Relation between DNA damage measured by comet assay and OGG1 Ser326Cys polymorphism in antineoplastic drugs biomonitoring

Antineoplastic drugs are hazardous chemical agents used mostly in the treatment of patients with cancer, however health professionals that handle and administer these drugs can become exposed and develop DNA damage. Comet assay is a standard method for assessing DNA damage in human biomonitoring and, combined with formamidopyrimidine DNA glycosylase (FPG) enzyme, it specifically detects DNA oxidative damage. The aim of this study was to investigate genotoxic effects in workers occupationally exposed to cytostatics (n = 46), as compared to a control group with no exposure (n = 46) at two Portuguese hospitals, by means of the alkaline comet assay. The potential of the OGG1 Ser326Cys polymorphism as a susceptibility biomarker was also investigated. Exposure was evaluated by investigating the contamination of surfaces and genotoxic assessment was done by alkaline comet assay in peripheral blood lymphocytes. OGG1 Ser326Cys (rs1052133) polymorphism was studied by Real Time PCR. As for exposure assessment, there were 121 (37%) positive samples out of a total of 327 samples analysed from both hospitals. No statistically significant differences (Mann-Whitney test, p > 0.05) were found between subjects with and without exposure, regarding DNA damage and oxidative DNA damage, nevertheless the exposed group exhibited higher values. Moreover, there was no consistent trend regarding the variation of both biomarkers as assessed by comet assay with OGG1 polymorphism. Our study was not statistically significant regarding occupational exposure to antineoplastic drugs and genetic damage assessed by comet assay. However, health professionals should be monitored for risk behaviour, in order to ensure that safety measures are applied and protection devices are used correctly.

Real-time rheology of actively growing bacteria

The population growth of a Staphylococcus aureus culture, an active colloidal system of spherical cells, was followed by rheological measurements, under steady-state and oscillatory shear flows. We observed a rich viscoelastic behavior as a consequence of the bacteria activity, namely, of their multiplication and density-dependent aggregation properties. In the early stages of growth (lag and exponential phases), the viscosity increases by about a factor of 20, presenting several drops and full recoveries. This allows us to evoke the existence of a percolation phenomenon. Remarkably, as the bacteria reach their late phase of development, in which the population stabilizes, the viscosity returns close to its initial value. Most probably, this is caused by a change in the bacteria physiological activity and in particular, by the decrease of their adhesion properties. The viscous and elastic moduli exhibit power-law behaviors compatible with the "soft glassy materials" model, whose exponents are dependent on the bacteria growth stage. DOI: 10.1103/PhysRevE.87.030701.

ECG-based biometrics: A real time classification approach

Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer.

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.