadherin, N-cadherin, and vimentin were examined by Western blotting. Migration and invasion were analyzed by scratch test and Matrigel invasion assay. SB431542 inhibited expression of MMP2 and MMP9 in both cell lines. Single use of SB431542 inhibited expression of MMP-2/MMP-9 and corresponding mRNAs, but subsequent silencing of CLDN6 gene reversed this effect. TIMP-1 reversed down-regulation of E-cadherin, upregulation of N-cadherin and vimentin, facilitation of migration and invasion evoked by CLDN6 knocking down. Silencing of SNAIL gene inhibited migration and invasion, upregulated the expression of E-cadherin, and down-regulated expression of MMP2, MMP 9, N-cadherin, and vimentin. Thus, CLDN6 suppresses the epithelial-mesenchymal transition, migration, and invasion via blocking SMAD/Snail/MMP-2/9 signaling pathway in MCF-7 and SKBR-3 cancer cell lines.
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Affiliation(s)
- T Liu
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - L Jiang
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - Q Bai
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - S Wu
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - X Yu
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - T Wu
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - J Wang
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - X Zhang
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - H Li
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - K Zhao
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China
| | - L Wang
- Basic Pathology Department, Pathology College, Qiqihar Medical University, Qiqihar City, Heilongjiang Province, China.
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector. Phys Rev Lett 2023; 130:231802. [PMID: 37354393 DOI: 10.1103/physrevlett.130.231802] [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] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 06/26/2023]
Abstract
We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40} cm^{2}/Ar, where statistical and systematic uncertainties are combined.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Luo P, Hu W, Xu R, Wang Y, Li X, Jiang L, Chang S, Wu D, Li G, Dai Y. Enabling early detection of knee osteoarthritis using diffusion-relaxation correlation spectrum imaging. Clin Radiol 2023:S0009-9260(23)00224-6. [PMID: 37336674 DOI: 10.1016/j.crad.2023.05.013] [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: 03/20/2023] [Revised: 05/11/2023] [Accepted: 05/23/2023] [Indexed: 06/21/2023]
Abstract
AIM To present a technique that enables detection of early stage OA of the knee using diffusion-relaxation correlation spectrum imaging (DR-CSI). MATERIALS AND METHODS Fifty-five early osteoarthritis patients (OA, Kellgren-Lawrence [KL] score 1 to 2; mean age, 56.4 years) and 49 healthy volunteers (mean age, 56.7 years) were underwent magnetic resonance imaging (MRI) with T2-mapping and DR-CSI techniques. Maps of mean apparent diffusion coefficient (ADC), T2 relaxation time and volume fraction Vi for DR-CSI compartment i (A, B, C, D) sensitivity, specificity, and positive and negative likelihood ratio (PLR, NLR) were assessed to determine the diagnostic accuracy for detection of early-stage degeneration of knee articular cartilage. The structural abnormalities of articular cartilage were evaluated using modified Whole-Organ MR Imaging Scores (WORMS). RESULTS All intra- and interobserver agreements for DR-CSI compartment volume fractions and modified WORMS of cartilage were excellent. Early OA versus the controls had higher VC, lower VA and VB (p<0.001), but comparable VD (p>0.05). VA, VB and VC had a moderate association with WORMS. No significant correlation was identified between VD and WORMS. VC had better ability than VA,VB, VD, T2 and ADC to discriminate early OA patients from healthy controls (area under the curve, 0.898). Sensitivity, specificity, PLR, and NLR of VC with a cut-off value of 29.9% were 81.8% (95% confidence interval [CI], 69.1-90.9%), 95.9% (86-99.5%), 20.05% (5.13-78.34%), and 0.19% (0.11-0.33%). CONCLUSIONS DR-CSI compartment volume fractions may be sensitive indicators for detecting early-stage degeneration in knee articular cartilage.
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Affiliation(s)
- P Luo
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - W Hu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - R Xu
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Y Wang
- Department of Gastroenterology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - X Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - L Jiang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - S Chang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - D Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai 200062, China
| | - G Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
| | - Y Dai
- School of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China.
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Liu AN, Shen HQ, Xu CF, Jiang L, Shao J, Shu Q, Fu JF, Ni Y. [Characteristics of serum bile acids among healthy children in Zhejiang province]. Zhonghua Er Ke Za Zhi 2023; 61:509-514. [PMID: 37312461 DOI: 10.3760/cma.j.cn112140-20230127-00056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To characterize the serum bile acid profiles of healthy children in Zhejiang Province. Methods: A cross-sectional study was conducted on 245 healthy children who underwent imaging and laboratory biochemical tests during routine physical examinations at the Children's Hospital of Zhejiang University School of Medicine from January 2020 to July 2022. Overnight fasting venous blood samples were collected, and the concentrations of 18 individual bile acids in the serum were accurately quantitated using tandem mass spectrometry. The concentration difference of bile acid were compared between different genders and to explore the correlation between age and bile acid levels. Used the Mann-Whitney U test for intergroup comparison and Spearman test to correlation analysis. Results: A total of 245 health children with a age of 10 (8, 12) years including 125 boys and 120 girls. There were no significant differences in levels of total bile acids, primary and secondary bile acids, free and conjugated bile acids between the two gender groups (all P>0.05). The serum concentrations of ursodeoxycholic acid and glycoursodeoxycholic acid in girls were significantly higher than those in boys (199.0 (66.9, 276.5) vs. 154.7 (49.3, 205.0) nmol/L, 274.0 (64.8, 308.0) vs. 181.0 (43.8, 209.3) nmol/L, Z=2.06, 2.71, both P<0.05). The serum taurolithocholic acid in both boys and girls were positively correlated with age (r=0.31, 0.32, both P<0.05). The serum chenodeoxycholic acid and glycochenodeoxycholic acid in the boys group were positively correlated with age (r=0.20, 0.23, both P<0.05), whereas the serum tauroursodeoxycholic acid in the girls group was negatively correlated with age (r=-0.27, P<0.05), and the serum cholic acid was positively correlated with age (r=0.34, P<0.05). Conclusions: The total bile acid levels are relatively stable in healthy children in Zhejiang province. However, individual bile acids showed gender differences and were correlated with age.
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Affiliation(s)
- A N Liu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - H Q Shen
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - C F Xu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - L Jiang
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - J Shao
- Department of Child Healthcare, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - Q Shu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - J F Fu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - Y Ni
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
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Jin A, Xu H, Gao X, Sun S, Yang Y, Huang X, Wang X, Liu Y, Zhu Y, Dai Q, Bian Q, Jiang L. ScRNA-Seq Reveals a Distinct Osteogenic Progenitor of Alveolar Bone. J Dent Res 2023; 102:645-655. [PMID: 37148259 DOI: 10.1177/00220345231159821] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2023] Open
Abstract
The metabolism and remodeling of alveolar bone are the most active among the whole skeletal system, which is related to the biological characteristics and heterogeneity of the bone mesenchymal stromal cells (MSCs). However, there is a lack of systematic description of the heterogeneity of MSC-derived osteoblastic lineage cells as well as their distinct osteogenic differentiation trajectory of alveolar bone. In this study, we constructed a single-cell atlas of the mouse alveolar bone cells through single-cell RNA sequencing (scRNA-seq). Remarkably, by comparing the cell compositions between the alveolar bone and long bone, we uncovered a previously undescribed cell population that exhibits a high expression of protocadherin Fat4 (Fat4+ cells) and is specifically enriched around alveolar bone marrow cavities. ScRNA-seq analysis indicated that Fat4+ cells may initiate a distinct osteogenic differentiation trajectory in the alveolar bone. By isolating and cultivating Fat4+ cells in vitro, we demonstrated that they possess colony-forming, osteogenic, and adipogenic capabilities. Moreover, FAT4 knockdown could significantly inhibit the osteogenic differentiation of alveolar bone MSCs. Furthermore, we revealed that the Fat4+ cells exhibit a core transcriptional signature consisting of several key transcription factors, such as SOX6, which are involved in osteogenesis, and further demonstrated that SOX6 is required for the efficient osteogenic differentiation of the Fat4+ cells. Collectively, our high-resolution single-cell atlas of the alveolar bone reveals a distinct osteogenic progenitor that may contribute to the unique physiological characteristics of alveolar bone.
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Affiliation(s)
- A Jin
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - H Xu
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - X Gao
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - S Sun
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Y Yang
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - X Huang
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - X Wang
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Y Liu
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Y Zhu
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - Q Dai
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- The 2nd Dental Center, Ninth People's Hospital, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Q Bian
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Shanghai Institute of Precision Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - L Jiang
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Diseases, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
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29
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Wang MP, Xi XM, Zhu B, Lou R, Jiang Q, He Y, Jiang L. [Dose-response association between fluid overload and hospital mortality in patients with sepsis]. Zhonghua Nei Ke Za Zhi 2023; 62:513-519. [PMID: 37096277 DOI: 10.3760/cma.j.cn112138-20220516-00377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
Objective: To investigate dose-response associations between fluid overload (FO) and hospital mortality in patients with sepsis. Methods: The current cohort study was prospective and multicenter. Data were derived from the China Critical Care Sepsis Trial, which was conducted from January 2013 to August 2014. Patients aged≥18 years who were admitted to intensive care units (ICUs) for at least 3 days were included. Fluid input/output, fluid balance, fluid overload (FO), and maximum FO (MFO) were calculated during the first 3 days of ICU admission. The patients were divided into three groups based on MFO values: MFO<5%L/kg, MFO 5%-10%L/kg, and MFO≥10% L/kg. Kaplan-Meier analysis was used to predict time to death in hospital in the three groups. Associations between MFO and in-hospital mortality were evaluated via multivariable Cox regression models with restricted cubic splines. Results: A total of 2 070 patients were included in the study, of which 1 339 were male and 731 were female, and the mean age was (62.6±17.9) years. Of 696 (33.6%) who died in hospital, 968 (46.8%) were in the MFO<5%L/kg group, 530 (25.6%) were in the MFO 5%-10%L/kg group, and 572 (27.6%) were in the MFO≥10%L/kg group. Deceased patients had significantly higher fluid input than surviving patients during the first 3 days [7 642.0 (2 874.3, 13 639.5) ml vs. 5 738.0 (1 489.0, 7 153.5)ml], and lower fluid output [4 086.0 (1 367.0, 6 354.5) ml vs. 6 130.0 (2 046.0, 11 762.0) ml]. The cumulative survival rates in the three groups gradually decreased with length of ICU stay, and they were 74.9% (725/968) in the MFO<5% L/kg group, 67.7% (359/530) in the MFO 5%-10%L/kg group, and 51.6% (295/572) in the MFO≥10%L/kg group. Compared with the MFO<5%L/kg group, the MFO≥10%L/kg group had a 49% increased risk of inhospital mortality (HR=1.49, 95%CI 1.28-1.73). For each 1% L/kg increase in MFO, the risk of in-hospital mortality increased by 7% (HR=1.07, 95% CI 1.05-1.09). There was a"J-shaped"non-linear association between MFO and in-hospital mortality with a nadir of 4.1% L/kg. Conclusion: Higher and lower optimum fluid balance levels were associated with an increased risk of in-hospital mortality, as reflected by the observed J-shaped non-linear association between fluid overload and inhospital mortality.
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Affiliation(s)
- M P Wang
- Department of Critical Care Medicine,Xuanwu Hospital,Capital Medical University,Beijing 100053,China
| | - X M Xi
- Department of Critical Care Medicine,Fuxing Hospital,Capital Medical University,Beijing 100038,China
| | - B Zhu
- Department of Critical Care Medicine,Fuxing Hospital,Capital Medical University,Beijing 100038,China
| | - R Lou
- Department of Critical Care Medicine,Xuanwu Hospital,Capital Medical University,Beijing 100053,China
| | - Q Jiang
- Department of Critical Care Medicine,Fuxing Hospital,Capital Medical University,Beijing 100038,China
| | - Y He
- Department of Epidemiology and Health Statistics,School of Public Health,Capital Medical University, Beijing 100069, China
| | - L Jiang
- Department of Critical Care Medicine,Xuanwu Hospital,Capital Medical University,Beijing 100053,China
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Dai Q, Sun S, Jin A, Gong X, Xu H, Yang Y, Huang X, Wang X, Liu Y, Gao J, Gao X, Liu J, Bian Q, Wu Y, Jiang L. Osteoblastic RAR Inhibition Causes VAD-Like Craniofacial Skeletal Deformity. J Dent Res 2023; 102:667-677. [PMID: 37036085 DOI: 10.1177/00220345231151691] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2023] Open
Abstract
Retinoid signaling disorders cause craniofacial deformity, among which infants with maternal vitamin A deficiency (VAD) exhibited malformation of the eye, nose, palate, and parietal and jaw bone. Previous research uncovered the pathogenesis of eye defect and cleft palate of VAD in mice, but the studies on craniofacial skeletal deformity met obstacles, and the cell/lineage and underlying mechanism remain unclear. The retinoic acid receptor (RAR) is the key transcription factor in retinoid signaling, but individual knockout cannot simulate pathway inhibition. Here, we conditionally expressed dominant-negative RARα mutation (dnRARα) in osteoblasts to specifically inhibit the transcription activity of RAR in mice, which mimics the craniofacial deformities caused by VAD in clinical cases: hypomineralization of cranial bones, mandibular deformity, and clavicular hypoplasia. Furthermore, we performed 3-dimensional reconstruction based on micro-computed tomography and confirmed the abnormalities in the shape, size, and ossification of craniofacial bones due to osteoblastic RAR inhibition. Histological analysis indicated that inhibition of RAR in osteoblasts impaired both bone formation and bone resorption, which was confirmed by transcriptome sequencing of the calvaria. Furthermore, mechanism investigation showed that inhibition of RAR in osteoblasts directly decreased osteoblast differentiation in a cell-autonomous manner by impairing osteogenic gene transcription and also inhibited osteoclast differentiation via osteoblast-osteoclast crosstalk by impairing Rankl transcription. In summary, osteoblastic RAR activity is critical to craniofacial skeletal development, and its dysfunction leads to skeletal deformities mimicking VAD craniofacial defects, providing a new insight for VAD pathogenesis.
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Affiliation(s)
- Q Dai
- The 2nd Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Department of Stomatology, Zhang Zhiyuan Academician Work Station, Hainan Western Central Hospital, Shanghai Ninth People's Hospital, Danzhou, Hainan, China
| | - S Sun
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - A Jin
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - X Gong
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - H Xu
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Y Yang
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - X Huang
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - X Wang
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Y Liu
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - J Gao
- The 2nd Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - X Gao
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - J Liu
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Q Bian
- Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Precision Medicine, Shanghai, China
| | - Y Wu
- The 2nd Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
| | - L Jiang
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology, Shanghai, China
- National Clinical Research Center for Oral Disease, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai, China
- Center of Craniofacial Orthodontics, Department of Oral and Cranio-maxillofacial Science, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Wang TT, Cao QY, Zhang ZP, Guo YB, Cui L, Zhang Y, Zhang Y, Wang MP, Jiang L. [The predictive value of warning scores for intensive care unit admission in coronavirus disease 2019 patients]. Zhonghua Nei Ke Za Zhi 2023; 62:433-437. [PMID: 37032140 DOI: 10.3760/cma.j.cn112138-20220414-00277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
To evaluate the predictive value of early warning scores for intensive care unit (ICU) admission in patients with coronavirus disease 2019 (COVID-19). For COVID-19 patients who were admitted to Shijiazhuang People's Hospital from January 2021 to February 2021, national early warning score (NEWS), national early warning score 2 (NEWS2), rapid emergency medicine score (REMS), quick sepsis-related organ failure (qSOFA), altered consciousness, blood urea nitrogen, respiratory rate, blood pressure, and age-65 (CURB-65) were used to evaluate the inpatient condition and the predictive value for ICU admission. A total of 368 patients were included, and 32 patients (8.7%) were transferred to the ICU. The median age was 49.0 (34.0,61.0) years. The scores of NEWS, NEWS2, REMS, and CURB-65 were 1 (0, 2), 1 (0, 2), 4 (2, 6) and 0 (0, 1), respectively. The receiver operating characteristic (ROC) cure (AUC) was used to evaluate the predictive value in detecting patients who are at risk of being transferred to the ICU. Area under the ROC AUC of NEWS was 0.756, sensitivity 65.6%, and specificity 71.3%. ROC AUC of NEWS2 was 0.732, sensitivity 62.5%, and specificity 61.3%. ROC AUC of REMS was 0.787, sensitivity 84.4%, and specificity 64.6%. ROC AUC of CURB-65 was 0.814, sensitivity 81.3%, and specificity 76.8%. The predictive value of NEWS and NEWS2 combined with age were significantly improved. The ROC AUC of NEWS combined with age was 0.885, sensitivity 85.1%, and specificity 75.0%. The ROC AUC of NEWS2 combined with age was 0.883, sensitivity 84.2%, and specificity 75.0%. NEWS and NEWS2 combined with age can be used as a predictive tool for whether COVID-19 patients will be admitted to the ICU.
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Affiliation(s)
- T T Wang
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Q Y Cao
- Shijiazhuang People's Hospital, Shijiazhuang 050051, China
| | - Z P Zhang
- Shijiazhuang People's Hospital, Shijiazhuang 050051, China
| | - Y B Guo
- Department of Urology, Shijiazhuang People's Hospital, Shijiazhuang 050051, China
| | - L Cui
- Department of Geriatrics, Shijiazhuang People's Hospital, Shijiazhuang 050051, China
| | - Y Zhang
- Shijiazhuang People's Hospital, Shijiazhuang 050051, China
| | - Y Zhang
- Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu 610041, China
| | - M P Wang
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - L Jiang
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
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Jiang L, Jiang S, Luo Q. 88P Quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00343-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: 04/04/2023]
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33
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Chen Y, Tu L, Jiang L, Ji HX. [Analysis of serum CA125 and related influencing factors in silicosis patients with pulmonary heart disease]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2023; 41:209-212. [PMID: 37006147 DOI: 10.3760/cma.j.cn121094-20211115-00563] [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] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
Objective: To analyze the serum carbohydrate antigen 125 (CA125) level and its influencing factors in male silicosis patients with pulmonary heart disease. Methods: In October 2021, data of 38 male patients with simple silicosis (silicosis group), 28 cases of silicosis with pulmonary heart disease (pulmonary heart disease group), and 27 healthy controls (control group) in the same age group were collected in inpatient and outpatient of Nanjing Occupational Disease Prevention and Control Hospital from January 2017 to December 2020. The serum CA125 levels of the three groups were compared, and the correlation between disease-related indexes and serum CA125 in silicosis patients with pulmonary heart disease was analyzed, as well as the influencing factors of pulmonary heart disease and serum CA125 levels in silicosis patients. Results: The serum CA125 level[ (19.95±7.52) IU/ml] in pulmonary heart disease group was higher than that in silicosis group[ (12.98±6.35) IU/ml] and control group[ (9.17±5.32) IU/ml] (P<0.05). There was no significant difference in serum CA125 level between the silicosis group and the control group (P>0.05). Serum CA125 levels were positively correlated with blood uric acid and fasting blood glucose in silicosis patients with pulmonary heart disease (r=0.39, 0.46, P<0.05). Serum CA125 level was a risk factor for silicosis patients with pulmonary heart disease (OR=1.13, 95%CI: 1.02-1.24, P<0.05). Dust exposure time, lactate dehydrogenase and smoking history were positively correlated with serum CA125 level in silicosis patients (P<0.05) . Conclusion: The serum CA125 level of male silicosis patients with pulmonary heart disease is significantly increased, and the level of CA125 is correlated with the level of fasting blood glucose and blood uric acid.
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Affiliation(s)
- Y Chen
- Department of Occupational Diseases, Nanjing Occupational Disease Prevention and Control Hospital, Nanjing 210042, China
| | - L Tu
- Department of Pharmacy, Nanjing Occupational Disease Prevention and Control Hospital, Nanjing 210042, China
| | - L Jiang
- Laboratory of Nanjing Occupational Disease Prevention and Control Hospital, Nanjing 210042, China
| | - H X Ji
- Department of Occupational Diseases, Nanjing Occupational Disease Prevention and Control Hospital, Nanjing 210042, China
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Ji Y, Xie R, Wu C, Liu X, Zhang X, Jiang L. Cost-effective carbon-based amine adsorbents for carbon capture: Equilibrium, kinetics and selectivity. J CO2 UTIL 2023. [DOI: 10.1016/j.jcou.2023.102422] [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: 02/08/2023]
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35
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Sotirchos V, Zhan C, Haghani L, Zhao K, Alexander E, Jiang L, Marinelli B, Silk M, Yarmohammadi H, Ziv E, Sofocleous C, Solomon S, Erinjeri J. Abstract No. 252 Comparison of Perioperative and Procedure Room Times Between Moderate Sedation and Monitored Anesthesia Care in Interventional Radiology. J Vasc Interv Radiol 2023. [DOI: 10.1016/j.jvir.2022.12.316] [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: 02/27/2023] Open
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Bazhenova L, Chih-Hsin Yang J, Wang M, Mitchell P, Camidge DR, Fang J, Nian W, Chiu CH, Zhou J, Zhao Y, Su WC, Yang TY, Zhu V, Millward M, Fan Y, Huang WT, Cheng Y, Jiang L, Zheng L, Janne P. OA01.07 Sunvozertinib in NSCLC Patients with EGFR Exon20 Insertion Mutations. J Thorac Oncol 2023. [DOI: 10.1016/j.jtho.2022.09.123] [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: 01/30/2023]
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37
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Chen Y, Zhu P, Xu JJ, Song Y, Jiang L, Gao LJ, Chen J, Song L, Gao Z, Liu HB, Yang YJ, Gao RL, Xu B, Yuan JQ. [Clinical features and long-term prognosis of diabetic patients with low or intermediate complexity coronary artery disease post percutaneous coronary intervention]. Zhonghua Xin Xue Guan Bing Za Zhi 2023; 51:143-150. [PMID: 36789593 DOI: 10.3760/cma.j.cn112148-20220601-00432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Objective: To investigate the clinical features and long-term prognostic factors of diabetic patients with low or intermediate complexity coronary artery disease (CAD) post percutaneous coronary intervention (PCI). Methods: This was a prospective, single-centre observational study. Consecutive diabetic patients with SYNTAX score (SS)≤32 undergoing PCI between January and December 2013 in Fuwai hospital were included in this analysis. The patients were divided into two groups based on SS, namely SS≤22 group and SS 23-32 group. Multivariate Cox regression analysis was performed to identify independent factors related to poor 5-year prognosis. The primary outcomes were cardiac death and recurrent myocardial infarction, the secondary outcomes were all cause death and revascularization. Results: Of the 3 899 patients included in the study, 2 888 were men (74.1%); mean age was 59.4±9.8 years. There were 3 450 patients in the SS≤22 group and 449 patients in the SS 23-32 group. Compared with SS≤22 group, the incidence of revascularization was higher in SS 23-32 group (18.9% (85/449) vs. 15.2% (524/3450), log-rank P=0.019). There was no significant difference in all-cause death, cardiac death and recurrent myocardial infarction between the two groups (log-rank P>0.05). Multivariate Cox regression analysis showed that age (HR=1.05, 95%CI 1.02-1.08, P<0.001), chronic obstructive pulmonary disease (HR=3.12, 95%CI 1.37-7.07, P=0.007) and creatinine clearance rate (CCr)<60 ml/min (HR=3.67, 95%CI 2.05-6.58, P<0.001) were independent risk factors for 5-year cardiac death, while left ventricular ejection fraction (HR=0.94, 95%CI 0.91-0.96, P<0.001) was a protective factor. Previous PCI (HR=2.04, 95%CI 1.38-3.00, P<0.001), blood glucose level≥11.1 mmol/L on admission (HR=2.49, 95%CI 1.32-4.70, P=0.005) and CCr<60 ml/min (HR=1.85, 95%CI 1.14-2.99, P=0.012) were independent risk factors for 5-year recurrent myocardial infarction. The SS of 23-32 was independently associated with risk of revascularization (HR=1.54, 95%CI 1.09-2.16, P=0.014), after adjusting for residual SS. Residual SS was not a risk factor for 5-year prognosis. Conclusions: In diabetic patients with low-or intermediate complexity CAD, SS 23-32 is associated with increased risk of 5-year revascularization; the clinical characteristics of the patients are associated with the long-term mortality and recurrent myocardial infarction, but not related to revascularization.
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Affiliation(s)
- Y Chen
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - P Zhu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - J J Xu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Y Song
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - L Jiang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - L J Gao
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - J Chen
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - L Song
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Z Gao
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - H B Liu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Y J Yang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - R L Gao
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - B Xu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - J Q Yuan
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
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Piribauer M, Jiang L, Kostov T, Parr M, Steidel S, Bizjak DA, Steinacker JM, Diel P. Combinatory in vitro effects of the β2-agonists salbutamol and formoterol in skeletal muscle cells. Toxicol Lett 2023; 378:10-18. [PMID: 36822333 DOI: 10.1016/j.toxlet.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/13/2023] [Accepted: 02/15/2023] [Indexed: 02/25/2023]
Abstract
β2-agonists are used for the treatment of bronchoconstriction, but also abused in doping. Beside an ergogenic activity β2-agonists may have also anabolic activity. Therefore, we investigated the anabolic activity and associated molecular mechanisms of Salbutamol (SAL) and Formoterol (FOR) alone, as well as in combination in C2C12 myotubes. In differentiated C2C12 cells, dose-dependent effects of SAL and FOR (alone/in combination) on myotube diameter, myosin heavy chain (MHC) protein expression and the mRNA expression of genes involved in hypertrophy were analyzed. β2-adrenoceptor 2 (ADRB2), androgen receptor (AR) and estrogen receptor (ER) inhibitors, as well as dexamethasone (Dexa) were co-incubated with the β2-agonists and myotube diameter was determined. SAL and FOR treatment significantly induced hypertrophy and increased MHC expression and the mRNA expression of Igf1, mTOR, PIk3r1 and AMpKa2. In contrast to an ER inhibitor, the ADRB2 and AR inhibitors, as well as Dexa antagonized FOR and SAL induced hypertrophy. Combined treatment with SAL and FOR resulted in significant additive effects on myotube diameter and MHC expression. Future clinical studies are needed to prove this effect in humans and to evaluate this finding with respect to antidoping regulations.
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Affiliation(s)
- M Piribauer
- Department of Molecular and Cellular Sports Medicine, German Sports University Cologne, Cologne, Germany
| | - L Jiang
- Department of Molecular and Cellular Sports Medicine, German Sports University Cologne, Cologne, Germany; Division of Sports and Rehabilitation Medicine, Department of Medicine, University Hospital Ulm, Ulm, Germany
| | - T Kostov
- Department of Molecular and Cellular Sports Medicine, German Sports University Cologne, Cologne, Germany
| | - M Parr
- Institute of Pharmaceutical and Medicinal Chemistry, Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Germany
| | - S Steidel
- Department of Molecular and Cellular Sports Medicine, German Sports University Cologne, Cologne, Germany
| | - D A Bizjak
- Division of Sports and Rehabilitation Medicine, Department of Medicine, University Hospital Ulm, Ulm, Germany
| | - J M Steinacker
- Division of Sports and Rehabilitation Medicine, Department of Medicine, University Hospital Ulm, Ulm, Germany
| | - P Diel
- Department of Molecular and Cellular Sports Medicine, German Sports University Cologne, Cologne, Germany.
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Adnouni M, Jiang L, Zhang X, Zhang L, Pathare PB, Roskilly A. Computational modelling for decarbonised drying of agricultural products: Sustainable processes, energy efficiency, and quality improvement. J FOOD ENG 2023. [DOI: 10.1016/j.jfoodeng.2022.111247] [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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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Constraints on Light Sterile Neutrino Oscillations from Combined Appearance and Disappearance Searches with the MicroBooNE Detector. Phys Rev Lett 2023; 130:011801. [PMID: 36669216 DOI: 10.1103/physrevlett.130.011801] [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] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current ν_{e} and ν_{μ} interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×10^{20} protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm_{41}^{2} and the sterile neutrino mixing angles θ_{μe} and θ_{ee}, excluding part of the parameter space allowed by experimental anomalies. Cancellation of ν_{e} appearance and ν_{e} disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Liu T, Jiang L, Bai Q, Wu S, Yu X, Wu T, Wang J, Zhang X, Li H, Zhao K, Wang L. CLDN6 suppresses migration and invasion via blocking SMADs/Snail/MMP-2/9 axis in MCF-7 and SKBR-3 cell lines. Bull Exp Biol Med 2023. [DOI: 10.47056/0365-9615-2023-175-3-360-366] [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: 03/29/2023]
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Wang MP, Jiang L, Zhu B, Lou R, He Y, Jiang Q, Xi XM. [Association between fluid balance and clinical outcomes in sepsis patients with identified subtypes]. Zhonghua Yi Xue Za Zhi 2022; 102:3756-3762. [PMID: 36517425 DOI: 10.3760/cma.j.cn112137-20220516-01068] [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] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To identify clinical subphenotypes of sepsis by clinical variables, and the association between fluid balance (FB) and outcomes in sepsis patients with different subphenotypes. Methods: Data were derived from China Critical Care Sepsis Trial. A total of 2 075 patients were included in the study, with a mean age of (62.5±17.4) years, 1 362 (65.6%) were male, 713 (34.3%) were female. In-hospital mortality was the primary outcome. Clinical variables were entered into the latent profile analysis (LPA) model which was used to identify the subphenotypes of sepsis. Multivariable logistic regression model was used to explore the association of FB on the first 2 days admitted to ICU and in-hospital mortality. Results: Total of 687 (33.1%) patients died in the hospital. Four subphenotypes of sepsis were identified by the PLA model: 1 421 (68.5%) patients were identified as profile 1, which was characterized by the lowest in-hospital mortality (28.3%, 402/1 421) and was considered as the baseline subphenotype; profile 2 was characterized by multiple organ dysfunction(232, 11.2%); profile 3 was characterized by respiratory dysfunction (196, 9.4%) and profile 4 was characterized by kidney injury/failure (226, 10.9%). Profile 2 showed the highest in-hospital mortality (54.3%, 126/232), followed by profile 4 (39.4%, 89/226), profile 3 (35.7%, 70/196). Profile 2 had the highest FB of 68.5(34.7, 89.4)ml/kg on day 1 and decreased rapidly to 29.4(13.6, 49.8) ml/kg on day 2. Multivariable analysis showed that for every 10 ml/kg of FB increased on the first 48 hours admitted to ICU, the risk of in-hospital mortality decreased 14% (OR=0.86, 95%CI: 0.81-0.97) in profile 2, and increased 4% (OR=1.04, 95%CI:1.02-1.07) in profile 4. However, there were no significant association between FB on the fist 2 days admitted to ICU and the risk of in-hospital mortality in profile 1 (OR=1.06, 95%CI: 0.94-1.19)and in profile 3 (OR=0.99, 95%CI: 0.94-1.05). Conclusions: Four subphenotypes of sepsis were identified according to the clinical variables, which showed different characteristics, distributions, outcomes and responses to fluid balance.
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Affiliation(s)
- M P Wang
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - L Jiang
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - B Zhu
- Department of Critical Care Medicine, Fuxing Hospital, Capital Medical University, Beijing 100038, China
| | - R Lou
- Department of Critical Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Y He
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Q Jiang
- Department of Critical Care Medicine, Fuxing Hospital, Capital Medical University, Beijing 100038, China
| | - X M Xi
- Department of Critical Care Medicine, Fuxing Hospital, Capital Medical University, Beijing 100038, China
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Shi A, Li L, Yang D, Min Y, Jiang L, Dong X, Deng W, Yu H, Yu R, Zhao J. 98P First-line atezolizumab/durvalumab plus platinum-etoposide combined with radiotherapy in extensive-stage small cell lung cancer. Immuno-Oncology and Technology 2022. [DOI: 10.1016/j.iotech.2022.100202] [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: 12/13/2022]
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Yi JR, Li ZN, Xie HQ, Chen BM, Jiang L, Qian LX, Xu HG, Li SR, Lei ZZ, Chen JD, Zhou J. [Effects and mechanism of human umbilical vein endothelial cells-derived exosomes on wound healing in diabetic rabbits]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2022; 38:1023-1033. [PMID: 36418259 DOI: 10.3760/cma.j.cn501225-20220622-00254] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: The investigate the effects and mechanism of exosomes derived from human umbilical vein endothelial cells (HUVECs) on wound healing in diabetes rabbits. Methods: The experimental research methods were used. The primary vascular endothelial cells (VECs) and human skin fibroblasts (HSFs) were extracted from skin tissue around ulcer by surgical excision of two patients with diabetic ulcer (the male aged 49 years and the female aged 58 years) admitted to Xiangya Third Hospital of Central South University in June 2019. The cells were successfully identified through morphological observation and flow cytometry. The HUVEC exosomes were extracted by ultracentrifugation and identified successfully by morphological observation, particle size detection, and Western blotting detection. Twenty female 3-month-old New Zealand rabbits were taken to create one type 2 diabetic full-thickness skin defect wound respectively on both sides of the back. The wounds were divided into exosomes group and phosphate buffer solution (PBS) group and treated accordingly, with 20 wounds in each group, the time of complete tissue coverage of wound was recorded. On PID 14, hematoxylin-eosin staining or Masson staining was performed to observe angiogenesis or collagen fiber hyperplasia (n=20). The VECs and HSFs were co-cultured with HUVEC exosomes for 24 h to observe the uptake of HUVEC exosomes by the two kinds of cells. The VECs and HSFs were divided to exosome group treated with HUVEC exosomes and PBS group treated with PBS to detect the cell proliferation on 4 d of culture with cell count kit 8, to detect and calculate the cell migration rate at 24 and 48 h after scratch by scratch test, to detect the cell migration number at 24 h of culture with Transwell test, and to detect the mRNA expressions of nuclear factor-erythroid 2-related factor 2 (NRF2) and transcription activating factor 3 (ATF3) by real time fluorescence quantitative reverse transcription polymerase chain reaction. Besides, the number of vascular branches and vascular length were observed in the tube forming experiment after 12 h of culture of VECs (n=3). The VECs and HSFs were taken and divided into PBS group and exosome group treated as before, and NRF2 interference group, ATF3 interference group, and no-load interference group with corresponding gene interference. The proliferation and migration of the two kinds of cells, and angiogenesis of VECs were detected as before (n=3). Data were statistically analyzed with analysis of variance for repeated measurement, one-way analysis of variance, independent sample t test, and least significant difference test. Results: The time of complete tissue coverage of wound in exosome group was (17.9±1.9) d, which was significantly shorter than (25.2±2.3) d in PBS group (t=4.54, P<0.05). On PID14, the vascular density of wound in PBS group was significantly lower than that in exosome group (t=10.12, P<0.01), and the collagen fiber hyperplasia was less than that in exosome group. After 24 h of culture, HUVEC exosomes were successfully absorbed by VECs and HSFs. The proliferative activity of HSFs and VECs in exosome group was significantly higher than that in PBS group after 4 d of culture (with t values of 54.73 and 7.05, respectively, P<0.01). At 24 and 48 h after scratch, the migration rates of HSFs (with t values of 3.42 and 11.87, respectively, P<0.05 or P<0.01) and VECs (with t values of 21.42 and 5.49, respectively, P<0.05 or P<0.01) in exosome group were significantly higher than those in PBS group. After 24 h of culture, the migration numbers of VECs and HSFs in exosome group were significantly higher than those in PBS group (with t values of 12.31 and 16.78, respectively, P<0.01). After 12 h of culture, the mRNA expressions of NRF2 in HSFs and VECs in exosome group were significantly higher than those in PBS group (with t values of 7.52 and 5.78, respectively, P<0.05 or P<0.01), and the mRNA expressions of ATF3 were significantly lower than those in PBS group (with t values of 13.44 and 8.99, respectively, P<0.01). After 12 h of culture, the number of vascular branches of VECs in exosome group was significantly more than that in PBS group (t=17.60, P<0.01), and the vascular length was significantly longer than that in PBS group (t=77.30, P<0.01). After 4 d of culture, the proliferation activity of HSFs and VECs in NRF2 interference group was significantly lower than that in PBS group and exosome group (P<0.05 or P<0.01); the proliferation activity of HSFs and VECs in ATF3 interference group was significantly higher than that in PBS group (P<0.05 or P<0.01) and significantly lower than that in exosome group (P<0.05 or P<0.01). At 24 and 48 h after scratch, the migration rates of HSFs and VECs in ATF3 interference group were significantly higher than those in PBS group (P<0.05 or P<0.01) and significantly lower than those in exosome group (P<0.05 or P<0.01). At 24 and 48 h after scratch, the migration rates of HSFs and VECs in NRF2 interference group were significantly lower than those in PBS group and exosome group (P<0.05 or P<0.01). After 24 h of culture, the migration numbers of VECs and HSFs in ATF3 interference group were significantly more than those in PBS group (P<0.05) and significantly less than those in exosome group (P<0.05 or P<0.01); the migration numbers of VECs and HSFs in NRF2 interference group were significantly less than those in PBS group and exosome group (P<0.01). After 12 h of culture, the vascular length and number of branches of VECs in NRF2 interference group were significantly decreased compared with those in PBS group and exosome group (P<0.01); the vascular length and number of branches of VECs in ATF3 interference group were significantly increased compared with those in PBS group (P<0.01) and were significantly decreased compared with those in exosome group (P<0.01). Conclusions: HUVEC exosomes can promote the wound healing of diabetic rabbits by promoting the proliferation and migration of VECs and HSFs, and NRF2 and ATF3 are obviously affected by exosomes in this process, which are the possible targets of exosome action.
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Affiliation(s)
- J R Yi
- Department of Breast Cancer Surgery, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z N Li
- Department of Burns and Plastic Surgery, Xiangya Third Hospital, Central South University, Changsha 410006, China
| | - H Q Xie
- Department of Rehabilitation Medicine, Xiangya Third Hospital, Central South University, Changsha 410006, China
| | - B M Chen
- Department of Burns and Plastic Surgery, Xiangya Third Hospital, Central South University, Changsha 410006, China
| | - L Jiang
- Xiangya School of Medicine, Central South University, Changsha 410006, China
| | - L X Qian
- Department of Burns and Plastic Surgery, Xiangya Second Hospital, Central South University, Changsha 410004, China
| | - H G Xu
- Department of Neurosurgery, Changde First People's Hospital, Xiangya School of Medicine, Central South University, Changde 415003, China
| | - S R Li
- Department of Trauma Repair and Dermatologic Surgery, Taihe Hospital, Hubei Medical College, Shiyan 442000, China
| | - Z Z Lei
- Department of Burn Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410005, China
| | - J D Chen
- Department of Burns and Plastic Surgery, Xiangya Third Hospital, Central South University, Changsha 410006, China
| | - Jianda Zhou
- Department of Burns and Plastic Surgery, Xiangya Third Hospital, Central South University, Changsha 410006, China
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Jiang L, Zhou J, Zhong D, Zhou Y, Zhang W, Wu W, Zhao Z, Wang W, Xu W, He L, Ma Y, Hu Y, Zhang W, Li J. Correction: Overexpression of SMC4 activates TGFβ/Smad signaling and promotes aggressive phenotype in glioma cells. Oncogenesis 2022; 11:68. [DOI: 10.1038/s41389-022-00442-2] [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: 11/19/2022] Open
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Jiang L, Lyu Q, Abdelhamid A, Hui S, Sheng K. A Sparse Orthogonal Collimators System for Experiments on Small-Animal Scale. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.608] [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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Wu YL, Zhao J, Hu J, Wu J, Xu Y, Yang Z, Liu Z, Jiang L, Chen J, Yu Y, Huang M, Dong X, Liu L, Feng W, Wu L, Cang S, Sun J, Xie Q, Chen HJ. 388P Capmatinib in Chinese adults with EGFR wt, ALK rearrangement negative (ALK-R−), MET exon 14 skipping mutation (METex14), advanced NSCLC: Results from the phase II GEOMETRY-C study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.425] [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: 12/07/2022] Open
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Yang J, Zhou J, M. li, Zhang ZY, Cheng Y, Chu D, Pan H, Wang B, Chen G, Wang K, Jiang L, Hu Y, Shi J, Hui AM, Zhou Y, Wu Z, Sun J, Tan Y, Xiang X, Wu YL. 392P A phase II study of SAF-189s in patients with advanced ROS1 fusion-positive non-small cell lung cancer. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.429] [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: 12/07/2022] Open
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Jiang L, Wan RX, Li JT, Yan Y. Comparative effectiveness of exercise-based cardiac rehabilitation for heart failure: a Bayesian network analysis of 44 randomized trials and 5896 patients. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.994] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Introduction
The prevalence of heart failure (HF) is increasing nowadays. Exercise-based cardiac rehabilitation (CR) reduces mortality and further improves the outcome of patients with HF. However, the effect of different types of CR on HF remains unclear. Data comparing these CR have not been synthesized. Thus, the purpose of this study is to determine the relative efficacy of different types of exercise-based CR for individuals with HF using a Bayesian network meta-analysis.
Methods
We followed a pre-specified protocol (PROSPERO: CRD42021278351). We conducted a systematic literature review of any randomized controlled trials which evaluated exercise-based CR for patients with HF. Databases including Embase, Medline, the Cochrane Central Register of Controlled Trials, and Web of Science were screened up to 31 December 2021. The primary outcomes focus on functional capacity (peak oxygen uptake and 6-minute walk distance) and health-related quality of life (hr-QOL). The main analysis was complemented by network subanalysis, standard pairwise comparisons, and subgroup and sensitivity analyses. The pooled estimates were quantified as mean differences (MD) or standardized mean difference (SMD)where appropriate, at 95% confidence intervals (CI).
Results
We identified 44 randomized controlled trials with a total of 5896 HF participants. Among 23 studies that compared exercise-based CR and usual care, participants in center-based CR (CBCR) had improvement of peak oxygen uptake (MD: 2.30 mL/kg per minute; 95% CI, 0.43–4.40) and 6-minute walk distance (MD: 33 meters; 95% CI, 11.00–58.00).18 studies that compared exercise-based CR with usual care showed that CBCR and cardiac telerehabilitation (CTR) had greater improvements in hr-QOL (SMD: −0.38; 95% CI, −0.49 to −0.15 and SMD: −0.18,95% CI, −0.36 to −0.00 respectively). Treatment ranking indicated CTR has the highest probability (46.0%, 50.2%) of being the most effective CR for peak oxygen uptake and hr-QOL elevation respectively. CBCR was similarly indicated as the most effective treatment for 6-min walk distance (38.7%).
Conclusion
Exercise-based CR programs provide broader cardiovascular benefits compared with UC. CBCR significantly improved functional capacity. CBCR and CTR have favorable effects on hr-QOL.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): China Scholarship Council
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Affiliation(s)
- L Jiang
- University Hospital Ulm , Ulm , Germany
| | - R X Wan
- University of Washington , Seattle , United States of America
| | - J T Li
- Tsinghua University , Beijing , China
| | - Y Yan
- Nanjing Medical University , Nanjing , China
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Zhao Y, Huang S, Jia Y, Duan Y, Jin L, Zhai X, Wang H, Hu B, Liu Y, Liu A, Liu W, Zheng C, Li F, Sun L, Yuan X, Dai Y, Zhang B, Jiang L, Wang X, Wang H, Zhou C, Gao Z, Zhang L, Zhang Y. CLINICOPATHOLOGIC FEATURES AND PROGNOSIS OF PEDIATRIC HIGH-GRADE B-CELL LYMPHOMA: A MULTICENTER ANALYSIS. Leuk Res 2022. [DOI: 10.1016/s0145-2126(22)00254-5] [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: 11/06/2022]
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