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The World Health Organization (WHO) recognized COVID-19 as the cause of a worldwide pandemic in 2019. The disease is usually contagious, and those who are infected can quickly pass it to others with whom they originate into contact. As a result, observing is an effective way to stop the virus from spreading more. Another disease caused by a pandemic the same as COVID-19 is pneumonia. This is of-ten significantly unsafe for young-sters, individuals over 65 years getting on, and people with health issues or immune systems that are affected. In this paper, we have classified COVID-19 and pneumonia using deep transfer learning. We have used the VGG16 architecture, which was constructed by collecting dataset of COVID-19, Pneumonia and normal X-Ray images. Our main objective is to ease the work of radiologist by providing a Graphical User Interface which takes x-ray as input and can directly distinguish whether or not patient has COVID-19, pneumonia or is normal.

Electrophilic diol epoxide metabolites are involved in the carcinogenicity of benzo[a]pyrene, one of the widely studied polycyclic aromatic hydrocarbons (PAHs). The exposure of humans to this PAH can be assessed by measuring stable blood protein adducts, such as to histidine and lysine in serum albumin, from their reactive metabolites. In this respect, measurement of the adducts originating from the genotoxic (+)-anti-benzo[a]pyrene diol epoxide is of interest. However, these are difficult to measure at such low levels as are expected in humans generally exposed to benzo[a]pyrene from air pollution and the diet. The analytical methods detecting PAH-biomarkers still suffer from low selectivity and/or detectability to enable generation of data for calculation of in vivo doses of specific stereoisomers, for evaluation of risk factors and assessing risk from exposures to PAH. Here, we suggest an analytical methodology based on high-pressure liquid chromatography (HPLC) coupled to high-resolution tandem mass spectrometry (MS) to lower the detection limits as well as to increase the selectivity with improvements in both chromatographic separation and mass determination. Method development was performed using serum albumin alkylated in vitro by benzo[a]pyrene diol epoxide isomers. The (+)-anti-benzo[a]pyrene diol epoxide adducts could be chromatographically resolved by using an HPLC column with a pentafluorophenyl stationary phase. Interferences were further diminished by the high mass accuracy and resolving power of Orbitrap MS. The achieved method detection limit for the (+)-anti-benzo[a]pyrene diol epoxide adduct to histidine was approximately 4 amol/mg serum albumin. This adduct as well as the adducts to histidine from (−)-anti- and (+/−)-syn-benzo[a]pyrene diol epoxide were quantified in the samples from benzo[a]pyrene-exposed mice. Corresponding adducts to lysine were also quantified. In human serum albumin, the anti-benzo[a]pyrene diol epoxide adducts to histidine were detected in only two out of twelve samples and at a level of approximately 0.1 fmol/mg.