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1.
J Sci Food Agric ; 104(2): 572-582, 2024 Jan 30.
Article in English | MEDLINE | ID: mdl-37650308

ABSTRACT

Pumpkin seed oil (PSO), a rich source of nutrients, is extracted from the seeds of different pumpkin varieties for food and medicines. This article aims to provide an evidence-based review of the literature and to explore the extraction technologies, nutritional properties, and biological activity of PSO. From previous literature, PSO contains a large proportion of unsaturated fatty acids, with linoleic acid as the main component, and an amount of tocopherol, phytosterol, and phenolic acids. Some differences in the yield, composition, and physicochemical properties of PSO can be associated with the pumpkin's cultivars and the extraction methods. Some novel technologies involved in supercritical fluid extraction, enzyme-assisted aqueous extraction, and ultrasound-assisted extraction have been replacing the conventional technologies gradually as promising methods for the safe, non-polluting, and effective recovery of PSO. This healthy vegetable oil was reported by several in vitro and in vivo studies to have potential protective roles in oxidative stress, inflammation, cancer, and cardiovascular diseases. © 2023 Society of Chemical Industry.


Subject(s)
Cucurbita , Cucurbita/chemistry , Fatty Acids/chemistry , Tocopherols/analysis , Antioxidants/chemistry , Seeds/chemistry , Plant Oils/chemistry
2.
Environ Sci Technol ; 57(46): 18282-18295, 2023 Nov 21.
Article in English | MEDLINE | ID: mdl-37114869

ABSTRACT

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.


Subject(s)
Air Pollutants , Air Pollution , Deep Learning , Inorganic Chemicals , Air Pollutants/analysis , Reproducibility of Results , Respiratory Aerosols and Droplets , Particulate Matter/analysis , Inorganic Chemicals/analysis , China , Seasons , Environmental Monitoring/methods , Aerosols/analysis , Air Pollution/analysis
3.
Wei Sheng Yan Jiu ; 52(6): 965-971, 2023 Nov.
Article in Zh | MEDLINE | ID: mdl-38115662

ABSTRACT

OBJECTIVE: To investigate the effects of the concentration of fine particulate matter(PM_(2.5)) on the risk of death among residents in an urban area of Chongqing, China. METHODS: Daily data on mean PM_(2.5) concentration, meteorological factors(air temperature and relative humidity), and the number of deaths from 2013 to 2020 in this urban area were collected. A generalized additive model was used to analyze the association of PM_(2.5) concentration with the number of deaths, and stratified analyses by sex and age were further performed. RESULTS: In this area from 2013 to 2020, the median concentration of atmospheric ambient PM_(2.5) was 44.00 µg/m~3; 48 089 non-accidental deaths, 19 252 deaths from circulatory diseases, and 8753 deaths from respiratory diseases were reported. The PM_(2.5) concentration was higher in winter and spring. The number of deaths showed no obvious seasonal changes. The time series analysis showed that for every 10 µg/m~3 increase in the PM_(2.5) concentration, the risks of non-accidental death(lag03), circulatory diseases-caused death(lag3), and respiratory diseases-caused death(lag03) increased by 0.64%(95% CI 0.07%-1.21%), 0.68%(95% CI 0.05%-1.32%) and 1.72%(95% CI 0.54%-2.90%), respectively. After adjusting for several gaseous pollutants(PM_(10), NO_2, O_3, SO_2 and CO), the impact of PM_(2.5) concentration on residents' health had no significant changes. The stratified analyses by sex and age showed that when the PM_(2.5) concentration increased, the risks of non-accidental death and death from respiratory diseases were higher in women and residents aged ≥65 years than in men and higher in residents aged ≥65 years than in those aged 5-64 years, but there were no significant differences between the groups. CONCLUSION: PM_(2.5) pollution may increase the risk of death for residents in this urban area in Chongqing.


Subject(s)
Air Pollutants , Air Pollution , Cardiovascular Diseases , Respiratory Tract Diseases , Male , Humans , Female , Particulate Matter/adverse effects , Particulate Matter/analysis , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Time Factors , China/epidemiology , Environmental Exposure/adverse effects , Environmental Exposure/analysis
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