Search

The exploration of active ingredients and new activities of industrial crops could expand their scope of applications. Liriodendron chinense (L. chinense), an important ornamental and economic forest tree in China, has been widely used in timber, medicine and landscape. Flavonoids are major constituents of L. chinense leaves, while their effects of preventing brain damage are still unclear. In this study, flavonoids from L. chinense leaves (LCLF) were obtained through AB-8 resin chromatography and UPLC-MS/MS assay indicated that 16 compounds were identified from LCLF. LCLF treatment showed significant scavenging activities against DPPH•, ABTS•+, •OH, FRAP and total reducing power. D-galactose-impaired exploratory behaviors, cognitive functions and histopathological alterations in hippocampus of mice were obviously recovered by LCLF administration. Network pharmacology results demonstrated that LCLF could produce the healing efficacy through multiple pathways, mostly related to oxidative stress and inflammation. Further i n vivo experiments revealed that LCLF treatment could regulated MDA content, SOD, CAT and GSH-Px activity, as well as the production of inflammatory factors (NO, IL-1β and IL-6). The underlying mechanisms of LCLF were probably related to Nrf2/HO-1, NF-κB and AMPK/SIRT1 pathways. Molecular docking results and surface plasmon resonance analysis validated that especially hesperidin in LCLF had strong binding activities with all 8 genes in the mentioned pathways. Our study revealed the beneficial effects of LCLF on oxidative activity and D-galactose-induced brain injury, offering experimental support for its potential application in pharmaceutical and other industries. [Display omitted] • LCLF was a flavonoid-rich fraction from L. chinense leaves. • LCLF showed significant scavenging capacities against different radicals. • LCLF prevented D-galactose-induced brain injuries via AMPK/SIRT1-mediated Nrf2/HO-1 and NF-κB pathways. • Hesperidin in LCLF had strong binding activities with 8 genes in the mentioned pathways. [ABSTRACT FROM AUTHOR]

As lung cancer becomes a primary source of death in China, investigation on incidence rate, death rate, and disability-adjusted life years (DALYs) is of great significance to optimize prevention measures and allocation of healthcare resources. We utilized data from the Global Burden of Disease (GBD) database to evaluate the incidence rate, death rate, and DALYs of lung cancer in China from 1990 to 2019. Analysis of lung cancer risk factor-related death rate and DALYs was performed. Age-standardized rates (ASR) and estimated annual percentage change (EAPC) were calculated. The incidence trend of lung cancer from 2020 to 2034 was predicted by the Nordpred age-period-cohort (APC) model. Age-standardized incidence rate (ASIR) increased from 30.2/100000 (95 % UI 26.2–34.3) in 1990 to 41.7/100000 (95 % UI 35.2–48.8) in 2019, and EAPC was 1.33 (95 % CI 1.16–1.49). From 1990 to 2019, men were noted for the highest incidence rate, death rate, and DALYs rate across three age groups (15–49 years, 50–69 years, and over 70). During this period, the ASIR of lung cancer in females was always lower than that in males. The predominant risk factors of lung cancer were smoking, air pollution, and diet, among which smoking was the most significant one. The analysis results showed that new cases and deaths may increase in the following 15 years since 2020 in the context of lung cancer. Faced with the heavy burden of lung cancer, China must issue corresponding policies and roll out prevention avenues against smoking and air pollution. [ABSTRACT FROM AUTHOR]

Unprecedented urbanization in China has directly resulted in residential vacancies, which has seriously stunted sustainable development, a part of China's new-type urbanization plan. Understanding the various types and mixes of residential vacancies is critical for the advancement of our knowledge of speculative urbanism and for devising vacancy-mitigation policies, but this issue remains insufficiently studied. Using municipal water consumption data, this study proposes a feasible and general-purpose framework for providing innovative insights into the variability in residential vacancies at the household level and the mixture of residential vacancies at the building level. This framework was applied to the city of Changshu, China, and four categories of vacant residences at the household level were identified: seasonally vacant residences, long-term vacant residences, newly built residences and occasionally vacant residences. The first category is closely related to tourism and seasonal industries, while the last three exhibit a Matthew effect. In addition to revealing significant and intensifying spatial clustering and three patterns of changes in vacancy mixtures (i.e., emergence, disappearance, and increases or decreases), the results identify particular types of vacant residences at the building level (e.g., extremely low-entropy long-term multihousehold buildings). The insights from this study can contribute to devising customized policies for alleviating residential vacancies. • The proposed framework reveals variability in and mixtures among residential vacancies using municipal water consumption. • The document representations of vacant residences are extracted based on the vacant residence corpus and Doc2Vec method. • Four categories of vacant residences at the household level are identified using the Doc2Vec and K-means++ methods. • Seasonally vacant residences are closely related to tourism and seasonal industries. • Long-term, newly built and occasionally vacant residences exhibit a Matthew effect. [ABSTRACT FROM AUTHOR]

Reducing water use and relieving negative environmental consequences contribute to regional water and ecological sustainability. This work examined water resource efficiency (WRE) and the effects of effective crop water use from the perspective of the water footprint. WRE was defined as the ratio of consumptive field water use (CWU) to the total crop water footprint (CWF), including the blue water footprint applied (BWFA), green water footprint (GWF), and grey water footprint (GYWF). WRE for the cultivation of the main crops (rice, wheat, maize, beans, and tubers) produced in China during the period of 1996–2015 was determined from estimates of provincial CWFs and CWUs. The results show that national CWF was estimated as 678.5 Gm³, of which GWF comprised 55.1%; the national crop CWU was approximately 455.6 Gm³ in the period considered, and this included 82.1% green and 17.9% blue water. The spatial patterns of CWF and CWU densities differed greatly but were stable over time, with increasing trends exhibited from 1996 to 2015. The national WRE for crops was 0.672, and that for beans was 0.869, an efficiency larger than that of any other crop. The indices for rice and wheat were approximately 0.630. WRE cannot be replaced by the global efficiency (GEF) or generalized efficiency (GE) indices, either for scientific evaluations or for considerations of spatial distributions. This study aids in the evaluation of effective water resource consumption by considering the process of agricultural water use, and also the impact of crop production on water quality and quantity. Hence, WRE is an advanced indicator linking measurements of water footprint with assessments of crop management and the sustainability of regional water resources. [Display omitted] • Water resources effectiveness (WRE) was assessed from the water footprint perspective. • WRE was 0.672 and varied among crops in grain production of China. • It's needs to reduce crop water footprint and improve WRE in rice production of China. • WRE is an improvement of agricultural water use efficiency evaluation index system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Long-term daily NO 2 are derived for post-policy evaluation and exposure assessment. • A common modeling approach (Base-RF) gives biased estimation in back-extrapolation. • We propose a novel approach named RBE-RF for the bias correction. • Average NO 2 levels for China in 2011 can be underestimated by 22.4% by Base-RF. • National population exposed to NO 2 > 40 µg/m3 is 18.5% by Base-RF and 33.0% by RBE-RF. Long-term surface NO 2 data are essential for retrospective policy evaluation and chronic human exposure assessment. In the absence of NO 2 observations for Mainland China before 2013, training a model with 2013–2018 data to make predictions for 2005–2012 (back-extrapolation) could cause substantial estimation bias due to concept drift. This study aims to correct the estimation bias in order to reconstruct the spatiotemporal distribution of daily surface NO 2 levels across China during 2005–2018. On the basis of ground- and satellite-based data, we proposed the robust back-extrapolation with a random forest (RBE-RF) to simulate the surface NO 2 through intermediate modeling of the scaling factors. For comparison purposes, we also employed a random forest (Base-RF), as a representative of the commonly used approach, to directly model the surface NO 2 levels. The validation against Taiwan's NO 2 observations during 2005–2012 showed that RBE-RF adequately corrected the substantial underestimation by Base-RF. The RMSE decreased from 10.1 to 8.2 µg/m3, 7.1 to 4.3 µg/m3, and 6.1 to 2.9 µg/m3 in predicting daily, monthly, and annual levels, respectively. For North China with the most severe pollution, the population-weighted NO 2 ([NO 2 ] pw) during 2005–2012 was estimated as 40.2 and 50.9 µg/m3 by Base-RF and RBE-RF, respectively, i.e., 21.0% difference. While both models predicted that the national annual [NO 2 ] pw increased during 2005–2011 and then decreased, the interannual trends were underestimated by >50.2% by Base-RF relative to RBE-RF. During 2005–2018, the nationwide population that lived in the areas with NO 2 > 40 µg/m3 were estimated as 259 and 460 million by Base-RF and RBE-RF, respectively. With RBE-RF, we corrected the estimation bias in back-extrapolation and obtained a full-coverage dataset of daily surface NO 2 across China during 2005–2018, which is valuable for environmental management and epidemiological research. [ABSTRACT FROM AUTHOR]