Effect of prophylactic use of intra-nasal oil formulations in the hamster model of Covid-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection initiates with viral entry in upper respiratory tract leading to coronavirus disease 2019 (Covid-19). Severe Covid-19 is characterized by pulmonary pathologies associated with respiratory failure. Thus, therapeutics aimed at inhibiting entry of the virus or its internalization in the upper respiratory tract, are of interest. Herein, we report the prophylactic application of two intra-nasal formulations provided by the National Medicinal Plant Board (NMPB), Anu oil and Til tailya in SARS-CoV2 infection hamster model. Prophylactic nasal instillation of these oil formulations exhibited reduced viral load in lungs, and resulted in reduced body weight loss and pneumonitis. In line with reduced viral load, histopathlogical analysis revealed a reduction in lung pathology in Anu oil group as compared to the control infected group. However, Til tailya group did not show a significant reduction in lung pathology. Furthermore, molecular analysis using mRNA expression profiling indicated reduced expression of pro-inflammatory cytokines genes, including Th1 and Th17 cytokines for both the intra-nasal formulations as a result of decreased viral load. Together, the prophylactic intra-nasal application of Annu oil seems to be useful in limiting both the viral load and disease severity disease in SARS-CoV2 infection in hamster model.

Optimization of Gaussian Kernel Function in Support Vector Machine aided QSAR studies of C-aryl glucoside SGLT2 inhibitors.

The present investigations include utility of latest statistical algorithm Support Vector Machine (SVM) to identify non-linear structure activity relationship between IC50 values and structures of C-aryl glucoside SGLT2 inhibitors. Training dataset consisted of forty molecules and the remaining six molecules were chosen for test set validation. SVM under Gaussian Kernel Function yielded non-linear QSAR models. Forward selection algorithm was applied after pruning and redundancy check on molecular descriptors. Internal validations of QSAR models have been achieved using R CV (2) (LOO), PRESS, SDEP and Y-Scrambling. SVM aided non-linear models are more efficient when optimization of Gaussian Kernel Function was introduced. Non-linear QSAR studies further identified atomic van der Waals volumes, atomic masses, sum of geometrical distances between O..S and degree of unsaturation as molecular descriptors and crucial structural requirements to model IC50 of C-aryl glucoside derivatives.

Pleomorphic lobular carcinoma in a male breast: a rare occurrence.

Carcinoma of male breast is uncommon as it accounts for 0.7% of total breast cancer. The pathology of male breast cancer is remarkably similar to that of cancers seen in women. The same histological subtypes of invasive cancer are present, although papillary carcinomas (both invasive and in situ) are more common and lobular carcinomas are less common. The predominant histological type, in males, as in females, reported in large series has been infiltrating ductal carcinoma with scattered reports of infiltrating lobular carcinoma, all of them of classical type except for a single case of pleomorphic infiltrating lobular carcinoma. Herein, we describe a case of pleomorphic lobular carcinoma occurring in male breast.