Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Enalapril Treatment Alters the Contribution of Epoxyeicosatrienoic Acids but Not Gap Junctions to Endothelium-Derived Hyperpolarizing Factor Activity in Mesenteric Arteries of Spontaneously Hypertensive Rats

Reduction in endothelium-derived hyperpolarizing factor (EDHF)-mediated dilatory function in large, elastic arteries during hypertension is reversed after blood pressure normalization. We investigated whether similar mechanisms occurred in smaller mesenteric resistance arteries from aged Wistar-Kyoto (WKY) rats, spontaneously hypertensive rats (SHRs), and SHRs treated with the angiotensin-converting enzyme inhibitor, enalapril, using immunohistochemistry, serial-section electron microscopy, electrophysiology and wire myography. Unlike the superior mesenteric artery, EDHF relaxations in muscular mesenteric arteries were not reduced in SHRs, although morphological differences were found in the endothelium and smooth muscle. In WKY rats, SHRs and enalapril-treated SHRs, relaxations were mediated by small-, large-, and intermediate-conductance calcium-activated potassium channels, which were distributed in the endothelium, smooth muscle, and both layers, respectively. However, only WKY hyperpolarizations and relaxations were sensitive to gap junction blockers, and these arteries expressed more endothelial and myoendothelial gap junctions than arteries from SHRs. Responses in WKY rats, but not SHRs, were also reduced by inhibitors of epoxyeicosatrienoic acids (EETs), 14,15-epoxyeicosa-5(Z)-enoic acid (14,15-EEZE) and miconazole, although sensitivity to EET regioisomers was endothelium-independent in all rats. Enalapril treatment of SHRs reduced blood pressure and restored sensitivity to 14,15-EEZE, but not to gap junction blockers, and failed to reverse the morphological changes. In conclusion, the mechanisms underlying EDHF in muscular mesenteric arteries differ between WKY rats and SHRs, with gap junctions and EETs involved only in WKY rats. However, reduction of blood pressure in SHRs with enalapril restored a role for EETs, but not gap junctions, without reversing morphological changes, suggesting a differential control of chemical and structural alterations

Vascular microarray profiling in two models of hypertension identifies Cav-1, Rgs2 and Rgs5 as antihypertensive targets

BACKGROUND: Hypertension is a complex disease with many contributory genetic and environmental factors. We aimed to identify common targets for therapy by gene expression profiling of a resistance artery taken from animals representing two different models of hypertension. We studied gene expression and morphology of a saphenous artery branch in normotensive WKY rats, spontaneously hypertensive rats (SHR) and adrenocorticotropic hormone (ACTH)-induced hypertensive rats. RESULTS: Differential remodeling of arteries occurred in SHR and ACTH-treated rats, involving changes in both smooth muscle and endothelium. Increased expression of smooth muscle cell growth promoters and decreased expression of growth suppressors confirmed smooth muscle cell proliferation in SHR but not in ACTH. Differential gene expression between arteries from the two hypertensive models extended to the renin-angiotensin system, MAP kinase pathways, mitochondrial activity, lipid metabolism, extracellular matrix and calcium handling. In contrast, arteries from both hypertensive models exhibited significant increases in caveolin-1 expression and decreases in the regulators of G-protein signalling, Rgs2 and Rgs5. Increased protein expression of caveolin-1 and increased incidence of caveolae was found in both smooth muscle and endothelial cells of arteries from both hypertensive models. CONCLUSION: We conclude that the majority of differences in gene expression found in the saphenous artery taken from rats with two different forms of hypertension reflect distinctive morphological and physiological alterations. However, changes in common to caveolin-1 expression and G protein signalling, through attenuation of Rgs2 and Rgs5, may contribute to hypertension through augmentation of vasoconstrictor pathways and provide potential targets for common drug development

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets

Abstract Background Hypertension is a complex disease with many contributory genetic and environmental factors. We aimed to identify common targets for therapy by gene expression profiling of a resistance artery taken from animals representing two different models of hypertension. We studied gene expression and morphology of a saphenous artery branch in normotensive WKY rats, spontaneously hypertensive rats (SHR) and adrenocorticotropic hormone (ACTH)-induced hypertensive rats. Results Differential remodeling of arteries occurred in SHR and ACTH-treated rats, involving changes in both smooth muscle and endothelium. Increased expression of smooth muscle cell growth promoters and decreased expression of growth suppressors confirmed smooth muscle cell proliferation in SHR but not in ACTH. Differential gene expression between arteries from the two hypertensive models extended to the renin-angiotensin system, MAP kinase pathways, mitochondrial activity, lipid metabolism, extracellular matrix and calcium handling. In contrast, arteries from both hypertensive models exhibited significant increases in caveolin-1 expression and decreases in the regulators of G-protein signalling, Rgs2 and Rgs5. Increased protein expression of caveolin-1 and increased incidence of caveolae was found in both smooth muscle and endothelial cells of arteries from both hypertensive models. Conclusion We conclude that the majority of differences in gene expression found in the saphenous artery taken from rats with two different forms of hypertension reflect distinctive morphological and physiological alterations. However, changes in common to caveolin-1 expression and G protein signalling, through attenuation of Rgs2 and Rgs5, may contribute to hypertension through augmentation of vasoconstrictor pathways and provide potential targets for common drug development.</p

Time-dependent homeostatic mechanisms underlie brain-derived neurotrophic factor action on neural circuitry

Abstract Plasticity and homeostatic mechanisms allow neural networks to maintain proper function while responding to physiological challenges. Despite previous work investigating morphological and synaptic effects of brain-derived neurotrophic factor (BDNF), the most prevalent growth factor in the central nervous system, how exposure to BDNF manifests at the network level remains unknown. Here we report that BDNF treatment affects rodent hippocampal network dynamics during development and recovery from glutamate-induced excitotoxicity in culture. Importantly, these effects are not obvious when traditional activity metrics are used, so we delve more deeply into network organization, functional analyses, and in silico simulations. We demonstrate that BDNF partially restores homeostasis by promoting recovery of weak and medium connections after injury. Imaging and computational analyses suggest these effects are caused by changes to inhibitory neurons and connections. From our in silico simulations, we find that BDNF remodels the network by indirectly strengthening weak excitatory synapses after injury. Ultimately, our findings may explain the difficulties encountered in preclinical and clinical trials with BDNF and also offer information for future trials to consider

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets-3

<p><b>Copyright information:</b></p><p>Taken from "Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets"</p><p>http://www.biomedcentral.com/1471-2164/8/404</p><p>BMC Genomics 2007;8():404-404.</p><p>Published online 7 Nov 2007</p><p>PMCID:PMC2219888.</p><p></p>aveolin-1 in both endothelial cells (EC: A-C) and in smooth muscle cells (SMC: D-F) of saphenous arteries taken from SHR (B, E) and ACTH (C, F), compared to WKY (A, D). Arrows indicate staining delineating the membranes of smooth muscle cells (D-F). Preincubation of the antibody with the immunogen eliminated staining in both endothelium and smooth muscle (G). Calibration bars represent 25 μm

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets-5

<p><b>Copyright information:</b></p><p>Taken from "Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets"</p><p>http://www.biomedcentral.com/1471-2164/8/404</p><p>BMC Genomics 2007;8():404-404.</p><p>Published online 7 Nov 2007</p><p>PMCID:PMC2219888.</p><p></p>10 μm

Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets-1

<p><b>Copyright information:</b></p><p>Taken from "Vascular microarray profiling in two models of hypertension identifies caveolin-1, Rgs2 and Rgs5 as antihypertensive targets"</p><p>http://www.biomedcentral.com/1471-2164/8/404</p><p>BMC Genomics 2007;8():404-404.</p><p>Published online 7 Nov 2007</p><p>PMCID:PMC2219888.</p><p></p>he position of each array is shown as a label joined by a dotted line to the origin. B. A heat map (white: up-regulated; red: down-regulated) using hierarchical clustering with complete linkage for the columns only. The rank order of the p-values, gene names and Affymetrix IDs are included on the right and correspond to the numbering in A