DEEMD: Drug Efficacy Estimation Against SARS-CoV-2 Based on Cell Morphology With Deep Multiple Instance Learning.

Drug repurposing can accelerate the identification of effective compounds for clinical use against SARS-CoV-2, with the advantage of pre-existing clinical safety data and an established supply chain. RNA viruses such as SARS-CoV-2 manipulate cellular pathways and induce reorganization of subcellular structures to support their life cycle. These morphological changes can be quantified using bioimaging techniques. In this work, we developed DEEMD: a computational pipeline using deep neural network models within a multiple instance learning framework, to identify putative treatments effective against SARS-CoV-2 based on morphological analysis of the publicly available RxRx19a dataset. This dataset consists of fluorescence microscopy images of SARS-CoV-2 non-infected cells and infected cells, with and without drug treatment. DEEMD first extracts discriminative morphological features to generate cell morphological profiles from the non-infected and infected cells. These morphological profiles are then used in a statistical model to estimate the applied treatment efficacy on infected cells based on similarities to non-infected cells. DEEMD is capable of localizing infected cells via weak supervision without any expensive pixel-level annotations. DEEMD identifies known SARS-CoV-2 inhibitors, such as Remdesivir and Aloxistatin, supporting the validity of our approach. DEEMD can be explored for use on other emerging viruses and datasets to rapidly identify candidate antiviral treatments in the future. Our implementation is available online at https://www.github.com/Sadegh-Saberian/DEEMD.

Chromosomal aberrations in ascetic fluid of metastatic gastric cancer patients: A clustering analysis.

To date, no specific pattern of chromosomal abnormalities has been established in gastric cancer (GC). Cytogenetic analysis was performed using G-banding and fluorescence in situ hybridization (FISH) in 9 ascetic fluids from GC patients, and the clustering patterns of chromosomal abnormalities were studied. Twenty-six different types of chromosomal abnormalities were identified. In contrast to structural abnormalities, the gain or loss of chromosomes was infrequent. Moreover, five main clusters of chromosomal abnormalities were identified by clustering analysis. Extensive cytogenetic complexity, specific chromosomal abnormalities and karyotype heterogeneity are the main characterizations of GC. Some of the recurrent and novel chromosomal abnormalities with distinct clustering patterns identified in this study may play important roles for GC initiation and progression and could serve as promising diagnostic and prognostic markers in GC patients.

How does the supernatant of Lactobacillus acidophilus affect the proliferation and differentiation activities of rat bone marrow-derived stromal cells?

Low proliferation rate and unwanted differentiation of bone marrow-derived stromal cells (rBMSCs) during the frequent passages have limited the use of such cells in clinical cell therapy. Recently, the researchers have focused on the effects of the components produced by some bacteria on proliferation of the stem cells. In this study, we discussed the possible effects of the Lactobacillus acidophilus supernatant on proliferation and differentiation of the rBMSCs. For this aim, the cells were isolated from rat bone marrow, characterized by culturing on tissue specific differentiation media and stained. The cells (passage two) were treated with different concentrations of the L. acidophilus supernatant (0, 0.1, 0.3, 0.9, 3, 9 and 30 &mgr;l/ml) for 14 days. The proliferation and differentiation capacity of the cells were then determined by 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT assay) and tissue specific staining. The results showed a positive effect of the supernatant on the cell proliferation in 3 and 9 &mgr;l/ml concentrations, while did not affect the differentiation capacity of the rBMSCs. The current study strongly suggests the L. acidophilus supernatant as an alternative material that could be added to the media with aim of improvement in the proliferation rate of the rBMSCs without affecting their differentiation capacity.