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Ye B, Wu Y, Cao M, Xu C, Zhou C, Zhang X. Altered patterns of dynamic functional connectivity of brain networks in deficit and non-deficit schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01803-1. [PMID: 38662092 DOI: 10.1007/s00406-024-01803-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 03/19/2024] [Indexed: 04/26/2024]
Abstract
This study aims to investigate the altered patterns of dynamic functional network connectivity (dFNC) between deficit schizophrenia (DS) and non-deficit schizophrenia (NDS), and further explore the associations with cognitive impairments. 70 DS, 91 NDS, and 120 matched healthy controls (HCs) were enrolled. The independent component analysis was used to segment the whole brain. The fMRI brain atlas was used to identify functional networks, and the dynamic functional connectivity (FC) of each network was detected. Correlation analysis was used to explore the associations between altered dFNC and cognitive functions. Four dynamic states were identified. Compared to NDS, DS showed increased FC between sensorimotor network and default mode network in state 1 and decreased FC within auditory network in state 4. Additionally, DS had a longer mean dwell time of state 2 and a shorter one in state 3 compared to NDS. Correlation analysis showed that fraction time and mean dwell time of states were correlated with cognitive impairments in DS. This study demonstrates the distinctive altered patterns of dFNC between DS and NDS patients. The associations with impaired cognition provide specific neuroimaging evidence for the pathogenesis of DS.
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Affiliation(s)
- Biying Ye
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Yiqiao Wu
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Mingjun Cao
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Chanhuan Xu
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No.264 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No.264 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
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Chong JSX, Chua KY, Ng KK, Chong SW, Leong RLF, Chee MWL, Koh WP, Zhou JH. Higher handgrip strength is linked to higher salience ventral attention functional network segregation in older adults. Commun Biol 2024; 7:214. [PMID: 38383572 PMCID: PMC10881588 DOI: 10.1038/s42003-024-05862-x] [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] [Received: 07/03/2023] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
Converging evidence suggests that handgrip strength is linked to cognition in older adults, and this may be subserved by shared age-related changes in brain function and structure. However, the interplay among handgrip strength, brain functional connectivity, and cognitive function remains poorly elucidated. Hence, our study sought to examine these relationships in 148 community-dwelling older adults. Specifically, we examined functional segregation, a measure of functional brain organization sensitive to ageing and cognitive decline, and its associations with handgrip strength and cognitive function. We showed that higher handgrip strength was related to better processing speed, attention, and global cognition. Further, higher handgrip strength was associated with higher segregation of the salience/ventral attention network, driven particularly by higher salience/ventral attention intra-network functional connectivity of the right anterior insula to the left posterior insula/frontal operculum and right midcingulate/medial parietal cortex. Importantly, these handgrip strength-related inter-individual differences in salience/ventral attention network functional connectivity were linked to cognitive function, as revealed by functional decoding and brain-cognition association analyses. Our findings thus highlight the importance of the salience/ventral attention network in handgrip strength and cognition, and suggest that inter-individual differences in salience/ventral attention network segregation and intra-network connectivity could underpin the handgrip strength-cognition relationship in older adults.
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Affiliation(s)
- Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kevin Yiqiang Chua
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shin Wee Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Woon Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore, Singapore.
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
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Pugliese V, de Filippis R, Aloi M, Carbone EA, Rania M, Segura-Garcia C, De Fazio P. Cognitive biases are associated with aberrant salience experience in schizophrenia spectrum disorders. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2023:S2950-2853(23)00005-4. [PMID: 38570903 DOI: 10.1016/j.sjpmh.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/02/2023] [Accepted: 07/12/2023] [Indexed: 04/05/2024]
Abstract
INTRODUCTION Cognitive models suggest the co-occurrence of cognitive biases and aberrant salience is unique to psychosis, but their interaction is not yet fully understood. Therefore, we aimed to elucidate the relationship between subjective cognitive biases and aberrant salience in individuals with schizophrenia spectrum disorders (SSDs) in this study. METHODS A sample of 92 subjects with SSDs underwent an assessment using Davos Assessment Cognitive Biases (DACOBS) and the Aberrant Salience Inventory (ASI) in a cross-sectional design. We evaluated psychopathological differences based on ASI scores and conducted a linear regression analysis to examine the variables associated with aberrant salience. RESULTS Subjects with an ASI score ≥14 demonstrated significantly higher scores across all subscales and total score of ASI and DACOBS (p<0.001). ASI subscales were significantly positive correlated with all DACOBS subscales, ranging from 0.250 for Increased Significance and Safety Behavior to 0.679 for Heightened Emotionality and Social cognition problems. The linear regression analysis revealed a positive association between aberrant salience and the DACOBS subscales jumping to conclusions (JTC) (β=0.220), social cognition problems (β=0.442), subjective cognitive problems (β=0.405), and a negative association with the subscale belief inflexibility (β=-0.350). CONCLUSIONS Our findings suggest that JTC, social cognition problems and subjective cognitive problems may play a central role in the experience of aberrant salience in individuals with SSDs. This work informs about the need of developing prevention and intervention strategies that specifically target cognitive biases and aberrant salience in the treatment of psychosis.
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Affiliation(s)
- Valentina Pugliese
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy
| | - Renato de Filippis
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy
| | - Matteo Aloi
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy; Department of Clinical and Experimental Medicine, University of Messina, 98125 Messina, Italy
| | - Elvira Anna Carbone
- Psychiatry Unit, Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy
| | - Marianna Rania
- Center for Clinical Research and Treatment of Eating Disorders, University Hospital Mater Domini, Catanzaro, Italy
| | - Cristina Segura-Garcia
- Psychiatry Unit, Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy; Center for Clinical Research and Treatment of Eating Disorders, University Hospital Mater Domini, Catanzaro, Italy
| | - Pasquale De Fazio
- Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro 88100, Italy.
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Li Z, Wang Z, Cao D, You R, Hu J. Altered dynamic functional network connectivity states in patients with acute basal ganglia ischemic stroke. Brain Res 2023:148406. [PMID: 37201623 DOI: 10.1016/j.brainres.2023.148406] [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: 12/26/2022] [Revised: 05/04/2023] [Accepted: 05/08/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Dynamic functional network connectivity (dFNC) patterns are successfully able to capture the time-varying features of intrinsic fluctuations throughout a scan. We explored dFNC alterations across the entire brain in patients with acute ischemic stroke (AIS) of the basal ganglia (BG). METHOD Resting-state functional magnetic resonance imaging data were acquired from 26 patients with first-ever AIS in the BG and 26 healthy controls (HCs). Independent component analysis, the sliding window method, and the K-means clustering method were used to obtain reoccurring dynamic network connectivity patterns. Moreover, temporal features across diverse dFNC states were compared between the two groups, and the local and global efficiencies across states were analyzed to explore the characteristics of the topological networks among states. RESULTS Four dFNC states were characterized for comparison of dynamic brain network connectivity patterns. In contrast to the HC group, the AIS group spent a significantly higher fraction of time in State 1, which is characterized by a relatively weaker brain network connectome. Conversely, compared with HC, patients with AIS showed a lower mean dwell time in State 2, which was characterized by a relatively stronger brain network connectome. Additionally, functional networks exhibited variable efficiency of information transfer across 4 states. CONCLUSIONS AIS not only altered the interaction between the different dynamic networks but also promoted characteristic alterations in the temporal and topological features of large-scale dynamic network connectivity.
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Affiliation(s)
- Zhongming Li
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
| | - Zhimin Wang
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Dairong Cao
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Ruixiong You
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jianping Hu
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
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Rong B, Huang H, Gao G, Sun L, Zhou Y, Xiao L, Wang H, Wang G. Widespread Intra- and Inter-Network Dysconnectivity among Large-Scale Resting State Networks in Schizophrenia. J Clin Med 2023; 12:jcm12093176. [PMID: 37176617 PMCID: PMC10179370 DOI: 10.3390/jcm12093176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/08/2023] [Accepted: 04/07/2023] [Indexed: 05/15/2023] Open
Abstract
Schizophrenia is characterized by the distributed dysconnectivity of resting-state multiple brain networks. However, the abnormalities of intra- and inter-network functional connectivity (FC) in schizophrenia and its relationship to symptoms remain unknown. The aim of the present study is to compare the intra- and inter-connectivity of the intrinsic networks between a large sample of patients with schizophrenia and healthy controls. Using the Region of interest (ROI) to ROI FC analyses, the intra- and inter-network FC of the eight resting state networks [default mode network (DMN); salience network (SN); frontoparietal network (FPN); dorsal attention network (DAN); language network (LN); visual network (VN); sensorimotor network (SMN); and cerebellar network (CN)] were investigated in 196 schizophrenia and 169-healthy controls. Compared to the healthy control group, the schizophrenia group exhibited increased intra-network FC in the DMN and decreased intra-network FC in the CN. Additionally, the schizophrenia group showed the decreased inter-network FC mainly involved the SN-DMN, SN-LN and SN-CN while increased inter-network FC in the SN-SMN and SN-DAN (p < 0.05, FDR-corrected). Our study suggests widespread intra- and inter-network dysconnectivity among large-scale RSNs in schizophrenia, mainly involving the DMN, SN and SMN, which may further contribute to the dysconnectivity hypothesis of schizophrenia.
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Affiliation(s)
- Bei Rong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huan Huang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Guoqing Gao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Limin Sun
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yuan Zhou
- Institute of Psychology, CAS Key Laboratory of Behavioral Science, Beijing 100101, China
| | - Ling Xiao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan 430071, China
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Disorganization domain as a putative predictor of Treatment Resistant Schizophrenia (TRS) diagnosis: A machine learning approach. J Psychiatr Res 2022; 155:572-578. [PMID: 36206601 DOI: 10.1016/j.jpsychires.2022.09.044] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Treatment Resistant Schizophrenia (TRS) is the persistence of significant symptoms despite adequate antipsychotic treatment. Although consensus guidelines are available, this condition remains often unrecognized and an average delay of 4-9 years in the initiation of clozapine, the gold standard for the pharmacological treatment of TRS, has been reported. We aimed to determine through a machine learning approach which domain of the Positive and Negative Syndrome Scale (PANSS) 5-factor model was most associated with TRS. METHODS In a cross-sectional design, 128 schizophrenia patients were classified as TRS (n = 58) or non-TRS (n = 60) after a structured retrospective-prospective analysis of treatment response. The random forest algorithm (RF) was trained to analyze the relationship between the presence/absence of TRS and PANSS-based psychopathological factor scores (positive, negative, disorganization, excitement, and emotional distress). As a complementary strategy to identify the variables most associated with the diagnosis of TRS, we included the variables selected by the RF algorithm in a multivariate logistic regression model. RESULTS according to the RF model, patients with higher disorganization, positive, and excitement symptom scores were more likely to be classified as TRS. The model showed an accuracy of 67.19%, a sensitivity of 62.07%, and a specificity of 71.43%, with an area under the curve (AUC) of 76.56%. The multivariate model including disorganization, positive, and excitement factors showed that disorganization was the only factor significantly associated with TRS. Therefore, the disorganization factor was the variable most consistently associated with the diagnosis of TRS in our sample.
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Zhuo C, Chen G, Chen J, Yang L, Zhang Q, Li Q, Wang L, Ma X, Sun Y, Jia F, Tian H, Jiang D. Baseline global brain structural and functional alterations at the time of symptom onset can predict subsequent cognitive deterioration in drug-naïve first-episode schizophrenia patients: Evidence from a follow-up study. Front Psychiatry 2022; 13:1012428. [PMID: 36311504 PMCID: PMC9615917 DOI: 10.3389/fpsyt.2022.1012428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 09/26/2022] [Indexed: 01/10/2023] Open
Abstract
Alterations in the global brain gray matter volume (gGMV) and global functional connectivity density (gFCD) play a pivotal role in the cognitive impairment and further deterioration in schizophrenia. This study aimed to assess the correlation between alterations in the gGMV and gFCD at baseline (ΔgGMV and ΔgFCD), and the subsequent alterations of cognitive function in schizophrenia patients after 2-year antipsychotic treatment. Global-brain magnetic resonance imaging scans were acquired from 877 drug-naïve, first-episode schizophrenia patients at baseline and after two years of antipsychotic treatment with adequate dosage and duration, and 200 healthy controls. According to ΔgGMV at baseline, schizophrenia patients were divided into mild, moderate, and severe alteration groups. The MATRICS consensus cognitive battery and Global Deficit Score (GDS) were used to assess cognitive impairment. We found that ΔgGMV and ΔgFCD at baseline were significantly correlated with the severity of the cognitive deterioration (ΔGDS). The correlation coefficient indicated a significant positive correlation between baseline ΔgFCD and subsequent cognitive deterioration, with a relatively stronger relation in the mild alteration group (r = 0.31). In addition, there was a significant positive correlation between baseline ΔgGMV and subsequent cognitive deterioration, with a stronger relation in the moderate and severe alteration groups (r = 0.303; r = 0.302, respectively). Our results showed that ΔgGMV and ΔgFCD are correlated with the severity of cognitive deterioration after completion of a 2-year antipsychotic treatment in schizophrenia patients. These findings suggest that baseline alterations in gGMV and gFCD hold potential for predicting subsequent cognitive decline in schizophrenia.
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Affiliation(s)
- Chuanjun Zhuo
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China.,Department of Psychiatry, Wenzhou Seventh Peoples Hospital, Wenzhou, China.,Department of Psychiatry, Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China
| | - Guangdong Chen
- Department of Psychiatry, Wenzhou Seventh Peoples Hospital, Wenzhou, China
| | - Jiayue Chen
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China
| | - Lei Yang
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China
| | - Qiuyu Zhang
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China
| | - Qianchen Li
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China
| | - Lina Wang
- Department of Psychiatry, Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China
| | - Xiaoyan Ma
- Department of Psychiatry, Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China
| | - Yun Sun
- Department of Psychiatry, Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China
| | - Feng Jia
- Department of Psychiatry, Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Nankai University Affiliated Tianjin Anding Hospital, Tianjin, China
| | - Hongjun Tian
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPAS_Lab), Tianjin Fourth Center Hospital, Nankai University Affiliated Tianjin Fourth Center Hospital, Tianjin Medical University Affiliated of Tianjin Fourth Center Hospital, Tianjin, China
| | - Deguo Jiang
- Department of Psychiatry, Wenzhou Seventh Peoples Hospital, Wenzhou, China
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