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Detecting clinical progression from abnormal regional brain volumes at baseline in genetic frontotemporal dementia: A GENFI study

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Alzheimer's & Dementia 2021年第S1期17卷

作者： Martina Bocchetta Emily G Todd Jennifer M Nicholas Georgia Peakman David M Cash Rhian S Convery Lucy L Russell David L Thomas Juan Eugenio Iglesias John C van Swieten Lize C. Jiskoot Harro Seelaar Barbara Borroni Daniela Galimberti Raquel Sanchez-Valle Robert Laforce Jr. Fermin Moreno Matthis Synofzik Caroline Graff Mario Masellis Maria Carmela Tartaglia James B Rowe Rik Vandenberghe Elizabeth Finger Fabrizio Tagliavini Alexandre Mendonca Isabel Santana Christopher Butler Simon Ducharme Alexander Gerhard Adrian Danek Johannes Levin Markus Otto Sandro Sorbi Isabelle Le Ber Florence Pasquier Jonathan D Rohrer Genetic Frontotemporal dementia Initiative (GENFI) Dementia Research Centre UCL Queen Square Institute of Neurology University College London London United Kingdom Department of Medical Statistics London School of Hygiene and Tropical Medicine London United Kingdom Dementia Research Centre Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London United Kingdom Dementia Research Centre Queen Square Institute of Neurology University College London London United Kingdom Centre for Medical Image Computing Department of Medical Physics and Biomedical Engineering University College London London United Kingdom Neuroradiological Academic Unit UCL Queen Square Institute of Neurology UCL London United Kingdom Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School Charlestown MA USA Alzheimer Center Erasmus Medical Center Rotterdam Netherlands Erasmus MC Rotterdam Netherlands Erasmus Medical Center Rotterdam Netherlands Centre for Neurodegenerative Disorders Neurology Unit Department of Clinical and Experimental Sciences University of Brescia Brescia Italy University of Milan Milan Italy Department of Biomedical Surgical and Dental Sciences University of Milan Milan Italy Neurology Department Hospital Clínic Institut d'Investigacions Biomediques Barcelona Spain Clinique Interdisciplinaire de Mémoire CHU de Québec/Université Laval/Hôpital de l’Enfant-Jésus Quebec City QC Canada Hospital Universitario Donostia San Sebastian Spain Centre for Neurology and Hertie-Institute for Clinical Brain Research Hoppe-Seyler-Str Tuebingen Germany Karolinska Institutet Department NVS Division of Neurogeriatrics Karolinska Institutet Stockholm Sweden Unit for Hereditary Dementia Theme Aging Karolinska University Hospital-Solna Stockholm Sweden LC Campbell Cognitive Neurology Research Unit Sunnybrook Research Institute Toronto ON Canada T

Background Genetic frontotemporal dementia is highly heterogeneous, with different progression patterns seen between individuals. Using in vivo MR images from the Genetic FTD Initiative (GENFI), we aimed to identify clinical progression in genetic mutation carriers from their brain volumes at baseline. Method Cortical and subcortical volumes of interest (VOIs) were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans for 480 carriers (198 GRN , 202 C9orf72 , 80 MAPT ). W-scores for 79 VOIs were computed from a linear regression model carried out on 298 non-carrier cognitively normal controls adjusting for the effect of age, sex, total intracranial volume and scanner type. Carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score (CDR-GS): asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more). Cut-off points for each VOI were derived from Youden indices estimated with ROC curves to distinguish between CDR-GS=0 and CDR-GS≥1 within each gene. CDR-GS=0.5 carriers (30 GRN , 32 C9orf72 , 13 MAPT ) were classified as ‘normal’ or ‘abnormal’ based on these cut-off points. We compared the CDR® plus NACC FTLD sum-of-boxes scores (CDR-SOB) at one year follow-up in these two groups. Result Compared to those with normal baseline volumes, C9orf72 expansion carriers at CDR-GS=0.5 showed significantly higher CDR-SOB scores at follow-up if they had abnormal volumes in the total frontal (+5 points), orbitofrontal (+3), dorsolateral prefrontal (+6), or anterior cingulate (+4) cortices, the basal-paralaminar amygdala region (+2), CA1 region of the hippocampus (+4), total hippocampus (+6), cerebellar lobule VIIIb (+4), or lateral ventricles (+8). GRN mutation carriers showed significantly higher CDR-SOB scores if their volumes were abnormal in the frontal (+10), parietal (+14), insula (+8), orbitofrontal (+12), or medial parietal (+7) cortices, or the total hippocampus (+10). MAPT mu

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Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes

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Nature 2022年第7909期605卷 E3页

作者： Jill E Moore Michael J Purcaro Henry E Pratt Charles B Epstein Noam Shoresh Jessika Adrian Trupti Kawli Carrie A Davis Alexander Dobin Rajinder Kaul Jessica Halow Eric L Van Nostrand Peter Freese David U Gorkin Yin Shen Yupeng He Mark Mackiewicz Florencia Pauli-Behn Brian A Williams Ali Mortazavi Cheryl A Keller Xiao-Ou Zhang Shaimae I Elhajjajy Jack Huey Diane E Dickel Valentina Snetkova Xintao Wei Xiaofeng Wang Juan Carlos Rivera-Mulia Joel Rozowsky Jing Zhang Surya B Chhetri Jialing Zhang Alec Victorsen Kevin P White Axel Visel Gene W Yeo Christopher B Burge Eric Lécuyer David M Gilbert Job Dekker John Rinn Eric M Mendenhall Joseph R Ecker Manolis Kellis Robert J Klein William S Noble Anshul Kundaje Roderic Guigó Peggy J Farnham J Michael Cherry Richard M Myers Bing Ren Brenton R Graveley Mark B Gerstein Len A Pennacchio Michael P Snyder Bradley E Bernstein Barbara Wold Ross C Hardison Thomas R Gingeras John A Stamatoyannopoulos Zhiping Weng University of Massachusetts Medical School Program in Bioinformatics and Integrative Biology Worcester MA USA. The Broad Institute of Harvard and MIT Cambridge MA USA. Department of Genetics School of Medicine Stanford University Palo Alto CA USA. Cold Spring Harbor Laboratory Functional Genomics Cold Spring Harbor NY USA. Altius Institute for Biomedical Sciences Seattle WA USA. Department of Medicine University of Washington School of Medicine Seattle WA USA. Department of Cellular and Molecular Medicine Institute for Genomic Medicine Stem Cell Program Sanford Consortium for Regenerative Medicine University of California San Diego La Jolla CA USA. Program in Computational and Systems Biology Massachusetts Institute of Technology Cambridge MA USA. Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA. Ludwig Institute for Cancer Research University of California San Diego La Jolla CA USA. Institute for Human Genetics Department of Neurology University of California San Francisco San Francisco CA USA. Genomics Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA. HudsonAlpha Institute for Biotechnology Huntsville AL USA. Division of Biology and Biological Engineering California Institute of Technology Pasadena CA USA. Department of Developmental and Cell Biology University of California Irvine Irvine CA USA. Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park PA USA. Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory Berkeley CA USA. Department of Genetics and Genome Sciences Institute for Systems Genomics UConn Health Farmington CT USA. Département de Biochimie et Médecine Moléculaire Université de Montréal Montréal Quebec Canada. Division of Experimental Medicine McGill University Montreal Quebec Canada. Institut de Recherches Cliniques de Montréal (IR

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An easy-to-hard learning paradigm for multiple classes and multiple labels

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2017年第1期18卷

作者： Weiwei Liu Ivor W. Tsang Klaus-Robert Müller School of Computer Science and Engineering The University of New South Wales Sydney NSW Australia and Centre for Artificial Intelligence FEIT University of Technology Sydney NSW Australia Centre for Artificial Intelligence FEIT University of Technology Sydney NSW Australia Machine Learning Group Computer Science Berlin Institute of Technology Berlin Germany and Max Planck Institute for Informatics Saarbrcken and Department of Brain and Cognitive Engineering Korea University Seoul Korea

Many applications, such as human action recognition and object detection, can be formulated as a multiclass classification problem. One-vs-rest (OVR) is one of the most widely used approaches for multiclass classification due to its simplicity and excellent performance. However, many confusing classes in such applications will degrade its results. For example, hand clap and boxing are two confusing actions. Hand clap is easily misclassified as boxing, and vice versa. Therefore, precisely classifying confusing classes remains a challenging task. To obtain better performance for multiclass classifications that have confusing classes, we first develop a classifier chain model for multiclass classification (CCMC) to transfer class information between classifiers. Then, based on an analysis of our proposed model, we propose an easy-to-hard learning paradigm for multiclass classification to automatically identify easy and hard classes and then use the predictions from simpler classes to help solve harder classes. Similar to CCMC, the classifier chain (CC) model is also proposed by Read et al. (2009) to capture the label dependency for multi-label classification. However, CC does not consider the order of di_culty of the labels and achieves degenerated performance when there are many confusing labels. Therefore, it is non-trivial to learn the appropriate label order for CC. Motivated by our analysis for CCMC, we also propose the easy-to-hard learning paradigm for multi-label classification to automatically identify easy and hard labels, and then use the predictions from simpler labels to help solve harder labels. We also demonstrate that our proposed strategy can be successfully applied to a wide range of applications, such as ordinal classification and relationship prediction. Extensive empirical studies validate our analysis and the efiectiveness of our proposed easy-to-hard learning strategies.

关键词： classifier Chain easy-to-hard learning paradigm multi-label classification multiclass classification

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Application of pattern spectra and convolutional neural networks to the analysis of simulated Cherenkov Telescope Array data

arXiv

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arXiv 2021年

作者： Aschersleben, Jann Peletier, R.F. Vecchi, M. Wilkinson, M.H.F. Abdalla, H. Abe, H. Abe, S. Abusleme, A. Acero, F. Acharyya, A. Portella, V. Acín Ackley, K. Adam, R. Adams, C. Adhikari, S.S. Aguado-Ruesga, I. Agudo, I. Aguilera, R. Aguirre-Santaella, A. Aharonian, F. Alberdi, A. Alfaro, R. Alfaro, J. Alispach, C. Aloisio, R. Batista, R. Alves Amans, J.-P. Amati, L. Amato, E. Ambrogi, L. Ambrosi, G. Ambrosio, M. Ammendola, R. Anderson, J. Anduze, M. Angüner, E.O. Antonelli, L.A. Antonuccio, V. Antoranz, P. Anutarawiramkul, R. Gutierrez, J. Aragunde Aramo, C. Araudo, A. Araya, M. Arbet-Engels, A. Arcaro, C. Arendt, V. Armand, C. Armstrong, T. Arqueros, F. Arrabito, L. Arsioli, B. Artero, M. Asano, K. Ascasíbar, Y. Ashley, M. Attinà, P. Aubert, P. Singh, C.B. Baack, D. Babic, A. Backes, M. Baena, V. Bajtlik, S. Baktash, A. Balazs, C. Balbo, M. Ballester, O. Ballet, J. Balmaverde, B. Bamba, A. Bandiera, R. Larriva, A. Baquero Barai, P. Barbier, C. Martins, V. Barbosa Barcelo, M. Barkov, M. Barnard, M. Baroncelli, L. de Almeida, U. Barres Barrio, J.A. Bastieri, D. Batista, P.I. Batkovic, I. Bauer, C. Bautista-González, R. Baxter, J. Becciani, U. González, J. Becerra Becherini, Y. Beck, G. Tjus, J. Becker Bednarek, W. Belfiore, A. Bellizzi, L. Belmont, R. Benbow, W. Berge, D. Bernardini, E. Bernardos, M.I. Bernlöhr, K. Berti, A. Berton, M. Bertucci, B. Beshley, V. Bhatt, N. Bhattacharyya, S. Bhattacharyya, W. Bhattacharyya, S. Bi, B. Bicknell, G. Biederbeck, N. Bigongiari, C. Biland, A. Bird, R. Bissaldi, E. Biteau, J. Bitossi, M. Blanch, O. Blank, M. Blazek, J. Bobin, J. Boccato, C. Bocchino, F. Boehm, C. Bohacova, M. Boisson, C. Boix, J. Bolle, J.-P. Bolmont, J. Bonanno, G. Bonavolontà, C. Arbeletche, L. Bonneau Bonnoli, G. Bordas, P. Borkowski, J. Bórquez, S. Bose, R. Bose, D. Bosnjak, Z. Bottacini, E. Böttcher, M. Botticella, M.T. Boutonnet, C. Bouyjou, F. Bozhilov, V. Bozzo, E. Brahimi, L. Braiding, C. Brau-Nogué, S. Breen, S. Kapteyn Astronomical Institute University of Groningen PO Box 800 Groningen9700 AV Netherlands Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen PO Box 407 AK GroningenNL-9700 Netherlands Centre for Space Research North-West University Potchefstroom2520 South Africa Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Pontificia Universidad Católica de Chile Av. Libertador Bernardo O'Higgins 340 Santiago Chile AIM CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité CEA Paris-Saclay IRFU/DAp Bat 709 Orme des Merisiers Gif-sur-Yvette91191 France Centre for Advanced Instrumentation Dept. of Physics Durham University South Road DurhamDH1 3LE United Kingdom Port d'Informació Científica Edifici D Carrer de l'Albareda Cerdanyola del Vallès Bellaterrra08193 Spain School of Physics and Astronomy Monash University MelbourneVIC3800 Australia Palaiseau91128 France Department of Physics Columbia University 538 West 120th Street New YorkNY10027 United States University of Oslo Department of Physics Sem Saelandsvei 24 - PO Box 1048 Blindern OsloN-0316 Norway EMFTEL Department IPARCOS Universidad Complutense de Madrid Madrid28040 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Campus UAB Carrer de Can Magrans s/n Cerdanyola del Vallés08193 Spain Instituto de Física Teórica UAM/CSIC Departamento de Física Teórica Universidad Autónoma de Madrid Campus de Cantoblanco UAM c/ Nicolás Cabrera 13-15 Madrid28049 Spain Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Universidad Nacional Autónoma de México Delegación Coyoacán Ciudad de México04510 Mexico University of Geneva Département de Physique Nucléaire et Corpusculaire 24 rue du Général-Dufour Genève 41211 Switzerland INFN Dipartimento di Scienze Fisiche e Chimiche Università

The Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory and will be the major global instrument for very-high-energy astronomy over the next decade, offering 5 - 10 × better flux sensitivity than current generation gamma-ray telescopes. Each telescope will provide a snapshot of gamma-ray induced particle showers by capturing the induced Cherenkov emission at ground level. The simulation of such events provides images that can be used as training data for convolutional neural networks (CNNs) to determine the energy of the initial gamma rays. Compared to other state-of-the-art algorithms, analyses based on CNNs promise to further enhance the performance to be achieved by CTA. Pattern spectra are commonly used tools for image classification and provide the distributions of the shapes and sizes of various objects comprising an image. The use of relatively shallow CNNs on pattern spectra would automatically select relevant combinations of features within an image, taking advantage of the 2D nature of pattern spectra. In this work, we generate pattern spectra from simulated gamma-ray events instead of using the raw images themselves in order to train our CNN for energy reconstruction. This is different from other relevant learning and feature selection methods that have been tried in the past. Thereby, we aim to obtain a significantly faster and less computationally intensive algorithm, with minimal loss of performance. © 2021, CC BY.

关键词： Gamma rays

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Test of Lepton Flavor Universality with B+→K+π+π−ℓ+ℓ− Decays

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Physical Review Letters 2025年第18期134卷 181803-181803页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellan Beteta F. Abudinén T. Ackernley A. A. Adefisoye B. Adeva M. Adinolfi P. Adlarson C. Agapopoulou C. A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht F. Alessio M. Alexander Z. Aliouche P. Alvarez Cartelle R. Amalric S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov P. Andreola M. Andreotti D. Andreou A. Anelli D. Ao F. Archilli M. Argenton S. Arguedas Cuendis A. Artamonov M. Artuso E. Aslanides R. Ataíde Da Silva M. Atzeni B. Audurier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R. J. Barlow M. Barnyakov S. Barsuk W. Barter J. Bartz J. M. Basels S. Bashir G. Bassi B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I. B. Bediaga N. A. Behling S. Belin K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko J. Bhom M. S. Bieker N. V. Biesuz P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J. E. Blank S. Blusk V. Bocharnikov J. A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C. S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J. T. Borsuk E. Bottalico S. A. Bouchiba M. Bovill T. J. V. Bowcock A. Boyer C. Bozzi J. D. Brandenburg A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan L. Buonincontri M. Burgos Marcos A. T. Burke C. Burr J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai A. C. Caillet R. Calabrese S. Calderon Ramirez L. Calefice S. Cali M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Syracuse University Syracuse New York USA Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Department of Physics and Astronomy Uppsala University Uppsala Sweden (associated with School of Physics and Astronomy University of Glasgow Glasgow United Kingdom) Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France INFN Laboratori Nazionali di Frascati Frascati Italy Fakultät Physik Technische Universität Dortmund Dortmund Germany Also at Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany. European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Department of Physics and Astronomy University of Manchester Manchester United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China INFN Sezione di Firenze Firenze Italy Authors affiliated with an institute formerly covered by a cooperation agreement with CERN INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Milano-Bicocca Milano Italy Also at Università degli Studi di Milano-Bicocca Milano Italy. University of Chinese Academy o

The first test of lepton flavor universality between muons and electrons using B+→K+π+π−ℓ+ℓ− (ℓ=e, μ) decays is presented. The measurement is performed with data from proton-proton collisions collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. The ratio of branching fractions between B+→K+π+π−e+e− and B+→K+π+π−μ+μ− decays is measured in the dilepton invariant-mass-squared range 1.1

关键词： Charged particles

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Search for resonance-enhanced CP and angular asymmetries in the Λc+→pμ+μ− decay at LHCb

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Physical Review D 2025年第9期111卷 L091102-L091102页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellan Beteta F. Abudinén T. Ackernley A. A. Adefisoye B. Adeva M. Adinolfi P. Adlarson C. Agapopoulou C. A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht F. Alessio M. Alexander Z. Aliouche P. Alvarez Cartelle R. Amalric S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov P. Andreola M. Andreotti D. Andreou A. Anelli D. Ao F. Archilli M. Argenton S. Arguedas Cuendis A. Artamonov M. Artuso E. Aslanides R. Ataíde Da Silva M. Atzeni B. Audurier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R. J. Barlow M. Barnyakov S. Barsuk W. Barter J. Bartz J. M. Basels S. Bashir G. Bassi B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I. B. Bediaga N. A. Behling S. Belin K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko J. Bhom M. S. Bieker N. V. Biesuz P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J. E. Blank S. Blusk V. Bocharnikov J. A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C. S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J. T. Borsuk E. Bottalico S. A. Bouchiba M. Bovill T. J. V. Bowcock A. Boyer C. Bozzi J. D. Brandenburg A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan L. Buonincontri M. Burgos Marcos A. T. Burke C. Burr J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai A. Caillet R. Calabrese S. Calderon Ramirez L. Calefice S. Cali M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M. C Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Syracuse University Syracuse New York USA Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Department of Physics and Astronomy Uppsala University Uppsala Sweden (associated with School of Physics and Astronomy University of Glasgow Glasgow United Kingdom) Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse NewYork USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France INFN Laboratori Nazionali di Frascati Frascati Italy Fakultät Physik Technische Universität Dortmund Dortmund Germany Also at Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany. European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Department of Physics and Astronomy University of Manchester Manchester United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China INFN Sezione di Firenze Firenze Italy Authors affiliated with an institute formerly covered by a cooperation agreement with CERN INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Milano-Bicocca Milano Italy Also at Università degli Studi di Milano-Bicocca Milano Italy. University of Chinese Academy of

The first measurement of the CP asymmetry of the decay rate (ACP) and the CP average (ΣAFB) and CP asymmetry (ΔAFB) of the forward-backward asymmetry in the muon system of Λc+→pμ+μ− decays is reported. The measurement is performed using a data sample of proton-proton collisions, recorded by the LHCb experiment from 2016 to 2018 at a center-of-mass energy of 13 TeV, which corresponds to an integrated luminosity of 5.4 fb−1. The asymmetries are measured in two regions of dimuon mass near the ϕ-meson mass peak. The dimuon-mass integrated results are ACP=(−1.1±4.0±0.5)%, ΣAFB=(3.9±4.0±0.6)%, ΔAFB=(3.1±4.0±0.4)%, where the first uncertainty is statistical and the second systematic. The results are consistent with the conservation of CP symmetry and the Standard Model expectations.

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Branching fraction measurement of the decay B+→ψ(2S)ϕ(1020)K+

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Physical Review D 2025年第9期111卷 092008-092008页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellan Beteta F. Abudinén T. Ackernley A. A. Adefisoye B. Adeva M. Adinolfi P. Adlarson C. Agapopoulou C. A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht F. Alessio Z. Aliouche P. Alvarez Cartelle R. Amalric S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov P. Andreola M. Andreotti D. Andreou A. Anelli D. Ao F. Archilli M. Argenton S. Arguedas Cuendis A. Artamonov M. Artuso E. Aslanides R. Ataíde Da Silva M. Atzeni B. Audurier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R. J. Barlow M. Barnyakov S. Barsuk W. Barter M. Bartolini J. Bartz J. M. Basels S. Bashir G. Bassi B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I. B. Bediaga N. A. Behling S. Belin K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko J. Bhom M. S. Bieker N. V. Biesuz P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J. E. Blank S. Blusk V. Bocharnikov J. A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C. S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J. T. Borsuk S. A. Bouchiba M. Bovill T. J. V. Bowcock A. Boyer C. Bozzi A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan A. Buonaura L. Buonincontri A. T. Burke C. Burr J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai A. Caillet R. Calabrese S. Calderon Ramirez L. Calefice S. Cali M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M. Cattaneo G. Cavallero V. Cavallini S. Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Syracuse University Syracuse New York USA Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Department of Physics and Astronomy Uppsala University Uppsala Sweden (associated with Institution School of Physics and Astronomy University of Glasgow Glasgow United Kingdom) Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati Ohio USA INFN Laboratori Nazionali di Frascati Frascati Italy Fakultät Physik Technische Universität Dortmund Dortmund Germany Also at Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany. European Organization for Nuclear Research (CERN) Geneva Switzerland Department of Physics and Astronomy University of Manchester Manchester United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China INFN Sezione di Firenze Firenze Italy Authors affiliated with an institute formerly covered by a cooperation agreement with CERN INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Milano-Bicocca Milano Italy Also at Università degli Studi di Milano-Bicocca Milano Italy. University of Chinese Academy of Sciences Beijing

The branching fraction of the decay B+→ψ(2S)ϕ(1020)K+, relative to the topologically similar decay B+→J/ψϕ(1020)K+, is measured using proton-proton collision data collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. The ratio is found to be 0.061±0.004±0.009, where the first uncertainty is statistical and the second systematic. Using the world-average branching fraction for B+→J/ψϕ(1020)K+, the branching fraction for the decay B+→ψ(2S)ϕ(1020)K+ is found to be (3.0±0.2±0.5±0.2)×10−6, where the first uncertainty is statistical, the second systematic, and the third is due to the branching fraction of the normalization channel.

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Study of light-meson resonances decaying to KS0Kπ in the B→(KS0Kπ)K channels

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Physical Review D 2025年第9期111卷 092009-092009页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellan Beteta F. Abudinén T. Ackernley A. A. Adefisoye B. Adeva M. Adinolfi P. Adlarson C. Agapopoulou C. A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht F. Alessio M. Alexander Z. Aliouche P. Alvarez Cartelle R. Amalric S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov P. Andreola M. Andreotti D. Andreou A. Anelli D. Ao F. Archilli M. Argenton S. Arguedas Cuendis A. Artamonov M. Artuso E. Aslanides R. Ataíde Da Silva M. Atzeni B. Audurier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R. J. Barlow M. Barnyakov S. Barsuk W. Barter J. Bartz J. M. Basels S. Bashir G. Bassi B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I. B. Bediaga N. A. Behling S. Belin K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko J. Bhom M. S. Bieker N. V. Biesuz P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J. E. Blank S. Blusk V. Bocharnikov J. A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C. S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J. T. Borsuk E. Bottalico S. A. Bouchiba M. Bovill T. J. V. Bowcock A. Boyer C. Bozzi J. D. Brandenburg A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan L. Buonincontri M. Burgos Marcos A. T. Burke C. Burr J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai A. Caillet R. Calabrese S. Calderon Ramirez L. Calefice S. Cali M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M. C Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Syracuse University Syracuse New York USA Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Department of Physics and Astronomy Uppsala University Uppsala Sweden (associated with School of Physics and Astronomy University of Glasgow Glasgow United Kingdom) Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France INFN Laboratori Nazionali di Frascati Frascati Italy Fakultät Physik Technische Universität Dortmund Dortmund Germany Also at Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany. European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Department of Physics and Astronomy University of Manchester Manchester United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China INFN Sezione di Firenze Firenze Italy Authors affiliated with an institute formerly covered by a cooperation agreement with CERN INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Milano-Bicocca Milano Italy Also at Università degli Studi di Milano-Bicocca Milano Italy. University of Chinese Academy o

A study is presented of B+→KS0K−π+K+ and B+→KS0K+π−K+ decays based on the analysis of proton-proton collision data collected with the LHCb detector at center-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb−1. The KS0Kπ invariant-mass distributions of both B+ decay modes show, in the m(KS0Kπ)<1.85 GeV mass region, large activity which is resolved using an amplitude analysis. A simple model, where JPC amplitudes are described by multiple Breit-Wigner functions with appropriate angular distributions, provides a good description of the experimental data. In this approach a complex mixture of JPC=0−+, 1++ and 1+− amplitudes is observed that is dominated by η(1405), η(1470), η(1760), f1(1285), f1(1420) and h1(1405) resonances. The KS0Kπ Dalitz plots are dominated by asymmetric crossing K*K¯ bands which are different for the two B+ decay modes. This is due to a different interference pattern between the 1++ and 1+− amplitudes in the two channels. Branching fractions are measured for each resonant contribution.

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Search for D0 meson decays to π+π−e+e− and K+K−e+e− final states

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Physical Review D 2025年第9期111卷 L091101-L091101页

A search for D0 meson decays to the π+π−e+e− and K+K−e+e− final states is reported using a sample of proton-proton collisions collected by the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1. The decay D0→π+π−e+e− is observed for the first time when requiring that the two electrons are consistent with coming from the decay of a ϕ or ρ0/ω meson. The corresponding branching fractions are measured relative to the D0→K−π−[e+e−]ρ0/ω decay, where the two electrons are consistent with coming from the decay of a ρ0 or ω meson. No evidence is found for the D0→K+K−e+e− decay and world-best limits are set on its branching fraction. The results are compared to, and found to be consistent with, the branching fractions of the D0→π+π−μ+μ− and D0→K+K−μ+μ− decays recently measured by LHCb and confirm lepton universality at the current precision.

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Measurement of CP asymmetries in Λb0→ph− decays

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Physical Review D 2025年第9期111卷 092004-092004页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellan Beteta F. Abudinén T. Ackernley A. A. Adefisoye B. Adeva M. Adinolfi P. Adlarson C. Agapopoulou C. A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht F. Alessio M. Alexander Z. Aliouche P. Alvarez Cartelle R. Amalric S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov P. Andreola M. Andreotti D. Andreou A. Anelli D. Ao F. Archilli M. Argenton S. Arguedas Cuendis A. Artamonov M. Artuso E. Aslanides R. Ataíde Da Silva M. Atzeni B. Audurier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R. J. Barlow M. Barnyakov S. Barsuk W. Barter J. Bartz J. M. Basels S. Bashir G. Bassi B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I. B. Bediaga N. A. Behling S. Belin K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko J. Bhom M. S. Bieker N. V. Biesuz P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J. E. Blank S. Blusk V. Bocharnikov J. A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C. S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J. T. Borsuk E. Bottalico S. A. Bouchiba M. Bovill T. J. V. Bowcock A. Boyer C. Bozzi J. D. Brandenburg A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan L. Buonincontri M. Burgos Marcos A. T. Burke C. Burr J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai A. C. Caillet R. Calabrese S. Calderon Ramirez L. Calefice S. Cali M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Syracuse University Syracuse New York USA Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Department of Physics and Astronomy Uppsala University Uppsala Sweden (associated with School of Physics and Astronomy University of Glasgow Glasgow United Kingdom) Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France INFN Laboratori Nazionali di Frascati Frascati Italy Fakultät Physik Technische Universität Dortmund Dortmund Germany Also at Lamarr Institute for Machine Learning and Artificial Intelligence Dortmund Germany. European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom Department of Physics and Astronomy University of Manchester Manchester United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China INFN Sezione di Firenze Firenze Italy Affiliated with an institute formerly covered by a cooperation agreement with CERN INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Milano-Bicocca Milano Italy Also at Università degli Studi di Milano-Bicocca Milano Italy. University of Chinese Academy of Scienc

A search for CP violation in Λb0→pK− and Λb0→pπ− decays is presented using the full Run 1 and Run 2 data samples of pp collisions collected with the LHCb detector, corresponding to an integrated luminosity of 9 fb−1 at center-of-mass energies of 7, 8, and 13 TeV. For the Run 2 data sample, the CP-violating asymmetries are measured to be ACPpK−=(−1.4±0.7±0.4)% and ACPpπ−=(0.4±0.9±0.4)%, where the first uncertainty is statistical and the second is systematic. Following significant improvements in the evaluation of systematic uncertainties compared to the previous LHCb measurement, the Run 1 dataset is reanalyzed to update the corresponding results. When combining the Run 2 and updated Run 1 measurements, the final results are found to be ACPpK−=(−1.1±0.7±0.4)% and ACPpπ−=(0.2±0.8±0.4)%, constituting the most precise measurements of these asymmetries to date.

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