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Article ; Online: Biomechanics of parasite migration within hosts.

Yeh, Yi-Ting / Del Álamo, Juan C / Caffrey, Conor R

2024 Volume 40, Issue 2, Page(s) 164–175

Abstract: The dissemination of protozoan and metazoan parasites through host tissues is hindered by cellular barriers, dense extracellular matrices, and fluid forces in the bloodstream. To overcome these diverse biophysical impediments, parasites implement ... ...

Abstract	The dissemination of protozoan and metazoan parasites through host tissues is hindered by cellular barriers, dense extracellular matrices, and fluid forces in the bloodstream. To overcome these diverse biophysical impediments, parasites implement versatile migratory strategies. Parasite-exerted mechanical forces and upregulation of the host's cellular contractile machinery are the motors for these strategies, and these are comparably better characterized for protozoa than for helminths. Using the examples of the protozoans, Toxoplasma gondii and Plasmodium, and the metazoan, Schistosoma mansoni, we highlight how quantitative tools such as traction force and reflection interference contrast microscopies have improved our understanding of how parasites alter host mechanobiology to promote their migration.
MeSH term(s)	Animals ; Parasites ; Biomechanical Phenomena ; Helminths/physiology ; Toxoplasma/physiology ; Plasmodium
Language	English
Publishing date	2024-01-02
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2036227-4
ISSN	1471-5007 ; 1471-4922
ISSN (online)	1471-5007
ISSN	1471-4922
DOI	10.1016/j.pt.2023.12.001
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Article ; Online: Personalized biomechanical insights in atrial fibrillation: opportunities & challenges.

Telle, Åshild / Bargellini, Clarissa / Chahine, Yaacoub / Del Álamo, Juan C / Akoum, Nazem / Boyle, Patrick M

Expert review of cardiovascular therapy

2023 Volume 21, Issue 11, Page(s) 817–837

Abstract: Introduction: Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the ... ...

Abstract	Introduction: Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke. Areas covered: In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care. Expert opinion: Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.
MeSH term(s)	Humans ; Atrial Fibrillation ; Reproducibility of Results ; Heart Atria ; Fibrosis ; Stroke/etiology ; Stroke/prevention & control
Language	English
Publishing date	2023-12-10
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2192343-7
ISSN	1744-8344 ; 1477-9072
ISSN (online)	1744-8344
ISSN	1477-9072
DOI	10.1080/14779072.2023.2273896
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Article ; Online: Cyclic Mechanical Stresses Alter Erythrocyte Membrane Composition and Microstructure and Trigger Macrophage Phagocytosis.

Garcia-Herreros, Antoni / Yeh, Yi-Ting / Peng, Zhangli / Del Álamo, Juan C

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

2022 Volume 9, Issue 20, Page(s) e2201481

Abstract: Red blood cells (RBCs) are cleared from the circulation when they become damaged or display aging signals targeted by macrophages. This process occurs mainly in the spleen, where blood flows through submicrometric constrictions called inter-endothelial ... ...

Abstract	Red blood cells (RBCs) are cleared from the circulation when they become damaged or display aging signals targeted by macrophages. This process occurs mainly in the spleen, where blood flows through submicrometric constrictions called inter-endothelial slits (IES), subjecting RBCs to large-amplitude deformations. In this work, RBCs are circulated through microfluidic devices containing microchannels that replicate the IES. The cyclic mechanical stresses experienced by the cells affect their biophysical properties and molecular composition, accelerating cell aging. Specifically, RBCs quickly transition to a more spherical, less deformable phenotype that hinders microchannel passage, causing hemolysis. This transition is associated with the release of membrane vesicles, which self-extinguishes as the spacing between membrane-cytoskeleton linkers becomes tighter. Proteomics analysis of the mechanically aged RBCs reveals significant losses of essential proteins involved in antioxidant protection, gas transport, and cell metabolism. Finally, it is shown that these changes make mechanically aged RBCs more susceptible to macrophage phagocytosis. These results provide a comprehensive model explaining how physical stress induces RBC clearance in the spleen. The data also suggest new biomarkers of early "hemodamage" and inflammation preceding hemolysis in RBCs subjected to mechanical stress.
MeSH term(s)	Erythrocyte Membrane/metabolism ; Hemolysis ; Humans ; Macrophages ; Phagocytosis ; Stress, Mechanical
Language	English
Publishing date	2022-05-04
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2808093-2
ISSN	2198-3844 ; 2198-3844
ISSN (online)	2198-3844
ISSN	2198-3844
DOI	10.1002/advs.202201481
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Article: Editorial: Novel methods to advance diagnostic and treatment value of medical imaging for cardiovascular disease.

Keshavarz-Motamed, Zahra / Del Alamo, Juan C / Bluestein, Danny / Edelman, Elazer R / Wentzel, Jolanda J

Frontiers in bioengineering and biotechnology

2022 Volume 10, Page(s) 987326

Language	English
Publishing date	2022-08-31
Publishing country	Switzerland
Document type	Editorial
ZDB-ID	2719493-0
ISSN	2296-4185
ISSN	2296-4185
DOI	10.3389/fbioe.2022.987326
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Article: Deriving Explainable Metrics of Left Ventricular Flow by Reduced-Order Modeling and Classification.

Borja, María Guadalupe / Martinez-Legazpi, Pablo / Nguyen, Cathleen / Flores, Oscar / Kahn, Andrew M / Bermejo, Javier / Del Álamo, Juan C

medRxiv : the preprint server for health sciences

2023

Abstract: Background: Extracting explainable flow metrics is a bottleneck to the clinical translation of advanced cardiac flow imaging modalities. We hypothesized that reduced-order models (ROMs) of intraventricular flow are a suitable strategy for deriving ... ...

Abstract	Background: Extracting explainable flow metrics is a bottleneck to the clinical translation of advanced cardiac flow imaging modalities. We hypothesized that reduced-order models (ROMs) of intraventricular flow are a suitable strategy for deriving simple and interpretable clinical metrics suitable for further assessments. Combined with machine learning (ML) flow-based ROMs could provide new insight to help diagnose and risk-stratify patients. Methods: We analyzed 2D color-Doppler echocardiograms of 81 non-ischemic dilated cardiomyopathy (DCM) patients, 51 hypertrophic cardiomyopathy (HCM) patients, and 77 normal volunteers (Control). We applied proper orthogonal decomposition (POD) to build patient-specific and cohort-specific ROMs of LV flow. Each ROM aggregates a low number of components representing a spatially dependent velocity map modulated along the cardiac cycle by a time-dependent coefficient. We tested three classifiers using deliberately simple ML analyses of these ROMs with varying supervision levels. In supervised models, hyperparameter gridsearch was used to derive the ROMs that maximize classification power. The classifiers were blinded to LV chamber geometry and function. We ran vector flow mapping on the color-Doppler sequences to help visualize flow patterns and interpret the ML results. Results: POD-based ROMs stably represented each cohort through 10-fold cross-validation. The principal POD mode captured >80% of the flow kinetic energy (KE) in all cohorts and represented the LV filling/emptying jets. Mode 2 represented the diastolic vortex and its KE contribution ranged from <1% (HCM) to 13% (DCM). Semi-unsupervised classification using patient-specific ROMs revealed that the KE ratio of these two principal modes, the vortex-to-jet (V2J) energy ratio, is a simple, interpretable metric that discriminates DCM, HCM, and Control patients. Receiver operating characteristic curves using V2J as classifier had areas under the curve of 0.81, 0.91, and 0.95 for distinguishing HCM vs. Control, DCM vs. Control, and DCM vs. HCM, respectively. Conclusions: Modal decomposition of cardiac flow can be used to create ROMs of normal and pathological flow patterns, uncovering simple interpretable flow metrics with power to discriminate disease states, and particularly suitable for further processing using ML.
Language	English
Publishing date	2023-10-05
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.10.03.23296524
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Article: Machine Learning and the Conundrum of Stroke Risk Prediction.

Chahine, Yaacoub / Magoon, Matthew J / Maidu, Bahetihazi / Del Álamo, Juan C / Boyle, Patrick M / Akoum, Nazem

Arrhythmia & electrophysiology review

2023 Volume 12, Page(s) e07

Abstract: Stroke is a leading cause of death worldwide. With escalating healthcare costs, early non-invasive stroke risk stratification is vital. The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. ... ...

Abstract	Stroke is a leading cause of death worldwide. With escalating healthcare costs, early non-invasive stroke risk stratification is vital. The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. This review summarises recent efforts to deploy machine learning (ML) to predict stroke risk and enrich the understanding of the mechanisms underlying stroke. The surveyed body of literature includes studies comparing ML algorithms with conventional statistical models for predicting cardiovascular disease and, in particular, different stroke subtypes. Another avenue of research explored is ML as a means of enriching multiscale computational modelling, which holds great promise for revealing thrombogenesis mechanisms. Overall, ML offers a new approach to stroke risk stratification that accounts for subtle physiologic variants between patients, potentially leading to more reliable and personalised predictions than standard regression-based statistical associations.
Language	English
Publishing date	2023-04-12
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2813970-7
ISSN	2050-3377 ; 2050-3369
ISSN (online)	2050-3377
ISSN	2050-3369
DOI	10.15420/aer.2022.34
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Article ; Online: Benchtop Models of Patient-Specific Intraventricular Flow During Heart Failure and LVAD Support.

Vu, Vi / Rossini, Lorenzo / Del Alamo, Juan C / Dembitsky, Walter / Gray, Richard A / May-Newman, Karen

Journal of biomechanical engineering

2023 Volume 145, Issue 11

Abstract: The characterization of intraventricular flow is critical to evaluate the efficiency of fluid transport and potential thromboembolic risk but challenging to measure directly in advanced heart failure (HF) patients with left ventricular assist device ( ... ...

Abstract	The characterization of intraventricular flow is critical to evaluate the efficiency of fluid transport and potential thromboembolic risk but challenging to measure directly in advanced heart failure (HF) patients with left ventricular assist device (LVAD) support. The study aims to validate an in-house mock loop (ML) by simulating specific conditions of HF patients with normal and prosthetic mitral valves (MV) and LVAD patients with small and dilated left ventricle volumes, then comparing the flow-related indices result of vortex parameters, residence time (RT), and shear-activation potential (SAP). Patient-specific inputs for the ML studies included heart rate, end-diastolic and end-systolic volumes, ejection fraction, aortic pressure, E/A ratio, and LVAD speed. The ML effectively replicated vortex development and circulation patterns, as well as RT, particularly for HF patient cases. The LVAD velocity fields reflected altered flow paths, in which all or most incoming blood formed a dominant stream directing flow straight from the mitral valve to the apex. RT estimation of patient and ML compared well for all conditions, but SAP was substantially higher in the LVAD cases of the ML. The benchtop system generated comparable and reproducible hemodynamics and fluid dynamics for patient-specific conditions, validating its reliability and clinical relevance. This study demonstrated that ML is a suitable platform to investigate the fluid dynamics of HF and LVAD patients and can be utilized to investigate heart-implant interactions.
MeSH term(s)	Humans ; Heart-Assist Devices ; Reproducibility of Results ; Heart Failure/therapy ; Hemodynamics/physiology ; Heart Ventricles
Language	English
Publishing date	2023-08-11
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	243094-0
ISSN	1528-8951 ; 0148-0731
ISSN (online)	1528-8951
ISSN	0148-0731
DOI	10.1115/1.4063147
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Article ; Online: Reduced-order models of wall shear stress patterns in the left atrial appendage from a data-augmented atrial database.

Dueñas-Pamplona, Jorge / Rodríguez-Aparicio, Sergio / Gonzalo, Alejandro / Bifulco, Savannah F / Castro, Francisco / Ferrera, Conrado / Flores, Óscar / Boyle, Patrick M / Sierra-Pallares, José / García, Javier García / Del Álamo, Juan C

ArXiv

2024

Abstract: Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, affecting over 1% of the population. It is usually triggered by irregular electrical impulses that cause the atria to contract irregularly and ineffectively. It ... ...

Abstract	Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, affecting over 1% of the population. It is usually triggered by irregular electrical impulses that cause the atria to contract irregularly and ineffectively. It increases blood stasis and the risk of thrombus formation within the left atrial appendage (LAA) and aggravates adverse atrial remodeling. Despite recent efforts, LAA flow patterns representative of AF conditions and their association with LAA stasis remain poorly characterized. Aim: To develop reduced-order data-driven models of LAA flow patterns during atrial remodeling in order to uncover flow disturbances concurrent with LAA stasis that could add granularity to clinical decision criteria. Methods: We combined a geometric data augmentation process with projection of results from 180 CFD atrial simulations on a universal LAA coordinate (ULAAC) system. The projection approach enhances data visualization and facilitates direct comparison between different anatomical and functional states. ULAAC projections were used as input for a proper orthogonal decomposition (POD) algorithm to build reduced-order models of hemodynamic metrics, extracting flow characteristics associated with AF and non-AF anatomies. Results: We verified that the ULAAC system provides an adequate representation to visualize data distributions on the LAA surface and to build POD-based reduced-order models. These models revealed significant differences in LAA flow patterns for atrial geometries that underwent adverse atrial remodeling and experienced elevated blood stasis. Together with anatomical morphing-based patient-specific data augmentation, this approach could facilitate data-driven analyses to identify flow features associated with thrombosis risk due to atrial remodeling.
Language	English
Publishing date	2024-04-08
Publishing country	United States
Document type	Preprint
ISSN	2331-8422
ISSN (online)	2331-8422
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Article: Super-resolution Left Ventricular Flow and Pressure Mapping by Navier-Stokes-Informed Neural Networks.

Maidu, Bahetihazi / Martinez-Legazpi, Pablo / Guerrero-Hurtado, Manuel / Nguyen, Cathleen M / Gonzalo, Alejandro / Kahn, Andrew M / Bermejo, Javier / Flores, Oscar / Del Alamo, Juan C

bioRxiv : the preprint server for biology

2024

Abstract: Intraventricular vector flow mapping (VFM) is a growingly adopted echocardiographic modality that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic constraints ... ...

Abstract	Intraventricular vector flow mapping (VFM) is a growingly adopted echocardiographic modality that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic constraints arising from planar flow incompressibility. However, these models are not informed by crucial information about flow physics; most notably the pressure and shear forces within the fluid and the resulting accelerations. This limitation has rendered VFM unable to combine information from different time frames in an acquisition sequence or derive fluctuating pressure maps. In this study, we leveraged recent advances in artificial intelligence (AI) to develop AI-VFM, a vector flow mapping modality that uses physics-informed neural networks (PINNs) encoding mass conservation and momentum balance inside the LV, and no-slip boundary conditions at the LV endocardium. AI-VFM recovers the flow and pressure fields in the LV from standard echocardiographic scans. It performs phase unwrapping and recovers flow data in areas without input color-Doppler data. AI-VFM also recovers complete flow maps at time points without color-Doppler input data, producing super-resolution flow maps. We show that informing the PINNs with momentum balance is essential to achieving temporal super-resolution and significantly increases the accuracy of AI-VFM compared to informing the PINNs only with mass conservation. AI-VFM is solely informed by each patient's flow physics; it does not utilize explicit smoothness constraints or incorporate data from other patients or flow models. AI-VFM takes 15 minutes to run in off-the-shelf graphics processing units and its underlying PINN framework could be extended to map other flow-associated metrics like blood residence time or the concentration of coagulation species.
Language	English
Publishing date	2024-04-15
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.04.12.589319
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Article ; Online: Distinct platelet F-actin patterns and traction forces on von Willebrand factor versus fibrinogen.

Mollica, Molly Y / Beussman, Kevin M / Kandasamy, Adithan / Rodríguez, Lesley Martínez / Morales, Francisco R / Chen, Junmei / Manohar, Krithika / Del Álamo, Juan C / López, José A / Thomas, Wendy E / Sniadecki, Nathan J

Biophysical journal

2023 Volume 122, Issue 18, Page(s) 3738–3748

Abstract: Upon vascular injury, platelets form a hemostatic plug by binding to the subendothelium and to each other. Platelet-to-matrix binding is initially mediated by von Willebrand factor (VWF) and platelet-to-platelet binding is mediated mainly by fibrinogen ... ...

Abstract	Upon vascular injury, platelets form a hemostatic plug by binding to the subendothelium and to each other. Platelet-to-matrix binding is initially mediated by von Willebrand factor (VWF) and platelet-to-platelet binding is mediated mainly by fibrinogen and VWF. After binding, the actin cytoskeleton of a platelet drives its contraction, generating traction forces that are important to the cessation of bleeding. Our understanding of the relationship between adhesive environment, F-actin morphology, and traction forces is limited. Here, we examined F-actin morphology of platelets attached to surfaces coated with fibrinogen and VWF. We identified distinct F-actin patterns induced by these protein coatings and found that these patterns were identifiable into three classifications via machine learning: solid, nodular, and hollow. We observed that traction forces for platelets were significantly higher on VWF than on fibrinogen coatings and these forces varied by F-actin pattern. In addition, we analyzed the F-actin orientation in platelets and noted that their filaments were more circumferential when on fibrinogen coatings and having a hollow F-actin pattern, while they were more radial on VWF and having a solid F-actin pattern. Finally, we noted that subcellular localization of traction forces corresponded to protein coating and F-actin pattern: VWF-bound, solid platelets had higher forces at their central region while fibrinogen-bound, hollow platelets had higher forces at their periphery. These distinct F-actin patterns on fibrinogen and VWF and their differences in F-actin orientation, force magnitude, and force localization could have implications in hemostasis, thrombus architecture, and venous versus arterial thrombosis.
MeSH term(s)	von Willebrand Factor/metabolism ; Fibrinogen/metabolism ; Blood Platelets/metabolism ; Actins/metabolism ; Traction ; Platelet Membrane Glycoproteins/metabolism ; Hemostatics/metabolism ; Actin Cytoskeleton/metabolism
Chemical Substances	von Willebrand Factor ; Fibrinogen (9001-32-5) ; Actins ; Platelet Membrane Glycoproteins ; Hemostatics
Language	English
Publishing date	2023-07-10
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	218078-9
ISSN	1542-0086 ; 0006-3495
ISSN (online)	1542-0086
ISSN	0006-3495
DOI	10.1016/j.bpj.2023.07.006
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