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Wang Y, Han Z, Wang C, Liu J, Guo J, Miao P, Wei Y, Wu L, Wang X, Wang P, Zhang Y, Cheng J, Fan S. Withdrawn: The altered dynamic community structure for adaptive adjustment in stroke patients with multidomain cognitive impairments: A multilayer network analysis. Comput Biol Med 2024:108712. [PMID: 38906761 DOI: 10.1016/j.compbiomed.2024.108712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 05/10/2024] [Accepted: 06/03/2024] [Indexed: 06/23/2024]
Abstract
This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconveniencethis may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/policies/article-withdrawal.
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Affiliation(s)
- Yingying Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zongli Han
- Department of Neurosurgery, Peking University Shenzhen Hospital, Futian District Shenzhen Guangdong, P.R. China
| | - Caihong Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jun Guo
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Peifang Miao
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ying Wei
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Luobing Wu
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Peipei Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Siyuan Fan
- Cardiovascular Center, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Qin K, Lei D, Zhu Z, Li W, Tallman MJ, Rodrigo Patino L, Fleck DE, Aghera V, Gong Q, Sweeney JA, McNamara RK, DelBello MP. Different brain functional network abnormalities between attention-deficit/hyperactivity disorder youth with and without familial risk for bipolar disorder. Eur Child Adolesc Psychiatry 2024; 33:1395-1405. [PMID: 37336861 DOI: 10.1007/s00787-023-02245-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 06/07/2023] [Indexed: 06/21/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) commonly precedes the initial onset of mania in youth with familial risk for bipolar disorder (BD). Although ADHD youth with and without BD familial risk exhibit different clinical features, associated neuropathophysiological mechanisms remain poorly understood. This study aimed to identify brain functional network abnormalities associated with ADHD in youth with and without familial risk for BD. Resting-state functional magnetic resonance imaging scans were acquired from 37 ADHD youth with a family history of BD (high-risk), 45 ADHD youth without a family history of BD (low-risk), and 32 healthy controls (HC). Individual whole-brain functional networks were constructed, and graph theory analysis was applied to estimate network topological metrics. Topological metrics, including network efficiency, small-worldness and nodal centrality, were compared across groups, and associations between topological metrics and clinical ratings were evaluated. Compared to HC, low-risk ADHD youth exhibited weaker global integration (i.e., decreased global efficiency and increased characteristic path length), while high-risk ADHD youth showed a disruption of localized network components with decreased frontoparietal and frontolimbic connectivity. Common topological deficits were observed in the medial superior frontal gyrus between low- and high-risk ADHD. Distinct network deficits were found in the inferior parietal lobule and corticostriatal circuitry. Associations between global topological metrics and externalizing symptoms differed significantly between the two ADHD groups. Different patterns of functional network topological abnormalities were found in high- as compared to low-risk ADHD, suggesting that ADHD in youth with BD familial risk may represent a phenotype that is different from ADHD alone.
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, China
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, China.
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Wenbin Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Veronica Aghera
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China.
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
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Neal J, Song I, Katz B, Lee TH. Association of Intrinsic Functional Connectivity between the Locus Coeruleus and Salience Network with Attentional Ability. J Cogn Neurosci 2023; 35:1557-1569. [PMID: 37584586 DOI: 10.1162/jocn_a_02036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
The locus coeruleus (LC) is a brainstem region associated with broad neural arousal because of norepinephrine production, but it has increasingly been associated with specific cognitive processes. These include sustained attention, with deficits associated with various neuropsychological disorders. Neural models of attention deficits have focused on interrupted dynamics between the salience network (SAL) with the frontoparietal network, which has been associated with task-switching and processing of external stimuli, respectively. Conflicting findings for these regions suggest the possibility of upstream signaling leading to attention dysfunction, and recent research suggests LC involvement. In this study, resting-state functional connectivity and behavioral performance on an attention task was examined within 584 individuals. Analysis revealed significant clusters connected to LC activity in the SAL. Given previous findings that attention deficits may be caused by SAL network switching dysfunctions, findings here further suggest that dysfunction in LC-SAL connectivity may impair attention.
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Previously Marzena Szkodo MOR, Micai M, Caruso A, Fulceri F, Fazio M, Scattoni ML. Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review. Neurosci Biobehav Rev 2023; 145:105021. [PMID: 36581169 DOI: 10.1016/j.neubiorev.2022.105021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 12/27/2022]
Abstract
In recent years, there has been a great interest in utilizing technology in mental health research. The rapid technological development has encouraged researchers to apply technology as a part of a diagnostic process or treatment of Neurodevelopmental Disorders (NDDs). With the large number of studies being published comes an urgent need to inform clinicians and researchers about the latest advances in this field. Here, we methodically explore and summarize findings from studies published between August 2019 and February 2022. A search strategy led to the identification of 4108 records from PubMed and APA PsycInfo databases. 221 quantitative studies were included, covering a wide range of technologies used for diagnosis and/or treatment of NDDs, with the biggest focus on Autism Spectrum Disorder (ASD). The most popular technologies included machine learning, functional magnetic resonance imaging, electroencephalogram, magnetic resonance imaging, and neurofeedback. The results of the review indicate that technology-based diagnosis and intervention for NDD population is promising. However, given a high risk of bias of many studies, more high-quality research is needed.
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Affiliation(s)
| | - Martina Micai
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Angela Caruso
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Francesca Fulceri
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
| | - Maria Fazio
- Department of Mathematics, Computer Science, Physics and Earth Sciences (MIFT), University of Messina, Viale F. Stagno d'Alcontres, 31, 98166 Messina, Italy.
| | - Maria Luisa Scattoni
- Research Coordination and Support Service, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy.
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Karavallil Achuthan S, Coburn KL, Beckerson ME, Kana RK. Amplitude of low frequency fluctuations during resting state fMRI in autistic children. Autism Res 2023; 16:84-98. [PMID: 36349875 DOI: 10.1002/aur.2846] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022]
Abstract
Resting state fMRI (rs-fMRI) provides an excellent platform for examining the amplitude of low frequency fluctuations (ALFF) and fractional amplitude of low frequency fluctuations (fALFF), which are key indices of brain functioning. However, ALFF and fALFF have been used only sporadically to study autism. rs-fMRI data from 69 children (40 autistic, mean age = 8.47 ± 2.20 years; age range: 5.2 to 13.2; and 29 non-autistic, mean age = 9.02 ± 1.97 years; age range 5.9 to 12.9) were obtained from the Autism Brain Imaging Data Exchange (ABIDE II). ALFF and fALFF were measured using CONN connectivity toolbox and SPM12, at whole-brain & network-levels. A two-sampled t-test and a 2 Group (autistic, non-autistic) × 7 Networks ANOVA were conducted to test group differences in ALFF and fALFF. The whole-brain analysis identified significantly reduced ALFF values for autistic participants in left parietal opercular cortex, precuneus, and right insula. At the network level, there was a significant effect of diagnostic group and brain network on ALFF values, and only significant effect of network, not group, on fALFF values. Regression analyses indicated a significant effect of age on ALFF values of certain networks in autistic participants. Such intrinsically different network-level responses in autistic participants may have implications for task-level recruitment and synchronization of brain areas, which may in turn impact optimal cognitive functioning. Moreover, differences in low frequency fluctuations of key networks, such as the DMN and SN, may underlie alterations in brain responses in autism that are frequently reported in the literature.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Kelly L Coburn
- Department of Speech-Language Pathology & Audiology, Towson University, Towson, Maryland, USA
| | - Meagan E Beckerson
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Rajesh K Kana
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
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Liloia D, Crocetta A, Cauda F, Duca S, Costa T, Manuello J. Seeking Overlapping Neuroanatomical Alterations between Dyslexia and Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Replication Study. Brain Sci 2022; 12:brainsci12101367. [PMID: 36291301 PMCID: PMC9599506 DOI: 10.3390/brainsci12101367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/23/2022] [Accepted: 09/29/2022] [Indexed: 01/18/2023] Open
Abstract
The present work is a replication article based on the paper “Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies” by McGrath and Stoodley (2019). In the original research, the authors used activation likelihood estimation (ALE), a technique to perform coordinate-based meta-analysis (CBMA), to investigate the existence of brain regions undergoing gray matter alteration in association with both attention-deficit/hyper-activity disorder (ADHD) and dyslexia. Here, the same voxel-based morphometry dataset was analyzed, while using the permutation-subject images version of signed differential mapping (PSI-SDM) in place of ALE. Overall, the replication converged with the original paper in showing a limited overlap between the two conditions. In particular, no significant effect was found for dyslexia, therefore precluding any form of comparison between the two disorders. The possible influences of biological sex, age, and medication status were also ruled out. Our findings are in line with literature about gray matter alteration associated with ADHD and dyslexia, often showing conflicting results. Therefore, although neuropsychological and clinical evidence suggest some convergence between ADHD and dyslexia, more future research is sorely needed to reach a consensus on the neuroimaging domain in terms of patterns of gray matter alteration.
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Affiliation(s)
- Donato Liloia
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Annachiara Crocetta
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Franco Cauda
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
- Neuroscience Institute of Turin, 10043 Turin, Italy
- Correspondence: ; Tel.: +39-011-670-29-80; Fax: +39-011-814-62-31
| | - Sergio Duca
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Tommaso Costa
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Jordi Manuello
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
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He W, Liu W, Mao M, Cui X, Yan T, Xiang J, Wang B, Li D. Reduced Modular Segregation of White Matter Brain Networks in Attention Deficit Hyperactivity Disorder. J Atten Disord 2022; 26:1591-1604. [PMID: 35373644 DOI: 10.1177/10870547221085505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Despite studies reporting alterations in the brain networks of patients with ADHD, alterations in the modularity of white matter (WM) networks are still unclear. METHOD Based on the results of module division by generalized Louvain algorithm, the modularity of ADHD was evaluated. The correlation between the modular changes of ADHD and its clinical characteristics was analyzed. RESULTS The participation coefficient and the connectivity between modules of ADHD increased, and the modularity coefficient decreased. Provincial hubs of ADHD did not change, and the number of connector hubs increased. All results showed that the modular segregation of WM networks of ADHD decreased. Modules with reduced modular segregation are mainly responsible for language and motor functions. Moreover, modularity showed evident correlation with the symptoms of ADHD. CONCLUSION The modularity changes in WM network provided a novel insight into the understanding of brain cognitive alterations in ADHD.
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Affiliation(s)
- Wenbo He
- Taiyuan University of Technology, Shanxi, China
| | - Weichen Liu
- Taiyuan University of Technology, Shanxi, China
| | - Min Mao
- Taiyuan University of Technology, Shanxi, China
| | | | - Ting Yan
- Shanxi Medical University, Taiyuan, China
| | - Jie Xiang
- Taiyuan University of Technology, Shanxi, China
| | - Bin Wang
- Taiyuan University of Technology, Shanxi, China
| | - Dandan Li
- Taiyuan University of Technology, Shanxi, China
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Tarchi L, Damiani S, Fantoni T, Pisano T, Castellini G, Politi P, Ricca V. Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study. Brain Imaging Behav 2022; 16:2526-2542. [PMID: 35859076 DOI: 10.1007/s11682-022-00708-8] [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] [Accepted: 07/10/2022] [Indexed: 11/26/2022]
Abstract
Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy.
| | - Stefano Damiani
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Teresa Fantoni
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Tiziana Pisano
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
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Frontal corticostriatal functional connectivity reveals task positive and negative network dysregulation in relation to ADHD, sex, and inhibitory control. Dev Cogn Neurosci 2022; 54:101101. [PMID: 35338900 PMCID: PMC8956922 DOI: 10.1016/j.dcn.2022.101101] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/18/2022] [Accepted: 03/18/2022] [Indexed: 01/21/2023] Open
Abstract
Frontal corticostriatal circuits (FCSC) are involved in self-regulation of cognition, emotion, and motor function. While these circuits are implicated in attention-deficit/hyperactivity disorder (ADHD), the literature establishing FCSC associations with ADHD is inconsistent. This may be due to study variability in considerations of how fMRI motion regression was handled between groups, or study specific differences in age, sex, or the striatal subregions under investigation. Given the importance of these domains in ADHD it is crucial to consider the complex interactions of age, sex, striatal subregions and FCSC in ADHD presentation and diagnosis. In this large-scale study of 362 8-12 year-old children with ADHD (n = 165) and typically developing (TD; n = 197) children, we investigate associations between FCSC with ADHD diagnosis and symptoms, sex, and go/no-go (GNG) task performance. Results include: (1) increased striatal connectivity with age across striatal subregions with most of the frontal cortex, (2) increased frontal-limbic striatum connectivity among boys with ADHD only, mostly in default mode network (DMN) regions not associated with age, and (3) increased frontal-motor striatum connectivity to regions of the DMN were associated with greater parent-rated inattention problems, particularly among the ADHD group. Although diagnostic group differences were no longer significant when strictly controlling for head motion, with motion possibly reflecting the phenotypic variance of ADHD itself, the spatial distribution of all symptom, age, sex, and other ADHD group effects were nearly identical to the initial results. These results demonstrate differential associations of FCSC between striatal subregions with the DMN and FPN in relation to age, ADHD, sex, and inhibitory control.
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Mozaffari M, Hassani-Abharian P, Kholghi G, Vaseghi S, Zarrindast MR, Nasehi M. Treatment with RehaCom computerized rehabilitation program improves response control, but not attention in children with attention-deficit/hyperactivity disorder (ADHD). J Clin Neurosci 2022; 98:149-153. [PMID: 35180505 DOI: 10.1016/j.jocn.2022.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 10/15/2020] [Accepted: 02/05/2022] [Indexed: 11/24/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder in children. ADHD impairs attention, response control, emotion regulation, and other cognitive functions. On the other hand, RehaCom is a cognitive rehabilitation software that has therapeutic effects on cognitive dysfunctions in many diseases such as stroke, multiple sclerosis, and schizophrenia. The goal of the present study was to investigate the effect of treatment with RehaCom on auditory and visual response control, and auditory and visual attention in children with ADHD. Forty patients were selected. The participants were assigned to control (n = 20) and experimental (n = 20) groups, while only the participants in the experimental group were trained by RehaCom for five weeks (ten 45-min sessions, two sessions per week). At weeks 0 and 5, performance of the participants of experimental group was compared with the participants of control group. The results showed that treatment with RehaCom significantly improved auditory and visual response control in children with ADHD, with no effect on auditory and visual attention. In conclusion, RehaCom may alter brain's structural and functional properties that are related to response control. We suggest that attention deficit in ADHD may be a result of more complicated dysfunctions in the brain, that are not affected by RehaCom.
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Affiliation(s)
- Mitra Mozaffari
- Department of Psychology, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | | | - Gita Kholghi
- Department of Psychology, Faculty of Human Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran
| | - Salar Vaseghi
- Medicinal Plants Research Center, Institute of Medicinal Plants, ACECR, Karaj, Iran
| | - Mohammad-Reza Zarrindast
- Department of Cognitive Neuroscience, Institute for Cognitive Science Studies (ICSS), Tehran, Iran; Department of Pharmacology School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroendocrinology, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Nasehi
- Cognitive and Neuroscience Research Center (CNRC), Amir-Almomenin Hospital, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
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11
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Liu S, Zhao L, Zhao J, Li B, Wang SH. Attention deficit/hyperactivity disorder Classification based on deep spatio-temporal features of functional Magnetic Resonance Imaging. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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12
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Tarchi L, Damiani S, La Torraca Vittori P, Marini S, Nazzicari N, Castellini G, Pisano T, Politi P, Ricca V. The colors of our brain: an integrated approach for dimensionality reduction and explainability in fMRI through color coding (i-ECO). Brain Imaging Behav 2021; 16:977-990. [PMID: 34689318 PMCID: PMC9107439 DOI: 10.1007/s11682-021-00584-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2021] [Indexed: 11/29/2022]
Abstract
Several systematic reviews have highlighted the role of multiple sources in the investigation of psychiatric illness. For what concerns fMRI, the focus of recent literature preferentially lies on three lines of research, namely: functional connectivity, network analysis and spectral analysis. Data was gathered from the UCLA Consortium for Neuropsychiatric Phenomics. The sample was composed by 130 neurotypicals, 50 participants diagnosed with Schizophrenia, 49 with Bipolar disorder and 43 with ADHD. Single fMRI scans were reduced in their dimensionality by a novel method (i-ECO) averaging results per Region of Interest and through an additive color method (RGB): local connectivity values (Regional Homogeneity), network centrality measures (Eigenvector Centrality), spectral dimensions (fractional Amplitude of Low-Frequency Fluctuations). Average images per diagnostic group were plotted and described. The discriminative power of this novel method for visualizing and analyzing fMRI results in an integrative manner was explored through the usage of convolutional neural networks. The new methodology of i-ECO showed between-groups differences that could be easily appreciated by the human eye. The precision-recall Area Under the Curve (PR-AUC) of our models was > 84.5% for each diagnostic group as evaluated on the test-set – 80/20 split. In conclusion, this study provides evidence for an integrative and easy-to-understand approach in the analysis and visualization of fMRI results. A high discriminative power for psychiatric conditions was reached. This proof-of-work study may serve to investigate further developments over more extensive datasets covering a wider range of psychiatric diagnoses.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy.
| | - Stefano Damiani
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
| | | | - Simone Marini
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Nelson Nazzicari
- Council for Agricultural Research and Economics (CREA), Research Centre for Fodder Crops and Dairy Productions, Lodi, LO, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy
| | - Tiziana Pisano
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, PV, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, viale della Maternità, Padiglione 8b, AOU Careggi, Firenze, Florence, FI, 50134, Italy
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Kaiser A, Bottelier MA, de Ruiter MB, Solleveld MM, Tamminga HGH, Bouziane C, Geurts HM, Lindauer RJL, Kooij JJS, Lucassen PJ, Schrantee A, Reneman L. Effects of prolonged methylphenidate treatment on amygdala reactivity and connectivity: a randomized controlled trial in stimulant treatment-naive, male participants with ADHD. PSYCHORADIOLOGY 2021; 1:152-163. [PMID: 38665807 PMCID: PMC10917223 DOI: 10.1093/psyrad/kkab013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/07/2021] [Accepted: 09/24/2021] [Indexed: 04/28/2024]
Abstract
Background Problems with emotional processing are widely reported in individuals with attention-deficit/hyperactivity disorder (ADHD). Although methylphenidate (MPH) effectively alleviates inattention and hyperactivity symptoms in ADHD, its effects on emotional processing and internalizing symptoms have remained elusive. While we previously found that acute MPH administration modulated neural mechanisms underlying emotional processing in an age-dependent manner, the effects of prolonged administration remained unknown. Objectives Therefore, we investigated: (i) whether prolonged MPH treatment influences neural substrates (amygdala reactivity and connectivity) of emotional processing, and (ii) whether these effects are modulated by age. Methods The "effects of Psychotropic drugs On Developing brain-MPH" ("ePOD-MPH") randomized controlled trial was a 16-week double-blind, placebo-controlled, multi-center trial with MPH in 50 boys (10-12 years of age) and 49 men (23-40 years of age), all stimulant treatment-naive and diagnosed with ADHD. Participants performed an emotional face-matching task during functional magnetic resonance imaging. We assessed their symptoms of ADHD and internalizing symptoms at baseline, during the trial (8 weeks), and 1 week after the trial end (17 weeks). Results and Conclusions We did not find effects of prolonged MPH treatment on emotional processing, as measured by amygdala reactivity and connectivity and internalizing symptoms in this trial with stimulant treatment-naive participants. This differs from our findings on emotional processing following acute MPH administration and the effects of prolonged MPH treatment on the dopamine system, which were both modulated by age. Interestingly, prolonged MPH treatment did improve ADHD symptoms, although depressive and anxiety symptoms showed a medication-independent decrease. Furthermore, our data indicate that baseline internalizing symptoms may be used to predict MPH treatment effects on ADHD symptoms, particularly in (male) adults with ADHD.
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Affiliation(s)
- Antonia Kaiser
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
| | - Marco A Bottelier
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
- University Medical Center Groningen, Child Study Center, Accare, Groningen, 9713GZ, the Netherlands
| | - Michiel B de Ruiter
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
- Netherlands Cancer Institute, Division of Psychosocial Research and Epidemiology, Amsterdam, 1066CX, the Netherlands
| | - Michelle M Solleveld
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
| | - Hyke G H Tamminga
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
- University of Amsterdam, Dutch Autism & ADHD Research Center, Department of Psychology, Amsterdam, 1018WT, the Netherlands
| | - Cheima Bouziane
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
| | - Hilde M Geurts
- University of Amsterdam, Dutch Autism & ADHD Research Center, Department of Psychology, Amsterdam, 1018WT, the Netherlands
| | - Ramon J L Lindauer
- Amsterdam UMC, University of Amsterdam, Department of Child and Adolescent Psychiatry, Amsterdam, 1105AZ, the Netherlands
- Academic Centre for Child and Adolescent Psychiatry, Levvel, Amsterdam, 1076EC, the Netherlands
| | - J J Sandra Kooij
- Expertise Center Adult ADHD, PsyQ, The Hague, 2512VA, the Netherlands
- Amsterdam UMC, Vrije Universiteit, Amsterdam Public Health Research Institute, Department of Psychiatry, Amsterdam, 1105AZ, the Netherlands
| | - Paul J Lucassen
- University of Amsterdam, Brain Plasticity Group, Swammerdam Institute for Life Sciences, Amsterdam, 1012WX, The Netherlands
| | - Anouk Schrantee
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
| | - Liesbeth Reneman
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam, 1105 AZ, the Netherlands
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14
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A Novel Knowledge Distillation-Based Feature Selection for the Classification of ADHD. Biomolecules 2021; 11:biom11081093. [PMID: 34439759 PMCID: PMC8393979 DOI: 10.3390/biom11081093] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/21/2021] [Accepted: 07/21/2021] [Indexed: 01/17/2023] Open
Abstract
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience, difficulty in organizing tasks, increased forgetfulness, and interrupting conversation, and it is affecting millions of people worldwide. There is, until now, not a gold standard test using which an ADHD expert can differentiate between an individual with ADHD and a healthy subject, making accurate diagnosis of ADHD a challenging task. We are proposing a Knowledge Distillation-based approach to search for discriminating features between the ADHD and healthy subjects. Learned embeddings from a large neural network, trained on the functional connectivity features, were fed to one hidden layer Autoencoder for reproduction of the embeddings using the same connectivity features. Finally, a forward feature selection algorithm was used to select a combination of most discriminating features between the ADHD and the Healthy Controls. We achieved promising classification results for each of the five individual sites. A combined accuracy of 81% in KKI, 60% Peking, 56% in NYU, 64% NI, and 56% OHSU and individual site wise accuracy of 72% in KKI, 60% Peking, 73% in NYU, 70% NI, and 71% OHSU were obtained using our extracted features. Our results also outperformed state-of-the-art methods in literature which validates the efficacy of our proposed approach.
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Differential Modulation of Effective Connectivity in the Brain's Extended Face Processing System by Fearful and Sad Facial Expressions. eNeuro 2021; 8:ENEURO.0380-20.2021. [PMID: 33658311 PMCID: PMC8174049 DOI: 10.1523/eneuro.0380-20.2021] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 02/18/2021] [Accepted: 02/22/2021] [Indexed: 11/21/2022] Open
Abstract
The processing of emotional facial expressions is underpinned by the integration of information from a distributed network of brain regions. Despite investigations into how different emotional expressions alter the functional relationships within this network, there remains limited research examining which regions drive these interactions. This study investigated effective connectivity during the processing of sad and fearful facial expressions to better understand how these stimuli differentially modulate emotional face processing circuitry. Ninety-eight healthy human adolescents and young adults, aged between 15 and 25 years, underwent an implicit emotional face processing fMRI task. Using dynamic causal modeling (DCM), we examined five brain regions implicated in face processing. These were restricted to the right hemisphere and included the occipital and fusiform face areas, amygdala, and dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC). Processing sad and fearful facial expressions were associated with greater positive connectivity from the amygdala to dlPFC. Only the processing of fearful facial expressions was associated with greater negative connectivity from the vmPFC to amygdala. Compared with processing sad faces, processing fearful faces was associated with significantly greater connectivity from the amygdala to dlPFC. No difference was found between the processing of these expressions and the connectivity from the vmPFC to amygdala. Overall, our findings indicate that connectivity from the amygdala and dlPFC appears to be responding to dimensional features which differ between these expressions, likely those relating to arousal. Further research is necessary to examine whether this relationship is also observable for positively valenced emotions.
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Moreno C. Diagnostic overlap and exploration of risk factors in child psychiatry. Eur Child Adolesc Psychiatry 2021; 30:493-495. [PMID: 33796939 DOI: 10.1007/s00787-021-01766-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Carmen Moreno
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine Complutense University of Madrid, Madrid, Spain.
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17
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Wang LJ, Lin LC, Lee SY, Wu CC, Chou WJ, Hsu CF, Tseng HH, Lin WC. l-Cystine is associated with the dysconnectivity of the default-mode network and salience network in attention-deficit/hyperactivity disorder. Psychoneuroendocrinology 2021; 125:105105. [PMID: 33338922 DOI: 10.1016/j.psyneuen.2020.105105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 11/04/2020] [Accepted: 12/06/2020] [Indexed: 11/16/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Distributed dysconnectivity within both the default-mode network (DMN) and the salience network (SN) has been observed in ADHD. L-cystine may serve as a neuroprotective molecule and signaling pathway, as well as a biomarker of ADHD. The purpose of this study was to explore whether differential brain network connectivity is associated with peripheral L-cystine levels in ADHD patients. We recruited a total of 31 drug-naïve patients with ADHD (mean age: 10.4 years) and 29 healthy controls (mean age: 10.3 years) that underwent resting state functional magnetic resonance imaging scans. Functional connectomes were generated for each subject, and we examined the cross-sectional group difference in functional connectivity (FC) within and between DMN and SN. L-cystine plasma levels were determined using high-performance chemical isotope labeling (CIL)-based liquid chromatography-mass spectrometry (LC-MS). Compared to the control group, the ADHD group showed decreased FC of dorsal DMN (p = 0.031), as well as decreased FC of precuneus-post SN (p = 0.006) and ventral DMN-post SN (p = 0.001). The plasma L-cystine levels of the ADHD group were significantly higher than in the control group (p = 0.002). Furthermore, L-cystine levels were negatively correlated with FC of precuneus-post SN (r = -0.404, p = 0.045) and ventral DMN-post SN (r = -0.540, p = 0.007). The findings suggest that decreased synergies of DMN and SN may serve as neurobiomarkers for ADHD, while L-cystine may be involved in the pathophysiology of network dysconnectivity. Future studies on the molecular mechanism of the cystine-glutamate system in brain network connectivity are warranted.
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Affiliation(s)
- Liang-Jen Wang
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Liang-Chun Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Taiwan; Chang Gung University College of Medicine, Taiwan
| | - Sheng-Yu Lee
- Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Department of Psychiatry, College of Medicine, Graduate Institute of Medicine, School of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chih-Ching Wu
- Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan; Department of Otolaryngology-Head & Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan; Research Center for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wen-Jiun Chou
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chia-Fen Hsu
- Division of Clinical Psychology, Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan; Department of Child Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Huai-Hsuan Tseng
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Wei-Che Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Taiwan; Chang Gung University College of Medicine, Taiwan.
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