Hypermethylation in the promoter region inhibits AJAP1 expression and activates the JAK/STAT pathway to promote prostate cancer cell migration and stem cell sphere formation.

BACKGROUND: AJAP1 is down-regulated in multiple cancer types and plays a suppressive role in cancer progression. However, its molecular regulatory mechanism in prostate cancer has not been reported. METHODS: Bioinformatics methods were employed to analyze AJAP1 expression in prostate cancer tissues and its association with TNM staging. MSP and qRT-PCR were used to quantify promoter methylation and AJAP1 expression after 5-aza-20-deoxycytidine (5-AzaC) treatment. Scratch healing assay and Transwell method were adopted to analyze the effects of aberrant AJAP1 expression, 5-AzaC and AG490 on cell migration and invasion. The levels of AJAP1 protein, EMT-related and JAK/STAT pathway-related proteins were determined by Western blot. The effects of AJAP1 aberrant expression and AG490 treatment on the sphere forming ability of prostate cancer cells were analyzed by sphere formation assay. RESULTS: This study confirmed the significant down-regulation of AJAP1 expression in prostate cancer tissues and cells, and its negative correlation with TNM staging. 5-AzaC treatment led to a significant reduction of AJAP1 methylation level and a significant upregulation of AJAP1 expression, indicating that the methylation level of AJAP1 promoter may affect the expression of AJAP1. Cell function experiments found that overexpression or decreased methylation of AJAP1 inhibited epithelial mesenchymal transition (EMT), migration, and invasion, while silencing or increased methylation of AJAP1 had the opposite functions. JAK2/STAT3 pathway inhibiting assay found that inhibition of JAK2/STAT3 pathway significantly reduced EMT, cell migration, and stem cell sphere formation in prostate cancer. SIGNIFICANCE: Therefore, investigating the influence of aberrant AJAP1 expression on functions of prostate cancer cells is conducive to our in-depth understanding of the mechanism of prostate cancer genesis and development.

[Research progress in lung parenchyma segmentation based on computed tomography].

Lung diseases such as lung cancer and COVID-19 seriously endanger human health and life safety, so early screening and diagnosis are particularly important. computed tomography (CT) technology is one of the important ways to screen lung diseases, among which lung parenchyma segmentation based on CT images is the key step in screening lung diseases, and high-quality lung parenchyma segmentation can effectively improve the level of early diagnosis and treatment of lung diseases. Automatic, fast and accurate segmentation of lung parenchyma based on CT images can effectively compensate for the shortcomings of low efficiency and strong subjectivity of manual segmentation, and has become one of the research hotspots in this field. In this paper, the research progress in lung parenchyma segmentation is reviewed based on the related literatures published at domestic and abroad in recent years. The traditional machine learning methods and deep learning methods are compared and analyzed, and the research progress of improving the network structure of deep learning model is emphatically introduced. Some unsolved problems in lung parenchyma segmentation were discussed, and the development prospect was prospected, providing reference for researchers in related fields.

The impact of air pollutant deposition on solar energy system efficiency: An approach to estimate PV soiling effects with the Community Multiscale Air Quality (CMAQ) model.

Deposition and accumulation of aerosol particles on photovoltaics (PV) panels, which is commonly referred to as "soiling of PV panels," impacts the performance of the PV energy system. It is desirable to estimate the soiling effect at different locations and times for modeling the PV system performance and devising cost-effective mitigation. This study presents an approach to estimate the soiling effect by utilizing particulate matter (PM) dry deposition estimates from air quality model simulations. The Community Multiscale Air Quality (CMAQ) modeling system used in this study was developed by the U.S. Environmental Protection Agency (U.S. EPA) for air quality assessments, rule-making, and research. Three deposition estimates based on different surface roughness length parameters assumed in CMAQ were used to illustrate the soling effect in different land-use types. The results were analyzed for three locations in the U.S. for year 2011. One urban and one suburban location in Colorado were selected because there have been field measurements of particle deposition on solar panels and analysis on the consequent soiling effect performed at these locations. The third location is a coastal city in Texas, the City of Brownsville. These three locations have distinct ambient environments. CMAQ underestimates particle deposition by 40% to 80% when compared to the field measurements at the two sites in Colorado due to the underestimations in both the ambient PM10 concentration and deposition velocity. The estimated panel transmittance sensitivity due to the deposited particles is higher than the sensitivity obtained from the measurements in Colorado. The final soiling effect, which is transmittance loss, is estimated as 3.17 ±â€¯4.20% for the Texas site, 0.45 ±â€¯0.33%, and 0.31 ±â€¯0.25% for the Colorado sites. Although the numbers are lower compared to the measurements in Colorado, the results are comparable with the soiling effects observed in U.S.

Increasing vertical resolution in US models to improve track forecasts of Hurricane Joaquin with HWRF as an example.

The atmosphere-ocean coupled Hurricane Weather Research and Forecast model (HWRF) developed at the National Centers for Environmental Prediction (NCEP) is used as an example to illustrate the impact of model vertical resolution on track forecasts of tropical cyclones. A number of HWRF forecasting experiments were carried out at different vertical resolutions for Hurricane Joaquin, which occurred from September 27 to October 8, 2015, in the Atlantic Basin. The results show that the track prediction for Hurricane Joaquin is much more accurate with higher vertical resolution. The positive impacts of higher vertical resolution on hurricane track forecasts suggest that National Oceanic and Atmospheric Administration/NCEP should upgrade both HWRF and the Global Forecast System to have more vertical levels.