Magnetic nanoparticles (MNPs) derived from the Massart coprecipitation method have played a pioneering role in bridging materials science and biology. Their magnetic moment and nanoscale dimensions have long enabled applications in magnetic resonance imaging, targeted drug delivery, separation technologies, and hyperthermia. Beyond these well-established uses, a growing research direction has emerged at the interface of physics and biology: the application of MNPs in mechanobiology, the study of how mechanical forces regulate cellular and tissue functions. This review examines how Massart MNPs can be used to generate, transmit, and measure forces within living systems. Particular attention is given to interfacial control through advanced surface chemistries, which ensure colloidal stability, minimize toxicity, and preserve the nanoscale integrity of the particles. We also show that the robustness and scalability of Massart synthesis make it ideally suited to the production of biocompatible nanomaterials in quantities required for comprehensive biological studies. Two complementary approaches are discussed. The first exploits MNP assemblies that arise spontaneously within cells, in
Mechanobiology is gaining more and more traction as the fundamental role of physical forces in biological function becomes clearer. Forces at the microscale are often measured indirectly using inverse problems such as Traction Force Microscopy because biological experiments are hard to access with physical probes. In contrast with the experimental nature of biology and physics, these measurements do not come with error bars, confidence regions, or p-values. The aim of this manuscript is to publicize this issue and to propose a first step towards a remedy therefor in the form of a general reconstruction framework. We also show that this opens the door to hypothesis testing of seemingly abstract experimental questions.
Morphoelasticity represents a foundational theory for tracing back growth, remodelling, and morphogenesis, yet crucial challenges persist. A unified growth law -- independent of a priori assumptions about constitutive relations or specified structures of the growth tensor -- remains in fact elusive, as does an intimate connection between local anisotropic growth, morphogenesis dynamics, diffusion phenomena and mechanics. When anisotropy of growth is not prescribed arbitrarily, current frameworks mainly attribute shape emergence to growth-induced global configurational switches, somehow neglecting the existence of local drivers of spontaneous patterning or distorsions also in stress-free conditions. To overcome these limitations, in this work we propose a theoretical approach that reformulates anisotropic growth, remodeling, and morphogenesis starting from first principles, grounded in mass balance. In particular, by positing mass conservation as the sole dynamic constraint for the growth problem, we generalize the mass balance equation to derive evolution laws for mass distribution and geometric reconfiguration. This reveals how mass transport and associated microstructural evoluti
The proteins involved in cells' mechanobiological processes have evolved specialized and surprising responses to applied forces. Biochemical transformations that show catch-to-slip switching and force-induced pathway switching serve important functions in cell adhesion, mechano-sensing and signaling, and protein folding. We show that these switching behaviors are generated by singularities in the flow field that describes force-induced deformation of bound and transition states. These singularities allow for a complete characterization of switching mechanisms in 2-dimensional (2D) free energy landscapes, and provide a path toward elucidating novel forms of switching in higher dimensional models. Remarkably, the singularity that generates a catch-slip switch occurs in almost every 2D free energy landscape, implying that almost any bond admitting a 2D model will exhibit catch-slip behavior under appropriate force. We apply our analysis to models of P-selectin and antigen extraction to illustrate how these singularities provide an intuitive framework for explaining known behaviors and predicting new behaviors.
In-vivo, cells are frequently exposed to multiple mechanical stimuli arising from the extracellular microenvironment, with deep impact on many biological functions. On the other hand, current methods for mechanobiology do not allow to easily replicate in-vitro the complex spatio-temporal behavior of such mechanical signals. Here, we introduce a new platform for studying the mechanical coupling between the extracellular environment and the nucleus in living cells, based on active substrates for cell culture made of Fe-coated polymeric micropillars. Under the action of quasi-static external magnetic fields, each group of pillars produces synchronous nano-mechanical stimuli at different points of the cell membrane, thanks to the highly controllable pillars' deflection. This method enables to perform a new set of experiments for the investigation of cellular dynamics and mechanotransduction mechanisms in response to a periodic nano-pinching, with tunable strength and arbitrary temporal shape. We applied this methodology to NIH3T3 cells, demonstrating how the nano-mechanical stimulation affects the actin cytoskeleton, nuclear morphology, H2B core-histone dynamics and MKL transcription-c
Tumor cells invade individually or in groups, mediated by mechanical interactions between cells and their surrounding matrix. These multicellular dynamics are reminiscent of leader-follower coordination and epithelial-mesenchymal transitions (EMT) in tissue development, which may occur via dysregulation of associated molecular or physical mechanisms. However, it remains challenging to elucidate such phenotypic heterogeneity and plasticity without precision measurements of single cell behavior. The convergence of technological developments in live cell imaging, biophysical measurements, and 3D biomaterials are highly promising to reveal how tumor cells cooperate in aberrant microenvironments. Here, we highlight new results in collective migration from the perspective of cancer biology and bioengineering. First, we review the biology of collective cell migration. Next, we consider physics-inspired analyses based on order parameters and phase transitions. Further, we examine the interplay of metabolism and heterogeneity in collective migration. We then review the extracellular matrix, and new modalities for mechanical characterization of 3D biomaterials. We also explore epithelial-mes
Clustering of ligand-binding receptors of different types on thickened isles of the cell membrane, namely lipid rafts, is an experimentally observed phenomenon. Although its influence on cell response is deeply investigated, the role of the coupling between mechanical processes and multiphysics involving the active receptors and the surrounding lipid membrane during ligand-binding has not yet been understood. Specifically, the focus of this work is on G-protein-coupled receptors (GPCRs), which regulate specific cell processes through chemical signalling pathways involving a synergistic balance between the cyclic Adenosine Monophosphate (cAMP) produced by active GPCRs in the intracellular environment and its efflux, mediated by Multidrug Resistance Proteins (MRPs) transporters. This paper develops a multiphysics approach based on the interplay among energetics, multiscale geometrical changes and mass balance of species, i.e. active GPCRs and MRPs, including diffusion and kinetics of binding and unbinding. Because the obtained energy depends upon both the kinematics and the changes of species densities, balance of mass and of linear momentum are coupled and govern the space-time evol
The role and importance of mechanical properties of cells and tissues in cellular function, development as well as disease has widely been acknowledged, however standard techniques currently used to assess them exhibit intrinsic limitations. Recently, a new type of optical elastography, namely Brillouin microscopy, has emerged as a non-destructive, label- and contact-free method which can probe the viscoelastic properties of biological samples with diffraction-limited resolution in 3D. This has led to increased attention amongst the biological and medical research communities, but also to debates about the interpretation and relevance of the measured physical quantities. Here, we review this emerging technology by describing the underlying biophysical principles and discussing the interpretation of Brillouin spectra arising from heterogeneous biological matter. We further elaborate on the technique's limitations as well as its potential for new insights in biology in order to guide interested researchers from various fields.
A famous and thoroughly investigated instability set-up, susceptible to wrinkling and creasing, consists of an elastic half-space being prestressed under a dead load, applied at infinity and, possibly, on its surface. We consider the case of a pressure or a suction applied on the surface and show that wrinkling and creasing occur in a surprising way, completely different from dead load. With reference to incompressible neo-Hookean elasticity and assuming the prevalence of a uniaxial prestress state induced by the application of a uniform pressure, no wrinkling or creasing is foreseen, whereas -- unexpectedly -- they do when reversing the sign of pressure, which is then a suction, thus leading to tensile creasing and tensile wrinkling. When a biaxial prestress state is considered, it is shown that some loading paths can be envisaged, able to grow to infinity without causing any instability. Consequently, we suggest that, according to its sign, pressure can promote or delay surface instabilities, a finding which may have implications for mechanobiology or microfluidic fluid-structure interaction.
In this article, I advance the idea that physics plays a central role in cell differentiation and makes fundamental contributions to morphogenesis, revealing the totipotent nature of the zygote. Totipotency is a persistent mechanical memory that preserves the biomechanical records of animal morphogenesis. I examine the mechanical and biophysical pathways underlying cell differentiation in embryonic development and cancer, treating them as closely related biological and mechanical processes. Drawing inspiration from evolutionary history, I also propose a biophysical mechanism for the emergence of the animal nervous system. By linking physical principles to cellular differentiation, this review positions mechanobiology as a pillar of innovation with high-impact clinical implications for diseases such as cancer.
Cellular traction forces are conventionally measured by tracking the displacement of beads or micropillars, an approach fundamentally limited by optical diffraction and the classical Euler-Bernoulli beam assumption, which is accurate only when the traction-induced deformation is relatively small while the aspect ratio of micropillars is large. Here we introduce an alternative approach: quantifying force through direct measurement of rotational angle, in addition of displacement of the micropillar, using fluorescent nanodiamonds as embedded 3D orientation markers. Specifically, by integrating optically detected magnetic resonance (ODMR) with laser polarization modulation (LPM), we determine the complete three-dimensional orientation of nanodiamonds attached to PDMS micropillars with sub-degree precision ($\sim$0.5$^\circ$). This angle-based measurement framework bypasses the resolution constraints of displacement tracking and remains valid for stocky beams or when large deformations occur. Finite-element simulations demonstrate that our method reduces force estimation errors by at least 10% compared to conventional displacement-based approaches. Moreover, we successfully capture mul
Probing forces, deformations and generally speaking the mechanical properties of cells is the hallmark of mechanobiology. In the last two decades many techniques have been developed to this end that are largely based on deforming the cells and measuring the reaction force. In cells, an alternative approach has been implemented mid 2010's, based on Brillouin Light Scattering (BLS) that produces a spectrum that can be interpreted as the response of the sample to an infinitesimal uniaxial compression at picosecond timescales. In all of these measurements, the response of the cell is quantified with a colloquial "stiffness" that encompasses both the contribution of load-bearing structures and volume changes, much to confusion. To clarify the interpretation of the hypersonic data obtained from BLS spectra, we vary the relative volume fraction of intracellular water and solid network by applying osmotic compressions to single cells. In the nucleus, we observe a non-linear increase in the sound velocity and attenuation with increasing osmotic pressure that we fit to a poroelastic model, providing an estimate of the friction coefficient between the water phase and the network. By comparing
The accurate modeling of biological processes allows to predict the spatio-temporal behavior of living tissues by computer-aided (in-silico) testing, a useful tool for the development of medical strategies, avoiding the expenses and potential ethical implications of in-vivo experimentation. A model for bone healing in mouth would be useful for selecting proper surgical techniques in dental procedures. In this paper, the formulation and implementation of a model for Intramembranous Ossification is presented aiming to describe the complex process of bone tissue formation in tooth extraction sites. The model consists in a mathematical description of the mechanisms in which different types of cells interact, synthesize and degrade extra-cellular matrices under the influence of biochemical factors. Special attention is given to angiogenesis, oxygen-dependent effects and growth factor-induced apoptosis of fibroblasts. Furthermore, considering the depth-dependent vascularization of mandibular bone and its influence on bone healing, a functional description of the cell distribution on the severed periodontal ligament (PDL) is proposed. The developed model was implemented using the finite e
The cytoskeleton (CSK) plays an important role in many cell functions. Given the similarities between the mechanical behavior of tensegrity structures and the CSK, many studies have proposed different tensegrity-based models for simulating cell mechanics. However, the low symmetry of most tensegrity units has hindered the analysis of realistic 3D structures. As a result, tensegrity-based modeling in cell mechanics has been mainly focused on single cells or monolayers. In this paper, we propose a 3D tensegrity model based on the finite element method for simulating 3D cell mechanics. We show that the proposed model not only captures the nonlinearity of a single cell in an indentation test and a monolayer in stretch test but also the non-uniform stress distribution in multicellular spheroids upon non-uniform prestress design. Furthermore, we introduce a multiscale data-driven framework for cellular mechanics to optimize the computation, thus paving the way for modeling the mechanobiology of large cellular assemblies such as organs.
While mechanobiology has demonstrated that precise control over mechanical properties at the whole-cell level is crucial for many biological functions, comparatively little attention has been paid to the intracellular mechanical properties. Experimental tools have only recently become available to adequately measure the viscoelasticity and activity of the cytosol, revealing, revealing that the active, non-equilibrium nature of the intracellular environment must be carefully considered. To explore the interplay between active forces and viscoelastic properties, it is helpful to consider our current understanding of intracellular active mechanics. In this review, we aim not only to provide an intuitive and quantitative introduction to the relevant physical concepts, but also to offer an overview of the proteins that establish intracellular active mechanics, highlighting their spatial and temporal variation with a particular focus on the role of activity. Although we are only beginning to uncover the importance of intracellular active mechanics for cellular mechanisms, it is increasingly clear that these properties must be precisely regulated to ensure proper cellular function.
Recent studies have highlighted intracellular viscosity as a key biomechanical property with potential as a biomarker for cancer cell metastasis. In the context of cellular mechanobiology, magnetic rotational spectroscopy (MRS), which employs rotating magnetic wires of length\,! = 2-8 $μ$m to probe cytoplasmic rheology, has emerged as an effective method for quantifying intracellular viscoelasticity. This study examines microrheology data from three breast epithelial cell lines, MCF-10A, MCF-7, and MDA-MB-231, along with new data from HeLa cervical cancer cells. Here, MRS is combined with finite element simulations to characterize the flow field induced by wire rotation in the cytoplasm. COMSOL simulations performed at low Reynolds numbers show that the flow velocity is localized around the wire, and display characteristic dumbbellshaped profiles. For wires representative of MRS experiments in cells, the product of shear rate and cytoplasmic relaxation time (''$ with $ ~ 1 s) remains below unity, indicating that the flow occurs within the linear regime. This outcome confirms that MRS can reliably measure the zeroshear viscosity of the intracellular medium in living cells. This stud
Physics-informed machine learning (PIML) is emerging as a potentially transformative paradigm for modeling complex biomedical systems by integrating parameterized physical laws with data-driven methods. Here, we review three main classes of PIML frameworks: physics-informed neural networks (PINNs), neural ordinary differential equations (NODEs), and neural operators (NOs), highlighting their growing role in biomedical science and engineering. We begin with PINNs, which embed governing equations into deep learning models and have been successfully applied to biosolid and biofluid mechanics, mechanobiology, and medical imaging among other areas. We then review NODEs, which offer continuous-time modeling, especially suited to dynamic physiological systems, pharmacokinetics, and cell signaling. Finally, we discuss deep NOs as powerful tools for learning mappings between function spaces, enabling efficient simulations across multiscale and spatially heterogeneous biological domains. Throughout, we emphasize applications where physical interpretability, data scarcity, or system complexity make conventional black-box learning insufficient. We conclude by identifying open challenges and fu
We present a microfluidic device that enables trapping, analysis, and on-demand release of individual microparticles through membrane deformation driven by pneumatic actuation. Inspired by Pachinko-style architectures, the system features an array of traps supported by a deformable PDMS membrane, actuated via pressure control in a pneumatic chamber bonded above. Unlike conventional rigid designs, our configuration enhances membrane flexibility using a wide elliptical cavity and suspended rectilinear flow guides. Device characterization was performed using confocal microscopy to measure membrane deformation under controlled negative pressure. The displacement profiles obtained were compared to several theoretical models, showing strong agreement with a thick-membrane approximation. Vertical membrane displacement exceeded 120 $μ$m under -100 mbar, allowing release of 80 $μ$m particles. We demonstrated rapid and repeatable particle trapping and release by applying coordinated fluidic and pneumatic pressures. The system was further integrated with a Python-based control interface using $μ$Manager libraries, enabling automated sequences of particle trapping, imaging, and release. The pr
Particles with high anisotropy in their magnetic properties and shape are of increasing interest for mechanobiology, where transducing a remotely applied magnetic field vector to a local mechanical response is crucial. An outstanding challenge is quantifying the mechanical torque of a single nanoparticle, typically in the range of atto- to femto-Newton-meters (Nm). The magneto-mechanical torque manifests due to a misalignment of the external magnetic field vector with the built-in magnetic anisotropy axis, as opposed to a magnetic force, and complicates the measurement scheme. In this work, we developed a method using a commercially available Atomic Force Microscopy setup and cantilevers to quantify the torque generated by a single synthetic antiferromagnetic (SAF) nanoplatelet with high perpendicular magnetic anisotropy. Specifically, we measured 1.6$\pm$0.6$\cdot$10$^{-15}$ Nm torque while applying 373$\pm$5 mT field at 12$\pm$2 degrees to the built-in anisotropy axis exerted by a single circular SAF nanoplatelet with 1.88 $μ$m diameter and 72 nm thickness, naively translating to a $\approx$ 1.7 nN maximum force at the nanoplatelet apex. This measured torque and derived force of
Cell spheroids are a widely used model to investigate cell-cell and cell-matrix interactions in a 3D microenvironment in vitro. Most research on cell spheroids has been focused on their response to various stimuli under static conditions. Recently, the effect of flow on cell spheroids has been investigated in the context of tumor invasion in interstitial space. In particular, microfluidic perfusion of cell spheroids embedded in a collagen matrix has been shown to modulate cell-cell adhesion and to represent a possible mechanism promoting tumor invasion by interstitial flow. However, studies on the effects of well-defined flow fields on cell spheroids are lacking in the literature. Here, we apply simple shear flow to cell spheroids in a parallel plate apparatus while observing their morphology by optical microscopy. By using image analysis techniques, we show that cell spheroids rotate under flow as rigid particles. As time goes on, cells from the outer layer detach from the sheared cell spheroids and are carried away by the flow. Hence, the size of cell spheroids declines with time at a rate increasing with the external shear stress, which can be used to estimate cell-cell adhesion