Qiber3D-an open-source software package for the quantitative analysis of networks from 3D image stacks.

BACKGROUND: Optical slice microscopy is commonly used to observe cellular morphology in 3D tissue culture, e.g., the formation of cell-derived networks. The morphometric quantification of these networks is essential to study the cellular phenotype. Commonly, the quantitative measurements are performed on 2D projections of the image stack, resulting in the loss of information in the third dimension. Currently available 3D image analysis tools rely on manual interactions with the software and are therefore not feasible for large datasets. FINDINGS: Here we present Qiber3D, an open-source image processing toolkit. The software package includes the essential image analysis procedures required for image processing, from the raw image to the quantified data. Optional pre-processing steps can be switched on/off depending on the input data to allow for analyzing networks from a variety of sources. Two reconstruction algorithms are offered to meet the requirements for a wide range of network types. Furthermore, Qiber3D's rendering capabilities enable the user to inspect each step of the image analysis process interactively to ensure the creation of an optimal workflow for each application. CONCLUSIONS: Qiber3D is implemented as a Python package, and its source code is freely available at https://github.com/theia-dev/Qiber3D. The toolkit was designed using a building block principle to enable the analysis of a variety of structures, such as vascular networks, neuronal structures, or scaffolds from numerous input formats. While Qiber3D can be used interactively in the Python console, it is aimed at unsupervised automation to process large image datasets efficiently.

Techniques for RNA extraction from cells cultured in starPEG-heparin hydrogels.

Three-dimensional (3D) cell culture models that provide a biologically relevant microenvironment are imperative to investigate cell-cell and cell-matrix interactions in vitro. Semi-synthetic star-shaped poly(ethylene glycol) (starPEG)-heparin hydrogels are widely used for 3D cell culture due to their highly tuneable biochemical and biomechanical properties. Changes in gene expression levels are commonly used as a measure of cellular responses. However, the isolation of high-quality RNA presents a challenge as contamination of the RNA with hydrogel residue, such as polymer or glycosaminoglycan fragments, can impact template quality and quantity, limiting effective gene expression analyses. Here, we compare two protocols for the extraction of high-quality RNA from starPEG-heparin hydrogels and assess three subsequent purification techniques. Removal of hydrogel residue by centrifugation was found to be essential for obtaining high-quality RNA in both isolation methods. However, purification of the RNA did not result in further improvements in RNA quality. Furthermore, we show the suitability of the extracted RNA for cDNA synthesis of three endogenous control genes confirmed via quantitative polymerase chain reaction (qPCR). The methods and techniques shown can be tailored for other hydrogel models based on natural or semi-synthetic materials to provide robust templates for all gene expression analyses.

3D Quantification of Vascular-Like Structures in z Stack Confocal Images.

Optical slice microscopy is commonly used to characterize the morphometric features of 3D cellular cultures, such as in vitro vascularization. However, the quantitative analysis of those structures is often performed on a single 2D maximum intensity projection image, limiting the accuracy of data obtained from 3D cultures. Here, we present a protocol for the quantitative analysis of z stack images, utilizing Fiji, Amira, and WinFiber3D. This protocol facilitates the in-depth examination of vascular-like structures within 3D cell culture models. For complete details on the use and execution of this protocol, please refer to Koch et al. (2020).

Stromal fibroblasts regulate microvascular-like network architecture in a bioengineered breast tumour angiogenesis model.

The plasticity of the tumour microenvironment is a key contributor to cancer development and progression. Here, we present a bioengineered breast tumour angiogenesis model comprised of mammary derived epithelial, endothelial and fibroblast cells, to dissect the mechanisms of cancer-associated fibroblasts (CAFs) on microvascular-like network formation and epithelial spheroid morphology. Primary patient-derived mammary endothelial cells, normal breast fibroblasts (NBF, patient matched) and CAFs were cultured within three-dimensional (3D) semi-synthetic hydrogels where CAFs promoted an increase in the density and morphology of the microvascular-like network. The mammary microenvironment also increased the number of MCF-10a epithelial spheroids when compared with a non-mammary microenvironment, and a malignant mammary microenvironment resulted in further morphological differences in the epithelial spheroids. The morphological changes observed following interactions between breast CAFs and endothelial cells, highlight the plasticity of the malignant stroma in tumour vascularisation. Our in vitro bioengineered breast cancer microenvironment provides a robust model to study cell-cell and cell-matrix interactions. Statement of Significance In recent years there has been an increase in the sophistication of 3D culture models, however less attention has been paid to the cell source utilised. In this study, we describe the influence of a normal and malignant stromal microenvironment on vessel-like behaviour in a 3D model. Using a semi-synthetic hydrogel, we studied the effects of mammary-derived cancer-associated fibroblasts and normal fibroblasts on human umbilical vein endothelial cells or human mammary microvascular endothelial cells. An increase in vessel-like network and epithelial cell density was seen in a mammary versus non-mammary microenvironment. This study highlights the importance of using tissue-specific endothelial cells in cancer research and demonstrates the microenvironmental impact of fibroblasts on endothelial and epithelial growth and morphology.

proMAD: semiquantitative densitometric measurement of protein microarrays.

BACKGROUND: Protein microarrays are a versatile and widely used tool for analyzing complex protein mixtures. Membrane arrays utilize antibodies which are captured on a membrane to specifically immobilize several proteins of interest at once. Using detection antibodies, the bound protein-antibody-complex is converted into visual signals, which can be quantified using densitometry. The reliability of such densitometric assessments depends on a variety of factors, not only sample preparation and the choice of acquisition device but also the selected analysis software and the algorithms used for readout and processing data. Currently available software packages use a single image of a membrane at an optimal exposure time selected for that specific experimental framework. This selection is based on a user's best guess and is subject to inter-user variability or the acquisition device algorithm. With modern image acquisition systems proving the capacity to collect signal development over time, this information can be used to improve densitometric measurements. Here we introduce proMAD, a toolkit for protein microarray analysis providing a novel systemic approach for the quantification of membrane arrays based on the kinetics of the analytical reaction. RESULTS: Briefly, our toolkit ensures an exact membrane alignment, utilizing basic computer vision techniques. It also provides a stable method to estimate the background light level. Finally, we model the light production over time, utilizing the knowledge about the reaction kinetics of the underlying horseradish peroxidase-based signal detection method. CONCLUSION: proMAD incorporates the reaction kinetics of the enzyme to model the signal development over time for each membrane creating an individual, self-referencing concept. Variations of membranes within a given experimental set up can be accounted for, allowing for a better comparison of such. While the open-source library can be implemented in existing workflows and used for highly user-tailored analytic setups, the web application, on the other hand, provides easy platform-independent access to the core algorithm to a wide range of researchers. proMAD's inherent flexibility has the potential to cover a wide range of use-cases and enables the automation of data analytic tasks.

A Scoping Review of Health Outcomes Examined in Randomized Controlled Trials Using Guided Imagery.

INTRODUCTION: Guided imagery involves the controlled visualization of detailed mental images. This integrative health technique is used for healing, health maintenance, or the treatment of specific conditions. Guided imagery is an integral part of mindfulness meditation, hypnosis, and various relaxation exercises. However, evidence to support the widespread use and dissemination of guided imagery interventions has been lacking. The purposes of this scoping review were to document the scope of health outcomes and disease processes examined by guided imagery researchers and the journal outlets where this work has been published. Secondary purposes were to review the efficacy of guided imagery, risk of bias from studies published in selected integrative health journals, and gain feedback from clinicians in a practiced-based research network (PBRN) about potential barriers for use in clinical settings. METHODS: Ten bibliographic databases were searched for randomized controlled trials (RCTs) published between 1960 and 2013 that included adult participants. Descriptive and analytic methods were employed to document the journal outlets, diseases, and health outcomes investigated. RESULTS: 320 RCTs that included more than 17,979 adult participants were reviewed. The published studies appeared in 216 peer-reviewed journals from diverse disciplines largely representing psychology, the sport sciences, rehabilitation, nursing, and medicine. Major outcomes observed were coping with pain, stroke recovery, anxiety, coping with stress, and sport skills. Practitioner feedback from the PBRN revealed some interest but skepticism and time constraints were discussed as barriers. CONCLUSIONS: Ongoing research and creative dissemination techniques are warranted.

Guided Imagery for Arthritis and Other Rheumatic Diseases: A Systematic Review of Randomized Controlled Trials.

Many individuals suffering from arthritis and other rheumatic diseases (AORD) supplement pharmacologic treatments with psychosocial interventions. One promising approach, guided imagery, has been reported to have positive results in randomized controlled trials (RCTs) and is a highly scalable treatment for those with AORD. The main purpose of this study was to conduct a systematic review of RCTs that have examined the effects of guided imagery on pain, function, and other outcomes such as anxiety, depression, and quality of life in adults with AORD. Ten electronic bibliographic databases were searched for reports of RCTs published between 1960 and 2013. Selection criteria included adults with AORD who participated in RCTs that used guided imagery as a partial or sole intervention strategy. Risk of bias was assessed using the Cochrane Risk of Bias Assessment Instrument. Results were synthesized qualitatively. Seven studies representing 306 enrolled and 287 participants who completed the interventions met inclusion criteria. The average age of the participants was 62.9 years (standard deviation = 12.2). All interventions used guided imagery scripts that were delivered via audio technology. The interventions ranged from a one-time exposure to 16 weeks in duration. Risk of bias was low or unclear in all but one study. All studies reported statistically significant improvements in the observed outcomes. Guided imagery appears to be beneficial for adults with AORD. Future theory-based studies with cost-benefit analyses are warranted.

Synergistic effect of defined artificial extracellular matrices and pulsed electric fields on osteogenic differentiation of human MSCs.

In vivo, bone formation is a complex, tightly regulated process, influenced by multiple biochemical and physical factors. To develop a vital bone tissue engineering construct, all of these individual components have to be considered and integrated to gain an in vivo-like stimulation of target cells. The purpose of the present studies was to investigate the synergistic role of defined biochemical and physical microenvironments with respect to osteogenic differentiation of human mesenchymal stem cells (MSCs). Biochemical microenvironments have been designed using artificial extracellular matrices (aECMs), containing collagen I (coll) and glycosaminoglycans (GAGs) like chondroitin sulfate (CS), or a high-sulfated hyaluronan derivative (sHya), formulated as coatings on three-dimensional poly(caprolactone-co-lactide) (PCL) scaffolds. As part of the physical microenvironment, cells were exposed to pulsed electric fields via transformer-like coupling (TC). Results showed that aECM containing sHya enhanced osteogenic differentiation represented by increases in ALP activity and gene-expression (RT-qPCR) of several bone-related proteins (RUNX-2, ALP, OPN). Electric field stimulation alone did not influence cell proliferation, but osteogenic differentiation was enhanced if osteogenic supplements were provided, showing synergistic effects by the combination of sHya and electric fields. These results will improve the understanding of bone regeneration processes and support the development of effective tissue engineered bone constructs.