DNA Sensor-Based Strategy to Visualize the TRPM7 mRNA-Mg2+ Signaling Pathway in Cancer Cells.

Technological advances and methodological innovations in cell signaling pathway analysis will facilitate progress in understanding biological processes, intervening in diseases, and screening drugs. In this work, an elaborate strategy for visualizing and monitoring the transient receptor potential melastatin 7 (TRPM7)-Mg2+ signaling pathway in living cells was constructed through the logical analysis of upstream mRNA and downstream molecules by two individual DNA sensors. The DNA sensors are constructed by modifying the dye-labeled DNA sequences on the surface of gold nanoparticles. By hybridizing with upstream mRNA, Cy5-modified DNA sensor 1 can detect and silence it simultaneously, outputting a red fluorescence signal. When the upstream mRNA is silenced, the concentration of downstream molecules of Mg2+ will be affected and down-regulated. The FAM-modified DNA sensor 2 detects this change and emits a green fluorescence as a signal. Therefore, the dynamic information on TRPM7 mRNA and the Mg2+-mediated signaling pathway can be successfully obtained by fluorescence imaging methods. Furthermore, the TRPM7 mRNA-Mg2+ signaling pathway also affects cell activity and migratory function through cell scratching and other experiments. More importantly, the proposed sensor also shows potential for screening signaling pathway inhibitors. Our work provides a simple and general strategy for the visualization of signaling pathways, which helps to understand the changes in the physiological activities of cancer cells and the causes of carcinogenesis and is crucial for cancer diagnosis and prognosis.

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors.

Purpose: To develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs). Methods: This retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS. Results: The CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874-0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850. Conclusions: The PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery.

Characterization of organic matter and disinfection by-products in membrane backwash water from drinking water treatment.

Two pilot-scale membrane plants were set up to produce drinking water, and membrane backwash water was discharged during the production process. This work studied the characteristics of dissolved organic matter (DOM) in membrane backwash water from submerged microfiltration (MBWS) and pressurized ultrafiltration (MBWP) both of which are coupled with the pre-coagulation process. The results showed that the two waters had similar molecular weight (MW) distributions. Dissolved organic carbon (DOC) and trihalomethane formation potential (THMFP) in MBWS and MBWP were both mainly distributed in MW>30 kDa and MW<1 kDa, and UV(254) was mainly in MW<1 kDa. For Luan River water (LRW, the raw water for the two pilot-scale membrane plants in this study), organic matter enriched in membrane backwash water was mainly in sizes of MW>30 kDa. In addition, organic matter with MW>10 kDa was higher in MBWP than in MBWS. The quality of membrane backwash water was influenced by the changes in LRW quality during different periods. The quality of membrane backwash water was worse in alga-laden period than in normal period and organic matter concentrations in MW<1 kDa increased significantly in this period. The small size DOM in membrane backwash water was more reactive to form trihalomethanes (THMs) in the disinfection process. The variability of specific UV absorbance and THMFP/DOC was consistent in membrane backwash water.