Spatial interaction between breast cancer and environmental pollution in the Monterrey Metropolitan Area

Vaccinia-related kinase 2 variants differentially affect breast cancer growth by regulating kinase activity

Genetic information is transcribed from genomic DNA to mRNA, which is then translated into three-dimensional proteins. mRNAs can undergo various post-transcriptional modifications, including RNA editing that alters mRNA sequences, ultimately affecting protein function. In this study, RNA editing was identified at the 499th base (c.499) of human vaccinia-related kinase 2 (VRK2). This RNA editing changes the amino acid in the catalytic domain of VRK2 from isoleucine (with adenine base) to valine (with guanine base). Isoleucine-containing VRK2 has higher kinase activity than the valine-containing VRK2, which leads to an increase in tumor cell proliferation. Earlier we reported that VRK2 directly interacts with dystrobrevin-binding protein (dysbindin) and results in reducing its stability. Herein, we demonstrate that isoleucine-containing VRK2 decreases the level of dysbindin than valine-containing VRK2. Dysbindin interacts with cyclin D and thereby regulates its expression and function. The reduction in the level of dysbindin by isoleucine-containing VRK2 further enhances the cyclin D expression, resulting in increased tumor growth and reduction in survival rates. It has also been observed that in patient samples, VRK2 level was elevated in breast cancer tissue compared to normal breast tissue. Additionally, the isoleucine form of VRK2 exhibited a greater increase in breast cancer tissue. Therefore, it is concluded that VRK2, especially dependent on the 167th variant amino acid, can be one of the indexes of tumor progression and proliferation.

Exploring the geospatial epidemiology of breast cancer in Iran: identifying significant risk factors and spatial patterns for evidence-based prevention strategies

BACKGROUND

Breast Cancer (BC) is a formidable global health challenge, and Iran is no exception, with BC accounting for a significant proportion of women's malignancies. To gain deeper insights into the epidemiological characteristics of BC in Iran, this study employs advanced geospatial techniques and feature selection methods to identify significant risk factors and spatial patterns associated with BC incidence.

METHODS

Using rigorous statistical methods, geospatial data from Iran, including cancer-related, sociodemographic, healthcare infrastructure, environmental, and air quality data at the provincial level, were meticulously analyzed. Age-standardized incidence rates (ASR) are calculated, and different regression models are used to identify significant variables associated with BC incidence. Spatial analysis techniques, including global and local Moran's index, geographically weighted regression, and Emerging hotspot analysis, were utilized to examine geospatial patterns, identify clustering and hotspots, and assess spatiotemporal distribution of BC incidence.

RESULTS

The findings reveal that BC predominantly affects women (98.03%), with higher incidence rates among those aged 50 to 79. Isfahan (ASR = 26.1) and Yazd (ASR = 25.7) exhibit the highest rates. Significant predictors of BC incidence, such as marriage, tertiary education attainment rate, physician-to-population ratio, and PM2.5 air pollution, are identified through regression models.

CONCLUSION

The study's results provide valuable information for the development of evidence-based prevention strategies to reduce the burden of BC in Iran. The findings underscore the importance of early detection, health education campaigns, and targeted interventions in high-risk clusters and adjacent regions. The geospatial insights generated by this study have implications for policy-makers, researchers, and public health practitioners, facilitating the formulation of effective BC prevention strategies tailored to the unique epidemiological patterns in Iran.

Dye decomposition and air de-pollution performance of TiO2/SiO2 and N-TiO2/SiO2 photocatalysts coated on Portland cement mortar substates

In this study, the newly synthesized TiO₂ and N doped TiO₂ clusters were added to silica sol to synthesize N-TiO₂/SiO₂ composites via the sol-gel method. Afterwards, the prepared sols were applied by brushing on portland cement. Doping with nitrogen significantly increased the absorption of TiO₂ towards the visible region, thus, increasing the photocatalytic activity. SEM characterization of the treated samples showed that the clusters were distributed in form of aggregates on the samples' surface. The self-cleaning and air de-polluting performances were assessed through methylene blue degradation and the oxidation of nitrogen oxide, resulting in methylene blue (MB) removal of 85% and 78% after 60 min of irradiation for SN10TiO₂ and STiO₂, respectively. Regarding air de-pollution performance, the newly synthesized photocatalysts showed the ability of NOx reduction. However, their efficiency was somewhat lower, in which 23.81% of NO has been oxidized by the sample SN10TiO₂, while SP25 showed a total NO conversion of 38.98%. The powdered xerogels of the newly synthesized nanoparticles revealed high photocatalytic efficiency concerning NO oxidation, resulting in a higher performance compared to those obtained by the xerogel containing P25.

Determining the Spatial Distribution Characteristics of Urban Regeneration Projects in China on the City Scale: The Case of Shenzhen

Urban regeneration (UR) has been a leading concern in urban studies globally. China’s rapid urbanization has undergone profound urban decay and social contestation, for which UR has emerged as a viable solution. However, UR is not without its drawbacks. It has caused emerging spatial and planning problems; however, few studies have explored the characteristics and issues of UR from the view of spatial analytics on the city scale. This study aims to depict the distribution characteristics of UR projects in Chinese cities and to reveal whether it meets the requirements of urban development from the planning perspective. The nearest neighbor index and its hierarchical clustering, as well as kernel density estimation are used in conjunction to investigate the spatial distribution characteristics; and the relationship between project distribution and each urban development indicator is explored using mixed spatial characteristics analyses, such as buffer analysis, space syntax, and heat mapping. Considering Shenzhen as the empirical study city, this research is based on all officially released data of implemented UR projects between 2010 and 2021. The findings imply that the UR projects in Shenzhen are mostly located in areas with higher economic development levels and accessibility with areas witnessing industrial restructuring and severe urban decay being prone to be designated for UR initiatives. The spatial distribution characteristics disclose the challenges inherent in the mix of top-down and market-driven UR approaches as well as the dilemma of the center-periphery pattern in UR implementation. Furthermore, the contradiction between the growing population and limited land resources as well as the barriers to industrial clustering formation are also revealed. This study enriches the methodological framework for spatial and visualization studies of urban regeneration in worldwide cities and sheds light on how to promote UR in regard to urban sustainability with ramifications for future urban development in other Chinese cities.