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The efficacy of polylactic acid (PLA)/Magnesium (Mg)-based materials for driving stem cells toward bone tissue engineering applications requires specific Mg surface properties to modulate the interface of stem cells with the film. Here, we have developed novel PLA/Mg-based composites and explored their osteogenic differentiation potential on human adipose stem cells (hASCs). Mg-particles/polymer interface was improved by two treatments: heating in oxidative atmosphere (TT) and surface modification with a compatibilizer (PEI). Different contents of Mg particles were dispersed in PLA and composite surface and bulk properties, protein adsorption, stem cell-PLA/Mg interactions, osteogenic markers expressions, and lipids composition profile were evaluated. Mg particles were uniformly distributed on the surface and in the bulk PLA polymer. Improved and modulated particle-polymer adhesion was observed in Mg particle-treated composites. After 21 days in canonical growth culture conditions, hASCs on PLA/MgTT displayed the highest expression of the general osteogenic markers, RUNX2, SSP1, and BGLAP genes, Alkaline Phosphatase, type I Collagen, Osteopontin, and Calcium deposits. Moreover, by LC/MS QTOF mass-spectrophotometry lipidomic analysis, we found in PLA/MgTT-cells, for the first time, a remodeling of the lipid classes composition associated with the osteogenic differentiation. We ascribed these results to MgTT characteristics, which improve Mg availability and composite osteoinductive performance., This work has been carried out within the M-ERANET Programme: Project POLYMAGIC. A. Ferrandez-Montero thanks Project ADITIMAT-CM: Fabricación aditiva: del material a la aplicación. S2018/NMT-4411. M. Lieblich thanks Project PID2019-104351GB-C21 financed by MCIN/AEI/10.13039/501100011033.

Herein, we have generated ssRNA aptamers to inhibit SARS-CoV-2 Mpro, a protease necessary for the SARS-CoV-2 coronavirus replication. Because there is no aptamer 3D structure currently available in the databanks for this protein, first, we modeled an ssRNA aptamer using an entropic fragment-based strategy. We refined the initial sequence and 3D structure by using two sequential approaches, consisting of an elitist genetic algorithm and an RNA inverse process. We identified three specific aptamers against SARS-CoV-2 Mpro, called MAptapro, MAptapro-IR1, and MAptapro-IR2, with similar 3D conformations and that fall in the dimerization region of the SARS-CoV-2 Mpro necessary for the enzymatic activity. Through the molecular dynamic simulation and binding free energy calculation, the interaction between the MAptapro-IR1 aptamer and the SARS-CoV-2 Mpro enzyme resulted in the strongest and the highest stable complex, therefore, the ssRNA MAptapro-IR1 aptamer was selected as the best potential candidate for the inhibition of SARS-CoV-2 Mpro and a perspective therapeutic drug for the COVID-19 disease.

Considerable evidence is accumulating about the regulatory function of coding- and non-coding RNAs through chemical modifications on their own nitrogen bases. The mechanisms by which the amount and types of these modifications are built to each type of RNA are yet poorly clarified, although some classes of proteins have been identified as actors able to introduce (writers), specifically recognize (readers) or delate (erasers) such modifications. In this context, advances have been made thanks to bioinformatic tools, which have allowed a comprehensive database, where RNA processing and post-transcriptional modification are integrated and elucidated, to be generated. Now, it is accepted that the abovementioned epitranscriptome interplay is involved in orchestrating development, health, and disease, also including the development, function, and dysfunction of the nervous system. In this chapter, we aim at reviewing and describing the potential mechanisms associated with the dysregulation of the epitranscriptome and neuropathologies, focusing specifically on brain cancer and neurodegenerative disorders.

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.

Nowadays, the amyloid cascade hypothesis is the dominant model to explain Alzheimer’s disease (AD) pathogenesis. By this hypothesis, the inherited genetic form of AD is discriminated from the sporadic form of AD (SAD) that accounts for 85–90% of total patients. The cause of SAD is still unclear, but several studies have shed light on the involvement of environmental factors and multiple susceptibility genes, such as Apolipoprotein E and other genetic risk factors, which are key mediators in different metabolic pathways (e.g., glucose metabolism, lipid metabolism, energetic metabolism, and inflammation). Furthermore, growing clinical evidence in AD patients highlighted the presence of affected systemic organs and blood similarly to the brain. Collectively, these findings revise the canonical understating of AD pathogenesis and suggest that AD has metabolic disorder features. This review will focus on AD as a metabolic disorder and highlight the contribution of this novel understanding on the identification of new biomarkers for improving an early AD diagnosis.

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.