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Liu S, Lu Y, Tian D, Zhang T, Zhang C, Hu CY, Chen P, Meng Y. Hydroxytyrosol Alleviates Obesity-Induced Cognitive Decline by Modulating the Expression Levels of Brain-Derived Neurotrophic Factors and Inflammatory Factors in Mice. J Agric Food Chem 2024; 72:6250-6264. [PMID: 38491001 DOI: 10.1021/acs.jafc.3c08319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
Abstract
Hydroxytyrosol (HT; 3,4-dihydroxyphenyl ethanol) is an important functional polyphenol in olive oil. Our study sought to evaluate the protective effects and underlying mechanisms of HT on obesity-induced cognitive impairment. A high-fat and high-fructose-diet-induced obese mice model was treated with HT for 14 weeks. The results show that HT improved the learning and memory abilities and enhanced the expressions of brain-derived neurotrophic factors (BDNFs) and postsynaptic density proteins, protecting neuronal and synaptic functions in obese mice. Transcriptomic results further confirmed that HT improved cognitive impairment by regulating gene expression in neural system development and synaptic function-related pathways. Moreover, HT treatment alleviated neuroinflammation in the brain of obese mice. To sum up, our results indicated that HT can alleviate obesity-induced cognitive dysfunction by enhancing BDNF expression and alleviating neuroinflammation in the brain, which also means that HT may become a potentially useful nutritional supplement to alleviate obesity-induced cognitive decline.
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Affiliation(s)
- Shenlin Liu
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
| | - Yalong Lu
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
| | - Dan Tian
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
| | - Tingting Zhang
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
| | - Chaoqun Zhang
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
| | - Ching Yuan Hu
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
- Department of Human Nutrition, Food and Animal Sciences, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, 1955 East-West Road, AgSci. 415J, Honolulu, Hawaii 96822, United States
| | - Ping Chen
- Shaanxi Provincial Center for Disease Control and Prevention, Xian, Shaanxi 710054, P. R. China
| | - Yonghong Meng
- The Engineering Research Center of High-Valued Utilization of Fruit Resources in Western China, Ministry of Education; National Research & Development Center of Apple Processing Technology; College of Food Engineering and Nutritional Science, Shaanxi Normal University, 620 West Changan Avenue, Xian, Shaanxi 710119, P. R. China
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Denomme MM, McCallie BR, Haywood ME, Parks JC, Schoolcraft WB, Katz-Jaffe MG. Paternal aging impacts expression and epigenetic markers as early as the first embryonic tissue lineage differentiation. Hum Genomics 2024; 18:32. [PMID: 38532526 PMCID: PMC10964547 DOI: 10.1186/s40246-024-00599-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 03/14/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Advanced paternal age (APA) is associated with adverse outcomes to offspring health, including increased risk for neurodevelopmental disorders. The aim of this study was to investigate the methylome and transcriptome of the first two early embryonic tissue lineages, the inner cell mass (ICM) and the trophectoderm (TE), from human blastocysts in association with paternal age and disease risk. High quality human blastocysts were donated with patient consent from donor oocyte IVF cycles from either APA (≥ 50 years) or young fathers. Blastocysts were mechanically separated into ICM and TE lineage samples for both methylome and transcriptome analyses. RESULTS Significant differential methylation and transcription was observed concurrently in ICM and TE lineages of APA-derived blastocysts compared to those from young fathers. The methylome revealed significant enrichment for neuronal signaling pathways, as well as an association with neurodevelopmental disorders and imprinted genes, largely overlapping within both the ICM and TE lineages. Significant enrichment of neurodevelopmental signaling pathways was also observed for differentially expressed genes, but only in the ICM. In stark contrast, no significant signaling pathways or gene ontology terms were identified in the trophectoderm. Despite normal semen parameters in aged fathers, these significant molecular alterations can adversely contribute to downstream impacts on offspring health, in particular neurodevelopmental disorders like autism spectrum disorder and schizophrenia. CONCLUSIONS An increased risk for neurodevelopmental disorders is well described in children conceived by aged fathers. Using blastocysts derived from donor oocyte IVF cycles to strategically control for maternal age, our data reveals evidence of methylation dysregulation in both tissue lineages, as well as transcription dysregulation in neurodevelopmental signaling pathways associated with APA fathers. This data also reveals that embryos derived from APA fathers do not appear to be compromised for initial implantation potential with no significant pathway signaling disruption in trophectoderm transcription. Collectively, our work provides insights into the complex molecular mechanisms that occur upon paternal aging during the first lineage differentiation in the preimplantation embryo. Early expression and epigenetic markers of APA-derived preimplantation embryos highlight the susceptibility of the future fetus to adverse health outcomes.
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Affiliation(s)
| | - Blair R McCallie
- CCRM Genetics, 10290 Ridgegate Circle, Lone Tree, CO, 80124, USA
| | - Mary E Haywood
- CCRM Genetics, 10290 Ridgegate Circle, Lone Tree, CO, 80124, USA
| | - Jason C Parks
- CCRM Genetics, 10290 Ridgegate Circle, Lone Tree, CO, 80124, USA
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Glausier JR, Bouchet-Marquis C, Maier M, Banks-Tibbs T, Wu K, Ning J, Melchitzky D, Lewis DA, Freyberg Z. Characterization of the three-dimensional synaptic and mitochondrial nanoarchitecture within glutamatergic synaptic complexes in postmortem human brain via focused ion beam-scanning electron microscopy. bioRxiv 2024:2024.02.26.582174. [PMID: 38463986 PMCID: PMC10925168 DOI: 10.1101/2024.02.26.582174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Glutamatergic synapses are the primary site of excitatory synaptic signaling and neural communication in the cerebral cortex. Electron microscopy (EM) studies in non-human model organisms have demonstrated that glutamate synaptic activity and functioning are directly reflected in quantifiable ultrastructural features. Thus, quantitative EM analysis of glutamate synapses in ex vivo preserved human brain tissue has the potential to provide novel insight into in vivo synaptic functioning. However, factors associated with the acquisition and preservation of human brain tissue have resulted in persistent concerns regarding the potential confounding effects of antemortem and postmortem biological processes on synaptic and sub-synaptic ultrastructural features. Thus, we sought to determine how well glutamate synaptic relationships and nanoarchitecture are preserved in postmortem human dorsolateral prefrontal cortex (DLPFC), a region that substantially differs in size and architecture from model systems. Focused ion beam-scanning electron microscopy (FIB-SEM), a powerful volume EM (VEM) approach, was employed to generate high-fidelity, fine-resolution, three-dimensional (3D) micrographic datasets appropriate for quantitative analyses. Using postmortem human DLPFC with a 6-hour postmortem interval, we optimized a tissue preservation and staining workflow that generated samples of excellent ultrastructural preservation and the high-contrast staining intensity required for FIB-SEM imaging. Quantitative analysis of sub-cellular, sub-synaptic and organelle components within glutamate axo-spinous synapses revealed that ultrastructural features of synaptic function and activity were well-preserved within and across individual synapses in postmortem human brain tissue. The synaptic, sub-synaptic and organelle measures were highly consistent with findings from experimental models that are free from antemortem or postmortem effects. Further, dense reconstruction of neuropil revealed a unique, ultrastructurally-complex, spiny dendritic shaft that exhibited features characteristic of neuronal processes with heightened synaptic communication, integration and plasticity. Altogether, our findings provide a critical proof-of-concept that ex vivo VEM analysis provides a valuable and informative means to infer in vivo functioning of human brain.
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Affiliation(s)
| | | | | | - Tabitha Banks-Tibbs
- Department of Psychiatry, University of Pittsburgh
- Department of Human Genetics, University of Pittsburgh
- College of Medicine, The Ohio State University
| | - Ken Wu
- Materials and Structural Analysis, Thermo Fisher Scientific
| | - Jiying Ning
- Department of Psychiatry, University of Pittsburgh
| | | | | | - Zachary Freyberg
- Department of Psychiatry, University of Pittsburgh
- Department of Cell Biology, University of Pittsburgh
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4
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Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Li Q, Xu Z, Men W, Wang Y, Tan S, Gao JH, Qin S, Tao S, Dong Q, Zhao T, He Y. Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence. Nat Commun 2024; 15:784. [PMID: 38278807 PMCID: PMC10817914 DOI: 10.1038/s41467-024-44863-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.
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Affiliation(s)
- Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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5
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Li S, Spitz N, Ghantous A, Abrishamcar S, Reimann B, Marques I, Silver MJ, Aguilar-Lacasaña S, Kitaba N, Rezwan FI, Röder S, Sirignano L, Tuhkanen J, Mancano G, Sharp GC, Metayer C, Morimoto L, Stein DJ, Zar HJ, Alfano R, Nawrot T, Wang C, Kajantie E, Keikkala E, Mustaniemi S, Ronkainen J, Sebert S, Silva W, Vääräsmäki M, Jaddoe VWV, Bernstein RM, Prentice AM, Cosin-Tomas M, Dwyer T, Håberg SE, Herceg Z, Magnus MC, Munthe-Kaas MC, Page CM, Völker M, Gilles M, Send T, Witt S, Zillich L, Gagliardi L, Richiardi L, Czamara D, Räikkönen K, Chatzi L, Vafeiadi M, Arshad SH, Ewart S, Plusquin M, Felix JF, Moore SE, Vrijheid M, Holloway JW, Karmaus W, Herberth G, Zenclussen A, Streit F, Lahti J, Hüls A, Hoang TT, London SJ, Wiemels JL. A Pregnancy and Childhood Epigenetics Consortium (PACE) meta-analysis highlights potential relationships between birth order and neonatal blood DNA methylation. Commun Biol 2024; 7:66. [PMID: 38195839 PMCID: PMC10776586 DOI: 10.1038/s42003-023-05698-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 12/12/2023] [Indexed: 01/11/2024] Open
Abstract
Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P < 0.05) and 1107 regions. Forty CpGs were located within known quantitative trait loci for gene expression traits in blood, and trait enrichment analysis suggested a strong association with immune-related, transcriptional control, and blood pressure regulation phenotypes. Decreasing fertility rates worldwide with the concomitant increased proportion of first-born children highlights a potential reflection of birth order-related epigenomic states on changing disease incidence trends.
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Affiliation(s)
- Shaobo Li
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Natalia Spitz
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Brigitte Reimann
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Irene Marques
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Matt J Silver
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, UK
| | - Sofía Aguilar-Lacasaña
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Negusse Kitaba
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK
| | - Stefan Röder
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Giulia Mancano
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Catherine Metayer
- School of Public Health, University of California Berkeley, Berkeley, California, USA
| | - Libby Morimoto
- School of Public Health, University of California Berkeley, Berkeley, California, USA
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Rondebosch, South Africa
| | - Heather J Zar
- SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Rondebosch, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Rondebosch, South Africa
| | - Rossella Alfano
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Tim Nawrot
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Eero Kajantie
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Pediatric Research Centre, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Elina Keikkala
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - Sanna Mustaniemi
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - Justiina Ronkainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Wnurinham Silva
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Marja Vääräsmäki
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Robin M Bernstein
- Department of Anthropology and Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Andrew M Prentice
- MRC Unit The Gambia at the London School of Hygiene & Tropical Medicine, Fajara, The Gambia
| | - Marta Cosin-Tomas
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Terence Dwyer
- Nuffield Department of Women's & Reproductive Health, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Siri Eldevik Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Monica Cheng Munthe-Kaas
- Department of Pediatric Oncology and Hematology, Oslo University Hospital, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Physical Health and Aging, Division for Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maja Völker
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Maria Gilles
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tabea Send
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Luigi Gagliardi
- Woman and Child Health Department, Ospedale Versilia, AUSL Toscana Nord Ovest, Pisa, Italy
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin, CPO Piemonte, Turin, Italy
| | - Darina Czamara
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Lida Chatzi
- Department of Population and Public Health Sciences, Keck School of Medicine of USC. University of Southern California, Los Angeles, CA, USA
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - S Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Michelle Plusquin
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sophie E Moore
- Department of Women & Children's Health, King's College London, London, UK
| | - Martine Vrijheid
- ISGlobal, Institute for Global Health, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Gunda Herberth
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
| | - Ana Zenclussen
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
- Perinatal Immunology, Medical Faculty, Saxonian Incubator for Clinical Translation (SIKT), University of Leipzig, Leipzig, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA.
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6
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Alcaide Martin A, Mayerl S. Local Thyroid Hormone Action in Brain Development. Int J Mol Sci 2023; 24:12352. [PMID: 37569727 PMCID: PMC10418487 DOI: 10.3390/ijms241512352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 07/28/2023] [Accepted: 07/30/2023] [Indexed: 08/13/2023] Open
Abstract
Proper brain development essentially depends on the timed availability of sufficient amounts of thyroid hormone (TH). This, in turn, necessitates a tightly regulated expression of TH signaling components such as TH transporters, deiodinases, and TH receptors in a brain region- and cell-specific manner from early developmental stages onwards. Abnormal TH levels during critical stages, as well as mutations in TH signaling components that alter the global and/or local thyroidal state, result in detrimental consequences for brain development and neurological functions that involve alterations in central neurotransmitter systems. Thus, the question as to how TH signaling is implicated in the development and maturation of different neurotransmitter and neuromodulator systems has gained increasing attention. In this review, we first summarize the current knowledge on the regulation of TH signaling components during brain development. We then present recent advances in our understanding on how altered TH signaling compromises the development of cortical glutamatergic neurons, inhibitory GABAergic interneurons, cholinergic and dopaminergic neurons. Thereby, we highlight novel mechanistic insights and point out open questions in this evolving research field.
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Affiliation(s)
| | - Steffen Mayerl
- Department of Endocrinology Diabetes & Metabolism, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147 Essen, Germany
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Xiong M, Roshanbin S, Sehlin D, Hansen HD, Knudsen GM, Rokka J, Eriksson J, Syvänen S. Synaptic density in aging mice measured by [ 18F]SynVesT-1 PET. Neuroimage 2023:120230. [PMID: 37355199 DOI: 10.1016/j.neuroimage.2023.120230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 05/03/2023] [Accepted: 06/14/2023] [Indexed: 06/26/2023] Open
Abstract
Synaptic alterations in certain brain structures are related to cognitive decline in neurodegeneration and in aging. Synaptic loss in many neurodegenerative diseases can be visualized by positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A). However, the use of SV2A PET for studying synaptic changes during aging is not particularly explored. Thus, in the present study, PET ligand [18F]SynVesT-1, which binds to SV2A, was used to investigate synaptic density at different ages in healthy mice. Wild type C57BL/6 mice divided into three age groups (4-5 months (n = 7), 12-14 months (n = 11), 17-19 months (n = 7)) were PET scanned with [18F]SynVesT-1. Brain retention of [18F]SynVesT-1 expressed as the volume of distribution (VIDIF) was calculated using an image-derived input function. Estimates of VIDIF were derived using either a one-tissue compartment model (1TCM), a two-tissue compartment model (2TCM), or the Logan plot with blood input to find the best-fit model for [18F]SynVesT-1. After the PET scans, tissue sections were immunostained for the detection of SV2A and neuronal markers. We found that [18F]SynVesT-1 data acquired 60 min post intravenously injection and analyzed with 1TCM described the brain pharmacokinetics of the radioligand in mice well. [18F]SynVesT-1 brain retention was lower in the oldest group of mice, indicating a decrease in synaptic density in this age group. However, no gradual age-dependent decrease in synaptic density at a region-specific level was observed. Immunostaining indicated that SV2A expression and neuron numbers were similar across all three age groups. In general, these data obtained in healthy aging mice are consistent with previous findings in humans where synaptic density appeared stable during aging up to a certain age, after which a small decrease is observed.
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Affiliation(s)
- Mengfei Xiong
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, SE-751 85 Uppsala, Sweden
| | - Sahar Roshanbin
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, SE-751 85 Uppsala, Sweden
| | - Dag Sehlin
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, SE-751 85 Uppsala, Sweden
| | - Hanne D Hansen
- Neurobiology Research Unit, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark
| | - Johanna Rokka
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, SE-751 85 Uppsala, Sweden
| | - Jonas Eriksson
- PET Centre, Uppsala University Hospital, SE-751 85 Uppsala, Sweden; Department of Medicinal Chemistry, Uppsala University, SE-751 23 Uppsala, Sweden
| | - Stina Syvänen
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, SE-751 85 Uppsala, Sweden.
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Liu M, Sun X. Spatial integration of dendrites in fast-spiking basket cells. Front Neurosci 2023; 17:1132980. [PMID: 37081933 PMCID: PMC10110864 DOI: 10.3389/fnins.2023.1132980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 03/20/2023] [Indexed: 04/07/2023] Open
Abstract
Dendrites of fast-spiking basket cells (FS BCs) impact neural circuit functions in brain with both supralinear and sublinear integration strategies. Diverse spatial synaptic inputs and active properties of dendrites lead to distinct neuronal firing patterns. How the FS BCs with this bi-modal dendritic integration respond to different spatial dispersion of synaptic inputs remains unclear. In this study, we construct a multi-compartmental model of FS BC and analyze neuronal firings following simulated synaptic protocols from fully clustered to fully dispersed. Under these stimulation protocols, we find that supralinear dendrites dominate somatic firing of FS BC, while the preference for dispersing is due to sublinear dendrites. Moreover, we find that dendritic diameter and Ca2+-permeable AMPA conductance play an important role in it, while A-type K+ channel and NMDA conductance have little effect. The obtained results may give some implications for understanding dendritic computation.
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Xue CY, Gao T, Mao E, Kou ZZ, Dong L, Gao F. Hippocampus Insulin Receptors Regulate Episodic and Spatial Memory Through Excitatory/Inhibitory Balance. ASN Neuro 2023; 15:17590914231206657. [PMID: 37908089 PMCID: PMC10621302 DOI: 10.1177/17590914231206657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/25/2023] [Accepted: 09/23/2023] [Indexed: 11/02/2023] Open
Abstract
It is well known that the hippocampus is a vital brain region playing a key role in both episodic and spatial memory. Insulin receptors (InsRs) are densely distributed in the hippocampus and are important for its function. However, the effects of InsRs on the function of the specific hippocampal cell types remain elusive. In this study, hippocampal InsRs knockout mice had impaired episodic and spatial memory. GABAergic neurons and glutamatergic neurons in the hippocampus are involved in the balance between excitatory and inhibitory (E/I) states and participate in the processes of episodic and spatial memory. InsRs are located mainly at excitatory neurons in the hippocampus, whereas 8.5% of InsRs are glutamic acid decarboxylase 2 (GAD2)::Ai9-positive (GABAergic) neurons. Next, we constructed a transgenic mouse system in which InsR expression was deleted from GABAergic (glutamate decarboxylase 2::InsRfl/fl, GAD2Cre::InsRfl/fl) or glutamatergic neurons (vesicular glutamate transporter 2::InsRfl/fl,Vglut2Cre::InsRfl/fl). Our results showed that in comparison to the InsRfl/fl mice, both episodic and spatial memory were lower in GAD2Cre::InsRfl/fl and Vglut2Cre::InsRfl/fl. In addition, both GAD2Cre::InsRfl/fl and Vglut2Cre::InsRfl/fl were associated with more anxiety and lower glucose tolerance. These findings reveal that hippocampal InsRs might be crucial for episodic and spatial memory through E/I balance hippocampal regulation.
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Affiliation(s)
- Cai-Yan Xue
- Key Laboratory of Aerospace Medicine of the Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi’an, China
| | - Tian Gao
- Division of Health Management, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - E Mao
- Department of Anatomy, Histology and Embryology & K. K. Leung Brain Research Centre, Fourth Military Medical University, Xi’an, China
| | - Zhen-Zhen Kou
- Department of Anatomy, Histology and Embryology & K. K. Leung Brain Research Centre, Fourth Military Medical University, Xi’an, China
| | - Ling Dong
- Key Laboratory of Aerospace Medicine of the Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi’an, China
| | - Feng Gao
- Key Laboratory of Aerospace Medicine of the Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi’an, China
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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. Adv Neurobiol 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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Zhang Y, Pan X, Wang Y. Category learning in a recurrent neural network with reinforcement learning. Front Psychiatry 2022; 13:1008011. [PMID: 36387007 PMCID: PMC9640766 DOI: 10.3389/fpsyt.2022.1008011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 10/10/2022] [Indexed: 11/13/2022] Open
Abstract
It is known that humans and animals can learn and utilize category information quickly and efficiently to adapt to changing environments, and several brain areas are involved in learning and encoding category information. However, it is unclear that how the brain system learns and forms categorical representations from the view of neural circuits. In order to investigate this issue from the network level, we combine a recurrent neural network with reinforcement learning to construct a deep reinforcement learning model to demonstrate how the category is learned and represented in the network. The model consists of a policy network and a value network. The policy network is responsible for updating the policy to choose actions, while the value network is responsible for evaluating the action to predict rewards. The agent learns dynamically through the information interaction between the policy network and the value network. This model was trained to learn six stimulus-stimulus associative chains in a sequential paired-association task that was learned by the monkey. The simulated results demonstrated that our model was able to learn the stimulus-stimulus associative chains, and successfully reproduced the similar behavior of the monkey performing the same task. Two types of neurons were found in this model: one type primarily encoded identity information about individual stimuli; the other type mainly encoded category information of associated stimuli in one chain. The two types of activity-patterns were also observed in the primate prefrontal cortex after the monkey learned the same task. Furthermore, the ability of these two types of neurons to encode stimulus or category information was enhanced during this model was learning the task. Our results suggest that the neurons in the recurrent neural network have the ability to form categorical representations through deep reinforcement learning during learning stimulus-stimulus associations. It might provide a new approach for understanding neuronal mechanisms underlying how the prefrontal cortex learns and encodes category information.
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Affiliation(s)
- Ying Zhang
- Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, China
| | - Xiaochuan Pan
- Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, China
| | - Yihong Wang
- Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, China
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