{"title":"Identification of major depressive disorder based on Triple-GCN model constructed with multimodal elastic network from higher-order brain connectivity","authors":"Ying Zou , Helu Shan , Yuan Li","doi":"10.1016/j.pscychresns.2026.112142","DOIUrl":"10.1016/j.pscychresns.2026.112142","url":null,"abstract":"<div><div>Major Depressive Disorder (MDD) is the common mental health disease threatening human well-being. Several neuroimaging studies show that analyzing neural connectivity patterns improved diagnostic accuracy, though most approaches overlook node-edge interactions. Our study proposed an integrated approach combining <em>LASSO</em> and <em>Ridge</em> regression algorithms with brain connectivity features. Using both sMRI and fMRI data, we constructed a Multi-feature(gray matter volume/ALFF/Reho) Fusion Elastic Net (MFEN) framework to enhance MDD identification. Furthermore, we improved the Graph Convolutional Neural Network (GCN) algorithm by incorporating a self-attention mechanism and applied a triple Siamese Network to enhance feature extraction. Our proposed method of MDD identification was experimented on 2048 first-episode drug-naive MDD patients and 2562 healthy controls, using rs-fMRI data and sMRI features from the UK Biobank database. Results demonstrated that the extracted features significantly enhanced discriminative capability, establishing the foundation for identifying more reliable biomarkers in MDD patients. By integrating these techniques with elastic networks, the classification accuracy for MDD detection improved substantially to 89%, highlighting the framework's superior performance in mental health diagnostics. In summary, this MDD identification framework proved highly effective and may offer novel insights for auxiliary diagnosis of other neuropsychiatric disorders in clinical practice.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112142"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Testing dopaminergic markers of problematic social media use using neuromelanin-sensitive MRI","authors":"Holly Shannon , Matteo Montgomery , Clifford Cassidy , Marianne Lemieux , Jasmin A. Yee , Lisa-Sarah Brunier , Kim G.C. Hellemans , Synthia Guimond","doi":"10.1016/j.pscychresns.2026.112144","DOIUrl":"10.1016/j.pscychresns.2026.112144","url":null,"abstract":"<div><h3>Background</h3><div>Neuromelanin-sensitive MRI (NM-MRI) has demonstrated potential as a proxy measure of dopamine functioning in the brain. Altered NM-MRI has been associated with substance use disorders, yet remains unexplored in problematic social media use (PSMU). The current study aims to determine whether higher PSMU is linked to lower NM-MRI signal intensity in the substantia nigra and ventral tegmental area (SN-VTA).</div></div><div><h3>Methods</h3><div>Seventy-two young adults (18–35 years of age) completed the Bergen Social Media Addiction Scale to measure PSMU and underwent an NM-MRI scan. Half of the participants had a first degree relative (FDR) with a psychotic disorder. Within the SN-VTA, the average contrast-to-noise ratio was calculated on NM-MRI images. Linear regressions included NM-MRI signal intensity and PSMU scores, with age, sex, and FDR status as covariates.</div></div><div><h3>Results</h3><div>Higher levels of PSMU were not significantly associated with average NM-MRI signal intensity in the whole SN-VTA (<em>p</em> = 0.65). Voxelwise analysis revealed ninety-nine voxels with higher NM-signal intensity (p<sub>corrected</sub> > 0.05). No significant main effect or interactions were observed for any covariates.</div></div><div><h3>Conclusions</h3><div>As the first application of NM-MRI to examine dopaminergic markers in relation to PSMU, these results highlight the importance of further studying brain correlates of PSMU beyond dopaminergic neuroadaptation.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112144"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoping Yi , Xueying Wang , Mingzhao Ma , Jinfan Zhang , Feifei Wu , Haimiao Huang , Qian Xiao , Xiaoqun Liu , Alessandro Grecucci
{"title":"Disease and state dependent neural markers in adolescents with BD. Understanding the neural bases of mania, depression and remission in a data fusion approach","authors":"Xiaoping Yi , Xueying Wang , Mingzhao Ma , Jinfan Zhang , Feifei Wu , Haimiao Huang , Qian Xiao , Xiaoqun Liu , Alessandro Grecucci","doi":"10.1016/j.pscychresns.2025.112113","DOIUrl":"10.1016/j.pscychresns.2025.112113","url":null,"abstract":"<div><h3>Background</h3><div>Pediatric bipolar disorder (PBD) is a severe and disabling condition marked by alternating episodes of mania and depression, intermitted with periods of remission. A critical challenge in the field is to elucidate the neural mechanisms underlying these distinct mood states, as manic and depressive presentations reflect profoundly different clinical phenotypes. Despite their relevance, the functional and structural brain alterations associated with manic, depressed, and remitted states in PBD remain poorly understood.</div></div><div><h3>Method</h3><div>In this study, data on Resting-State Regional Homogeneity (ReHo) and grey matter concentration (GMC) were considered from 58 PBD patients and 21 healthy controls (HC), matched for age, gender, education, and IQ. The analysis was conducted using Parallel ICA, a multivariate data-driven approach that identifies joint patterns of covariation across resting-state functional and gray matter features.</div></div><div><h3>Results</h3><div>Among the nine RS-GM components identified, distinct disease- and state-dependent networks were detected. GM2, a cortico-limbic network, differentiated PBD from HC, suggesting a neural substrate of bipolar disorder independent of mood state. GM9, including the cingulate and the precuneus, distinguished manic from depressed states, while RS7, including the fusiform and occipital regions, was specific to depression compared to HC. RS1, including regions of the DMN, differentiated manic from remitted states.</div></div><div><h3>Conclusions</h3><div>These findings provide new fresh understanding on the common and separate functional and structural abnormalities displayed during mania, depression and remission phases in bipolar patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112113"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enlarged cavum septum pellucidum & increased incidence of schizophrenia: Narrative review for neurodevelopmental correlate","authors":"Mugdha Tendulkar , Dr.Reshma Tendulkar","doi":"10.1016/j.pscychresns.2025.112134","DOIUrl":"10.1016/j.pscychresns.2025.112134","url":null,"abstract":"<div><div>Schizophrenia being a major psychiatric disorder comprises of dominant neurodevelopmental corroborations; still there are inadequate markers which reveal the brain vulnerability. Recognition of such neurodevelopmental correlates linked with schizophrenia is a major hindrance observed in today’s era. It presents itself as a major hurdle as it necessitates comprehending the early brain alterations hinting towards vulnerability of brain parenchyma towards disorders. One such correlate being cavum septum pellucidum (CSP), has been frequently linked with schizophrenia. The primary obstacle in the management of psychological disorders is the significantly delayed diagnosis because of the societal stigma and the preconceived notions about these diseases.</div><div>This narrative review encompasses recent studies from 2018–2025 extracting high yield neuroimaging, molecular, genetic data to meticulously explain the association between enlarged CSP and schizophrenia, to critically appraise the clinical potential of enlarged cavum septum pellucidum as a neurodevelopmental liability marker as well as for incorporating them with multimodal artificial intelligence models rather than predicting or diagnosing schizophrenia at patient level.</div><div>This review is first to amalgamate extensive volumetric, meta-analyses as well as genetic data to highlight the role of CSP as a correlation risk marker from other non-specific parameters, aiding in better management of patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112134"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145918313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhongsi Wang , Yang Jiaqin , Yuyan Jing , Chunlei Liu , Min Chen
{"title":"Spatiotemporal decoding of visual working memory deficits in schizophrenia using EEG multivariate pattern analysis","authors":"Zhongsi Wang , Yang Jiaqin , Yuyan Jing , Chunlei Liu , Min Chen","doi":"10.1016/j.pscychresns.2026.112160","DOIUrl":"10.1016/j.pscychresns.2026.112160","url":null,"abstract":"<div><div>Deficits in visual working memory (vWM) are a fundamental cognitive characteristic of schizophrenia; however, the dynamic spatiotemporal characterization of their neural mechanisms remains unclear. The present study employs multivariate pattern classification (MVPC) and searchlight analysis to investigate neural signaling differences between patients with schizophrenia (PSZ) and healthy controls (HCS) during a vWM task. A total of 46 participants (22 PSZ, 24 HCS) completed the change detection task (1T/2T/4T). Contralateral delay activity (CDA) was extracted through ERP analysis. MVPC was employed in the temporal dimension, while a searchlight approach was employed in the spatial dimension to decode memory load (1T/2T/4T) and memory side (left/right) information. CDA amplitude was significantly lower in the PSZ group (<em>p</em> = .04). MVPC analysis indicated that decoding accuracy in the PSZ group was significantly lower than that in the HCS group during the 176–656 ms window (pcorrected < 0.05), suggesting reduced discriminability of multivariate ERP patterns during the delay period. Searchlight analysis revealed broadly reduced decoding across the scalp in PSZ, with the strongest group differences over posterior parieto-occipital scalp electrodes (peaking around PO3/PO4), which is consistent with prior evidence implicating posterior parietal systems in vWM maintenance. This study reveals the spatiotemporal dynamics of vWM deficits in schizophrenia using ERP decoding approaches and may inform future development of neuromarker-guided cognitive interventions.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112160"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146119945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qinnaer Bolatijiang , Shaohong Zou , Chengji Wang , Jianliang Zhang , Zhiyuan Chen , Longyuan Zhang
{"title":"Brain biochemical metabolism using proton magnetic resonance spectroscopy in adolescents bipolar depression with verbal auditory hallucinations","authors":"Qinnaer Bolatijiang , Shaohong Zou , Chengji Wang , Jianliang Zhang , Zhiyuan Chen , Longyuan Zhang","doi":"10.1016/j.pscychresns.2025.112135","DOIUrl":"10.1016/j.pscychresns.2025.112135","url":null,"abstract":"<div><h3>Objective</h3><div>This study utilizes proton magnetic resonance spectroscopy (<sup>1</sup>H-MRS) imaging to analyze neuro-metabolic alterations in the ventromedial prefrontal cortex (vmPFC) of adolescents with bipolar depression (BD-Dep) and verbal auditory hallucinations (AVHs).</div></div><div><h3>Methods</h3><div>A retrospective analysis was conducted on 47 untreated adolescent BD-Dep patients within 30 days, between January 2024 and August 2025. Comprehensive clinical data were collected for all patients, including gender, age, age of onset, years of education, and the presence of suicidal or self-harming behaviors. Patients were divided into two groups: an AVH group (P3 score >3, <em>n</em> = 24) and a non-hallucination group (P3 score ≤3, <em>n</em> = 23), based on PANSS P3 scores and the presence of AVHs. Both groups underwent <sup>1</sup>H-MRS scanning of the vmPFC to compare the ratios of N-acetyl aspartate/creatine (NAA/Cr), choline/creatine (Cho/Cr), myo-inositol/creatine (mI/Cr), glutamate/creatine (Glu/Cr), and NAA/Cho.</div></div><div><h3>Results</h3><div>The comparison of Cho/Cr ratios between the two groups—0.685 (0.653, 0.748) versus 0.600 (0.530, 0.650)—revealed a statistically significant difference (<em>Z</em> = 3.346, <em>P</em> = 0.001, <0.05). No statistically significant differences were found in the NAA/Cr, mI/Cr, and Glu/Cr ratios between the two groups.</div></div><div><h3>Conclusion</h3><div>Adolescent BD-Dep patients with AVHs exhibit elevated Cho/Cr ratios. These biochemical metabolic changes in the vmPFC may be associated with the occurrence of AVHs in these patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112135"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"EEG/MEG-based biomarkers of cognitive training effects in schizophrenia: A systematic review","authors":"Alp Eren Yüce , Işın Yaman , Serdar Gündoğdu","doi":"10.1016/j.pscychresns.2025.112112","DOIUrl":"10.1016/j.pscychresns.2025.112112","url":null,"abstract":"<div><div>This systematic review aims to evaluate the effects of cognitive training methods on brain electrical activity in patients with schizophrenia, focusing on studies published between January 2010 and October 2025 in the PubMed and Web of Science databases. Twenty experimental and quasi-experimental studies were included in the study, examining various cognitive training methods, including auditory, visual, emotional, and social skills training. These studies measured Electroencephalography (EEG) and Magnetoencephalography (MEG) metrics, including oscillations, mismatch negativity (MMN), and event-related potentials (ERPs), to assess changes in neural activity associated with schizophrenia. Findings demonstrate that different cognitive training methods may improve neural oscillations, particularly in the gamma and alpha bands, and may enhance cognitive functions such as working memory, attention, and emotional regulation. While some studies have shown limited effects on specific EEG and MEG indices, the overall evidence suggests that personalized cognitive interventions can promote neuroplasticity and cognitive recovery in individuals with schizophrenia. These findings show the potential of integrating EEG/MEG-based biomarkers into clinical practices to enhance the effect of treatment and improve neural outcomes for schizophrenia patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112112"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146012244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emily L Matthews , Ely M Marceau , Charlotte C van Schie , Brin FS Grenyer
{"title":"Neural correlates of personal agency in borderline personality disorder - An fMRI investigation using attachment-informed autobiographical memories","authors":"Emily L Matthews , Ely M Marceau , Charlotte C van Schie , Brin FS Grenyer","doi":"10.1016/j.pscychresns.2025.112111","DOIUrl":"10.1016/j.pscychresns.2025.112111","url":null,"abstract":"<div><div>Individuals with borderline personality disorder (BPD) have identity disturbance and difficulty with self/other distinction which may be linked to difficulties in personal agency. Neuroimaging research has helped inform underlying deficits linked to sociocognitive functioning, however, no research has specifically investigated neural correlates of personal agency in BPD. We used an attachment-informed autobiographical memory recall task to investigate behavioural and neural mechanisms of personal agency in BPD. Individuals with BPD (<em>n</em> = 34) and nonclinical controls (NCC, <em>n</em> = 35) recalled attachment and neutral memories during functional magnetic resonance imaging (fMRI). Behavioural analyses of affect, agency, and vividness of memories, and event-related fMRI analysis compared neutral and attachment-informed memories. Parametric modulation identified changes in neural activation associated with increasing agency. People with BPD felt less agentic and more negative during recall of attachment-informed memories, compared to NCCs. Agency was similar between groups for neutral memories. We found hyperactivation in the temporal parietal junction (TPJ) and superior temporal gyrus particularly during memories involving more distant attachment figures. Differential activation between BPD and NCC groups based on level of agency was found, including in the right-TPJ. Personal agency is influenced by relational contextual factors, with individuals with BPD being affected in agency when recalling memories with attachment figures. The neural hyperactivation findings provide evidence for how attachment distress or negative relational experiences may be associated with poor personal agency. This has implications for interpersonal functioning in BPD and highlights the importance and challenges of fostering personal agency in treatment.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"356 ","pages":"Article 112111"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145834632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intelligent electroencephalogram feature engineering for rapid mental health diagnosis","authors":"Ammu Kripalal , C. Sekar","doi":"10.1016/j.pscychresns.2025.112103","DOIUrl":"10.1016/j.pscychresns.2025.112103","url":null,"abstract":"<div><div>Schizophrenia is one of the serious disorders and, if left untreated, can result in a range of problems with cognition, behavior, and emotions that affect every area of life. Diagnosis based on behavioral and clinical investigations remains difficult with schizophrenia symptoms which are complex and heterogenic. Early detection of schizophrenia is essential for the timely treatment leading to betterment of the life of patients. In this study based on machine learning algorithms, we have identified the relevant set of features from the electroencephalogram (EEG) signal to improve the classification accuracy of patients with schizophrenia and healthy controls. Combinations of these identified relevant features have been used to diagnose schizophrenia.Furthermore, we validated this same feature set as the high performing feature subset on an independent dataset, confirming its robustness and generalizability. The results show that the selected features from the EEG signal achieve the highest accuracy of 94.7% and 96.4% for Logistic Regression (LR) and Support Vector Machines (SVM) respectively with reduced data. Reduction in training data with this feature selection enhances the performance of edge devices that are optimized for applications such as brain computer interfaces, neurological disorder detection, cognitive state monitoring, and neurofeedback training.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"356 ","pages":"Article 112103"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stéphanie Grot , Luigi De Benedictis , Alan Bougeard , Philippe Albouy , Emmanuel Stip , Stéphane Potvin , Pierre Orban
{"title":"Effect of personalized dorsolateral prefrontal cortex neuromodulation on default mode connectivity and working memory in schizophrenia spectrum disorders","authors":"Stéphanie Grot , Luigi De Benedictis , Alan Bougeard , Philippe Albouy , Emmanuel Stip , Stéphane Potvin , Pierre Orban","doi":"10.1016/j.pscychresns.2025.112093","DOIUrl":"10.1016/j.pscychresns.2025.112093","url":null,"abstract":"<div><div>Schizophrenia spectrum disorders (SSD) are marked by working memory impairments associated with abnormal functional brain connectivity. Although transcranial magnetic stimulation (TMS) shows promise in modulating dysconnectivity patterns and improving cognitive symptoms, current protocols often lack target personalization, overlooking significant variability in functional network topography between individuals. Twenty-two individuals with SSD and cognitive deficits underwent 20Hz repetitive TMS to the left lateral prefrontal cortex. Personalized TMS targeted regions with the strongest central executive-default mode network (CEN-DMN) antagonism, while standardized TMS focused on the EEG F3 site. Resting-state fMRI scans were conducted pre- and post-TMS sessions to evaluate changes in CEN-DMN connectivity, and working memory performance was assessed after the post-TMS fMRI scan. Both TMS protocols failed to significantly alter CEN-DMN connectivity or improve cognitive function, which may be due to the low reliability of the biomarker used for personalized targeting. However, stronger DMN intra-network connectivity at the stimulation site was positively correlated with a reduction in CEN-DMN connectivity and improved working memory performance. These findings highlight the need for more extensive fMRI data for better target determination, and suggest that targeting left prefrontal areas with higher DMN connectivity could more effectively modulate functional connectivity and improve working memory performance through TMS.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"356 ","pages":"Article 112093"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}