The Wilms’ tumor suppressor Wt1 is involved in multiple developmental processes and adult tissue homeostasis. The first phenotypes recognized in Wt1 knockout mice were developmental cardiac and kidney defects. Wt1 expression in the heart has been described in epicardial, endothelial, smooth muscle cells, and fibroblasts. Expression of Wt1 in cardiomyocytes has been suggested but remained a controversial issue, as well as the role of Wt1 in cardiomyocyte development and regeneration after injury. We determined cardiac Wt1 expression during embryonic development, in the adult, and after cardiac injury by quantitative RT-PCR and immunohistochemistry. As in vitro model, phenotypic cardiomyocyte differentiation, i.e., the appearance of rhythmically beating clones from mouse embryonic stem cells (mESCs) and associated changes in gene expression were analyzed. We detected Wt1 in cardiomyocytes from embryonic day (E10.5), the first time point investigated, until adult age. Cardiac Wt1 mRNA levels decreased during embryonic development. In the adult, Wt1 was reactivated in cardiomyocytes 48 h and 3 weeks following myocardial infarction. Wt1 mRNA levels were increased in differentiating mESCs. Overexpression of Wt1(-KTS) and Wt1(+KTS) isoforms in ES cells reduced the fraction of phenotypically cardiomyocyte differentiated clones, which was preceded by a temporary increase in c-kit expression in Wt1(-KTS) transfected ES cell clones and induction of some cardiomyocyte markers. Taken together, Wt1 shows a dynamic expression pattern during cardiomyocyte differentiation and overexpression in ES cells reduces their phenotypical cardiomyocyte differentiation.

Background: N-heptyl-D-galactonamide (GalC7) is a small synthetic carbohydrate derivative that forms a biocompatible supramolecular hydrogel. In this study, the objective was to analyze more in-depth how neural cells differentiate in contact with GalC7. Method: Direct (ex vivo) cells of the fresh hippocampus and culture (In vitro) of the primary cells were investigated. In vitro, investigation performed under three conditions: on culture in neurospheres for 19 days, on culture in GalC7 gel for 7 days, and on culture in both neurospheres and GalC7 gel. Total RNA was isolated with TRIzol from each group, Sox8, Sox9, Sox10, Dcx, and Neurod1 expression levels were measured by qPCR. Result: Sox8 and Sox10, oligodendrocyte markers, and Sox9, an astrocyte marker, were expressed at a much higher level after 7 days of culture in GalC7 hydrogel compared to all other conditions. Dcx, a marker of neurogenesis, and Neurod1, a marker of neuronal differentiation, were expressed at better levels in the GalC7 gel culture compared to the neurosphere. Conclusions: These results show that the GalC7 hydrogel brings different and interesting conditions for inducing the differentiation and maturation of neural progenitor cells compared with polymer-based scaffolds or cell-only conditions. The differences observed open new perspectives in tissue engineering, induction, and transcript analysis.

Autism Spectrum Disorder (ASD) poses significant challenges to society and science due to its impact on communication, social interaction, and repetitive behavior patterns in affected children. The Autism and Developmental Disabilities Monitoring (ADDM) Network continuously monitors ASD prevalence and characteristics. In 2020, ASD prevalence was estimated at 1 in 36 children, with higher rates than previous estimates. This study focuses on ongoing ASD research conducted by Erciyes University. Serum samples from 45 ASD patients and 21 unrelated control participants were analyzed to assess the expression of 372 microRNAs (miRNAs). Six miRNAs (miR-19a-3p, miR-361-5p, miR-3613-3p, miR-150-5p, miR-126-3p, and miR-499a-5p) exhibited significant downregulation in all ASD patients compared to healthy controls. The current study endeavors to identify dependable diagnostic biomarkers for ASD, addressing the pressing need for non-invasive, accurate, and cost-effective diagnostic tools, as current methods are subjective and time-intensive. A pivotal discovery in this study is the potential diagnostic value of miR-126-3p, offering the promise of earlier and more accurate ASD diagnoses, potentially leading to improved intervention outcomes. Leveraging machine learning, such as the K-nearest neighbors (KNN) model, presents a promising avenue for precise ASD diagnosis using miRNA biomarkers.