Bulletin of the American Physical Society
77th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 24–26, 2024; Salt Lake City, Utah
Session C05: Interact: Physiological and Biomedical Flows |
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Chair: Alison Marsden, Stanford University Room: Ballroom E |
Sunday, November 24, 2024 10:50AM - 11:20AM |
C05.00001: INTERACT FLASH TALKS: Physiological and Biomedical Flows Each Interact Flash Talk will last around 1 minute, followed by around 30 seconds of transition time. |
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C05.00002: Patient-Specific In-vitro Modeling and Fluid Dynamics Analysis after a Redo Transcatheter Aortic Valve Replacement Maryam Bagheri, Lakshmi P Dasi We are examining the fluid dynamics features in a patient-specific aorta model after a redo transcatheter aortic valve replacement (TAVR) therapy focusing on coronary artery access using hemodynamic and Particle Image Velocimetry (PIV). Initially, a 26-mm CoreValve (Medtronic) was deployed at two heights (deep and normal) into a patient-specific aortic root model with coronary arteries. The aortic geometry was based on Computed Tomography (CT) data and the chamber was manufactured through a Silicon-casting method. Subsequently, a 23-mm Sapien 3 was deployed in the first CoreValve at two different heights to incorporate the different feasibility of coronary flow. The redo (TAVR) model was tested in a left heart simulator consisting of a pneumatic bladder pump controlled by a LabVIEW program mimicking the physiological condition of 70 beats per minute, and 120/80 mmHg systolic/diastolic, with an averaged cardiac output of 5 L/min. Utilizing a PIV system, the flow field downstream of the redo TAVR, as well as within the left and right coronary arteries was evaluated. Blood flow stasis and coronary obstruction were assessed in detail. Flow measurements in this study provide insights for clinical procedures regarding the redo TAVR based on the anatomy and the cause of the first valve failure. |
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C05.00003: Stroke Risk Assessment in Atrial Fibrillation via Phase-Field Modeling of Thrombus Biomechanics Clarissa Bargellini, Alejandro Gonzalo, Manuel Guerrero-Hurtado, Pablo Martinez-Legazpi, Javier Bermejo, Manuel García-Villalba, Andrew M Kahn, Oscar Flores, Juan Carlos del Alamo Atrial Fibrillation (AF), the most common arrhythmia, is linked to one-third of all thromboembolic strokes. AF-related strokes are typically ischemic and cardioembolic, often fatal or leading to disability, with a high risk of recurrence. Despite the well-established correlation between AF and stroke, its underlying mechanisms remain poorly understood. Structural changes and eventual instabilities in a clot can give rise to microthrombi, potentially releasing emboli and significantly impacting stroke risk. To address this, we introduce a computational pipeline that investigates clotting biomechanics and thromboembolism within a unified mathematical framework. Our approach employs a phase-field model to represent the thrombus system as a continuum undergoing deformation and incorporates information from high-resolution, time-resolved medical imaging to track the thrombus behavior over time in a patient-specific manner. Coagulation cascade pathways are also integrated to mimic thrombus initiation. We test our pipeline with ground-truth data simulations in both idealized, fixed-wall geometries and patient-specific, moving-wall left atrial meshes. We demonstrate its clinical relevance using 4D CT acquisitions from clot- and/or stroke-positive AF patients. |
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C05.00004: Intracardiac Flow Analysis of Single Ventricle Hearts Brett A Meyers, Yue-Hin Loke, Mark R Payne, Pavlos P Vlachos Analysis of intracardiac blood flow dynamics and flow structures traditionally focuses on the left side of the adult heart, offering significant mechanistic insights. However, these insights do not translate to single ventricle (SV) hearts, a congenital anomaly where half the heart is functional. Given their increased risk of heart failure, it is crucial to understand the unique flow dynamics in SV hearts. Yet, comprehensive flow analysis is challenging due to their complex morphology and motion, leaving substantial knowledge gaps about SV flow dynamics and patterns, particularly as patients age. This study aims to bridge these gaps by quantifying SV flow dynamics from birth to childhood. We reconstruct the intracardiac velocity fields from color Doppler echocardiography using Doppler Vector Reconstruction (DoVeR), a method based on the streamfunction-vorticity formulation. We quantify kinetic energy and losses, vortex strength, and pressure fields across different ages, anticipating increased disorganization in flow patterns, elevated energy losses, and altered pressure gradients as SV hearts mature. This research highlights the importance of detailed intraventricular flow measurements for understanding the unique mechanics of SV hearts. |
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C05.00005: Simulating Blood Flow in Left Atrium using a Personalized Multiscale Electromechanics Modeling Framework Vijay Vedula, Lei Shi, Boyang (Bryan) Gan, Hannah Haider, Chen S Zhang, Ian Chen We innovated a workflow to simulate blood flow in the left atrium (LA) by coupling it to a personalized multiscale electromechanics model. The workflow begins by extracting the patient's clinical data, including time-dependent computed tomographic (CT) images and electrocardiogram (ECG) data, and feeding it to a semi-automatic tuning framework for personalizing the multiscale electromechanics model. In the tuning process, we developed a novel inverse finite element analysis framework to determine myocardial material parameters (passive expansion and active contraction) by applying realistic boundary conditions and physiological pressures, so that the simulated deformation matches clinical data, including four-chamber min/max volumes, cuff-based pressures, and LA volumes throughout the cardiac cycle. We then perform multiscale fluid-structure interaction (FSI) simulations in the LA using validated stabilized finite element methods and patient-specific tissue parameters, thereby integrating biophysics-based myocyte activation, tissue contraction, and blood flow coupled to a 0D lumped parameter network (LPN)-based circulatory system model. This integrated model overcomes the limitations of simulating LA blood dynamics by imposing image-based wall motion, enabling us to simulate realistic tissue contraction patterns and blood flow under pathological conditions, such as atrial fibrillation, and predict the biomechanical response to treatment and remodeling. |
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C05.00006: Principles of Decentralized Pumping in Biological Systems Paheli Desai-Chowdhry, Aaron C Winn, Purba Chatterjee, Stanislaw Zukowski, Laureline Julien, Annemiek Cornelissen, Eleni Katifori Jellyfish are interesting sea creatures that provide insight into the evolution of cardiovascular networks; while vertebrates are characterized by a centralized heart that allows the distribution of resources in the body through pulsatile pumping, jellyfish lack such a centralization. However, they also have complex vascular structures, with gastrovascular canals that extend throughout their bodies from their open mouths to their stomach pouches and back in 4-fold symmetrical fractal branching patterns that increase in complexity as they age and develop. Flow through these networks is generated through swimming motion, involving a muscle contraction leading to deformations of these canal networks. Here, we build a mathematical model using fluid dynamics and network theory principles to simulate the flow through these networks during contraction, looking at three different variations of swimming motions. Future directions include comparing the flow generated through simulation to experimental data, increasing the biological accuracy and complexity of the model, and incorporating the effects of cilia on the flow in our model. |
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C05.00007: Quantifying blood clot biomechanics with integrated CFD and intravital imaging Josh Gregory, Chayut Teeraratkul, Timothy J Stalker, Maurizio Tomaiuolo, Debanjan Mukherjee The dynamic flow environment around an in vivo hemostatic blood clot is highly complex, and often not fully quantifiably understood. Intravital microscopy is a common technique to study in vivo clot mechanics in mice. These in vivo data illustrate how a clot forms, grows, and embolizes but does not provide information on local flow and flow-induced forces. We have previously developed an in silico method named IVISim that integrates with in vivo intravital images to predict flow environment in a clot neighborhood. Here, we employ IVISim to compare the dynamic clot-hemodynamics interactions between a wild type mouse model and a diYF knockout model that has impaired clot contraction. Each cohort has six mice for our study. Using IVISim we will compare these phenotypes by computing flow patterns, quantifying unsteady force-deformation behavior of the clot, as well as characterizing features such as embolization. Such detailed comparisons between wild type and knockout mice from a biomechanical clot response perspective have been lacking.
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C05.00008: Assessment of Cerebral Oxygenation based on Blood Perfusion Maps Obtained from Ultrasonically Tracked Microbubbles Yibo Wu, David Le, Todd Kilbaugh, Misun Hwang, Joseph Katz Monitoring brain oxygenation plays a key role in preventing secondary injuries led by brain ischemia and hypoxia in hydrocephalic patients. However, conventional monitoring techniques are either invasive or inaccurate. A non-invasive and reliable assessment technique would be of great importance for continuous management of brain oxygenation and neurosurgical interventions. Here we use contrast-enhanced ultrasound (CEUS) imaging and ultrasound localization microscopy (ULM) to map the cerebral micro vessels and assess the microvascular blood flow. This procedure involves tracking of lipid-coated micro-bubbles (2-3 μm in diameter) in a coronal section of the brain and using the tracks to generate detailed maps of the cerebral micro- and macro-vessels and measuring the blood velocity in them. A 'cerebral microcirculation parameter (CMC),' is defined as the product of blood vessels concentration and flow velocity to characterize the perfusion in different cerebral sections. In efforts to develop means of measuring the intracranial pressure (ICP) non-invasively, tests involving infant pigs have examined the correlation between CMC of micro- and macro-vessels, ICP, and the invasively-measured cerebral oxygen tension (PbtO2). Results show that the cortical CMC scaled by mean arterial pressure is linearly correlated with the PbtO2 with a correlation coefficient exceeding 0.76. This finding suggests that CMC could be used as an effective non-invasive means for assessing cerebral oxygenation. |
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C05.00009: Effect of Myocardial Motion on Coronary Hemodynamics Yurui Chen, Hannah Zhai, Yeqing Ni, Ian Chen, Vijay Vedula Coronary artery disease is the most common type of heart disease, which is the leading cause of death. Significant advances were made in modeling coronary blood flow to the point of clinical translation and personalized treatment planning. Although it is postulated that myocardial motion could substantially impact coronary flow, computational models rarely account for it. We developed a multiscale moving-domain model to simulate blood flow through coronary arteries moving with the myocardium. Time-dependent CT data was used to segment, register, and extract motion of the proximal ascending aorta and coronary arteries. We employed a closed-loop multiscale model of the circulatory system, coupling the 3D model with a 0D lumped parameter model (LPN), with its parameters tuned to match patient data. We model the blood flow in moving coronaries using the arbitrary Lagrangian-Eulerian (ALE) formulation of Navier-Stokes equations, discretized using a stabilized finite element method. Computed flow metrics, including pressure gradients, shear profiles, and helicity, were compared against the rigid wall case. We then extended our model to evaluate the effect of myocardial motion on predicting fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) in stenosed coronaries. |
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C05.00010: Computational studies of renal artery hemodynamics induced by breathing in patient-specific models of abdominal aortic aneurysms Alessandra Corvo, Fanette Chassagne, Alberto Aliseda, Stéphane Avril Abdominal Aortic Aneurysm (AAA) is treated predominantly by endovascular aneurysm repair (EVAR), a minimally invasive insertion of a stent-graft (SG) into the aorta and, in some cases, fenestrated SGs in the renal arteries (RA). RA stenting can lead to occlusion. This study focuses on the effect of breathing-induced deformation on RA hemodynamics, a problem on which there are no studies to date. This motion is characterized by in vivo imaging. Changes in RA curvature and branching angle, associated with respiration, were measured in AAA patients. Numerical simulations are conducted to evaluate hemodynamic changes pre- and post-operatively. This research aims to assess if breathing-induced motion induces hemodynamic changes in the renal arteries that could result in thrombosis and occlusion. CFD simulations are conducted for two patients before and after EVAR, using a moving mesh, with motion prescribed by previous finite-element simulations of renal artery stenting and SG deformation. Hemodynamics in the renal arteries is assessed from Eulerian and Lagrangian metrics for thrombosis, with the goal of predicting EVAR complications. |
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C05.00011: Data-driven Wall Shear Stress Prediction with 3D Near-Wall and Surface Transport Models Mahmoud Elhadidy, Roshan M D'Souza, Amirhossein Arzani Accurate wall shear stress (WSS) measurement is essential in biomedical and cardiovascular flows. Estimating WSS in vascular flows necessitates detailed velocity field data near the vessel walls, which can be challenging due to experimental limitations such as resolution. This study explores using near-wall concentration measurements to derive WSS vectors through a data-driven approach. We compare two methods: a 3D near-wall region model with 3D conservation laws and a surface transport model where the 3D transport equations are projected to the wall, leveraging the close relationship between WSS and near-wall velocity. Physics-informed neural networks (PINNs) were used to solve the inverse problem and infer WSS from near-wall concentration data. Multiphysics CFD simulations provided synthetic concentration data in different benchmark problems, including a steady 2D backward-facing step, a pulsatile 3D constricted channel, and a pulsatile patient-specific coronary artery stenosis model. Our findings highlight the strengths and limitations of each approach in estimating WSS topology and magnitude. |
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C05.00012: Cell-resolved simulation of red blood cells' behavior in high-shear organ-scale flows: a Norwood case study Saba Mansour, Mahdi Esmaily A key challenge in the design and improvement of cardiovascular surgeries is preventing detrimental complications such as clot formation and hemolysis. Numerical simulation of red blood cell (RBC) membrane deformation is crucial in identifying and averting erythrocyte damage under high mechanical stresses. Hence, a multi-scale RBC solver is developed using the finite element method, fast Lagrangian particle tracking specially designed for periodic flows, and boundary element method for fluid-structure interactions. Using this framework, we can computationally study the mechanical behavior of RBCs at non-physiological stresses (up to 230Pa) present in complex biomedical applications, e.g., post-Norwood-surgery anatomy, a high-risk operation for single ventricles. The results of simulations performed on three geometries representing Blalock-Taussig (BT) shunts with 2.5 and 4mm diameters, and a 2.5mm central shunt, with more than 500 RBCs per case, suggest that RBCs under high shear stresses created due to the insertion of the shunt could experience around 10% increase in area and one-fold elongation (visualized as damage maps for comparison). Furthermore, the smaller BT shunt produces larger areal strains, proving its inferiority. Among the studied designs, the central shunt, creating the highest incidents of large areal strain, shear strain, and elongation, is the riskiest option. |
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C05.00013: Multi-fidelity uncertainty-aware coronary hemodynamics personalized by CT myocardial perfusion imaging Karthik Menon, Andrea Zanoni, Owais Khan, Gianluca Geraci, Koen Nieman, Daniele E Schiavazzi, Alison L Marsden This work presents a novel framework for personalized and uncertainty-aware coronary artery bypass graft (CABG) surgical planning that is informed by CT myocardial perfusion imaging. Current computational models of coronary hemodynamics distribute flow amongst coronary arteries based on purely empirical scaling between flow and the size of each artery. However, this does not account for anatomical inaccuracy, patient variability, disease, etc. Patient-specific models also do not incorporate uncertainty stemming from the clinical data they are based on. We demonstrate a framework for improved model personalization by estimating patient-specific and vessel-specific coronary flows from non-invasive myocardial perfusion imaging. We show significantly improved CABG predictions using these personalized models. We also develop an uncertainty-aware personalization framework that accounts for noisy clinical data. We use probabilistic Bayesian estimation of model parameters based on clinical data. We propagate clinical uncertainty into predicted quantities of interest using a novel multi-fidelity uncertainty quantification technique relying on non-linear dimensionality reduction. We demonstrate clinical data-informed confidence intervals with vastly improved precision in the estimated quantities of interest. |
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C05.00014: A Comparative Study of CFD Performance in Open-Source FEM Solvers for Patient-Specific Carotid Artery Models Alexis Throop, Nathan Sudbury, Lucas Timmins, Hediyeh Baradaran, Jeffery Weiss, Amirhossein Arzani Vascular conditions such as atherosclerosis and stroke are challenging to study in vivo due to invasive procedures. Computational fluid dynamics (CFD) offers a non-invasive technique to examine the role of blood flow in these conditions using 3D models constructed from patient imaging. Accurate blood flow simulations in these models are crucial for understanding hemodynamic parameters related to cardiovascular disease. This study compares the efficacy of different open-source Finite Element Method (FEM) CFD solvers – SimVascular, FEBio, and FEniCS Oasis – applied to patient-specific carotid artery models. These solvers use different formulations to solve the Navier-Stokes equations. Namely, SimVascular employs a coupled velocity-pressure method (u-p formulation), FEniCS Oasis uses a fractional steps method (the incremental pressure-correction scheme), and FEBio uses a compressible isothermal formulation to model nearly incompressible flow. 4D phase-contrast MRI (4D Flow MRI) is used to construct the models and validate the CFD results. Hemodynamic metrics and mesh convergence are compared for the different solvers. This analysis advances our understanding of the performance of FEM-based CFD software, contributing to enhanced cardiovascular disease modeling. |
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C05.00015: Exploring Cerebrospinal Fluid Dynamics in Perivascular Spaces via Numerical Simulations and Convolutional Long Short-Term Memory Models Parnian Hemmati, Hossein P Kavehpour The glymphatic system, crucial for brain waste clearance, involves cerebrospinal fluid (CSF) flow through spaces surrounding blood vessels, known as perivascular spaces (PVS). The dysfunction of the glymphatic system is linked to neurodegenerative diseases such as Chronic traumatic encephalopathy and Alzheimer's disease. Despite its importance, the fluid dynamics of this recently discovered system has remained relatively understudied. In this study, we used numerical simulations and a Convolutional Long Short-Term Memory (ConvLSTM) model to study the fluid dynamics of CSF inside PVS, and the effect of different factors including blood pulsation and PVS size on CSF flow. Unsteady deforming mesh simulations are used to generate a comprehensive dataset and consequently a ConvLSTM model is used to predict CSF velocity fields, marking its first application in this context. The results show that ConvLSTM effectively captures spatiotemporal patterns in CSF flow, providing insights into the mechanical behavior of the system. This approach advances predictive modeling in neurodegenerative disease research, offering potential for improved diagnostic and therapeutic strategies. |
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C05.00016: Can the phase lag between arterial pulsations and transmantle pressure fluctuations explain glymphatic flow through periarterial spaces? GUILLERMO LOPEZ NOZALEDA, Wilfried Coenen, Antonio L Sanchez The glymphatic system involves bulk motion of CSF through the perivascular spaces surrounding arteries and veins that penetrate the brain. In the perivenous spaces this bulk fluid motion occurs in the direction of the time-averaged transmantle pressure gradient, associated with the slight net overpressure found in the interior of the brain. However, in the periarterial spaces the bulk motion paradoxically occurs in the opposite direction. Experimental observations have shown that pulsations of the arterial wall driven by the cardiac cycle (absent in perivenous spaces) play a key role, but the precise mechanism connecting the fast, one-second, wall pulsations to the slow, time-averaged, bulk motion remains unclear. The present study employs an analytical model informed by synchronized magnetic resonance measurements to test whether the temporal interplay between the arterial pulsations and the fluctuations in transmantle pressure, which has been suggested to play a role in perivascular flow across the spinal cord (Bilston et al., J. Neurosurg. 112(4), 2010), can provide a pumping mechanism capable of driving a net periarterial flow against the existing time-averaged adverse pressure gradient. |
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C05.00017: Large-Scale In-Silico CSF Investigations within the Optic Nerve Diego Rossinelli, Gilles Fourestey, Hanspeter E Killer, Albert Neutzner, Gianluca Iaccarino, Jatta Berberat Studying cerebrospinal fluid (CSF) flow within the human optic nerve is crucial for understanding conditions such as papilledema and glaucoma. We discuss large-scale investigations combining supercomputing with Terabyte-sized synchrotron-radiation microcomputed tomography 3D imaging. |
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C05.00018: Numerical simulations reveal complementary function of blood-brain barrier and glymphatic transport in the brain Reza Yousofvand, Jeffrey Tithof The brain's high metabolic activity generates protein waste that must be efficiently cleared to avoid the formation of toxic aggregates associated with neurodegenerative diseases such as Alzheimer's (AD). Two primary pathways facilitate this clearance: the blood-brain barrier (BBB) and the glymphatic system. In the latter pathway, cerebrospinal fluid (CSF) flows through perivascular spaces (PVSs) - annular channels around the vessels in the brain - and mixes with interstitial fluid to aid in waste removal through bulk flow. The BBB comprises active transporters on the vasculature walls that permit waste proteins to cross from the brain into the blood. Despite their importance, the interplay and complementary roles of these two pathways are not well understood. To address this, we developed a Lattice Boltzmann simulation to model the clearance of amyloid-β (Aβ), a peptide associated with AD, from the brain tissue. This model includes arteries, veins, capillaries, and both clearance routes. We calibrated our model by activating different pathways and comparing the results with available experimental data of selectively deactivated Aβ production and/or BBB efflux. The results allowed us to derive critical parameters not yet measured in experiments and revealed distinct, complementary roles of the two waste clearance routes. Our study underscores the generic nature of these dual pathways in transporting large molecules, and our approach can be adapted to probe other proteins or drug delivery to the brain. |
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C05.00019: CT-based Subject-Specific Whole-lung Computational Fluid Dynamics and Particle Deposition in Post-COVID-19 Subjects Prathish Kumar Rajaraman, Xuan Zhang, Tianbao Yang, Alejandro P Comellas, Eric A Hoffman, Ching-Long Lin This work investigates the health-related effects of COVID-19 subjects using whole-lung computational fluid and particle dynamics (CFPD). The subjects underwent examination at approximately 4 months (V0) and 36 months (V1) after their initial COVID-19 diagnosis. Data gathered included demographic information, pulmonary function tests (PFT), St. George’s respiratory Questionnaire (SGRQ) and CT scans. This study identified two groups of post-COVID subjects at V1 based on the total SGRQ score (SGRQ ≥ 25 and SGRQ < 25). The mean SGRQ for subjects (n=14) with SGRQ ≥ 25 was approximately 42.6 ± 12.2, and the mean score was approximately 13.1 ± 6 for SGRQ < 25 (n=19). Subjects with higher SGRQ scores reported persistent coughing and difficulty in daily physical activities. The 1D CFPD predicted total resistances for all subjects decreased from V0 to V1 (7.03 cmH2O×s/L ± 2.5 vs. 5.9 cmH2O×s/L ± 1.6). We found that SGRQ ≥ 25 is negatively correlated (r =-0.41, p < 0.05) with predicted forced expiratory volume at 1s (FEV1) and SGRQ < 25 was weakly correlated with total airways resistance (r =0.11, p < 0.05). The study highlights distinct biomarkers associated with CFPD-predicted airway resistance, SGRQ score and PFTs among post-COVID subjects. The results indicate that health-related negative effects on their quality of life among post-COVID subjects with a higher prevalence among those with SGRQ ≥ 25. |
Sunday, November 24, 2024 11:20AM - 12:50PM |
C05.00020: INTERACT DISCUSSION SESSION WITH POSTERS: Physiological and Biomedical Flows After each Flash Talk has concluded, the Interact session will be followed by interactive poster or e-poster presentations, with plenty of time for one-on-one and small group discussions. |
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C05.00021: Abstract Withdrawn
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C05.00022: Abstract Withdrawn |
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