Biology subjects

del Alamo, J. C.

Publications and source records attributed to del Alamo, J. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Three-Dimensional Fluid-Structure Interaction Reveals Trade-offs Among Oxygen Delivery, Shear, and Washout in Pediatric Roller-Pump Cardiopulmonary Bypass

Objective: To determine how roller speed, tubing occlusion, and hematocrit jointly regulate oxygen delivery, shear, and washout in pediatric roller-pump cardiopulmonary bypass. Methods: A three-dimensional, closed-loop fluid-structure interaction model resolved roller-tube contact, tubing deformation, and blood flow. Forty simulations combined 4 roller speeds (38-95 revolutions per minute), 2 occlusion levels (77% and 83%), and 5 hematocrit levels (15%-50%). Cycle-averaged flow, oxygen delivery, peak shear stress, and viscosity-normalized relative residence time were quantified. Results: Roller compression produced retrograde leakage through the occluded gap, localized peak shear stress exceeding 100 pascals, and adjacent stagnation and recirculation. Flow increased nearly linearly with roller speed and was higher at greater occlusion, with little hematocrit dependence. Higher speed and occlusion increased peak shear stress while reducing relative residence time; higher hematocrit further increased peak shear stress. Similar oxygen delivery could arise from substantially different flow environments: among 10 conditions providing oxygen delivery of approximately 9-12 milliliters per minute, peak shear stress ranged from approximately 25 to 70 pascals. Within conditions satisfying an illustrative minimum oxygen-delivery threshold, lower hematocrit permitted speed and occlusion settings yielding lower peak shear stress and relative residence time. Conclusions: Pediatric roller-pump settings that provide similar oxygen delivery can expose blood to markedly different shear and washout environments. Joint evaluation of these metrics may guide selection of speed, occlusion, and hematocrit to meet a target oxygen delivery while reducing shear and improving washout. Keywords: Cardiopulmonary bypass; roller pump; pediatric cardiac surgery; fluid-structure interaction; shear stress; relative residence time

bioengineering↗

bioRxiv2026

Joint Vector Flow Mapping and Segmentation: Ill-Posedness,Differentiable Bayesian Inference, and Synthetic Vortex-FlowBenchmarks

Vector flow mapping (VFM) reconstructs left-ventricular (LV) blood velocity from color-Doppler echocardiography by combining the measured beamwise component with physical and regularizing constraints. Analysis of the discrete VFM formulation shows that the inverse problem is intrinsically ill posed: the occurrence of singular modes can be predicted from the geometry of the segmented blood-pool domain, the imposed boundary conditions, and the degree of smoothing. These modes can propagate uncertainty along entire transverse bands of the reconstructed velocity field, yet conventional VFM neither quantifies this uncertainty nor allows for correcting the blood-pool segmentation. We introduce Bayesian VFM (B--VFM), a hierarchical framework that jointly infers radial and transverse velocities, a probabilistic blood-pool mask, their spatially resolved uncertainties, and hyperparameters weighting Doppler and segmentation fidelity, mass conservation, boundary conditions, and smoothness. The discretized posterior admits a closed-form gradient and exact Hessian, enabling computationally efficient, gradient-based MAP estimation, sampling, and direct analysis of ill-posed modes. Posterior inference combines Gibbs sampling of conjugate Gamma-distributed hyperparameters with conditional maximum-a-posteriori estimation and a Laplace approximation for the high-dimensional velocity and mask fields. To accommodate systematic departures from planar mass conservation, B-VFM can learn the covariance of the planar divergence residual from an ensemble of flows and incorporate it as a structured model-discrepancy prior. Independent chains converged reproducibly, while covariance priors learned from flow ensembles illustrated how model discrepancies can be incorporated into the inference. B--VFM was evaluated using Lamb-Chaplygin dipoles under ideal conditions and with Doppler corruption, Doppler voids, and segmentation defects, and using the Hicks-Moffatt family of spherical vortices to assess violations of planar mass conservation. The method produced smooth reconstructions, localized uncertainty near unreliable measurements and regions of model inconsistency, and used flow information to correct segmentation errors. Within the tested vortex family, the data-informed planar divergence prior reduced velocity bias and mask distortion. B--VFM thus provides an uncertainty-aware reconstruction method and a flexible foundation for future VFM formulations incorporating additional priors, observations, and physical models. Future work will evaluate the method using clinical data and more complex three-dimensional benchmark flows.

bioengineering↗

bioRxiv2026

Fibrosis burden and spatial pattern affect left atrial appendage stasis in multi-beat multi-physics simulations

Purpose: Atrial fibrosis is associated with thromboembolic risk in atrial fibrillation, but how fibrosis-related contractile impairment alters blood transport in the left atrium (LA) and left atrial appendage (LAA) remains unclear. Prior multi-physics simulations coupled electromechanical (EM) and computational fluid dynamics (CFD) models to show that fibrosis impairs LA function and flow, but were limited to booster-only contraction and could not separate the effects of fibrosis burden from its spatial distribution. Here we examined how fibrosis burden and spatial pattern independently relate to long-term LA and LAA hemodynamics in full-cycle, multi-beat simulations on a common LA anatomy. Methods: Three fibrosis patterns derived from late gadolinium enhancement MRI were considered: one from the patient providing the common anatomy and two from additional patients, with the latter mapped onto the common anatomy via universal atrial coordinates. All three patterns were applied globally at matched burdens of 15.6% and 31.2%, yielding six global-fibrosis cases and a non-fibrotic reference. Two patterns were also confined to the LAA at three local burdens (10%, 25%, and 50%), yielding six LAA-fibrosis cases. A 3D EM model for the LA anatomy was coupled to a 0D circulatory model, so that the simulations resolved the reservoir, conduit, and booster phases. Full-cycle EM-derived wall motion drove subsequent multi-beat CFD simulations. Region-specific emptying fraction (EF), non-dimensional kinetic energy (KE), and the 90th percentile of blood residence time (TR) were evaluated for the LA and LAA. Results: Left ventricular stroke volume remained nearly constant across cases, while increasing global fibrosis burden progressively reduced LA and LAA EF (LA: 36% to 30-31%; LAA: 44% to 28-38%) and monotonically increased LA TR across all patterns. Non-dimensional LA KE showed an approximately quadratic association with LA EF across patterns, whereas LAA KE was more scattered but still increased with LAA EF. In contrast, the relationship between the 90th percentile of LAA TR and LAA EF showed pattern-specific, non-monotonic trends. Conclusions: Fibrosis burden and spatial distribution jointly shape LA and LAA hemodynamics, but through different mechanisms. LAA EF is a robust functional descriptor of chamber-averaged kinetic energy regardless of fibrosis pattern, whereas LAA blood stasis depends additionally on the spatial distribution of fibrosis beyond what bulk emptying fraction predicts. These findings support incorporating imaging-derived fibrosis pattern, and not only burden, alongside functional metrics when assessing thrombogenic risk in the LAA.

bioengineering↗

bioRxiv2026

Mapping fibrotic microenvironments: single-cell and spatial profiling of Schistosoma mansoni-induced tissue fibrosis

Schistosoma-induced tissue fibrosis, driven by immune response to trapped schistosome eggs, is the principal cause of pathology and schistosomiasis-related morbidity. While praziquantel effectively clears adult parasites, no therapies exist to target eggs or egg-induced tissue fibrosis. Here, we utilise single-cell spatial transcriptomics to define the high-resolution molecular architecture of the fibrotic niche in Schistosoma mansoni-infected mice at 8 weeks post-infection. Our data reveal that the host executes divergent, organ-specific biological programs: constructing a rigid, concentric fibrotic granuloma for permanent egg sequestration in the liver while building a flexible, discontinuous collagen architecture in the intestine to facilitate egg transit. Spatially resolved cell-cell interaction analysis, unprecedented in schistosome-induced fibrosis, identifies the strongest cellular interactions between macrophages and collagen-producing cells, with TGF-{beta}-dominant ligand-receptor pairs in the hepatic niche and integrin-centered pairs in the intestine. Despite this architectural divergence, we detected a core signature of five ligand-receptor pairs shared across both tissues, suggesting shared signalling interactions that could be leveraged for pan-tissue therapeutics for treating schistosome-induced fibrosis. Together, these findings provide the first high-resolution spatial atlas of schistosomiasis-associated fibrosis and provide a foundational framework for discovering novel drug targets capable of reversing established tissue damage, addressing a critical clinical gap where current therapies fail.

molecular biology↗

bioRxiv2026

Left atrial flow and thrombosis risk from 4D CT contrast dynamics by physics-informed neural network and indicator dilution theory

Atrial fibrillation (AF) promotes blood stasis and thrombus formation, most often within the left atrial appendage (LAA), and can lead to stroke or transient ischemic attack (TIA). Time-resolved contrast-enhanced computed tomography (4D CT) captures left atrial (LA) opacification and washout, but it does not directly provide quantitative stasis metrics such as blood residence time. Patient-specific computational fluid dynamics (CFD) can quantify LA/LAA residence time, yet routine clinical use is limited by computational cost and sensitivity to patient-specific boundary conditions. Here, we present two complementary approaches to infer time-resolved 3D residence time fields directly from contrast dynamics. First, a physics-informed neural network (PINN) treats contrast as a passive scalar and jointly reconstructs velocity and residence time by enforcing the incompressible Navier-Stokes equations and transport equations for contrast concentration and residence time in moving, patient-specific LA anatomies. Second, an indicator dilution theory (IDT) formulation computes voxelwise, time-resolved residence time maps from contrast time curves alone by constructing a PV-referenced impulse response and modeling transport with a tank-in-series model with spatially dependent parameters. Both methods are benchmarked against patient-specific CFD in six cases spanning diverse LA function, including three patients with TIA or thrombus in the LAA and three patients free of events. Both approaches reproduce expected spatial and temporal trends, with higher residence time in the distal LAA and higher LAA residence time in cases with TIA or thrombus. IDT demonstrates the closest agreement with CFD across the full range of residence times and produces maps in seconds, facilitating clinical translation. In contrast, the PINN additionally recovers phase-dependent atrial flow structures, but tends to smooth and underestimate the highest residence-time regions and requires hours of training. Together, these results support a scalable workflow in which IDT enables rapid stasis screening from contrast CT, and PINNs provide a complementary pathway for detailed, patient-specific hemodynamic inference when full-field flow information is needed.

bioengineering↗

bioRxiv2025

Effect of Wall Motion Sampling on CFD-Derived Left Atrial Flow Metrics

The temporal resolution of medical imaging sequences used to drive patient-specific computational fluid dynamics (CFD) simulations remains limited, typically providing 10-20 frames per cardiac cycle. Therefore, temporal interpolation to reconstruct left atrial (LA) wall motion and boundary conditions is required, but its impact on hemodynamic predictions has not been systematically characterized. To investigate this, we constructed high-temporal-resolution reference wall-motion data using electromechanical (EM) simulations on five patient-specific atrial geometries with a history of atrial fibrillation. We then generated temporally downsampled datasets to emulate clinical frame rates (5, 10, 20, and 40 frames per cycle) and performed CFD simulations to isolate the effects of temporal undersampling on hemodynamic metrics. The focus was placed on kinetic energy, KE, and residence time, TR, particularly in the left atrial appendage (LAA), where thrombosis is most likely to occur. We employed an immersed boundary method to prescribe the wall motion and computed blood TR through a passive scalar transport equation. Results indicate that while global LA hemodynamic indices were marginally affected by the frame rate (errors < 9%), LAA metrics were more sensitive with errors up to 31% compared to reference values. The results based on 20 and 40 frames per cycle yielded favorable agreement with reference results, while 5-and 10-frame reconstructions showed larger, though not systematically biased, deviations from the reference. Importantly, patient ranking by blood-stasis indices was largely preserved. The analysis suggests that patientspecific LA reconstructions derived from dynamic CT imaging provide a reliable basis for estimating LAA blood-stasis indices. Higher frame rates ([≥] 20 per cycle) offer improved quantitative accuracy, while lower temporal resolutions may remain informative for patient stratification purposes, where relative ranking is more relevant than absolute accuracy.

bioengineering↗

bioRxiv2025

Systematic computational assessment of atrial function impairment due to fibrotic remodeling in electromechanical properties

Cardiac fibrosis is a pathological condition associated with many cardiovascular diseases. Atrial fibrosis leads to reduced atrial function, resulting in diminished blood flow and an increased risk of stroke. This reduced function arises from altered myocardial electrophysiological and mechanical properties. Identifying the relative importance of these fibrosis-associated properties can reveal the most significant determinants of left atrial function impairment. In this study, we used a computational framework to investigate the relative importance of various fibrosis-associated properties. Our model, a 3D electromechanical framework coupled with a 0D circulatory model, incorporated patient-specific geometries and fibrosis distributions from clinical imaging data. Nine parameters related to fibrotic remodeling (conduction velocity, ion channel expression levels, cell- and tissue-scale contractility, and stiffness) were analyzed using two sensitivity analysis schemes: a one-factor-at-a-time setup, allowing for the analysis of isolated effects, and a fractional factorial design, enabling the examination of combined effects. As output, we tracked various metrics derived from model-predicted pressure-volume loops. Impairment of L-type calcium current (ICaL) was most detrimental (up to 64% reduction in A-loop area). Conversely, reduced inward rectifier current (IK1) led to improved atrial function (up to 27% increase in A-loop area). Fractional factorial design analysis revealed that combination with other parameter changes blunted the impact of reduced ICaL but amplified the impact of reduced IK1. Further analysis of spatiotemporal distributions linked these effects to changes in intracellular calcium handling. Future research focusing on IK1 and ICaL could be highly significant for clinical and scientific advances. Modeling work can potentially help evaluate left atrial function among larger patient cohorts, focusing on strain analysis. Our work could also be extended to spatiotemporal simulations of blood flow and thrombosis, shedding light onto the mechanisms underlying atriogenic stroke. Author summaryCardiac fibrosis is a process where healthy heart muscle is replaced with non-conductive, non-contractile tissue. This change disrupts how the heart beats and contracts. In the left atrium, fibrosis is strongly linked to atrial fibrillation and a higher risk of stroke, the latter due to impaired pumping and altered blood flow. In this study, we used a detailed computer model of the heart, based on real patient-specific left atrial shapes and fibrosis patterns, to understand how different fibrosis-related changes affect atrial function. We tested nine features of the hearts electrical and mechanical behavior that are known to change during fibrosis, aiming to identify which ones have the most impact on the atrial function. We found that reducing the L-type calcium current -- an important signal for muscle contraction -- caused the greatest decrease in atrial performance. Surprisingly, reducing the inward rectifier potassium current actually improved it. These effects were tied to changes in calcium handling inside heart cells. Our findings highlight promising directions for future heart disease research and treatment.

systems biology↗

bioRxiv2024

Flow transport and not ejection fraction determines left ventricular stasis in patients with impaired systolic function

BackgroundImpaired left ventricular (LV) systolic function is a major risk factor for mural thrombosis and embolism, but LV ejection fraction (EF) poorly predicts these events, suggesting the existence of additional sources of variability. Advances in multi-dimensional flow imaging and patient-specific simulations have sparked the derivation of diverse metrics to assess blood stasis and transit efficiency. However, simple models to interpret these metrics and their dependence on chamber function are lacking. MethodsWe introduce queue models of LV blood transit connecting two common metrics of LV efficiency: flow component analysis and residence time (RT) mapping. These models yield closed-form expressions for the average RT of blood in the LV as a function of EF, direct flow (DF) --blood entering and leaving the LV in one cardiac cycle, and residual volume (RV) -- blood persisting in the LV for >2 cycles. Models performance was tested against RT obtained from vector flow mapping in 332 subjects, including controls and patients with acute myocardial infarction (AMI), hypertrophic (HCM) and dilated (DCM) cardiomyopathy. ResultsQueue models revealed RT is increasingly sensitive to DF as EF decreases, contradicting the traditional view of large DF as a teleological advantage. Instead, RT is minimized when blood transits in a first-in-first-out (FIFO) manner, while DF short-circuits the FIFO pattern, prolonging RT for other flow components. FIFO models show a good performance to assess RT in the studied subjects, especially when accounting for patient-specific DF and RV, with R: 0.62 for the pooled data, 0.70 for control, and 0.60, 0.80 and 0.40 for AMI, DCM and HCM groups respectively. ConclusionBy developing queue models of LV blood transit, and testing them on a large clinical database, we show large DF may contribute to increased blood stasis when EF is low. These models also explain why EF is a poor thrombosis risk marker in AMI and DCM.

physiology↗

bioRxiv2024

Neutrophils exhibit distinct migration phenotypes that are modulated by transendothelial migration

The extravasation of polymorphonuclear neutrophils (PMNs) is a critical component of the innate immune response that involves transendothelial migration (TEM) and interstitial migration. TEM-mediated interactions between PMNs and vascular endothelial cells (VECs) trigger a cascade of biochemical and mechanobiological signals whose effects on interstitial migration are currently unclear. To address this question, we cultured human VECs on a fibronectin-treated transwell insert to model the endothelium and basement membrane, loaded PMN-like differentiated HL60 (dHL-60) cells in the upper chamber of the insert, and collected the PMNs that crossed the membrane-supported monolayer from the lower chamber. The 3D chemotactic migration of the TEM-conditioned PMNs through collagen matrices was then quantified. Data collected from over 50,000 trajectories showed two distinct migratory phenotypes, i.e., a high-persistence phenotype and a low-persistence phenotype. These phenotypes were conserved across treatment conditions, and their existence was confirmed in human primary PMNs. The high-persistence phenotype was characterized by more straight trajectories and faster migration speeds, whereas the low-persistence one exhibited more frequent sharp turns and loitering periods. A key finding of our study is that TEM induced a phenotypic shift in PMNs from high-persistence migration to low-persistence migration. Changes in the relative proportion of high-persistence and low-persistence populations correlated with GRK2 expression levels. Inhibiting GRK2 hindered the TEM-induced shift in migratory phenotype and impaired the phagocytic function of PMNs. Overall, our study suggests that TEM-mediated GRK2 signaling primes PMNs for a migration phenotype better suited for spatial exploration and inflammation resolution. These observations provide novel insight into the biophysical impacts of TEM that priming PMNs is essential to conduct sentinel functions.

cell biology↗

bioRxiv2024

Hemodynamics Affects Factor XI/XII Anticoagulation Efficacy in Patient-Specific Left Atrial Models

Atrial fibrillation (AF) disrupts the circulation of blood through the left atrium (LA), and may result in relative stasis in the left atrial appendage (LAA), increasing thromboembolic risk. Anticoagulant agents can lower this risk, but currently used agents target the common pathway central to the coagulation cascade, increasing bleeding risk. Anticoagulants such as factor XI/XII inhibitors target the initial phase of the intrinsic pathway, with a significantly lower associated bleeding risk. However, these agents efficacy in preventing thrombosis in patient-specific flow conditions is not fully understood. We hypothesized that patient-specific flow patterns in the LA and LAA not only influence the risk of thrombosis but also the effectiveness of anticoagulation agents. We simulated blood flow and the intrinsic coagulation pathway in patient-specific LA anatomies with and without factor XI/XII inhibition to test this hypothesis. We considered thirteen patients in sinus rhythm and AF, several of whom had an LAA clot or a history of transient ischemic attacks. We used computational fluid dynamics based on 4D CT imaging and a detailed 32-species coagulation system to run 247 simulations for 13 patients, systematically sweeping over a wide range of factor XI/XII inhibition levels. Implementing a novel multi-fidelity coagulation modeling approach accelerated computations by two orders of magnitude, enabling the large number of simulations performed. Our simulations provide spatiotemporally resolved maps of thrombin concentration throughout the LA, showing it peaks inside the LAA. Coagulation metrics based on peak LAA thrombin dynamics suggested patients could be classified as non-coagulating, moderately and severely coagulating cases. Severely coagulating cases had significantly slower flow and higher residence time than moderately coagulating patients inside the LAA, requiring stronger factor XI/XII inhibition to blunt thrombin growth. The methodology outlined in this study has the potential to enable personalized assessments of coagulation risk and tailor anticoagulation therapy based on medical imaging.

bioengineering↗

bioRxiv2024

Uncertainty-Aware Traction Force Microscopy

Traction Force Microscopy (TFM) is a versatile tool to quantify cell-exerted forces by imaging and tracking fiduciary markers embedded in elastic substrates. The computations involved in TFM are ill-conditioned, and data smoothing or regularization is required to avoid overfitting the noise in the tracked substrate displacements. Most TFM calculations depend critically on the heuristic selection of regularization (hyper)parameters affecting the balance between overfitting and smoothing. However, TFM methods rarely estimate or account for measurement errors in substrate deformation to adjust the regularization level accordingly. Moreover, there is a lack of tools to quantify how these errors propagate to the recovered traction stresses. These limitations make it difficult to interpret TFM readouts and hinder comparing different experiments. This manuscript presents an uncertainty-aware TFM technique that estimates the variability in the magnitude and direction of the traction stress vector recovered at each point in space and time of each experiment. In this technique, substrate deformation and its uncertainty are quantified using a non-parametric bootstrap PIV method by resampling the microscopy image pixels (PIV-UQ). This information is passed to a hierarchical Bayesian framework that automatically selects its hyperparameters to perform spatially adaptive regularization conditioned on image quality and propagates the uncertainty to the traction stress readouts (TFM-UQ). We validate the performance of PIV-UQ and TFM-UQ using synthetic datasets with prescribed image quality variations and demonstrate the application of PIV-UQ and TFM-UQ to experimental datasets. These studies show that TFM-UQ locally adapts the level of smoothing, outperforming traditional regularization methods. They also illustrate how uncertainty-aware TFM tools can be used to objectively choose key image analysis parameters like PIV-UQ interrogation window size. We anticipate that these tools will allow for decoupling biological heterogeneity from measurement variability and facilitate automating the analysis of large datasets by parameter-free, input data-based regularization.

biophysics↗

bioRxiv2024

Patient-specific multi-physics simulations of fibrotic changes in left atrial tissue mechanics impact on hemodynamics

Stroke is a leading cause of death and disability worldwide. Atrial myopathy, including fibrosis, is associated with an increased risk of ischemic stroke, but the mechanisms underlying this association are poorly understood. Fibrosis modifies myocardial structure, impairing electrical propagation and tissue biomechanics, and creating stagnant flow regions where clots could form. Fibrosis can be mapped non-invasively using late gadolinium enhancement magnetic resonance imaging (LGE-MRI). However, fibrosis maps are not currently incorporated into stroke risk calculations or computational electro-mechano-fluidic models. We present multi-physics simulations of left atrial (LA) myocardial motion and hemodynamics using patient-specific anatomies and fibrotic maps from LGE-MRI. We modify tissue stiffness and active tension generation in fibrotic regions and investigate how these changes affect LA flow for different fibrotic burdens. We find that fibrotic regions and, to a lesser extent, non-fibrotic regions experience reduced myocardial strain, resulting in decreased LA emptying fraction consistent with clinical observations. Both fibrotic tissue stiffening and hypocontractility independently reduce LA function, but together, these two alterations cause more pronounced effects than either one alone. Fibrosis significantly alters flow patterns throughout the atrial chamber, and particularly, the filling and emptying jets of the left atrial appendage (LAA). The effects of fibrosis in LA flow are largely captured by the concomitant changes in LA emptying fraction except inside the LAA, where a multi-factorial behavior is observed. This work illustrates how high-fidelity, multi-physics models can be used to study thrombogenesis mechanisms in patient-specific anatomies, shedding light onto the links between atrial fibrosis and ischemic stroke. Key pointsO_LILeft atrial (LA) fibrosis is associated with arrhythmogenesis and increased risk of ischemic stroke; its extent and pattern can be quantified on a patient-specific basis using late gadolinium enhancement magnetic resonance imaging. C_LIO_LICurrent stroke risk prediction tools have limited personalization, and their accuracy could be improved by incorporating patient-specific information like fibrotic maps and hemodynamic patterns. C_LIO_LIWe present the first electro-mechano-fluidic multi-physics computational simulations of LA flow, including fibrosis and anatomies from medical imaging. C_LIO_LIMechanical changes in fibrotic tissue impair global LA motion, decreasing LA and left atrial appendage (LAA) emptying fractions, especially in subjects with higher fibrosis burdens. C_LIO_LIFibrotic-mediated LA motion impairment alters LA and LAA flow near the endocardium and the whole cavity, ultimately leading to more stagnant blood regions in the LAA. C_LI

bioengineering↗

bioRxiv2024

Super-resolution Left Ventricular Flow and Pressure Mapping by Navier-Stokes-Informed Neural Networks

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 patients 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.

bioengineering↗

bioRxiv2023

Efficient multi-fidelity computation of blood coagulation under flow

Clot formation is a crucial process that prevents bleeding, but can lead to severe disorders when imbalanced. This process is regulated by the coagulation cascade, a biochemical network that controls the enzyme thrombin, which converts soluble fibrinogen into the fibrin fibers that constitute clots. Coagulation cascade models are typically complex and involve dozens of partial differential equations (PDEs) representing various chemical species transport, reaction kinetics, and diffusion. Solving these PDE systems computationally is challenging, due to their large size and multi-scale nature. We propose a multi-fidelity strategy to increase the efficiency of coagulation cascade simulations. Leveraging the slower dynamics of molecular diffusion, we transform the governing PDEs into ordinary differential equations (ODEs) representing the evolution of species concentrations versus blood residence time. We then Taylor-expand the ODE solution around the zero-diffusivity limit to obtain spatiotemporal maps of species concentrations in terms of the statistical moments of residence time, [Formula], and provide the governing PDEs for [Formula]. This strategy replaces a high-fidelity system of N PDEs representing the coagulation cascade of N chemical species by N ODEs and p PDEs governing the residence time statistical moments. The multi-fidelity order(p) allows balancing accuracy and computational cost, providing a speedup of over N/p compared to high-fidelity models. Using a simplified coagulation network and an idealized aneurysm geometry with a pulsatile flow as a benchmark, we demonstrate favorable accuracy for low-order models of p = 1 and p = 2. These models depart from the high-fidelity solution by under 16% (p = 1) and 5% (p = 2) after 20 cardiac cycles. The favorable accuracy and low computational cost of multi-fidelity models could enable unprecedented coagulation analyses in complex flow scenarios and extensive reaction networks. Furthermore, it can be generalized to advance our understanding of other systems biology networks affected by blood flow.

bioengineering↗

bioRxiv2023

Tunable photoinitiated hydrogel microspheres for direct quantification of cell-generated forces in complex three-dimensional environments

We present a high-throughput method using standard laboratory equipment and microfluidics to produce cellular force microscopy probes with controlled size and elastic modulus. Mechanical forces play crucial roles in cell biology but quantifying these forces in physiologically relevant systems remains challenging due to the complexity of the native cell environment. Polymerized hydrogel microspheres offer great promise for interrogating the mechanics of processes inaccessible to classic force microscopy methods. However, despite significant recent advances, their small size and large surface-to-volume ratio impede the high-yield production of probes with tunable, monodisperse distributions of size and mechanical properties. To overcome these limitations, we use a flow-focusing microfluidic device to generate large quantities of droplets with highly reproducible, adjustable radii. These droplets contain acrylamide gel precursor and the photoinitiator Lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) as a source of free radicals. LAP provides fine control over microsphere polymerization due to its high molar absorptivity at UV wavelengths and moderate water solubility. The polymerized microspheres can be functionalized with different conjugated extracellular matrix proteins and embedded with fluorescent nanobeads to promote cell attachment and track microsphere deformation. As proof of concept, we measure the mechanical forces generated by a monolayer of vascular endothelial cells engulfing functionalized microspheres. Individual nanobead motions are tracked in 3D and analyzed to determine the 3D traction forces within seconds and without the need for solving an ill-posed inverse problem. These results reveal that the cell monolayer collectively exerts strong radial compression and subtle lateral distortions on the encapsulated probe.

biophysics↗

bioRxiv2023

Pulmonary vein flow split effects in patient-specific simulations of left atrial flow

Disruptions to left atrial (LA) blood flow, such as those caused by atrial fibrillation (AF), can lead to thrombosis in the left atrial appendage (LAA) and an increased risk of systemic embolism. LA hemodynamics are influenced by various factors, including LA anatomy and function, and pulmonary vein (PV) inflow conditions. In particular, the PV flow split can vary significantly among and within patients depending on multiple factors. In this study, we investigated how changes in PV flow split affect LA flow transport, focusing on blood stasis in the LAA, using a high-fidelity patient-specific computational fluid dynamics (CFD) model. We analyzed LA anatomies from eight patients with varying atrial function, including three with AF and either a LAA thrombus or a history of TIAs. Using four different flow splits (60/40% and 55/45% through right and left PVs, even flow rate, and same velocity through each PV), we found that flow patterns are sensitive to PV flow split variations, particularly in planes parallel to the mitral valve. Changes in PV flow split also had a significant impact on blood stasis and could contribute to increased risk for thrombosis inside the LAA, particularly in patients with AF and previous LAA thrombus or a history of TIAs. Our study highlights the importance of considering patient-specific PV flow split variations when assessing LA hemodynamics and identifying patients at increased risk for thrombosis and stroke.

bioengineering↗

bioRxiv2021

Biomechanical interactions of Schistosoma mansoni eggs with vascular endothelial cells facilitate egg extravasation

The eggs of the parasitic blood fluke, Schistosoma, are the main drivers of the chronic pathologies associated with schistosomiasis, a disease of poverty afflicting approximately 220 million people worldwide. Eggs laid by Schistosoma mansoni in the bloodstream of the host are encapsulated by vascular endothelial cells (VECs), the first step in the migration of the egg from the blood stream into the lumen of the gut and eventual exit from the body. The biomechanics associated with encapsulation and extravasation of the egg are poorly understood. We demonstrate that S. mansoni eggs induce VECs to form two types of membrane extensions during encapsulation; filopodia that probe eggshell surfaces and intercellular nanotubes that presumably facilitate VEC communication. Encapsulation efficiency, the number of filopodia and intercellular nanotubes, and the length of these structures depend on the eggs vitality and, to a lesser degree, its maturation state. During encapsulation, live eggs induce VEC contractility and membranous structures formation, in a Rho/ROCK pathway-dependent manner. Using elastic hydrogels embedded with fluorescent microbeads as substrates to culture VECs, live eggs induce VECs to exert significantly greater contractile forces during encapsulation than dead eggs, which leads to 3D deformations on both the VEC monolayer and the flexible substrate underneath. These significant mechanical deformations cause the VEC monolayer tension to fluctuate with eventual rupture of VEC junctions, thus facilitating egg transit out of the blood vessel. Overall, our data on the mechanical interplay between host VECs and the schistosome egg improve our understanding of how this parasite manipulates its immediate environment to maintain disease transmission.

microbiology↗

bioRxiv2021

Cyclic mechanical stresses alter erythrocyte membrane composition and microstructure and trigger macrophage phagocytosis

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, we circulated RBCs through microfluidic devices containing microchannels that replicate the IES. The cyclic mechanical stresses experienced by the cells affected their biophysical properties and molecular composition, accelerating cell aging. Specifically, RBCs quickly transitioned to a more spherical, less deformable phenotype that hindered microchannel passage, causing hemolysis. This transition was associated with the release of membrane vesicles, which self-extinguished as the spacing between membrane-cytoskeleton linkers became tighter. Proteomics analysis of the mechanically aged RBCs revealed significant losses of essential proteins involved in antioxidant protection, gas transport, and cell metabolism. Finally, we show that these changes made mechanically aged RBCs more susceptible to macrophage phagocytosis. These results provide a comprehensive model to explain how physical stress induces RBC clearance in the spleen.

bioengineering↗