GfsA encodes a novel galactofuranosyltransferase involved in biosynthesis of galactofuranose antigen of O-glycan in Aspergillus nidulans and Aspergillus fumigatus.

The cells walls of filamentous fungi in the genus Aspergillus have galactofuranose (Galf)-containing polysaccharides and glycoconjugates, including O-glycans, N-glycans, fungal-type galactomannan and glycosylinositolphosphoceramide, which are important for cell wall integrity. Here, we attempted to identify galactofuranosyltransferases that couple Galf monomers onto other wall components in Aspergillus nidulans. Using reverse-genetic and biochemical approaches, we identified that the AN8677 gene encoded a galactofuranosyltransferase, which we called GfsA, involved in Galf antigen biosynthesis. Disruption of gfsA reduced binding of ß-Galf-specific antibody EB-A2 to O-glycosylated WscA protein and galactomannoproteins. The results of an in-vitro Galf antigen synthase assay revealed that GfsA has ß1,5- or ß1,6-galactofuranosyltransferase activity for O-glycans in glycoproteins, uses UDP-d-Galf as a sugar donor, and requires a divalent manganese cation for activity. GfsA was found to be localized at the Golgi apparatus based on cellular fractionation experiments. ΔgfsA cells exhibited an abnormal morphology characterized by poor hyphal extension, hyphal curvature and limited formation of conidia. Several gfsA orthologues were identified in members of the Pezizomycotina subphylum of Ascomycota, including the human pathogen Aspergillus fumigatus. To our knowledge, this is the first characterization of a fungal ß-galactofuranosyltransferase, which was shown to be involved in Galf antigen biosynthesis of O-glycans in the Golgi.

Geospatial intelligence system for evaluating the work environment and physical load of factory workers.

This study aimed to assess the effectiveness of methods for evaluating the environmental and physical loads on workers in manufacturing plants, considering their locations. Participants were employees of DENSO CORPORATION's manufacturing facilities, and environmental sensors (for temperature and humidity) and BLE beacons were installed to cover the work area. Questionnaires were completed by the participants twice to assess their thermal comfort and fatigue in the work environment. The results showed that a regression prediction model with an adjusted R-squared of 0.418 for fixed-point temperature and 0.495 for perceived temperature was developed for thermal comfort. No linear relationship was found between environmental factors and fatigue, and a decision tree analysis was conducted. Relative humidity and activity level, along with temperature, were selected as predictor variables. The findings suggest that it is possible to estimate the work environment and workload without adding additional measurement-related burdens or challenges. This highlights the usefulness of the proposed method, which takes into account the environmental distribution throughout the work area rather than relying solely on conventional fixed-point observation data, for assessing workers' exposure to the environment and preventing occupational accidents.Clinical Relevance- The proposed approach, combining indoor localization with environmental status, can estimate the condition of workers and is expected to be a good solution for preventing occupational accidents and enhancing workers' health.