UKIRT Widefield Infrared Survey for Fe+

The United Kingdom Infrared Telescope (UKIRT)Widefield Infrared Survey for Fe+ (UWIFE) is a 180 deg2 imaging survey of the first Galactic quadrant (7° < l < 62° |b| <1°.5) that uses a narrow-band filter centred on the [Fe II] 1.644-μm emission line. The [Fe II] 1.644-μm emission is a good tracer of dense, shock-excited gas, and the survey will probe violent environments around stars: star-forming regions, evolved stars, and supernova remnants, among others. The UWIFE survey is designed to complement the existing UKIRTW idefield Infrared Survey for H2 (UWISH2). The survey will also complement existing broad-band surveys. The observed images have a nominal 5Ï? detection limit of 18.7 mag for point sources, with a median seeing of 0.83 arcsec. For extended sources, we estimate a surface brightness limit of 8.1 Ã? 10-20 W m-2 arcsec-2. In this paper, we present an overview and some preliminary results of this survey. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society

Moxifloxacin: Clinically compatible contrast agent for multiphoton imaging

Multiphoton microscopy (MPM) is a nonlinear fluorescence microscopic technique widely used for cellular imaging of thick tissues and live animals in biological studies. However, MPM application to human tissues is limited by weak endogenous fluorescence in tissue and cytotoxicity of exogenous probes. Herein, we describe the applications of moxifloxacin, an FDA-approved antibiotic, as a cell-labeling agent for MPM. Moxifloxacin has bright intrinsic multiphoton fluorescence, good tissue penetration and high intracellular concentration. MPM with moxifloxacin was demonstrated in various cell lines, and animal tissues of cornea, skin, small intestine and bladder. Clinical application is promising since imaging based on moxifloxacin labeling could be 10 times faster than imaging based on endogenous fluorescence.David H. Koch Institute for Integrative Cancer Research at MIT (Bridge Initiative

Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

This paper presents a methodology for the size optimization of a stand-alone hybrid PV/wind/diesel/battery system while considering the following factors: total annual cost (TAC), loss of power supply probability (LPSP), and the fuel cost of the diesel generator required by the user. A new optimization algorithm and an object function (including a penalty method) are also proposed; these assist with designing the best structure for a hybrid system satisfying the constraints. In hybrid energy system sources such as photovoltaic (PV), wind, diesel, and energy storage devices are connected as an electrical load supply. Because the power produced by PV and wind turbine sources is dependent on the variation of the resources (sun and wind) and the load demand fluctuates, such a hybrid system must be able to satisfy the load requirements at any time and store the excess energy for use in deficit conditions. Therefore, reliability and cost are the two main criteria when designing a stand-alone hybrid system. Moreover, the operation of a diesel generator is important to achieve greater reliability. In this paper, TAC, LPSP, and the fuel cost of the diesel generator are considered as the objective variables and a hybrid teaching–learning-based optimization algorithm is proposed and used to choose the best structure of a stand-alone hybrid PV/wind/diesel/battery system. Simulation results from MATLAB support the effectiveness of the proposed method and confirm that it is more efficient than conventional methods

Can a semi-quantitative method replace the current quantitative method for the annual screening of microalbuminuria in patients with diabetes? Diagnostic accuracy and cost-saving analysis considering the potential health burden.

OBJECTIVES:Diabetes is a global epidemic, and the high cost of annually and quantitatively measuring urine albumin excretion using the turbidimetric immunoassay is challenging. We aimed to determine whether a semi-quantitative urinary albumin-creatinine ratio test could be used as a screening tool for microalbuminuria in diabetic patients. METHODS:We assessed the diagnostic accuracy of the semi-quantitative method. The costs of false results in the semi-quantitative method were calculated based on the annual probability of disease progression analyzed through a systematic literature review and meta-analysis. The pooled long-term cost-saving effect of the semi-quantitative method compared with the quantitative test was assessed using a Markov model simulating a long-term clinical setting. Diagnostic accuracy and the cost-saving effect were also validated in an independent external cohort. RESULTS:Compared with the quantitative test, the semi-quantitative method had sensitivities of 93.5% and 81.3% and specificities of 61.4% and 63.1% in the overall sample of diabetic patients (n = 1,881) and in diabetic patients with eGFR ≥60 ml/min/1.73 m2 and a negative dipstick test (n = 1,110), respectively. After adjusting for direct and indirect medical costs, including the risk of disease progression, which was adjusted by the meta-analyzed hazard ratio for clinical outcomes, it was determined that using the semi-quantitative method could save 439.4 USD per person for 10 years. Even after adjusting the result to the external validation cohort, 339.6 USD could be saved for one diabetic patient for 10 years. CONCLUSIONS:The semi-quantitative method could be an appropriate screening tool for albuminuria in diabetic patients. Moreover, it can minimize the testing time and inconvenience and significantly reduce national health costs

Comprehensive Analysis of Mutation-Based and Expressed Genes-Based Pathways in Head and Neck Squamous Cell Carcinoma

Over- or under-expression of mRNA results from genetic alterations. Comprehensive pathway analyses based on mRNA expression are as important as single gene level mutations. This study aimed to compare the mutation- and mRNA expression-based signaling pathways in head and neck squamous cell carcinoma (HNSCC) and to match these with potential drug or druggable pathways. Altogether, 93 recurrent/metastatic HNSCC patients were enrolled. We performed targeted gene sequencing using Illumina HiSeq-2500 for NGS, and nanostring nCounter® for mRNA expression; mRNA expression was classified into over- or under-expression groups based on the expression. We investigated mutational and nanostring data using the CBSJukebox® system, which is a big-data driven platform to analyze druggable pathways, genes, and protein-protein interaction. We calculated a Treatment Benefit Prediction Score (TBPS) to identify suitable drugs. By mapping the high score interaction genes to identify druggable pathways, we found highly related signaling pathways with mutations. Based on the mRNA expression and interaction gene scoring model, several pathways were found to be associated with over- and under-expression. Mutation-based pathways were associated with mRNA under-expressed genes-based pathways. These results suggest that HNSCCs are mainly caused by the loss-of-function mutations. TBPS found several matching drugs such as immune checkpoint inhibitors, EGFR inhibitors, and FGFR inhibitors