Technology and Health Care最新文献

{"title":"Cancer-associated fibroblasts derived-exosomal circ_0076535 promotes esophageal squamous cell carcinoma progression.","authors":"Ningning Kang, Wei Ge, Jinxiu Hu, Yuan Zhao, Hao Zheng, Xuan Lu","doi":"10.1177/09287329241291432","DOIUrl":"https://doi.org/10.1177/09287329241291432","url":null,"abstract":"<p><p>BackgroundEsophageal cancer (EC) is a common malignant tumor of the digestive tract and an important health-related problem in many developing countries. Esophageal squamous cell carcinoma (ESCC) is the most common subtype of EC. The cancer-associated fibroblasts (CAFs) are the major stromal cells in ESCC microenvironment. They play important role in ESCC proliferation, metastasis, angiogenesis and chemotherapy resistance through paracrine processes. However, the roles of circRNAs enriched in CAF-derived exosmes have not been reported.ObjectiveTo explore the mechanisms of how CAF affects ESCC proliferation and metastasis through paracrine processes and to investigate the role of circRNAs enriched in CAF-derived exosomes.MethodsExosomes were isolated from the conditional medium of CAF using differential ultracentrifugation, and then validated by Nanosight analysis. Exosome secretion inhibitor-GW4869 validates the pro-carcinogenic role of exosomes. The qRT-PCR showed the highest expression of circ_0076535 in the exosomal CircRNA, and knockdown of it confirmed its function. Online bioinformatics tool was utilized to predict the potential target gene of circ_0076535, and captured miR-145-5p as the target gene with high predictive value. The targeting association between miR-145-5p and circ_0076535 is further confirmed by the dual luciferase reporter experiment. The stimulation of tumour development and EMT by the CAF-derived exosome circ_0076535 is further validated <i>in vivo.</i>ResultsIn our research, we found that CAF-derived exosomes increased proliferation, migration, invasion and EMT in ESCC cells. Circ_0076535 was highly enriched in CAF-exosomes and transferred into ESCC cells directly depend on internalization of exosomes. CAF-exosomal circ_0076535 increased the level of circ_0076535 in ESCC cells and induced EMT. Mechanistic experiments revealed circ_0076535 acted as a sponge to absorb miR-145-5p and activated NF-κB signaling pathway.<b>Conclusions:</b> Conclusively, CAF-exosomal circ_0076535 promoted the ESCC progression via miR-145-5p/NF-κB axis and expected to be a potential biomarker for early diagnosis and treatment of ESCC.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"1088-1098"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659470","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":"Clinical characteristics and prognostic analysis of patients with SMARCA4-deficient lung cancer.","authors":"Lingling Xu, Xianquan Xu, Pengfei Wu, Wei Ye, Jieting Zhao, Jingwen Yang, Yuanyuan Yao, Maoxi Chen, Xiaoyan Wang, Anbang Wang, Yanbo Fan","doi":"10.1177/09287329241296242","DOIUrl":"https://doi.org/10.1177/09287329241296242","url":null,"abstract":"<p><p>BackgroundSMARCA4-deficient NSCLC is a rare type of tumor, accounting for approximately 10% of all NSCLC. It exhibits a weak response to conventional chemotherapy and has a poor prognosis, and lacks alterations in EGFR (epidermal growth factor receptor), ALK (anaplastic lymphoma kinase), and ROS1 (ROS proto-oncogene 1) genes Therefore, the mechanisms of SMARCA4 in NSCLC development urgently need to be explored to identify novel biomarkers and precise therapeutic strategies for this subtype.ObjectiveThe aim of this study was to understand the clinical characteristics of this special type of tumor and its response to different treatments.MethodsWe collected clinical data from 42 patients with SMARCA4-deficient NSCLC from July 2022 to January 2024, and analyzed their clinical features and survival state.ResultsThe study included a total of 42 patients diagnosed with NSCLC and harboring SMARCA4 mutation. The majority of these patients were male with a median age of 67 years. Most patients presented at stage IV upon diagnosis with highly aggressive tumors characterized by high Ki-67 proliferation index values resulting in poor overall prognosis. Genetic testing revealed TP53 gene mutations to be most prevalent (21%), followed by KRAS mutations (13%). Patients receiving immunotherapy exhibited significantly longer median overall survival compared to those treated solely with chemotherapy. Targeted drug therapy demonstrated favorable effects in some patients.ConclusionNSCLC patients harboring SMARCA4 deficiency exhibit poor overall survival rates with a median overall survival time of 5.4 months. Immunotherapy may provide benefits for NSCLC patients with SMARCA4 deficiency.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"1014-1020"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659472","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":"Developing a method for predicting DNA nucleosomal sequences using deep learning.","authors":"Nizal Alshammry","doi":"10.1177/09287329241297900","DOIUrl":"https://doi.org/10.1177/09287329241297900","url":null,"abstract":"<p><p>BackgroundDeep learning excels at processing raw data because it automatically extracts and classifies high-level features. Despite biology's low popularity in data analysis, incorporating computer technology can improve biological research.ObjectiveTo create a deep learning model that can identify nucleosomes from nucleotide sequences and to show that simpler models outperform more complicated ones in solving biological challenges.MethodsA classifier was created utilising deep learning and machine learning approaches. The final model consists of two convolutional layers, one max pooling layer, two fully connected layers, and a dropout regularisation layer. This structure was chosen on the basis of the 'less is frequently more' approach, which emphasises simple design without large hidden layers.ResultsExperimental results show that deep learning methods, specifically deep neural networks, outperform typical machine learning algorithms for recognising nucleosomes. The simplified network architecture proved suitable without the requirement for numerous hidden neurons, resulting in effective network performance.ConclusionThis study demonstrates that machine learning and other computational techniques may streamline and expedite the resolution of biological issues. The model helps identify nucleosomes and can be used in future research or labs. This study discusses the challenges of understanding and addressing simple biological problems with sophisticated computer technology and offers practical solutions for academic and economic sectors.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"989-999"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659492","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":"Automated arrhythmia classification based on a pyramid dense connectivity layer and BiLSTM.","authors":"Xiangkui Wan, Xiaoyu Mei, Yunfan Chen, Jieqiang Luo, Luguo Hao","doi":"10.1177/09287329241290941","DOIUrl":"10.1177/09287329241290941","url":null,"abstract":"<p><p>BackgroundDeep neural networks (DNNs) have recently been significantly applied to automatic arrhythmia classification. However, their classification accuracy still has room for improvement.ObjectivesThe aim of this study is to address the existing limitations in current models by developing a more effective approach for automatic arrhythmia classification. The specific objectives include enhancing the receptive field sizes to capture more detailed information across various temporal scales, and incorporating inter-channel correlations to improve the feature extraction process.MethodsThis study proposes a pyramidal dense connectivity layer and bidirectional long short-term memory network (PDC-BiLSTM) to effectively extract waveform features across various temporal scales, which can capture the intricate details and the broader global information in the signals through a wide range of sensory fields. The efficient channel attention (ECA) is additionally introduced to dynamically allocate weights to each feature channel, assisting the model inefficiently prioritizing essential characteristics during the training process.ResultsThe experimental results on the MIT-BIH arrhythmia database showed that the overall classification accuracy of the proposed method under the intra-patient paradigm reached 99.82%, and the positive predictive value, sensitivity and F1 Score were 99.64%, 97.61% and 98.60% respectively; under the inter-patient paradigm, the overall accuracy was 96.30%.ConclusionCompared with the latest research results in this field, the proposed model is also better than the existing models in terms of accuracy, which has the potential value of being applied to devices that assist in diagnosing cardiovascular diseases.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"797-813"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460153","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":"Application of 3D visualization virtual surgery system in percutaneous transforaminal endoscopic discectomy.","authors":"Chen Gong, Min Zhang, Jianming Wu, Zhiwei Shi, Xiangyang Liu, Yahui Niu","doi":"10.1177/09287329241290908","DOIUrl":"10.1177/09287329241290908","url":null,"abstract":"<p><p>BackgroundPercutaneous transforaminal endoscopic discectomy (PTED) is an effective minimally invasive technique for treating lumbar disc herniation (LDH). However, precise channel establishment remains challenging. A three-dimensional visualization virtual surgery system (3DVVSS) is increasingly used in specific surgeries, yet its value in PTED remains uncertain.ObjectiveTo investigate the application of a 3DVVSS combined with a self-made intervertebral foramen positioning puncture device (IFPPD) in PTED for the treatment of LDH.MethodsThis study enrolled 120 LDH patients who underwent PTED between January 2021 and February 2022. Patients were randomly assigned to 3DVVSS combined with the IFPPD group (V group), and the traditional freehand methods group (T group). Hospitalization days, number of puncture attempts, fluoroscopy time, operation time, visual analog scale (VAS), Oswestry disability index (ODI), and complications were analyzed.ResultsAll patients completed follow-up without serious complications. Hospitalization days between the two groups were comparable (<i>p</i> > 0.05). However, the V group showed statistically significant advantages over the T group in puncture time, number of puncture attempts, fluoroscopy times, and operation time (<i>p</i> < 0.05). All patients exhibited significant improvements in VAS and ODI compared to those of preoperation (<i>p</i> < 0.05). Still, there was no significant difference in VAS and ODI between T and V groups (<i>p</i> > 0.05).Conclusion3DVVSS combined with IFPPD can significantly improve the successful puncture rate, and reduce the operation time and the fluoroscopy times, indicating its great potential in future clinical applications.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"744-754"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460216","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":"Detection of motor nervous disease using deep learning based Duple feature extraction network.","authors":"Sony Helen S, Joseph Jawhar S","doi":"10.1177/09287329241291367","DOIUrl":"https://doi.org/10.1177/09287329241291367","url":null,"abstract":"<p><p>BackgroundA motor nervous disease (MND) is a debilitating nervous disease that affects motor neurons that regulates the muscular voluntary movements. The disease gradually destroys parts of the neurological system. Generally, MND develops owing to a grouping of genetic, behavioural, and natural features.ObjectiveHowever, early detection of MND is challenging and manual identification requires a lot of time. Therefore, automated methods like deep learning structures are needed to detect MND quickly and more accurately than manual classification. In this work, a novel deep learning-based Duple feature extraction network is proposed for identifying MND in its early stages.MethodsInitially, the input DTI images are pre-processed utilizing a Gaussian adaptive bilateral filter (GAB) to improve the quality of the image. Then the pre-processed DTI images are fed into the dual feature extraction phase for colour and structural conversion. The Colour Information Feature (CIF) with Local and Global sampling (LOG) is integrated into the LinkNet module to extract colour features. Moreover, the Local Binary Pattern (LBP) with Edge sampling models is integrated into the MobileNet module to extract edge features. Afterward, the extracted colour and texture features of images are flattered and given as the input to a Deep Neural Network for classifying the MND levels.ResultsFrom the test results, the proposed Duple feature extraction network has yielded a 99.62% accuracy rate. The proposed DNN improves its F1-score by 1.32%, 2.1%, and 3.18% better than FNN, GNN, and GRU respectively. The proposed Duple-feature extraction network improves overall accuracy by 6.15%, 5.56%, 5.96%, and 6.68% compared to CNN, SVM-RFE, MLP, and Tri-planar CNN respectively.ConclusionThe novel deep learning-based Duple feature extraction framework shows promising results in early detection of motor nervous disease, significantly improving accuracy and f1-scores compared to existing models.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"877-894"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659485","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":"The impact of high-intensity interval training on insulin sensitivity and quality of life in women with overweight polycystic ovary syndrome.","authors":"Ling Jiang, Yaxin Chen, Meiying Huang","doi":"10.1177/09287329241296228","DOIUrl":"https://doi.org/10.1177/09287329241296228","url":null,"abstract":"<p><p>BackgroundPolycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women of reproductive age, characterized by menstrual irregularities, hyperandrogenism, and polycystic ovaries. Insulin resistance is central to its pathophysiology, contributing to metabolic disturbances and increased cardiometabolic risks. High-Intensity Interval Training (HIIT) has emerged as a promising intervention to improve metabolic health.ObjectiveThis study aimed to investigate the specific effects of HIIT on insulin sensitivity, body composition, metabolic profile, and quality of life in women with overweight PCOS.MethodsA retrospective analysis was conducted on 107 female patients with overweight PCOS who were divided into two groups: the Regular Interval Training Group (n = 54) and the HIIT Group (n = 53). Baseline data, including insulin sensitivity, glucose metabolism, body composition, metabolic profile, and quality of life, were measured and compared between the two groups.ResultsThe HIIT Group demonstrated significantly improved insulin sensitivity, reduced fasting glucose levels, lower HOMA-IR index, lower body fat percentage, decreased waist and hip circumferences, improved favorable changes in metabolic profile, and significant improvements in quality of life compared to the Regular Interval Training Group. These findings suggest that HIIT led to beneficial outcomes across various metabolic and clinical parameters in women with overweight PCOS.ConclusionThe findings of this study highlight the potential of personalized exercise prescriptions, such as HIIT, in optimizing health outcomes in women with overweight PCOS. The observed improvements in insulin sensitivity, body composition, metabolic profile, and quality of life underscore the promising role of HIIT in addressing the multifaceted implications of PCOS and its associated metabolic and reproductive implications.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"1038-1045"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659345","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":"Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Patient monitors case study.","authors":"Faruk Bećirović, Lemana Spahić, Nejra Merdović, Lejla Gurbeta Pokvić, Almir Badnjević","doi":"10.1177/09287329241291424","DOIUrl":"https://doi.org/10.1177/09287329241291424","url":null,"abstract":"<p><p>BackgroundHealthcare institutions throughout the world rely on medical devices to provide their services reliably and effectively. However, medical devices can, and do sometimes fail. These failures pose significant risk to patients.ObjectiveOne way to address these issues is through the use of artificial intelligence for the detection of medical device failure. This goal of this study was to develop automated systems utilising machine learning algorithms to predict patient monitor performance and potential failures based on data collected during regular safety and performance inspections.MethodsThe system developed in this study utilised machine learning techniques as its core. Throughout the study four algorithms were utilised. These algorithms include Decision Tree, Random Forest, Linear Regression and Support Vector Machines.ResultsFinal results showed that Random Forest algorithms had the best performance on various metrics among the four developed models. It achieved accuracy of 94% and precision and recall of 70% and 93% respectively.ConclusionThis study shows that use of systems like the one developed in this study have the potential to improve management and maintenance of medical devices.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":"33 2","pages":"974-980"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659443","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":"Research progress on influencing factors and intervention measures of pre-hospital delays in acute ischemic stroke.","authors":"Liming Shi, Muqun Xu, Qingjie Su","doi":"10.1177/09287329241296739","DOIUrl":"10.1177/09287329241296739","url":null,"abstract":"<p><p>BackgroundStroke, a leading cause of health impairment globally, sees intravenous thrombolysis as the primary treatment during the acute phase, yet delays persist due to pre-hospital and in-hospital factors. While research has reduced in-hospital delays significantly, pre-hospital delays remain a concern both domestically and internationally.ObjectiveThis article aims to provide a comprehensive review of the research progress on the influencing factors and intervention measures of pre-hospital delays in acute ischemic stroke.MethodsBy analyzing the literature, summarize the risk factors leading to treatment delay in acute ischemic stroke (AIS), and provide a review of potential improvement methods.ResultsPre-hospital delay in acute ischemic stroke (AIS) is influenced by both objective factors like age, gender, and regional economic status, as well as subjective factors such as stroke awareness. The introduction of \"Stroke 120,\" a stroke education slogan tailored to Chinese language habits, aims to improve stroke awareness and address delayed treatment and low AIS venous thrombolysis utilization among the Chinese publicConclusionIn conclusion, collaborative efforts from the government, society, and hospitals are essential to enhance stroke education comprehensively. This will ensure widespread awareness of stroke knowledge, facilitating timely and effective treatment for AIS patients.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"1121-1127"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460252","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":"MRI manifestations and quantitative parameters of fat pad PDW-SPAIR in patients with knee osteoarthritis and their predictive value.","authors":"Yanan He, Yaoqu Huang, Chuying Chen, Lilei Yi, Shouguo Zhou, Juan Wang","doi":"10.1177/09287329241296227","DOIUrl":"10.1177/09287329241296227","url":null,"abstract":"<p><p>BackgroundKnee osteoarthritis (KOA) is a degenerative joint disease characterized by the breakdown of cartilage and underlying bone, often leading to pain and stiffness. There is limited research on the correlation between magnetic resonance imaging (MRI) manifestations and changes in quantitative parameters of the proton density-weighted spectral attenuated inversion recovery (PDW-SPAIR) sequence in the fat pad of KOA patients.ObjectiveTo investigate the MRI manifestations and quantitative parameters of fat pad PDW-SPAIR in patients with KOA and their predictive value.Methods82 patients with KOA admitted to the hospital from January 2023 to January 2024 were selected as the study subjects. All of them received an MRI examination before the operation. Their MRI manifestations and quantitative parameters of fat pad PDW-SPAIR were analyzed to evaluate their application value in patients with KOA.ResultsAmong the 82 patients, there were 25 cases of bony defects, 43 cases of cartilage defects, and 14 cases of hydrops articuli. There were 63 cases of bone marrow edema, 54 cases of soft tissue swelling, 68 cases of synovitis, and 42 cases of bone erosion. Different quantitative parameters of fat pad PDW-SPAIR showed that patients with cartilage defects were 50, 53, 32, and 32. Cartilage defects were 130, 131, 53, and 49. There were statistically significant differences in signal intensity ratios of non-cartilage and cartilage defects displayed by different quantitative parameters of fat pad PDW-SPAIR (p < 0.05). Spearman correlation analysis showed that PD-FSE-SAG-SPAIR, PD-FSE-COR-SPAIR, T2-FSE-SAG, and T1-FSE-COR positively correlated with KOA (p < 0.05).ConclusionMRI manifestations and quantitative parameters of fat pad PDW-SPAIR may be helpful for the clinical prediction of KOA.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"762-767"},"PeriodicalIF":1.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460309","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}