Anti-HSV Tag polyclonal antibody

Essential oils are complex mixtures of strongly active compounds, very volatile and sensitive to light, oxygen, moisture and temperature. Loading inside nanocarriers can be a strategy to increase their stability and successfully use them in therapy. In the present study, a commercialMelissa officinalisL. (Lamiaceae) essential oil (MEO) was analyzed by gas chromatography-mass spectrometry, loaded inside glycerosomes (MEO-GS) and evaluated for its anti-herpetic activity against HSV type 1. MEO-GS analyses were prepared by the thin layer evaporation method and they were characterized by light scattering techniques, determining average diameter, polydispersity index and zeta-potential. By transmission electron microscopy, MEO-GS appeared as small nano-sized vesicles with a spherical shape. MEO encapsulation efficiency inside glycerosomes, in terms of citral and beta-caryophyllene, was found to be ca. 63% and 76% respectively, and MEO release from glycerosomes, performed by dialysis bag method, resulted in less than 10% within 24h. In addition, MEO-GS had high chemical and physical stability during 4 months of storage. Finally, MEO-GS were very active in inhibiting HSV type 1 infection of mammalian cells in vitro, without producing cytotoxic effects. Thus, MEO-GS could be a promising tool in order to provide a suitable anti-herpetic formulation.

Autoencoders (AEs) have been applied in several applications such as anomaly detectors and object recognition systems. However, although the recent neural networks have relatively high accuracy but sometimes false detection may occur. This paper introduces AE as an anomaly detector. The proposed AE is trained using both normal and anomalous data based on convolutional neural network with three different color models Hue Saturation Value (HSV), Red Green Blue (RGB), and our own model (TUV). As a result, the trained AE reconstruct the normal images without change, whereas the anomalous image would be reconstructed reversely. The training and testing of the AE in case of RGB, HSV, and TUV color models were demonstrated and Cifar-10 dataset had been used for the evaluation process. It can be noticed that HSV color model has been more effective and achievable as an anomaly detector rather than other color models based on Z- and F-test analyses. (C) 2020 The Authors. Published by Atlantis Press SARL.