Biology subjects

Apolinar-Fernandez, A.

Publications and source records attributed to Apolinar-Fernandez, A..

4 recordsLinked to original sources

bioRxiv2025

Data-driven traction force microscopy in 3D collagen hydrogels

Quantitative measurements of cell-generated forces in fibrillar hydrogels have traditionally modeled the extracellular matrix as a continuum. Here we present a data-driven 3D traction force microscopy (DD-TFM) approach that reconstructs discrete collagen fiber networks from second-harmonic generation images and assigns fiber mechanics calibrated by shear rheology. In silico tests confirm the robustness of an inverse force-recovery method, and application to cells in collagen reveals pulling patterns and fiber-level stress distributions.

biophysics↗

bioRxiv2025

Inverse modeling of heterogeneous ECM mechanical properties in nonlinear 3DTFM

Accurate characterization of cellular tractions is crucial for understanding cell-extracellular matrix (ECM) mechanical interactions and their implications in pathology-related situations, yet their direct measurement in experimental setups remains challenging. Traction Force Microscopy (TFM) has emerged as a key methodology to reconstruct traction fields from displacement data obtained via microscopic imaging techniques. While traditional TFM methods assume homogeneous and static ECM properties, the dynamic nature of the ECM through processes such as enzyme-induced collagen degradation or cellmediated collagen deposition i.e. ECM remodeling, requires approaches that account for spatio-temporal evolution of ECM stiffness heterogeneity and other mechanical properties. In this context, we present a novel inverse methodology for 3DTFM, capable of reconstructing spatially heterogeneous distributions of the ECMs stiffness. Our approach formulates the problem as a PDE-constrained inverse method which searches for both displacement and the stiffness map featured in the selected constitutive law. The elaborated numerical algorithm is integrated then into an iterative Newton-Raphson/Finite Element Method (NR/FEM) framework, bypassing the need for external iterative solvers. We validate our methodology using in silico 3DTFM cases based on real cell geometries, modeled within a nonlinear hyperelastic framework suitable for collagen hydrogels. The performance of our approach is evaluated across different noise levels, and compared versus the commonly used iterative L-BFGS algorithm. Besides the novelty of our formulation, we demonstrate the efficacy of our approach both in terms of accuracy and CPU time efficiency.

biophysics↗

bioRxiv2024

Multiscale characterization of the mechanics of curved fibered structures with application to biological materials

Curved fibered structures are ubiquitous in nature and this organization is found in the majority of biological tissues. Indeed, the mechanical behavior of these materials is of pivotal importance in biomechanics and mechanobiology fields. In this paper, we develop a multiscale formulation to characterize the macroscopic mechanical nonlinear behavior from the microstructure of fibered matrices. From the analysis of the mechanics of a randomly curved single fiber, a fibered matrix model is built to determine the macroscopic behavior following a homogenization approach. The model is tested for tensile, compression and shear loads in a number of applications reminiscent to collagen extracellular matrices. However, any other fibered microstructures can be studied following the proposed formulation. The presented approach naturally recovers instabilities at compression as well as the strain stiffening regime, which are observed experimentally in the mechanical behavior of collagen matrices. Indeed, it was found that the bending energy associated to fiber unrolling, is the most important source of energy developed by fibers for the analyzed cases in tensile and shear in all deformation regions (except the strain stiffening region), whereas bending energy dominates at compression too during buckling. The proposed computational framework can also be used to perform multiscale simulations in the referred applications. As a result, the developed methodology may be an interesting and complementary tool to characterize the nonlinear behavior and evolution of curved fibered structures present in biology and engineered materials.

bioengineering↗

bioRxiv2022

Traction force reconstruction assessment on real three-dimensional matrices and cellular morphologies

Traction force microscopy (TFM) allows to estimate tractions on the surface of cells when they mechanically interact with hydrogel substrates that mimic the extracellular matrix (ECM). The field of mechanobiology has a strong interest in using TFM in 3D in vitro models. However, there are a number of challenges that hamper the accuracy of 3D TFM and that are often bypassed. In this study, the computational efficiency and accuracy of TFM, referred to traction reconstruction from synthetically generated (control) ground truth solutions, are assessed from four different perspectives: magnitude of cellular pulling force (and hence strain level achieved in the hydrogel), effect of the complexity of the cellular morphology, accuracy and computational efficiency of forward vs inverse traction recovery methods, and the effect of incorrectly selecting a constitutive model that describes the behavior of the ECM (i.e. linear/nonlinear). The main results showed: (i) traction reconstruction is more challenging for complex cell morphologies, (ii) there is no significant impact of the magnitude of cellular pulling force on the overall reconstruction accuracy, and (iii) modeling a nonlinear hydrogel with a linear constitutive model leads to non-negligible errors (up to 80% and 30% for forward and inverse methodologies, respectively) in traction reconstruction. This study expands the characterization of the accuracy and efficiency of 3D TFM, highlighting important factors to be considered in future 3D TFM in vitro applications.

cell biology↗