Fluconazole resistance Candida albicans in females with recurrent vaginitis and Pir1 overexpression

Background: Some genes may be associated with Candida albicans resistance to azoles. Pir1 gene is described as responsible to induce resistance in C. albicans. Objectives: The current study aimed to find the relationship between fluconazole resistance and Pir1 protein (Pir1p) overexpression in the females with recurrent C. albicans vaginitis requiring longer fluconazole therapy. Patients and Methods: A total of 52l vaginal samples were obtained from the females with C. albicans vaginitis. The azole susceptibility phenotype was determined according to the Clinical Laboratory for Standards Institute (CLSI) protocol for disk diffusion method and inhibition zone for fluconazole. Expression of pir1 gene and fluconazole -resistance were evaluated using polymerase chain reaction (PCR) in C. albicans. Results: In the 52 isolates, 49 (94) were resistant to fluconazole. Overexpression of Pir1 gene was detected in 47 (96) fluconazole-resistant C. albicans isolates. Conclusions: The findings show fluconazole -resistance in C. albicans isolates with overexpression of Pir1p. © 2015, Ahvaz Jundishapur University of Medical Sciences

Deep Burst Denoising

Noise is an inherent issue of low-light image capture, one which is exacerbated on mobile devices due to their narrow apertures and small sensors. One strategy for mitigating noise in a low-light situation is to increase the shutter time of the camera, thus allowing each photosite to integrate more light and decrease noise variance. However, there are two downsides of long exposures: (a) bright regions can exceed the sensor range, and (b) camera and scene motion will result in blurred images. Another way of gathering more light is to capture multiple short (thus noisy) frames in a "burst" and intelligently integrate the content, thus avoiding the above downsides. In this paper, we use the burst-capture strategy and implement the intelligent integration via a recurrent fully convolutional deep neural net (CNN). We build our novel, multiframe architecture to be a simple addition to any single frame denoising model, and design to handle an arbitrary number of noisy input frames. We show that it achieves state of the art denoising results on our burst dataset, improving on the best published multi-frame techniques, such as VBM4D and FlexISP. Finally, we explore other applications of image enhancement by integrating content from multiple frames and demonstrate that our DNN architecture generalizes well to image super-resolution

Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to quantify the concentration of annual rainfall and the number of dry months and to build a monsoon dimensionless seasonality index (DSI). The RE is projected to increase, with high inter-model agreement over Mediterranean-type regions---southern Europe, northern Africa and southern Australia---and areas of South and Central America, implying an increase in the number of dry days up to 1Â month by the end of the twenty-first century. Positive RE changes are also projected over the monsoon regions of southern Africa and North America, South America. These trends are consistent with a shortening of the wet season associated with a more prolonged pre-monsoonal dry period. The extent of the global monsoon region, characterized by large DSI, is projected to remain substantially unaltered. Centroid analysis shows that most of CMIP5 projections suggest that the monsoonal annual rainfall distribution is expected to change from early to late in the course of the hydrological year by the end of the twenty-first century and particularly after year 2050. This trend is particularly evident over northern Africa, southern Africa and western Mexico, where more than 90% of the models project a delay of the rainfall centroid from a few days up to 2Â weeks. Over the remaining monsoonal regions, there is little inter-model agreement in terms of centroid changes

Preliminary report of a nationwide case-control study for identifying risk factors of tuberculosis following renal transplantation

Background. Tuberculosis (TB) is an important infection encountered posttransplantation, especially among patients in developing countries, where there are high incidences of morbidity and mortality. Materials and Methods. One hundred and twenty subjects (1) from 15 major kidney transplantation centers in Iran from 1984 to 2003 were compared with 440 controls who were matched for operative time, treatment center, and surgical team. Results. Mean ages of research subjects and controls were 38.6 and 36.6 years (P = .04), respectively. The mean duration of pretransplantation hemodialysis was 29 months (range, 2 to 192 months) in research subjects and 20 months (range, 1 to 180 months) in controls (P = .003). Positive past history of tuberculosis was detected in 4 (3.3) research subjects and in 7 (1.5) controls (P = .2). Fifty-two research subjects (43.3) and 241 controls (54.8) had pretransplantation purified protein derivative of tuberculin less than 5 mm (P = .02). Mean dosages of initial and maintenance immunosuppressive drugs in research subjects and in controls were not significantly different. Sixty research subjects (50) and 152 controls (34.5) had rejection prior to diagnosis of TB (P = .03). Conclusion. To our knowledge, this is the first study that demonstrates an increased risk of posttransplant TB by prolonged duration of pretransplant hemodialysis and number of posttransplant rejection episodes. Further study is needed to clarify these findings specifically with respect to various immunosuppressive regimens. © 2005 by Elsevier Inc. All rights reserved

Building Performance Modeling in Non-simplified Architectural Design Procedural and cognitive challenges in education

The building technology class ìParametric Designî simultaneously teaches thermal and daylight performance simulation to novice users, usually Master of Architecture students. Own buildings are created, analysed and geometrically modified during the design process, resulting in structures that are energetically pre-optimized. It is shown that energy demand and daylight utilization can be signifi cantly improved while taking into account formal considerations. Departing from a design process model that gives preference to either engineering or design thinking, multi-modal decision-making is diagnosed to be mediated by hybrid or multivalent representations, necessitating a shift in how inter-domain design knowledge flows might be understood. Opposed to purely linear or iterative process assumptions, a fluent state model of interconnected domains of analytic inquiry is proposed