Small island economies : Caribbean versus Pacific

After a review of the small island economy literature, this study compares the average performance of 16 Caribbean versus 15 mainly Pacific islands with three from the Indian Ocean. Mean difference analysis is employed across 22 socio-economic and demographic variables. Results confirm previous research. The Caribbean outperforms the Pacific with higher per capita GDP and life expectancy and lower infant mortality and fertility. Different migration experiences discriminate the more dynamic Caribbean characterized by heavy immigration from the relatively stagnant Pacific marked by chronic emigration. The three determinants offered to account for these differences involve significant Caribbean advantages: geographic proximity to the major global markets, early post-war development of international tourism and offshore banking, and a longer and more intense period of colonisation that early on established basic infrastructure and market institutions.peer-reviewe

Erosion Wear of Axial Flow Impellersin a Solid-liquid Suspension

A study was made of the erosion wear of the blades of pitched blade impellers in a suspension of waste gypsum from a thermal power station (vol. concentration CV=18.3 %, particle mean diameter d=0.1 mm, degree of hardness “2.5”) and silicious sand (CV=10 %, d=0.4 mm, degree of hardness “7.5”) in water under a turbulent flow regime of agitated charge when complete homogeneity of the suspension was achieved. Experiments were carried out on pilot plant mixing equipment made of stainless steel (diameter of cylindrical vessel T=390 mm, diameter of impeller D=100 mm, impeller off-bottom clearance h=100 mm) equipped with four wall radial baffles (width b=39 mm) and an impeller with four inclined plane blades (pitch angle α =20°, 30°, 45°, relative blade width W/D=0.2) made either of rolled brass (Brinell hardness 40–50 BH) or of structural steel (Brinell hardness 100–120 BH) always pumping the liquid downwards towards the flat vessel bottom. Two erosion process mechanisms appear, depending on the hardness of the solid particles in the suspension: while the particles of gypsum (lower hardness) generate a uniform sheet erosion over the whole surface of the impeller blade, the particles of silicious sand (higher hardness) generate wear of the leading edge of the impeller blades, together with a reduction of the surface of the worn blade. The hardness of the impeller blade also affects the rate of the erosion process: the higher the hardness of the impeller blade, the lower the wear rate of the blade. This study consists of a description of the kinetics of the erosion process of both mechanisms in dependence on the pitch angle of the tested impellers. While the wear of the leading edge of the blade exhibits a monotonous dependence on the pitch angle, the sheet erosion exhibits the maximum rate within the interval of the pitch angles tested α ϵ <20°; 45°>.However, generally the pitch angle α =45° seems to be the most convenient angle of blade inclination when both investigated mechanisms of the blade erosion process are considered at their minimum rate

MolAxis: a server for identification of channels in macromolecules

MolAxis is a freely available, easy-to-use web server for identification of channels that connect buried cavities to the outside of macromolecules and for transmembrane (TM) channels in proteins. Biological channels are essential for physiological processes such as electrolyte and metabolite transport across membranes and enzyme catalysis, and can play a role in substrate specificity. Motivated by the importance of channel identification in macromolecules, we developed the MolAxis server. MolAxis implements state-of-the-art, accurate computational-geometry techniques that reduce the dimensions of the channel finding problem, rendering the algorithm extremely efficient. Given a protein or nucleic acid structure in the PDB format, the server outputs all possible channels that connect buried cavities to the outside of the protein or points to the main channel in TM proteins. For each channel, the gating residues and the narrowest radius termed ‘bottleneck’ are also given along with a full list of the lining residues and the channel surface in a 3D graphical representation. The users can manipulate advanced parameters and direct the channel search according to their needs. MolAxis is available as a web server or as a stand-alone program at http://bioinfo3d.cs.tau.ac.il/MolAxis

MolAxis: a server for identification of channels in macromolecules

MolAxis is a freely available, easy-to-use web server for identification of channels that connect buried cavities to the outside of macromolecules and for transmembrane (TM) channels in proteins. Biological channels are essential for physiological processes such as electrolyte and metabolite transport across membranes and enzyme catalysis, and can play a role in substrate specificity. Motivated by the importance of channel identification in macromolecules, we developed the MolAxis server. MolAxis implements state-of-the-art, accurate computational-geometry techniques that reduce the dimensions of the channel finding problem, rendering the algorithm extremely efficient. Given a protein or nucleic acid structure in the PDB format, the server outputs all possible channels that connect buried cavities to the outside of the protein or points to the main channel in TM proteins. For each channel, the gating residues and the narrowest radius termed ‘bottleneck’ are also given along with a full list of the lining residues and the channel surface in a 3D graphical representation. The users can manipulate advanced parameters and direct the channel search according to their needs. MolAxis is available as a web server or as a stand-alone program at http://bioinfo3d.cs.tau.ac.il/MolAxis

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration >= 5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). Methodology/Principal Findings: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. Conclusions: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin

A multinuclear 1H, 13C and 11B solid-state MAS NMR study of 16- and 18-electron organometallic ruthenium and osmium carborane complexes

YesThe first 1H, 13C, 31P and 11B solid state MAS NMR studies of electron- deficient carborane-containing ruthenium and osmium complexes [Ru/Os(p-cym)(1,2-dicarba-closo-dodecaborane-1,2- dithiolate)] are reported. The MAS NMR data from these 16-electron complexes are compared to those of free carborane-ligand and an 18-electron triphenylphosphine ruthenium adduct, and reveal clear spectral differences between 16- and 18-electron organometallic carborane systems in the solid state.We thank the Swiss National Science Foundation (grant no. PA00P2-145308 to NPEB), the ERC (grant no. 247450 to PJS), EPSRC (grant no. EP/F034210/1) and EC COST Action CM1105 for support. JVH thanks EPSRC and the University of Warwick for partial funding of the solid state NMR infrastructure at Warwick, and acknowledges additional support obtained through Birmingham Science City: Innovative Uses for Advanced Materials in the Modern World (West Midlands Centre for Advanced Materials Project 2), with support from Advantage West Midlands (AWM) and partial funding by the European Regional Development Fund (ERDF)

Urinary Collagen Fragments Are Significantly Altered in Diabetes: A Link to Pathophysiology

Background: The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). Methodology/Principal Findings: Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92-95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81-94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81-88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. Conclusions/Significance: These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling

Structure and Ionic Conductivity in the Mixed-Network Former Chalcogenide Glass System [Na2S]2/3[(B2S3)x(P2S5)1–x]1/3

Glasses in the system [Na2S]2/3[(B2S3)x(P2S5)1–x]1/3 (0.0 ≤ x ≤ 1.0) were prepared by the melt quenching technique, and their properties were characterized by thermal analysis and impedance spectroscopy. Their atomic-level structures were comprehensively characterized by Raman spectroscopy and 11B, 31P, and 23Na high resolution solid state magic-angle spinning (MAS) NMR techniques. 31P MAS NMR peak assignments were made by the presence or absence of homonuclear indirect 31P–31P spin–spin interactions as detected using homonuclear J-resolved and refocused INADEQUATE techniques. The extent of B–S–P connectivity in the glassy network was quantified by 31P{11B} and 11B{31P} rotational echo double resonance spectroscopy. The results clearly illustrate that the network modifier alkali sulfide, Na2S, is not proportionally shared between the two network former components, B and P. Rather, the thiophosphate (P) component tends to attract a larger concentration of network modifier species than predicted by the bulk composition, and this results in the conversion of P2S74–, pyrothiophosphate, Na/P = 2:1, units into PS43–, orthothiophosphate, Na/P = 3:1, groups. Charge balance is maintained by increasing the net degree of polymerization of the thioborate (B) units through the formation of covalent bridging sulfur (BS) units, B–S–B. Detailed inspection of the 11B MAS NMR spectra reveals that multiple thioborate units are formed, ranging from neutral BS3/2 groups all the way to the fully depolymerized orthothioborate (BS33–) species. On the basis of these results, a comprehensive and quantitative structural model is developed for these glasses, on the basis of which the compositional trends in the glass transition temperatures (Tg) and ionic conductivities can be rationalized. Up to x = 0.4, the dominant process can be described in a simplified way by the net reaction equation P1 + B1 P0 + B4, where the superscripts denote the number of BS atoms for the respective network former species. Above x = 0.4, all of the thiophosphate units are of the P0 type and both pyro- (B1) and orthothioborate (B0) species make increasing contributions to the network structure with increasing x. In sharp contrast to the situation in sodium borophosphate glasses, four-coordinated thioborate species are generally less abundant and heteroatomic B–S–P linkages appear to not exist. On the basis of this structural information, compositional trends in the ionic conductivities are discussed in relation to the nature of the charge-compensating anionic species and the spatial distribution of the charge carriers

Future Climate Projections in Africa: Where Are We Headed?

This paper offers an overview of how climate change is already affecting farmers across eastern and southern Africa, and how it will continue to affect them in the future. The rising temperatures and increased rainfall variability associated with climate change are undermining the livelihoods and food security of Africa’s farmers, most of whom work at a subsistence level and also face problems of poverty, inadequate infrastructure and poor governance. To address these problems, governments and development organizations have promoted climate-smart agriculture (CSA). These projects, however, have been constrained by inadequate data and predictions regarding future climate change. In particular, farmers in Africa need better projections of the climate hazards for specific regions. Historical weather data at the local level contains many gaps, and the continuing collection of such data could be much improved. Strengthening the database of observed weather is critical to understanding the changes that have occurred already, to project future changes, and to plan appropriately to address them. Once collected and analyzed, climate data must be communicated in ways that help decision-makers understand climate impacts. Good tools are available—such as ClimateWizard.org and Servir ClimateServ—but practitioners at the local level must have the access and training to use them. Even in places where projections are uncertain, steps can be taken now to implement CSA practices and make farmers more resilient in the face of climate change