Biosensors-Basel最新文献

{"title":"Interaction of Organic Semiconductors and Graphene Materials in the Source-Drain Channel of Field-Effect Transistors.","authors":"Eugen Chiriac, Bianca Adiaconita, Tiberiu Burinaru, Catalin Marculescu, Marius Stoian, Catalin Parvulescu, Marioara Avram","doi":"10.3390/bios15090622","DOIUrl":"10.3390/bios15090622","url":null,"abstract":"<p><p>This study investigates the interfacial interactions between two organic semiconductors (tetrathiafulvalene (TTF) and hexaazatriphenylene-hexacarbonitrile (HAT-CN)) and graphene-based materials (nanocrystalline graphite and vertically aligned graphene) used in Field-Effect Transistors (FETs). The interaction mechanisms, including π-π stacking, charge transfer, and dipole-dipole interactions, were explored through SEM imaging, Raman and FTIR spectroscopy, and FET transfer characteristics. Spectroscopic data confirmed strong π-π and charge-transfer interactions, with distinct modifications in graphene structural and electronic features. Electrical measurements revealed significant modulation of channel conductivity, confirming effective surface functionalization. These findings provide a framework for engineering high-performance organic/graphene hybrid interfaces in electronic devices and biosensors. Importantly, the results demonstrate that molecular design and interfacial control at the nanoscale can be strategically used to modulate charge transport in graphene-based FETs. This approach opens new pathways for developing tunable, molecule-specific biosensors and nanoelectronic platforms with enhanced sensitivity and selectivity.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Haptens Optimization Using Molecular Modeling and Paper-Based Immunosensor for On-Site Detection of Carbendazim in Vegetable Products.","authors":"Wenjing Chen, Zhuzeyang Yuan, Kangliang Pan, Yu Wang, Xiaoqin Yu, Tian Guan, Jiahong Chen, Hongtao Lei","doi":"10.3390/bios15090625","DOIUrl":"10.3390/bios15090625","url":null,"abstract":"<p><p>Carbendazim is a benzimidazole fungicide widely used in the prevention and control of vegetable diseases. However, if misused, it may result in residues in agricultural products, not only reducing vegetable quality but also posing potential risks to human health. Currently, the on-site rapid detection technology for carbendazim still faces challenges, including insufficient antibody specificity and low sensitivity, which hinder its ability to meet practical regulatory requirements. Therefore, this study screened a rational hapten structure by applying a computer-aided hapten design and obtained a specific antibody. Compared to previous studies, the cross-reactivity rate of the antibody with thiabendazole-methyl was less than 0.1%, and the cross-reactivity rate with 2-aminobenzimidazole was 52.7% lower than that of the existing reported antibodies, which significantly improved the detection specificity of the method. Based on a high-specificity antibody, a gold nanoparticle-based lateral flow immunoassay (AuNPs-LFIA) for carbendazim was established. The detection limits of green beans and leeks are 3.80 μg/kg and 1.80 μg/kg, respectively, which still maintain high specificity in complex samples. Good agreement was also demonstrated between the results of blind samples detected by AuNPs-LFIA and LC-MS/MS, respectively. The establishment of AuNPs-LFIA provides an effective solution for the rapid and specific detection of carbendazim.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Possible Use of the SUDOSCAN Nephropathy Risk Score in Chronic Kidney Disease Diagnosis: Application in Patients with Type 2 Diabetes.","authors":"Claudiu Cobuz, Mădălina Ungureanu-Iuga, Dana-Teodora Anton-Paduraru, Maricela Cobuz","doi":"10.3390/bios15090620","DOIUrl":"10.3390/bios15090620","url":null,"abstract":"<p><p>The use of quick and non-invasive techniques for detecting chronic kidney disease (CKD) in patients with type 2 diabetes mellitus is desirable and has recently garnered attention. One of these techniques is the evaluation of nephropathy risk based on electrochemical skin conductance (ESC) measured with a SUDOSCAN device. This paper aims to evaluate the possibility of using SUDOSCANs in chronic kidney disease prediction in diabetic patients and to investigate the relationships between clinical characteristics and SUDOSCAN parameters. The number of patients with type 2 diabetes included in this study was 254. Clinical metabolic characteristics like glycated hemoglobin, total and LDL cholesterol, triglyceride, blood pressure, and creatinine were determined along with body mass index, diabetes duration, and age. The estimated glomerular filtration rate (EGFR) was calculated and patients were grouped into three CKD stages based on EGFR values. Electrochemical skin conductance in hands and feet was determined with a SUDOSCAN device. The results showed that patients with symptomatic CKD (S2 and 3) presented lower ESC values, along with lower EFGRs and higher creatinine levels. A significant positive but weak correlation (<i>p</i> < 0.05) was observed between SUDOSCAN nephropathy risk and EGFR. The general linear model indicated that the SUDOSCAN nephropathy risk score could be used in CKD diagnosis only if considering age, diabetes duration, and body mass index. The area under the curve (AUC) of the receiver operating characteristic (ROC) analysis revealed the moderate possibility of using the SUDOSCAN nephropathy risk score to predict CKD, since it was 0.61 (<i>p</i> < 0.01, 95% CI 0.54-0.68), but only if the other factors mentioned above are included. Based on the cut-off value of 59.50 identified, patients were grouped (values above and below cut-off), and the results showed that patients with a SUDOSCAN nephropathy risk score of <59.50 have lower SUDOSCAN-ESC values measured in their hands and feet, lower EGFR and higher creatinine levels. These results indicated the possibility of using SUDOSCAN as a supporting tool to identify CKD if it is correlated with other factors like age, diabetes duration, and body mass index. This is important for medical progress regarding the use of novel non-invasive technologies in identifying CKD associated with type 2 diabetes.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Evaluation of Combined Denoising and Resolution Enhancement Algorithms for Intravital Two-Photon Imaging of Organs.","authors":"Saeed Bohlooli Darian, Woo June Choi, Jeongmin Oh, Jun Ki Kim","doi":"10.3390/bios15090616","DOIUrl":"10.3390/bios15090616","url":null,"abstract":"<p><p>Intravital two-photon microscopy enables deep-tissue imaging of subcellular structures in live animals, but its original spatial resolution and image quality are limited by scattering, motion, and low signal-to-noise ratios. To address these challenges, we used a combination of tissue stabilization, denoising methods, and motion correction, together with resolution enhancement algorithms, including enhanced Super-Resolution Radial Fluctuations (eSRRF) and deconvolution, to acquire high-fidelity time-lapse images of internal organs. We applied this imaging pipeline to image genetically labeled mitochondria in vivo, in Dendra2 mice. Our results demonstrate that the eSRRF-combined method, compared to other evaluated algorithms, significantly shows improved spatial resolution and mitochondrial structure visualization, while each method exhibiting distinct strengths in terms of noise tolerance, edge preservation, and computational efficiency. These findings provide a practical framework for selecting enhancement strategies in intravital imaging studies targeting dynamic subcellular processes.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D Printing Assisted Wearable and Implantable Biosensors.","authors":"Somnath Maji, Myounggyu Kwak, Reetesh Kumar, Hyungseok Lee","doi":"10.3390/bios15090619","DOIUrl":"10.3390/bios15090619","url":null,"abstract":"<p><p>Biosensors have undergone transformative advancements, evolving into sophisticated wearable and implantable devices capable of real-time health monitoring. Traditional manufacturing methods, however, face limitations in scalability, cost, and design complexity, particularly for miniaturized, multifunctional biosensors. The integration of 3D printing technology addresses these challenges by enabling rapid prototyping, customization, and the production of intricate geometries with high precision. This review explores how additive manufacturing techniques facilitate the fabrication of flexible, stretchable, and biocompatible biosensors. By incorporating advanced materials like conductive polymers, nanocomposites, and hydrogels, 3D-printed biosensors achieve enhanced sensitivity, durability, and seamless integration with biological systems. Innovations such as biodegradable substrates and multi-material printing further expand applications in continuous glucose monitoring, neural interfaces, and point-of-care diagnostics. Despite challenges in material optimization and regulatory standardization, the convergence of 3D printing with nanotechnology and smart diagnostics heralds a new era of personalized, proactive healthcare, offering scalable solutions for both clinical and remote settings. This synthesis underscores the pivotal role of additive manufacturing in advancing wearable and implantable biosensor technology, paving the way for next-generation devices that prioritize patient-specific care and real-time health management.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12468503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitive and Selective Electrochemical Detection of Hydrogen Peroxide Using a Silver-Incorporated CeO₂/Ag₂O Nanocomposite.","authors":"Gunasekaran Manibalan, Govindhasamy Murugadoss, Dharmalingam Krishnamoorthy, Venkataraman Dharuman, Shaik Gouse Peera","doi":"10.3390/bios15090617","DOIUrl":"10.3390/bios15090617","url":null,"abstract":"<p><p>Precision and real-time detection of hydrogen peroxide (H₂O₂) are essential in pharmaceutical, industrial, and defence sectors due to its strong oxidizing nature. In this study, silver (Ag)-doped CeO₂/Ag₂O-modified glassy carbon electrode (Ag-CeO₂/Ag₂O/GCE) has been developed as a non-enzymatic electrochemical sensor for the sensitive and selective detection of H₂O₂. The synthesized Ag-doped CeO₂/Ag₂O nanocomposite was characterized using various advanced techniques, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), field-emission scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscopy (HR-TEM). Their optical, magnetic, thermal, and chemical properties were further analyzed using UV-vis spectroscopy, electron paramagnetic resonance (EPR), thermogravimetric-differential thermal analysis (TG-DTA), and X-ray photoelectron spectroscopy (XPS). Electrochemical sensing performance was evaluated using cyclic voltammetry and amperometry. The Ag-CeO₂/Ag₂O/GCE exhibited superior electrocatalytic activity for H₂O₂, attributed to the increased number of active sites and enhanced electron transfer. The sensor displayed a high sensitivity of 2.728 µA cm^-2 µM^-1, significantly outperforming the undoped CeO₂/GCE (0.0404 µA cm^-2 µM^-1). The limit of detection (LOD) and limit of quantification (LOQ) were found to be 6.34 µM and 21.1 µM, respectively, within a broad linear detection range of 1 × 10^-8 to 0.5 × 10^-3 M. The sensor also demonstrated excellent selectivity with minimal interference from common analytes, along with outstanding storage stability, reproducibility, and repeatability. Owing to these attributes, the Ag-CeO₂/Ag₂O/GCE sensor proved effective for real sample analysis, showcasing its potential as a reliable, non-enzymatic platform for H₂O₂ detection.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding Molecular Network Dynamics in Cells: Advances in Multiplexed Live Imaging of Fluorescent Biosensors.","authors":"Qiaowen Chen, Yichu Xu, Jhen-Wei Wu, Jr-Ming Yang, Chuan-Hsiang Huang","doi":"10.3390/bios15090614","DOIUrl":"10.3390/bios15090614","url":null,"abstract":"<p><p>Genetically encoded fluorescent protein (FP)-based biosensors have revolutionized cell biology research by enabling real-time monitoring of molecular activities in live cells with exceptional spatial and temporal resolution. Multiplexed biosensing advances this capability by allowing the simultaneous tracking of multiple signaling pathways to uncover network interactions and dynamic coordination. However, challenges in spectral overlap limit broader implementation. Innovative strategies have been devised to address these challenges, including spectral separation through FP palette expansion and novel biosensor designs, temporal differentiation using photochromic or reversibly switching FPs, and spatial segregation of biosensors to specific subcellular regions or through cell barcoding techniques. Combining multiplexed biosensors with artificial intelligence-driven analysis holds great potential for uncovering cellular decision-making processes. Continued innovation in this field will deepen our understanding of molecular networks in cells, with implications for both fundamental biology and therapeutic development.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pancreatic Lipase in Eutectogels as Emerging Materials: Exploring Their Properties and Potential Applications in Biosensing.","authors":"Raúl Martínez-Baquero, María José Martínez-Tomé, Javier Gómez, Rocío Esquembre, C Reyes Mateo","doi":"10.3390/bios15090615","DOIUrl":"10.3390/bios15090615","url":null,"abstract":"<p><p>Eutectogels are advanced gel-based systems that integrate deep eutectic solvents (DES) into polymer networks. In this study, we report the first detailed characterization of an enzyme-containing eutectogel, representing a significant step toward advanced biosensing and biocatalytic applications. Specifically, we have incorporated pancreatic lipase, one of the main target enzymes in the treatment of obesity, in eutectogels via UV-induced radical polymerization of suitable precursors in appropriate DESs. Prior to immobilization, the enzyme was solubilized in selected DESs and its activity and conformational stability were evaluated using colorimetry and intrinsic fluorescence. Combinations of choline chloride/glycerol and tetramethylammonium chloride/glycerol were shown to be effective media for preserving and enhancing enzymatic function and conformational stability. The enzyme immersed in eutectogel exhibited high structural integrity and excellent thermal stability, maintaining its activity over several weeks. The ability of this new material to screen enzyme inhibitors was assessed using orlistat, a well-established anti-obesity agent. The results demonstrated clear detection of the drug's inhibitory effect, even at nanomolar concentrations, highlighting the material's potential as a screening platform for novel inhibitors with prospective anti-obesity activity. Furthermore, the device proved effective in quantifying drug presence, offering a promising and highly sensitive tool for pharmaceutical quality control applications.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning-Based Framework for Pre-Impact Same-Level Fall and Fall-from-Height Detection in Construction Sites Using a Single Wearable Inertial Measurement Unit.","authors":"Oleksandr Yuhai, Yubin Cho, Joung Hwan Mun","doi":"10.3390/bios15090618","DOIUrl":"10.3390/bios15090618","url":null,"abstract":"<p><p>Same-level-falls (SLFs) and falls-from-height (FFHs) remain major causes of severe injuries and fatalities on construction sites. Researchers are actively developing fall-prevention systems requiring accurate SLF and FFH detection in construction settings prone to false positives. In this study, a machine learning-based approach was established for accurate identification of SLF, FFH, and non-fall events using a single waist-mounted inertial measurement unit (IMU). A total of 48 participants executed 39 non-fall activities, 10 types of SLFs, and 8 types of FFHs, with a dummy used for falls exceeding 0.5 m. A two-stage feature extraction yielded 168 descriptors per data window, and an ensemble SHAP-PFI method selected the 153 most informative variables. The weighted XGBoost classifier, optimized via Bayesian techniques, outperformed other current boosting algorithms. Using 5-fold cross-validation, it achieved an average macro F1-score of 0.901 and macro Matthews correlation coefficient of 0.869, with a latency of 1.51 × 10^-3 ms per window. Notably, the average lead times were 402 ms for SLFs and 640 ms for FFHs, surpassing the 130 ms inflation time required for wearable airbags. This pre-impact SLF and FFH detection approach delivers both rapid and precise detection, positioning it as a viable central component for wearable fall-prevention devices in fast-paced construction scenarios.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration and Analysis of GaN-Based FETs with Varied Doping Concentration in Nano Regime for Biosensing Application.","authors":"Abhishek Saha, Sneha Singh, Rudra Sankar Dhar, Kajjwal Ghosh, A Y Seteikin, Amit Banerjee, I G Samusev","doi":"10.3390/bios15090613","DOIUrl":"10.3390/bios15090613","url":null,"abstract":"<p><p>This study conducts a comprehensive examination of a GaN channel-based nanobiosensor featuring a dielectrically modulated trigate FinFET structure, incorporating both uniform and Gaussian channel doping. The proposed device incorporates a nanocavity structure situated beneath the gate region, intended for the analysis of diverse biomolecules in biosensing applications. The proposed biosensor employs HfO₂ as the gate dielectric, characterized by a dielectric constant of 25, leading to an enhanced switching ratio for the device. This study examines the electrical properties relevant to biomolecule identification, including the switching ratio, DIBL, threshold swing, threshold voltage, and transconductance. The sensitivity of these properties concerning the drain current is subsequently assessed. Enhanced sensitivity increases the likelihood of detecting biomolecules. The electrical property of a biomolecule is examined in the absence of another biomolecule within the cavity. The apparatus is designed to detect neutral biomolecules. Simultaneously, further investigational research has been undertaken regarding the linearity behavior of GAA FET, nanobiosensors, and dielectrically modulated TGFinFET. This study's results have been compared with those of GaN-based FinFET and GaN SOI FinFET technologies. The data indicates approximately ∼103% and ∼42% improvements in <i>I</i>_<i>OFF</i> and Switching ratio, respectively, when compared to IRDS 2025. The nanobiosensor (GAA FET) demonstrates enhanced linear performance concerning higher-order voltage and current intercept points, including VIP2, VIP3, IIP3, and P1dB.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 9","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467650/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}