Publications by authors named "Zhenxiang Jiang"

4 Publications

  • Page 1 of 1

Inverse modeling framework for characterizing patient-specific microstructural changes in the pulmonary arteries.

J Mech Behav Biomed Mater 2021 Mar 27;119:104448. Epub 2021 Mar 27.

Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA.

Microstructural changes in the pulmonary arteries associated with pulmonary arterial hypertension (PAH) is not well understood and characterized in humans. To address this issue, we developed and applied a patient-specific inverse finite element (FE) modeling framework to characterize mechanical and structural changes of the micro-constituents in the proximal pulmonary arteries using in-vivo pressure measurements and magnetic resonance images. The framework was applied using data acquired from a pediatric PAH patient and a heart transplant patient with normal pulmonary arterial pressure, which serves as control. Parameters of a constrained mixture model that are associated with the structure and mechanical properties of elastin, collagen fibers and smooth muscle cells were optimized to fit the patient-specific pressure-diameter responses of the main pulmonary artery. Based on the optimized parameters, individual stress and linearized stiffness resultants of the three tissue constituents, as well as their aggregated values, were estimated in the pulmonary artery. Aggregated stress resultant and stiffness are, respectively, 4.6 and 3.4 times higher in the PAH patient than the control subject. Stress and stiffness resultants of each tissue constituent are also higher in the PAH patient. Specifically, the mean stress resultant is highest in elastin (PAH: 69.96, control: 14.42 kPa-mm), followed by those in smooth muscle cell (PAH: 13.95, control: 4.016 kPa-mm) and collagen fibers (PAH: 13.19, control: 2.908 kPa-mm) in both the PAH patient and the control subject. This result implies that elastin may be the key load-bearing constituent in the pulmonary arteries of the PAH patient and the control subject.
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http://dx.doi.org/10.1016/j.jmbbm.2021.104448DOI Listing
March 2021

Mitochondrial AOX Supports Redox Balance of Photosynthetic Electron Transport, Primary Metabolite Balance, and Growth in under High Light.

Int J Mol Sci 2019 Jun 23;20(12). Epub 2019 Jun 23.

School of Life Sciences, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo 192-0392, Japan.

When leaves receive excess light energy, excess reductants accumulate in chloroplasts. It is suggested that some of the reductants are oxidized by the mitochondrial respiratory chain. Alternative oxidase (AOX), a non-energy conserving terminal oxidase, was upregulated in the photosynthetic mutant of , , which accumulated reductants in chloroplast stroma. AOX is suggested to have an important role in dissipating reductants under high light (HL) conditions, but its physiological importance and underlying mechanisms are not yet known. Here, we compared wild-type (WT), , and a double mutant of AOX1a-knockout plant () and () grown under high- and low-light conditions, and conducted physiological analyses. The net assimilation rate () was lower in than that in the other genotypes at the early growth stage, while the leaf area ratio was higher in . We assessed detailed mechanisms in relation to . In , photosystem II parameters decreased under HL, whereas respiratory O uptake rates increased. Some intermediates in the tricarboxylic acid (TCA) cycle and Calvin cycle decreased in , whereas γ-aminobutyric acid (GABA) and N-rich amino acids increased in . Under HL, AOX may have an important role in dissipating excess reductants to prevent the reduction of photosynthetic electron transport and imbalance in primary metabolite levels.
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http://dx.doi.org/10.3390/ijms20123067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628045PMC
June 2019

Patient-Specific Prediction of Abdominal Aortic Aneurysm Expansion Using Bayesian Calibration.

IEEE J Biomed Health Inform 2019 11 30;23(6):2537-2550. Epub 2019 Jan 30.

Translating recent advances in abdominal aortic aneurysm (AAA) growth and remodeling (G&R) knowledge into a predictive, patient-specific clinical treatment tool requires a major paradigm shift in computational modeling. The objectives of this study are to develop a prediction framework that first calibrates the physical AAA G&R model using patient-specific serial computed tomography (CT) scan images, predicts the expansion of an AAA in the future, and quantifies the associated uncertainty in the prediction. We adopt a Bayesian calibration method to calibrate parameters in the G&R computational model and predict the magnitude of AAA expansion. The proposed Bayesian approach can take different sources of uncertainty; therefore, it is well suited to achieve our aims in predicting the AAA expansion process as well as in computing the propagated uncertainty. We demonstrate how to achieve the proposed aims by solving the formulated Bayesian calibration problems for cases with the synthetic G&R model output data and real medical patient-specific CT data. We compare and discuss the performance of predictions and computation time under different sampling cases of the model output data and patient data, both of which are simulated by the G&R computation. Furthermore, we apply our Bayesian calibration to real patient-specific serial CT data and validate our prediction. The accuracy and efficiency of the proposed method is promising, which appeals to computational and medical communities.
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http://dx.doi.org/10.1109/JBHI.2019.2896034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890695PMC
November 2019

High Spatial Resolution Multi-Organ Finite Element Modeling of Ventricular-Arterial Coupling.

Front Physiol 2018 2;9:119. Epub 2018 Mar 2.

Department of Mechanical Engineering, Michigan State University, East Lansing, MI, United States.

While it has long been recognized that bi-directional interaction between the heart and the vasculature plays a critical role in the proper functioning of the cardiovascular system, a comprehensive study of this interaction has largely been hampered by a lack of modeling framework capable of simultaneously accommodating high-resolution models of the heart and vasculature. Here, we address this issue and present a computational modeling framework that couples finite element (FE) models of the left ventricle (LV) and aorta to elucidate ventricular-arterial coupling in the systemic circulation. We show in a baseline simulation that the framework predictions of (1) LV pressure-volume loop, (2) aorta pressure-diameter relationship, (3) pressure-waveforms of the aorta, LV, and left atrium (LA) over the cardiac cycle are consistent with the physiological measurements found in healthy human. To develop insights of ventricular-arterial interactions, the framework was then used to simulate how alterations in the geometrical or, material parameter(s) of the aorta affect the LV and vice versa. We show that changing the geometry and microstructure of the aorta model in the framework led to changes in the functional behaviors of both LV and aorta that are consistent with experimental observations. On the other hand, changing contractility and passive stiffness of the LV model in the framework also produced changes in both the LV and aorta functional behaviors that are consistent with physiology principles.
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http://dx.doi.org/10.3389/fphys.2018.00119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841309PMC
March 2018