Akhila Krishna, Ravi Kant Gupta, Pranav Jeevan, Amit Sethi
Gene selection plays a pivotal role in oncology research for improving outcome prediction accuracy and facilitating cost-effective genomic profiling for cancer patients. This paper introduces two gene selection strategies for deep learning-based survival prediction models. The first strategy uses a sparsity-inducing method while the second one uses importance based gene selection for identifying relevant genes. Our overall approach leverages the power of deep learning to model complex biological data structures, while sparsity-inducing methods ensure the selection process focuses on the most informative genes, minimizing noise and redundancy. Through comprehensive experimentation on diverse genomic and survival datasets, we demonstrate that our strategy not only identifies gene signatures with high predictive power for survival outcomes but can also streamlines the process for low-cost genomic profiling. The implications of this research are profound as it offers a scalable and effective tool for advancing personalized medicine and targeted cancer therapies. By pushing the boundaries of gene selection methodologies, our work contributes significantly to the ongoing efforts in cancer genomics, promising improved diagnostic and prognostic capabilities in clinical settings.
{"title":"Advancing Gene Selection in Oncology: A Fusion of Deep Learning and Sparsity for Precision Gene Selection","authors":"Akhila Krishna, Ravi Kant Gupta, Pranav Jeevan, Amit Sethi","doi":"arxiv-2403.01927","DOIUrl":"https://doi.org/arxiv-2403.01927","url":null,"abstract":"Gene selection plays a pivotal role in oncology research for improving\u0000outcome prediction accuracy and facilitating cost-effective genomic profiling\u0000for cancer patients. This paper introduces two gene selection strategies for\u0000deep learning-based survival prediction models. The first strategy uses a\u0000sparsity-inducing method while the second one uses importance based gene\u0000selection for identifying relevant genes. Our overall approach leverages the\u0000power of deep learning to model complex biological data structures, while\u0000sparsity-inducing methods ensure the selection process focuses on the most\u0000informative genes, minimizing noise and redundancy. Through comprehensive\u0000experimentation on diverse genomic and survival datasets, we demonstrate that\u0000our strategy not only identifies gene signatures with high predictive power for\u0000survival outcomes but can also streamlines the process for low-cost genomic\u0000profiling. The implications of this research are profound as it offers a\u0000scalable and effective tool for advancing personalized medicine and targeted\u0000cancer therapies. By pushing the boundaries of gene selection methodologies,\u0000our work contributes significantly to the ongoing efforts in cancer genomics,\u0000promising improved diagnostic and prognostic capabilities in clinical settings.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140035448","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}
Roman Cherniha, Joanna Stachowska-Pietka, Jacek Waniewski
Using well-known mathematical foundations of the elasticity theory, a mathematical model for two solutes transport in a poroelastic material (soft tissue is a typical example) is suggested. It is assumed that molecules of essentially different sizes dissolved in fluid and are transported through pores of different sizes. The stress tensor, the main force leading to the material deformation, is taken not only in the standard linear form but also with an additional nonlinear part. The model is constructed in 1D space and consists of six nonlinear equations. It is shown that the governing equations are integrable in stationary case, therefore all steady-state solutions are constructed. The obtained solutions are used in an example for healthy and tumour tissue, in particular, tissue displacements are calculated and compared for parameters taken from experimental data in cases of the linear and nonlinear stress tensors. Since the governing equations are non-integrable in non-stationary case, the Lie symmetry analysis is used in order to construct time-dependent exact solutions. Depending on parameters arising in the governing equations, several special cases with non-trivial Lie symmetries are identified. As a result, multi-parameter families of exact solutions are constructed including those in terms of special functions(hypergeometric and Bessel functions). A possible application of the solutions obtained is demonstrated.
{"title":"A Mathematical Model for Two Solutes Transport in a Poroelastic Material and Its Applications","authors":"Roman Cherniha, Joanna Stachowska-Pietka, Jacek Waniewski","doi":"arxiv-2403.00216","DOIUrl":"https://doi.org/arxiv-2403.00216","url":null,"abstract":"Using well-known mathematical foundations of the elasticity theory, a\u0000mathematical model for two solutes transport in a poroelastic material (soft\u0000tissue is a typical example) is suggested. It is assumed that molecules of\u0000essentially different sizes dissolved in fluid and are transported through\u0000pores of different sizes. The stress tensor, the main force leading to the\u0000material deformation, is taken not only in the standard linear form but also\u0000with an additional nonlinear part. The model is constructed in 1D space and\u0000consists of six nonlinear equations. It is shown that the governing equations\u0000are integrable in stationary case, therefore all steady-state solutions are\u0000constructed. The obtained solutions are used in an example for healthy and\u0000tumour tissue, in particular, tissue displacements are calculated and compared\u0000for parameters taken from experimental data in cases of the linear and\u0000nonlinear stress tensors. Since the governing equations are non-integrable in\u0000non-stationary case, the Lie symmetry analysis is used in order to construct\u0000time-dependent exact solutions. Depending on parameters arising in the\u0000governing equations, several special cases with non-trivial Lie symmetries are\u0000identified. As a result, multi-parameter families of exact solutions are\u0000constructed including those in terms of special functions(hypergeometric and\u0000Bessel functions). A possible application of the solutions obtained is\u0000demonstrated.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140035445","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}
Takumi Ogawa, Shuji Koyama, Toshihiro Omori, Kenji Kikuchi, Helene de Maleprade, Raymond E. Goldstein, Takuji Ishikawa
Sponges, the basalmost members of the animal kingdom, exhibit a range of complex architectures in which microfluidic channels connect multitudes of spherical chambers lined with choanocytes, flagellated filter-feeding cells. Choanocyte chambers can possess scores or even hundreds of such cells, which drive complex flows entering through porous walls and exiting into the sponge channels. One of the mysteries of the choanocyte chamber is its spherical shape, as it seems inappropriate for inducing directional transport since many choanocyte flagella beat in opposition to such a flow. Here we combine direct imaging of choanocyte chambers in living sponges with computational studies of many-flagella models to understand the connection between chamber architecture and directional flow. We find that those flagella that beat against the flow play a key role in raising the pressure inside the choanocyte chamber, with the result that the mechanical pumping efficiency, calculated from the pressure rise and flow rate, reaches a maximum at a small outlet opening angle. Comparison between experimental observations and the results of numerical simulations reveal that the chamber diameter, flagellar wave number and the outlet opening angle of the freshwater sponge $E. muelleri$, as well as several other species, are related in a manner that maximizes the mechanical pumping efficiency. These results indicate the subtle balances at play during morphogenesis of choanocyte chambers, and give insights into the physiology and body design of sponges.
海绵是动物界最底层的成员，具有一系列复杂的结构，其中微流体通道连接着许多球形腔室，腔室内衬有绒毛细胞（鞭毛滤食细胞）。绒毛细胞腔室可以拥有几十个甚至上百个这样的细胞，它们驱动复杂的水流通过多孔壁进入海绵腔室，然后流出。藻细胞室的奥秘之一是它的球形，因为它似乎不适合诱导定向运输，因为许多藻细胞鞭毛的跳动与这种流动相反。在这里，我们将活体海绵绒毛细胞腔的直接成像与多鞭毛虫模型的计算研究结合起来，以了解细胞腔结构与定向流动之间的联系。我们发现，那些逆流拍打的鞭毛在提高绒毛细胞腔内压力方面起着关键作用，其结果是，根据压力上升和流速计算出的机械泵效率在较小的出口张开角度时达到最大值。将实验观察结果与数值模拟结果进行比较后发现，淡水海绵 E. muelleri$ 以及其他一些物种的腔直径、鞭毛波数和出口张开角度之间的关系能使机械泵效率达到最大值。这些结果表明了绒毛膜腔在形态发生过程中的微妙平衡，并对海绵的生理学和身体设计提供了启示。
{"title":"The Architecture of Sponge Choanocyte Chambers Maximizes Mechanical Pumping Efficiency","authors":"Takumi Ogawa, Shuji Koyama, Toshihiro Omori, Kenji Kikuchi, Helene de Maleprade, Raymond E. Goldstein, Takuji Ishikawa","doi":"arxiv-2402.14364","DOIUrl":"https://doi.org/arxiv-2402.14364","url":null,"abstract":"Sponges, the basalmost members of the animal kingdom, exhibit a range of\u0000complex architectures in which microfluidic channels connect multitudes of\u0000spherical chambers lined with choanocytes, flagellated filter-feeding cells.\u0000Choanocyte chambers can possess scores or even hundreds of such cells, which\u0000drive complex flows entering through porous walls and exiting into the sponge\u0000channels. One of the mysteries of the choanocyte chamber is its spherical\u0000shape, as it seems inappropriate for inducing directional transport since many\u0000choanocyte flagella beat in opposition to such a flow. Here we combine direct\u0000imaging of choanocyte chambers in living sponges with computational studies of\u0000many-flagella models to understand the connection between chamber architecture\u0000and directional flow. We find that those flagella that beat against the flow\u0000play a key role in raising the pressure inside the choanocyte chamber, with the\u0000result that the mechanical pumping efficiency, calculated from the pressure\u0000rise and flow rate, reaches a maximum at a small outlet opening angle.\u0000Comparison between experimental observations and the results of numerical\u0000simulations reveal that the chamber diameter, flagellar wave number and the\u0000outlet opening angle of the freshwater sponge $E. muelleri$, as well as several\u0000other species, are related in a manner that maximizes the mechanical pumping\u0000efficiency. These results indicate the subtle balances at play during\u0000morphogenesis of choanocyte chambers, and give insights into the physiology and\u0000body design of sponges.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139951246","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}
Morteza Rasouligandomani, Alex del Arco, Francis Kiptengwer Chemorion, Marc-Antonio Bisotti, Fabio Galbusera, Jerome Noailly, Miguel Angel Gonzalez Ballester
Adult spine deformity (ASD) is prevalent and leads to a sagittal misalignment in the vertebral column. Computational methods, including Finite Element (FE) Models, have emerged as valuable tools for investigating the causes and treatment of ASD through biomechanical simulations. However, the process of generating personalized FE models is often complex and time-consuming. To address this challenge, we present a repository of FE models with diverse spine morphologies that statistically represent real geometries from a cohort of patients. These models are generated using EOS images, which are utilized to reconstruct 3D surface spine models. Subsequently, a Statistical Shape Model (SSM) is constructed, enabling the adaptation of a FE hexahedral mesh template for both the bone and soft tissues of the spine through mesh morphing. The SSM deformation fields facilitate the personalization of the mean hexahedral FE model based on sagittal balance measurements. Ultimately, this new hexahedral SSM tool offers a means to generate a virtual cohort of 16807 thoracolumbar FE spine models, which are openly shared in a public repository.
成人脊柱畸形（ASD）很普遍，会导致椎体矢状位错位。包括有限元（FE）模型在内的计算方法已成为通过生物力学模拟研究 ASD 病因和治疗方法的重要工具。然而，生成个性化 FE 模型的过程通常既复杂又耗时。为了解决这一难题，我们建立了一个具有不同脊柱形态的 FE 模型库，这些模型在统计学上代表了一批患者的真实几何形态。这些模型使用 EOS 图像生成，并利用这些图像重建三维表面脊柱模型。随后，构建统计形状模型（SSM），通过网格变形，使脊柱的骨骼和软组织都能适应 FE 六面体网格模板。SSM 变形域有助于根据矢状面平衡测量结果对平均六面体 FE 模型进行个性化定制。最终，这一新的六面体 SSM 工具提供了一种生成 16807 个胸腰椎 FE 脊柱模型的虚拟队列的方法，这些模型在公共存储库中公开共享。
{"title":"Data Repository of Finite Element Models of Normal and Deformed Thoracolumbar Spine","authors":"Morteza Rasouligandomani, Alex del Arco, Francis Kiptengwer Chemorion, Marc-Antonio Bisotti, Fabio Galbusera, Jerome Noailly, Miguel Angel Gonzalez Ballester","doi":"arxiv-2402.13041","DOIUrl":"https://doi.org/arxiv-2402.13041","url":null,"abstract":"Adult spine deformity (ASD) is prevalent and leads to a sagittal misalignment\u0000in the vertebral column. Computational methods, including Finite Element (FE)\u0000Models, have emerged as valuable tools for investigating the causes and\u0000treatment of ASD through biomechanical simulations. However, the process of\u0000generating personalized FE models is often complex and time-consuming. To\u0000address this challenge, we present a repository of FE models with diverse spine\u0000morphologies that statistically represent real geometries from a cohort of\u0000patients. These models are generated using EOS images, which are utilized to\u0000reconstruct 3D surface spine models. Subsequently, a Statistical Shape Model\u0000(SSM) is constructed, enabling the adaptation of a FE hexahedral mesh template\u0000for both the bone and soft tissues of the spine through mesh morphing. The SSM\u0000deformation fields facilitate the personalization of the mean hexahedral FE\u0000model based on sagittal balance measurements. Ultimately, this new hexahedral\u0000SSM tool offers a means to generate a virtual cohort of 16807 thoracolumbar FE\u0000spine models, which are openly shared in a public repository.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139921102","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}
Timothy J Tyree, Patrick Murphy, Wouter-Jan Rappel
Pair-annihilation events are ubiquitous in a variety of spatially extended systems and are often studied using computationally expensive simulations. Here we develop an approach in which we simulate the pair-annihilation of spiral wave tips in cardiac models using a computationally efficient particle model. Spiral wave tips are represented as particles with dynamics governed by diffusive behavior and short-ranged attraction. The parameters for diffusion and attraction are obtained by comparing particle motion to the trajectories of spiral wave tips in cardiac models during spiral defect chaos. The particle model reproduces the annihilation rates of the cardiac models and can determine the statistics of spiral wave dynamics, including its mean termination time. We show that increasing the attraction coefficient sharply decreases the mean termination time, making it a possible target for pharmaceutical intervention
{"title":"Annihilation dynamics during spiral defect chaos revealed by particle models","authors":"Timothy J Tyree, Patrick Murphy, Wouter-Jan Rappel","doi":"arxiv-2402.10308","DOIUrl":"https://doi.org/arxiv-2402.10308","url":null,"abstract":"Pair-annihilation events are ubiquitous in a variety of spatially extended\u0000systems and are often studied using computationally expensive simulations. Here\u0000we develop an approach in which we simulate the pair-annihilation of spiral\u0000wave tips in cardiac models using a computationally efficient particle model.\u0000Spiral wave tips are represented as particles with dynamics governed by\u0000diffusive behavior and short-ranged attraction. The parameters for diffusion\u0000and attraction are obtained by comparing particle motion to the trajectories of\u0000spiral wave tips in cardiac models during spiral defect chaos. The particle\u0000model reproduces the annihilation rates of the cardiac models and can determine\u0000the statistics of spiral wave dynamics, including its mean termination time. We\u0000show that increasing the attraction coefficient sharply decreases the mean\u0000termination time, making it a possible target for pharmaceutical intervention","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902790","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}
Sarah Zaidan, Syamsudin Abdillah, Nur Arfian, Wawaimuli Arozal
The purpose of this study was to obtain natural drugs from brown seaweed (Sargassum crassifolium) as antiatherosclerosis candidates through the study of hypolipidemic mechanisms of action. Modeling of dyslipidemia rats was carried out by feeding high-fat (HFF) and doses of crude fucoidan 100. 200. 400mg / KgBB. in both treatments measured blood lipid profile levels taken from the orbital sinuses. HE's histopathology. mRNA expression. immunohistochemistry (IHC) with parameters VCAM-1. ICAM-1. and MCP-1 were performed on adipose tissue. as well as liver. Total cholesterol values 51.07-225.2. triglycerides 30.43-115.73. HDL 13.1-24.86 mg/dl and LDL 20.22-189.68 mg/dl. In the treatment of crude fucoidan obtained the result of p value < {alpha} (0.05. Histopathological features of adipose tissue after administration of HFF for 60 days resulted in an increase in adipose cell size. and the liver experienced structural damage and inflammation. but after 21 days of treatment the morphological picture of adipose tissue was similar to normal morphology and the liver also decreased in severity and inflammation. The results of histochemical staining after treatment showed a positive staining part on MCP-1. The result of p value < {alpha} (0.05) of mRNA expression for administration of 3 treatment doses. A dyslipidemic mouse model with HFF administration for 60 days succeeded in becoming a dyslipidemic rat. and crude fucoidan had hypolipidemic activity. Doses of 100. 200. and 400 mg/KgBB crude fucoidan showed improvement in adipose and liver morphological features of severity and inflammation of dyslipidemic rats and decreased mRNA expression.
{"title":"Hypolipidemic effect of brown seaweed (Sargassum crassifolium) extract in vivo (Study of histopathology, mRNA expression, and immunohistochemistry (IHC) with VCAM-1, ICAM-1, and MCP-1 parameters)","authors":"Sarah Zaidan, Syamsudin Abdillah, Nur Arfian, Wawaimuli Arozal","doi":"arxiv-2402.07497","DOIUrl":"https://doi.org/arxiv-2402.07497","url":null,"abstract":"The purpose of this study was to obtain natural drugs from brown seaweed\u0000(Sargassum crassifolium) as antiatherosclerosis candidates through the study of\u0000hypolipidemic mechanisms of action. Modeling of dyslipidemia rats was carried\u0000out by feeding high-fat (HFF) and doses of crude fucoidan 100. 200. 400mg /\u0000KgBB. in both treatments measured blood lipid profile levels taken from the\u0000orbital sinuses. HE's histopathology. mRNA expression. immunohistochemistry\u0000(IHC) with parameters VCAM-1. ICAM-1. and MCP-1 were performed on adipose\u0000tissue. as well as liver. Total cholesterol values 51.07-225.2. triglycerides\u000030.43-115.73. HDL 13.1-24.86 mg/dl and LDL 20.22-189.68 mg/dl. In the treatment\u0000of crude fucoidan obtained the result of p value < {alpha} (0.05.\u0000Histopathological features of adipose tissue after administration of HFF for 60\u0000days resulted in an increase in adipose cell size. and the liver experienced\u0000structural damage and inflammation. but after 21 days of treatment the\u0000morphological picture of adipose tissue was similar to normal morphology and\u0000the liver also decreased in severity and inflammation. The results of\u0000histochemical staining after treatment showed a positive staining part on\u0000MCP-1. The result of p value < {alpha} (0.05) of mRNA expression for\u0000administration of 3 treatment doses. A dyslipidemic mouse model with HFF\u0000administration for 60 days succeeded in becoming a dyslipidemic rat. and crude\u0000fucoidan had hypolipidemic activity. Doses of 100. 200. and 400 mg/KgBB crude\u0000fucoidan showed improvement in adipose and liver morphological features of\u0000severity and inflammation of dyslipidemic rats and decreased mRNA expression.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139773560","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}
Mariia Soloviova, Juan Carlos Beltran Vargas, Luis Fernandez de Castro, Juan Belmonte-Beitia, Víctor M. Pérez-García, Magdalena Caballero
Fibrous dysplasia (FD) is a mosaic non-inheritable genetic disorder of the skeleton in which normal bone is replaced by structurally unsound fibro-osseous tissue. There is no curative treatment for FD, partly because its pathophysiology is not yet fully known. We present a simple mathematical model of the disease incorporating its basic known biology, to gain insight on the dynamics of the involved bone-cell populations, and shed light on its pathophysiology. Our mathematical models account for the dynamic evolution over time of several interacting populations of bone cells averaged over a volume of bone of sufficient size in order to obtain consistent results. We develop an analytical study of the model and study its basic properties. The existence and stability of steady states are studied, an analysis of sensitivity on the model parameters is done, and different numerical simulations provide findings in agreement with the analytical results. We discuss the model dynamics match with known facts on the disease, and how some open questions could be addressed using the model.
{"title":"A mathematical model for fibrous dysplasia: The role of the flow of mutant cells","authors":"Mariia Soloviova, Juan Carlos Beltran Vargas, Luis Fernandez de Castro, Juan Belmonte-Beitia, Víctor M. Pérez-García, Magdalena Caballero","doi":"arxiv-2402.07724","DOIUrl":"https://doi.org/arxiv-2402.07724","url":null,"abstract":"Fibrous dysplasia (FD) is a mosaic non-inheritable genetic disorder of the\u0000skeleton in which normal bone is replaced by structurally unsound fibro-osseous\u0000tissue. There is no curative treatment for FD, partly because its\u0000pathophysiology is not yet fully known. We present a simple mathematical model\u0000of the disease incorporating its basic known biology, to gain insight on the\u0000dynamics of the involved bone-cell populations, and shed light on its\u0000pathophysiology. Our mathematical models account for the dynamic evolution over\u0000time of several interacting populations of bone cells averaged over a volume of\u0000bone of sufficient size in order to obtain consistent results. We develop an\u0000analytical study of the model and study its basic properties. The existence and\u0000stability of steady states are studied, an analysis of sensitivity on the model\u0000parameters is done, and different numerical simulations provide findings in\u0000agreement with the analytical results. We discuss the model dynamics match with\u0000known facts on the disease, and how some open questions could be addressed\u0000using the model.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772442","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}
Fabrication of tissue engineering scaffolds with tailored physicochemical and biological characteristics is a relevant task in biomedical engineering. The present work was focused at the evaluation of the effect of fabrication approach (single-channel or multi-channel electrospinning) on the properties of the fabricated poly(lactic acid)(PLA)/poly(epsilon-caprolactone)(PCL) scaffolds with various polymer mass ratios (1/0, 2/1, 1/1, 1/2, and 0/1). The scaffolds with same morphology (regardless of electrospinning variant) were fabricated and characterized using SEM, water contact angle measurement, FTIR, XRD, tensile testing and in vitro experiment with multipotent mesenchymal stem cells. It was demonstrated, that multi-channel electrospinning prevents intermolecular interactions between the polymer components of the scaffold, preserving their crystal structure, what affects the mechanical characteristics of the scaffold (particularly, leads to 2-fold difference in elongation). Better adhesion of multipotent mesenchymal stem cells on the surface of the scaffolds fabricated using multichannel electrospinning was demonstrated.
{"title":"Single-channel and multi-channel electrospinning for the fabrication of PLA/PCL tissue engineering scaffolds: comparative study of the materials physicochemical and biological properties","authors":"Semen Goreninskii, Ulyana Chernova, Elisaveta Prosetskaya, Alina Laushkina, Alexander Mishanin, Alexey Golovkin, Evgeny Bolbasov","doi":"arxiv-2403.00767","DOIUrl":"https://doi.org/arxiv-2403.00767","url":null,"abstract":"Fabrication of tissue engineering scaffolds with tailored physicochemical and\u0000biological characteristics is a relevant task in biomedical engineering. The\u0000present work was focused at the evaluation of the effect of fabrication\u0000approach (single-channel or multi-channel electrospinning) on the properties of\u0000the fabricated poly(lactic acid)(PLA)/poly(epsilon-caprolactone)(PCL) scaffolds\u0000with various polymer mass ratios (1/0, 2/1, 1/1, 1/2, and 0/1). The scaffolds\u0000with same morphology (regardless of electrospinning variant) were fabricated\u0000and characterized using SEM, water contact angle measurement, FTIR, XRD,\u0000tensile testing and in vitro experiment with multipotent mesenchymal stem\u0000cells. It was demonstrated, that multi-channel electrospinning prevents\u0000intermolecular interactions between the polymer components of the scaffold,\u0000preserving their crystal structure, what affects the mechanical characteristics\u0000of the scaffold (particularly, leads to 2-fold difference in elongation).\u0000Better adhesion of multipotent mesenchymal stem cells on the surface of the\u0000scaffolds fabricated using multichannel electrospinning was demonstrated.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140035712","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}
One of the most crucial and lethal characteristics of solid tumors is represented by the increased ability of cancer cells to migrate and invade other organs during the so-called metastatic spread. This is allowed thanks to the production of matrix metalloproteinases (MMPs), enzymes capable of degrading a type of collagen abundant in the basal membrane separating the epithelial tissue from the connective one. In this work, we employ a synergistic experimental and mathematical modelling approach to explore the invasion process of tumor cells. A athematical model composed of reaction-diffusion equations describing the evolution of the tumor cells density on a gelatin substrate, MMPs enzymes concentration and the degradation of the gelatin is proposed. This is completed with a calibration strategy. We perform a sensitivity analysis and explore a parameter estimation technique both on synthetic and experimental data in order to find the optimal parameters that describe the in vitro experiments. A comparison between numerical and experimental solutions ends the work.
{"title":"A model for membrane degradation using a gelatin invadopodia assay","authors":"Giorgia Ciavolella, Nathalie Ferrand, Michèle Sabbah, Benoît Perthame, Roberto Natalini","doi":"arxiv-2404.05730","DOIUrl":"https://doi.org/arxiv-2404.05730","url":null,"abstract":"One of the most crucial and lethal characteristics of solid tumors is\u0000represented by the increased ability of cancer cells to migrate and invade\u0000other organs during the so-called metastatic spread. This is allowed thanks to\u0000the production of matrix metalloproteinases (MMPs), enzymes capable of\u0000degrading a type of collagen abundant in the basal membrane separating the\u0000epithelial tissue from the connective one. In this work, we employ a\u0000synergistic experimental and mathematical modelling approach to explore the\u0000invasion process of tumor cells. A athematical model composed of\u0000reaction-diffusion equations describing the evolution of the tumor cells\u0000density on a gelatin substrate, MMPs enzymes concentration and the degradation\u0000of the gelatin is proposed. This is completed with a calibration strategy. We\u0000perform a sensitivity analysis and explore a parameter estimation technique\u0000both on synthetic and experimental data in order to find the optimal parameters\u0000that describe the in vitro experiments. A comparison between numerical and\u0000experimental solutions ends the work.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140584832","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}
Jixin Hou, Xianyan Chen, Taotao Wu, Ellen Kuhl, Xianqiao Wang
We introduce a data-driven framework to automatically identify interpretable and physically meaningful hyperelastic constitutive models from sparse data. Leveraging symbolic regression, an algorithm based on genetic programming, our approach generates elegant hyperelastic models that achieve accurate data fitting through parsimonious mathematic formulae, while strictly adhering to hyperelasticity constraints such as polyconvexity. Our investigation spans three distinct hyperelastic models -- invariant-based, principal stretch-based, and normal strain-based -- and highlights the versatility of symbolic regression. We validate our new approach using synthetic data from five classic hyperelastic models and experimental data from the human brain to demonstrate algorithmic efficacy. Our results suggest that our symbolic regression robustly discovers accurate models with succinct mathematic expressions in invariant-based, stretch-based, and strain-based scenarios. Strikingly, the strain-based model exhibits superior accuracy, while both stretch- and strain-based models effectively capture the nonlinearity and tension-compression asymmetry inherent to human brain tissue. Polyconvexity examinations affirm the rigor of convexity within the training regime and demonstrate excellent extrapolation capabilities beyond this regime for all three models. However, the stretch-based models raise concerns regarding potential convexity loss under large deformations. Finally, robustness tests on noise-embedded data underscore the reliability of our symbolic regression algorithms. Our study confirms the applicability and accuracy of symbolic regression in the automated discovery of hyperelastic models for the human brain and gives rise to a wide variety of applications in other soft matter systems.
{"title":"Automated Data-Driven Discovery of Material Models Based on Symbolic Regression: A Case Study on Human Brain Cortex","authors":"Jixin Hou, Xianyan Chen, Taotao Wu, Ellen Kuhl, Xianqiao Wang","doi":"arxiv-2402.05238","DOIUrl":"https://doi.org/arxiv-2402.05238","url":null,"abstract":"We introduce a data-driven framework to automatically identify interpretable\u0000and physically meaningful hyperelastic constitutive models from sparse data.\u0000Leveraging symbolic regression, an algorithm based on genetic programming, our\u0000approach generates elegant hyperelastic models that achieve accurate data\u0000fitting through parsimonious mathematic formulae, while strictly adhering to\u0000hyperelasticity constraints such as polyconvexity. Our investigation spans\u0000three distinct hyperelastic models -- invariant-based, principal stretch-based,\u0000and normal strain-based -- and highlights the versatility of symbolic\u0000regression. We validate our new approach using synthetic data from five classic\u0000hyperelastic models and experimental data from the human brain to demonstrate\u0000algorithmic efficacy. Our results suggest that our symbolic regression robustly\u0000discovers accurate models with succinct mathematic expressions in\u0000invariant-based, stretch-based, and strain-based scenarios. Strikingly, the\u0000strain-based model exhibits superior accuracy, while both stretch- and\u0000strain-based models effectively capture the nonlinearity and\u0000tension-compression asymmetry inherent to human brain tissue. Polyconvexity\u0000examinations affirm the rigor of convexity within the training regime and\u0000demonstrate excellent extrapolation capabilities beyond this regime for all\u0000three models. However, the stretch-based models raise concerns regarding\u0000potential convexity loss under large deformations. Finally, robustness tests on\u0000noise-embedded data underscore the reliability of our symbolic regression\u0000algorithms. Our study confirms the applicability and accuracy of symbolic\u0000regression in the automated discovery of hyperelastic models for the human\u0000brain and gives rise to a wide variety of applications in other soft matter\u0000systems.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772437","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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