Foremanlawrence6990

Our studies showed that phosphorothioate ASOs are associated with filopodia and the inner nuclear membrane in cultured cells, and also revealed substantial cellular and subcellular heterogeneity of ASO uptake in mouse tissues. NanoSIMS imaging represents a significant advance in visualizing uptake and distribution of NATs; this approach will be useful in optimizing efficacy and delivery of NATs for treating human disease.

Accurate prediction of drug-target interactions (DTI) is crucial for drug discovery. Recently, deep learning (DL) models for show promising performance for DTI prediction. However, these models can be difficult to use for both computer scientists entering the biomedical field and bioinformaticians with limited DL experience. We present DeepPurpose, a comprehensive and easy-to-use DL library for DTI prediction. DeepPurpose supports training of customized DTI prediction models by implementing 15 compound and protein encoders and over 50 neural architectures, along with providing many other useful features. We demonstrate state-of-the-art performance of DeepPurpose on several benchmark datasets.

https//github.com/kexinhuang12345/DeepPurpose.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.

Quantitative Immunofluorescence (QIF) is often used for immunohistochemistry (IHC) quantification of proteins that serve as cancer biomarkers. Advanced image analysis systems for pathology allow capturing expression levels in each individual cell or subcellular compartment. However, only the Mean Signal Intensity (MSI) within the cancer tissue region of interest is usually considered as biomarker completely ignoring the issue of tumor heterogeneity.

We propose using IHC image-derived information on the spatial distribution of cellular signal intensity (CSI) of protein expression within the cancer cell population to quantify both mean expression level and tumor heterogeneity of CSI levels. We view CSI levels as marks in a marked point process of cancer cells in the tissue and define spatial indices based on conditional mean and conditional variance of the marked point process. The proposed methodology provides objective metrics of cell-to-cell heterogeneity in protein expressions that allow discriminating between different patterns of heterogeneity. The prognostic utility of new spatial indices is investigated and compared to the standard MSI biomarkers using the protein expressions in tissue microarrays (TMAs) incorporating tumor tissues from1000+ breast cancer patients.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.Single mRNA molecules are frequently detected by single molecule fluorescence in situ hybridization (smFISH) using branched DNA technology. While providing strong and background-reduced signals, the method is inefficient in detecting mRNAs within dense structures, in monitoring mRNA compactness and in quantifying abundant mRNAs. To overcome these limitations, we have hybridized slices of high pressure frozen, freeze-substituted and LR White embedded cells (LR White smFISH). mRNA detection is physically restricted to the surface of the resin. This enables single molecule detection of RNAs with accuracy comparable to RNA sequencing, irrespective of their abundance, while at the same time providing spatial information on RNA localization that can be complemented with immunofluorescence and electron microscopy, as well as array tomography. Moreover, LR White embedding restricts the number of available probe pair recognition sites for each mRNA to a small subset. As a consequence, differences in signal intensities between RNA populations reflect differences in RNA structures, and we show that the method can be employed to determine mRNA compactness. We apply the method to answer some outstanding questions related to trans-splicing, RNA granules and mitochondrial RNA editing in single-cellular trypanosomes and we show an example of differential gene expression in the metazoan Caenorhabditis elegans.Slit proteins have been reported to act as axonal repellents in Drosophila; however, their role in the placental microenvironment has not been explored. In this study, we found that human placental multipotent mesenchymal stromal cells (hPMSCs) constitutively express Slit2. Therefore, we hypothesized that Slit2 expressed by hPMSCs could be involved in macrophage migration during placental inflammation through membrane cognate Roundabout (Robo) receptor signaling. In order to develop a preclinical in vitro mouse model of hPMSCs in treatment of perinatal infection, RAW 264.7 cells were used in this study. Slit2 interacted with Robo4 that was highly expressed in RAW 264.7 macrophages their interaction increased the adhesive ability of RAW 264.7 cells and inhibited migration. Lipopolysaccharide (LPS)-induced CD11bCD18 expression could be inhibited by Slit2 and by hPMSC-conditioned medium (CM). LPS-induced activation of p38 and Rap1 was also attenuated by Slit2 and by hPMSC-CM. Noticeably, these inhibitory effects of hPMSC-CM decreased after depletion of Slit2 from the CM. Furthermore, we found that p38 siRNA inhibited LPS-induced Rap1 expression in RAW 264.7 cells, indicating that Rap1 functions downstream of p38 signaling. p38 siRNA increased cell adhesion and inhibited migration through reducing LPS-stimulated CD11bCD18 expression in RAW 264.7 cells. Thus, hPMSC-derived Slit2 may inhibit LPS-induced CD11bCD18 expression to decrease cell migration and increase adhesion through modulating the activity and motility of inflammatory macrophages in placenta. This may represent a novel mechanism for LPS-induced placental infection.Rolling neutrophils form tethers with submicron diameters. Here, we report that these tethers detach, forming elongated neutrophil-derived structures (ENDS) in the vessel lumen. find more We studied ENDS formation in mice and humans in vitro and in vivo. ENDS do not contain mitochondria, endoplasmic reticulum, or DNA, but are enriched for S100A8, S100A9, and 57 other proteins. Within hours of formation, ENDS round up, and some of them begin to present phosphatidylserine on their surface (detected by annexin-5 binding) and release S100A8-S100A9 complex, a damage-associated molecular pattern protein that is a known biomarker of neutrophilic inflammation. ENDS appear in blood plasma of mice upon induction of septic shock. Compared with healthy donors, ENDS are 10-100-fold elevated in blood plasma of septic patients. Unlike neutrophil-derived extracellular vesicles, most ENDS are negative for the tetraspanins CD9, CD63, and CD81. We conclude that ENDS are a new class of bloodborne submicron particles with a formation mechanism linked to neutrophil rolling on the vessel wall.