Many drugs are developed for commonly occurring, well studied cancer drivers such as vemurafenib for BRAF V600E and erlotinib for EGFR exon 19 mutations. However, most tumors also harbor mutations which have an uncertain role in disease formation, commonly called Variants of Uncertain Significance (VUS), which are not studied or characterized and could play a significant role in drug resistance and relapse. Therefore, the determination of the functional significance of VUS and their response to Molecularly Targeted Agents (MTA) is essential for developing new drugs and predicting response of patients. Here we present a multi-scale deep convolutional neural network (DCNN) architecture combined with an in-vitro functional assay to investigate the functional role of VUS and their response to MTA's. Our method achieved high accuracy and precision on a hold-out set of examples (0.98 mean AUC for all tested genes) and was used to predict the oncogenicity of 195 VUS in 6 genes. 63 (32%) of the assayed VUS's were classified as pathway activating, many of them to a similar extent as known driver mutations. Finally, we show that responses of various mutations to FDA approved MTAs are accurately predicted by our platform in a dose dependent manner. Taken together this novel system can uncover the treatable mutational landscape of a drug and be a useful tool in drug development.In this study, we measured the human epidermal growth factor receptor 2 (HER2) copy number in both tissue and plasma samples of gastric cancer patients by using droplet digital polymerase chain reaction (ddPCR) method. Eighty gastric cancer patients were enrolled and both formalin-fixed and paraffin-embedded tissue and preoperative plasma samples were collected. HER2 status was determined by HER2 immunohistochemistry (IHC)/silver in situ hybridization (SISH) in tissue samples and ddPCR of the target gene HER2 and the reference gene eukaryotic translation initiation factor 2C, 1 in both tissue and plasma. The concordance rate of tissue HER2 status determined by IHC/SISH and HER2 ddPCR was 90.0% (72/80), and the sensitivity and specificity of tissue ddPCR were 85.0% and 95.0%, respectively. The concordance rate of plasma ddPCR and IHC/SISH was 63.8% (51/80). The sensitivity, specificity, positive predictive value, and negative predictive value of plasma HER2 ddPCR were 37.5%, 90.0%, 79.0%, and 59.0%, respectively. As HER2 measurement by tissue ddPCR showed a high concordance rate with HER2 status by IHC/SISH, it could replace tissue IHC/SISH testing in gastric cancer. These findings may contribute to the development of tissue and plasma HER2 testing that would be useful in daily practice.Kidney renal clear cell carcinoma (KIRC) is the most common renal cell carcinoma (RCC). However, patients with KIRC usually have poor prognosis due to limited biomarkers for early detection and prognosis prediction. In this study, we analysed key genes and pathways involved in KIRC from an array dataset including 26 tumour and 26 adjacent normal tissue samples. Weighted gene co-expression network analysis (WGCNA) was performed with the WGCNA package, and 20 modules were characterized as having the highest correlation with KIRC. The upregulated genes in the tumour samples are involved in the innate immune response, whereas the downregulated genes contribute to the cellular catabolism of glucose, amino acids and fatty acids. Furthermore, the key genes were evaluated through a protein-protein interaction (PPI) network combined with a co-expression network. The comparatively lower expression of AGXT, PTGER3 and SLC12A3 in tumours correlates with worse prognosis in KIRC patients, while higher expression of ALOX5 predicts reduced survival.  https://www.selleckchem.com/products/catechin-hydrate.html  Our integrated analysis illustrated the hub genes involved in KIRC tumorigenesis, shedding light on the development of prognostic markers. Further understanding of the function of the identified KIRC hub genes could provide deep insights into the molecular mechanisms of KIRC.Herein, the preparation of gold nanoparticles-silk fibroin (SF-AuNPs) dispersion and its label-free colorimetric detection of the organophosphate pesticide, namely chlorpyrifos, at ppb level are reported. The silk fibroin solution was extracted from B. mori silk after performing degumming, dissolving and dialysis steps. This fibroin solution was used for synthesis of gold nanoparticles in-situ without using any external reducing and capping agent. X-ray Diffractometry (XRD), Field Emission Transmission Electron Microscopy (FETEM) along with Surface Plasmon Resonance based optical evaluation confirmed generation of gold nanoparticles within SF matrix. The resultant SF-AuNPs dispersion exhibited rapid and excellent colorimetric pesticide sensing response even at 10 ppb concentration. Effect of additional parameters viz. pH, ionic concentration and interference from other pesticide samples was also studied. Notably, SF-AuNPs dispersion exhibited selective colorimetric pesticide sensing response which can be calibrated. Furthermore, this method was extended to various simulated real life samples such as tap water, soil and agricultural products including plant residues to successfully detect the presence of chlorpyrifos pesticide. The proposed colorimetric sensor system is facile yet effective and can be employed by novice rural population and expert researchers alike. It can be exploited as preliminary tool for label-free colorimetric chlorpyrifos pesticide sensing in water and agricultural products.Pluripotent stem cell-derived cardiomyocytes (PSC-CMs) hold great promise for disease modeling and drug discovery. However, PSC-CMs exhibit immature phenotypes in culture, and the lack of maturity limits their broad applications. While physical and functional analyses are generally used to determine the status of cardiomyocyte maturation, they could be time-consuming and often present challenges in comparing maturation-enhancing strategies. Therefore, there is a demand for a method to assess cardiomyocyte maturation rapidly and reproducibly. In this study, we found that Myomesin-2 (Myom2), encoding M-protein, is upregulated postnatally, and based on this, we targeted TagRFP to the Myom2 locus in mouse embryonic stem cells. Myom2-RFP+ PSC-CMs exhibited more mature phenotypes than RFP- cells in morphology, function and transcriptionally, conductive to sarcomere shortening assays. Using this system, we screened extracellular matrices (ECMs) and identified laminin-511/521 as potent enhancers of cardiomyocyte maturation.