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Development and Retrospective Clinical Assessment of a Patient-Specific Closed-Form Integro-Differential Equation Model of Plasma Dilution. 血浆稀释患者特异性闭式积分-微分方程模型的建立和回顾性临床评估。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2017-10-26 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217730305
Glen Atlas, John K-J Li, Shawn Amin, Robert G Hahn

A closed-form integro-differential equation (IDE) model of plasma dilution (PD) has been derived which represents both the intravenous (IV) infusion of crystalloid and the postinfusion period. Specifically, PD is mathematically represented using a combination of constant ratio, differential, and integral components. Furthermore, this model has successfully been applied to preexisting data, from a prior human study, in which crystalloid was infused for a period of 30 minutes at the beginning of thyroid surgery. Using Euler's formula and a Laplace transform solution to the IDE, patients could be divided into two distinct groups based on their response to PD during the infusion period. Explicitly, Group 1 patients had an infusion-based PD response which was modeled using an exponentially decaying hyperbolic sine function, whereas Group 2 patients had an infusion-based PD response which was modeled using an exponentially decaying trigonometric sine function. Both Group 1 and Group 2 patients had postinfusion PD responses which were modeled using the same combination of hyperbolic sine and hyperbolic cosine functions. Statistically significant differences, between Groups 1 and 2, were noted with respect to the area under their PD curves during both the infusion and postinfusion periods. Specifically, Group 2 patients exhibited a response to PD which was most likely consistent with a preoperative hypovolemia. Overall, this IDE model of PD appears to be highly "adaptable" and successfully fits clinically-obtained human data on a patient-specific basis, during both the infusion and postinfusion periods. In addition, patient-specific IDE modeling of PD may be a useful adjunct in perioperative fluid management and in assessing clinical volume kinetics, of crystalloid solutions, in real time.

本文建立了一种反映晶体药物静脉输注和输注后血浆稀释(PD)的闭型积分-微分方程(IDE)模型。具体地说,PD是用常数比、微分和积分分量的组合在数学上表示的。此外,该模型已成功应用于先前存在的数据,来自先前的人类研究,在甲状腺手术开始时注入晶体30分钟。使用欧拉公式和IDE的拉普拉斯变换解,可以根据患者在输注期间对PD的反应将患者分为两组。明确地,1组患者有基于输注的PD反应,使用指数衰减双曲正弦函数建模,而2组患者有基于输注的PD反应,使用指数衰减三角正弦函数建模。1组和2组患者均有输注后PD反应,采用双曲正弦和双曲余弦函数的相同组合建模。1组和2组在输注期间和输注后PD曲线下的面积有统计学上的显著差异。具体来说,第2组患者对PD的反应很可能与术前低血容量一致。总的来说,PD的IDE模型似乎具有高度的“适应性”,并且在输注和输注后阶段成功地适应了临床获得的针对患者的人类数据。此外,PD患者特异性IDE模型可能是围手术期液体管理和实时评估临床体积动力学晶体溶液的有用辅助手段。
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引用次数: 3
Diffusion in Tube Dialyzer. 管内扩散透析器。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2017-09-29 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217732006
Yohannes Nigatie

Nowadays, kidney failure is a problem of many peoples in the world. We know that the main function of kidney is maintaining the chemical quality of blood particularly removing urea through urine. But when they malfunction, the pathologic state known as uremia results in a condition in which the urea is retained in the body. Failure of the kidney results in building up of harmful wastes and excess fluids in the body. Kidney diseases (failures) can be due to infections, high blood pressure (hypertension), diabetes, and/or extensive use of medication. The best form of treatment is the implantation of a healthy kidney from a donor. However, this is often not possible due to the limited availability of human organs. Chronic kidney failure requires the treatment using a tube dialyzer called dialysis. Blood is taken out of the body and passes through a special membrane that removes waste and extra fluids. The clean blood is then returned to the body. The process is controlled by a dialysis machine (tube dialyzer) which is equipped with a blood pump and monitoring systems to ensure safety. So this article investigates the real application of mathematics (diffusion) in medical science, and it also contains the mathematical formulation and interpretation of tube dialyzer in relation to diffusion.

如今,肾衰竭是世界上许多人的问题。我们知道肾脏的主要功能是维持血液的化学性质,特别是通过尿液排出尿素。但当它们发生功能障碍时,这种被称为尿毒症的病理状态会导致尿素滞留在体内。肾功能衰竭会导致有害废物和体液在体内堆积。肾脏疾病(衰竭)可能是由于感染,高血压(高血压),糖尿病,和/或广泛使用药物。最好的治疗方式是从捐赠者那里移植一个健康的肾脏。然而,由于人体器官的供应有限,这往往是不可能的。慢性肾衰竭需要使用一种叫做透析的管式透析器进行治疗。血液被排出体外,通过一层特殊的膜,去除废物和多余的液体。然后,干净的血液被送回体内。整个过程由一台透析机(管式透析器)控制,该透析机配有血泵和监控系统,以确保安全。因此,本文探讨了数学(扩散)在医学中的实际应用,并包含了与扩散有关的管式透析器的数学公式和解释。
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引用次数: 2
Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review. 光学相干断层扫描技术和皮肤光学相干断层扫描图像质量改进方法:简评。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2017-06-12 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217713475
Saba Adabi, Zahra Turani, Emad Fatemizadeh, Anne Clayton, Mohammadreza Nasiriavanaki

Optical coherence tomography (OCT) delivers 3-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution method, OCT images experience some artifacts that lead to misapprehension of tissue structures. Speckle, intensity decay, and blurring are 3 major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. In this short review, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts.

光学相干断层扫描(OCT)可提供组织微观结构的三维图像。虽然 OCT 成像是一种很有前景的高分辨率方法,但 OCT 图像会出现一些伪影,导致对组织结构的误解。斑点、强度衰减和模糊是 OCT 图像中的三大伪像。斑点是由于 OCT 配置中使用的低相干光源造成的。强度衰减是光线随深度的衰减,而模糊则是光学元件缺陷的结果。在这篇简短的综述中,我们总结了一些针对上述伪影的 OCT 图像增强算法。
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引用次数: 0
FSI Simulations of Pulse Wave Propagation in Human Abdominal Aortic Aneurysm: The Effects of Sac Geometry and Stiffness. 脉冲波在人腹主动脉瘤内传播的FSI模拟:囊腔几何形状和刚度的影响。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-07-18 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S40094
Han Li, Kexin Lin, Danial Shahmirzadi

This study aims to quantify the effects of geometry and stiffness of aneurysms on the pulse wave velocity (PWV) and propagation in fluid-solid interaction (FSI) simulations of arterial pulsatile flow. Spatiotemporal maps of both the wall displacement and fluid velocity were generated in order to obtain the pulse wave propagation through fluid and solid media, and to examine the interactions between the two waves. The results indicate that the presence of abdominal aortic aneurysm (AAA) sac and variations in the sac modulus affect the propagation of the pulse waves both qualitatively (eg, patterns of change of forward and reflective waves) and quantitatively (eg, decreasing of PWV within the sac and its increase beyond the sac as the sac stiffness increases). The sac region is particularly identified on the spatiotemporal maps with a region of disruption in the wave propagation with multiple short-traveling forward/reflected waves, which is caused by the change in boundary conditions within the saccular region. The change in sac stiffness, however, is more pronounced on the wall displacement spatiotemporal maps compared to those of fluid velocity. We conclude that the existence of the sac can be identified based on the solid and fluid pulse waves, while the sac properties can also be estimated. This study demonstrates the initial findings in numerical simulations of FSI dynamics during arterial pulsations that can be used as reference for experimental and in vivo studies. Future studies are needed to demonstrate the feasibility of the method in identifying very mild sacs, which cannot be detected from medical imaging, where the material property degradation exists under early disease initiation.

本研究旨在量化动脉脉动流固耦合(FSI)模拟中动脉瘤的几何形状和刚度对脉冲波速度(PWV)和传播的影响。为了获得脉冲波在流体和固体介质中的传播,并研究两种波之间的相互作用,生成了壁面位移和流体速度的时空图。结果表明,腹主动脉瘤(AAA)囊的存在和囊模量的变化对脉冲波的传播既有定性影响(如正向波和反射波的变化模式),也有定量影响(如随着囊刚度的增加,囊内PWV减小,囊外PWV增大)。囊状区域在时空图上被特别识别,在波传播中有多个短行正/反射波的中断区域,这是由囊状区域内边界条件的变化引起的。然而,与流体速度相比,囊腔刚度的变化在壁面位移时空图上更为明显。我们得出结论,根据固体和流体脉冲波可以识别囊的存在,并可以估计囊的性质。本研究证明了动脉搏动过程中FSI动力学数值模拟的初步发现,可作为实验和体内研究的参考。未来的研究需要证明该方法在识别非常轻微的囊泡方面的可行性,这些囊泡无法从医学成像中检测到,在早期疾病开始时存在材料性能退化。
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引用次数: 10
IMAGE AND VIDEO ACQUISITION AND PROCESSING FOR CLINICAL APPLICATIONS. 临床应用的图像和视频采集与处理。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-06-16 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S40272
Elie Zakhem, Sean V Murphy, Matthew L Davis, Shreya Raghavan, Mai T Lam
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引用次数: 1
Fluorescent Cell Imaging in Regenerative Medicine. 再生医学中的荧光细胞成像。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-05-02 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S39045
Etai Sapoznik, Guoguang Niu, Yu Zhou, Sean V Murphy, Shay Soker

Fluorescent protein imaging, a promising tool in biological research, incorporates numerous applications that can be of specific use in the field of regenerative medicine. To enhance tissue regeneration efforts, scientists have been developing new ways to monitor tissue development and maturation in vitro and in vivo. To that end, new imaging tools and novel fluorescent proteins have been developed for the purpose of performing deep-tissue high-resolution imaging. These new methods, such as intra-vital microscopy and Förster resonance energy transfer, are providing new insights into cellular behavior, including cell migration, morphology, and phenotypic changes in a dynamic environment. Such applications, combined with multimodal imaging, significantly expand the utility of fluorescent protein imaging in research and clinical applications of regenerative medicine.

荧光蛋白成像是生物学研究中一个很有前途的工具,在再生医学领域具有广泛的应用前景。为了加强组织再生的努力,科学家们一直在研究新的方法来监测体外和体内组织的发育和成熟。为此,开发了新的成像工具和新型荧光蛋白,用于进行深部组织高分辨率成像。这些新方法,如生命内显微镜和Förster共振能量转移,为细胞行为提供了新的见解,包括细胞迁移、形态学和动态环境中的表型变化。这些应用与多模态成像相结合,极大地扩展了荧光蛋白成像在再生医学研究和临床应用中的应用。
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引用次数: 3
Lung-On-A-Chip Technologies for Disease Modeling and Drug Development. 用于疾病建模和药物开发的肺芯片技术。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-04-20 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S34252
Dipasri Konar, Mahesh Devarasetty, Didem V Yildiz, Anthony Atala, Sean V Murphy

Animal and two-dimensional cell culture models have had a profound impact on not only lung research but also medical research at large, despite inherent flaws and differences when compared with in vivo and clinical observations. Three-dimensional (3D) tissue models are a natural progression and extension of existing techniques that seek to plug the gaps and mitigate the drawbacks of two-dimensional and animal technologies. In this review, we describe the transition of historic models to contemporary 3D cell and organoid models, the varieties of current 3D cell and tissue culture modalities, the common methods for imaging these models, and finally, the applications of these models and imaging techniques to lung research.

动物和二维细胞培养模型不仅对肺部研究,而且对整个医学研究都产生了深远的影响,尽管与体内和临床观察相比存在固有的缺陷和差异。三维(3D)组织模型是现有技术的自然发展和延伸,旨在填补空白并减轻二维和动物技术的缺点。在这篇综述中,我们描述了历史模型到当代3D细胞和类器官模型的转变,当前3D细胞和组织培养模式的种类,这些模型的常见成像方法,最后,这些模型和成像技术在肺研究中的应用。
{"title":"Lung-On-A-Chip Technologies for Disease Modeling and Drug Development.","authors":"Dipasri Konar,&nbsp;Mahesh Devarasetty,&nbsp;Didem V Yildiz,&nbsp;Anthony Atala,&nbsp;Sean V Murphy","doi":"10.4137/BECB.S34252","DOIUrl":"https://doi.org/10.4137/BECB.S34252","url":null,"abstract":"<p><p>Animal and two-dimensional cell culture models have had a profound impact on not only lung research but also medical research at large, despite inherent flaws and differences when compared with in vivo and clinical observations. Three-dimensional (3D) tissue models are a natural progression and extension of existing techniques that seek to plug the gaps and mitigate the drawbacks of two-dimensional and animal technologies. In this review, we describe the transition of historic models to contemporary 3D cell and organoid models, the varieties of current 3D cell and tissue culture modalities, the common methods for imaging these models, and finally, the applications of these models and imaging techniques to lung research. </p>","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"7 Suppl 1","pages":"17-27"},"PeriodicalIF":2.8,"publicationDate":"2016-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4137/BECB.S34252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34440156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 80
Prediction of Peaks of Seasonal Influenza in Military Health-Care Data. 军队卫生资料中季节性流感高峰的预测
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-04-19 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S36277
Anna L Buczak, Benjamin Baugher, Erhan Guven, Linda Moniz, Steven M Babin, Jean-Paul Chretien

Influenza is a highly contagious disease that causes seasonal epidemics with significant morbidity and mortality. The ability to predict influenza peak several weeks in advance would allow for timely preventive public health planning and interventions to be used to mitigate these outbreaks. Because influenza may also impact the operational readiness of active duty personnel, the US military places a high priority on surveillance and preparedness for seasonal outbreaks. A method for creating models for predicting peak influenza visits per total health-care visits (ie, activity) weeks in advance has been developed using advanced data mining techniques on disparate epidemiological and environmental data. The model results are presented and compared with those of other popular data mining classifiers. By rigorously testing the model on data not used in its development, it is shown that this technique can predict the week of highest influenza activity for a specific region with overall better accuracy than other methods examined in this article.

流感是一种高度传染性疾病,可引起季节性流行病,发病率和死亡率很高。提前数周预测流感高峰的能力将允许及时进行预防性公共卫生规划和干预措施,以减轻这些疫情。由于流感也可能影响现役人员的作战准备,美国军方高度重视季节性疫情的监测和准备工作。利用先进的数据挖掘技术,利用不同的流行病学和环境数据,开发了一种方法,可以创建模型,提前数周预测流感高峰就诊次数(即活动)。给出了模型结果,并与其他流行的数据挖掘分类器进行了比较。通过对模型在开发过程中未使用的数据进行严格测试,结果表明,该技术可以预测特定地区流感活动最高的一周,总体上比本文所研究的其他方法更准确。
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引用次数: 5
A Unified Frequency Domain Model to Study the Effect of Demyelination on Axonal Conduction. 用统一频域模型研究脱髓鞘对轴突传导的影响。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-04-18 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S38554
Saurabh Chaubey, Shikha J Goodwin
Multiple sclerosis is a disease caused by demyelination of nerve fibers. In order to determine the loss of signal with the percentage of demyelination, we need to develop models that can simulate this effect. Existing time-based models does not provide a method to determine the influences of demyelination based on simulation results. Our goal is to develop a system identification approach to generate a transfer function in the frequency domain. The idea is to create a unified modeling approach for neural action potential propagation along the length of an axon containing number of Nodes of Ranvier (N). A system identification approach has been used to identify a transfer function of the classical Hodgkin-Huxley equations for membrane voltage potential. Using this approach, we model cable properties and signal propagation along the length of the axon with N node myelination. MATLAB/ Simulink platform is used to analyze an N node-myelinated neuronal axon. The ability to transfer function in the frequency domain will help reduce effort and will give a much more realistic feel when compared to the classical time-based approach. Once a transfer function is identified, the conduction as a cascade of each linear time invariant system-based transfer function can be modeled. Using this approach, future studies can model the loss of myelin in various parts of nervous system.
多发性硬化症是由神经纤维脱髓鞘引起的疾病。为了确定信号的损失与脱髓鞘的百分比,我们需要开发可以模拟这种影响的模型。现有的基于时间的模型没有提供一种基于仿真结果来确定脱髓鞘影响的方法。我们的目标是开发一种系统识别方法来在频域生成传递函数。我们的想法是创建一个统一的建模方法,用于神经动作电位沿着包含Ranvier节点数(N)的轴突的长度传播。系统识别方法已用于识别膜电压电位的经典Hodgkin-Huxley方程的传递函数。使用这种方法,我们模拟了电缆特性和信号沿轴突长度与N节点髓鞘形成的传播。利用MATLAB/Simulink平台对N节髓鞘神经元轴突进行分析。在频域中传递函数的能力将有助于减少工作量,并且与经典的基于时间的方法相比,会给人更真实的感觉。一旦一个传递函数被确定,传导作为一个级联的每个线性时不变的系统为基础的传递函数可以建模。利用这种方法,未来的研究可以模拟神经系统不同部位髓磷脂的损失。
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引用次数: 5
Network-Based Enriched Gene Subnetwork Identification: A Game-Theoretic Approach. 基于网络的富集基因子网络识别:一种博弈论方法。
IF 2.8 Q3 ENGINEERING, BIOMEDICAL Pub Date : 2016-04-05 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S38244
Abolfazl Razi, Fatemeh Afghah, Salendra Singh, Vinay Varadan

Identifying subsets of genes that jointly mediate cancer etiology, progression, or therapy response remains a challenging problem due to the complexity and heterogeneity in cancer biology, a problem further exacerbated by the relatively small number of cancer samples profiled as compared with the sheer number of potential molecular factors involved. Pure data-driven methods that merely rely on multiomics data have been successful in discovering potentially functional genes but suffer from high false-positive rates and tend to report subsets of genes whose biological interrelationships are unclear. Recently, integrative data-driven models have been developed to integrate multiomics data with signaling pathway networks in order to identify pathways associated with clinical or biological phenotypes. However, these approaches suffer from an important drawback of being restricted to previously discovered pathway structures and miss novel genomic interactions as well as potential crosstalk among the pathways. In this article, we propose a novel coalition-based game-theoretic approach to overcome the challenge of identifying biologically relevant gene subnetworks associated with disease phenotypes. The algorithm starts from a set of seed genes and traverses a protein-protein interaction network to identify modulated subnetworks. The optimal set of modulated subnetworks is identified using Shapley value that accounts for both individual and collective utility of the subnetwork of genes. The algorithm is applied to two illustrative applications, including the identification of subnetworks associated with (i) disease progression risk in response to platinum-based therapy in ovarian cancer and (ii) immune infiltration in triple-negative breast cancer. The results demonstrate an improved predictive power of the proposed method when compared with state-of-the-art feature selection methods, with the added advantage of identifying novel potentially functional gene subnetworks that may provide insights into the mechanisms underlying cancer progression.

由于癌症生物学的复杂性和异质性,确定共同介导癌症病因、进展或治疗反应的基因亚群仍然是一个具有挑战性的问题,与潜在分子因素的绝对数量相比,相对较少的癌症样本进一步加剧了这一问题。纯数据驱动的方法仅仅依赖于多组学数据,已经成功地发现了潜在的功能基因,但存在高假阳性率,并且倾向于报告生物相互关系不清楚的基因亚群。最近,综合数据驱动的模型已经被开发出来,将多组学数据与信号通路网络相结合,以确定与临床或生物表型相关的通路。然而,这些方法有一个重要的缺点,即局限于先前发现的通路结构,错过了新的基因组相互作用以及通路之间潜在的串扰。在这篇文章中,我们提出了一种新的基于联盟的博弈论方法来克服识别与疾病表型相关的生物学相关基因亚网络的挑战。该算法从一组种子基因开始,遍历蛋白质-蛋白质相互作用网络来识别调制子网络。使用Shapley值确定调制子网络的最优集,该值考虑了基因子网络的个人和集体效用。该算法应用于两个说明性应用,包括确定与(i)卵巢癌对铂类药物治疗反应的疾病进展风险和(ii)三阴性乳腺癌的免疫浸润相关的子网。结果表明,与最先进的特征选择方法相比,所提出的方法具有改进的预测能力,并且具有识别新的潜在功能基因子网络的额外优势,这可能为癌症进展的潜在机制提供见解。
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引用次数: 5
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Biomedical Engineering and Computational Biology
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