Neurodegeneration in diabetic retinopathy : does it really matter?

Altres ajuts: RS is supported by the following grants: Ministerio de Economía y Competitividad and the Fundació Marató TV3 (201629-10). AWS is supported by the following grants: Fight for Sight, The Belfast Association for the Blind and The Jules Thorn Trust. TWG is supported by the following grants: R01EY20582, R24DK082841, Research to Prevent Blindness and The Taubman Medical Research Institute.The concept of diabetic retinopathy as a microvascular disease has evolved, in that it is now considered a more complex diabetic complication in which neurodegeneration plays a significant role. In this article we provide a critical overview of the role of microvascular abnormalities and neurodegeneration in the pathogenesis of diabetic retinopathy. A special emphasis is placed on the pathophysiology of the neurovascular unit (NVU), including the contributions of microvascular and neural elements. The potential mechanisms linking retinal neurodegeneration and early microvascular impairment, and the effects of neuroprotective drugs are summarised. Additionally, we discuss how the assessment of retinal neurodegeneration could be an important index of cognitive status, thus helping to identify individuals at risk of dementia, which will impact on current procedures for diabetes management. We conclude that glial, neural and microvascular dysfunction are interdependent and essential for the development of diabetic retinopathy. Despite this intricate relationship, retinal neurodegeneration is a critical endpoint and neuroprotection, itself, can be considered a therapeutic target, independently of its potential impact on microvascular disease. In addition, interventional studies targeting pathogenic pathways that impact the NVU are needed. Findings from these studies will be crucial, not only for increasing our understanding of diabetic retinopathy, but also to help to implement a timely and efficient personalised medicine approach for treating this diabetic complication

Dynamic reconfiguration of cortical functional connectivity across brain states

Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (?ECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states

Single feature polymorphism (SFP)-based selective sweep identification and association mapping of growth-related metabolic traits in Arabidopsis thaliana

Background: Natural accessions of Arabidopsis thaliana are characterized by a high level of phenotypic variation that can be used to investigate the extent and mode of selection on the primary metabolic traits. A collection of 54 A. thaliana natural accession-derived lines were subjected to deep genotyping through Single Feature Polymorphism (SFP) detection via genomic DNA hybridization to Arabidopsis Tiling 1.0 Arrays for the detection of selective sweeps, and identification of associations between sweep regions and growth-related metabolic traits. Results: A total of 1,072,557 high-quality SFPs were detected and indications for 3,943 deletions and 1,007 duplications were obtained. A significantly lower than expected SFP frequency was observed in protein-, rRNA-, and tRNA-coding regions and in non-repetitive intergenic regions, while pseudogenes, transposons, and non-coding RNA genes are enriched with SFPs. Gene families involved in plant defence or in signalling were identified as highly polymorphic, while several other families including transcription factors are depleted of SFPs. 198 significant associations between metabolic genes and 9 metabolic and growth-related phenotypic traits were detected with annotation hinting at the nature of the relationship. Five significant selective sweep regions were also detected of which one associated significantly with a metabolic trait. Conclusions: We generated a high density polymorphism map for 54 A. thaliana accessions that highlights the variability of resistance genes across geographic ranges and used it to identify selective sweeps and associations between metabolic genes and metabolic phenotypes. Several associations show a clear biological relationship, while many remain requiring further investigation

Potencijalna profilaktička uloga aminogvanidina u diabetičkoj retinopatiji i nefropatiji u eksperimentalnih životinja

This study sought to determine the potential prophylactic and antioxidant effects of aminoguanidine in experimentally induced diabetes. Four groups of Wistar rats, each composed of ten rats, were used. Two groups served as control. In group 3, diabetes was induced by a single intraperitoneal injection of streptozotocin (65 mg kg1). In group 4, diabetes was induced and treated with aminoguanidine 100 mg kg1 daily orally for 3 months. Levels of serum glucose, glutathione peroxidase, glutathione reductase and erythrocytes catalase were analyzed on day 90 of the experiment. Retinal and kidney specimens were examined histopathologically after sacrifice of the animals. A significant antioxidant effect of aminoguanidine and its prophylactic role in diabetic retinopathy and nephropathy were observed in experimental animals.U ovom radu ispitivano je potencijalno profilaktičko i antioksidativno djelovanje aminogvanidina u eksperimentalno induciranom dijabetesu. Ispitivanja su provedena na četiri skupine od 10 štakora. Dvije skupine bile su kontrolne skupine, u trećoj skupini dijabetes je induciran jednokratnom intraperitonealnom injekcijom streptozotocina 65 mg kg1, a u četvrtoj dijabetes je induciran i tretiran aminogvanidinom 100 mg kg1 dnevno, peroralno, tijekom 3 mjeseca. Devedeseti dan eksperimenta analizirane su koncentracije glukoze u serumu, glutation peroksidaze, glutation reduktaze i eritrocitne katalaze. Životinje su žrtvovane, a uzorci retine i bubrega ispitivani su histopatologiški. Uočen je značajni antioksidativni učinak aminogvanidina i njegova profilaktička uloga u dijabetičkoj retinopatiji i nefropatiji

Epitaxial Graphene Growth on SiC Wafers

An in vacuo thermal desorption process has been accomplished to form epitaxial graphene (EG) on 4H- and 6H-SiC substrates using a commercial chemical vapor deposition reactor. Correlation of growth conditions and the morphology and electrical properties of EG are described. Raman spectra of EG on Si-face samples were dominated by monolayer thickness. This approach was used to grow EG on 50 mm SiC wafers that were subsequently fabricated into field effect transistors with fmax of 14 GHz.Comment: 215th Meeting of the Electrochemical Society, 8 pages, 8 figure

Intraspecfic variation in cold-temperature metabolic phenotypes of Arabidopsis lyrata ssp petraea

Atmospheric temperature is a key factor in determining the distribution of a plant species. Alongside this, plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. We investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes associated with exposure to cold temperatures. Seeds of A. petraea were obtained from populations along a latitudinal gradient, namely Wales, Sweden and Iceland and grown in a controlled cabinet environment. Mannose, glucose, fructose, sucrose and raffinose concentrations were different between cold treatments and populations, especially in the Welsh population, but polyhydric alcohol concentrations were not. The free amino acid compositions were population specific, with fold differences in most amino acids, especially in the Icelandic populations, with gross changes in amino acids, particularly those associated with glutamine metabolism. Metabolic fingerprints and profiles were obtained. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic characteristic phenotypes for each population and temperature. It is suggested that amino acids and carbohydrates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations at different atmospheric temperatures. These findings show that there is significant natural variation in cold metabolism among populations of A. l. petraea which may signify plant adaptation to local climates

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth

Understanding how dynamic molecular networks affect wholeorganism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field. (Résumé d'auteur