Biomechanics and Modeling in Mechanobiology最新文献

{"title":"Computational models for predicting bone fracture healing: a review of modeling approaches, predictions, and emerging strategies","authors":"Diogo G. Pires,&nbsp;A. Completo,&nbsp;Marco P. Soares dos Santos","doi":"10.1007/s10237-026-02061-x","DOIUrl":"10.1007/s10237-026-02061-x","url":null,"abstract":"<div><p>Background and Objective: The development of computational models for predicting bone fracture healing process holds strong potential to optimize therapeutic management in non-unions and delayed healing, reducing healthcare costs and disability-adjusted life years. The main goal of this study is to provide a thoroughly comparative analysis to computational models already proposed to predict fracture healing, including methodologies, mathematical frameworks, validation techniques, and comparative findings across different studies. Methods: This review analyzes 60 computational models selected through a systematic search in the Scopus database (2000–2025) using targeted keywords and rigorously screened according to predefined inclusion and exclusion criteria for simulating bone fracture healing, focusing on mechanical, biological, mechanobiological, ultrasound, and bioelectronic dynamics, employing FEM and artificial intelligence techniques. The effectiveness of each model in predicting healing progression was assessed by analyzing their computational frameworks, accuracy, and limitations. Results: Comparative analysis revealed that both mechanical and biological models provide fundamental predictions related to fracture healing (e.g., stress distribution and vascularization), but they often lack the physiological complexity demanded for clinical application. Mechanobiological models accurately predict tissue differentiation by combining mechanical stimuli, with strong qualitative agreement with in vivo histological patterns. Ultrasound models have been effective for non-invasive structural assessment, despite existing limitations due to simplified boundary conditions. Notably, the development of bioelectric models has been demonstrating a highly sensitive approach for assessing fracture healing. Conclusions:This study highlights that multidomain computational frameworks combining mechanobiological dynamics with dielectric properties hold significant potential to personalize the clinical management of delayed bone healing.\u0000</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10237-026-02061-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simple personalised prediction model for hip fracture risk based on mechanistic parameters","authors":"Christina Wapp,&nbsp;Yvan Gugler,&nbsp;Paula Cameron,&nbsp;Alice Dudle,&nbsp;Daniela Frauchiger,&nbsp;Maria Papageorgiou,&nbsp;Emmanuel Biver,&nbsp;Serge Ferrari,&nbsp;Kurt Lippuner,&nbsp;Philippe Zysset","doi":"10.1007/s10237-026-02051-z","DOIUrl":"10.1007/s10237-026-02051-z","url":null,"abstract":"<div><p>Fragility hip fractures in older adults are a major burden for the individual and the society, as they result in increased morbidity, mortality and substantial health care expenditure. Most fragility hip fractures are caused by falls, resulting in an impact on the postero-lateral aspect of the hip, inducing a force that exceeds the femoral bone strength. The risk of fracture depends on the rate of falling, the fall-induced impact force, and the femoral bone strength. This article presents the framework of a novel fragility hip fracture risk calculator based on a combined mechanistic and stochastic modelling approach. The model integrates the stochastic aspects of a fall and its dynamics together with a 1D mechanical model predicting the impact force in the hip to calculate a one-year absolute fracture risk. The required input parameters are based on QCT images, but can be substituted with more accessible anthropometric and densitometric data. To demonstrate how the parameters are extracted from clinical data and how the model is calibrated, data from the AFFIRM-CT cohort were used. A sensitivity analysis was conducted, confirming that the fall rate, the trochanteric soft tissue thickness and the bone strength are the dominating parameters influencing the risk of fragility hip fractures. Furthermore, output variables such as the predicted impact velocity and impact force aligned well with experimental data. Thus, the model is able to reflect observations from empirical data, indicating that it can capture the intrinsic aspects that define the risk of fragility hip fractures.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3d elastic-modulus imaging using ultrasound linear arrays and efficient data-driven training strategies","authors":"Will Newman,&nbsp;Jamshid Ghaboussi,&nbsp;Michael F. Insana","doi":"10.1007/s10237-026-02056-8","DOIUrl":"10.1007/s10237-026-02056-8","url":null,"abstract":"<div><p>We are developing ultrasonic-based techniques for elastic modulus imaging throughout a tissue volume using the autoprogressive (AutoP) method with linear array transducers. AutoP discovers the constitutive properties of media by estimating the stress and strain in a volume from force-displacement measurements recorded in planes. AutoP is a data-driven machine learning technique that combines shallow neural network structures with object-specific measurements, in stark contrast with traditional deep learning techniques. In this paper, we outline a strategy for acquiring measurements from a series of compression planes across the volume and applying them in a training sequence that efficiently trains networks to model volumetric deformation patterns. We show with phantom studies that measurements collected while compressing the medium in parallel planes throughout the volume can yield elastic modulus image values within 10% of values measured independently. Deformation models are developed accurately in minutes using a comprehensive set of exact measurements. However, experimental limitations slow the learning process and ultimately limit the contrast and spatial resolution of modulus images in ways that can be minimized. An efficient imaging strategy balances the need to provide more planes of force-displacement measurements to enhance learning with the need to manage measurement errors. Test statistics obtained from the developing model can guide the learning process.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13035627/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale computational modeling of the cardiopulmonary consequences of postnatal hyperoxia with implications for preterm-born children","authors":"Salla M. Kim,&nbsp;Filip Jezek,&nbsp;Pim J. A. Oomen,&nbsp;Gregory P. Barton,&nbsp;Feng Gu,&nbsp;Daniel A. Beard,&nbsp;Kara N. Goss,&nbsp;Mitchel J. Colebank,&nbsp;Naomi C. Chesler","doi":"10.1007/s10237-026-02047-9","DOIUrl":"10.1007/s10237-026-02047-9","url":null,"abstract":"<div><p>Moderate to extreme preterm birth (&lt; 32 weeks gestation) affects cardiopulmonary structure and function and is associated with increased risk of heart failure through adulthood. The rat hyperoxia (Hx) model (term born; postnatal Hx exposure) captures biventricular changes, including at the cell and organ scale, and pulmonary vascular remodeling seen in preterm humans. However, synthesizing these measures across scales and organ systems is challenging. We hypothesized that in silico modeling of biventricular mitochondrial, myofiber, and organ-scale function plus circulatory function could capture key features of cardiopulmonary abnormalities due to preterm birth. Therefore, we calibrated a multiscale model to subject-specific biventricular pressure–volume data previously obtained from Hx rats alongside normoxic (Nx) controls to investigate the abnormalities in cardiopulmonary function at multiple scales in this animal model of human preterm birth. The calibrated model demonstrates excellent agreement with the data and captures the expected pulmonary vascular changes and right ventricular dilation seen in preterm-born children. Our multiscale modeling approach captures cardiopulmonary abnormalities across spatial scales and provides an innovative approach to explore the consequences of preterm birth beyond preclinical experimental data alone. This is a foundational step in understanding the impact of preterm birth on cardiopulmonary disease in childhood as well as adulthood.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13035550/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of blood flow characteristics of intimal rupture in intramural hematoma using computational fluid dynamics","authors":"Kun Liu,&nbsp;Shanlin Qin,&nbsp;Zhifu Huan,&nbsp;Jia Liu,&nbsp;Minxin Wei","doi":"10.1007/s10237-026-02058-6","DOIUrl":"10.1007/s10237-026-02058-6","url":null,"abstract":"<div><p>Intramural hematoma (IMH) is frequently accompanied by intimal tear, presenting as penetrating atherosclerotic ulcer (PAU) or ulcer-like projection (ULP) in aortic computed tomography angiography (CTA) examination, and usually requires clinical intervention. To analyze potential hemodynamic risk factors for intimal rupture in IMH, computational fluid dynamics (CFD) methods were used. CTA images from IMH patients were collected to establish three-dimensional models. The models with ULP removed served as the morphological representation before IMH formed. The three-dimensional models were discretized into grids, and simulations were conducted using the CFD method. No extensive regions of high oscillatory shear index (OSI) and endothelial cell activation potential (ECAP) occurred in the normal aortic arch. The ulcer-like projections or intimal tear sites in IMH exhibit significantly elevated OSI and ECAP. Following repair of the intimal rupture site in the IMH models, hemodynamic parameters demonstrated significant differences between pre-IMH and normal cases. Statistically significant differences were identified in segmented aortic ECAP and OSI between the IMH pre-model and normal aortas. The average ECAP_max was significantly lower in the intimal rupture of pre-IMH cases compared to corresponding normal cases (0.73 vs. 0.84, <i>P</i> = 0.04). Similarly, the average ECAP_ave showed a higher value in the intimal rupture of pre-IMH cases compared to corresponding normal cases (0.0027 vs 0.0021 with <i>P</i> = 0.03). Notably, the average OSI_ave was markedly elevated in the intimal rupture of pre-IMH cases compared to corresponding normal controls (0.0038 vs 0.0024 with <i>P</i> = 0.001). This indicates that intimal rupture in IMH was associated with high OSI and ECAP regions in the aorta.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical behavior of human breast tissues: ex vivo and in silico characterization","authors":"Ana Margarida Teixeira,&nbsp;António Diogo André,&nbsp;Marco Parente,&nbsp;Maria da Luz Barroso,&nbsp;Cristina Cunha,&nbsp;Horácio Costa,&nbsp;Pedro Martins","doi":"10.1007/s10237-026-02045-x","DOIUrl":"10.1007/s10237-026-02045-x","url":null,"abstract":"<div><p>To study the mechanics of a biological tissue is crucial to understand its behavior under a variety of realistic loading conditions. In particular, an accurate estimation of the mechanical properties of breast tissues is essential to enhance current diagnostic techniques, such as mammography, and to improve clinical treatments, including tissue engineering approaches. This study focuses on the mechanical characterization of human breast tissues, harvested from women who underwent a mammary reduction surgery. <i>Ex vivo</i> experiments, consisted in indentation tests, were performed to determine the elastic properties. Additionally, using inverse finite element analysis, the hyperelastic properties were obtained for the Yeoh and Ogden (N = 3) constitutive models. The samples were grouped based on the characteristics of the female population (i.e., age, body mass index and menopausal status) and according to the breast side (tissue sample site). Significant differences in the Young’s modulus were only observed in association with age and menopausal status, in the first linear region (3.75–11.5% strain) of the experimental curve. In the second linear region (22.5–30% strain), although samples presented a higher stiffness, no significant differences were observed. Regarding the hyperelastic properties, Yeoh and Ogden (N = 3) models accurately fit the experimental data, presenting errors lower than 3.26% and 3.86%, respectively. In this work, the model developed successfully converged with a 3 mm of indentation (corresponding to 30% of deformation), enabling reliable analysis in the large deformations domain. The findings of this study provide valuable insights that can contribute to future clinical applications and research, including improvements in diagnostic techniques, treatments and esthetic reconstructions.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13035888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic algorithm-based optimization of columella shape with FEM surrogate modeling: convergence analysis and application to ossicular chain reconstruction","authors":"Takumi Asakura,&nbsp;Koyo Ozono,&nbsp;Takuma Ichino,&nbsp;Motoki Hirabayashi,&nbsp;Sho Kurihara,&nbsp;Yuta Kurashina","doi":"10.1007/s10237-026-02044-y","DOIUrl":"10.1007/s10237-026-02044-y","url":null,"abstract":"<div><p>Ossicular chain reconstruction is a vital surgical approach for restoring hearing in patients with ossicular chain disruption. Despite advancements in prosthetic design, selecting optimal material and geometric configurations remains a challenge due to the complex, nonlinear dynamics of middle ear biomechanics. This study presents a hybrid optimization framework that integrates genetic algorithms (GA) with machine learning-trained finite element (FE) surrogate models to design middle ear columella prostheses with enhanced acoustic performance. Four tympanoplasty models (III_c, III_i-M, IV_c, IV_i-M), based on extended Wullstein classifications, were analyzed using vibroacoustic FE simulations. Surrogate models based on Random Forest regression were trained on 5000 FEM samples per type, capturing key input–output relationships across geometric and material variables. These models enabled over 1000-fold acceleration in optimization time compared to full FEM runs, allowing GA-based design exploration across 40 generations with 200 individuals each. The optimized prosthesis designs favored low-density (1000–1600 kg/m³) and moderately stiff (2–6 MPa) materials, confirming clinical preferences for cartilage. Geometries with smaller cross-sectional areas and tapered shapes consistently improved high-frequency sound transmission. The framework also revealed multimodal design landscapes, underscoring the importance of global search strategies. This work demonstrates a scalable, clinically relevant approach to prosthesis optimization that supports patient-specific customization and efficient design-space exploration, with potential to improve outcomes in otologic surgery.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13035726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization and complexity analysis of homogeneous coagulation models","authors":"Junyi Chen,&nbsp;Franck Nicoud","doi":"10.1007/s10237-026-02059-5","DOIUrl":"10.1007/s10237-026-02059-5","url":null,"abstract":"<div><p>This study evaluates the performance of optimization strategies across homogeneous coagulation models of varying complexity, distinguished by differences in the number of species and reactions. In the two extrinsic pathway models examined, the more detailed scheme exhibits a more complex optimization landscape, with numerous local minima and increased convergence difficulties compared with the reduced model. To address these issues, we propose a hybrid optimization framework integrating gradient-based methods with evolutionary algorithms. When applied to synthetic numerical datasets, the approach demonstrates robust and reliable convergence. The strategy is further validated using real clinical and experimental thrombin generation data, confirming its practical utility in modeling physiological conditions and guiding treatment decisions.\u0000</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ferroptosis-related gene dysregulation impairs aortic wall biomechanics and contributes to aortic dissection pathogenesis","authors":"Huang Jing,&nbsp;Chai Qianqian,&nbsp;Liu Xiang,&nbsp;Lin Lihua,&nbsp;Hou Jiaqi,&nbsp;Li Haozheng,&nbsp;Liu Qian","doi":"10.1007/s10237-026-02053-x","DOIUrl":"10.1007/s10237-026-02053-x","url":null,"abstract":"<div><p>This study aimed to explore the association between smooth muscle cell (SMC) ferroptosis, aortic biomechanical properties, and the pathogenesis of aortic dissection (AD) across age groups to deepen mechanistic understanding. Assessments included immunohistochemistry for ferroptosis marker HMOX1, immunofluorescence for contractile SMC marker <i>α</i>-SMA, and uniaxial tensile testing. Results showed that the AD group had significantly higher HMOX1 expression and lower <i>α</i>-SMA expression across all age subgroups compared with controls. In AD, HMOX1 correlated positively with age, while <i>α</i>-SMA correlated negatively (no such correlations in controls). The AD group exhibited lower axial and circumferential failure stress than controls, with age-dependent directional variations: axial stress reduction dominated in the elderly, and circumferential reduction in the young. In AD, higher HMOX1 and lower <i>α</i>-SMA correlated with reduced axial stretch ratio. AD is characterized by enhanced SMC ferroptosis and loss of contractile SMCs, particularly in the elderly. Ferroptosis may reduce contractile cells via SMC phenotypic modulation, impairing aortic biomechanics, especially axially and increasing susceptibility to longitudinal intimal tearing. Age significantly influences ferroptosis severity and biomechanical failure patterns.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal intra-subject characterization of abdominal aortic aneurysm pathophysiology: a case study","authors":"Bahman Kargarbahrkhazar,&nbsp;Sanaz Farmani,&nbsp;Emma G. Foster,&nbsp;Rail Gilyazov,&nbsp;Sayed Ahmadreza Razian,&nbsp;Jason MacTaggart,&nbsp;Aditya N. Bade,&nbsp;Majid Jadidi","doi":"10.1007/s10237-026-02052-y","DOIUrl":"10.1007/s10237-026-02052-y","url":null,"abstract":"<div><p>Abdominal aortic aneurysm (AAA) is a degenerative vascular disease characterized by significant remodeling of the aortic wall. This study presents a comprehensive, multimodal analysis of AAA pathophysiology by comparing aneurysmal abdominal aortic tissue with non-aneurysmal thoracic aortic tissue of the same deceased human donor (N = 2), eliminating inter-subject differences. The multimodal approach integrated micro-CT imaging, transverse section histology, matrix metalloproteinase (MMP) analysis, and planar biaxial mechanical testing. Compared to the subject-matched thoracic controls, the AAA segments exhibited severe and heterogeneous degradation of the elastic network, profound loss of smooth muscle cells, extensive fibrosis, and a significant increase in calcification volume. Biochemically, AAA tissue showed elevated total MMP activity. In parallel, gelatin zymography tests validated an increase in MMP-9 activity in the diseased segments. Moreover, AAA tissues were substantially stiffer and less extensible than the corresponding healthy aortic tissue. These data, taken together, underscore the interconnected roles of elastin degradation, proteolytic enzyme activity, and fibrotic remodeling in the mechanical failure of the aortic wall, while highlighting the value of an intra-subject study design for elucidating disease-specific mechanisms.</p></div>","PeriodicalId":489,"journal":{"name":"Biomechanics and Modeling in Mechanobiology","volume":"25 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13033011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147571632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}