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      Methylglyoxal, a highly reactive dicarbonyl compound, in diabetes, its vascular complications and other age-related diseases

      1 , 2
      Physiological Reviews
      American Physiological Society

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          Abstract

          The formation and accumulation of methylglyoxal (MGO), a highly reactive dicarbonyl compound, has been implicated in the pathogenesis of type 2 diabetes, vascular complications of diabetes, and several other age-related chronic inflammatory diseases such as cardiovascular disease, cancer and disorders of the central nervous system. MGO is mainly formed as a byproduct of glycolysis and, under physiological circumstances, detoxified by the glyoxalase system. MGO is the major precursor of non-enzymatic glycation of proteins and DNA, subsequently leading to the formation of advanced glycation endproducts (AGEs). MGO and MGO-derived AGEs can impact on organs and tissues affecting their functions and structure. This review summarizes the mechanisms through which MGO is formed, its detoxification by the glyoxalase system, and its effect on biochemical pathways in relation to the development of diabetes, vascular complications of diabetes and other age-related diseases. Although therapies to treat MGO-associated complications are not yet available for application in clinical practice, several strategies to lower MGO have been developed over the years. We will summarize several new directions to target MGO stress including glyoxalase inducers and MGO scavengers. Diminishing MGO burden can potentially form the basis for new treatment strategies for age-related disorders in which MGO plays a pivotal role.

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          Global variation in copy number in the human genome.

          Copy number variation (CNV) of DNA sequences is functionally significant but has yet to be fully ascertained. We have constructed a first-generation CNV map of the human genome through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia (the HapMap collection). DNA from these individuals was screened for CNV using two complementary technologies: single-nucleotide polymorphism (SNP) genotyping arrays, and clone-based comparative genomic hybridization. A total of 1,447 copy number variable regions (CNVRs), which can encompass overlapping or adjacent gains or losses, covering 360 megabases (12% of the genome) were identified in these populations. These CNVRs contained hundreds of genes, disease loci, functional elements and segmental duplications. Notably, the CNVRs encompassed more nucleotide content per genome than SNPs, underscoring the importance of CNV in genetic diversity and evolution. The data obtained delineate linkage disequilibrium patterns for many CNVs, and reveal marked variation in copy number among populations. We also demonstrate the utility of this resource for genetic disease studies.
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            Pathologic classification of diabetic nephropathy.

            Although pathologic classifications exist for several renal diseases, including IgA nephropathy, focal segmental glomerulosclerosis, and lupus nephritis, a uniform classification for diabetic nephropathy is lacking. Our aim, commissioned by the Research Committee of the Renal Pathology Society, was to develop a consensus classification combining type1 and type 2 diabetic nephropathies. Such a classification should discriminate lesions by various degrees of severity that would be easy to use internationally in clinical practice. We divide diabetic nephropathy into four hierarchical glomerular lesions with a separate evaluation for degrees of interstitial and vascular involvement. Biopsies diagnosed as diabetic nephropathy are classified as follows: Class I, glomerular basement membrane thickening: isolated glomerular basement membrane thickening and only mild, nonspecific changes by light microscopy that do not meet the criteria of classes II through IV. Class II, mesangial expansion, mild (IIa) or severe (IIb): glomeruli classified as mild or severe mesangial expansion but without nodular sclerosis (Kimmelstiel-Wilson lesions) or global glomerulosclerosis in more than 50% of glomeruli. Class III, nodular sclerosis (Kimmelstiel-Wilson lesions): at least one glomerulus with nodular increase in mesangial matrix (Kimmelstiel-Wilson) without changes described in class IV. Class IV, advanced diabetic glomerulosclerosis: more than 50% global glomerulosclerosis with other clinical or pathologic evidence that sclerosis is attributable to diabetic nephropathy. A good interobserver reproducibility for the four classes of DN was shown (intraclass correlation coefficient = 0.84) in a test of this classification.
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              Sugar for the brain: the role of glucose in physiological and pathological brain function.

              The mammalian brain depends upon glucose as its main source of energy, and tight regulation of glucose metabolism is critical for brain physiology. Consistent with its critical role for physiological brain function, disruption of normal glucose metabolism as well as its interdependence with cell death pathways forms the pathophysiological basis for many brain disorders. Here, we review recent advances in understanding how glucose metabolism sustains basic brain physiology. We synthesize these findings to form a comprehensive picture of the cooperation required between different systems and cell types, and the specific breakdowns in this cooperation that lead to disease. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Physiological Reviews
                Physiological Reviews
                American Physiological Society
                0031-9333
                1522-1210
                September 20 2019
                Affiliations
                [1 ]Internal medicine, Maastricht University Medical Center, Netherlands
                [2 ]Maastricht University Medical Centre (MUMC+), Netherlands
                Article
                10.1152/physrev.00001.2019
                31539311
                a3c2ecd5-197b-4d36-a0c5-f3017d12def7
                © 2019
                History

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