Expression of Heterologous OsDHAR Gene Improves Glutathione (GSH)-Dependent Antioxidant System and Maintenance of Cellular Redox Status in Synechococcus elongatus PCC 7942.

An excess of reactive oxygen species (ROS) can cause severe oxidative damage to cellular components in photosynthetic cells. Antioxidant systems, such as the glutathione (GSH) pools, regulate redox status in cells to guard against such damage. Dehydroascorbate reductase (DHAR, EC 1.8.5.1) catalyzes the glutathione-dependent reduction of oxidized ascorbate (dehydroascorbate) and contains a redox active site and glutathione binding-site. The DHAR gene is important in biological and abiotic stress responses involving reduction of the oxidative damage caused by ROS. In this study, transgenic Synechococcus elongatus PCC 7942 (TA) was constructed by cloning the Oryza sativa L. japonica DHAR (OsDHAR) gene controlled by an isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible promoter (Ptrc) into the cyanobacterium to study the functional activities of OsDHAR under oxidative stress caused by hydrogen peroxide exposure. OsDHAR expression increased the growth of S. elongatus PCC 7942 under oxidative stress by reducing the levels of hydroperoxides and malondialdehyde (MDA) and mitigating the loss of chlorophyll. DHAR and glutathione S-transferase activity were higher than in the wild-type S. elongatus PCC 7942 (WT). Additionally, overexpression of OsDHAR in S. elongatus PCC 7942 greatly increased the glutathione (GSH)/glutathione disulfide (GSSG) ratio in the presence or absence of hydrogen peroxide. These results strongly suggest that DHAR attenuates deleterious oxidative effects via the glutathione (GSH)-dependent antioxidant system in cyanobacterial cells. The expression of heterologous OsDHAR in S. elongatus PCC 7942 protected cells from oxidative damage through a GSH-dependent antioxidant system via GSH-dependent reactions at the redox active site and GSH binding site residues during oxidative stress

An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

The landscape freeze–thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979–2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow- and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow- and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts, and climate anomalies from longer-term trends extending over multiple decades. The dataset is freely available online (doi:10.5067/MEASURES/CRYOSPHERE/nsidc-0477.003)

Loss of the tumor suppressor, Tp53, enhances the androgen receptor-mediated oncogenic transformation and tumor development in the mouse prostate.

Recent genome analysis of human prostate cancers demonstrated that both AR gene amplification and TP53 mutation are among the most frequently observed alterations in advanced prostate cancer. However, the biological role of these dual genetic alterations in prostate tumorigenesis is largely unknown. In addition, there are no biologically relevant models that can be used to assess the molecular mechanisms for these genetic abnormalities. Here, we report a novel mouse model, in which elevated transgenic AR expression and Trp53 deletion occur simultaneously in mouse prostatic epithelium to mimic human prostate cancer cells. These compound mice developed an earlier onset of high-grade prostatic intraepithelial neoplasia and accelerated prostate tumors in comparison with mice harboring only the AR transgene. Histological analysis showed prostatic sarcomatoid and basaloid carcinomas with massive squamous differentiation in the above compound mice. RNA-sequencing analyses identified a robust enrichment of the signature genes for human prostatic basal cell carcinomas in the above prostate tumors. Master regulator analysis revealed SOX2 as a transcriptional regulator in prostatic basal cell tumors. Elevated expression of SOX2 and its downstream target genes were detected in prostatic tumors of the compound mice. Chromatin immunoprecipitation analyses implicate a coregulatory role of AR and SOX2 in the expression of prostatic basal cell signature genes. Our data demonstrate a critical role of SOX2 in prostate tumorigenesis and provide mechanistic insight into prostate tumor aggressiveness and progression mediated by aberrant AR and p53 signaling pathways

GPU-based Acceleration of Symbol Timng Recovery

This paper presents a novel implementation of graphics processing unit (GPU) based symbol timing recovery using polyphase interpolators to detect symbol timing error. Symbol timing recovery is a compute intensive procedure that detects and corrects the timing error in a coherent receiver. We provide optimal sample-time timing recovery using a maximum likelihood (ML) estimator to minimize the timing error. This is an iterative and adaptive system that relies on feedback, therefore, we present an accelerated implementation design by using a GPU for timing error detection (TED), enabling fast error detection by exploiting the 2D filter structure found in the polyphase interpolator. We present this hybrid/ heterogeneous CPU and GPU architecture by computing a low complexity and low noise matched filter (MF) while simultaneously performing TED. We then compare the performance of the CPU vs. GPU based timing recovery for different interpolation rates to minimize the error and improve the detection by up to a factor of 35. We further improve the process by utilizing GPU optimization and performing block processing to improve the throughput even more, all while maintaining the lowest possible sampling rate.Laboratory for Telecommunications SciencesNational Science Foundation (NSF

A mathematical model for cell cycle-specific cancer virotherapy

Oncolytic viruses preferentially infect and replicate in cancerous cells, leading to elimination of tumour populations, while sparing most healthy cells. Here, we study the cell cycle-specific activity of viruses such as vesicular stomatitis virus (VSV). In spite of its capacity as a robust cytolytic agent,VSVcannot effectively attack certain tumour cell types during the quiescent, or resting, phase of the cell cycle. In an effort to understand the interplay between the time course of the cell cycle and the specificity of VSV, we develop a mathematical model for cycle-specific virus therapeutics. We incorporate the minimum biologically required time spent in the non-quiescent cell cycle phases using systems of differential equations with incorporated time delays. Through analysis and simulation of the model, we describe how varying the minimum cycling time and the parameters that govern viral dynamics affect the stability of the cancer-free equilibrium, which represents therapeutic success