Biology subjects

Kandasamy, A.

Publications and source records attributed to Kandasamy, A..

4 recordsLinked to original sources

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↗

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↗

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↗

bioRxiv2020

A balance between matrix deformation and the coordination of turning events governs directed neutrophil migration in 3-D matrices

Three-dimensional (3-D) neutrophil migration is essential for immune surveillance and inflammatory responses. During 3-D migration, especially through extravascular spaces, neutrophils rely on frontal protrusions and rear contractions to squeeze and maneuver through extracellular matrices containing narrow pores. However, the role of matrix density and the cells ability to probe and remodel matrix pores during 3-D chemotaxis are far from being understood. We investigated these processes by tracking the trajectories of over 20,000 neutrophils in a 3-D migration device containing collagen matrices of varying concentrations and analyzing the shape of these trajectories at multiple scales. Additionally, we quantified the transient 3-D matrix deformations caused by the migrating cells. The mean pore size of our reconstituted collagen matrices decreased when the collagen concentration ([col]) was increased. In low-[col] matrices, neutrophils exerted large transient deformations and migrated in relatively straight trajectories. In contrast, they were not able to appreciably deform high- [col] matrices and adapted to this inability by turning more often to circumvent these narrow matrix pores. While this adaptation resulted in slower migration, the cells were able to balance the more frequent turning with the long-range directional bias necessary for chemotaxis. Based on our statistical analysis of cell trajectories, we postulate that neutrophils achieve this balance by using matrix obstacles as pivoting points to steer their motion towards the chemoattractant. Inhibiting myosin-II contractility or Arp2/3-mediated pseudopod protrusions not only compromised the cells ability to deform the matrix, but also made them switch to increased turning in more restrictive matrices when compared to untreated control cells. Both myosin-II contractility and Arp2/3-mediated branched polymerization of actin played a role in fast migration, but Arp2/3 was also crucial for neutrophils when coordinating the orientations of successive turns to prevent veering away from the chemotactic path. These results may contribute to an improved understanding of the mechanisms employed by migrating neutrophils in confined 3-D environments, as well as the molecular and environmental regulators for maintaining persistent motion.

biophysics↗