Response to "a simplified implementation of the bubble analysis of biopolymer networks pores"

Image analysis method for heterogeneity and porosity characterization of biomimetic hydrogels

This work presents an image processing procedure for characterization of porosity and heterogeneity of hydrogels network mainly based on the analysis of cryogenic scanning electron microscopy (cryo-SEM) images and can be extended to any other type of microscopy images of hydrogel porous network. An algorithm consisting of different filtering, morphological transformation, and thresholding steps to denoise the image whilst emphasizing the edges of the hydrogel walls for extracting either the pores or hydrogel walls features is explained. Finally, the information of hydrogel porosity and heterogeneity is presented in form of pore size distribution, spatial contours maps and kernel density dot plots. The obtained results reveal that a non-parametric kernel density plot effectively determines the spatial heterogeneity and porosity of the hydrogel.

Structural characterization of fibrous synthetic hydrogels using fluorescence microscopy

The structural features of the matrix surrounding the cells play a crucial role in regulating their behavior. Here, we used fluorescence microscopy and customized analysis algorithms to characterize the architecture of fibrous hydrogel networks. As a model system, we investigated a new class of synthetic biomimetic material, hydrogels prepared from polyisocyanides. Our results show that these synthetic gels present a highly heterogeneous fibrous network, with pores reaching a few micrometers in diameter. By encapsulating HeLa cells in different hydrogels, we show that a more porous structure is linked to a higher proliferation rate. The approach described here, for the characterization of the network of fibrous hydrogels, can be easily applied to other polymer-based materials and provide new insights into the influence of structural features in cell behavior. This knowledge is crucial to develop the next generation of biomimetic materials for 3D cell models and tissue engineering applications.

Fast and reliable advanced two-step pore-size analysis of biomimetic 3D extracellular matrix scaffolds

The tissue microenvironment is a major contributor to cellular functions, such as cell adhesion, migration and invasion. A critical physical parameter for determining the effect of the microenvironment on cellular functions is the average pore-size of filamentous scaffolds, such as 3D collagen fiber matrices, which are assembled by the polymerization of biopolymers. The scaffolds of these matrices can be analyzed easily by using state-of-the-art laser scanning confocal imaging. However, the generation of a quantitative estimate of the pore-size in a 3D microenvironment is not trivial. In this study, we present a reliable and fast analytical method, which relies on a two-step 3D pore-size analysis utilizing several state-of-the-art image analysis methods, such as total variation (TV) denoising and adaptive local thresholds, and another crucial parameter, such as pore-coverage. We propose an iterative approach of pore-size analysis to determine even the smallest and obscure pores in a collagen scaffold. Additionally, we propose a novel parameter, the pseudo-pore-size, which describes a virtual scaffold porosity. In order to validate the advanced two-step pore-size analysis different types of artificial collagens, such as a rat and bovine mixture with two different collagen concentrations have been utilized. Additionally, we compare a traditional approach with our method using an artificially generated network with predefined pore-size distributions. Indeed, our analytical method provides a precise, fast and parameter-free, user-independent and automatic analysis of 3D pore topology, such as pore-sizes and pore-coverage. Additionally, we are able to determine non-physiological network topologies by taking the pore-coverage as a goodness-of-fit parameter.

Fibrous nonlinear elasticity enables positive mechanical feedback between cells and ECMs

In native states, animal cells of many types are supported by a fibrous network that forms the main structural component of the ECM. Mechanical interactions between cells and the 3D ECM critically regulate cell function, including growth and migration. However, the physical mechanism that governs the cell interaction with fibrous 3D ECM is still not known. In this article, we present single-cell traction force measurements using breast tumor cells embedded within 3D collagen matrices. We recreate the breast tumor mechanical environment by controlling the microstructure and density of type I collagen matrices. Our results reveal a positive mechanical feedback loop: cells pulling on collagen locally align and stiffen the matrix, and stiffer matrices, in return, promote greater cell force generation and a stiffer cell body. Furthermore, cell force transmission distance increases with the degree of strain-induced fiber alignment and stiffening of the collagen matrices. These findings highlight the importance of the nonlinear elasticity of fibrous matrices in regulating cell-ECM interactions within a 3D context, and the cell force regulation principle that we uncover may contribute to the rapid mechanical tissue stiffening occurring in many diseases, including cancer and fibrosis.

Heidelberg-mCT-Analyzer: a novel method for standardized microcomputed-tomography-guided evaluation of scaffold properties in bone and tissue research

Bone tissue engineering and bone scaffold development represent two challenging fields in orthopaedic research. Micro-computed tomography (mCT) allows non-invasive measurement of these scaffolds' properties in vivo. However, the lack of standardized mCT analysis protocols and, therefore, the protocols' user-dependency make interpretation of the reported results difficult. To overcome these issues in scaffold research, we introduce the Heidelberg-mCT-Analyzer. For evaluation of our technique, we built 10 bone-inducing scaffolds, which underwent mCT acquisition before ectopic implantation (T0) in mice, and at explantation eight weeks thereafter (T1). The scaffolds' three-dimensional reconstructions were automatically segmented using fuzzy clustering with fully automatic level-setting. The scaffold itself and its pores were then evaluated for T0 and T1. Analysing the scaffolds' characteristic parameter set with our quantification method showed bone formation over time. We were able to demonstrate that our algorithm obtained the same results for basic scaffold parameters (e.g. scaffold volume, pore number and pore volume) as other established analysis methods. Furthermore, our algorithm was able to analyse more complex parameters, such as pore size range, tissue mineral density and scaffold surface. Our imaging and post-processing strategy enables standardized and user-independent analysis of scaffold properties, and therefore is able to improve the quantitative evaluations of scaffold-associated bone tissue-engineering projects.

Quantifying Modes of 3D Cell Migration

Although it is widely appreciated that cells migrate in a variety of diverse environments in vivo, we are only now beginning to use experimental workflows that yield images with sufficient spatiotemporal resolution to study the molecular processes governing cell migration in 3D environments. Since cell migration is a dynamic process, it is usually studied via microscopy, but 3D movies of 3D processes are difficult to interpret by visual inspection. In this review, we discuss the technologies required to study the diversity of 3D cell migration modes with a focus on the visualization and computational analysis tools needed to study cell migration quantitatively at a level comparable to the analyses performed today on cells crawling on flat substrates.