Marta Varela-Eirin, Adrian Varela-Vazquez, Amanda Guitian-Caamano, Carlos Luis Paino, Virginia Mato, Raquel Largo, Trond Aasen, Arantxa Tabernero, Eduardo Fonseca, Mustapha Kandouz, Jose Ramon Caeiro, Alfonso Blanco, Maria D. Mayan
Osteoarthritis (OA), a chronic disease characterized by articular cartilage degeneration, is a leading cause of disability and pain worldwide. In OA, chondrocytes in cartilage undergo phenotypic changes and senescence, restricting cartilage regeneration and favouring disease progression. Similar to other wound-healing disorders, chondrocytes from OA patients show a chronic increase in the gap junction channel protein connexin43 (Cx43), which regulates signal transduction through the exchange of elements or recruitment/release of signalling factors. Although immature or stem-like cells are present in cartilage from OA patients, their origin and role in disease progression are unknown. In this study, we found that Cx43 acts as a positive regulator of chondrocyte-mesenchymal transition. Downregulation of either Cx43 by CRISPR/Cas9 or Cx43-mediated gap junctional intercellular communication (GJIC) by carbenoxolone treatment triggered rediferentiation of osteoarthritic chondrocytes into a more differentiated state, associated with decreased synthesis of MMPs and proinflammatory factors, and reduced senescence. We have identified causal Cx43-sensitive circuit in chondrocytes that regulates dedifferentiation, redifferentiation and senescence. We propose that chondrocytes undergo chondrocyte-mesenchymal transition where increased Cx43-mediated GJIC during OA facilitates Twist-1 nuclear translocation as a novel mechanism involved in OA progression. These findings support the use of Cx43 as an appropriate therapeutic target to halt OA progression and to promote cartilage regeneration.
骨关节炎（OA）是一种以关节软骨变性为特征的慢性疾病，是导致全球残疾和疼痛的主要原因。在 OA 中，软骨中的软骨细胞会发生表型变化和衰老，从而限制软骨再生并导致疾病恶化。与其他伤口愈合疾病类似，OA 患者的软骨细胞中的缝隙连接通道蛋白 connexin43（Cx43）也出现了慢性增加，Cx43 通过元素交换或信号因子的招募/释放来调节信号转导。虽然OA患者的软骨中存在未成熟细胞或干样细胞，但它们的来源和在疾病进展中的作用尚不清楚。在这项研究中，我们发现 Cx43 是软骨细胞-间充质转化的正向调节因子。通过CRISPR/Cas9下调Cx43或通过卡泊三醇处理下调Cx43介导的细胞间隙连接通讯（GJIC），都会引发骨关节炎软骨细胞重新分化为更分化的状态，这与MMPs和促炎因子合成减少以及衰老减少有关。我们在软骨细胞中发现了调节分化、再分化和衰老的 Cx43 敏感电路。我们提出，软骨细胞在经历软骨细胞-间充质转化过程中，OA 期间 Cx43 介导的 GJIC 增加会促进 Twist-1 核转位，这是参与 OA 进展的一种新机制。这些发现支持将 Cx43 作为阻止 OA 进展和促进软骨再生的适当治疗靶点。
{"title":"Targeting of chondrocyte plasticity via connexin43 modulation attenuates cellular senescence and fosters a pro-regenerative environment in osteoarthritis","authors":"Marta Varela-Eirin, Adrian Varela-Vazquez, Amanda Guitian-Caamano, Carlos Luis Paino, Virginia Mato, Raquel Largo, Trond Aasen, Arantxa Tabernero, Eduardo Fonseca, Mustapha Kandouz, Jose Ramon Caeiro, Alfonso Blanco, Maria D. Mayan","doi":"arxiv-2402.00624","DOIUrl":"https://doi.org/arxiv-2402.00624","url":null,"abstract":"Osteoarthritis (OA), a chronic disease characterized by articular cartilage\u0000degeneration, is a leading cause of disability and pain worldwide. In OA,\u0000chondrocytes in cartilage undergo phenotypic changes and senescence,\u0000restricting cartilage regeneration and favouring disease progression. Similar\u0000to other wound-healing disorders, chondrocytes from OA patients show a chronic\u0000increase in the gap junction channel protein connexin43 (Cx43), which regulates\u0000signal transduction through the exchange of elements or recruitment/release of\u0000signalling factors. Although immature or stem-like cells are present in\u0000cartilage from OA patients, their origin and role in disease progression are\u0000unknown. In this study, we found that Cx43 acts as a positive regulator of\u0000chondrocyte-mesenchymal transition. Downregulation of either Cx43 by\u0000CRISPR/Cas9 or Cx43-mediated gap junctional intercellular communication (GJIC)\u0000by carbenoxolone treatment triggered rediferentiation of osteoarthritic\u0000chondrocytes into a more differentiated state, associated with decreased\u0000synthesis of MMPs and proinflammatory factors, and reduced senescence. We have\u0000identified causal Cx43-sensitive circuit in chondrocytes that regulates\u0000dedifferentiation, redifferentiation and senescence. We propose that\u0000chondrocytes undergo chondrocyte-mesenchymal transition where increased\u0000Cx43-mediated GJIC during OA facilitates Twist-1 nuclear translocation as a\u0000novel mechanism involved in OA progression. These findings support the use of\u0000Cx43 as an appropriate therapeutic target to halt OA progression and to promote\u0000cartilage regeneration.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662279","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}
Ruben C. Boot, Anouk van der Net, Christos Gogou, Pranav Mehta, Dimphna H. Meijer, Gijsje H. Koenderink, Pouyan E. Boukany
Tissue surface tension influences cell sorting and tissue fusion. Earlier mechanical studies suggest that multicellular spheroids actively reinforce their surface tension with applied force. Here we study this open question through high-throughput microfluidic micropipette aspiration measurements on cell spheroids to identify the role of force duration and cell contractility. We find that larger spheroid deformations lead to faster cellular retraction once the pressure is released, regardless of the applied force and cellular contractility. These new insights demonstrate that spheroid viscoelasticity is deformation-dependent and challenge whether surface tension truly reinforces.
{"title":"Cell spheroid viscoelasticity is deformation-dependent","authors":"Ruben C. Boot, Anouk van der Net, Christos Gogou, Pranav Mehta, Dimphna H. Meijer, Gijsje H. Koenderink, Pouyan E. Boukany","doi":"arxiv-2401.17155","DOIUrl":"https://doi.org/arxiv-2401.17155","url":null,"abstract":"Tissue surface tension influences cell sorting and tissue fusion. Earlier\u0000mechanical studies suggest that multicellular spheroids actively reinforce\u0000their surface tension with applied force. Here we study this open question\u0000through high-throughput microfluidic micropipette aspiration measurements on\u0000cell spheroids to identify the role of force duration and cell contractility.\u0000We find that larger spheroid deformations lead to faster cellular retraction\u0000once the pressure is released, regardless of the applied force and cellular\u0000contractility. These new insights demonstrate that spheroid viscoelasticity is\u0000deformation-dependent and challenge whether surface tension truly reinforces.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139647973","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}
Hao Wu, Yingnan Song, Ammar Hoori, Ananya Subramaniam, Juhwan Lee, Justin Kim, Tao Hu, Sadeer Al-Kindi, Wei-Ming Huang, Chun-Ho Yun, Chung-Lieh Hung, Sanjay Rajagopalan, David L. Wilson
We assessed the benefit of combining stress cardiac CT perfusion (CCTP) myocardial blood flow (MBF) with coronary CT angiography (CCTA) using our innovative CCTP software. By combining CCTA and CCTP, one can uniquely identify a flow limiting stenosis (obstructive-lesion + low-MBF) versus MVD (no-obstructive-lesion + low-MBF. We retrospectively evaluated 104 patients with suspected CAD, including 18 with diabetes, who underwent CCTA+CCTP. Whole heart and territorial MBF was assessed using our automated pipeline for CCTP analysis that included beam hardening correction; temporal scan registration; automated segmentation; fast, accurate, robust MBF estimation; and visualization. Stenosis severity was scored using the CCTA coronary-artery-disease-reporting-and-data-system (CAD-RADS), with obstructive stenosis deemed as CAD-RADS>=3. We established a threshold MBF (MBF=199-mL/min-100g) for normal perfusion. In patients with CAD-RADS>=3, 28/37(76%) patients showed ischemia in the corresponding territory. Two patients with obstructive disease had normal perfusion, suggesting collaterals and/or a hemodynamically insignificant stenosis. Among diabetics, 10 of 18 (56%) demonstrated diffuse ischemia consistent with MVD. Among non-diabetics, only 6% had MVD. Sex-specific prevalence of MVD was 21%/24% (M/F). On a per-vessel basis (n=256), MBF showed a significant difference between territories with and without obstructive stenosis (165 +/- 61 mL/min-100g vs. 274 +/- 62 mL/min-100g, p <0.05). A significant and negative rank correlation (rho=-0.53, p<0.05) between territory MBF and CAD-RADS was seen. CCTA in conjunction with a new automated quantitative CCTP approach can augment the interpretation of CAD, enabling the distinction of ischemia due to obstructive lesions and MVD.
{"title":"Coronary CTA and Quantitative Cardiac CT Perfusion (CCTP) in Coronary Artery Disease","authors":"Hao Wu, Yingnan Song, Ammar Hoori, Ananya Subramaniam, Juhwan Lee, Justin Kim, Tao Hu, Sadeer Al-Kindi, Wei-Ming Huang, Chun-Ho Yun, Chung-Lieh Hung, Sanjay Rajagopalan, David L. Wilson","doi":"arxiv-2401.17433","DOIUrl":"https://doi.org/arxiv-2401.17433","url":null,"abstract":"We assessed the benefit of combining stress cardiac CT perfusion (CCTP)\u0000myocardial blood flow (MBF) with coronary CT angiography (CCTA) using our\u0000innovative CCTP software. By combining CCTA and CCTP, one can uniquely identify\u0000a flow limiting stenosis (obstructive-lesion + low-MBF) versus MVD\u0000(no-obstructive-lesion + low-MBF. We retrospectively evaluated 104 patients\u0000with suspected CAD, including 18 with diabetes, who underwent CCTA+CCTP. Whole\u0000heart and territorial MBF was assessed using our automated pipeline for CCTP\u0000analysis that included beam hardening correction; temporal scan registration;\u0000automated segmentation; fast, accurate, robust MBF estimation; and\u0000visualization. Stenosis severity was scored using the CCTA\u0000coronary-artery-disease-reporting-and-data-system (CAD-RADS), with obstructive\u0000stenosis deemed as CAD-RADS>=3. We established a threshold MBF\u0000(MBF=199-mL/min-100g) for normal perfusion. In patients with CAD-RADS>=3,\u000028/37(76%) patients showed ischemia in the corresponding territory. Two\u0000patients with obstructive disease had normal perfusion, suggesting collaterals\u0000and/or a hemodynamically insignificant stenosis. Among diabetics, 10 of 18\u0000(56%) demonstrated diffuse ischemia consistent with MVD. Among non-diabetics,\u0000only 6% had MVD. Sex-specific prevalence of MVD was 21%/24% (M/F). On a\u0000per-vessel basis (n=256), MBF showed a significant difference between\u0000territories with and without obstructive stenosis (165 +/- 61 mL/min-100g vs.\u0000274 +/- 62 mL/min-100g, p <0.05). A significant and negative rank correlation\u0000(rho=-0.53, p<0.05) between territory MBF and CAD-RADS was seen. CCTA in\u0000conjunction with a new automated quantitative CCTP approach can augment the\u0000interpretation of CAD, enabling the distinction of ischemia due to obstructive\u0000lesions and MVD.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139659181","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}
Caleb C. Berggren, David Jiang, Y. F. Jack Wang, Jake A. Bergquist, Lindsay C. Rupp, Zexin Liu, Rob S. MacLeod, Akil Narayan, Lucas H. Timmins
Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Simulation frameworks must be robust to uncertainty in model input(s), and levels of confidence should accompany results. In this study we applied a coupled uncertainty quantification-finite element (FE) framework to understand the impact of uncertainty in vascular material properties on variability in predicted stresses. Univariate probability distributions were fit to material parameters derived from layer-specific mechanical behavior testing of human coronary tissue. Parameters were assumed to be probabilistically independent, allowing for efficient parameter ensemble sampling. In an idealized coronary artery geometry, a forward FE model for each parameter ensemble was created to predict tissue stresses under physiologic loading. An emulator was constructed within the UncertainSCI software using polynomial chaos techniques, and statistics and sensitivities were directly computed. Results demonstrated that material parameter uncertainty propagates to variability in predicted stresses across the vessel wall, with the largest dispersions in stress within the adventitial layer. Variability in stress was most sensitive to uncertainties in the anisotropic component of the strain energy function. Unary and binary interactions within the adventitial layer were the main contributors to stress variance, and the leading factor in stress variability was uncertainty in the stress-like material parameter summarizing contribution of the embedded fibers to the overall artery stiffness. Results from a patient-specific coronary model confirmed many of these findings. Collectively, this highlights the impact of material property variation on predicted artery stresses and presents a pipeline to explore and characterize uncertainty in computational biomechanics.
临床采用患者特异性建模策略的核心是证明模拟结果是可靠和安全的。仿真框架必须对模型输入的不确定性具有稳健性，并且结果应具有可信度。在这项研究中，我们采用了不确定性量化-有限元（FE）耦合框架来了解血管材料属性的不确定性对预测应力变化的影响。根据人体冠状动脉组织特定层力学行为测试得出的材料参数拟合了单变量概率分布。假定参数在概率上是独立的，因此可以进行有效的参数集合采样。在理想化的冠状动脉几何形状中，为每个参数集合创建了一个前向 FE 模型，以预测生理负荷下的组织应力。利用多项式混沌技术在 UncertainSCI 软件中构建了一个仿真器，并直接计算了统计量和灵敏度。结果表明，材料参数的不确定性会导致整个血管壁预测应力的变化，其中ventitial层的应力分散最大。应力的变化对应变能函数各向异性分量的不确定性最为敏感。内膜层内的一元和二元相互作用是造成应力变异的主要因素，而应力变异的主要因素是应力样材料参数的不确定性，该参数概括了内嵌纤维对整个动脉刚度的贡献。患者特异性冠状动脉模型的结果证实了上述许多发现。总之，这凸显了材料特性变化对预测动脉应力的影响，并为探索和描述计算生物力学中的不确定性提供了一条途径。
{"title":"Influence of Material Parameter Variability on the Predicted Coronary Artery Biomechanical Environment via Uncertainty Quantification","authors":"Caleb C. Berggren, David Jiang, Y. F. Jack Wang, Jake A. Bergquist, Lindsay C. Rupp, Zexin Liu, Rob S. MacLeod, Akil Narayan, Lucas H. Timmins","doi":"arxiv-2401.15047","DOIUrl":"https://doi.org/arxiv-2401.15047","url":null,"abstract":"Central to the clinical adoption of patient-specific modeling strategies is\u0000demonstrating that simulation results are reliable and safe. Simulation\u0000frameworks must be robust to uncertainty in model input(s), and levels of\u0000confidence should accompany results. In this study we applied a coupled\u0000uncertainty quantification-finite element (FE) framework to understand the\u0000impact of uncertainty in vascular material properties on variability in\u0000predicted stresses. Univariate probability distributions were fit to material\u0000parameters derived from layer-specific mechanical behavior testing of human\u0000coronary tissue. Parameters were assumed to be probabilistically independent,\u0000allowing for efficient parameter ensemble sampling. In an idealized coronary\u0000artery geometry, a forward FE model for each parameter ensemble was created to\u0000predict tissue stresses under physiologic loading. An emulator was constructed\u0000within the UncertainSCI software using polynomial chaos techniques, and\u0000statistics and sensitivities were directly computed. Results demonstrated that\u0000material parameter uncertainty propagates to variability in predicted stresses\u0000across the vessel wall, with the largest dispersions in stress within the\u0000adventitial layer. Variability in stress was most sensitive to uncertainties in\u0000the anisotropic component of the strain energy function. Unary and binary\u0000interactions within the adventitial layer were the main contributors to stress\u0000variance, and the leading factor in stress variability was uncertainty in the\u0000stress-like material parameter summarizing contribution of the embedded fibers\u0000to the overall artery stiffness. Results from a patient-specific coronary model\u0000confirmed many of these findings. Collectively, this highlights the impact of\u0000material property variation on predicted artery stresses and presents a\u0000pipeline to explore and characterize uncertainty in computational biomechanics.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139587357","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}
Sean M. Edwards, Amy L. Harding, Joseph A. Leedale, Steve D. Webb, Helen E. Colley, Craig Murdoch, Rachel N. Bearon
In pharmaceutical therapeutic design or toxicology, accurately predicting the permeation of chemicals through human epithelial tissues is crucial, where permeation is significantly influenced by the tissue's cellular architecture. Current mathematical models for multi-layered epithelium such as the oral mucosa only use simplistic 'bricks and mortar' geometries and therefore do not account for the complex cellular architecture of these tissues at the microscale level, such as the extensive plasma membrane convolutions that define the extracellular spaces between cells. Chemicals often permeate tissues via this paracellular route, meaning that permeation is underestimated. To address this, measurements of human buccal mucosal tissue were conducted to ascertain the width and tortuosity of extracellular spaces across the epithelium. Using mechanistic mathematical modelling, we show that the convoluted geometry of extracellular spaces significantly impacts chemical permeation and that this can be approximated, provided that extracellular tortuosity is accounted for. We next developed an advanced physically-relevant in silico model of oral mucosal chemical permeation using partial differential equations, fitted to chemical permeation in vitro assays on tissue-engineered human oral mucosa. Tissue geometries were measured and captured in silico, and permeation examined and predicted for chemicals with different physicochemical properties. The effect of altering the extracellular space to mimic permeation enhancers was also assessed by perturbing the in silico model. This novel in vitro-in silico approach has the potential to expedite pharmaceutical innovation for testing oromucosal chemical permeation, providing a more accurate, physiologically-relevant model which can reduce animal testing with early screening based on chemical properties.
{"title":"An innovative in silico model of the oral mucosa reveals the impact of extracellular spaces on chemical permeation through epithelium","authors":"Sean M. Edwards, Amy L. Harding, Joseph A. Leedale, Steve D. Webb, Helen E. Colley, Craig Murdoch, Rachel N. Bearon","doi":"arxiv-2401.14928","DOIUrl":"https://doi.org/arxiv-2401.14928","url":null,"abstract":"In pharmaceutical therapeutic design or toxicology, accurately predicting the\u0000permeation of chemicals through human epithelial tissues is crucial, where\u0000permeation is significantly influenced by the tissue's cellular architecture.\u0000Current mathematical models for multi-layered epithelium such as the oral\u0000mucosa only use simplistic 'bricks and mortar' geometries and therefore do not\u0000account for the complex cellular architecture of these tissues at the\u0000microscale level, such as the extensive plasma membrane convolutions that\u0000define the extracellular spaces between cells. Chemicals often permeate tissues\u0000via this paracellular route, meaning that permeation is underestimated. To\u0000address this, measurements of human buccal mucosal tissue were conducted to\u0000ascertain the width and tortuosity of extracellular spaces across the\u0000epithelium. Using mechanistic mathematical modelling, we show that the\u0000convoluted geometry of extracellular spaces significantly impacts chemical\u0000permeation and that this can be approximated, provided that extracellular\u0000tortuosity is accounted for. We next developed an advanced physically-relevant\u0000in silico model of oral mucosal chemical permeation using partial differential\u0000equations, fitted to chemical permeation in vitro assays on tissue-engineered\u0000human oral mucosa. Tissue geometries were measured and captured in silico, and\u0000permeation examined and predicted for chemicals with different physicochemical\u0000properties. The effect of altering the extracellular space to mimic permeation\u0000enhancers was also assessed by perturbing the in silico model. This novel in\u0000vitro-in silico approach has the potential to expedite pharmaceutical\u0000innovation for testing oromucosal chemical permeation, providing a more\u0000accurate, physiologically-relevant model which can reduce animal testing with\u0000early screening based on chemical properties.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139587172","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}
Julia Camps, Zhinuo Jenny Wang, Ruben Doste, Maxx Holmes, Brodie Lawson, Jakub Tomek, Kevin Burrage, Alfonso Bueno-Orovio, Blanca Rodriguez
Cardiac digital twins are computational tools capturing key functional and anatomical characteristics of patient hearts for investigating disease phenotypes and predicting responses to therapy. When paired with large-scale computational resources and large clinical datasets, digital twin technology can enable virtual clinical trials on virtual cohorts to fast-track therapy development. Here, we present an automated pipeline for personalising ventricular anatomy and electrophysiological function based on routinely acquired cardiac magnetic resonance (CMR) imaging data and the standard 12-lead electrocardiogram (ECG). Using CMR-based anatomical models, a sequential Monte-Carlo approximate Bayesian computational inference method is extended to infer electrical activation and repolarisation characteristics from the ECG. Fast simulations are conducted with a reaction-Eikonal model, including the Purkinje network and biophysically-detailed subcellular ionic current dynamics for repolarisation. For each patient, parameter uncertainty is represented by inferring a population of ventricular models rather than a single one, which means that parameter uncertainty can be propagated to therapy evaluation. Furthermore, we have developed techniques for translating from reaction-Eikonal to monodomain simulations, which allows more realistic simulations of cardiac electrophysiology. The pipeline is demonstrated in a healthy female subject, where our inferred reaction-Eikonal models reproduced the patient's ECG with a Pearson's correlation coefficient of 0.93, and the translated monodomain simulations have a correlation coefficient of 0.89. We then apply the effect of Dofetilide to the monodomain population of models for this subject and show dose-dependent QT and T-peak to T-end prolongations that are in keeping with large population drug response data.
心脏数字孪生是捕捉患者心脏关键功能和解剖特征的计算工具，用于研究疾病表型和预测治疗反应。如果与大规模计算资源和大型临床数据集搭配使用，数字孪生技术就能在虚拟队列中进行虚拟临床试验，从而快速开发疗法。在这里，我们介绍了一种基于常规获取的心脏磁共振（CMR）成像数据和标准 12 导联心电图（ECG）的个性化心室解剖和电生理功能的自动化管道。利用基于 CMR 的解剖模型，将顺序蒙特卡洛近似贝叶斯计算推断方法扩展到从心电图推断电激活和复极化特征。快速模拟采用了反应-Eikonal 模型，包括浦肯野网络和生物物理上详细的亚细胞离子电流动态复极化。此外，我们还开发了从反应-Eikonal 到单域模拟的转换技术，从而可以对心脏电生理进行更真实的模拟。我们在一名健康女性受试者身上演示了这一管道，我们推断出的反应-Eikonal 模型再现了患者的心电图，皮尔逊相关系数为 0.93，转换后的单域模拟相关系数为 0.89。然后，我们将多非利特的效应应用到该受试者的单域模型群体中，结果显示了剂量依赖性 QT 和 T 峰至 T 端延长，这与大量群体药物反应数据相符。
{"title":"Cardiac Digital Twin Pipeline for Virtual Therapy Evaluation","authors":"Julia Camps, Zhinuo Jenny Wang, Ruben Doste, Maxx Holmes, Brodie Lawson, Jakub Tomek, Kevin Burrage, Alfonso Bueno-Orovio, Blanca Rodriguez","doi":"arxiv-2401.10029","DOIUrl":"https://doi.org/arxiv-2401.10029","url":null,"abstract":"Cardiac digital twins are computational tools capturing key functional and\u0000anatomical characteristics of patient hearts for investigating disease\u0000phenotypes and predicting responses to therapy. When paired with large-scale\u0000computational resources and large clinical datasets, digital twin technology\u0000can enable virtual clinical trials on virtual cohorts to fast-track therapy\u0000development. Here, we present an automated pipeline for personalising\u0000ventricular anatomy and electrophysiological function based on routinely\u0000acquired cardiac magnetic resonance (CMR) imaging data and the standard 12-lead\u0000electrocardiogram (ECG). Using CMR-based anatomical models, a sequential\u0000Monte-Carlo approximate Bayesian computational inference method is extended to\u0000infer electrical activation and repolarisation characteristics from the ECG.\u0000Fast simulations are conducted with a reaction-Eikonal model, including the\u0000Purkinje network and biophysically-detailed subcellular ionic current dynamics\u0000for repolarisation. For each patient, parameter uncertainty is represented by\u0000inferring a population of ventricular models rather than a single one, which\u0000means that parameter uncertainty can be propagated to therapy evaluation.\u0000Furthermore, we have developed techniques for translating from reaction-Eikonal\u0000to monodomain simulations, which allows more realistic simulations of cardiac\u0000electrophysiology. The pipeline is demonstrated in a healthy female subject,\u0000where our inferred reaction-Eikonal models reproduced the patient's ECG with a\u0000Pearson's correlation coefficient of 0.93, and the translated monodomain\u0000simulations have a correlation coefficient of 0.89. We then apply the effect of\u0000Dofetilide to the monodomain population of models for this subject and show\u0000dose-dependent QT and T-peak to T-end prolongations that are in keeping with\u0000large population drug response data.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139500644","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}
Y. Ben-Ami, B. D. Wood, J. M. Pitt-Francis, P. K. Maini, H. M. Byrne
In this work we develop a homogenisation methodology to upscale mathematical descriptions of microcirculatory blood flow from the microscale (where individual vessels are resolved) to the macroscopic (or tissue) scale. Due to the assumed two-phase nature of blood and specific features of red blood cells (RBCs), mathematical models for blood flow in the microcirculation are highly nonlinear, coupling the flow and RBC concentrations (haematocrit). In contrast to previous works which accomplished blood-flow homogenisation by assuming that the haematocrit level remains constant, here we allow for spatial heterogeneity in the haematocrit concentration and thus begin with a nonlinear microscale model. We simplify the analysis by considering the limit of small haematocrit heterogeneity which prevails when variations in haematocrit concentration between neighbouring vessels are small. Homogenisation results in a system of coupled, nonlinear partial differential equations describing the flow and haematocrit transport at the macroscale, in which a nonlinear Darcy-type model relates the flow and pressure gradient via a haematocrit-dependent permeability tensor. During the analysis we obtain further that haematocrit transport at the macroscale is governed by a purely advective equation. Applying the theory to particular examples of two- and three-dimensional geometries of periodic networks, we calculate the effective permeability tensor associated with blood flow in these vascular networks. We demonstrate how the statistical distribution of vessel lengths and diameters, together with the average haematocrit level, affect the statistical properties of the macroscopic permeability tensor. These data can be used to simulate blood flow and haematocrit transport at the macroscale.
{"title":"Homogenisation of nonlinear blood flow in periodic networks: the limit of small haematocrit heterogeneity","authors":"Y. Ben-Ami, B. D. Wood, J. M. Pitt-Francis, P. K. Maini, H. M. Byrne","doi":"arxiv-2401.10932","DOIUrl":"https://doi.org/arxiv-2401.10932","url":null,"abstract":"In this work we develop a homogenisation methodology to upscale mathematical\u0000descriptions of microcirculatory blood flow from the microscale (where\u0000individual vessels are resolved) to the macroscopic (or tissue) scale. Due to\u0000the assumed two-phase nature of blood and specific features of red blood cells\u0000(RBCs), mathematical models for blood flow in the microcirculation are highly\u0000nonlinear, coupling the flow and RBC concentrations (haematocrit). In contrast\u0000to previous works which accomplished blood-flow homogenisation by assuming that\u0000the haematocrit level remains constant, here we allow for spatial heterogeneity\u0000in the haematocrit concentration and thus begin with a nonlinear microscale\u0000model. We simplify the analysis by considering the limit of small haematocrit\u0000heterogeneity which prevails when variations in haematocrit concentration\u0000between neighbouring vessels are small. Homogenisation results in a system of\u0000coupled, nonlinear partial differential equations describing the flow and\u0000haematocrit transport at the macroscale, in which a nonlinear Darcy-type model\u0000relates the flow and pressure gradient via a haematocrit-dependent permeability\u0000tensor. During the analysis we obtain further that haematocrit transport at the\u0000macroscale is governed by a purely advective equation. Applying the theory to\u0000particular examples of two- and three-dimensional geometries of periodic\u0000networks, we calculate the effective permeability tensor associated with blood\u0000flow in these vascular networks. We demonstrate how the statistical\u0000distribution of vessel lengths and diameters, together with the average\u0000haematocrit level, affect the statistical properties of the macroscopic\u0000permeability tensor. These data can be used to simulate blood flow and\u0000haematocrit transport at the macroscale.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139552320","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}
Mehdi Ramezanpour, Anne M. Robertson, Yasutaka Tobe, Xiaowei Jia, Juan R. Cebral
Vascular calcification is implicated as an important factor in major adverse cardiovascular events (MACE), including heart attack and stroke. A controversy remains over how to integrate the diverse forms of vascular calcification into clinical risk assessment tools. Even the commonly used calcium score for coronary arteries, which assumes risk scales positively with total calcification, has important inconsistencies. Fundamental studies are needed to determine how risk is influenced by the diverse calcification phenotypes. However, studies of these kinds are hindered by the lack of high-throughput, objective, and non-destructive tools for classifying calcification in imaging data sets. Here, we introduce a new classification system for phenotyping calcification along with a semi-automated, non-destructive pipeline that can distinguish these phenotypes in even atherosclerotic tissues. The pipeline includes a deep-learning-based framework for segmenting lipid pools in noisy micro-CT images and an unsupervised clustering framework for categorizing calcification based on size, clustering, and topology. This approach is illustrated for five vascular specimens, providing phenotyping for thousands of calcification particles across as many as 3200 images in less than seven hours. Average Dice Similarity Coefficients of 0.96 and 0.87 could be achieved for tissue and lipid pool, respectively, with training and validation needed on only 13 images despite the high heterogeneity in these tissues. By introducing an efficient and comprehensive approach to phenotyping calcification, this work enables large-scale studies to identify a more reliable indicator of the risk of cardiovascular events, a leading cause of global mortality and morbidity.
{"title":"Phenotyping calcification in vascular tissues using artificial intelligence","authors":"Mehdi Ramezanpour, Anne M. Robertson, Yasutaka Tobe, Xiaowei Jia, Juan R. Cebral","doi":"arxiv-2401.07825","DOIUrl":"https://doi.org/arxiv-2401.07825","url":null,"abstract":"Vascular calcification is implicated as an important factor in major adverse\u0000cardiovascular events (MACE), including heart attack and stroke. A controversy\u0000remains over how to integrate the diverse forms of vascular calcification into\u0000clinical risk assessment tools. Even the commonly used calcium score for\u0000coronary arteries, which assumes risk scales positively with total\u0000calcification, has important inconsistencies. Fundamental studies are needed to\u0000determine how risk is influenced by the diverse calcification phenotypes.\u0000However, studies of these kinds are hindered by the lack of high-throughput,\u0000objective, and non-destructive tools for classifying calcification in imaging\u0000data sets. Here, we introduce a new classification system for phenotyping\u0000calcification along with a semi-automated, non-destructive pipeline that can\u0000distinguish these phenotypes in even atherosclerotic tissues. The pipeline\u0000includes a deep-learning-based framework for segmenting lipid pools in noisy\u0000micro-CT images and an unsupervised clustering framework for categorizing\u0000calcification based on size, clustering, and topology. This approach is\u0000illustrated for five vascular specimens, providing phenotyping for thousands of\u0000calcification particles across as many as 3200 images in less than seven hours.\u0000Average Dice Similarity Coefficients of 0.96 and 0.87 could be achieved for\u0000tissue and lipid pool, respectively, with training and validation needed on\u0000only 13 images despite the high heterogeneity in these tissues. By introducing\u0000an efficient and comprehensive approach to phenotyping calcification, this work\u0000enables large-scale studies to identify a more reliable indicator of the risk\u0000of cardiovascular events, a leading cause of global mortality and morbidity.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483144","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}
Benjamin SchneiderISU, Sébastien BenzekryCOMPO, Jonathan MochelISU
First-line antiproliferatives for non-small cell lung cancer (NSCLC) have a relatively high failure rate due to high intrinsic resistance rates and acquired resistance rates to therapy. 57% patients are diagnosed in late-stage disease due to the tendency of early-stage NSCLC to be asymptomatic. For patients first diagnosed with metastatic disease the 5-year survival rate is approximately 5%. To help accelerate the development of novel therapeutics and computer-based tools for optimizing individual therapy, we have collated data from 11 different clinical trials in NSCLC and developed a semi-mechanistic, clinical model of NSCLC growth and pharmacodynamics relative to the various therapeutics represented in the study. In this study, we have produced extremely precise estimates of clinical parameters fundamental to cancer modeling such as the rate of acquired resistance to various pharmaceuticals, the relationship between drug concentration and rate of cancer cell death, as well as the fine temporal dynamics of anti-VEGF therapy. In the simulation sets documented in this study, we have used the model to make meaningful descriptions of efficacy gain in making bevacizumab-antiproliferative combination therapy sequential, over a series of days, rather than concurrent.
{"title":"Comprehensive Joint Modeling of First-Line Therapeutics in Non-Small Cell Lung Cancer","authors":"Benjamin SchneiderISU, Sébastien BenzekryCOMPO, Jonathan MochelISU","doi":"arxiv-2401.07719","DOIUrl":"https://doi.org/arxiv-2401.07719","url":null,"abstract":"First-line antiproliferatives for non-small cell lung cancer (NSCLC) have a\u0000relatively high failure rate due to high intrinsic resistance rates and\u0000acquired resistance rates to therapy. 57% patients are diagnosed in late-stage\u0000disease due to the tendency of early-stage NSCLC to be asymptomatic. For\u0000patients first diagnosed with metastatic disease the 5-year survival rate is\u0000approximately 5%. To help accelerate the development of novel therapeutics and\u0000computer-based tools for optimizing individual therapy, we have collated data\u0000from 11 different clinical trials in NSCLC and developed a semi-mechanistic,\u0000clinical model of NSCLC growth and pharmacodynamics relative to the various\u0000therapeutics represented in the study. In this study, we have produced\u0000extremely precise estimates of clinical parameters fundamental to cancer\u0000modeling such as the rate of acquired resistance to various pharmaceuticals,\u0000the relationship between drug concentration and rate of cancer cell death, as\u0000well as the fine temporal dynamics of anti-VEGF therapy. In the simulation sets\u0000documented in this study, we have used the model to make meaningful\u0000descriptions of efficacy gain in making bevacizumab-antiproliferative\u0000combination therapy sequential, over a series of days, rather than concurrent.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483203","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}
Iron accumulates in the neural tissue during peripheral nerve degeneration. Some studies have already been suggested that iron facilitates Wallerian degeneration (WD) events such as Schwann cell de-differentiation. On the other hand, intracellular iron levels remain elevated during nerve regeneration and gradually decrease. Iron enhances Schwann cell differentiation and axonal outgrowth. Therefore, there seems to be a paradox in the role of iron during nerve degeneration and regeneration. We explain this contradiction by suggesting that the increase in intracellular iron concentration during peripheral nerve degeneration is likely to prepare neural cells for the initiation of regeneration. Changes in iron levels are the result of changes in the expression of iron homeostasis proteins. In this review, we will first discuss the changes in the iron/iron homeostasis protein levels during peripheral nerve degeneration and regeneration and then explain how iron is related to nerve regeneration. This data may help better understand the mechanisms of peripheral nerve repair and find a solution to prevent or slow the progression of peripheral neuropathies.
{"title":"Iron role paradox in nerve degeneration and regeneration","authors":"Samira Bolandghamat, Morteza Behnam-Rassouli","doi":"arxiv-2401.07016","DOIUrl":"https://doi.org/arxiv-2401.07016","url":null,"abstract":"Iron accumulates in the neural tissue during peripheral nerve degeneration.\u0000Some studies have already been suggested that iron facilitates Wallerian\u0000degeneration (WD) events such as Schwann cell de-differentiation. On the other\u0000hand, intracellular iron levels remain elevated during nerve regeneration and\u0000gradually decrease. Iron enhances Schwann cell differentiation and axonal\u0000outgrowth. Therefore, there seems to be a paradox in the role of iron during\u0000nerve degeneration and regeneration. We explain this contradiction by\u0000suggesting that the increase in intracellular iron concentration during\u0000peripheral nerve degeneration is likely to prepare neural cells for the\u0000initiation of regeneration. Changes in iron levels are the result of changes in\u0000the expression of iron homeostasis proteins. In this review, we will first\u0000discuss the changes in the iron/iron homeostasis protein levels during\u0000peripheral nerve degeneration and regeneration and then explain how iron is\u0000related to nerve regeneration. This data may help better understand the\u0000mechanisms of peripheral nerve repair and find a solution to prevent or slow\u0000the progression of peripheral neuropathies.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483145","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}
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