di-8-ANEPPS is a lipophilic fluorescent probe sensitive to membrane potential. It has been used for several purposes in biological imaging and physical chemistry spectroscopic studies. Among the latter, solute-lipid membrane interaction stands out in the past 30 years. Solute-induced perturbations of lipid membrane hydration result in spectral shifts of this probe, which are used to infer on how extensively solutes bind membranes. Inferring solute distribution to lipid membranes from lipophilic probes such as di-8-ANEPPS has the advantage of not requiring labelled solutes, but is limited by lack of a theoretical framework that relates experimental outputs to mechanistic molecular events. Hill plot-like data treatment is usually performed but the relationship remains empirical, based on chemical intuition rather than on a well-defined biophysical rationale. Here, we present a rationalization of the method that frames data analysis in order to attain precise molecular level conclusions based on the water-lipid partition constant and the lipid-to-solute saturation ratio. Experimental proof of concept is provided using peptide solutes to disturb lipid bilayers of unilamellar vesicles. The rational physical chemistry foundations of the methods are also addressed and used to improve the experimental protocol.
This study presents a multi-scale computational framework to quantify how externally applied acoustic waves propagate through the knee joint and induce mechanotransductive strain at the level of the chondrocyte nucleus. Patient-specific knee geometries (n = 8) were used to simulate acoustic wave transmission through layered tissues, while a representative volume element modelled the coupled solid–shell–acoustic behaviour of the chondrocyte, pericellular matrix, and extracellular matrix. Modal and frequency–response analyses identified the spheroidal s3 mode as the dominant contributor to nuclear deformation. Strain amplification was found to occur within defined frequency bands rather than at a single frequency, with healthy patients exhibiting a broader mid-frequency amplification region (50–170 kHz) and diseased patients showing a shifted low-frequency (30–85 kHz) dominance due to hypertrophy and altered stiffness. Macro-to-micro coupling demonstrated that, despite anatomical variability, consistent transmissibility trends were preserved across patients, with ideal frequencies for healthy and OA patients. Time-explicit simulations comparing linear and nonlinear acoustic formulations revealed negligible harmonic generation at the applied pressure levels, indicating that linear acoustics adequately describe propagation within the mechanotransductive strain range considered. Overall, the results demonstrate that cartilage stimulation is frequency-band dependent and disease-sensitive, and they provide a mechanistically grounded basis for optimizing ultrasound excitation parameters based on cellular-scale mechanics rather than empirical frequency selection.
Marfan syndrome, caused primarily by mutations in the fibrillin-1 (FBN1) gene, is associated with progressive dilation of the proximal aorta, with dissection and rupture representing the leading causes of early mortality. A characteristic feature of Marfan-associated aneurysm is fragmentation of elastic fibers; however, the extent to which elastin loss alone can account for the observed geometric and mechanical changes remains unclear. In this study, we use a multiscale computational growth and remodeling framework to determine which geometric and mechanical features of the Marfan aorta can be reproduced by prescribed elastin loss acting through mechanically regulated fiber remodeling and tissue growth. The model couples a discrete fiber network representation of collagen, elastin, and actomyosin with a continuum description of the tissue. It is first calibrated to reproduce experimental measurements in the healthy mouse aorta, and Marfan conditions are then introduced by prescribing graded reductions in elastin content (10–80
In early years of life, the cranium rapidly changes in size and shape to accommodate brain growth, primarily driven by mechanical stress from brain expansion. Developmental disorders such as premature fusion of sutures in craniosynostosis disrupt normal growth process, leading to abnormal cranial shapes. Thus, understanding the interplay between biomechanical forces, soft tissues, and individual bone plates is crucial for understanding their role in shaping infant cranial development. This study develops a mechanically driven growth model to simulate healthy cranial growth in the first year. The algorithm considers simultaneous and coupled growth of brain, cranial bones, sutures, with volumetric brain expansion as the primary driver, with strain-based feedback governing growth in bone and suture tissues. A bulk bone formation approach accounts for evolving mechanical properties, with elastic moduli of bone and sutures increasing monthly. The growth algorithm was applied on an idealised geometry model of a healthy cranium, then on individual fused sutures cases, and dysmorphologies due to craniosynostosis were developed. The results showed good agreement with the typical features of clinical observations. Stress at bone–suture interfaces and elevated contact pressure under fused sutures highlighted biomechanical impacts due to the disorders. Sensitivity analysis explored how material properties and growth rates affect cranial morphology in the absence of longitudinal clinical data. This framework enhances understanding of cranial growth and is potential to be further modified and validated to support treatment planning for craniosynostosis.
