Ambient fine and coarse particles in Japan affect nasal and bronchial epithelial cells differently and elicit varying immune response

Ambient particulate matter (PM) epidemiologically exacerbates respiratory and immune health, including allergic rhinitis (AR) and bronchial asthma (BA). Although fine and coarse particles can affect respiratory tract, the differences in their effects on the upper and lower respiratory tract and immune system, their underlying mechanism, and the components responsible for the adverse health effects have not been yet completely elucidated. In this study, ambient fine and coarse particles were collected at three different locations in Japan by cyclone technique. Both particles collected at all locations decreased the viability of nasal epithelial cells and antigen presenting cells (APCs), increased the production of IL-6, IL-8, and IL-1β from bronchial epithelial cells and APCs, and induced expression of dendritic and epithelial cell (DEC) 205 on APCs. Differences in inflammatory responses, but not in cytotoxicity, were shown between both particles, and among three locations. Some components such as Ti, Co, Zn, Pb, As, OC (organic carbon) and EC (elemental carbon) showed significant correlations to inflammatory responses or cytotoxicity. These results suggest that ambient fine and coarse particles differently affect nasal and bronchial epithelial cells and immune response, which may depend on particles size diameter, chemical composition and source related particles types

Evaluating Multispectral Imaging for Assessing Bacterial Leaf Blight Damage in Indonesian Agricultural Insurance

Bacterial Leaf Blight (BLB) is one of the main diseases in Indonesia that causes a 90% reduction in grain weight. Multispectral imaging may be used as a quick and effective method for damage assessment and is expected to utilize on agricultural insurance in Indonesia. Data were collected at the rainy season and dry season 2018 in Farmers rice field at Bali Province. Vegetation indices (NDVI, GNDVI, and VARIred-edge) was analyzed using QGIS 2.18 from multispectral images. Some vegetation index shows positive correlation with SPAD and negative correlation with DSI (%). VARIred-edge has a higher relationship with DSI (R2: 0.8443) than NDVI (R2: 0.8291) and GNDVI (R2: 0.5463) at the average value on each location, but the relation seems to be affected by that relation between SPAD and LAI. Further data and analysis are required