Lauritzen Enemark (foodarrow0)

The IC50 of BDTF and PDTF were 25 µg/mL and 11 µg/mL respectively, while their methanol crude extracts demonstrated lower antiviral efficacy (IC50 ≈ 101-107 µg/mL). BDTF and PDTF also exerted a similar higher virucidal effect (IC50 of 11 µg/mL) than methanol crude extracts (IC50 ≈ 52-66 µg/mL). Furthermore, all the extracts inhibited the attachment of DENV-2 by at least 80%. Pre-treatments of cells with BDTF and PDTF markedly prevented DENV-2 infection when compared to methanol crude extracts. Conclusion This study suggests that porcupine dates possess antiviral properties against DENV-2, which is attributed to its tannin compounds.Background Transcriptomic structural variants (TSVs)-large-scale transcriptome sequence change due to structural variation - are common in cancer. TSV detection from high-throughput sequencing data is a computationally challenging problem. Among all the confounding factors, sample heterogeneity, where each sample contains multiple distinct alleles, poses a critical obstacle to accurate TSV prediction. Results To improve TSV detection in heterogeneous RNA-seq samples, we introduce the Multiple Compatible Arrangements Problem (MCAP), which seeks k genome arrangements that maximize the number of reads that are concordant with at least one arrangement. This models a heterogeneous or diploid sample. We prove that MCAP is NP-complete and provide a 1 4 -approximation algorithm for k = 1 and a 3 4 -approximation algorithm for the diploid case ( k = 2 ) assuming an oracle for k = 1 . Combining these, we obtain a 3 16 -approximation algorithm for MCAP when k = 2 (without an oracle). We also present an integer linear programming formulation for general k. We characterize the conflict structures in the graph that require k > 1 alleles to satisfy read concordancy and show that such structures are prevalent. Conclusions We show that the solution to MCAP accurately addresses sample heterogeneity during TSV detection. Our algorithms have improved performance on TCGA cancer samples and cancer cell line samples compared to a TSV calling tool, SQUID. The software is available at https//github.com/Kingsford-Group/diploidsquid.Background In situ analysis of biomarkers such as DNA, RNA and proteins are important for research and diagnostic purposes. At the RNA level, plant gene expression studies rely on qPCR, RNAseq and probe-based in situ hybridization (ISH). However, for ISH experiments poor stability of RNA and RNA based probes commonly results in poor detection or poor reproducibility. Recently, the development and availability of the RNAscope RNA-ISH method addressed these problems by novel signal amplification and background suppression. This method is capable of simultaneous detection of multiple target RNAs down to the single molecule level in individual cells, allowing researchers to study spatio-temporal patterning of gene expression. However, this method has not been optimized thus poorly utilized for plant specific gene expression studies which would allow for fluorescent multiplex detection. Here we provide a step-by-step method for sample collection and pretreatment optimization to perform the RNAscope assay in the le in the plant tissues the standard protocol is deficient and required optimization. Utilizing barley specific HvGAPDH and Rpg1 RNA probes we report an optimized method which can be used for RNAscope detection to determine the spatial expression and semi-quantification of target RNAs. This optimized method will be immensely useful in other plant species such as the widely utilized Arabidopsis.Background Auxin response factors (ARFs) have long been a research focus and represent a class of key regulators of plant growth and development. Integrated phylogenomic synteny network analyses were able to provide novel insights into the evolution of the ARF gene family. Results Here, more than 3500 ARFs collected from plant genomes and transcriptomes covering major streptophyte lineages were used t