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Wu KY, Ren YX, Ruan YM, Ma JL, Li CX, Wang Z. [The effect of the AIM2 inflammasome in noise-induced cognitive dysfunction in rats]. ZHONGHUA LAO DONG WEI SHENG ZHI YE BING ZA ZHI = ZHONGHUA LAODONG WEISHENG ZHIYEBING ZAZHI = CHINESE JOURNAL OF INDUSTRIAL HYGIENE AND OCCUPATIONAL DISEASES 2024; 42:332-339. [PMID: 38802305 DOI: 10.3760/cma.j.cn121094-20230915-00157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Objective: To explore the effect of the absent in melanoma 2 (AIM2) -mediated neuroinflammation in noise-induced cognitive dysfunction in rats. Methods: In April 2023, sixteen male Wistar rats were randomly divided into control group and noise group, with 8 rats in each group. The rats in the noise group were placed in 50 cm×50 cm×40 cm transparent boxes and exposed to 100 dB (A) white noise with a sound pressure level of 100 dB (A) (4 h/d for 30 d) . At the same time, rats in the control group were kept in similar boxes with environmental noise less than 60 dB (A) . After 30 days of noise exposure, the Morris water maze experiment was applied to test the learning and memory abilities of the rats; the pathological morphology of hippocampal tissues was observed by Hematoxylin-Eosin (HE) staining. Western blot was used to detect the protein expression levels of AIM2, cysteinyl aspartate specific proteinase-1 (caspase-1) , apoptosis-associated speck-like protein (ASC) , interleukin-1β (IL-1β) , IL-18, ionic calcium-binding articulation molecule-1 (Iba-1) , and glial fibrillary acidic protein (GFAP) . The expression of both Iba-1 and GFAP in hippocampal tissue was assessed by immunohistochemical staining. The co-localization of AIM2 with Iba-1 or GFAP was determined by immunofluorescence double staining. Results: Compared with the control group, the escape latency of rats in the noise group was increased by 16.29 s, 17.71 s, and 20.26 s on days 3, 4, and 5, respectively. On day 6, the noise-exposed rats spent shorter time in the target quadrant and had fewer times in crossing the platform[ (7.25±2.27) s and (1.13±0.64) times] than the control group[ (15.64±3.99) s and (4.25±2.12) times] (P<0.05) . After noise exposure, hippocampal neurons of rats displayed marked nuclear hyperchromatic and pyknosis phenomenon. The noise-exposed rats had higher numbers of both microglia and astrocytes (27.00±2.65 and 43.33±5.51) in the DG area of the hippocampus relative to the control group (14.67±3.06 and 20.00±4.58) (P<0.05) . Moreover, the glial cells in the noise group had larger cell cytosol with more and thicker branches. The protein expression levels of inflammatory cytokines Cleaved-IL-1β and Cleaved-IL-18 in the hippocampus of rats in the noise group (1.55±0.19 and 1.74±0.12) were significantly higher than the control group (1.00±0.11 and 1.00±0.13) (P<0.05) . After noise exposure, the protein expression levels of AIM2, Cleaved-Caspase-1 and ASC (1.19±0.09, 1.34±0.07 and 1.14±0.01) were higher than the control group (1.00±0.07, 1.00±0.14 and 1.00±0.06) and differences between the two groups were statistically significant (P<0.05) . A significant increase in the number of cells co-localizing AIM2 with Iba-1 or GFAP in the noise group (28.67±4.04 and 40.67±5.13) compared with the control group (15.67±4.04 and 17.67±3.79) , and statistically significant differences were observed between the two groups (P<0.05) . Conclusion: Noise exposure may activate the AIM2 inflammasome in hippocampal glial cells of rats, releasing excessive inflammatory cytokines and causing neuroinflammation that damages neurons.
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Azimuthal Angle Correlations of Muons Produced via Heavy-Flavor Decays in 5.02 TeV Pb+Pb and pp Collisions with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 132:202301. [PMID: 38829073 DOI: 10.1103/physrevlett.132.202301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 03/13/2024] [Indexed: 06/05/2024]
Abstract
Angular correlations between heavy quarks provide a unique probe of the quark-gluon plasma created in ultrarelativistic heavy-ion collisions. Results are presented of a measurement of the azimuthal angle correlations between muons originating from semileptonic decays of heavy quarks produced in 5.02 TeV Pb+Pb and pp collisions at the LHC. The muons are measured with transverse momenta and pseudorapidities satisfying p_{T}^{μ}>4 GeV and |η^{μ}|<2.4, respectively. The distributions of azimuthal angle separation Δϕ for muon pairs having pseudorapidity separation |Δη|>0.8, are measured in different Pb+Pb centrality intervals and compared to the same distribution measured in pp collisions at the same center-of-mass energy. Results are presented separately for muon pairs with opposite-sign charges, same-sign charges, and all pairs. A clear peak is observed in all Δϕ distributions at Δϕ∼π, consistent with the parent heavy-quark pairs being produced via hard-scattering processes. The widths of that peak, characterized using Cauchy-Lorentz fits to the Δϕ distributions, are found to not vary significantly as a function of Pb+Pb collision centrality and are similar for pp and Pb+Pb collisions. This observation will provide important constraints on theoretical descriptions of heavy-quark interactions with the quark-gluon plasma.
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Huerta Escamilla C, Simsek AE, Uniyal R, Vargas Hernandez AM, Chudasama R, Cooper SI, Gleyzer SV, Perez CU, Rumerio P, Usai E, West C, Yi R, Akpinar A, Albert A, Arcaro D, Cosby C, Demiragli Z, Erice C, Fontanesi E, Gastler D, Jeon S, Rohlf J, Salyer K, Sperka D, Spitzbart D, Suarez I, Tsatsos A, Yuan S, Benelli G, Coubez X, Cutts D, Hadley M, Heintz U, Hogan JM, Kwon T, Landsberg G, Lau KT, Li D, Luo J, Mondal S, Narain M, Pervan N, Sagir S, Simpson F, Stamenkovic M, Wong WY, Yan X, Zhang W, Abbott S, Bonilla J, Brainerd C, Breedon R, Calderon De La Barca Sanchez M, Chertok M, Citron M, Conway J, Cox PT, Erbacher R, Jensen F, Kukral O, Mocellin G, Mulhearn M, Pellett D, Wei W, Yao Y, Zhang F, Bachtis M, Cousins R, Datta A, Hauser J, Ignatenko M, Iqbal MA, Lam T, Manca E, Nash WA, Saltzberg D, Stone B, Valuev V, Clare R, Gordon M, Hanson G, Si W, Wimpenny S, Branson JG, Cittolin S, Cooperstein S, Diaz D, Duarte J, Gerosa R, Giannini L, Guiang J, Kansal R, Krutelyov V, Lee R, Letts J, Masciovecchio M, Mokhtar F, Pieri M, Quinnan M, Sathia Narayanan BV, Sharma V, Tadel M, Vourliotis E, Würthwein F, Xiang Y, Yagil A, Barzdukas A, Brennan L, Campagnari C, Collura G, Dorsett A, Incandela J, Kilpatrick M, Kim J, Li AJ, Masterson P, Mei H, Oshiro M, Richman J, Sarica U, Schmitz R, Setti F, Sheplock J, Stuart D, Wang S, Bornheim A, Cerri O, Latorre A, Lawhorn JM, Mao J, Newman HB, Nguyen TQ, Spiropulu M, Vlimant JR, Wang C, Xie S, Zhu RY, Alison J, An S, Andrews MB, Bryant P, Dutta V, Ferguson T, Harilal A, Liu C, Mudholkar T, Murthy S, Paulini M, Roberts A, Sanchez A, Terrill W, Cumalat JP, Ford WT, Hassani A, Karathanasis G, MacDonald E, Manganelli N, Marini F, Perloff A, Savard C, Schonbeck N, Stenson K, Ulmer KA, Wagner SR, Zipper N, Alexander J, Bright-Thonney S, Chen X, Cranshaw DJ, Fan J, Fan X, Gadkari D, Hogan S, Monroy J, Patterson JR, Reichert J, Reid M, Ryd A, Thom J, Wittich P, Zou R, Albrow M, Alyari M, Amram O, Apollinari G, Apresyan A, Bauerdick LAT, Berry D, Berryhill J, Bhat PC, Burkett K, Butler JN, Canepa A, Cerati GB, Cheung HWK, Chlebana F, Cummings G, Dickinson J, Dutta I, Elvira VD, Feng Y, Freeman J, Gandrakota A, Gecse Z, Gray L, Green D, Grummer A, Grünendahl S, Guerrero D, Gutsche O, Harris RM, Heller R, Herwig TC, Hirschauer J, Horyn L, Jayatilaka B, Jindariani S, Johnson M, Joshi U, Klijnsma T, Klima B, Kwok KHM, Lammel S, Lincoln D, Lipton R, Liu T, Madrid C, Maeshima K, Mantilla C, Mason D, McBride P, Merkel P, Mrenna S, Nahn S, Ngadiuba J, Noonan D, Papadimitriou V, Pastika N, Pedro K, Pena C, Ravera F, Reinsvold Hall A, Ristori L, Sexton-Kennedy E, Smith N, Soha A, Spiegel L, Stoynev S, Strait J, Taylor L, Tkaczyk S, Tran NV, Uplegger L, Vaandering EW, Zoi I, Aruta C, Avery P, Bourilkov D, Cadamuro L, Chang P, Cherepanov V, Field RD, Koenig E, Kolosova M, Konigsberg J, Korytov A, Lo KH, Matchev K, Menendez N, Mitselmakher G, Muthirakalayil Madhu A, Rawal N, Rosenzweig D, Rosenzweig S, Shi K, Wang J, Adams T, Al Kadhim A, Askew A, Bower N, Habibullah R, Hagopian V, Hashmi R, Kim RS, Kim S, Kolberg T, Martinez G, Prosper H, Prova PR, Viazlo O, Wulansatiti M, Yohay R, Zhang J, Alsufyani B, Baarmand MM, Butalla S, Elkafrawy T, Hohlmann M, Kumar Verma R, Rahmani M, Adams MR, Bennett C, Cavanaugh R, Dittmer S, Escobar Franco R, Evdokimov O, Gerber CE, Hofman DJ, Lee JH, Lemos DS, Merrit AH, Mills C, Nanda S, Oh G, Ozek B, Pilipovic D, Roy T, Rudrabhatla S, Tonjes MB, Varelas N, Wang X, Ye Z, Yoo J, Alhusseini M, Blend D, Dilsiz K, Emediato L, Karaman G, Köseyan OK, Merlo JP, Mestvirishvili A, Nachtman J, Neogi O, Ogul H, Onel Y, Penzo A, Snyder C, Tiras E, Blumenfeld B, Corcodilos L, Davis J, Gritsan AV, Kang L, Kyriacou S, Maksimovic P, Roguljic M, Roskes J, Sekhar S, Swartz M, Vámi TÁ, Abreu A, Alcerro Alcerro LF, Anguiano J, Baringer P, Bean A, Flowers Z, Grove D, King J, Krintiras G, Lazarovits M, Le Mahieu C, Lindsey C, Marquez J, Minafra N, Murray M, Nickel M, Pitt M, Popescu S, Rogan C, Royon C, Salvatico R, Sanders S, Smith C, Wang Q, Wilson G, Allmond B, Ivanov A, Kaadze K, Kalogeropoulos A, Kim D, Maravin Y, Nam K, Natoli J, Roy D, Sorrentino G, Rebassoo F, Wright D, Adams E, Baden A, Baron O, Belloni A, Bethani A, Chen YM, Eno SC, Hadley NJ, Jabeen S, Kellogg RG, Koeth T, Lai Y, Lascio S, Mignerey AC, Nabili S, Palmer C, Papageorgakis C, Paranjpe MM, Wang L, Wong K, Bendavid J, Busza W, Cali IA, Chen Y, D’Alfonso M, Eysermans J, Freer C, Gomez-Ceballos G, Goncharov M, Harris P, Hoang D, Kovalskyi D, Krupa J, Lavezzo L, Lee YJ, Long K, Mironov C, Paus C, Rankin D, Roland C, Roland G, Rothman S, Shi Z, Stephans GSF, Wang J, Wang Z, Wyslouch B, Yang TJ, Crossman B, Joshi BM, Kapsiak C, Krohn M, Mahon D, Mans J, Marzocchi B, Pandey S, Revering M, Rusack R, Saradhy R, Schroeder N, Strobbe N, Wadud MA, Cremaldi LM, Bloom K, Bryson M, Claes DR, Fangmeier C, Golf F, Haza G, Hossain J, Joo C, Kravchenko I, Reed I, Siado JE, Snow GR, Tabb W, Vagnerini A, Wightman A, Yan F, Yu D, Zecchinelli AG, Agarwal G, Bandyopadhyay H, Hay L, Iashvili I, Kharchilava A, McLean C, Morris M, Nguyen D, Pekkanen J, Rappoccio S, Rejeb Sfar H, Williams A, Alverson G, Barberis E, Haddad Y, Han Y, Krishna A, Li J, Lu M, Madigan G, Morse DM, Nguyen V, Orimoto T, Parker A, Skinnari L, Tishelman-Charny A, Wang B, Wood D, Bhattacharya S, Bueghly J, Chen Z, Hahn KA, Liu Y, Miao Y, Monk DG, Schmitt MH, Taliercio A, Velasco M, Band R, Bucci R, Castells S, Cremonesi M, Das A, Goldouzian R, Hildreth M, Ho KW, Hurtado Anampa K, Jessop C, Lannon K, Lawrence J, Loukas N, Lutton L, Mariano J, Marinelli N, Mcalister I, McCauley T, Mcgrady C, Mohrman K, Moore C, Musienko Y, Nelson H, Osherson M, Ruchti R, Townsend A, Wayne M, Yockey H, Zarucki M, Zygala L, Basnet A, Bylsma B, Carrigan M, Durkin LS, Hill C, Joyce M, Lesauvage A, Nunez Ornelas M, Wei K, Winer BL, Yates BR, Addesa FM, Bouchamaoui H, Das P, Dezoort G, Elmer P, Frankenthal A, Greenberg B, Haubrich N, Higginbotham S, Kopp G, Kwan S, Lange D, Loeliger A, Marlow D, Ojalvo I, Olsen J, Stickland D, Tully C, Malik S, Bakshi AS, Barnes VE, Chandra S, Chawla R, Das S, Gu A, Gutay L, Jones M, Jung AW, Kondratyev D, Koshy AM, Liu M, Negro G, Neumeister N, Paspalaki G, Piperov S, Purohit A, Scheurer V, Schulte JF, Stojanovic M, Thieman J, Virdi AK, Wang F, Xie W, Dolen J, Parashar N, Pathak A, Acosta D, Baty A, Carnahan T, Dildick S, Ecklund KM, Fernández Manteca PJ, Freed S, Gardner P, Geurts FJM, Kumar A, Li W, Miguel Colin O, Padley BP, Redjimi R, Rotter J, Yigitbasi E, Zhang Y, Bodek A, de Barbaro P, Demina R, Dulemba JL, Fallon C, Garcia-Bellido A, Hindrichs O, Khukhunaishvili A, Parygin P, Popova E, Taus R, Van Onsem GP, Goulianos K, Chiarito B, Chou JP, Gershtein Y, Halkiadakis E, Hart A, Heindl M, Jaroslawski D, Karacheban O, Laflotte I, Lath A, Montalvo R, Nash K, Routray H, Salur S, Schnetzer S, Somalwar S, Stone R, Thayil SA, Thomas S, Vora J, Wang H, Acharya H, Ally D, Delannoy AG, Fiorendi S, Holmes T, Karunarathna N, Lee L, Nibigira E, Spanier S, Aebi D, Ahmad M, Bouhali O, Dalchenko M, Eusebi R, Gilmore J, Huang T, Kamon T, Kim H, Luo S, Malhotra S, Mueller R, Overton D, Rathjens D, Safonov A, Akchurin N, Damgov J, Hegde V, Hussain A, Kazhykarim Y, Lamichhane K, Lee SW, Mankel A, Mengke T, Muthumuni S, Peltola T, Volobouev I, Whitbeck A, Appelt E, Greene S, Gurrola A, Johns W, Kunnawalkam Elayavalli R, Melo A, Romeo F, Sheldon P, Tuo S, Velkovska J, Viinikainen J, Cardwell B, Cox B, Hakala J, Hirosky R, Ledovskoy A, Li A, Neu C, Perez Lara CE, Karchin PE, Aravind A, Banerjee S, Black K, Bose T, Dasu S, De Bruyn I, Everaerts P, Galloni C, He H, Herndon M, Herve A, Koraka CK, Lanaro A, Loveless R, Madhusudanan Sreekala J, Mallampalli A, Mohammadi A, Mondal S, Parida G, Pinna D, Savin A, Shang V, Sharma V, Smith WH, Teague D, Tsoi HF, Vetens W, Warden A, Afanasiev S, Andreev V, Andreev Y, Aushev T, Azarkin M, Babaev A, Belyaev A, Blinov V, Boos E, Borshch V, Budkouski D, Bunichev V, Chadeeva M, Chekhovsky V, Chistov R, Dermenev A, Dimova T, Druzhkin D, Dubinin M, Dudko L, Ershov A, Gavrilov G, Gavrilov V, Gninenko S, Golovtcov V, Golubev N, Golutvin I, Gorbunov I, Gribushin A, Ivanov Y, Kachanov V, Kardapoltsev L, Karjavine V, Karneyeu A, Kim V, Kirakosyan M, Kirpichnikov D, Kirsanov M, Klyukhin V, Kodolova O, Konstantinov D, Korenkov V, Kozyrev A, Krasnikov N, Lanev A, Levchenko P, Lychkovskaya N, Makarenko V, Malakhov A, Matveev V, Murzin V, Nikitenko A, Obraztsov S, Oreshkin V, Palichik V, Perelygin V, Perfilov M, Petrushanko S, Polikarpov S, Popov V, Radchenko O, Savina M, Savrin V, Shalaev V, Shmatov S, Shulha S, Skovpen Y, Slabospitskii S, Smirnov V, Sosnov D, Sulimov V, Tcherniaev E, Terkulov A, Teryaev O, Tlisova I, Toropin A, Uvarov L, Uzunian A, Vorobyev A, Voytishin N, Yuldashev BS, Zarubin A, Zhizhin I, Zhokin A. Search for exotic decays of the Higgs boson to a pair of pseudoscalars in the μμbb and ττbb final states. THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS 2024; 84:493. [PMID: 38757620 PMCID: PMC11093753 DOI: 10.1140/epjc/s10052-024-12727-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 03/25/2024] [Indexed: 05/18/2024]
Abstract
A search for exotic decays of the Higgs boson (H ) with a mass of 125Ge V to a pair of light pseudoscalars a 1 is performed in final states where one pseudoscalar decays to two b quarks and the other to a pair of muons or τ leptons. A data sample of proton-proton collisions at s = 13 Te V corresponding to an integrated luminosity of 138fb - 1 recorded with the CMS detector is analyzed. No statistically significant excess is observed over the standard model backgrounds. Upper limits are set at 95% confidence level (CL ) on the Higgs boson branching fraction to μ μ b b and to τ τ b b , via a pair of a 1 s. The limits depend on the pseudoscalar mass m a 1 and are observed to be in the range (0.17-3.3) × 10 - 4 and (1.7-7.7) × 10 - 2 in the μ μ b b and τ τ b b final states, respectively. In the framework of models with two Higgs doublets and a complex scalar singlet (2HDM+S), the results of the two final states are combined to determine upper limits on the branching fraction B ( H → a 1 a 1 → ℓ ℓ b b ) at 95% CL , with ℓ being a muon or a τ lepton. For different types of 2HDM+S, upper bounds on the branching fraction B ( H → a 1 a 1 ) are extracted from the combination of the two channels. In most of the Type II 2HDM+S parameter space, B ( H → a 1 a 1 ) values above 0.23 are excluded at 95% CL for m a 1 values between 15 and 60Ge V .
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Grants
- Austrian Federal Ministry of Education, Science and Research
- Austrian Science Fund
- Belgian Fonds de la Recherche Scientifique
- Belgian Fonds voor Wetenschappelijk Onderzoek
- CNPq
- CAPES
- FAPERJ
- FAPERGS
- FAPESP
- Bulgarian Ministry of Education and Science
- Bulgarian National Science Fund
- CERN
- Chinese Academy of Sciences
- Ministry of Science and Technology
- Chinese National Natural Science Foundation of China
- Colombian Funding Agency (MINICIENCIAS)
- Croatian Ministry of Science, Education and Sport
- Croatian Science Foundation
- Research and Innovation Foundation
- SENESCYT
- Ministry of Education and Research
- Estonian Research Council via PRG780, PRG803, and PRG445
- European Regional Development Fund
- Academy of Finland
- Finnish Ministry of Education and Culture
- Helsinki Institute of Physics
- Institut National de Physique Nucléaire et de Physique des Particules
- Centre National de la Recherche Scientifique
- Commissariat à l’Énergie Atomique et aux Énergies Alternatives
- Bundesministerium für Bildung und Forschung
- Deutsche Forschungsgemeinschaft
- Helmholtz-Gemeinschaft Deutscher Forschungszentren
- General Secretariat for Research and Innovation
- National Research, Development and Innovation Office
- Department of Atomic Energy
- Department of Science and Technology
- Institute for Research in Fundamental Studies
- Science Foundation
- Istituto Nazionale di Fisica Nucleare
- Korean Ministry of Education, Science and Technology
- National Research Foundation of Korea (NRF)
- MES
- Lithuanian Academy of Sciences
- Ministry of Education
- University of Malaya
- BUAP
- CINVESTAV
- CONACYT
- LNS
- SEP
- UASLP
- MOS
- Ministry of Business, Innovation and Employment
- Pakistan Atomic Energy Commission
- Ministry of Educaton and Science
- National Science Centre
- Fundação para a Ciência e a Tecnologia, CERN/FIS-PAR/0025/2019 and CERN/FIS-INS/0032/2019
- Ministry of Education, Science and Technological Development of Serbia
- MCIN/AEI/10.13039/501100011033, ERDF “a way of making Europe”
- Fondo Europeo de Desarrollo Regional, Spain
- Plan de Ciencia, Tecnología e Innovación del Principado de Asturias
- MOSTR
- ETH Board
- ETH Zurich
- PSI
- SNF
- UniZH
- Canton Zurich
- SER
- Thailand Center of Excellence in Physics
- Institute for the Promotion of Teaching Science and Technology of Thailand
- Special Task Force for Activating Research
- National Science and Technology Development Agency of Thailand
- Scientific and Technical Research Council of Turkey
- Turkish Atomic Energy Authority
- National Academy of Sciences of Ukraine
- Science and Technology Facilities Council
- US Department of Energy
- US National Science Foundation
- Marie-Curie programme
- European Research Council and EPLANET (European Union)
- European Research Council/European Cooperation in Science and Technology), Action CA16108
- Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353 (European Union)
- Leventis Foundation
- Alfred P. Sloan Foundation
- Alexander von Humboldt Foundation
- Science Committee, project no. 22rl-037
- Belgian Federal Science Policy Office
- Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium)
- Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium)
- Belgian Fonds de la Recherche Scientifique, “Excellence of Science - EOS” - be.h project n. 30820817
- Belgian Fonds voor Wetenschappelijk Onderzoek, “Excellence of Science - EOS” - be.h project n. 30820817
- Beijing Municipal Science & Technology Commission, No. Z191100007219010
- Fundamental Research Funds for the Central Universities
- Ministry of Education, Youth and Sports (MEYS) of the Czech Republic
- Shota Rustaveli National Science Foundation
- Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy – EXC 2121 “Quantum Universe” – 390833306
- Deutsche Forschungsgemeinschaft (DFG), project number 400140256 - GRK2497
- Hellenic Foundation for Research and Innovation, Project Number 2288
- Hungarian Academy of Sciences
- New National Excellence Program - ÚNKP, the NKFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64
- Council of Scientific and Industrial Research, India
- Latvian Council of Science
- Ministy of Education and Science, project no. 2022/WK/14
- National Science Center, Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552
- Fundação para a Ciência e a Tecnologia, CEECIND/01334/2018
- National Priorities Research Program by Qatar National Research Fund
- Ministry of Science and Higher Education, project no. FSWU-2023-0073 and FSWW-2020-0008
- Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2017-0765 and projects PID2020-113705RB, PID2020-113304RB, PID2020-116262RB and PID2020-113341RB-I00
- Programa Severo Ochoa del Principado de Asturias
- Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand)
- CUAASC
- Kavli Foundation
- Nvidia Corporation
- Welch Foundation, contract C-1845
- Weston Havens Foundation
- Institut für Hochenergiephysik (HEPHY) using the Cloud Infrastructure Platform (CLIP), Vienna
- Inter-University Institute for High Energies, Brussels
- Université Catholique de Louvain, Louvain-la-Neuve
- São Paulo Research and Analysis Center, São Paulo
- Universidade do Estado do Rio de Janeiro, Rio de Janeiro
- University of Sofia, Sofia
- Institute of High Energy Physics of the Chinese Academy of Sciences, Beijing
- National Institute of Chemical Physics and Biophysics, Tallinn
- Helsinki Institute of Physics, Helsinki
- Grille de Recherche d’Ile de France (GRIF), Institut de recherche sur les lois fondamentales de l’Univers, CEA, Université Paris-Saclay, Gif-sur-Yvette, France and Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris
- Institut de recherche sur les lois fondamentales de l’Univers, CEA, Université Paris-Saclay, Gif-sur-Yvette
- Institut national de physique nucléaire et de physique des particules, IN2P3, Villeurbanne
- Institut Pluridisciplinaire Hubert Curien (IPHC), Strasbourg
- Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau
- Deutsches Elektronen-Synchrotron, Hamburg
- Karlsruher Institut für Technologie, Karlsruhe
- RWTH Aachen University, Aachen
- University of Ioánnina, Ioánnina
- Wigner Research Centre for Physics, Budapest
- Tata Institute of Fundamental Research, Mumbai
- INFN CNAF, Bologna
- INFN Sezione di Bari, Università di Bari, Politecnico di Bari, Bari
- INFN Sezione di Pisa, Università di Pisa, Scuola Normale Superiore di Pisa, Pisa
- INFN Sezione di Roma, Sapienza Università di Roma, Rome
- INFN Sezione di Trieste, Università di Trieste, Trieste
- Laboratori Nazionali di Legnaro, Legnaro
- Kyungpook National University, Daegu
- National Centre for Physics, Quaid-I-Azam University, Islamabad
- Akademickie Centrum Komputerowe Cyfronet AGH, Krakow
- National Centre for Nuclear Research, Swierk
- Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa
- Korea Institute of Science and Technology Information (KISTI), Daejeon
- Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid
- Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander
- Port d’Informació Científica, Bellaterra
- CERN, European Organization for Nuclear Research, Geneva
- CSCS - Swiss National Supercomputing Centre, Lugano
- Instrumentation and Detector Consortium, Taipei
- National Center for High-performance Computing (NCHC), Hsinchu City
- Middle East Technical University, Physics Department, Ankara
- National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov
- GridPP, Brunel University, Uxbridge
- GridPP, Imperial College, London
- GridPP, Queen Mary University of London, London
- GridPP, Royal Holloway, University of London, London
- GridPP, Rutherford Appleton Laboratory, Didcot
- GridPP, University of Bristol, Bristol
- GridPP, University of Glasgow, Glasgow
- GridPP, University of Oxford, Oxford
- Baylor University, Waco
- California Institute of Technology, Pasadena
- Fermi National Accelerator Laboratory, Batavia
- Massachusetts Institute of Technology, Cambridge
- National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility, Berkeley
- Open Science Grid (OSG) Consortium
- Pittsburgh Supercomputing Center (PSC), Pittsburgh
- Purdue University, West Lafayette
- San Diego Supercomputer Center (SDSC), La Jolla
- Texas Advanced Computing Center (TACC), Austin
- University of California, San Diego, La Jolla
- University of Colorado Boulder, Boulder
- University of Florida, Gainesville
- University of Nebraska-Lincoln, Lincoln
- University of Wisconsin - Madison, Madison
- Vanderbilt University, Nashville
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang LL, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. First Observation of a Three-Resonance Structure in e^{+}e^{-}→Nonopen Charm Hadrons. PHYSICAL REVIEW LETTERS 2024; 132:191902. [PMID: 38804946 DOI: 10.1103/physrevlett.132.191902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 03/10/2024] [Accepted: 03/29/2024] [Indexed: 05/29/2024]
Abstract
We report the measurement of the inclusive cross sections for e^{+}e^{-}→nOCH (where nOCH denotes non-open charm hadrons) with improved precision at center-of-mass (c.m.) energies from 3.645 to 3.871 GeV. We observe three resonances: R(3760), R(3780), and R(3810) with significances of 8.1σ, 13.7σ, and 8.8σ, respectively. The R(3810) state is observed for the first time, while the R(3760) and R(3780) states are observed for the first time in the nOCH cross sections. Two sets of resonance parameters describe the energy-dependent line shape of the cross sections well. In set I [set II], the R(3810) state has mass (3805.7±1.1±2.7) [(3805.7±1.1±2.7)] MeV/c^{2}, total width (11.6±2.9±1.9) [(11.5±2.8±1.9)] MeV, and an electronic width multiplied by the nOCH decay branching fraction of (10.9±3.8±2.5) [(11.0±3.4±2.5)] eV. In addition, we measure the branching fractions B[R(3760)→nOCH]=(25.2±16.1±30.4)%[(6.4±4.8±7.7)%] and B[R(3780)→nOCH]=(12.3±6.6±8.3)%[(10.4±4.8±7.0)%] for the first time. The R(3760) state can be interpreted as an open-charm (OC) molecular state, but containing a simple four-quark state component. The R(3810) state can be interpreted as a hadrocharmonium state.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Fang YQ, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Feng YT, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Gutierrez J, Han KL, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu BY, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khachatryan V, Khoukaz A, Kiuchi R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Moses B, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang NY, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YL, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZD, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Determination of Spin-Parity Quantum Numbers of X(2370) as 0^{-+} from J/ψ→γK_{S}^{0}K_{S}^{0}η^{'}. PHYSICAL REVIEW LETTERS 2024; 132:181901. [PMID: 38759175 DOI: 10.1103/physrevlett.132.181901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/05/2024] [Accepted: 03/28/2024] [Indexed: 05/19/2024]
Abstract
Based on (10087±44)×10^{6} J/ψ events collected with the BESIII detector, a partial wave analysis of the decay J/ψ→γK_{S}^{0}K_{S}^{0}η^{'} is performed. The mass and width of the X(2370) are measured to be 2395±11(stat)_{-94}^{+26}(syst) MeV/c^{2} and 188_{-17}^{+18}(stat)_{-33}^{+124}(syst) MeV, respectively. The corresponding product branching fraction is B[J/ψ→γX(2370)]×B[X(2370)→f_{0}(980)η^{'}]×B[f_{0}(980)→K_{S}^{0}K_{S}^{0}]=(1.31±0.22(stat)_{-0.84}^{+2.85}(syst))×10^{-5}. The statistical significance of the X(2370) is greater than 11.7σ and the spin parity is determined to be 0^{-+} for the first time. The measured mass and spin parity of the X(2370) are consistent with the predictions of the lightest pseudoscalar glueball.
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Raghuwanshi S, Zhang X, Arbieva Z, Khan I, Mohammed H, Wang Z, Domling A, Camacho CJ, Gartel AL. Novel FOXM1 inhibitor STL001 sensitizes human cancers to a broad-spectrum of cancer therapies. Cell Death Discov 2024; 10:211. [PMID: 38697979 PMCID: PMC11066125 DOI: 10.1038/s41420-024-01929-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 05/05/2024] Open
Abstract
Forkhead box protein M1 (FOXM1) is often overexpressed in human cancers and strongly associated with therapy resistance and less good patient survival. The chemotherapy options for patients with the most aggressive types of solid cancers remain very limited because of the acquired drug resistance, making the therapy less effective. NPM1 mutation through the inactivation of FOXM1 via FOXM1 relocalization to the cytoplasm confers more favorable treatment outcomes for AML patients, confirming FOXM1 as a crucial target to overcome drug resistance. Pharmacological inhibition of FOXM1 could be a promising approach to sensitize therapy-resistant cancers. Here, we explore a novel FOXM1 inhibitor STL001, a first-generation modification drug of our previously reported FOXM1 inhibitor STL427944. STL001 preserves the mode of action of the STL427944; however, STL001 is up to 50 times more efficient in reducing FOXM1 activity in a variety of solid cancers. The most conventional cancer therapies studied here induce FOXM1 overexpression in solid cancers. The therapy-induced FOXM1 overexpression may explain the failure or reduced efficacy of these drugs in cancer patients. Interestingly, STL001 increased the sensitivity of cancer cells to conventional cancer therapies by suppressing both the high-endogenous and drug-induced FOXM1. Notably, STL001 does not provide further sensitization to FOXM1-KD cancer cells, suggesting that the sensitization effect is conveyed specifically through FOXM1 suppression. RNA-seq and gene set enrichment studies revealed prominent suppression of FOXM1-dependent pathways and gene ontologies. Also, gene regulation by STL001 showed extensive overlap with FOXM1-KD, suggesting a high selectivity of STL001 toward the FOXM1 regulatory network. A completely new activity of FOXM1, mediated through steroid/cholesterol biosynthetic process and protein secretion in cancer cells was also detected. Collectively, STL001 offers intriguing translational opportunities as combination therapies targeting FOXM1 activity in a variety of human cancers driven by FOXM1.
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Wang Z, Van Faassen M, Groen H, Cantineau AEP, Van Oers A, Van der Veen A, Hawley JM, Keevil BG, Kema IP, Hoek A. Resumption of ovulation in anovulatory women with PCOS and obesity is associated with reduction of 11β-hydroxyandrostenedione concentrations. Hum Reprod 2024; 39:1078-1088. [PMID: 38503490 PMCID: PMC11063562 DOI: 10.1093/humrep/deae058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 02/02/2024] [Indexed: 03/21/2024] Open
Abstract
STUDY QUESTION Is resumption of ovulation after a 6-month lifestyle intervention in women with PCOS and obesity associated with differential changes in endocrine and metabolic parameters (weight, insulin resistance, anti-Müllerian hormone (AMH), and androgens) compared to women with PCOS who remained anovulatory? SUMMARY ANSWER Resumption of ovulation after a 6-month lifestyle intervention in women with PCOS and obesity is associated with changes in serum 11β-hydroxyandrostenedione (11OHA4) concentrations. WHAT IS KNOWN ALREADY Lifestyle interventions have been shown to reduce clinical and biochemical hyperandrogenism in women with PCOS. Weight loss of 5-10% may reverse anovulatory status, thereby increasing natural conception rates. However, the mechanisms underlying why some women with PCOS remain anovulatory and others resume ovulation after weight loss are unclear. Reproductive characteristics at baseline and a greater degree of change in endocrine and metabolic features with lifestyle intervention may be crucial for ovulatory response. STUDY DESIGN, SIZE, DURATION We used data and samples originating from an earlier randomized controlled trial (RCT), which examined the efficacy of a 6-month lifestyle intervention prior to infertility treatment compared to prompt infertility treatment on live birth rate in women with obesity. A total of 577 women with obesity (BMI > 29 kg/m2) were randomized between 2009 and 2012. Anovulatory women with PCOS who were allocated to the intervention arm of the original RCT (n = 95) were included in the current analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS We defined women as having resumed ovulation (RO+) based on the following criteria: spontaneous pregnancy; or assignment to expectant management; or IUI in natural cycles as the treatment strategy after lifestyle intervention. Steroid hormones were measured using liquid chromatography tandem mass spectrometry. Generalized estimating equations with adjustment for baseline measures and interaction between group and time was used to examine differences in changes of endocrine and metabolic parameters between RO+ (n = 34) and persistently anovulatory women (RO-, n = 61) at 3 and 6 months after intervention. MAIN RESULTS AND THE ROLE OF CHANCE At baseline, the mean ± SD age was 27.5 ± 3.6 years in the RO+ group and 27.9 ± 4.1 years in the RO- group (P = 0.65), and the mean ± SD weights were 101.2 ± 9.5 kg and 105.0 ± 14.6 kg, respectively (P = 0.13). Baseline AMH concentrations showed significant differences between RO+ and RO- women (median and interquartile range [IQR] 4.7 [3.2; 8.3] versus 7.2 [5.3; 10.8] ng/ml, respectively). Baseline androgen concentrations did not differ between the two groups. During and after lifestyle intervention, both groups showed weight loss; changes in 11OHA4 were significantly different between the RO+ and RO groups (P-value for interaction = 0.03). There was a similar trend for SHBG (interaction P-value = 0.07), and DHEA-S (interaction P-value = 0.06), with the most pronounced differences observed in the first 3 months. Other parameters, such as AMH and FAI, decreased over time but with no difference between the groups. LIMITATIONS, REASONS FOR CAUTION No high-resolution transvaginal ultrasonography was used to confirm ovulatory status at the end of the lifestyle program. The small sample size may limit the robustness of the results. WIDER IMPLICATIONS OF THE FINDINGS Reduction of androgen concentrations during and after lifestyle intervention is associated with recovery of ovulatory cycles. If our results are confirmed in other studies, androgen concentrations could be monitored during lifestyle intervention to provide individualized recommendations on the timing of resumption of ovulation in anovulatory women with PCOS and obesity. STUDY FUNDING/COMPETING INTEREST(S) The study was supported by a grant from ZonMw, the Dutch Organization for Health Research and Development (50-50110-96-518). The Department of Obstetrics and Gynecology of the UMCG received an unrestricted educational grant from Ferring Pharmaceuticals BV, The Netherlands. A.H. reports consultancy for the development and implementation of a lifestyle App MyFertiCoach developed by Ferring Pharmaceutical Company. All other authors have no conflicts to declare. TRIAL REGISTRATION NUMBER The LIFEstyle RCT was registered at the Dutch trial registry (NTR 1530).
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Huang Y, Li X, Niu L, Zhang H, Zhang C, Feng Y, Wang Z, Zhang F, Luo X. CT venography combined with ultrasound-guided minimally invasive treatment for recurrent varicose veins: a pilot paired-design clinical trial. Clin Radiol 2024; 79:363-370. [PMID: 38290939 DOI: 10.1016/j.crad.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 09/26/2023] [Accepted: 12/24/2023] [Indexed: 02/01/2024]
Abstract
AIM To compare 1-year outcomes of computed tomography venography (CTV) combined with ultrasound-guided minimally invasive treatment with ascending phlebography and ultrasound-guided treatment for recurrent varicose veins. MATERIALS AND METHODS Consecutive patients with unilateral recurrent varicose veins were matched by gender, age, C classification, and degree of obesity, and randomised in a 1:1 ratio to receive either CTV (CTV group) or ascending phlebography (control group) combined with ultrasound-guided minimally invasive treatment. Patients were followed up by clinical and ultrasound examination. Follow-up was scheduled at 1 week, and 3, 6, and 12 months. The primary outcome measure was the Venous Clinical Severity Score (VCSS) at 12 months. Measures of secondary outcome included Chronic Insufficiency Venous International Questionnaire-20 (CIVIQ-20) score, recurrence of varicose vein or ulcer during 12 months, ulcer healing time, detection and location of treated veins. RESULTS Eighty patients were enrolled. Median VCSS in the CTV group was lower than it in the control group (p=0.04) and the CIVIQ-20 score was higher than the control group (p=0.02). By 12 months, no symptomatically recurrent varicose veins or ulcers had occurred. The ulcer healing time in CTV group was shorter (p<0.01). A greater number of patients had treated veins detected using CTV than by ascending venography (p=0.01), especially among patients with recurrence reflux veins in the groin, perineum, and vulva (p<0.01). CONCLUSION CTV combined with ultrasound may be more helpful than ascending phlebography combined with ultrasound to improve treatment efficacy for recurrent varices. These results should be verified by an future study with more patients and long-term follow-up.
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Luo L, Wang Z, Wang X, Gao J, Zheng A, Duan X. Fluorine-18 prostate-specific membrane antigen-1007-avid indeterminate bone lesions in prostate cancer: clinical and PET/CT features to predict outcomes and prognosis. Clin Radiol 2024; 79:346-353. [PMID: 38216370 DOI: 10.1016/j.crad.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/29/2023] [Accepted: 12/11/2023] [Indexed: 01/14/2024]
Abstract
AIM To determine clinical and fluorine-18 prostate-specific membrane antigen-1007 (18F-PSMA-1007) integrated positron-emission tomography (PET)/computed tomography (CT) features that could be used to interpret indeterminate bone lesions (IBLs) and assess the prognosis of prostate cancer (PCa) in patients with IBLs. MATERIALS AND METHODS Consecutive patients who underwent PSMA PET/CT were analysed retrospectively. IBLs were identified as benign or malignant based on follow-up imaging and clinical management. Lesion- and patient-based assessments were performed to define features predictive of bone lesion results and determine clinical risk. Patients' prognosis was analysed based on clinical characteristics, including prostate-specific antigen (PSA) and alkaline phosphatase (ALP), respectively. RESULTS A total of 105 patients (mean age ± SD, 72.1 ± 8 years) were evaluated and 158 IBLs were identified. Fifty-three (33.5%), 36 (22.8%), and 69 (43.7%) IBLs were benign, malignant, and equivocal, respectively. Variables including location, maximum standard uptake value (SUVmax), and lymph node metastases (LNM) were related to the benignancy or malignancy of IBLs (p=0.046, p<0.001 and p<0.001, respectively). Regression analysis indicated that LNM, SUVmax, and location of IBLs could be predictors of lesion interpretation (p<0.001, p=0.002 and p=0.035). Patients with benign IBLs experienced the most considerable decreases in PSA and ALP levels. CONCLUSIONS LNM, SUVmax, and location may contribute to IBL interpretation. A rapid decrease in PSA and ALP levels might suggest a better prognosis for patients with benign IBLs.
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Gao SH, Wang GZ, Wang LP, Feng L, Zhou YC, Yu XJ, Liang F, Yang FY, Wang Z, Sun BB, Wang D, Liang LJ, Xie DW, Zhao S, Feng HP, Li X, Li KK, Tang TS, Huang YC, Wang SQ, Zhou GB. Corrigendum to "Mutations and clinical significance of calcium voltage-gated channel subunit alpha 1E (CACNA1E) in non-small cell lung cancer" [Cell Calcium 102 (2022) 102527]. Cell Calcium 2024; 119:102866. [PMID: 38428281 DOI: 10.1016/j.ceca.2024.102866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
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Wang Z, Bi H, Wang YD, Liu Q, Shao B, Li CQ, Fu C, Fu S, Shan GY, Chen A, Lv CC, Zeng Y. Tislelizumab, a novel PD-1 monoclonal antibody in urothelial cancer: A real-world study. Actas Urol Esp 2024; 48:295-303. [PMID: 38160794 DOI: 10.1016/j.acuroe.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/26/2023] [Accepted: 10/28/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Tislelizumab, a monoclonal antibody against programed death protein-1 (PD-1), has shown encouraging antitumor activity in urothelial cancer. This study was designed to assess the efficacy and safety of tislelizumab in urotelial cancer in a real-world setting. METHODS The study was a real-world retrospective study undertaken at Liaoning Cancer Hospital & Institute, China. Eligible patients were ≥18 years. Patients received 200-mg tislelizumab monotherapy intravenously every 3 weeks until the disease progressed to intolerable toxicity. Outcomes included an objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and safety. RESULTS Between March 2020 and December 2022, 33 patients were enrolled. The median follow-up was 10.17 (IQR 5.73-12.47) months. Of all 33 patients, ORR and DCR were 30.30% (95% CI 15.6%-48.7%) and 42.42% (95% CI 25.48%-60.78%), respectively. The median PFS was 5.73 (95% CI 3.27-13.00) months, with a 12-month PFS rate of 31.90% (95% CI 19.20%-53.00%). The median OS was 17.7 (95% CI 12.80-not reach) months, with a 12-month OS rate of 67.50% (95% CI 52.70%-86.40%). Eleven (33.33%) and 8 (24.24%) experienced ≥grade 3 treatment-related adverse events (TRAEs) and immune-related Aes, respectively. No treatment-related deaths occurred. CONCLUSION The excellent efficacy and controllable safety of tislelizumab in locally advanced or metastatic urothelial cancer suggest that it may be a promising therapeutic option for this population.
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Wu S, Duan WX, Yang X, Wei WZ, Ma QY, Wang Z, Wu Z. [Pancreaticoduodenectomy combined with longitudinal pancreaticojejunostomy in the treatment of chronic pancreatitis: initial experience in 11 cases]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:412-418. [PMID: 38548610 DOI: 10.3760/cma.j.cn112139-20231202-00251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
Objective: To investigate the surgical strategy for chronic pancreatitis complicated with suspected malignant lesions in the pancreatic head and pancreatolithiasis in the distal pancreas. Methods: This is a retrospective cohort study. Clinical data from 11 patients with chronic pancreatitis who underwent pancreaticoduodenectomy combined with longitudinal pancreaticojejunostomy(PD-L) were retrospectively collected(PD-L group) from the Department of Hepatobiliary Surgery of the First Affiliated Hospital of Xi'an Jiaotong University between December 2021 and September 2023. All patients were male with an age of (49.0±11.2) years(range:32 to 70 years). Their primary preoperative diagnoses included pancreatic lesions, chronic pancreatitis, pancreatolithiasis, and dilatation of the pancreatic duct. Data from 248 patients who underwent pancreaticoduodenectomy(PD) during the same period were retrospectively collected(PD group). There were 157 males and 91 females in the PD group, with an age of (61.5±10.8) years(range:27 to 82 years). Among them, 87 cases were diagnosed as pancreatic cancer or chronic pancreatitis. The propensity score matching method was used to reduce confounding bias between the two groups. The caliper value of 0.1 was used and the 1∶4 nearest neighbor matching method was used for the matching. Comparisons between the two groups were made using the independent sample t test, Mann-Whitney U test or χ2 test,respectively. Results: After complete excision of the specimen during pancreaticoduodenectomy, the key surgical step of PD-L was longitudinal pancreaticojejunostomy in the remaining pancreas. Intraoperative blood loss in the PD-L group was lower than that in the PD group [M(IQR)](300(200)ml vs. 500(500)ml, respectively; P<0.05). Similarly, hospitalization days(21.0(7.0)days vs. 25.0(8.5)days) and postoperative hospitalization days(13.0(8.0)days vs. 17.0(5.0) days) were also lower in the PD-L group compared to the PD group (P<0.05). There were no significant differences in the operation time and postoperative complication rate between the two groups(P>0.05). In the PD-L group, the postoperative follow-up time was 5(5)months(range: 3 to 21 months). One case was lost for follow-up. Abdominal pain was relieved in 10 patients. Additionally, abdominal distension and steatosis were alleviated in 8 cases. Furthermore, 5 cases of diabetes mellitus showed improved control of HbA1c and fasting blood glucose levels after surgery. Conclusions: PD-L treatment can be used to treat chronic pancreatitis complicated by suspected malignant lesions in the pancreatic head and pancreatolithiasis in the distal pancreas. PD-L also has advantages in removing stones from the pancreatic duct and evaporation of pancreatic fluid. However, due to the single-center design and the small sample size of this study, further practice and long-term follow-up are still necessary.
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Wang C, Wang Z, Fu L, Du J, Ji F, Qiu X. CircNRCAM up-regulates NRCAM to promote papillary thyroid carcinoma progression. J Endocrinol Invest 2024; 47:1215-1226. [PMID: 38485895 DOI: 10.1007/s40618-023-02241-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 11/04/2023] [Indexed: 04/23/2024]
Abstract
PURPOSE Papillary Thyroid Carcinoma (PTC) is the most prevalent subtype of Thyroid Carcinoma (THCA), a type of malignancy in the endocrine system. According to prior studies, Neural Cell Adhesion Molecule (NRCAM) has been found to be up-regulated in PTC and stimulates the proliferation and migration of PTC cells. However, the specific mechanism of NRCAM in PTC cells is not yet fully understood. Consequently, this study aimed to investigate the underlying mechanism of NRCAM in PTC cells, the findings of which could provide new insights for the development of potential treatment targets for PTC. METHODS AND RESULTS Bioinformatics tools were utilized and a series of experiments were conducted, including Western blot, colony formation, and dual-luciferase reporter assays. The data collected indicated that NRCAM was overexpressed in THCA tissues and PTC cells. Circular RNA NRCAM (circNRCAM) was found to be highly expressed in PTC cells and to positively regulate NRCAM expression. Through loss-of-function assays, both circNRCAM and NRCAM were shown to promote the proliferation, invasion, and migration of PTC cells. Mechanistically, this study confirmed that precursor microRNA-506 (pre-miR-506) could bind with m6A demethylase AlkB Homolog 5 (ALKBH5), leading to its m6A demethylation. It was also discovered that circNRCAM could competitively bind to ALKBH5, which restrained miR-506-3p expression and promoted NRCAM expression. CONCLUSION In summary, circNRCAM could up-regulate NRCAM by down-regulating miR-506-3p, thereby enhancing the biological behaviors of PTC cells.
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Wang Z, Yang M, Li S, Chi H, Wang J, Xiao C. [A transcriptomic analysis of correlation between mitochondrial function and energy metabolism remodeling in mice with myocardial fibrosis following myocardial infarction]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024; 44:666-674. [PMID: 38708499 DOI: 10.12122/j.issn.1673-4254.2024.04.07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
OBJECTIVE To investigate the changes of mitochondrial respiratory function during myocardial fibrosis in mice with myocardial infarction (MI) and its correlation with the increase of glycolytic flux. METHODS Forty C57BL/6N mice were randomized into two equal groups to receive sham operation or ligation of the left anterior descending coronary artery to induce acute MI. At 28 days after the operation, 5 mice from each group were euthanized and left ventricular tissue samples were collected for transcriptomic sequencing. FPKM method was used to calculate gene expression levels to identify the differentially expressed genes (DEGs) in MI mice, which were analyzed using GO and KEGG databases to determine the pathways affecting the disease process. Heat maps were drawn to show the differential expressions of the pathways and the related genes in the enrichment analysis. In primary cultures of neonatal mouse cardiac fibroblasts (CFs), the changes in mitochondrial respiration and glycolysis levels in response to treatment with the pro-fibrotic agonist TGF-β1 were analyzed using Seahorse experiment. RESULTS The mouse models of MI showed significantly increased diastolic and systolic left ventricular diameter (P < 0.05) and decreased left ventricular ejection fraction (P < 0.0001). A total of 124 up-regulated and 106 down-regulated DEGs were identified in the myocardial tissues of MI mice, and GO and KEGG enrichment analysis showed that these DEGs were significantly enriched in fatty acid metabolism, organelles and other metabolic pathways and in the mitochondria. Heat maps revealed fatty acid beta oxidation, mitochondrial dysfunction and increased glycolysis levels in MI mice. In the primary culture of CFs, treatment with TGF-β1 significantly reduced the basal and maximum respiratory levels and increased the basal and maximum glycolysis levels (P < 0.0001). CONCLUSION During myocardial fibrosis, energy metabolism remodeling occurs in the CFs, manifested by lowered mitochondrial function and increased energy generation through glycolysis.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}. PHYSICAL REVIEW LETTERS 2024; 132:161901. [PMID: 38701481 DOI: 10.1103/physrevlett.132.161901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 03/13/2024] [Accepted: 03/22/2024] [Indexed: 05/05/2024]
Abstract
We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0 fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8) MeV/c^{2} and Γ=(110.5±15.0±2.9) MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7) MeV/c^{2} and Γ=(116.1±33.5±1.7) MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.
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Wang Z, Xue F, Sui X, Han W, Song W, Jiang J. Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study. Pulmonology 2024:S2531-0437(24)00040-0. [PMID: 38614860 DOI: 10.1016/j.pulmoe.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography. METHODS We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year). RESULTS In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules. CONCLUSIONS The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data. PHYSICAL REVIEW LETTERS 2024; 132:151903. [PMID: 38682963 DOI: 10.1103/physrevlett.132.151903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/03/2024] [Accepted: 03/11/2024] [Indexed: 05/01/2024]
Abstract
We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06}) MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07} MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14} MeV.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, In der Wiesche N, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kui X, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold. PHYSICAL REVIEW LETTERS 2024; 132:151901. [PMID: 38682972 DOI: 10.1103/physrevlett.132.151901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/16/2024] [Accepted: 02/23/2024] [Indexed: 05/01/2024]
Abstract
Using a sample of (10087±44)×10^{6} J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84 GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7 MeV/c^{2} and 30.7±5.5±2.4 MeV, respectively, which indicates the existence of a pp[over ¯] bound state.
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Wang Z, Li YP, Huang GH, Gong JW, Li YF, Zhang Q. A factorial-analysis-based Bayesian neural network method for quantifying China's CO 2 emissions under dual-carbon target. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170698. [PMID: 38342455 DOI: 10.1016/j.scitotenv.2024.170698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/10/2024] [Accepted: 02/02/2024] [Indexed: 02/13/2024]
Abstract
Energy-structure transformation and CO2-emission reduction are becoming particularly urgent for China and many other countries. Development of effective methods that are capable of quantifying and predicting CO2 emissions to achieve carbon neutrality is desired. This study advances a factorial-analysis-based Bayesian neural network (abbreviated as FABNN) method to reflect the complex relationship between inputs and outputs as well as reveal the individual and interactive effects of multiple factors affecting CO2 emissions. FABNN is then applied to analyzing CO2 emissions of China (abbreviated as CEC), where multiple factors involve in energy (e.g., the consumption of natural gas, CONG), economic (e.g., Gross domestic product, GDP) and social (e.g., the rate of urbanization, ROU) aspects are investigated and 512 scenarios are designed to achieve the national dual carbon targets (i.e., carbon peak before 2030 and carbon neutrality by 2060). Comparing to the conventional machine learning methods, FABNN performs better in calibration and validation results, indicating that FABNN is suitable for CEC simulation and prediction. Results disclose that the top three factors affecting CEC under the dual‑carbon target are GDP, CONG, and ROU; energy, economic and social contributions are 43.5 %, 34.6 % and 21.9 %, respectively. CEC reaches its carbon peak during 2027-2032 and achieve carbon neutrality during 2053-2057 under all scenarios. Under the optimal scenario (S195), the CO2-emission reduction potential is about 772.2 million tonnes and the consumptions of coal, petroleum and natural gas can be respectively reduced by 3.1 %, 9.9 % and 23.0 % compared to the worst scenario (S466). The results can provide solid support for national energy-structure transformation and CO2-emission reduction to achieve carbon-peak and carbon-neutrality targets.
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Del Mauro G, Wang Z. Cross-subject brain entropy mapping. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588307. [PMID: 38645267 PMCID: PMC11030347 DOI: 10.1101/2024.04.05.588307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
We present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data. While we only showed the cross-subject brain entropy (BEN) mapping results in this manuscript, the same concept can be directly extended to map the cross-sessional BEN and the cross-regional cross-subject or subject-session BEN.
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Liang JY, Wang YM, Wen Z, Zhang WH, Gao ZZ, Wang Z, Guo SP. [Clinicopathological characteristics and immune microenvironment of breast squamous cell carcinoma]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2024; 53:337-343. [PMID: 38556816 DOI: 10.3760/cma.j.cn112151-20231023-00293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Objective: To investigate the clinicopathological characteristics of breast squamous cell carcinoma and to analyze the relationship between its immune microenvironment tumor infiltrating lymphocytes (TILs) and prognosis. Methods: Forty-four cases of primary squamous cell carcinoma of the breast diagnosed and treated in the First Affiliated Hospital of Air Force Medical University, Xi'an, China from January 2006 to July 2022 were selected. Their clinicopathological characteristics were analyzed. The cell composition of TILs was evaluated using immunohistochemistry (Mainly markers of B lymphocytes, T lymphocytes and plasma cells). The relationship between TILs and prognosis was also analyzed. Results: The 44 patients of breast squamous cell carcinoma were all female and all were invasive carcinoma. Eight cases (8/44, 18.2%) were squamous cell carcinoma, while 36 cases (36/44, 81.8%) were mixed squamous cell carcinoma. The mixed components included non-specific carcinoma and spindle cell metaplastic carcinoma (17 cases each). One case contained ductal carcinoma in situ of the breast and 1 case contained tubular carcinoma. The proportion of squamous cell carcinoma was 10% to 90%. The cases with pure squamous cell carcinoma often had a large cystic cavity, which was lined by atypical squamous epithelium, while infiltrating squamous cell carcinoma nests were seen in the breast tissue around the cystic cavity. Immunohistochemical staining showed that p63 and CK5/6 were expressed in the squamous cell carcinoma component, but ER, PR and HER2 were not, except for one case of HER2 1+. The positive rates of TRPS1 and PDL-1 were 76% and less than 1%, respectively. Fifteen cases were in the high TILs group (TILs≥30%) and 29 cases were in the low TILs group (TILs<30%). Twenty-three patients were followed up for 5 to 118 months. Among them, 12 died within 3 years and 9 were alive at the end of the follow up. There was no significant difference in TNM stage, TILs and prognosis between simple squamous cell carcinoma and mixed squamous cell carcinoma. Conclusions: Breast squamous cell carcinoma can be divided into simple squamous cell carcinoma and mixed squamous cell carcinoma. There are differences in gross findings and histology between the simple and mixed squamous cell carcinoma of the breast. Sufficient samples should be taken to avoid missing the diagnosis of a minor squamous component. The prognosis of patients with high TILs is significantly better than that of patients with low TILs. The expression rate of TRPS1 in primary squamous cell carcinoma of breast is high and helpful to the differential diagnosis from metastatic squamous cell carcinoma.
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Sun Q, Wang Z. [Interpretation of myeloid neoplasms in the 5th WHO classification of haematolymphoid tumors]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2024; 53:323-330. [PMID: 38556814 DOI: 10.3760/cma.j.cn112151-20230823-00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
The 5th edition of the WHO classification of haematolymphoid tumors β version had been released online, in which the section of myeloid neoplasms had undergone significant changes in the classification framework,standards of diagnosis and classification criteria. The principle of comprehensive diagnosis based on clinicopathologic multi-parameter was maintained, especially strengthening the priority importance of biological features in diagnosis and classification, and highlighting the biological characteristics of the disease and thus providing the basis for targeted treatment and prognostic evaluation. This article introduces the main updates and changes in the myeloid neoplasms of the 5th edition of the WHO haematolymphoid tumor classification, in order to better understand and guide clinical diagnosis and therapeutic treatment in the future.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Hou XT, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}. PHYSICAL REVIEW LETTERS 2024; 132:141901. [PMID: 38640399 DOI: 10.1103/physrevlett.132.141901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 11/29/2023] [Accepted: 02/28/2024] [Indexed: 04/21/2024]
Abstract
Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33 fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.
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Wang Z, He D, Yang JL. Gastrointestinal: Chronic anemia caused by diffuse lesions of the stomach. J Gastroenterol Hepatol 2024; 39:615-616. [PMID: 38105504 DOI: 10.1111/jgh.16412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/19/2023] [Accepted: 10/28/2023] [Indexed: 12/19/2023]
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Wang Z, Shang Y, Li Z, Song K. Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 356:120576. [PMID: 38513585 DOI: 10.1016/j.jenvman.2024.120576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 09/22/2023] [Accepted: 03/09/2024] [Indexed: 03/23/2024]
Abstract
Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.
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