The cross-talk between stem cells and their microenvironment has been shown to have a direct impact on stem cells’ decisions about proliferation, growth, migration, and differentiation. It is well known that stem cells, tissues, organs, and whole organisms change their internal architecture and composition in response to external physical stimuli, thanks to cells’ ability to sense mechanical signals and elicit selected biological functions. Likewise, stem cells play an active role in governing the composition and the architecture of their microenvironment. Is now being documented that, thanks to this dynamic relationship, stemness identity and stem cell functions are maintained. In this work, we review the current knowledge in mechanobiology on stem cells. We start with the description of theoretical basis of mechanobiology, continue with the effects of mechanical cues on stem cells, development, pathology, and regenerative medicine, and emphasize the contribution in the field of the development of ex-vivo mechanobiology modelling and computational tools, which allow for evaluating the role of forces on stem cell biology.
During the last five years, there has been a significantly increasing interest in adult adipose stem cells (ASCs) as a suitable tool for translational medicine applications. The abundant and renewable source of ASCs and the relatively simple procedure for cell isolation are only some of the reasons for this success. Here, we document the advances in the biology and in the innovative biotechnological applications of ASCs. We discuss how the multipotential property boosts ASCs toward mesenchymal and non-mesenchymal differentiation cell lineages and how their character is maintained even if they are combined with gene delivery systems and/or biomaterials, both in vitro and in vivo.
Sequence databases and transcriptome-wide mapping have revealed different reversible and dynamic chemical modifications of the nitrogen bases of RNA molecules. Modifications occur in coding RNAs and noncoding-RNAs post-transcriptionally and they can influence the RNA structure, metabolism, and function. The result is the expansion of the variety of the transcriptome. In fact, depending on the type of modification, RNA molecules enter into a specific program exerting the role of the player or/and the target in biological and pathological processes. Many research groups are exploring the role of RNA modifications (alias epitranscriptome) in cell proliferation, survival, and in more specialized activities. More recently, the role of RNA modifications has been also explored in stem cell biology. Our understanding in this context is still in its infancy. Available evidence addresses the role of RNA modifications in self-renewal, commitment, and differentiation processes of stem cells. In this review, we will focus on five epitranscriptomic marks: N6-methyladenosine, N1-methyladenosine, 5-methylcytosine, Pseudouridine (Ψ) and Adenosine-to-Inosine editing. We will provide insights into the function and the distribution of these chemical modifications in coding RNAs and noncoding-RNAs. Mainly, we will emphasize the role of epitranscriptomic mechanisms in the biology of naïve, primed, embryonic, adult, and cancer stem cells.
Ex vivo cell/tissue-based models are an essential step in the workflow of pathophysiology studies, assay development, disease modeling, drug discovery, and development of personalized therapeutic strategies. For these purposes, both scientific and pharmaceutical research have adopted ex vivo stem cell models because of their better predictive power. As matter of a fact, the advancing in isolation and in vitro expansion protocols for culturing autologous human stem cells, and the standardization of methods for generating patient-derived induced pluripotent stem cells has made feasible to generate and investigate human cellular disease models with even greater speed and efficiency. Furthermore, the potential of stem cells on generating more complex systems, such as scaffold-cell models, organoids, or organ-on-a-chip, allowed to overcome the limitations of the two-dimensional culture systems as well as to better mimic tissues structures and functions. Finally, the advent of genome-editing/gene therapy technologies had a great impact on the generation of more proficient stem cell-disease models and on establishing an effective therapeutic treatment. In this review, we discuss important breakthroughs of stem cell-based models highlighting current directions, advantages, and limitations and point out the need to combine experimental biology with computational tools able to describe complex biological systems and deliver results or predictions in the context of personalized medicine.Since their establishment, cell cultures have been proven to be the first and most powerful tool for the in vitro investigation of cell biology, from basic research to more complex translational approaches [6]. Classical two-dimensional (2D)-cultures usually consist of a unique type of cells (primary or continuous cultures) that grow in tissue culture polystyrene as adherent monolayers or in floating suspension, both in culture media that provide essential nutrients and growth factors. 2D-strategies are widely used to obtain a large number of cells, thus allowing the in vitro study of molecular mechanisms and development of metabolic assays [7-9]. However, due to their inability to recreate the in vivo complexity of the biological environment, they are not suitable for accurate disease modeling. These limitations have been overcome by the development of three-dimensional (3D)-cell cultures systems [10]. The rationale design of 3D-cell cultures is to harvest cells in microstructures that resemble tissues or organs shape and organization, thus allowing better cell-to-cell/cell-environment contacts and signaling crosstalk [11][12][13][14][15], essential events for tissues correct development and functioning [14,15]. The 3D-cell culture strategy is articulated in many different methods and techniques that can be grouped in scaffold-based or non-scaffold based platforms, each with particular advantages and disadvantages that make them useful for different applications [10,[16][17][18][19]. 3D-cell culture strategies are supported by the in silico...
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