RESUMEN
BACKGROUND: Long-standing health inequalities in Australian society that were exposed by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were described as "fault lines" in a recent call to action by a consortium of philanthropic organizations. With asthma a major contributor to childhood disease burden, studies of its spatial epidemiology can provide valuable insights into the emergence of health inequalities early in life. OBJECTIVE: The aims of this study were to characterize the spatial variation of asthma prevalence among children living within Australia's 4 largest cities and quantify the relative contributions of climatic and environmental factors, outdoor air pollution, and socioeconomic status in determining this variation. METHODS: A Bayesian model with spatial smoothing was developed to regress ecologic health status data from the 2021 Australian Census against groups of explanatory covariates intended to represent mechanistic pathways. RESULTS: The prevalence of asthma in children aged 5 to 14 years averages 7.9%, 8.2%, 8.5%, and 7.6% in Sydney, Melbourne, Brisbane, and Perth, respectively. This small inter-city variation contrasts against marked intracity variation at the small-area level, which ranges from 6% to 12% between the least and most affected locations in each. Statistical variance decomposition on a subsample of Australian-born, nonindigenous children attributes 66% of the intracity spatial variation to the assembled covariates. Of these covariates, climatic and environmental factors contribute 30%, outdoor air pollution contributes 19%, and areal socioeconomic status contributes the remaining 51%. CONCLUSION: Geographic health inequalities in the prevalence of childhood asthma within Australia's largest cities reflect a complex interplay of factors, among which socioeconomic status is a principal determinant.
RESUMEN
Prevotella intermedia, a Gram-negative bacterium from the Bacteroidota phylum, is associated with periodontitis. Other species within this phylum are known to possess the general O-glycosylation system. The O-glycoproteome has been characterized in several species, including Tannerella forsythia, Porphyromonas gingivalis, and Flavobacterium johnsoniae. In our study, we used electron cryotomography (cryoET) and glycoproteomics to reveal the ultrastructure of P. intermedia and characterize its O-glycoproteome. Our cryoET analysis unveiled the ultrastructural details of the cell envelope and outer membrane vesicles (OMVs) of P. intermedia. We observed an electron-dense surface layer surrounding both cells and OMVs. The OMVs were often large (>200 nm) and presented two types, with lumens being either electron-dense or translucent. LC-MS/MS analyses of P. intermedia fractions led to the identification of 1655 proteins, which included 62 predicted T9SS cargo proteins. Within the glycoproteome, we identified 443 unique O-glycosylation sites within 224 glycoproteins. Interestingly, the O-glycosylation motif exhibited a broader range than reported in other species, with O-glycosylation found at D(S/T)(A/I/L/M/T/V/S/C/G/F/N/E/Q/D/P). We identified a single O-glycan with a delta mass of 1531.48 Da. Its sequence was determined by MS2 and MS3 analyses using both collision-induced dissociation and high-energy collisional dissociation fragmentation modes. After partial deglycosylation with trifluoromethanesulfonic acid, the O-glycan sequence was confirmed to be dHex-dHex-HexNAc (HPO3 -C6 H12 O5 )-dHex-Hex-HexA-Hex(dHex). Bioinformatic analyses predicted the localization of O-glycoproteins, with 73 periplasmic proteins, 53 inner membrane proteins, 52 lipoproteins, 26 outer membrane proteins, and 14 proteins secreted by the T9SS.
