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This study aimed to evaluate the epidemiological, clinical and mycological characteristics of invasive candidiasis (IC) in China. A ten-year retrospective study including 183 IC episodes was conducted in a tertiary hospital in Beijing, China. The overall incidence of IC from 2010–2019 was 0.261 episodes per 1,000 discharges. Candidemia (71.0%) was the major infective pattern; 70.3% of the patients tested positive for Candida spp. colonization before IC and the median time to develop an invasive infection after colonization was 13.5 days (interquartile range: 4.5–37.0 days). Candida albicans (45.8%) was the most prevalent species, followed by Candida parapsilosis (19.5%), Candida glabrata (14.2%) and Candida tropicalis (13.7%). C. non-albicans IC was more common in patients with severe anemia (P = 0.018), long-term hospitalization (P = 0.015), hematologic malignancies (P = 0.002), continuous administration of broad-spectrum antibiotics (P < 0.001) and mechanical ventilation (P = 0.012). In vitro resistance testing showed that 11.0% of the Candida isolates were resistant/non-wild type (non-WT) to fluconazole, followed by voriconazole (9.6%), micafungin (3.8%), and caspofungin (2.9%). Fluconazole was the most commonly used drug to initiate antifungal therapy both before and after the proven diagnosis (52.6% and 54.6%, respectively). The 30-day and 90-day all-cause mortality rates were 24.5% and 32.7%, respectively. The incidence of IC has declined in the recent five years. C. non-albicans contributed to more than half of the IC cases. Fluconazole can be used as first-line therapy if resistant strains are not prevalent. Prospective, multi-center surveillance of the clinical and mycological characteristics of IC is required. [ABSTRACT FROM AUTHOR]

Epidemiological studies have consistently linked exposure to PM 2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM 2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM 2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM 2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM 2.5 , including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM 2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM 2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM 2.5 mass concentrations (µgm-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM 2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM 2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM 2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM 2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM 2.5 and how they affect both PM 2.5 OP and the concentrations of particle-bound reactive oxygen species. [ABSTRACT FROM AUTHOR]