The antiherpetic and anti-inflammatory activity of the frog-derived peptide Hylin-a1.

AIM: The high incidence of virus-related infections and the large diffusion of drug-resistant pathogens stimulate the search and identification of new antiviral agents with a broad spectrum of action. Antivirals can be designed to act on a single target by interfering with a specific step in the viral lifecycle. On the contrary, antiviral peptides (AVPs) are known for acting on a wide range of viruses, with a diversified mechanism of action targeting virus and/or host cell. In the present study, we evaluated the antiviral potential of the peptide Hylin-a1 secreted by the frog Hypsiobas albopunctatus against members of the Herpesviridae family. METHODS AND RESULTS: The inhibitory capacity of the peptide was evaluated in vitro by plaque assays in order to understand the possible mechanism of action. The results were also confirmed by Real-Time PCR and Western blot evaluating the expression of viral genes. Hylin-a1 acts to block the herpetic infection interfering at the early stages of both herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infection. Its mechanism is mainly directed on the membrane, probably by damaging the viral envelope. The same effect was also observed against HSV-1 strains resistant to acyclovir. CONCLUSIONS: The data presented in this study, such as the increased activity of the peptide when combined to acyclovir, a weak hemolytic profile, an anti-inflammatory effect, and a tolerable half-life in serum, indicates Hylin-a1 as a novel antiherpetic molecule with promising potential in the clinical setting.

Fe3O4/SiO2/TiO2 nanoparticles for photocatalytic degradation of 2-chlorophenol in simulated wastewater.

Photocatalysis has emerged as an advance and environmental-friendly process for breakdown of organic contaminants in wastewater. This work reports facile synthesis and characterization of stable magnetic core-shell-shell Fe3O4/SiO2/TiO2 nanoparticles and their effectiveness for photocatalysis. The surface morphology, crystal structure, and chemical properties of the photocatalyst were characterized by using scanning electron microscope (SEM), energy-dispersive X-ray (EDX), X-ray diffraction (XRD), and nitrogen physisorption. Stability of synthesized nanoparticles in aqueous medium was tested by leaching test. The photocatalytic degradation of 2-chlorophenol was investigated and reaction parameters for best catalyst performance were optimized. Catalyst dose of 0.5 g/L under optimized conditions produced complete degradation of 25 mg/L 2-chlorophenol (2-CP) within 130 min of 100-W ultraviolet (UV) irradiation while 97.2 % degradation of 50 mg/L 2-CP was achieved within 3 h. The rate of photocatalytic degradation was determined by considering pseudo first-order kinetics and Hugul's kinetic equations. The Hugul's kinetics was found to provide a better interpretation of the experimental results than the generally adopted pseudo first-order reaction kinetics.

Multiresolution spot detection by means of entropy thresholding.

Many imaging applications deal with the detection of small targets or spots embedded within an inhomogeneous background. We present a method that accomplishes a multiresolution detection on the wavelet-transformed image. The targets are separated from the background by the exploitation of Renyi's information, which is evaluated at the different decomposition levels of the wavelet transform. The scale-dependent candidate detections are successively combined by means of majority voting for final detection. Connections with results provided in different fields such as multifractal analysis, generalized information measures in scale-space, and cross-entropy analysis in fine-to-coarse transformations are discussed. Detection performance is investigated through an example from medical image analysis.

Computer aided detection of microcalcifications in digital mammograms.

Microcalcification detection is widely used for early diagnosis of breast cancer. Nevertheless, mammogram visual analysis is a complex task for expert radiologists. In this paper, we present a new method for computer aided detection of microcalcifications in digital mammograms. The detection is performed on the wavelet transformed image. The calcifications are separated from the background by exploiting the evaluation of Renyi's information at the different decomposition levels of the wavelet transform. Experiments are performed on a standard and publicly available dataset and the results are evaluated with respect to recent achievements reported in the literature.