FGF-2b and h-PL transform duct and non-endocrine human pancreatic cells into endocrine insulin secreting cells by modulating differentiating genes

Background: Diabetes mellitus (DM) is a multifactorial disease orphan of a cure. Regenerative medicine has been proposed as novel strategy for DM therapy. Human fibroblast growth factor (FGF)-2b controls β-cell clusters via autocrine action, and human placental lactogen (hPL)-A increases functional β-cells. We hypothesized whether FGF-2b/hPL-A treatment induces β-cell differentiation from ductal/non-endocrine precursor(s) by modulating specific genes expression. Methods: Human pancreatic ductal-cells (PANC-1) and non-endocrine pancreatic cells were treated with FGF-2b plus hPL-A at 500 ng/mL. Cytofluorimetry and Immunofluorescence have been performed to detect expression of endocrine, ductal and acinar markers. Bromodeoxyuridine incorporation and annexin-V quantified cells proliferation and apoptosis. Insulin secretion was assessed by RIA kit, and electron microscopy analyzed islet-like clusters. Results: Increase in PANC-1 duct cells de-differentiation into islet-like aggregates was observed after FGF-2b/hPL-A treatment showing ultrastructure typical of islets-aggregates. These clusters, after stimulation with FGF-2b/hPL-A, had significant (p < 0.05) increase in insulin, C-peptide, pancreatic and duodenal homeobox 1 (PDX-1), Nkx2.2, Nkx6.1, somatostatin, glucagon, and glucose transporter 2 (Glut-2), compared with control cells. Markers of PANC-1 (Cytokeratin-19, MUC-1, CA19-9) were decreased (p < 0.05). These aggregates after treatment with FGF-2b/hPL-A significantly reduced levels of apoptosis. Conclusions: FGF-2b and hPL-A are promising candidates for regenerative therapy in DM by inducing de-differentiation of stem cells modulating pivotal endocrine genes

Sildenafil Reduces Insulin-Resistance in Human Endothelial Cells

The efficacy of Phosphodiesterase 5 (PDE5) inhibitors to re-establish endothelial function is reduced in diabetic patients. Recent evidences suggest that therapy with PDE5 inhibitors, i.e. sildenafil, may increase the expression of nitric oxide synthase (NOS) proteins in the heart and cardiomyocytes. In this study we analyzed the effect of sildenafil on endothelial cells in insulin resistance conditions in vitro

Profile and differential expression of protein tyrosine phosphatases in mouse pancreatic islet tumor cell lines

Protein tyrosine phosphatases (PTPs) play important roles in cell growth and differentiation of normal and tumor cells. In this study, we analyzed the PTP profile in two pancreatic islet tumor cell lines. Transcripts were isolated from alphaTC-1 (glucagon-secreting) and betaTC-1 (insulin-secreting) cell lines for templates. A pair of degenerative primers, based on the conserved regions of known PTPs, was used to amplify the transcripts by polymerase chain reaction. A total of 1,620 clones was examined by restriction enzyme analysis and cDNA sequencing. Twenty-one PTPs were identified, including nine cytosolic PTPs (TcPTP, P19PTP, PTP1B, PTPMEG, PTP1C, SYP, PTPH1, PTPL1, and PTPD1), nine transmembrane PTPs (PTPdelta, PTPgamma, PTPkappa, DEP-1, IA-2, LAR, PTPalpha, PTPNE3, and PTPepsilon), and three new PTPs--PTPmu-like PTPkappa-like, and IA-2beta. An RNase protection assay demonstrated that some of these PTPs were expressed predominantly in glucagonoma (i.e., PTPdelta and IA-2) and others in insulinoma (i.e., PTP1C, PTPkappa, and PTPNE3) cells. In this report, we present the first profile of PTPs in alpha and beta tumor cell lines

cDNA sequence and genomic organization of mouse secretin

A murine insulinoma library was constructed by subtracting glucagonoma cDNAs from insulinoma cDNAs. Comparison of the nucleotide sequence of one of the clones with sequences from the GenBank database showed that it was a member of the secretin family. The clone, 490 bp long, encodes a protein of 133 amino acids consisting of a signal peptide, a N-terminal peptide, secretin, and a C-terminal peptide, which showed 88% and 80% homology with rat and porcine secretin precursor proteins, respectively. The translated secretin peptide showed a unique Met to Thr substitution at position 5 as compared to the secretins from other species. That the Met to Thr substitution was not tumor-related was demonstrated by the fact that an identical sequence was found in cDNA from normal mouse intestine. Studies on the mouse secretin gene revealed that it contains four exons separated by 81 bp, 110 bp, and 96 bp introns

Identifying patterns in multiple biomarkers to diagnose diabetic foot using an explainable genetic programming-based approach

Diabetes mellitus is a global health problem, recognized as the seventh cause of death in the world. One of the most debilitating complications of diabetes mellitus is the diabetic foot (DF), resulting in an increased risk of hospitalization and significant morbidity and mortality. Amputation above or below the knee is a feared complication and the mortality in these patients is higher than for most forms of cancer. Identifying and interpreting relationships existing among the factors involved in DF diagnosis is still challenging. Although machine learning approaches have proven to achieve great accuracy in DF prediction, few advances have been performed in understanding how they make such predictions, resulting in mistrust of their use in real contexts. In this study, we present an approach based on Genetic Programming to build a simple global explainable classifier, named X-GPC, which, unlike existing tools such as LIME and SHAP, provides a global interpretation of the DFU diagnosis through a mathematical model. Also, an easy consultable 3d graph is provided, which could be used by the medical staff to figure out the patients’ situation and take decisions for patients’ healing. Experimental results obtained by using a real-world dataset have shown the ability of the proposal to diagnose DF with an accuracy of 100% outperforming other techniques of the state-of-the-art