The durability of oral diabetic medications: Time to A1c baseline and a review of common oral medications used by the primary care provider.

Introduction:Cost of generic medications has risen more in the past few years than any other time in history. While medical insurance covers much of these costs, health care professionals can better provide medications that have the longest duration of action when compared to placebo-treated controls. This will save health care costs and improve prescribing accuracy. Methods:Papers in PubMed were identified with keywords placebo. The study must be at least 2 years in length to evaluate the change in A1c over time. The primary endpoint was time to A1c neutrality (return of A1c to baseline at a maximum dose of single oral agent). A medication would be considered at neutrality if the 95% CI crossed baseline. Time to neutrality was averaged for each medication within the class and each summarized for class effect. Results:Effective therapy for the DPP-4 and sulfonylurea classes of medications are 3-4 years as compared to a 5-year time to A1c neutrality for metformin usage. In comparison, the projected time to A1c neutrality was approximately 6-8 years for rosiglitazone and pioglitazone. While only a few studies have been published in the SGLT-2 class of medication, the time to A1c neutrality was also 6-8 years with Canagliflozin and full dosage of Empagliflozin. Conclusion:Metformin appears to have a 5-year duration of effect before the A1c returns to baseline. The sulfonylureas and DPP-4 inhibitors class of medications have one of the shortest durability which ranges between 3.3 to 4.4 years. In contrast, the SGLT-2 class of medication and the TZD class of medications has a projected time to A1c neutrality from 6-8 years. Diabetic duration of therapy as compared to placebo should be listed with those medications tested so the provider can choose wisely

A Novel Global MPP Tracking of Photovoltaic System Based on Whale Optimization Algorithm

To harvest maximum amount of solar energy and to attain higher efficiency, photovoltaic generation (PVG) systems are to be operated at their maximum power point (MPP) under both variable climatic and partial shaded condition (PSC). From literature most of conventional MPP tracking (MPPT) methods are able to guarantee MPP successfully under uniform shading condition but fails to get global MPP as they may trap at local MPP under PSC, which adversely deteriorates the efficiency of Photovoltaic Generation (PVG) system. In this paper a novel MPPT based on Whale Optimization Algorithm (WOA) is proposed to analyze analytic modeling of PV system considering both series and shunt resistances for MPP tracking under PSC. The proposed algorithm is tested on 6S, 3S2P and 2S3P Photovoltaic array configurations for different shading patterns and results are presented. To compare the performance, GWO and PSO MPPT algorithms are also simulated and results are also presented. From the results it is noticed that proposed MPPT method is superior to other MPPT methods with reference to accuracy and tracking speed.Article History: Received July 23rd 2016; Received in revised form September 15th 2016; Accepted October 1st 2016; Available onlineHow to Cite This Article: Kumar, C.H.S and Rao, R.S. (2016) A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm. Int. Journal of Renewable Energy Development, 5(3), 225-232.http://dx.doi.org/10.14710/ijred.5.3.225-23

Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition

Partial shading condition is one of the adverse phenomena which effects the power output of photovoltaic (PV) systems due to inaccurate tracking of global maximum power point. Conventional Maximum Power Point Tracking (MPPT) techniques like Perturb and Observe, Incremental Conductance and Hill Climbing can track the maximum power point effectively under uniform shaded condition, but fails under partial shaded condition. An attractive solution under partial shaded condition is application of meta-heuristic algorithms to operate at global maximum power point. Hence in this paper, an Enhanced Grey Wolf Optimizer (EGWO) based maximum power point tracking algorithm is proposed to track the global maximum power point of PV system under partial shading condition. A Mathematical model of PV system is developed under partial shaded condition using single diode model and EGWO is applied to track global maximum power point. The proposed method is programmed in MATLAB environment and simulations are carried out on 4S and 2S2P PV configurations for dynamically changing shading patterns. The results of the proposed method are analyzed and compared with GWO and PSO algorithms. It is observed that proposed method is effective in tracking global maximum power point with more accuracy in less computation time compared to other methods.Article History: Received June 12nd 2017; Received in revised form August 13rd 2017; Accepted August 15th 2017; Available onlineHow to Cite This Article: Kumar, C.H.S and Rao, R.S. (2017 Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition. Int. Journal of Renewable Energy Development, 6(3), 203-212.https://doi.org/10.14710/ijred.6.3.203-21

Toxic Effects of Silver Ions on Early Developing Zebrafish Embryos Distinguished From Silver Nanoparticles

Currently, effects of nanomaterials and their ions, such as silver nanoparticles (Ag NPs) and silver ions (Ag+), on living organisms are not yet fully understood. One of the vital questions is whether nanomaterials have distinctive effects on living organisms from any other conventional chemicals (e.g., their ions), owing to their unique physicochemical properties. Due to various experimental protocols, studies of this crucial question have been inconclusive, which hinders rational design of effective regulatory guidelines for safely handling NPs. In this study, we chronically exposed early developing zebrafish embryos (cleavage-stage, 2 hours post-fertilization, hpf) to a dilution series of Ag+ (0–1.2 μM) in egg water (1 mM NaCl, solubility of Ag+ = 0.18 μM) until 120 hpf. We systematically investigated effects of Ag+ on developing embryos and compared them with our previous studies of effects of purified Ag NPs on developing embryos. We found the concentration- and time-dependent effects of Ag+ on embryonic development, and only half of the embryos developed normally after being exposed to 0.25 μM (27 μg/L) Ag+ until 120 hpf. As the Ag+ concentration increases, the number of embryos that developed normally decreases, while the number of embryos that became dead increases. The number of abnormally developing embryos increases as the Ag+ concentration increases from 0 to 0.3 μM and then decreases as the concentration increases from 0.3 to 1.2 μM because the number of embryos that became dead increases. The concentration-dependent phenotypes were observed, showing fin fold abnormality, tail and spinal cord flexure, and yolk sac edema at low Ag+ concentrations (≤0.2 μM) and head and eye abnormalities along with fin fold abnormality, tail and spinal cord flexure, and yolk sac edema at high concentrations (≥0.3 μM). Severities of phenotypes and the number of abnormally developing embryos were far less than those observed in Ag NPs. The results also show concentration-dependent effects on heart rates and hatching rates of developing embryos, attributing to the dose-dependent abnormally developing embryos. In summary, the results show that Ag+ and Ag NPs have distinctive toxic effects on early developing embryos, and toxic effects of Ag+ are far less severe than those of Ag NPs, which further demonstrates that the toxicity of Ag NPs toward embryonic development is attributed to the NPs themselves and their unique physicochemical properties but not the release of Ag+ from the Ag NPs

Wasserstein Distributionally Robust Look-Ahead Economic Dispatch

We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy generation subject to uncertain operational constraints. The risk of violating these constraints must be below a given threshold for a family of probability distributions with characteristics similar to observed past data or predictions. We present two data-driven approaches based on two novel mathematical reformulations of this distributionally robust decision problem. The first one is a tractable convex program in which the uncertain constraints are defined via the distributionally robust conditional-value-at-risk. The second one is a scalable robust optimization program that yields an approximate distributionally robust chance-constrained LAED. Numerical experiments on the IEEE 39-bus system with real solar production data and forecasts illustrate the effectiveness of these approaches. We discuss how system operators should tune these techniques in order to seek the desired robustness-performance trade-off and we compare their computational scalability

Increased urinary nitrite, a marker of nitric oxide, in active inflammatory bowel disease.

BACKGROUND: Nitric oxide (NO) production is increased in inflammatory bowel disease (IBD), and measurement of NO metabolites may be useful for monitoring disease activity. AIMS AND OBJECTIVES: To characterise urinary nitrite levels, a stable metabolite of NO, in IBD and to evaluate its potential as a marker of disease activity. METHODS: Twelve-hour urinary nitrites were measured by the microplate assay method in 46 patients with IBD (active; n = 32). Urinary samples from 16 healthy individuals served as controls. RESULTS: Increased levels of urinary nitrites were found in patients with active IBD compared with those with inactive IBD. Twenty-eight out of 32 patients (87.5%) with active IBD had detectable levels of nitrite in their urine as compared with 2/14 (14.3%) patients with inactive IBD. None of the 16 healthy controls had detectable urinary nitrite. Twelve-hour urinary nitrite in active compared with inactive IBD: 5 0.7 versus 0.1+/-0.04 micromol (P < 0.05). There was good correlation between urinary nitrite and some markers of disease activity in IBD such as C-reactive protein and microalbuminuria but not with erythrocyte sedimentation rate. Conclusions: Increased levels of nitrite were detected in urine of patients with active IBD, consistent with increased NO synthesis. This simple assay may be exploited as a potential marker of disease activity in IBD

Deep-Tissue Anatomical Imaging of Mice Using Carbon Nanotube Fluorophores in the Second Near Infrared Window

Fluorescent imaging in the second near infrared window (NIR II, 1-1.4 {\mu}m) holds much promise due to minimal autofluorescence and tissue scattering. Here, using well functionalized biocompatible single-walled carbon nanotubes (SWNTs) as NIR II fluorescent imaging agents, we performed high frame rate video imaging of mice during intravenous injection of SWNTs and investigated the path of SWNTs through the mouse anatomy. We observed in real-time SWNT circulation through the lungs and kidneys several seconds post-injection, and spleen and liver at slightly later time points. Dynamic contrast enhanced imaging through principal component analysis (PCA) was performed and found to greatly increase the anatomical resolution of organs as a function of time post-injection. Importantly, PCA was able to discriminate organs such as the pancreas which could not be resolved from real-time raw images. Tissue phantom studies were performed to compare imaging in the NIR II region to the traditional NIR I biological transparency window (700- 900 nm). Examination of the feature sizes of a common NIR I dye (indocyanine green, ICG) showed a more rapid loss of feature contrast and integrity with increasing feature depth as compared to SWNTs in the NIR II region. The effects of increased scattering in the NIR I versus NIR II region were confirmed by Monte Carlo simulation. In vivo fluorescence imaging in the NIR II region combined with PCA analysis may represent a powerful approach to high resolution optical imaging through deep tissues, useful for a wide range of applications from biomedical research to disease diagnostics.Comment: Proceedings of the National Academy of Sciences (PNAS), 201

Transitional B cell cytokines predict renal allograft outcomes

Early immunological biomarkers that predict rejection and chronic allograft loss are needed to inform preemptive therapy and improve long-term outcomes. Here, we prospectively examined the ratio of interleukin-10 (IL-10) to tumor necrosis factor–α (TNFα) produced by transitional-1 B cells (T1B) 3 months after transplantation as a predictive biomarker for clinical and subclinical renal allograft rejection and subsequent clinical course. In both Training (n = 162) and Internal Validation (n = 82) Sets, the T1B IL-10/TNFα ratio 3 months after transplantation predicted both clinical and subclinical rejection anytime in the first year. The biomarker also predicted subsequent late rejection with a lead time averaging 8 months. Among biomarker high-risk patients, 60% had early rejection, of which 48% recurred later in the first posttransplant year. Among high-risk patients without early rejection, 74% developed rejection later in the first year. In contrast, only 5% of low-risk patients had early and 5% late rejection. The biomarker also predicted rejection in an External Validation Set (n = 95) and in key patient subgroups, confirming generalizability. Biomarker high-risk patients exhibited progressively worse renal function and decreased 5-year graft survival compared to low-risk patients. Treatment of B cells with anti-TNFα in vitro augmented the IL-10/TNFα ratio, restored regulatory activity, and inhibited plasmablast differentiation. To conclude, the T1B IL-10/TNFα ratio was validated as a strong predictive biomarker of renal allograft outcomes and provides a rationale for preemptive therapeutic intervention with TNF blockade