The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus poses serious threats to the global public health and leads to worldwide crisis. No effective drug or vaccine is readily available. The viral RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target. A hybrid drug screening procedure was proposed and applied to identify potential drug candidates targeting RdRp from 1906 approved drugs. Among the four selected market available drug candidates, Pralatrexate and Azithromycin were confirmed to effectively inhibit SARS-CoV-2 replicationin vitrowith EC₅₀values of 0.008μM and 9.453 μM, respectively. For the first time, our study discovered that Pralatrexate is able to potently inhibit SARS-CoV-2 replication with a stronger inhibitory activity than Remdesivir within the same experimental conditions. The paper demonstrates the feasibility of fast and accurate anti-viral drug screening for inhibitors of SARS-CoV-2 and provides potential therapeutic agents against COVID-19.

Circular RNAs (circRNAs) are RNA molecules formed by joining a downstream 3 splice donor site and an upstream 5 splice acceptor site. Several recent studies have identified circRNAs as potential biomarker for different diseases. A number of methods are available for the identification of circRNAs. The circRNA identification methods cannot provide full-length sequences. Reconstruction of the full-length sequences is crucial for the downstream analyses of circRNA research including differential expression analysis, circRNA-miRNA interaction analysis and other functional studies of the circRNAs. However, a limited number of methods are available in the literature for the reconstruction of full-length circRNA sequences. We developed a new method, circRNA-full, for full-length circRNA sequence reconstruction utilizing chimeric alignment information from the STAR aligner. To evaluate our method, we used full-length circRNA sequences produced by isocirc and ciri-long using long-reads RNA-seq data. Our method achieved better reconstruction rate, precision, sensitivity and F1 score than the existing full-length circRNA sequence reconstruction tool ciri-full for both human and mouse data.

Circular RNAs (circRNAs) are formed by joining the 3′ and 5′ ends of RNA molecules. Identification of circRNAs is an important part of circRNA research. The circRNA prediction methods can predict the circRNAs with start and end positions in the chromosome but cannot identify the full-length circRNA sequences. We present an R package FcircSEC (Full Length circRNA Sequence Extraction and Classification) to extract the full-length circRNA sequences based on gene annotation and the output of any circRNA prediction tools whose output has a chromosome, start and end positions, and a strand for each circRNA. To validate FcircSEC, we have used three databases, circbase, circRNAdb, and plantcircbase. With information such as the chromosome and strand of each circRNA as the input, the identified sequences by FcircSEC are consistent with the databases. The novelty of FcircSEC is that it can take the output of state-of-the-art circRNA prediction tools as input and is applicable for human and other species. We also classify the circRNAs as exonic, intronic, and others. The R package FcircSEC is freely available.

Breast cancer (BC) is the most frequent malignancy identified in adult females, resulting in enormous financial losses worldwide. Owing to the heterogeneity as well as various molecular subtypes, the molecular pathways underlying carcinogenesis in various forms of BC are distinct. Therefore, the advancement of alternative therapy is required to combat the ailment. Recent analyses propose that long non-coding RNAs (lncRNAs) perform an essential function in controlling immune response, and therefore, may provide essential information about the disorder. However, their function in patients with triple-negative BC (TNBC) has not been explored in detail. Here, we analyzed the changes in the genomic expression of messenger RNA (mRNA) and lncRNA in standard control in response to cancer metastasis using publicly available single-cell RNA-Seq data. We identified a total of 197 potentially novel lncRNAs in TNBC patients of which 86 were differentially upregulated and 111 were differentially downregulated. In addition, among the 909 candidate lncRNA transcripts, 19 were significantly differentially expressed (DE) of which three were upregulated and 16 were downregulated. On the other hand, 1901 mRNA transcripts were significantly DE of which 1110 were upregulated and 791 were downregulated by TNBCs subtypes. The Gene Ontology (GO) analyses showed that some of the host genes were enriched in various biological, molecular, and cellular functions. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that some of the genes were involved in only one pathway of prostate cancer. The lncRNA-miRNA-gene network analysis showed that the lncRNAs TCONS_00076394 and TCONS_00051377 interacted with breast cancer-related micro RNAs (miRNAs) and the host genes of these lncRNAs were also functionally related to breast cancer. Thus, this study provides novel lncRNAs as potential biomarkers for the therapeutic intervention of this cancer subtype.

Endoplasmic reticulum (ER) stress plays a critical role in the progression of type 2 diabetes mellitus (T2DM) through activation of the pro-apoptotic transcription factor C/EBP homologous protein (CHOP). Accumulation of CHOP in the nucleus promotes thioredoxin-interacting protein (TXNIP) expression and its translocation to mitochondria, thereby contributing to mitochondrial dysfunction and β-cell loss. Tauroursodeoxycholic acid (TUDCA) and ursodeoxycholic acid (UDCA) are established inhibitors of ER stress–induced CHOP expression. This study evaluated the combined effects of TUDCA and UDCA on body weight regulation and glycemic control in a rat model of T2DM induced by high-fat diet (HFD) feeding and low-dose streptozotocin (STZ). Swiss albino male rats were divided into four groups: control, HFD control, diabetic (HFD+STZ), and treatment [HFD+STZ+TUDCA (0.02%)/UDCA (0.3%)]. Body weight, fasting blood glucose, and postprandial blood glucose were assessed over 90 days. Supplementation with TUDCA and UDCA significantly reduced weight gain and improved glycemic control in diabetic rats (p < 0.0001). The incidence of diabetes was substantially lower in the treatment group compared with untreated diabetic rats, with 0% vs. 50% incidence by day 54 and 34% vs. 75% by day 90. By day 90, PBG levels were significantly lower in treated diabetic rats than in untreated diabetic rats (p < 0.0001). These findings indicate that combined TUDCA and UDCA supplementation exerts strong anti-obesogenic and anti-diabetic effects, enhancing glucose homeostasis and delaying diabetes onset. These findings suggest that blockers of TBP-2 mitochondrial shuttling, such as TUDCA and UDCA, may represent promising strategies for the prevention and treatment of T2DM.

Modeling total children ever born is very crucial since Bangladesh is going under a rapid growth of population. We use logistic regression model, a well-known technique for categorical data analysis, to predict the number of children ever born using BDHS (2011) data. BDHS data is not random, since two stages stratified sampling is conducted to collect the data. Cluster correction and weight adjustment is necessary for analyzing this data. An extensive literature search fails to find any work which uses these adjustments for predicting the number of children ever born. In this paper these two adjustments have been used for predicting the number of children ever born. The prediction performance has been measured by training and test error.