Brain Imaging and Behavior最新文献

{"title":"Sex differences in brain network functional connectivity and their association with gene expression profiles in major depressive disorder: a REST-meta-MDD project-based study.","authors":"Jiang Wang, Chengfeng Chen, Shiying Wang, Yuan Liu, Peiying Li, Bin Zhang","doi":"10.1007/s11682-025-01062-1","DOIUrl":"https://doi.org/10.1007/s11682-025-01062-1","url":null,"abstract":"<p><p>The specific role of sex differences in major depressive disorder remains unclear, this study aims to explore sex-related variations in resting-state functional connectivity of major depressive disorder patients and their association with gene expression profiles. This study included 971 patients and 897 healthy controls from the REST-meta-MDD project. We compared the functional connectivity between sexes and used the Allen Human Brain Atlas to conduct partial least squares regression analysis to identify genes associated with these functional connectivity differences in patients, followed by functional enrichment analysis. Compared to female patients, male patients exhibit increased functional connectivities between the default mode network and the frontoparietal network, while connectivities between the frontoparietal network and the visual network are reduced. Additionally, Spearman's correlation analysis identified specific patterns of functional connectivity differences that are closely associated with the Hamilton Depression Rating Scale scores in both sexes. Transcriptomic-neuroimaging analysis revealed that the expression of 1,777 genes is associated with functional connectivity differences between sexes. Enrichment analysis indicated that these genes are primarily involved in biological processes including ion channel activity, synaptic plasticity, neuronal differentiation, and synaptic development. Patients with major depressive disorder exhibited sex-related differences in functional connectivity, particularly between networks involved in self-referential thinking, emotional regulation, and cognitive control. Genes associated with these differences were primarily enriched in ion channel activity and neuronal processes, highlighting the importance of sex-specific neural mechanisms in major depressive disorder and their potential relevance for personalized treatment strategies.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The plasticity of olfactory learning in culinary students and matched controls.","authors":"Andreas Steenholt Niklassen, Henrique M Fernandes, Emil Linnet, Nicoline Brochdorff Therkildsen, Thomas Hummel, Therese Ovesen, Alexander Wieck Fjaeldstad","doi":"10.1007/s11682-025-01055-0","DOIUrl":"https://doi.org/10.1007/s11682-025-01055-0","url":null,"abstract":"<p><strong>Background: </strong>Brain plasticity is essential for experts to develop and maintain a high skill level. The aim was to investigate chemosensory sensitivity and central structural connectivity in culinary students naturally training olfactory abilities throughout the first year of education and compare the findings to matched controls.</p><p><strong>Methodology: </strong>The population included 24 culinary students and 28 controls at the start of their education and 12 months later. The Sniffin' Sticks olfactory test of olfactory capabilities for threshold, discrimination, and identification were used. Central olfactory plasticity was investigated with magnetic resonance imaging and diffusion tensor imaging to create a structural connectivity matrix of primary and secondary olfactory processing areas for each participant with the seed at the primary olfactory cortex.</p><p><strong>Results: </strong>For olfactory function, the threshold worsened from 7.23 to 5.42 for controls (P = 0.01); however, Discrimination increased for culinary students from 12.16 to 13.61 (P = 0.03).Compared to controls,culinary students demonstrated stronger connectivity to the gyrus rectus (t = 2.49 p = 0.02) and had a priori stronger connectivity to the caudate nucleus at baseline (t = 2.7147, p = 0.0091), and at follow-up (t = 2.18, P = 0.03).</p><p><strong>Conclusions: </strong>Culinary students improved their discriminative olfactory abilities during the first year of their education compared to non-culinary students. The culinary students had apriori stronger connectivity to the caudate nucleus than the controls, which remained present at follow-up. Additionally, the culinary students demonstrated stronger connectivity to the gyrus rectus after the first year of their education compared to controls.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing Gray matter atrophy patterns associated with accelerometer-measured sedentary behavior: a population-based study.","authors":"Minle Tian, Xiaolei Han, Ming Mao, Xiaomeng Li, Yi Dong, Jiahao Ding, Qinghua Zhang, Shi Tang, Xiaojuan Han, Lin Song, Tingting Hou, Lin Cong, Yifeng Du, Chengxuan Qiu, Yongxiang Wang","doi":"10.1007/s11682-025-01054-1","DOIUrl":"https://doi.org/10.1007/s11682-025-01054-1","url":null,"abstract":"<p><p>Evidence has linked self-reported sedentary behaviors with dementia and cognitive impairment; however, the underlying mechanisms remain poorly understood. We investigated the associations of accelerometer-measured sedentary behavior patterns with gray matter atrophy patterns in rural-dwelling older adults, while taking into account the manner in which sedentary time is accrued (in short or long bouts). This community-based study involved 911 dementia-free older adults (age ≥ 60 years, 59% women) who participated in both ActiGraph and brain MRI substudies within MIND-China (2018-2020). Sedentary behavior parameters (total sedentary time, mean sedentary bout duration, and sedentary breaks) were recorded with accelerometers. Regional gray matter volumes (GMV) were measured using voxel-based morphometry (VBM) methods. Data were analyzed using the general linear regression models, restricted cubic spline curves, and VBM analysis. There was an inverted U-shaped association between daily sedentary time and GMV in temporal, cingulate, and medial temporal cortex, while longer mean sedentary bout duration was linearly related to decreased GMV in total, frontal, temporal, insula, cingulate, and medial temporal cortex. Greater daily time spent in light or moderate-to-vigorous physical activity (LPA and MVPA) was correlated with larger insula GMV. The VBM analysis suggested that prolonged daily total sedentary time and mean sedentary bout duration were significantly associated with smaller GMV in extensive brain regions, especially in thalamus and insula. In conclusion, gray matter atrophy associated with sedentary behavior in older adults is characterized by reduced GMV in global, frontal, temporal, medial temporal, and cingulate cortex, especially in the insula and thalamus regions.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive profiles among dementia-free older adults and their associations with neuroimaging markers.","authors":"Alice Hahn, Heather Volk, Corinne Pettigrew, Andreia Faria, Murat Bilgel, Hanzhang Lu, Michael Miller, Marilyn Albert, Anja Soldan","doi":"10.1007/s11682-025-01051-4","DOIUrl":"https://doi.org/10.1007/s11682-025-01051-4","url":null,"abstract":"<p><p>Prior studies have demonstrated the existence of cognitively-defined subgroups among dementia free older adults, however, it is unclear whether such subgroups are characterized by distinct neuroimaging measures of brain function and structure. To address this gap, the current study used latent profile analysis (LPA) to identify cognitively-defined subgroups in a sample of 167 (mean age = 69 years) dementia-free older adults with cognitive testing, amyloid PET, and multimodal brain MRI scans. The cognitive test scores covered the domains of episodic memory, executive function, language, and visuospatial processing. Linear regression models tested the associations between subgroup membership and neuroimaging measures, adjusting for age, sex, and years of education. Based on the LPA, three cognitive subgroups were identified: (1) high-average cognition (n = 61, 36%), (2) average cognition (n = 88, 53%), and low-average cognition (n = 18, 11%). Compared to the high-average group, the low-average group had lower volumes in cortical regions sensitive to Alzheimer's disease, lower global white matter microstructural integrity measured by diffusion tensor imaging, and higher global white matter hyperintensity burden. There were no group differences in global PET amyloid burden. Additionally, the high-average group tended to have higher resting-state functional connectivity within large-scale cognitive networks than the other two groups. These results suggest that cognitively-defined subgroups among older adults without dementia are associated with several measures of brain structure and function. Evaluating brain structure/function differences among dementia-free older adults may help identify individuals at greatest risk for future cognitive decline.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered effective connectivity within the hippocampal-prefrontal circuit in patients with non-small cell lung cancer after platinum chemotherapy.","authors":"Lanyue Hu, Zhengqian Wang, Shuo Li, Yujie Zhang, Jia You, Qian Li, Yu-Chen Chen, Xindao Yin","doi":"10.1007/s11682-025-01060-3","DOIUrl":"https://doi.org/10.1007/s11682-025-01060-3","url":null,"abstract":"<p><p>To investigate the effects of platinum-based chemotherapeutic drugs on the effective connectivity (EC) of hippocampal-prefrontal (HIP-PFC) circuit in non-small cell lung cancer (NSCLC) patients utilizing spectral dynamic causal model (sDCM), and to explore its correlation with cognitive deficits. A total of 109 patients diagnosed with NSCLC (57 without chemotherapy (CT-) and 52 with chemotherapy (CT+)) and 60 healthy controls (HCs) were enrolled. Longitudinal data pre- and post-chemotherapy were available for 30 patients. All participants underwent functional magnetic resonance imaging (fMRI) and cognitive assessments. Effective connectivity within the HIP-PFC circuit for all participants were analyzed using the sDCM approach. Relationships between abnormal connectivity strength and neuropsychological scores were evaluated. The results revealed ECs differences among three groups in the HIP-PFC circuit concentrated in the bilateral hippocampus and right frontal lobe. Analysis of paired groups identified more abnormalities across cerebral hemispheres, including excitatory connectivity from l-HIP to right lateral prefrontal cortex (LPFC). The reduced EC from the l-HIP to the medial prefrontal cortex (mPFC) was significantly negatively correlated with the MoCA scores (r = -0.315, p = 0.007), and the reduced EC from the r-HIP to the mPFC was significantly negatively correlated with the memory scores (r = -0.349, p = 0.006). These insights further bolstered the crucial role of the HIP-PFC circuit in the pathophysiology of cognitive impairment induced by platinum-based chemotherapeutic agents, highlighting its potential as a novel imaging biomarker and therapeutic target.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating structural-functional brain covariation in bipolar disorder using a multimodal fusion approach.","authors":"Wei Zhang, Yingling Hou, Xinyi Wang, Yurong Sun, Junneng Shao, Rui Yan, Xuejun Kang, Zhijian Yao, Qing Lu","doi":"10.1007/s11682-025-01049-y","DOIUrl":"https://doi.org/10.1007/s11682-025-01049-y","url":null,"abstract":"<p><p>Due to the lack of consistent findings across different modalities, the neurobiological underpinning of bipolar disorder (BD) remains elusive. This study aims to employ a multimodal fusion algorithm, integrating multimodal imaging data, to unravel the neurobiological underpinning of BD. A data-driven multimodal fusion algorithm was utilized to analyze covariant patterns across modalities in a cohort of 125 BD patients and 113 healthy controls (HCs). The study focused on fusing regional homogeneity (ReHo), gray matter volume (GMV), and fractional anisotropy (FA) derived from MRI scans to generate group-discriminative joint independent components (jIC). That differentiated BD patients from HCs across three modalities. An inverse functional pattern was observed in the default mode network (DMN) and sensorimotor network (SMN) in BD patients, characterized by increased ReHo in the DMN and decreased ReHo in the SMN compared to healthy individuals. This inverse pattern was also mirrored in GMV, showing increase in the DMN and decreases in the SMN. Meanwhile, significant functional hyperactivation coupled with decreased structural volume in the precuneus underscores its role in cognitive function in BD. Multimodal neuroimaging fusion provides a comprehensive understanding in pathophysiology of BD, offering valuable insights that could be pivotal in advancing the diagnosis and treatment of BD.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving presurgical language mapping by a method for optimally sorting independent components of resting-state fMRI.","authors":"Beatriz Vale, Diogo Duarte, Ricardo Vigário, Christopher Benjamin, Pedro Vilela, Martin Lauterbach, Alexandre Andrade","doi":"10.1007/s11682-025-01058-x","DOIUrl":"https://doi.org/10.1007/s11682-025-01058-x","url":null,"abstract":"<p><p>Pre-surgical planning often involves task-based functional magnetic resonance imaging (fMRI) in the context of intractable epilepsy or brain tumors. Resting-state fMRI can be used for the same goal, with the advantage of being a simpler technique that does not require the patient to cooperate in complex cognitive tasks. However, the methods for resting-state fMRI analysis are not yet robust or of practical usage. This work proposes an algorithm for sorting components resulting from independent component analysis (ICA) that emphasizes the language resting-state network. We recruited 20 healthy volunteers and acquired resting-state and task-based fMRI using three linguistic tasks. Task data was processed using general linear model analysis, while resting-state networks were extracted using ICA. An automated IC sorting procedure was developed based on three characteristics: spatial similarity with a probability map, low/high frequency ratio, and IC reliability over several bootstrapping folds. Task-related activation consistent with the language network was identified at the subject-specific level. The algorithm is shown to sort ICs with the resting-state language maps appearing among the first three with an accuracy of 74%. Overall, the Dice coefficient showed a good overlap between the sorted ICs of relevance and the task language maps. Results showed that resting-state networks were more specific and less sensitive than task-based maps. We expect that the proposed algorithm for optimal sorting will contribute towards making ICA usage viable in the clinical context and become a reliable alternative method for pre-surgical planning.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145172877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring individual differences in the impact of cognitive constraints on prosocial decision-making via intrinsic brain connectivity.","authors":"Zhengjie Liu, Jie Liu, Fang Cui","doi":"10.1007/s11682-025-01050-5","DOIUrl":"https://doi.org/10.1007/s11682-025-01050-5","url":null,"abstract":"<p><p>Prosocial decisions in daily life are often influenced by cognitive constraints, such as time pressure and cognitive load, which can impact how we process information and make decisions that benefit others. Understanding how these constraints interact with our brain's intrinsic connectivity patterns and contribute to individual differences is crucial. This study investigates the neural mechanisms underlying the effects of cognitive constraints on prosocial decision-making. We developed a resting-state functional connectivity (rsFC) network model using machine learning regression to predict how cognitive constraints influence prosocial choices, while accounting for individual variability through intersubject representational similarity analysis (IS-RSA). Our findings reveal that the rsFC network-including regions involved in affective processing (insula, INS; amygdala, AMYG), empathy (temporo-parietal junction, TPJ; medial cingulate gyrus, MCG), and valuation (ventral striatum, VS; ventral prefrontal cortex, vmPFC)-predicts the impact of cognitive constraints on decision-making. Notably, rsFC between MCG and TPJ and bilateral TPJ connectivity showed intersubject variability that aligned with behavioral responses. These findings elucidate how cognitive constraints shape prosocial decision-making at the neural level, uncovering individual variability that advances theoretical understanding and offers practical implications for fostering prosociality in cognitively demanding contexts.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145173828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional connectome fingerprinting related to BMI and its association with impulsivity.","authors":"Jizheng Zhao, Hongxing Ning, Jiahui Qiao, Feng Yan","doi":"10.1007/s11682-025-01056-z","DOIUrl":"https://doi.org/10.1007/s11682-025-01056-z","url":null,"abstract":"<p><p>Obesity is associated with intrinsic functional reorganization within the brain. However, limited research has utilized resting-state functional connectome models to predict body mass index (BMI) and explore the relationship between BMI-related resting-state functional connectivity (rsFC) and behavioral performance. Least absolute shrinkage and selection operator (LASSO) regression models were developed using the HCP500 dataset (440 subjects) to identify BMI-related rsFC patterns and predict BMI values. The model demonstrating the strongest predictive power was validated on the HCP900 dataset (309 subjects). Additional validation was performed using the HCP1200 (182 subjects), NKI (102 subjects), and MPI-LEMON (151 subjects) datasets. We examined the relationship between BMI-related rsFC sets and performance on the Dimensional Change Card Sort and Delay Discounting tests. Predicted BMI values were significantly correlated with actual BMI values across the HCP1200 and NKI datasets (HCP1200: r = 0.52, p = 8E-14, MAE = 3.30; NKI: r = 0.35, p = 0.0002, MAE = 4.17). The identified BMI-related rsFC sets encompassed brain circuits involved in hemostatic control, executive function, salience processing, motor planning, reward processing, and visual perception. Notably, these rsFC fingerprintings significantly accounted for scores on the delay discounting task. Our findings demonstrate that BMI can be predicted using a functional connectome-based model. Additionally, the identified BMI-related rsFC fingerprintings effectively explained scores on delay discounting tasks, providing new insights into the neural mechanisms associated with overweight and obesity.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State-base dynamic functional connectivity analysis of fMRI data during facial emotional processing.","authors":"Maryam Gholam Tamimi, Mohammad Reza Daliri","doi":"10.1007/s11682-025-01059-w","DOIUrl":"https://doi.org/10.1007/s11682-025-01059-w","url":null,"abstract":"<p><p>Emotion is present in all aspects of human life and serves as a crucial foundation for communication and interaction. Emotional processing (EP) is a complex phenomenon involving dynamic interactions among various brain regions. Despite significant progress in EP research, important challenges remain-particularly in understanding the temporal dynamics of emotion. In this study, we investigated alterations in dynamic functional connectivity (dFC) patterns during an emotional processing task, using fMRI data from 100 healthy participants in the Human Connectome Project (HCP). The brain was parcellated into 90 regions of interest (ROIs) and grouped into six networks and ten well-known brain regions using the AAL atlas. We applied dFC analysis based on sliding window correlation (SWC) and k-means clustering to identify discrete connectivity states. To define the optimum number of states, we employed non-supervised validity criteria silhouette measure. Additionally, we estimated mean dwell times and transition probability matrices between states in both face and shape conditions using a hidden Markov model (HMM). Within these states, we observed state-dependent alterations in within and between regional connectivity between the face and shape conditions. Our findings revealed three distinct dFC states and among them, dFC state with the most significant differences in probability of transitions included brain regions involved in, frontoparietal, limbic and visual networks. Across all three states, several key bilateral regions exhibited significant changes in dFC, involved in limbic (amygdala, hippocampus, parahippocampal and rectus), default mode (anterior cingulate gyrus, median cingulate gyrus, posterior cingulate gyrus and angular), frontoparietal (inferior parietal gyrus, superior parietal gyrus, and middle frontal gyrus), visual (inferior occipital gyrus, fusiform, cuneus, precuneus, lingual and calcarine), temporal-parietal (paracentral lobule, precentral, postcentral, superior temporal gyrus, temporal pole superior and insula), and subcortical (caudate, putamen, pallidum and thalamus) networks. Also, we identified three dFC states between ten brain regions -frontal-central-parietal, frontal-temporal-occipital, and global state.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}