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OBJECTIVES: Metastasis in breast cancer is the first cause of death in patients. The epidermal growth factor (EGF) increases cancer cells' invasion, and migration. Melatonin's inhibitory effects on various types of cancer were confirmed. This study aimed to investigate whether melatonin could apply its impact through the EGF-related pathways or not. METHODS: First, MDA-MB-231 and MCF7 cells were cultured, and then melatonin effects on cell viability were determined by MTT assay. Transwell invasion assay was applied to identify the invasiveness of these breast cancer cell lines under treatment of EGF and melatonin. Real-time RT-PCR then investigated the expression of MMP9 and MMP2 in determined groups. Cell proliferation was also assayed under EGF and melatonin treatment using Ki67 assessment by flow cytometry. RESULTS: The rate of invasion and migration of EGF-treated cells increased in both groups, in which melatonin caused increased invasion by EGF just in MCF7 cells. MMP9 and MMP2 expression increased significantly in both cell lines under EGF treatment, and melatonin increased these genes' expression in both cell lines (p<0.05). EGF increased the MMP9 and MMP2 gene expression, and melatonin increased EGF-induced expression (p<0.05). The EGF reduced the expression of the Ki67 protein in the MCF7 cell line, which was negatively affected by melatonin and EGF. In contrast, along with melatonin, EGF did not affect the proliferation of the MDA-MB-231 cell line. CONCLUSIONS: The results of this study show that melatonin in the presence of EGF does not show the anti-cancer properties previously described for this substance.
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Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.
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Overoxidation is the principal barrier against commercializing propane oxidative dehydrogenation (PODH) catalysts for propylene production. The current approach to reducing overoxidation, i.e., coating the non-selective support surface with a monolayer of active phase, can itself increase the probability of overoxidation of the produced propylene due to polymerization of active phase species. Incorporating the "confinement agents" onto the metal oxide support might be considered as an alternative solution to prevent hydrocarbons from reaching the support and overoxidizing. Herein, the UiO-66 metal-organic framework, which contains numerous organic ligands connected to the zirconia nodes, was used as support for the vanadia active phase to highlight the role of support's confinement effects on the overall catalytic performance toward the PODH. The UiO-66 supported vanadia catalysts with various vanadium loadings were fabricated via an ultrasonic-assisted wet impregnation procedure. The catalytic function is related to the underlying chemical processes at catalyst surfaces using physicochemical characterization techniques, PODH performance measurements, and machine learning tools. The results showed that the catalyst with a relatively low vanadia density of 2.7 nm-2, equivalent to less than half of the entire support surface coverage, could achieve propylene productivity of 4.43 [Formula: see text] , propane conversion of 17.1%, and propylene selectivity of 49.7% at 350 °C.
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Here, we show, for the first time, the use of graphitic carbon nitride (g-C3N4) nanosheets to improve the resolution and efficiency of protein separation in gel electrophoresis. By loading 0.04% (m/v) g-C3N4 nanosheets into the polyacrylamide gel at 25 °C, the thermal conductivity increased approximately 80% which resulted in 20% reduction in Joule heating and overall increase of separation efficiency. Also, polymerization of acrylamide occurred in the absence of tetramethylethylenediamine (TEMED) when the polyacrylamide gel contained g-C3N4 nanosheets. Hence, the g-C3N4 act simultaneously as a polymerization catalyst as well as heat sinks to lower Joule heating effect on band broadening.