1
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Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Arafat T, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. Prog Neurobiol 2024; 236:102604. [PMID: 38604584 DOI: 10.1016/j.pneurobio.2024.102604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 12/18/2023] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Thaera Arafat
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Department of Neurology, Duke University School of Medicine and Department of Biomedical Engineering, Duke University Pratt School of Engineering, Durham, NC 27705, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3 BG, United Kingdom
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Queretaro, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada.
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2
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Lenge M, Balestrini S, Napolitano A, Mei D, Conti V, Baldassarri G, Trivisano M, Pellacani S, Macconi L, Longo D, Rossi Espagnet MC, Cappelletti S, D'Incerti L, Barba C, Specchio N, Guerrini R. Morphometric network-based abnormalities correlate with psychiatric comorbidities and gene expression in PCDH19-related developmental and epileptic encephalopathy. Transl Psychiatry 2024; 14:35. [PMID: 38238304 PMCID: PMC10796344 DOI: 10.1038/s41398-024-02753-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/03/2024] [Accepted: 01/08/2024] [Indexed: 01/22/2024] Open
Abstract
Protocadherin-19 (PCDH19) developmental and epileptic encephalopathy causes an early-onset epilepsy syndrome with limbic seizures, typically occurring in clusters and variably associated with intellectual disability and a range of psychiatric disorders including hyperactive, obsessive-compulsive and autistic features. Previous quantitative neuroimaging studies revealed abnormal cortical areas in the limbic formation (parahippocampal and fusiform gyri) and underlying white-matter fibers. In this study, we adopted morphometric, network-based and multivariate statistical methods to examine the cortex and substructure of the hippocampus and amygdala in a cohort of 20 PCDH19-mutated patients and evaluated the relation between structural patterns and clinical variables at individual level. We also correlated morphometric alterations with known patterns of PCDH19 expression levels. We found patients to exhibit high-significant reductions of cortical surface area at a whole-brain level (left/right pvalue = 0.045/0.084), and particularly in the regions of the limbic network (left/right parahippocampal gyri pvalue = 0.230/0.016; left/right entorhinal gyri pvalue = 0.002/0.327), and bilateral atrophy of several subunits of the amygdala and hippocampus, particularly in the CA regions (head of the left CA3 pvalue = 0.002; body of the right CA3 pvalue = 0.004), and differences in the shape of hippocampal structures. More severe psychiatric comorbidities correlated with more significant altered patterns, with the entorhinal gyrus (pvalue = 0.013) and body of hippocampus (pvalue = 0.048) being more severely affected. Morphometric alterations correlated significantly with the known expression patterns of PCDH19 (rvalue = -0.26, pspin = 0.092). PCDH19 encephalopathy represents a model of genetically determined neural network based neuropsychiatric disease in which quantitative MRI-based findings correlate with the severity of clinical manifestations and had have a potential predictive value if analyzed early.
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Affiliation(s)
- Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Simona Balestrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children's Hospital, IRCCS, 00100, Rome, Italy
| | - Davide Mei
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Valerio Conti
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Giulia Baldassarri
- Medical Physics Department, Bambino Gesù Children's Hospital, IRCCS, 00100, Rome, Italy
| | - Marina Trivisano
- Neurology, Epilepsy and Movement Disorders, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, 00165, Rome, Italy
| | - Simona Pellacani
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Letizia Macconi
- Pediatric Radiology Unit, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Daniela Longo
- Functional and Interventional Neuroimaging Unit, Bambino Gesù Children's Hospital, IRCCS, 00165, Rome, Italy
| | | | - Simona Cappelletti
- Neurology, Epilepsy and Movement Disorders, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, 00165, Rome, Italy
| | - Ludovico D'Incerti
- Pediatric Radiology Unit, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Carmen Barba
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy
| | - Nicola Specchio
- Neurology, Epilepsy and Movement Disorders, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, 00165, Rome, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital IRCCS, 50139, Florence, Italy.
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3
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Woodfield J, Chin RFM, van Schooneveld MMJ, van den Heuvel M, Bastin ME, Braun KPJ. The association of structural connectome efficiency with cognition in children with epilepsy. Epilepsy Behav 2023; 148:109462. [PMID: 37844437 DOI: 10.1016/j.yebeh.2023.109462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/21/2023] [Accepted: 09/26/2023] [Indexed: 10/18/2023]
Abstract
OBJECTIVE Cognitive impairment is common in children with epilepsy (CWE), but understanding the underlying pathological processes is challenging. We aimed to investigate the association of structural brain network organisation with cognition. METHODS This was a retrospective cohort study of CWE without structural brain abnormalities, comparing whole brain network characteristics between those with cognitive impairment and those with intact cognition. We created structural whole-brain connectomes from anatomical and diffusion tensor magnetic resonance imaging using the number of streamlines and tract-averaged fractional anisotropy. We assessed the differences in average path length and global network efficiency between children with cognitive impairment and those without,using multivariable analyses to account for possible clinical group differences. RESULTS Twenty-eight CWE and cognitive impairment had lower whole brain network global efficiency compared with 34 children with intact cognition (0.54, standard deviation (SD):0.003 vs. 0.56, SD:0.002, p < 0.001), which is equivalent to longer normalized network average path lengths (1.14, SD:0.05 vs. 1.10, SD:0.02, p = 0.003). In multivariable logistic regression cognitive impairment was not significantly associated with age of onset, duration of epilepsy, or number of antiseizure medications, but was independently associated with daily seizures (p = 0.04) and normalized average path length (p = 0.007). CONCLUSIONS Higher structural network average path length and lower global network efficiency may be imaging biomarkers of cognitive impairment in epilepsy. Understanding what leads to changes in structural connectivity could aid identification of modifiable risk factors for cognitive impairment. These findings are only applicable to the specific cohort studied, and further confirmation in other cohorts is required.
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Affiliation(s)
- Julie Woodfield
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Department of Clinical Neurosciences, NHS Lothian, Edinburgh, United Kingdom; Muir Maxwell Epilepsy Centre, University of Edinburgh, Edinburgh, United Kingdom.
| | - Richard F M Chin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Muir Maxwell Epilepsy Centre, University of Edinburgh, Edinburgh, United Kingdom; Royal Hospital for Children and Young People, NHS Lothian, Edinburgh, United Kingdom
| | | | - Martijn van den Heuvel
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Kees P J Braun
- Department of Paediatric Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
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4
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Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.23.541934. [PMID: 37292996 PMCID: PMC10245853 DOI: 10.1101/2023.05.23.541934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Lorenzo Caciagli
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Douw L, Senden M, van den Heuvel M. Editorial: Focus feature on biomarkers in network neuroscience. Netw Neurosci 2022; 6:298-300. [PMID: 35733431 PMCID: PMC9205419 DOI: 10.1162/netn_e_00249] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
There is an ongoing need for novel biomarkers in clinical neuroscience, as diagnosis of neurological and psychiatric disorders is hampered by the pronounced overlap of behavioral symptoms and other pathophysiological characteristics. The question that this Focus Feature puts center stage is whether network-based biomarkers may provide a viable tool for distinguishing between disordered populations or whether they may yield only limited differentiating power because of largely shared network characteristics across conditions.
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Affiliation(s)
- Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Martijn van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
- Department of Child Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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