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Data Availability Statement: RNAseq and array data can be found via the following NCBI accession codes: PRJNA472611, PRJNA530150, PRJNA564843, PRJNA564843, PRJNA232817, and PRJNA318768. A full list of samples can be viewed in Supplementary Table S1 available online at https://www.mdpi.com/2072-6694/15/13/3350#app1-cancers-15-03350 . Simple Summary: Ovarian cancer is one of the most lethal female cancers. Numerous investigations into the development and progression of this disease have resulted in the creation of numerous three-dimensional culture models to better reflect the natural microenvironment of these tumours. In this study, we leverage the available transcriptomics and clinical and novel experimental data to evaluate the impact of the growth conditions on various cancer cells and examine whether they better approximate the behaviour of tumour cells compared to the classical two-dimensional models. Our results show that variability in the growth conditions can impact key genes and biological processes that are hallmarks of cancer, highlighting the need for future studies to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments. Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers15133350/s1, Figure S1: Top enriched gene sets for 2D vs. 3D OVCAR8; Table S1: Cell line information and associated accession codes; Figure S2: Growth of SKOV3 cells from Day 2 to Day 9 showing clear spheroid-like structures; Table S2: (A) Top 150 differentially expressed genes in OVCAR8 in all three grown media: grown on agarose, collagen, Matrigel. The differential expression in each of the growth media is with respect to 2D controls of the OVCAR8; (B) Top 150 differentially expressed genes across the cell lines A1847, A2780, C30, C70, OVCAR3, OVCAR4, OVCAR5, OVCAR8, OVCAR10, PEO1, SKOV-3, UPN275 grown on agarose vs. 2D controls; (C) Top 150 differentially expressed genes in the cell lines Kuramochi, OVCAR4, and OVCAR8, grown on collagen vs. 2D controls or the respective cell lines. Copyright © 2023 by the authors. Three-dimensional (3D) cancer models are revolutionising research, allowing for the recapitulation of an in vivo-like response through the use of an in vitro system, which is more complex and physiologically relevant than traditional monolayer cultures. Cancers such as ovarian (OvCa) are prone to developing resistance, are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D cultures. However, the current models often fall short of the predicted response, where reproducibility is limited owing to the lack of standardised methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in the genetic profiles presented by a vast array of 3D cultures. An analysis of the literature (Pubmed.gov) spanning 2012–2022 was used to identify studies with paired data of 3D and 2D monolayer counterparts in addition to RNA sequencing and microarray data. From the data, 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e., agarose, collagen, or Matrigel) compared to 2D cell cultures. The top genes differentially expressed in 2D vs. 3D included C3, CXCL1, 2, and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. The top enriched gene sets for 2D vs. 3D included IFN-α and IFN-γ response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial–mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape and identify key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments. Cancer Treatment and Research Trust and the University Hospitals Coventry and Warwickshire NHS Trust (grant no. 12899).

Objective: Imaging of tissue engineered three-dimensional (3D) specimens is challenging due to their thickness. We propose a novel multimodal imaging technique to obtain multi-physical 3D images and the electrical conductivity spectrum of tissue engineered specimens in vitro. Approach: We combine simultaneous recording of rotational multifrequency electrical impedance tomography (R-mfEIT) with optical projection tomography (OPT). Structural details of the specimen provided by OPT are used here as geometrical priors for R-mfEIT. Main results: This data fusion enables accurate retrieval of the conductivity spectrum of the specimen. We demonstrate experimentally the feasibility of the proposed technique using a potato phantom, adipose and liver tissues, and stem cells in biomaterial spheroids. The results indicate that the proposed technique can distinguish between viable and dead tissues and detect the presence of stem cells. Significance: This technique is expected to become a valuable tool for monitoring tissue engineered specimens' growth and viability in vitro. publishedVersion

This thesis studies the challenges that self-organizing organizations face, as well as the role of control in self-organizing organizations. Even though the self-organizing organization model has been studied for a while now, there is no comprehensive research in looking at it critically. This study aims to understand what the factors are to cause challenges and how does the different form of control impact the self-organizing organizations. The thesis begins with literature review of self-organizing, self-management and control concepts explaining the concepts on organizational and individual level, as well as the expected results and reasons for failing of self-organizing organizations. Control is also explained from an organizational control perspective and how does control show in self-organizing organization. In this study a qualitative approach is used, and data was gathered by structured email interviews and using blog posts as secondary data source. As using self-organizing organizational model is growing, it is important that the companies know the possible challenges of the model. In self-organizing organizations, the different form of control causes the challenges. In general, people are used to the traditional model of control and in self-organizing organizations, the basis of traditional form of control as manager-subordinate relationship is removed and different form of control is needed. This uncertainty of how to act without traditional form of control is one challenge and another one is caused by different form of control, like self-governance control that does not have proper limits or norms yet. There are situations that would be easier to handle with the traditional form of control because the allocation of control and responsibility is not clear with the different form. The results emphasise that top-down control causes the challenges, when people do not know how to work without it and how the different form of control should be treated. With the contribution of this thesis, companies practicing self-organizing organization model, can avoid problems by paying attention to the different form of control and create clear norms for it.

The aim of our work consists in developing a new model of the human ventricular cardiomyocyte, based on the O'Hara-Rudy model (ORd), to improve, in particular, the action potential duration (APD) dependence on the extracellular Ca2+ concentration (Cao). Moreover, the new model reproduces all the available experimental data on APD rate dependence, APD restitution, drug block effects, etc., when the experimental extracellular ionic concentrations are carefully reproduced in simulationsThe main differences between our and the ORd model are: a novel Markovian formulation for the L-type Ca2+ current; the Markovian rapid delayed rectifier K+ current formulation published by Li et al.; a new formulation of the Ca2+ release from the sarcoplasmic reticulum. Several model parameters were modifiedOur BS (Bartolucci-Severi) model successfully improved the ORd, one of the most detailed, used and influent models in computational cardiology, by reproducing the APD-Cao relationship while keeping all the original model features tested in the appropriate experimentally-matched conditions. Furthermore, the BS was suitability as baseline for the generation of in silico populations of models and for reproducing cardiac abnormalities such as early afterdepolarizations.