Development and application of a method to classify airborne pollen taxa concentration using light scattering data

Although automated pollen monitoring networks using laser optics are well-established in Japan, it is thought that these methods cannot distinguish between pollen counts when evaluating various pollen taxa. However, a method for distinguishing the pollen counts of two pollen taxa was recently developed. In this study, we applied such a method to field evaluate the data of the two main allergens in Japan, Chamaecyparis obtusa and Cryptomeria japonica. We showed that the method can distinguish between the pollen counts of these two species even when they are simultaneously present in the atmosphere. This result indicates that a method for automated and simple two pollen taxa monitoring with high spatial density can be developed using the existing pollen network.

Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – establishment of an automated multi-taxa pollen counting estimation system (AME system)

Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination. Our experimental results indicate that different pollen types often have different light scattering characteristics, as previous research has suggested. Our results also show that light scattering distributions did not undergo significant temporal changes. Further, we show that the concentration of two different types of pollen could be estimated separately from the total number of pollen grains by fitting the light scattering data to a probability density curve. These findings should help realize a fast and simple automatic pollen monitoring system.

Tracking tau fibrillogenesis and consequent primary phagocytosis of neurons mediated by microglia in a living tauopathy model

ABSTRACTFibrillary tau pathologies have been implicated in Alzheimer’s and allied neurodegenerative diseases, while mechanisms by which neurons bearing tau tangles die remain enigmatic. To address this issue, we pursued tau and related key pathologies macroscopically by PET and MRI and microscopically by intravital two-photon laser optics. Time-course macroscopic assays of tau transgenic mice demonstrated intimate associations of tau deposition and increase of an inflammatory microglial marker, translocator protein (TSPO), with regional brain atrophy. Longitudinal microscopy of these mice revealed a rapid turnover of tau lesions resulting from continuous generation of new tau aggregates followed by loss of neurons and their fibrillar contents. This technology also allowed the capturing of the disappearance of tangle-bearing neurons several days after being engulfed by activated microglia. Notably, a therapeutic TSPO ligand profoundly suppressed the mobility and phagocytotic activity of microglia and improved neuronal survival in this model, supporting the involvement of primary phagocytosis of viable neurons by microglia in tau-primed neuronal death. Finally, partial depletion of microglia revealed roles of immune factors, MFG-E8 and C1q, as ‘eat-me’ signals for an immediate attraction of phagocytic microglia towards the elimination of tangle-loaded neurons.

Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – Establishment of Automated Multi-taxa Pollen Counting Estimation System (AME System)

Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination. Our experimental results indicate that different pollen types often have different light scattering characteristics, as previous research has suggested. Our results also show that light scattering distributions did not undergo significant temporal changes. Further, we show that the concentration of two different types of pollen could be estimated separately from the total number of pollen grains by fitting the light scattering data to a probability density curve. These findings should help realize a fast and simple automatic pollen monitoring system.