Sectoral R&D intensity and exchange rate volatility: A panel study on economies of the OECD

A recent literature has pointed at potential negative effects of exchange rate volatility on innovation. In this paper, we propose that there may be a direct effect as well as an indirect effect via export activity. We test these hypotheses for sectoral R&D intensities using OECD panel data for manufacturing and services sectors for 14 OECD economies and the years 1987 - 2003. We find that the direct negative effect of volatility is pronounced in manufacturing sector but is dominated by the indirect effect via the export channel. Services do not face any effects of volatility on R&D intensities. While it is not clear which channel dominates our results confirm that there is a negative volatility affect related to openness on a sectoral level

Sectoral R&D intensity and exchange rate volatility: a panel study for OECD countries

A recent literature has pointed at potential negative effects of exchange rate volatility on innovation. In this paper, we propose that there may be a direct effect as well as an indirect effect via export activity. We test these hypotheses for sectoral R&D intensities using OECD panel data for manufacturing and services sectors for 14 OECD economies and the years 1987 - 2003. We find that the direct negative effect of volatility is pronounced in manufacturing sector but is dominated by the indirect effect via the export channel. Services do not face any effects of volatility on R&D intensities. While it is not clear which channel dominates our results confirm that there is a negative volatility affect related to openness on a sectoral level

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance

Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21

Meta-AnalysisThis is the final version of the article. Available from the American Diabetes Association via the DOI in this record.Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes-associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻⁹). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.The major funding for this work comes from Council for Scientific and Industrial Research, Government of India, in the form of the grant “Diabetes mellitus—New drug discovery R&D, molecular mechanisms, and genetic and epidemiological factors” (NWP0032-19). R.T. received a postdoctoral fellowship from the Fogarty International Center and the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (D43-HD-065249)

Development of Dissolution Test Method for Drotaverine Hydrochloride/Mefenamic Acid Combination Using Derivative Spectrophotometry

Purpose: To develop and validate a dissolution test method for tablets containing 80 mg of drotaverine hydrochloride (DRT) and 250 mg of mefenamic acid (MEF).Methods: Sink conditions, drug stability and specificity in different dissolution media were tested to optimize a dissolution test method using a USP paddle type dissolution test apparatus set at a speed of50 rpm. The dissolution medium consisted of 900 ml of phosphate buffer (pH 6.8) containing 0.25% w/v cetrimide at 37 ± 0.5 oC and 45 min time-point. To determine both drugs simultaneously, a first derivative UV spectrophotometric method was developed and validated. Drug release was analyzed by first derivative UV method at 253.8 nm and 304 nm for DRT and MEF respectively. The dissolution method was validated as per ICH guidelines.Results: The two brands each showed 98% of drug release for both drugs when the developed dissolution method was used. The regression plot was linear in the concentration range 4 - 24 ìg/mL for each of the drugs and regression coefficient (r2) was greater than 0.999 for each drug. Relativestandard deviation (% RSD) for precision and accuracy of proposed method was &lt; 2.Conclusion: The proposed dissolution method is simple, cost-effective, precise, accurate and specific. It can be successfully employed in routine quality control of DRT and MEF combination tablets.Keywords: Drotaverine hydrochloride, Mefenamic acid, First derivative spectrophotometry, Dissolution, Validatio

Mathematical models for immunology:current state of the art and future research directions

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years

Implementing the ‘Frozen Potential’ Approach on ADEPT to Analyze Thin Film Solar Cells

Thin film solar cells have higher absorption coefficients than traditional Silicon solar cells. This means that lesser material is required to produce the same power output for a given intensity of solar illumination. As a result, they are less expensive, easier to install and have a wider range of applications. Analyzing the performance of cells requires separating the current into the photocurrent and the injection current based on the ‘Superposition Principle’. For thin film solar cells, this cannot be done using the conventional method. This is because these components are interdependent, and so modeling one’s behavior requires understanding the other. We address this issue by implementing a new modeling approach. This novel ‘Frozen Potential’ Approach separates the photocurrent and injection current from the total current. The currents are then plotted individually. This method is implemented on a rigorous simulation tool called ADEPT 2.0, which is readily available on nanoHUB.org – the premier platform for research and simulation in nanotechnology. Equipped with this new modelling approach, a useful framework is provided for ADEPT 2.0 by tying in a traditional understanding of solar cells to a new class of materials, geometries and illumination profiles relevant for the solar cell community

Urinary Exosomal microRNA-451-5p Is a Potential Early Biomarker of Diabetic Nephropathy in Rats

Non-invasive renal signatures can help in serial monitoring of diabetic patients. We tested whether urinary exosomal (UE) microRNA (miR) analysis could non-invasively predict renal pathology in diabetic rats during the course of diabetes. Diabetes mellitus (DM) was induced in male Wistar rats by a single intraperitoneal injection of streptozotocin (STZ, 50 mg/kg body weight). Non-diabetic control (CTRL) rats were injected with vehicle. Insulin (INS) treatment (5U/d, s.c.) was provided to 50% of the DM rats. Urine samples were collected at weeks 3, 6, and 9 following injections and UE prepared. An increase in miR-451-5p and miR-16, observed by pilot small RNA sequencing of UE RNA, was confirmed by quantitative real-time polymerase chain reaction (qPCR) and selected for further study. Subsets of rats were euthanized after 3, 6, and 9 weeks of diabetes for renal pathology analysis, including determination of the tubulointerstitial fibrotic index (TFI) and glomerulosclerotic index (GI) scores. qPCR showed a substantial rise in miR-451-5p in UE from DM rats during thecourse of diabetes, with a significant rise (median fold change >1000) between 3 and 6 weeks. Moreover, UE miR-451-5p at 6 weeks predicted urine albumin at 9 weeks (r = 0.76). A delayed but significant rise was also observed for miR-16. In contrast, mean urine albumin only increased 21% between 3 and 6 weeks (non-significant rise), and renal TFI and GI were unchanged till 9 weeks. Renal expression of miR-451-5p and miR-16 (at 10 weeks) did not correlate with urine levels, and moreover, was negatively associated with indices of renal pathology (r�-0.70, p = 0.005 for TFI and r�-0.6, p�0.02 for GI). Overall, a relative elevation in renal miR-451-5p and miR-16 in diabetes appeared protective against diabetes- induced kidney fibrosis; while UE miR-451-5p may hold prognostic value as an earlyand sensitive non-invasive indicator of renal diseas

Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease

<p>Abstract</p> <p>Background</p> <p>Systems biology holds promise as a new approach to drug target identification and drug discovery against neglected tropical diseases. Genome-scale metabolic reconstructions, assembled from annotated genomes and a vast array of bioinformatics/biochemical resources, provide a framework for the interrogation of human pathogens and serve as a platform for generation of future experimental hypotheses. In this article, with the application of selection criteria for both <it>Leishmania major </it>targets (e.g. <it>in silico </it>gene lethality) and drugs (e.g. toxicity), a method (MetDP) to rationally focus on a subset of low-toxic Food and Drug Administration (FDA)-approved drugs is introduced.</p> <p>Results</p> <p>This metabolic network-driven approach identified 15 <it>L. major </it>genes as high-priority targets, 8 high-priority synthetic lethal targets, and 254 FDA-approved drugs. Results were compared to previous literature findings and existing high-throughput screens. Halofantrine, an antimalarial agent that was prioritized using MetDP, showed noticeable antileishmanial activity when experimentally evaluated <it>in vitro </it>against <it>L. major </it>promastigotes. Furthermore, synthetic lethality predictions also aided in the prediction of superadditive drug combinations. For proof-of-concept, double-drug combinations were evaluated <it>in vitro </it>against <it>L. major </it>and four combinations involving the drug disulfiram that showed superadditivity are presented.</p> <p>Conclusions</p> <p>A direct metabolic network-driven method that incorporates single gene essentiality and synthetic lethality predictions is proposed that generates a set of high-priority <it>L. major </it>targets, which are in turn associated with a select number of FDA-approved drugs that are candidate antileishmanials. Additionally, selection of high-priority double-drug combinations might provide for an attractive and alternative avenue for drug discovery against leishmaniasis.</p