Biology subjects

Hepburn, M. S.

Publications and source records attributed to Hepburn, M. S..

3 recordsLinked to original sources

bioRxiv2024

Three-dimensional quantitative micro-elastography reveals alterations in spatial elasticity patterns of follicles and corpora lutea in murine ovaries during ageing

Fibrosis and tissue stiffening are hallmarks of ovarian ageing, linked to a decrease in fertility. However, the lack of three-dimensional (3D) characterization of ovary elasticity limits our understanding of localized elasticity patterns and their connection to the tissue composition. Here, we developed an integrated approach to link ovarian tissue elasticity, volume, and cell-matrix composition using quantitative micro-elastography (QME), a label-free, non-invasive approach to study the 3D microscale elasticity in conjunction with immunofluorescence microscopy. QME revealed distinct spatial elasticity patterns in ovarian compartments, namely follicles and corpora lutea (CLs), and local elasticity alterations in different age cohorts. For example, CL elasticity significantly increased during ovarian ageing while follicle elasticity changed minimally. CLs showed size-dependent elasticity changes, while follicles exhibited distinct spatial variations in elasticity correlated with the emergence of theca cell layers during follicle development. These findings have the potential to guide the development of novel diagnostic tools and identify therapeutic targets, improving womens reproductive health and longevity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/617177v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1850b00org.highwire.dtl.DTLVardef@1956425org.highwire.dtl.DTLVardef@e1f051org.highwire.dtl.DTLVardef@16864a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2024

Tumor spheroid elasticity estimation using mechano-microscopy combined with a conditional generative adversarial network

Techniques for imaging the mechanical properties of cells are needed to study how cell mechanics influence cell function and disease progression. Mechano-microscopy (a high-resolution variant of compression optical coherence elastography) generates elasticity images of a sample undergoing compression from the phase difference between optical coherence microscopy (OCM) B-scans. However, the existing mechano-microscopy signal processing chain (referred to as the algebraic method) assumes the sample stress is uniaxial and axially uniform, such that violation of these assumptions reduces the accuracy and precision of elasticity images. Furthermore, it does not account for prior information regarding the sample geometry or mechanical property distribution. In this study, we investigate the feasibility of training a conditional generative adversarial network (cGAN) to generate elasticity images from phase difference images of samples containing a cell spheroid embedded in a hydrogel. To train and test the cGAN, we constructed 30,000 elasticity and phase difference image pairs, where elasticity images were generated using a parametric model to simulate artificial samples, and phase difference images were computed using finite element analysis to simulate compression applied to the artificial samples. By applying both the cGAN and algebraic methods to simulated phase difference images, our results indicate the cGAN elasticity images exhibit better spatial resolution and sensitivity. We also evaluated the cGAN on experimental phase difference images of real spheroids embedded in hydrogels and compared the cGAN elasticity with the algebraic elasticity, OCM, and confocal fluorescence microscopy, and found the cGAN elasticity is often more robust to noise, especially within stiff nuclei.

bioengineering↗

bioRxiv2024

Multimodal mechano-microscopy reveals mechanical phenotypes of breast cancer spheroids in three dimensions

Cancer cell invasion relies on an equilibrium between cell deformability and the biophysical constraints imposed by the extracellular matrix (ECM). However, there is little consensus on the nature of the local biomechanical alterations in cancer cell dissemination in the context of three-dimensional (3D) tumor microenvironments (TME). While the shortcomings of two-dimensional (2D) models in replicating in situ cell behavior are well known, 3D TME models remain underutilized because contemporary mechanical quantification tools are limited to surface measurements. Here, we overcome this major challenge by quantifying local mechanics of cancer cell spheroids in 3D TMEs. We achieve this using multimodal mechano-microscopy, integrating optical coherence microscopy-based elasticity imaging with confocal fluorescence microscopy. We observe that non-metastatic cancer spheroids show no invasion while showing increased peripheral cell elasticity in both stiff and soft environments. Metastatic cancer spheroids, however, show ECM-mediated softening in a stiff microenvironment and, in a soft environment, initiate cell invasion with peripheral softening associated with early metastatic dissemination. This exemplar of live-cell 3D mechanotyping supports that invasion increases cell deformability in a 3D context, illustrating the power of multimodal mechano-microscopy for quantitative mechanobiology in situ.

bioengineering↗