Essential role of insulin and insulin-like growth factor 1 receptor signaling in cardiac development and function

Cardiovascular disease is the leading cause of death in people with type 2 diabetes and is linked to insulin resistance even in the absence of diabetes. Here we show that mice with combined deficiency of the insulin receptor and insulin-like growth factor 1 (IGF-1) receptor in cardiac and skeletal muscle develop early-onset dilated cardiomyopathy and die from heart failure within the first month of life despite having a normal glucose homeostasis. Mice lacking the insulin receptor show impaired cardiac performance at 6 months, and mice lacking the insulin receptor plus one Igf1r allele have slightly increased mortality. By contrast, mice lacking the IGF-1 receptor or the IGF-1 receptor plus one Ir allele appear normal. Morphological characterization and oligonucleotide array analysis of gene expression demonstrate that prior to development of these physiological defects, mice with combined deficiency of both insulin and IGF-1 receptors have a coordinated down-regulation of genes encoding components of the electron transport chain and mitochondrial fatty acid beta-oxidation pathways and altered expression of contractile proteins. Thus, while neither the insulin receptor nor IGF-1 receptor in muscle is critical for glucose homeostasis during the first month of life, signaling from these receptors, particularly the insulin receptor, is required for normal cardiac metabolism and function.     

Nestin is expressed in vascular endothelial cells in the adult human pancreas.

In this study we examined the expression of nestin in islets, the exocrine part, and the big ducts of the adult human pancreas by immunofluorescent double staining. Two different anti-nestin antisera in combination with various pancreatic and endothelial markers were employed. Nestin-immunoreactive cells were found in islets and in the exocrine portion. All nestin-positive cells co-expressed the vascular endothelial markers PECAM-1 (CD31), endoglin (CD105), and CD34 as well as vimentin. Endocrine, acinar, and duct cells did not stain for nestin. We also demonstrated that in the area of big pancreatic ducts, nestin-positive cells represent small capillaries scattered in the connective tissue surrounding the duct epithelium and do not reside between the duct cells. We detected nestin-expressing endothelial cells located adjacent to the duct epithelium where endocrine differentiation occurs. We have shown that nestin is expressed by vascular endothelial cells in human pancreas, and therefore it is unlikely that nestin specifically marks a subpopulation of cells representing endocrine progenitors in the adult pancreas.     

Large-Scale metabolomics: Predicting biological age using 10,133 routine untargeted LC–MS measurements

Untargeted metabolomics is the study of all detectable small molecules, and in geroscience, metabolomics has shown great potential to describe the biological age—a complex trait impacted by many factors. Unfortunately, the sample sizes are often insufficient to achieve sufficient power and minimize potential biases caused by, for example, demographic factors. In this study, we present the analysis of biological age in ~10,000 toxicologic routine blood measurements. The untargeted screening samples obtained from ultra-high pressure liquid chromatography-quadruple time of flight mass spectrometry (UHPLC- QTOF) cover + 300 batches and + 30 months, lack pooled quality controls, lack controlled sample collection, and has previously only been used in small-scale studies. To overcome experimental effects, we developed and tested a custom neural network model and compared it with existing prediction methods. Overall, the neural network was able to predict the chronological age with an rmse of 5.88 years (r² = 0.63) improving upon the 6.15 years achieved by existing normalization methods. We used the feature importance algorithm, Shapley Additive exPlanations (SHAP), to identify compounds related to the biological age. Most importantly, the model returned known aging markers such as kynurenine, indole-3-aldehyde, and acylcarnitines along with a potential novel aging marker, cyclo (leu-pro). Our results validate the association of tryptophan and acylcarnitine metabolism to aging in a highly uncontrolled large-s cale sample. Also, we have shown that by using robust computational methods it is possible to deploy large LC-MS datasets for metabolomics studies to reduce the risk of bias and empower aging studies.     

Pancreatic-duodenal homeobox 1 -role in gastric endocrine patterning

The gastrointestinal tract is subdivided into regions with different roles in digestion and absorption. How this patterning is established is unknown. We now report that the pancreatic-duodenal homeobox 1 gene (pdx1) is also expressed in cells of the distal stomach. Positive cells include subpopulations of the three main endocrine (gastrin, somatostatin and serotonin) cell types of this region. Pdx1 deficient mice were virtually devoid of gastrin cells, had normal numbers of somatostatin cells and increased numbers of serotonin cells. Pdx1 is thus important for development of the gastrin cells of the antropyloric mucosa of the stomach and probably acts by controlling the fate of gastrin/serotonin precursor cells.     

Prediction of complex phenotypes using the Drosophila melanogaster metabolome

Understanding the genotype–phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.Subject terms: Quantitative trait, Genetic association study     

Colorimetric Evaluation of Cultured Osteoblast-like Cells (ROS 17/2.8)

We have developed a colorimetric method for evaluating the number of osteoblastic cells in culture without destroying the cells. This assay is based on the staining of basophilic cellular compounds with methylene blue. The dye bound by the cells is released at low pH and measured in a spectrophotometer at 662 nm. Linear correlations exist between the absorbance measured by the methylene blue assay and the number of cells seeded, the total cellular protein content, and thymidine labeling. This colorimetric method has the advantage of preserving cell integrity. After destaining, scanning electron microscopy can be performed on well preserved cell morphology.