Medical Engineering & Physics最新文献

{"title":"The influence of boiling bubble on the acoustic field and bubble dynamics in histotripsy: A numerical investigation","authors":"Ting Li ,&nbsp;Yufeng Zhou","doi":"10.1016/j.medengphy.2025.104367","DOIUrl":"10.1016/j.medengphy.2025.104367","url":null,"abstract":"<div><div>Boiling histotripsy (BH) is a non-invasive treatment technique that leverages cavitation effects to disintegrate soft tissue. However, the influence of boiling bubble on the acoustic field and bubble dynamics, which are key mechanisms underlying tissue destruction in BH, is not yet fully understood. This study aims to elucidate the acoustic field distribution and dynamics of a single bubble, demonstrate the generation of intrinsic cavitation bubbles, and predict the associated cavitation damage using a numerical model. The Westervelt equation was employed to simulate the nonlinear propagation of ultrasound pulses in biological tissues, considering varying boiling bubble sizes at the focus and initial acoustic pressures on the transducer surface. Moreover, the Keller-Miksis equation model, combined with the Voigt model, was used to simulate the nonlinear oscillation of bubbles. The presence of a boiling bubble results in significant acoustic reflection at the bubble interface, particularly a notably strong negative pressure. Simulation results show that intrinsic cavitation occurs in a bubble radius of 0.4 mm at an initial acoustic pressure of 2 MPa. Increasing the boiling bubble radius to 1.1 mm leads to the extension of cavitation bubbles toward the second layer of the standing wave field. Additionally, the initial acoustic pressure seems to influence intrinsic cavitation more significantly than the boiling bubble radius. Bubble dynamics, including its maximum bubble radii and expansion duration, is significantly affected by the rarefactional wave. This effect is attributed not only to the peak negative pressure but also to the waveform. In conclusion, the presence of a boiling bubble at the focus substantially modifies the acoustic field distribution, the formation of intrinsic cavitation clouds, and the characteristics of bubble dynamics. The boiling bubble radius and the initial acoustic pressure on the transducer surface are critical factors in modifying cavitation-associated tissue fractionation. Appropriate parameter settings for ultrasonic pulses may enhance the efficacy and reduce the potential complications in BH treatment.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104367"},"PeriodicalIF":1.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147850","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":"Novel fusion-based time-frequency analysis for early prediction of sudden cardiac death from electrocardiogram signals","authors":"Shaik Karimulla,&nbsp;Dipti Patra","doi":"10.1016/j.medengphy.2025.104370","DOIUrl":"10.1016/j.medengphy.2025.104370","url":null,"abstract":"<div><div>Sudden cardiac death (SCD) is one of the leading causes of global mortality, often occurring without warning and driven by complex cardiac dynamics. Despite significant advances in cardiovascular diagnostics, accurately predicting SCD at an early stage remains a critical challenge. This study proposes a novel fusion-based time-frequency (T-F) deep learning framework for the early prediction of SCD by classifying associated cardiac conditions. Electrocardiogram (ECG) signals were first denoised and segmented to isolate clinically relevant patterns. These signals were then transformed into two-dimensional T-F representations using spectrograms and scalograms, capturing complementary temporal and spectral information. An average fusion technique merged these representations, enriching T-F images with enhanced discriminatory power. The fused images were used to train deep learning (DL) models, and performance was evaluated using subject-wise data splits to assess generalizability across individuals. The proposed approach achieved a classification accuracy of 94.60 %, effectively identifying cardiac conditions associated with SCD one hour before its onset. This fusion-based framework shows strong potential for integration into real-time, automated diagnostic systems, enabling early warning, personalized monitoring, and timely intervention to reduce fatal outcomes.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104370"},"PeriodicalIF":1.7,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125261","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":"Whole-cycle and time-specific validation of a GUI-based ground reaction force estimation tool for clinical gait analysis without a force plate","authors":"Pegah Jamali ,&nbsp;Li-Shan Chou ,&nbsp;Robert D. Catena","doi":"10.1016/j.medengphy.2025.104366","DOIUrl":"10.1016/j.medengphy.2025.104366","url":null,"abstract":"<div><div>Relying on patients to make clean contacts with multiple force plates during clinical gait analysis can be time-consuming and dissuade clinicians from collecting biomechanical data. Several methods have been proposed to estimate ground reaction forces (GRFs) without force plates, though many can be computationally intensive. As an alternative to measuring GRFs, we evaluated the whole cycle and time frame accuracy of a built-in, GUI-based GRF estimation tool.</div><div>Twenty-seven healthy adult participants walked over two consecutive force plates. We evaluated the accuracy of estimated GRFs against force plates as the gold standard using correlation, residual error analysis, and statistical parametric mapping (SPM).</div><div>Estimated GRF magnitudes were accurate in the anterior-posterior (R²=0.86, %RMSE=7.28), and vertical directions (R²=0.86, %RMSE=6.09), but not in the medio-lateral direction (R²=0.30, %RMSE=12.46). SPM revealed errors in the sagittal plane in mid- and late-stance, with no specific errors in the medio-lateral direction.</div><div>Estimated centers of pressure (CoPs) showed good accuracy (R²≥0.99, %RMSE≤4.46). However, SPM showed estimated CoPs were consistently anterior to the true CoPs.</div><div>Sagittal GRFs are predicted with good accuracy, showing whole cycle errors comparable to more complex methods, while also displaying little early stance error and offering user-friendly implementation.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104366"},"PeriodicalIF":1.7,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134126","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":"Bimetallic nanoprobe strip for the detection of human chorionic gonadotrophin in pregnancy","authors":"Maithili Kantak ,&nbsp;Pravin Shende","doi":"10.1016/j.medengphy.2025.104354","DOIUrl":"10.1016/j.medengphy.2025.104354","url":null,"abstract":"<div><div>A novel nanotechnology-based approach was developed to enhance the accuracy and reliability of pregnancy detection to address the limitations of conventional kits like PregaNews, First Response, Accu-Clear, EPT (Error Proof Test), etc. which are based on the enzyme-linked immunosorbent assay (ELISA) method. Such conventional methods often suffer from complex procedures, low precision (33 %), cross-reactivity, and false positives. The developed new diagnostic platform employed a lateral flow assay-based gold-silver nanoprobe (GSNPs) system conjugated with 3-mercaptopropionate and monoclonal antibody 2 (mAb2), pre-dispersed on biodegradable Whatman filter paper and coupled with a smartphone-based application for the detection of hCG in pregnancy. The GSNPs with a particle size of 325.1 ± 0.64 nm, exhibited superior catalytic efficiency (0.29 to 0.37 nm) with significant specificity, and reliability in comparison to digital color analysis via RGB (red, green, blue) and HSV (hue, saturation, value) algorithmic model. This nanotechnology-based system demonstrated a wide detection range (0.4–2.4ng/mL) with a low limit of detection (LOD) at 0.79 ng/mL and limit of quantification (LOQ) at 9.67 ng/mL. The detection of pathological urine was consistent with the artificial urine sample at R²=0.9796 and showed linear relationship with saturation value (<em>y</em> = 5.1849x+3.4559). The biodegradable and portable diagnostic strip generates minimal bio-waste and offers eco-friendly disposal. This platform tool-based strip enables sensitive, rapid, user-friendly, and cost-effective detection of hCG compared to conventional pregnancy tests. The integration of bimetallic nanoprobe strip with smartphone technology ensures ease of accessibility, high precision, and environmental sustainability to increase the demand for such reliable and economic diagnostic tool.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104354"},"PeriodicalIF":1.7,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147851","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":"Study on the properties of capsule shell prepared by multi-type HPMC mixed system","authors":"Jun Wu ,&nbsp;Qingyang Meng ,&nbsp;Ruihe Zhao ,&nbsp;Yingling Zhu ,&nbsp;Jianhua Huang ,&nbsp;Yuan Zhang ,&nbsp;Jingrou Wang ,&nbsp;Jun Gong","doi":"10.1016/j.medengphy.2025.104362","DOIUrl":"10.1016/j.medengphy.2025.104362","url":null,"abstract":"<div><div>The objective of this study is to develop a viable formulation strategy aimed at minimizing the gel content in HPMC capsules and avoiding the issue of variable drug release rates in the different media environments attributed to the excessive gel content within the capsules. Through mixing various types of HPMC with different gel temperatures, the formulation facilitates reaching the staged gelation upon the mold as the temperature decreases, which effectively reduces the requisite amount of gelling agent. Consequently, the decrease in gel agent content ensures that the dissolution of the capsule shell is unaffected by the pH of the medium and the type of ions in the medium. This property allows for uniform drug release rates across diverse media, with complete drug release occurring within approximately 20 min. This improved formula not only reduces the gelling agent content in conventional HPMC formulations but also is characterized by the absence of any organic solvents and the simplicity of operation, thus providing a dependable and widely applicable method for the synthesis of HPMC capsules.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104362"},"PeriodicalIF":1.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071282","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":"Can we identify stroke sub-type without imaging? A multidimensional analysis","authors":"Abdulaziz Alshehri ,&nbsp;Ronney B. Panerai ,&nbsp;Man Yee Lam ,&nbsp;Osian Llwyd ,&nbsp;Thompson G. Robinson ,&nbsp;Jatinder S. Minhas","doi":"10.1016/j.medengphy.2025.104364","DOIUrl":"10.1016/j.medengphy.2025.104364","url":null,"abstract":"<div><div>Stroke is a major cause of mortality and disability worldwide, with ischemic stroke (AIS) and intracerebral haemorrhage (ICH) requiring distinct management approaches. Accurate early detection and differentiation of these subtypes is crucial for targeted treatment and improved patient outcomes. Traditionally, imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) are required to distinguish between AIS and ICH. However, this study explores a non-imaging approach to differentiate between stroke subtypes. Using a retrospective dataset of 80 mild-to-moderate patients suffering stroke (68 AIS and 12 ICH), we employed principal component analysis (PCA) combined with logistic regression (LR) to evaluate 67 parameters. These parameters include baroreceptor sensitivity, and cerebral and peripheral hemodynamic variables. The PCA-LR model, validated through two-fold and six-fold cross-validation methods, effectively differentiated between AIS and ICH. BRS parameters and cerebral hemodynamic factors contributed significantly to the model’s accuracy. The two-fold cross-validation approach achieved an area under the curve (AUC) of ≥0.92, while the six-fold method maintained a consistent variance explanation (AUC ≥0.79). Results suggest that this multidimensional approach may facilitate early stroke subtype identification (AIS vs ICH) without reliance on imaging, offering a promising tool for ultra-acute stroke care in prehospital settings. However, it is important to note that the model has been tested in confirmed stroke cases, and its ability to distinguish between stroke and stroke mimics remains an important limitation for broader clinical application. Future research with larger datasets is warranted to refine the model and validate its clinical applicability.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104364"},"PeriodicalIF":1.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072012","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":"Non-uniform assignment method for skeletal materials based on slope difference distribution and experimental validation","authors":"Yafeng Li ,&nbsp;Zichun Zou ,&nbsp;Fengyuan Lu ,&nbsp;Bopeng Zhang ,&nbsp;Zhifeng Tian ,&nbsp;Xi Zhang ,&nbsp;Jing Zhang","doi":"10.1016/j.medengphy.2025.104359","DOIUrl":"10.1016/j.medengphy.2025.104359","url":null,"abstract":"<div><div>A modeling method of non-uniform material assignment based on Slope Difference Distribution (SDD) is proposed to establish a complete and effective finite element (FE) model of the lower limb tibia. The validity and accuracy of the model based on <em>in vitro</em> mechanical experiments are verified. An initial tibia model was established based on Computed Tomography (CT) images. The numerical distribution of the extracted Hounsfield Unit histograms of the tibia mesh elements was fitted as a smooth curve. The critical point of the slope difference distribution curve was computed and selected to establish a tibia FE model with non-uniform material properties through numerical variations. The composite tibia's area of interest was subjected to data acquisition and analysis of displacement and strain at three gaits through a Digital Image Correlation (DIC) device. The slopes of the stress-strain straight fitting lines for slope difference distribution and structural FE models are 47.17 and 36.45. A comparison of the results of the previous experiments revealed that the FE model based on the material assignment method of slope difference distribution is more accurate. The assignment method is not limited to tibia models but also provides a method for modeling other human bones and reduces the cost of mechanical testing for accurate prediction in the simulation of bone biomechanics.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104359"},"PeriodicalIF":1.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147849","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":"A novel STA-EEGNet combined with channel selection for classification of EEG evoked in 2D and 3D virtual reality","authors":"MingLiang Zuo ,&nbsp;XiaoYu Chen ,&nbsp;Li Sui","doi":"10.1016/j.medengphy.2025.104363","DOIUrl":"10.1016/j.medengphy.2025.104363","url":null,"abstract":"<div><div>Virtual reality (VR), particularly through 3D presentations, significantly boosts user engagement and task efficiency in fields such as gaming, education, and healthcare, offering more immersive and interactive experiences than traditional 2D formats. This study investigates EEG classification in response to 2D and 3D VR stimuli to deepen our understanding of the neural mechanisms driving VR interactions, with implications for brain-computer interfaces (BCIs). We introduce STA-EEGNet, an innovative model that enhances EEGNet by incorporating spatial-temporal attention (STA), improving EEG signal classification from VR environments. A one-way analysis of variance (ANOVA) was utilized to optimize channel selection, enhancing model accuracy. Comparative experiments showed that STA-EEGNet surpassed traditional EEGNet, achieving a peak accuracy of 99.78 % with channel selection. These findings highlight the benefits of spatial-temporal attention and optimal channel selection in classifying VR-evoked EEG data. This study underscores the importance of integrating spatial-temporal attention with compact convolutional neural networks like EEGNet, not only improving EEG signal classification but also advancing neural decoding and optimizing BCI applications.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104363"},"PeriodicalIF":1.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071283","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":"Sulfonated polyetheretherketone enriched with MXene V2C promotes bone formation via WNT/β-catenin signaling in bone marrow mesenchymal stem cells","authors":"Shengjie Wang ,&nbsp;Wei Liu ,&nbsp;Chao Yang ,&nbsp;Xianlong Zhang ,&nbsp;Chunming Lyu","doi":"10.1016/j.medengphy.2025.104361","DOIUrl":"10.1016/j.medengphy.2025.104361","url":null,"abstract":"<div><div>Prosthetic loosening represents a catastrophic postoperative complication in artificial joint replacement, resulting in severe patient morbidity and substantial healthcare costs. This investigation aimed to develop a novel strategy for preventing prosthetic loosening. Two-dimensional MXene V₂C nanosheets were synthesized and subsequently immobilized onto three-dimensional porous sulfonated polyetheretherketone (SPEEK) surfaces with polydopamine (PDA) to form V₂C-PDA@SPEEK (Abbrev. V₂C-PS). The biocompatibility was systematically evaluated using rat bone marrow mesenchymal stem cells (rBMSCs) and murine models. The osteogenic differentiation potential of V₂C-PS was assessed through real-time PCR analysis, Alkaline phosphatase (ALP) staining, and Alizarin Red staining. The in vivo osteogenic capacity of V₂C-PS surrounding the implant material was evaluated in rat femoral models using micro-CT analysis, biomechanical pull-out testing, sequential fluorescent labeling of newly formed bone, and Van Gieson staining. The molecular mechanisms underlying V₂C-PS -mediated osteogenic differentiation of rBMSCs were investigated both in vitro and in vivo using chemical inhibitors, β-catenin shRNA lentiviral silencing, and β-catenin mRNA lentiviral overexpression. The results demonstrated that V₂C-PS exhibited excellent biocompatibility. Quantitative analysis revealed substantial upregulation (p &lt; 0.05) of critical osteogenic markers, including RUNX2 (4.4-fold), COL-1 (5.7-fold), OCN (3.3-fold), BMP-2 (4.4-fold), OPN (3.1-fold), BSP (3.3-fold), ON (4.3-fold), and OSX (2.83-fold), in the 25V₂C-PS treatment group compared to PS group. The bone parameters were also remarkably enhanced in the 25V₂C-PS group (BMD increased by 241 %, bone-implant contact by 159 %, BV/TV by 225 %, Tb.N by 281 %, Tb.Th by 214 %, maximum pull-out force by 250 %, and Tp.Sp decreased by 33 %). Furthermore, V₂C-PS were found to enhance rBMSC osteogenic differentiation through activation of the Wnt/β-catenin signaling pathway. This study presents a promising approach for preventing orthopedic prosthetic loosening and demonstrates significant potential for clinical translation.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104361"},"PeriodicalIF":1.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071284","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":"Prediction of heterotopic ossification on the cervical spine with offset of the artificial disc – A finite element study","authors":"Balaji Harinathan ,&nbsp;Davidson Jebaseelan ,&nbsp;Hemkar Sharma ,&nbsp;Lenin Babu ,&nbsp;Rajasekaran Shanmuganathan ,&nbsp;Narayan Yoganandan","doi":"10.1016/j.medengphy.2025.104356","DOIUrl":"10.1016/j.medengphy.2025.104356","url":null,"abstract":"<div><div>Heterotopic ossification (HO) is a significant complication of cervical total disc replacement (TDR), often leading to fusion and negating the intended benefits of motion preservation. Although clinical factors associated with HO formation are known, the exact biomechanical mechanism remains unclear. This study aims to predict HO formation after Mobi-C disc replacement at the C5-C6 level using a validated finite element model (FEM) of the cervical spine (C2-T1) under physiological loading. The results revealed that the Mobi-C disc increased the range of motion (ROM) at the implanted level by 52 % under flexion and extension, while adjacent levels exhibited a 2–5 % reduction. Following HO formation, ROM at the implanted level decreased by 67–76 % in flexion and extension, respectively, while adjacent levels showed a moderate increase of 5–8 %. Additionally, intradiscal pressure at the adjacent levels increased by up to 60 % in extension, mimicking fusion-like behavior. HO volume was 678 mm³ for the ideal implant position, to 760 mm³ (+12 %) for a 0.5 mm offset and 800 mm³ (+17 %) for a 1 mm offset. This study highlights the importance of Mobi-C placement to minimize HO formation, preserve motion, and mitigate complications, providing insights for clinical practice.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"141 ","pages":"Article 104356"},"PeriodicalIF":1.7,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147848","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}