This work develops a robust classifier for a COVID-19 pre-screening model from crowdsourced cough sound data. The crowdsourced cough recordings contain a variable number of coughs, with some input sound files more informative than the others. Accurate detection of COVID-19 from the sound datasets requires overcoming two main challenges (i) the variable number of coughs in each recording and (ii) the low number of COVID-positive cases compared to healthy coughs in the data. We use two open datasets of crowdsourced cough recordings and segment each cough recording into non-overlapping coughs. The segmentation enriches the original data without oversampling by splitting the original cough sound files into non-overlapping segments. Splitting the sound files enables us to increase the samples of the minority class (COVID-19) without changing the feature distribution of the COVID-19 samples resulted from applying oversampling techniques. Each cough sound segment is transformed into six image representations for further analyses. We conduct extensive experiments with shallow machine learning, Convolutional Neural Network (CNN), and pre-trained CNN models. The results of our models were compared to other recently published papers that apply machine learning to cough sound data for COVID-19 detection. Our method demonstrated a high performance using an ensemble model on the testing dataset with area under receiver operating characteristics curve = 0.77, precision = 0.80, recall = 0.71, F1 measure = 0.75, and Kappa = 0.53. The results show an improvement in the prediction accuracy of our COVID-19 pre-screening model compared to the other models.

We declare no conflict of interest. ABSTRACTThe impact of intestinal parasitic infection in renal transplant recipients requires careful consideration in the developing world. However, there have been very few studies addressing this issue in Iran. This study was conducted to determine the prevalence of intestinal parasitic infections in renal transplant recipients in Iran. Stool specimens from renal transplant recipients and control groups were obtained between June 2006 and January 2007. The samples screened for intestinal parasitic infections using direct smear, formalin-ether sedimentation, Sheather's flotation and modified Ziehl-Neelsen staining methods. Out of 150 renal transplant recipients, 33.3% (50), and out of 225 control group, 20% (45) were infected with one or more type of intestinal parasites. The parasites detected among patients included Entamoeba coli (10.6%), Endolimax nana (8.7%), Giardia lamblia (7.4%), Blastocystis spp. (4.7%), Iodamoeba butschlii (0.7%), Chilomastix mesnili (0.7%) and Ascaris lumbricoides (0.7%). Multiple infections were more common among renal transplant recipients group (p < 0.05). This study highlights the importance of testing for intestinal parasites among Iranian renal transplant recipients. Routine examinations of stool samples for parasites would significantly benefit the renal transplant recipients by contributing to reduce severe infections.

The impact of intestinal parasitic infection in renal transplant recipients requires careful consideration in the developing world. However, there have been very few studies addressing this issue in Iran. This study was conducted to determine the prevalence of intestinal parasitic infections in renal transplant recipients in Iran. Stool specimens from renal transplant recipients and control groups were obtained between June 2006 and January 2007. The samples screened for intestinal parasitic infections using direct smear, formalin-ether sedimentation, Sheather's flotation and modified Ziehl-Neelsen staining methods. Out of 150 renal transplant recipients, 33.3% (50), and out of 225 control group, 20% (45) were infected with one or more type of intestinal parasites. The parasites detected among patients included Entamoeba coli (10.6%), Endolimax nana (8.7%), Giardia lamblia (7.4%), Blastocystis spp. (4.7%), Iodamoeba butschlii (0.7%), Chilomastix mesnili (0.7%) and Ascaris lumbricoides (0.7%). Multiple infections were more common among renal transplant recipients group (p < 0.05). This study highlights the importance of testing for intestinal parasites among Iranian renal transplant recipients. Routine examinations of stool samples for parasites would significantly benefit the renal transplant recipients by contributing to reduce severe infections.

Background: The SARS-CoV-2 virus is a new highly contagious Coronavirus with a positive-sense RNA encoding 16 non-structural proteins (nsps16, nsp15, nsp3). In this study, the coronavirus pathogenicity and the losartan functional ligand for inhibiting TRPM2 and macrodomain have been molecularly evaluated.Material and method: In this study, the structures of macrodomain binding ADP ribose in CoVs and human Transient Receptor Potential Cation Channel Subfamily M Member 2 (TRPM2) protein were downloaded from protein data bank. Then, a virtual screening was done to recognize the hit compounds from GalaXi_2019-10, KnowledgeSpace_2019-05, and REALspace_2019-12 databases. This collection, then, was imported to the ligandScout software, on the base of Adenosine Diphosphate Ribose (ADPR) pharmacophore model. Result: Among seven compounds, five compounds were finally evaluated as the structural analogs of ADPR or other nucleotides, from which one compound was a non-FDA-approved sulphonamide and was removed. The other compound, losartan, was finally selected for molecular docking and molecular dynamic simulation. According to the virtual screening and docking, losartan was candidate as an effective ligand for TRPM2 and macrodomain. Conclusion: In the current study losartan earned a proper dock score and binding affinity to create the complexes with TRPM2 and macrodomain. The inhibitory effect of losartan on PARP has been shown and it could interfere positively in several points (PARP, PARG- macrodomain and TRPM2) and decreases oxidative stress and apoptosis in COVID-19.

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