Calcium Dobesilate Prevents Neurodegeneration and Vascular Leakage in Experimental Diabetes

<p><i>Purpose</i>: The mechanisms involved in the reported beneficial effects of Calcium dobesilate monohydrate (CaD) for the treatment of diabetic retinopathy (DR) remain to be elucidated. The main aim of the present study is to examine whether CaD prevents early events in the pathogenesis of DR such as neurodegeneration and vascular leakage. In addition, putative mediators of both neurodegeneration (glutamate/GLAST, ET-1/ETB receptor) and early microvascular impairment (ET-1/ETA receptor, oxidative stress, VEGF, and the PKC-delta-p38 MAPK pathway) have been examined.</p> <p><i>Methods</i>: Diabetic (db/db) mice were randomly assigned to daily oral treatment with CaD (200 mg/Kg/day) (<i>n</i> = 12) or vehicle (<i>n</i> = 12) for 14 days. In addition, 12 non-diabetic (db/+) mice matched by age were used as the control group. Functional abnormalities were assessed by electroretinography. Neurodegeneration and microvascular abnormalities were evaluated by immunohistochemistry and Western blot. Glutamate was determined by HPLC.</p> <p><i>Results</i>: CaD significantly decreased glial activation and apoptosis and produced a significant improvement in the electroretinogram parameters. Mechanistically, CaD prevented the diabetes-induced up-regulation of ET-1 and its cognate receptors (ETA-R and ETB-R), which are involved in microvascular impairment and neurodegeneration, respectively. In addition, treatment with CaD downregulated GLAST, the main glutamate transporter, and accordingly prevented the increase in glutamate. Finally, CaD prevented oxidative stress, and the upregulation of VEGF and PKC delta-p38 MAPK pathway induced by diabetes, thus resulting in a significant reduction in vascular leakage.</p> <p><i>Conclusions</i>: Our findings demonstrate for the first time that CaD exerts neuroprotection in an experimental model of DR. In addition, we provide first evidence that CaD prevents the overexpression of ET-1 and its receptors in the diabetic retina. These beneficial effects on the neurovascular unit could pave the way for clinical trials addressed to confirm the effectiveness of CaD in very early stages of DR.</p

geoRge: A Computational Tool To Detect the Presence of Stable Isotope Labeling in LC/MS-Based Untargeted Metabolomics

Studying the flow of chemical moieties through the complex set of metabolic reactions that happen in the cell is essential to understanding the alterations in homeostasis that occur in disease. Recently, LC/MS-based untargeted metabolomics and isotopically labeled metabolites have been used to facilitate the unbiased mapping of labeled moieties through metabolic pathways. However, due to the complexity of the resulting experimental data sets few computational tools are available for data analysis. Here we introduce geoRge, a novel computational approach capable of analyzing untargeted LC/MS data from stable isotope-labeling experiments. geoRge is written in the open language R and runs on the output structure of the XCMS package, which is in widespread use. As opposed to the few existing tools, which use labeled samples to track stable isotopes by iterating over all MS signals using the theoretical mass difference between the light and heavy isotopes, geoRge uses unlabeled and labeled biologically equivalent samples to compare isotopic distributions in the mass spectra. Isotopically enriched compounds change their isotopic distribution as compared to unlabeled compounds. This is directly reflected in a number of new <i>m</i>/<i>z</i> peaks and higher intensity peaks in the mass spectra of labeled samples relative to the unlabeled equivalents. The automated untargeted isotope annotation and relative quantification capabilities of geoRge are demonstrated by the analysis of LC/MS data from a human retinal pigment epithelium cell line (ARPE-19) grown on normal and high glucose concentrations mimicking diabetic retinopathy conditions in vitro. In addition, we compared the results of geoRge with the outcome of X¹³CMS, since both approaches rely entirely on XCMS parameters for feature selection, namely <i>m</i>/<i>z</i> and retention time values. To ensure data traceability and reproducibility, and enabling for comparison with other existing and future approaches, raw LC/MS files have been deposited in MetaboLights (MTBLS213) and geoRge is available as an R script at https://github.com/jcapelladesto/geoRge