Clinical EEG and neuroscience最新文献

{"title":"Electroencephalography can Ubiquitously Delineate the Brain Dysfunction of Neurodegenerative Dementia by Both Visual and Automatic Analysis Methods: A Preliminary Study.","authors":"Kei Sato, Takefumi Hitomi, Katsuya Kobayashi, Masao Matsuhashi, Akihiro Shimotake, Akira Kuzuya, Ayae Kinoshita, Riki Matsumoto, Hajime Takechi, Takenao Sugi, Shigeto Nishida, Ryosuke Takahashi, Akio Ikeda","doi":"10.1177/15500594241283512","DOIUrl":"10.1177/15500594241283512","url":null,"abstract":"<p><p><b>Introduction:</b> The aim was to examine the differences in electroencephalography (EEG) findings by visual and automated quantitative analyses between Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) and Parkinson's disease with dementia (PDD). <b>Methods:</b> EEG data of 20 patients with AD and 24 with DLB/PDD (12 DLB and 12 PDD) were retrospectively analyzed. Based on the awake EEG, the posterior dominant rhythm frequency and proportion of patients who showed intermittent focal and diffuse slow waves (IDS) were visually and automatically compared between the AD and DLB/PDD groups. <b>Results:</b> On visual analysis, patients with DLB/PDD showed a lower PDR frequency than patients with AD. In patients with PDR <8 Hz and occipital slow waves or patients with PDR <8 Hz and IDS, DLB/PDD was highly suspected (PPV 100%) and AD was unlikely (PPV 0%). On automatic analysis, the findings of the PDR were similar to those on visual analysis. Comparisons between visual and automatic analysis showed an overlap in the focal slow wave commonly detected by both methods in 10 of 44 patients, and concordant presence or absence of IDS in 29 of 43 patients. With respect to PDR <8 Hz and the combination of PDR <8 Hz and IDS, PPV and NPV in DLB/PDD and AD were not different between visual and automatic analysis. <b>Conclusions:</b> As the noninvasive, widely available clinical tool of low expense, visual analysis of EEG findings provided highly sufficient information to delineate different brain dysfunction in AD and DLB/PDD, and automatic EEG analysis could support visual analysis especially about PD.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"185-196"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Utility of 24-h Video-EEG Monitoring in the Diagnosis of Epilepsy in Children.","authors":"Qingxiang Zhang, Wenjin Zheng, Stéphane Jean, Fuliang Lai, Weihong Liu, Shiwei Song","doi":"10.1177/15500594241286684","DOIUrl":"10.1177/15500594241286684","url":null,"abstract":"<p><p><b>Objectives:</b> Evaluate the diagnostic yield of 24-h video-EEG monitoring in a group of children admitted in our epilepsy monitoring unit (EMU). <b>Methods:</b> 232 children who underwent 24-h video-EEG monitoring was analysed. We divided each patient's monitoring duration into the first 1, 2, 4, 8, 16 h, relative to the whole 24 h monitoring period. The detection of the first interictal epileptiform discharges (IEDs), epileptic seizures (ES), and psychogenic non-epileptic seizures (PNES) were analysed relative to the different monitoring time subdivision. <b>Results:</b> Our findings revealed that: (1) there was no significant difference in the prevalence of detecting initial IEDs between the first 4-h and 24-h monitoring periods (73.7% vs 81%); (2) clinical events detection rate was statistically similar between the first 8-h and 24-h monitoring periods (15.5% vs 19.3%); (4) an 8-h monitoring was sufficient to capture IEDs, ES and PNES in focal epilepsy children; (5) a 1-h monitoring was sufficient to capture IEDs, ES and PNES in generalized epilepsy children; and (6) IEDs were detected within the first 1-h of monitoring in 96.7% self-limited focal epilepsies (SeLFEs) patient. <b>Conclusion:</b> Our study suggests that a 4-h monitoring has more value in increasing the detection rate of IEDs compared to the traditional shorter routine EEG. And in the case of SeLFEs, a 1-h of monitoring might be sufficient in detecting IEDs. A 24-h VEEG monitoring can detect clinical events in 19.3% of patients. Overall, the yield of IEDs and clinical events detection is adequate in children in children undergoing 24-h video-EEG monitoring.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"197-203"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closed-Loop Infraslow Brain-Computer Interface can Modulate Cortical Activity and Connectivity in Individuals With Chronic Painful Knee Osteoarthritis: A Secondary Analysis of a Randomized Placebo-Controlled Clinical Trial.","authors":"Jerin Mathew, Divya Bharatkumar Adhia, Mark Llewellyn Smith, Dirk De Ridder, Ramakrishnan Mani","doi":"10.1177/15500594241264892","DOIUrl":"10.1177/15500594241264892","url":null,"abstract":"<p><p><i>Introduction.</i> Chronic pain is a percept due to an imbalance in the activity between sensory-discriminative, motivational-affective, and descending pain-inhibitory brain regions. Evidence suggests that electroencephalography (EEG) infraslow fluctuation neurofeedback (ISF-NF) training can improve clinical outcomes. It is unknown whether such training can induce EEG activity and functional connectivity (FC) changes. A secondary data analysis of a feasibility clinical trial was conducted to determine whether EEG ISF-NF training can significantly alter EEG activity and FC between the targeted cortical regions in people with chronic painful knee osteoarthritis (OA). <i>Methods.</i> A parallel, two-arm, double-blind, randomized, sham-controlled clinical trial was conducted. People with chronic knee pain associated with OA were randomized to receive sham NF training or source-localized ratio ISF-NF training protocol to down-train ISF bands at the somatosensory (SSC), dorsal anterior cingulate (dACC), and uptrain pregenual anterior cingulate cortices (pgACC). Resting state EEG was recorded at baseline and immediate post-training. <i>Results.</i> The source localization mapping demonstrated a reduction (<i>P</i> = .04) in the ISF band activity at the left dorsolateral prefrontal cortex (LdlPFC) in the active NF group. Region of interest analysis yielded significant differences for ISF (<i>P</i> = .008), slow (<i>P</i> = .007), beta (<i>P</i> = .043), and gamma (<i>P</i> = .012) band activities at LdlPFC, dACC, and bilateral SSC. The FC between pgACC and left SSC in the delta band was negatively correlated with pain bothersomeness in the ISF-NF group. <i>Conclusion.</i> The EEG ISF-NF training can modulate EEG activity and connectivity in individuals with chronic painful knee osteoarthritis, and the observed EEG changes correlate with clinical pain measures.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"165-180"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800731/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141763283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EEG Findings in a Patient with Holmes Tremor after AVM Surgery: A Case Report and Literature Review.","authors":"Yang Wang, Bingjie Jiang","doi":"10.1177/15500594241276269","DOIUrl":"10.1177/15500594241276269","url":null,"abstract":"<p><p><b>Background:</b> Holmes tremor (HT) is a rare motor disorder characterized by high-amplitude and low-frequency resting, intentional, and postural tremors. HT typically arises from disruptions in neural pathways, including the dopaminergic system. Its causes include cerebrovascular incidents, neoplasms, demyelination, and infections. Diagnosis involves thorough clinical, neurophysiological, and neuroimaging assessments. Our report details the clinical profile, neuroimaging and EEG results and levodopa treatment response of an HT patient after cerebral arteriovenous malformation (AVM) surgery. <b>Case Report:</b> A female patient who underwent AVM surgery developed head tremor and dystonia. Neuroimaging revealed left thalamus involvement. Video electroencephalography (EEG) revealed high-amplitude, low-frequency tremors. The patient responded well to levodopa treatment. <b>Conclusions:</b> Involuntary rhythmic or non-rhythmic movements are a primary clinical feature of HT. A differential diagnosis of epilepsy and HT can be achieved through neurophysiological monitoring, avoiding the overuse of antiepileptic drugs. Symptoms can be alleviated with levodopa intervention.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"181-184"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Changes in Hypsarrhythmia Assessed by Spectral Analysis: Group and Individual Assessments.","authors":"Jessica M Farinha, Peter R Bartel, Piet J Becker, Lynton T Hazelhurst","doi":"10.1177/15500594241258558","DOIUrl":"10.1177/15500594241258558","url":null,"abstract":"<p><p><b>Objectives:</b> To perform spectral analysis on previously recorded electroencephalograms (EEGs) containing hypsarrhythmia in an initial recording and to assess changes in spectral power (µV²) in a follow-up recording after a period of 10-25 days. <b>Methods:</b> Fifty participants, aged 2-39 months, with hypsarrhythmia in an initial recording (R1), were compared with regard to their spectral findings in a later recording (R2). Typically, anticonvulsant therapy was initiated or modified after R1. Average delta, theta, alpha, and beta power was derived from approximately 3 min of artifact-free EEG data recorded from 19 electrode derivations. Group and individual changes in delta power between R1 and R2 formed the main analyses. <b>Results:</b> Delta accounted for 84% of the total power. In group comparisons, median delta power decreased statistically significantly between R1 and R2 in all 19 derivations, for example, from 3940 µV² in R1 to 1722 µV² in R2, Cz derivation. When assessing individual participants, delta power decreases in R2 were >50% in 60% of the participants, but <25% in 24% of the participants. <b>Conclusion:</b> Spectral analysis may be used as an additional tool for providing a potential biomarker in the assessment of short-term changes in hypsarrhythmia, including the effects of treatment.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"159-164"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141238504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Quantitative-Electroencephalogram (q-EEG) Measurements Between Patients of Dementia with Lewy Bodies (DLB) and Parkinson Disease Dementia (PDD).","authors":"Mehrnaz Rezvanfard, Ali Khaleghi, Amirhossein Ghaderi, Maryam Noroozian, Vajiheh Aghamollaii, Mehdi Tehranidust","doi":"10.1177/15500594251319863","DOIUrl":"https://doi.org/10.1177/15500594251319863","url":null,"abstract":"<p><p>Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are synucleinopathy syndromes with similar symptom profiles that are distinguished clinically based on the arbitrary rule of the time of symptom onset. Identifying reliable electroencephalographic (EEG) biomarkers would provide a precise method for better diagnosis, treatment, and monitoring of treatment response in these two types of dementia. From April 2015 to March 2021, the records of new referrals to a neurology clinic were retrospectively reviewed and 28 DLB(70.3% male) and 20 PDD (80.8% male) patients with appropriate EEG were selected for this study. Artifact-free 60-s EEG signals (21 channels) at rest with eyes closed were analyzed using EEGLAB, and regional spectral power ratios were extracted. Marked diffuse slowing was found in DLB patients compared to PDD patients in all regions in terms of decrease in alpha and increase in theta band. Although, these findings demean between groups after adjusting for MMSE scores, the significant difference still remained in terms of the mean relative alpha powers, particularly in the anterior and central regions. QEEG measures may have the potential to discriminate between these two syndromes. However, further prospective and longitudinal studies are required to improve the early differentiation of these dementia syndromes and to elucidate the underlying causes and pathogenesis and specific treatment.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"15500594251319863"},"PeriodicalIF":0.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rhytmic Mid-Temporal Discharges in a Mother and Daughter with Psychogenic Non-Epileptic Seizures.","authors":"Irem Erkent, Candan Gurses","doi":"10.1177/15500594251321213","DOIUrl":"https://doi.org/10.1177/15500594251321213","url":null,"abstract":"<p><p>Psychogenic non-epileptic seizures (PNES) are complex episodes that outwardly resemble epileptic seizures but are not caused by any underlying neurological disease. Unlike true epileptic seizures, PNES are more likely to be linked to psychological factors and do not show any abnormal activity on electroencephalography (EEG) recordings. This differentiation is crucial for accurate diagnosis and treatment, as misdiagnosing can lead to unnecessary treatments.Diagnosis of PNES might become difficult in the presence of particular benign EEG variants such as Rhythmic Midtemporal Discharges (RMTD). RMTD is a rare benign variant of normal EEG, characterized by rhythmic 5-7 Hz discharges in the temporal regions. This pattern could be present in normal individuals, in patients with psychiatric disorders or epilepsy. It could mimic interictal epileptiform discharges. Recognition of this pattern is essential to avoid misinterpretation of EEG findings that might eventuate in inappropriate treatment and adverse effects on a patient's medical condition, especially when there is a recent suspicious event in terms of an epileptic seizure. Among patients with PNES, the occurrence of benign variants might be much harder to interpret and physicians may mistakenly interpret RMTD on the EEG as indicative for epilepsy, especially in the absence of clear clinical criteria for PNES. This report is the first to document RMTD in first-degree relatives with PNES, suggesting a possible genetic predisposition and the need for further research into the interaction between RMTD and PNES.Our aim is to raise awareness that will enable accurate EEG reading and correct diagnosis.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"15500594251321213"},"PeriodicalIF":0.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resting-State Electroencephalogram Microstate and Correlations with Motor Function and Balance in Chronic Stroke.","authors":"Eloise de Oliveira Lima, Letícia Maria Silva, Rebeca Andrade Laurentino, Vitória Ferreira Calado, Eliene Letícia da Silva Bezerra, José Maurício Ramos de Souza Neto, José Jamacy de Almeida Ferreira, Daniel Gomes da Silva Machado, Suellen Marinho Andrade","doi":"10.1177/15500594251317751","DOIUrl":"https://doi.org/10.1177/15500594251317751","url":null,"abstract":"<p><p><b>Objective:</b> This study aimed to compare electroencephalogram microstates of patients with chronic stroke to healthy subjects and correlated microstates with clinical and functional characteristics in stroke. <b>Methods:</b> This cross-sectional, exploratory and correlational study was performed with chronic stroke patients (n = 27) and healthy subjects (n = 27) matched for age and gender. We recorded electroencephalography microstates using 32 channels during eyes-closed and eyes-open conditions and analyzed the four classic microstates maps (A, B, C, D). Post-stroke participants were assessed using the modified Rankin Scale and the Fugl-Meyer Scale. All participants were assessed for cognitive function, fear of falling, and static balance. Student's t-test was used to compare groups and Pearson's correlation coefficient was used to assess correlations between microstates parameters and stroke-related clinical outcomes. <b>Results:</b> In the eyes-open condition, moderate correlations were observed between the duration of microstate C and functional disability. In the eyes-closed condition, moderate correlations were observed between the coverage of microstate C, the occurrence of microstate C and D, and the duration of microstate B with functional aspects (eg, lower limb motor function, balance, functional disability, and fear of falling). <b>Conclusions:</b> Changes in microstates and correlations between topographies and clinical and functional aspects suggest that electroencephalogram could be used as a biomarker in stroke patients.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"15500594251317751"},"PeriodicalIF":0.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143124151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"STIT-Net- A Wavelet based Convolutional Transformer Model for Motor Imagery EEG Signal Classification in the Sensorimotor Bands.","authors":"Chrisilla S, R Shantha SelvaKumari","doi":"10.1177/15500594241312450","DOIUrl":"https://doi.org/10.1177/15500594241312450","url":null,"abstract":"<p><p>Motor Imagery (MI) electroencephalographic (EEG) signal classification is a pioneer research branch essential for mobility rehabilitation. This paper proposes an end-to-end hybrid deep network \"Spatio Temporal Inception Transformer Network (STIT-Net)\" model for MI classification. Discrete Wavelet Transform (DWT) is used to derive the alpha (8-13) Hz and beta (13-30) Hz EEG sub bands which are dominant during motor tasks to enhance the performance of the proposed work. STIT-Net employs spatial and temporal convolutions to capture spatial dependencies and temporal information and an inception block with three parallel convolutions extracts multi-level features. Then the transformer encoder with self-attention mechanism highlights the similar task. The proposed model improves the classification of the Physionet EEG motor imagery dataset with an average accuracy of 93.52% and 95.70% for binary class in the alpha and beta bands respectively, and 85.26% and 87.34% for three class, for four class 81.95% and 82.66% were obtained in the alpha and beta band respective EEG based motor signals which is better compared to the results available in the literature. The proposed methodology is further evaluated on other motor imagery datasets, both for subject-independent and cross-subject conditions, to assess the performance of the model.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"15500594241312450"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contextualised Processing of Stimuli Modulates Auditory Mismatch Responses in the Rat.","authors":"Jaishree Jalewa, Juanita Todd, Patricia T Michie, Deborah M Hodgson, Lauren Harms","doi":"10.1177/15500594241300726","DOIUrl":"10.1177/15500594241300726","url":null,"abstract":"<p><p>Mismatch negativity (MMN), an auditory prediction error signal, is an enhanced response to unexpected (deviant) stimuli compared to expected (standard) stimuli. There is strong interest in MMN due to reliable findings of reduced MMN in schizophrenia. To interpret reduced MMN in schizophrenia, an enhanced understanding of the factors that influence MMN amplitude could lead to a better understanding of neural mechanisms underpinning the reduction. While several laboratories have observed mismatch responses (MMRs) in rodents, this study assesses how MMR is altered in more complex auditory sequences in rats. Prediction-errors are elicited in relation to \"predictive\" internal models of regularities. These internal models are updated dynamically when a regularity changes, but human MMN exhibits order effects when two regularities alternate; while deviants in both regularities elicit MMN (ie, the model updates) there is a slower build-up in MMN amplitude over time in the second encountered regularity type. We investigate whether order effects occur in rat MMRs. MMRs were studied to rare ascending and descending frequency deviations in awake, freely moving Wistar rats using wireless telemetry in both separate sequences (one regularity at a time) and in alternating sequences where regularities changed back and forth. The rat MMR did not show order effects, however, substantial MMRs occurred in response to both ascending and descending deviants in the alternating context but to the ascending deviant only when the same regularities were presented separately. The longer-term sequence structure altered prediction-error signalling in rat auditory system revealing a long term context sensitivity in internal models.</p>","PeriodicalId":93940,"journal":{"name":"Clinical EEG and neuroscience","volume":" ","pages":"35-45"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142678032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}