BME frontiers最新文献

{"title":"A Review of Deep Learning Applications in Lung Ultrasound Imaging of COVID-19 Patients.","authors":"Lingyi Zhao,&nbsp;Muyinatu A Lediju Bell","doi":"10.34133/2022/9780173","DOIUrl":"https://doi.org/10.34133/2022/9780173","url":null,"abstract":"<p><p>The massive and continuous spread of COVID-19 has motivated researchers around the world to intensely explore, understand, and develop new techniques for diagnosis and treatment. Although lung ultrasound imaging is a less established approach when compared to other medical imaging modalities such as X-ray and CT, multiple studies have demonstrated its promise to diagnose COVID-19 patients. At the same time, many deep learning models have been built to improve the diagnostic efficiency of medical imaging. The integration of these initially parallel efforts has led multiple researchers to report deep learning applications in medical imaging of COVID-19 patients, most of which demonstrate the outstanding potential of deep learning to aid in the diagnosis of COVID-19. This invited review is focused on deep learning applications in lung ultrasound imaging of COVID-19 and provides a comprehensive overview of ultrasound systems utilized for data acquisition, associated datasets, deep learning models, and comparative performance.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2022 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10646829","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":"Highly Integrated Multiplexing and Buffering Electronics for Large Aperture Ultrasonic Arrays.","authors":"Robert Wodnicki, Haochen Kang, Di Li, Douglas N Stephens, Hayong Jung, Yizhe Sun, Ruimin Chen, Lai-Ming Jiang, Nestor E Cabrera-Munoz, Josquin Foiret, Qifa Zhou, Katherine W Ferrara","doi":"10.34133/2022/9870386","DOIUrl":"10.34133/2022/9870386","url":null,"abstract":"<p><p>Large aperture ultrasonic arrays can be implemented by tiling together multiple pretested modules of high-density acoustic arrays with closely integrated multiplexing and buffering electronics to form a larger aperture with high yield. These modular arrays can be used to implement large 1.75D array apertures capable of focusing in elevation for uniform slice thickness along the axial direction which can improve image contrast. An important goal for large array tiling is obtaining high yield and sensitivity while reducing extraneous image artifacts. We have been developing tileable acoustic-electric modules for the implementation of large array apertures utilizing Application Specific Integrated Circuits (ASICs) implemented using 0.35 <b><i>μ</i></b> m high voltage (50 V) CMOS. Multiple generations of ASICs have been designed and tested. The ASICs were integrated with high-density transducer arrays for acoustic testing and imaging. The modules were further interfaced to a Verasonics Vantage imaging system and were used to image industry standard ultrasound phantoms. The first-generation modules comprise ASICs with both multiplexing and buffering electronics on-chip and have demonstrated a switching artifact which was visible in the images. A second-generation ASIC design incorporates low switching injection circuits which effectively mitigate the artifacts observed with the first-generation devices. Here, we present the architecture of the two ASIC designs and module types as well imaging results that demonstrate reduction in switching artifacts for the second-generation devices.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2022 ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9357820","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":"Recent Advances in the Science of Burst Wave Lithotripsy and Ultrasonic Propulsion.","authors":"Dima Raskolnikov,&nbsp;Michael R Bailey,&nbsp;Jonathan D Harper","doi":"10.34133/2022/9847952","DOIUrl":"https://doi.org/10.34133/2022/9847952","url":null,"abstract":"<p><p>Nephrolithiasis is a common, painful condition that requires surgery in many patients whose stones do not pass spontaneously. Recent technologic advances have enabled the use of ultrasonic propulsion to reposition stones within the urinary tract, either to relieve symptoms or facilitate treatment. Burst wave lithotripsy (BWL) has emerged as a noninvasive technique to fragment stones in awake patients without significant pain or renal injury. We review the preclinical and human studies that have explored the use of these two technologies. We envision that BWL will fill an unmet need for the noninvasive treatment of patients with nephrolithiasis.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2022 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117400/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9381331","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":"Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation","authors":"Joshua Peeples, Julie F. Jameson, Nisha M Kotta, J. Grasman, W. Stoppel, A. Zare","doi":"10.1101/2021.11.22.469463","DOIUrl":"https://doi.org/10.1101/2021.11.22.469463","url":null,"abstract":"Objective We quantify adipose tissue deposition at surgical sites as a function of biomaterial implantation. Impact Statement To our knowledge, this study is the first investigation to apply convolutional neural network (CNN) models to identify and segment adipose tissue in histological images from silk fibroin biomaterial implants. Introduction When designing biomaterials for the treatment of various soft tissue injuries and diseases, one must consider the extent of adipose tissue deposition. In this work, we implant silk fibroin biomaterials in a rodent subcutaneous injury model. Current strategies for quantifying adipose tissue after biomaterial implantation are often tedious and prone to human bias during analysis. Methods We used CNN models with novel spatial histogram layer(s) that can more accurately identify and segment regions of adipose tissue in hematoxylin and eosin (H&E) and Masson’s Trichrome stained images, allowing for determination of the optimal biomaterial formulation. We compared the method, Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA), to the baseline UNET model and an extension of the baseline model, Attention UNET, as well as to versions of the models with a supplemental “attention”-inspired mechanism (JOSHUA+ and UNET+). Results The inclusion of histogram layer(s) in our models shows improved performance through qualitative and quantitative evaluation. Conclusion Our results demonstrate that the proposed methods, JOSHUA and JOSHUA+, are highly beneficial for adipose tissue identification and localization. The new histological dataset and code for our experiments are publicly available.","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81634703","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":"Three-Dimensional Shear Wave Elastography Using a 2D Row Column Addressing (RCA) Array","authors":"Zhijie Dong, Jihun Kim, Chengwu Huang, Matthew R. Lowerison, Shigao Chen, P. Song","doi":"10.1101/2021.11.10.467798","DOIUrl":"https://doi.org/10.1101/2021.11.10.467798","url":null,"abstract":"Objective To develop a 3D shear wave elastography (SWE) technique using a 2D row column addressing (RCA) array, with either external vibration or acoustic radiation force (ARF) as the shear wave source. Impact Statement The proposed method paves the way for clinical translation of 3D-SWE based on the 2D RCA, providing a low-cost and high volume-rate solution that is compatible with existing clinical systems. Introduction SWE is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness, which is significant for a wide range of clinical applications including cancer and liver fibrosis. SWE requires high frame-rate imaging for robust shear wave tracking. Due to the technical challenges associated with high volume-rate imaging in 3D, current SWE techniques are typically confined to 2D. Advancing SWE from 2D to 3D is significant because of the heterogeneous nature of tissue, which demands 3D imaging for accurate and comprehensive evaluation. Methods A 3D SWE method using a 2D RCA array was developed with a volume-rate up to 2000 Hz. The performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms. Results 3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed method. Robust 3D shear wave speed maps were reconstructed for both homogeneous and heterogeneous phantoms with inclusions. Conclusion The high volume-rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation.","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"279 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86378560","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":"A Transparent Ultrasound Array for Real-Time Optical, Ultrasound, and Photoacoustic Imaging","authors":"Haoyang Chen, S. Agrawal, Mohamed Osman, Josiah Minotto, Shubham Mirg, Jinyun Liu, Ajay Dangi, Quyen Tran, Thomas Jackson, Sri-Rajasekhar Kothapalli","doi":"10.1101/2021.11.09.467971","DOIUrl":"https://doi.org/10.1101/2021.11.09.467971","url":null,"abstract":"Objective and Impact Statement Simultaneous imaging of ultrasound and optical contrasts can help map structural, functional and molecular biomarkers inside living subjects with high spatial resolution. There is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and specificity. Introduction Currently, combining ultrasound, photoacoustic and optical imaging modalities is challenging because con-ventional ultrasound transducer arrays are optically opaque. As a result, complex geometries are used to co-align both optical and ultrasound waves in the same field of view. Methods One elegant solution is to make the ultrasound transducer transparent to light. Here, we demonstrate a novel transparent ultrasound transducer (TUT) liner array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal imaging. Results The TUT array consisted of 64 elements and centered at ∼ 6 MHz frequency. We demonstrate a quad-mode ultrasound, Doppler ultrasound, photoacoustic and fluorescence imaging in real-time using the TUT array directly coupled to the tissue mimicking phantoms. Conclusion The TUT array successfully showed a multimodal imaging capability, and has potential applications in diagnosing cancer, neuro and vascular diseases, including image-guided endoscopy and wearable imaging.","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83425455","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":"Multimodal Metabolic Imaging Reveals Pigment Reduction and Lipid Accumulation in Metastatic Melanoma.","authors":"Hyeon Jeong Lee, Zhicong Chen, Marianne Collard, Fukai Chen, Jiaji G Chen, Muzhou Wu, Rhoda M Alani, Ji-Xin Cheng","doi":"10.34133/2021/9860123","DOIUrl":"10.34133/2021/9860123","url":null,"abstract":"<p><p><i>Objective and Impact Statement</i>. Molecular signatures are needed for early diagnosis and improved treatment of metastatic melanoma. By high-resolution multimodal chemical imaging of human melanoma samples, we identify a metabolic reprogramming from pigmentation to lipid droplet (LD) accumulation in metastatic melanoma. <i>Introduction</i>. Metabolic plasticity promotes cancer survival and metastasis, which promises to serve as a prognostic marker and/or therapeutic target. However, identifying metabolic alterations has been challenged by difficulties in mapping localized metabolites with high spatial resolution. <i>Methods</i>. We developed a multimodal stimulated Raman scattering and pump-probe imaging platform. By time-domain measurement and phasor analysis, our platform allows simultaneous mapping of lipids and pigments at a subcellular level. Furthermore, we identify the sources of these metabolic signatures by tracking deuterium metabolites at a subcellular level. By validation with mass spectrometry, a specific fatty acid desaturase pathway was identified. <i>Results</i>. We identified metabolic reprogramming from a pigment-containing phenotype in low-grade melanoma to an LD-rich phenotype in metastatic melanoma. The LDs contain high levels of cholesteryl ester and unsaturated fatty acids. Elevated fatty acid uptake, but not <i>de novo</i> lipogenesis, contributes to the LD-rich phenotype. Monounsaturated sapienate, mediated by FADS2, is identified as an essential fatty acid that promotes cancer migration. Blocking such metabolic signatures effectively suppresses the migration capacity both <i>in vitro</i> and <i>in vivo</i>. <i>Conclusion</i>. By multimodal spectroscopic imaging and lipidomic analysis, the current study reveals lipid accumulation, mediated by fatty acid uptake, as a metabolic signature that can be harnessed for early diagnosis and improved treatment of metastatic melanoma.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2021 ","pages":"9860123"},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241358","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":"Label-Free White Blood Cell Classification Using Refractive Index Tomography and Deep Learning.","authors":"DongHun Ryu,&nbsp;Jinho Kim,&nbsp;Daejin Lim,&nbsp;Hyun-Seok Min,&nbsp;In Young Yoo,&nbsp;Duck Cho,&nbsp;YongKeun Park","doi":"10.34133/2021/9893804","DOIUrl":"10.34133/2021/9893804","url":null,"abstract":"<p><p><i>Objective and Impact Statement</i>. We propose a rapid and accurate blood cell identification method exploiting deep learning and label-free refractive index (RI) tomography. Our computational approach that fully utilizes tomographic information of bone marrow (BM) white blood cell (WBC) enables us to not only classify the blood cells with deep learning but also quantitatively study their morphological and biochemical properties for hematology research. <i>Introduction</i>. Conventional methods for examining blood cells, such as blood smear analysis by medical professionals and fluorescence-activated cell sorting, require significant time, costs, and domain knowledge that could affect test results. While label-free imaging techniques that use a specimen's intrinsic contrast (e.g., multiphoton and Raman microscopy) have been used to characterize blood cells, their imaging procedures and instrumentations are relatively time-consuming and complex. <i>Methods</i>. The RI tomograms of the BM WBCs are acquired via Mach-Zehnder interferometer-based tomographic microscope and classified by a 3D convolutional neural network. We test our deep learning classifier for the four types of bone marrow WBC collected from healthy donors (<math><mi>n</mi><mo>=</mo><mn>10</mn></math>): monocyte, myelocyte, B lymphocyte, and T lymphocyte. The quantitative parameters of WBC are directly obtained from the tomograms. <i>Results</i>. Our results show >99% accuracy for the binary classification of myeloids and lymphoids and >96% accuracy for the four-type classification of B and T lymphocytes, monocyte, and myelocytes. The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique. <i>Conclusion</i>. We envision that the proposed cell classification framework can be easily integrated into existing blood cell investigation workflows, providing cost-effective and rapid diagnosis for hematologic malignancy.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2021 ","pages":"9893804"},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241357","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":"Optical Detection of Distal Lung Enzyme Activity in Human Inflammatory Lung Disease.","authors":"Alicia Megia-Fernandez, Adam Marshall, Ahsan R Akram, Bethany Mills, Sunay V Chankeshwara, Emma Scholefield, Amy Miele, Bruce C McGorum, Chesney Michaels, Nathan Knighton, Tom Vercauteren, Francois Lacombe, Veronique Dentan, Annya M Bruce, Joanne Mair, Robert Hitchcock, Nik Hirani, Chris Haslett, Mark Bradley, Kevin Dhaliwal","doi":"10.34133/2021/9834163","DOIUrl":"10.34133/2021/9834163","url":null,"abstract":"<p><p><i>Objective and Impact Statement.</i> There is a need to develop platforms delineating inflammatory biology of the distal human lung. We describe a platform technology approach to detect <i>in situ</i> enzyme activity and observe drug inhibition in the distal human lung using a combination of matrix metalloproteinase (MMP) optical reporters, fibered confocal fluorescence microscopy (FCFM), and a bespoke delivery device. <i>Introduction</i>. The development of new therapeutic agents is hindered by the lack of <i>in vivo in situ</i> experimental methodologies that can rapidly evaluate the biological activity or drug-target engagement in patients. <i>Methods</i>. We optimised a novel highly quenched optical molecular reporter of enzyme activity (FIB One) and developed a translational pathway for in-human assessment. <i>Results</i>. We demonstrate the specificity for matrix metalloproteases (MMPs) 2, 9, and 13 and probe dequenching within physiological levels of MMPs and feasibility of imaging within whole lung models in preclinical settings. Subsequently, in a first-in-human exploratory experimental medicine study of patients with fibroproliferative lung disease, we demonstrate, through FCFM, the MMP activity in the alveolar space measured through FIB One fluorescence increase (with pharmacological inhibition). <i>Conclusion</i>. This translational <i>in situ</i> approach enables a new methodology to demonstrate active drug target effects of the distal lung and consequently may inform therapeutic drug development pathways.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2021 1","pages":"9834163"},"PeriodicalIF":5.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530652/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43406068","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":"Real-Time High-Resolution MRI Endoscopy at up to 10 Frames per Second.","authors":"Xiaoyang Liu,&nbsp;Parag Karmarkar,&nbsp;Dirk Voit,&nbsp;Jens Frahm,&nbsp;Clifford R Weiss,&nbsp;Dara L Kraitchman,&nbsp;Paul A Bottomley","doi":"10.34133/2021/6185616","DOIUrl":"https://doi.org/10.34133/2021/6185616","url":null,"abstract":"<p><p><i>Objective</i>. Atherosclerosis is a leading cause of mortality and morbidity. Optical endoscopy, ultrasound, and X-ray offer minimally invasive imaging assessments but have limited sensitivity for characterizing disease and therapeutic response. Magnetic resonance imaging (MRI) endoscopy is a newer idea employing tiny catheter-mounted detectors connected to the MRI scanner. It can see through vessel walls and provide soft-tissue sensitivity, but its slow imaging speed limits practical applications. Our goal is high-resolution MRI endoscopy with real-time imaging speeds comparable to existing modalities. <i>Methods</i>. Intravascular (3 mm) transmit-receive MRI endoscopes were fabricated for highly undersampled radial-projection MRI in a clinical 3-tesla MRI scanner. Iterative nonlinear reconstruction was accelerated using graphics processor units connected via a single ethernet cable to achieve true real-time endoscopy visualization at the scanner. MRI endoscopy was performed at 6-10 frames/sec and 200-300 <i>μ</i>m resolution in human arterial specimens and porcine vessels <i>ex vivo</i> and <i>in vivo</i> and compared with fully sampled 0.3 frames/sec and three-dimensional reference scans using mutual information (MI) and structural similarity (3-SSIM) indices. <i>Results</i>. High-speed MRI endoscopy at 6-10 frames/sec was consistent with fully sampled MRI endoscopy and histology, with feasibility demonstrated <i>in vivo</i> in a large animal model. A 20-30-fold speed-up vs. 0.3 frames/sec reference scans came at a cost of ~7% in MI and ~45% in 3-SSIM, with reduced motion sensitivity. <i>Conclusion</i>. High-resolution MRI endoscopy can now be performed at frame rates comparable to those of X-ray and optical endoscopy and could provide an alternative to existing modalities, with MRI's advantages of soft-tissue sensitivity and lack of ionizing radiation.</p>","PeriodicalId":72430,"journal":{"name":"BME frontiers","volume":"2021 ","pages":"6185616"},"PeriodicalIF":0.0,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241359","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}