Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran.

Neoplasm is an umbrella term used to describe either benign or malignant conditions. The correlations between socioeconomic and environmental factors and the occurrence of new-onset of neoplasms have already been demonstrated in a body of research. Nevertheless, few studies have specifically dealt with the nature of relationship, significance of risk factors, and geographic variation of them, particularly in low- and middle-income communities. This study, thus, set out to (1) analyze spatiotemporal variations of the age-adjusted incidence rate (AAIR) of neoplasms in Iran throughout five time periods, (2) investigate relationships between a collection of environmental and socioeconomic indicators and the AAIR of neoplasms all over the country, and (3) evaluate geographical alterations in their relative importance. Our cross-sectional study design was based on county-level data from 2010 to 2020. AAIR of neoplasms data was acquired from the Institute for Health Metrics and Evaluation (IHME). HotSpot analyses and Anselin Local Moran's I indices were deployed to precisely identify AAIR of neoplasms high- and low-risk clusters. Multi-scale geographically weight regression (MGWR) analysis was worked out to evaluate the association between each explanatory variable and the AAIR of neoplasms. Utilizing random forests (RF), we also examined the relationships between environmental (e.g., UV index and PM2.5 concentration) and socioeconomic (e.g., Gini coefficient and literacy rate) factors and AAIR of neoplasms. AAIR of neoplasms displayed a significant increasing trend over the study period. According to the MGWR, the only factor that significantly varied spatially and was associated with the AAIR of neoplasms in Iran was the UV index. A good accuracy RF model was confirmed for both training and testing data with correlation coefficients R2 greater than 0.91 and 0.92, respectively. UV index and Gini coefficient ranked the highest variables in the prediction of AAIR of neoplasms, based on the relative influence of each variable. More research using machine learning approaches taking the advantages of considering all possible determinants is required to assess health strategies outcomes and properly formulate policy planning.

Neurobehavioral assessment of rats exposed to pristine polystyrene nanoplastics upon oral exposure.

The increasing use of plastics has raised concerns about pollution of freshwater by these polymeric materials. Knowledge about their potential effects on environmental and public health is limited. Recent publications have suggested that the degradation of plastics will result in the release of nano-sized plastic particles to the environment. Therefore, it is of utmost importance to gain knowledge about whether and how nanoplastics affect living organisms. The present study aimed to analyse potential neurobehavioral effects of polystyrene nanoparticles (PS-NPs) after long-term exposure on rat. Potential effects of PS-NPs were investigated using four test dosages (1, 3, 6, and 10 mg PS-NPs/kg of body weight/day) administrated orally with adult Wistar male rats for five weeks. Neurobehavioral tests were chosen to assess a variety of behavioral domains. Particle diameters in test suspensions were determined through dynamic light scattering and showed an average hydrodynamic diameter of approximately 38.92 nm. No statistically significant behavioral effects were observed in all tests performed (p > 0.05). In the elevated plus maze, PS-NPs-exposed rats showed greater number of entries into open arms compared to controls. Also, PS-NPs had no significant influence on body weight of animals. Taking into account the subtle and transient nature of neurobehavioral consequences, however, these results underline the possibility of even pristine plastic nanoparticles to induce behavioral alteration in the rest of the food web, including for marine biota and humans. Indeed even though studied neurobehavioral effects in our study was not statistically significant, the observed subtle effects may be clinically considerable.