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Air pollution is a major concern issue on Macao since the concentration levels of several of the most common pollutants are frequently above the internationally recommended values. The low air quality episodes impacts on human health paired with highly populated urban areas are important motivations to develop forecast methodologies in order to anticipate pollution episodes, allowing establishing warnings to the local community to take precautionary measures and avoid outdoor activities during this period. Using statistical methods (multiple linear regression (MLR) and classification and regression tree (CART) analysis) we were able to develop forecasting models for the main pollutants (NO2, PM2.5, and O3) enabling us to know the next day concentrations with a good skill, translated by high coefficients of determination (0.82–0.90) on a 95% confidence level. The model development was based on six years of historical data, 2013 to 2018, consisting of surface and upper-air meteorological observations and surface air quality observations. The year of 2019 was used for model validation. From an initially large group of meteorological and air quality variables only a few were identified as significant dependent variables in the model. The selected meteorological variables included geopotential height, relative humidity and air temperature at different altitude levels and atmospheric stability characterization parameters. The air quality predictors used included recent past hourly levels of mean concentrations for NO2 and PM2.5 and maximum concentrations for O3. The application of the obtained models provides the expected daily mean concentrations for NO2 and PM2.5 and maximum hourly concentrations O3 for the next day in Taipa Ambient air quality monitoring stations. The described methodology is now operational, in Macao, since 2020.
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Fish body mucus plays a protective role, especially in Halobatrachus didactylus, which inhabits intertidal zones vulnerable to anthropogenic contaminants. In silico predicted bioactive peptides were identified in its body mucus, namely, EDNSELGQETPTLR (HdKTLR), DPPNPKNL (HdKNL), PAPPPPPP (HdPPP), VYPFPGPLPN (HdVLPN), and PFPGPLPN (HdLPN). These peptides were studied in vitro for bioactivities and aggregation behavior under different ionic strengths and pH values. Size exclusion chromatography revealed significant peptide aggregation at 344 mM and 700 mM ionic strengths at pH 7.0, decreasing at pH 3.0 and pH 5.0. Although none exhibited antimicrobial properties, they inhibited Pseudomonas aeruginosa biofilm formation. Notably, HdVLPN demonstrated potential antioxidant activity (ORAC: 1.560 mu mol TE/mu mol of peptide; ABTS: 1.755 mu mol TE/mu mol of peptide) as well as HdLPN (ORAC: 0.195 mu mol TE/mu mol of peptide; ABTS: 0.128 mu mol TE/mu mol of peptide). Antioxidant activity decreased at pH 5.0 and pH 3.0. Interactions between the peptides and mucus synergistically enhanced antioxidant effects. HdVLPN and HdLPN were non-toxic to Caco-2 and HaCaT cells at 100 mu g of peptide/mL. HdPPP showed potential antihypertensive and antidiabetic effects, with IC50 values of 557 mu g of peptide/mL for ACE inhibition and 1700 mu g of peptide/mL for alpha-glucosidase inhibition. This study highlights the importance of validating peptide bioactivities in vitro, considering their native environment (mucus), and bioprospecting novel bioactive molecules while promoting species conservation.
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The investigation of pharmaceuticals as emerging contaminants in marine biota has been insufficient. In this study, we examined the presence of 51 pharmaceuticals in edible oysters along the coasts of the East and South China Seas. Only nine pharmaceuticals were detected. The mean concentrations of all measured pharmaceuticals in oysters per site ranged from 0.804 to 15.1 ng g–1 of dry weight, with antihistamines being the most common. Brompheniramine and promethazine were identified in biota samples for the first time. Although no significant health risks to humans were identified through consumption of oysters, 100–1000 times higher health risks were observed for wildlife like water birds, seasnails, and starfishes. Specifically, sea snails that primarily feed on oysters were found to be at risk of exposure to ciprofloxacin, brompheniramine, and promethazine. These high risks could be attributed to the monotonous diet habits and relatively limited food sources of these organisms. Furthermore, taking chirality into consideration, chlorpheniramine in the oysters was enriched by the S-enantiomer, with a relative potency 1.1–1.3 times higher when chlorpheniramine was considered as a racemate. Overall, this study highlights the prevalence of antihistamines in seafood and underscores the importance of studying enantioselectivities of pharmaceuticals in health risk assessments.
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