Characterization and stability assessment of polyphenols bound to Lycium barbarum polysaccharide: Insights from gastrointestinal digestion and colon fermentation.

Polysaccharides and polyphenols are biologically active components that coexist in Lycium barbarum fruit, and there may be interactions between them that affect the release of each other. In this study, polyphenols bound to L. barbarum polysaccharide (LBP) were characterized, and the stability of bound phenolics (BP) was assessed by gastrointestinal digestion and colon fermentation. The results showed that a total of 65 phytochemicals such as flavonoids, phenolic acids, and coumarins were identified by UPLC-MS/MS. Quantitative analysis revealed that the major phenolic constituents were rutin, p-coumaric acid, catechin, ferulic acid, protocatechuic acid, and gallic acid, and their contents were 58.72, 24.03, 14.24, 13.28, 10.39, and 6.7 mg GAE/100 g DW, respectively. The release of BP by gastric digestion and gastrointestinal digestion was 9.67 % and 19.39 %, respectively. Most polyphenols were greatly affected by gastric digestion, while rutin was released in small intestine. The BP were fully released (49.77 %) and metabolized by gut microorganisms, and a considerable number of intermediates and end-products were detected, such as phloroglucinol, phenylacetic acid, and phenyllactic acid. Microbiomics data emphasized the positive impact of LBP on gut bacteria of Bacteroides, Parabacteroides, and Clostridioides. These findings could deepen our understanding of the bioavailability and biological fate of BP and also provide reference data for nutrient release and utilization of L. barbarum as a whole.

Integrated global assessment of the natural forest carbon potential.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Burden of Common Neurologic Diseases in Asian Countries, 1990-2019: An Analysis for the Global Burden of Disease Study 2019.

BACKGROUND AND OBJECTIVES: Based on the Global Burden of Diseases, Injuries, and Risk Factors (GBD) study, neurologic disorders are a major cause of morbidity and mortality worldwide. However, there has been no comprehensive assessment of neurologic disorders in Asia. Data from the GBD 1990-2019 study were investigated to provide new details for neurologic disorders in Asia. METHODS: The burden of common neurologic disorders in Asia was calculated for 1990 and 2019 as incidence, prevalence, deaths, and disability-adjusted life-years (DALYs). Thirteen common neurologic disorders were analyzed. Data are presented as totals and by sex, age, year, location, risk factors, and sociodemographic index (SDI) and shown as counts and rates. RESULTS: In 2019, the most burdensome neurologic disorders in Asia for the absolute number of DALYs were stroke (98.8 million, 95% uncertainty interval [UI] 91.0-107.0), migraine (24.6 million, 95% UI 3.4-56.4), and Alzheimer disease (AD) and other dementias (13.5 million, 95% UI 5.9-29.8). From 1990 to 2019, the absolute number of DALYs and deaths caused by combined neurologic disorders (deaths by 60.7% and DALYs by 17.6%) increased, but the age-standardized rates (deaths by 34.1% and DALYs by 36.3%) decreased. The burden of neurologic disorders peaked among individuals aged 65-74 years and was higher among male than among female individuals; moreover, this burden varied considerably across Asian subregions and countries. Risk-attributable DALYs accounted for 86.9%, 28.5%, and 11.1% of DALYs for stroke, AD and other dementias, and multiple sclerosis, respectively. SDI was associated with both stroke and communicable neurological disorders. In terms of crude rate, the higher the SDI value, the higher the prevalence of stroke, and the lower all metrics of communicable neurological disorders. DISCUSSION: Neurologic disorders were the leading cause of DALYs and the second leading cause of deaths in Asia in 2019, and the burden may likely increase with the growth and aging of the Asian population. Urgent measures are needed for prevention, treatment, rehabilitation, and support services for common neurologic disorders regionally and nationally.

Exchange Rate Forecasting Based on Deep Learning and NSGA-II Models.

Today, the global exchange market has been the world's largest trading market, whose volume could reach nearly 5.345 trillion US dollars, attracting a large number of investors. Based on the perspective of investors and investment institutions, this paper combines theory with practice and creatively puts forward an innovative model of double objective optimization measurement of exchange forecast analysis portfolio. To be more specific, this paper proposes two algorithms to predict the volatility of exchange, which are deep learning and NSGA-II-based dual-objective measurement optimization algorithms for the exchange investment portfolio. Compared with typical traditional exchange rate prediction algorithms, the deep learning model has more accurate results and the NSGA-II-based model further optimizes the selection of investment portfolios and finally gives investors a more reasonable investment portfolio plan. In summary, the proposal of this article can effectively help investors make better investments and decision-making in the exchange market.

Trends in urban/rural inequalities in physical growth among Chinese children over three decades of urbanization in Guangzhou: 1985-2015.

BACKGROUND: Great growth inequalities between urban and rural areas have been reported in China over the past years. By examining urban/rural inequalities in physical growth among children < 7 years old over the past three decades from 1985 to 2015 in Guangzhou, we analyzed altering trends of anthropometric data in children and their association with economic development during the period of rapid urbanization in Guangzhou. METHODS: The height, body weight and nutrition status of children under 7 years old were obtained from two successive cross-sectional surveys and one health surveillance system. Student's t-test, Spearman's rank-order correlation and polynomial regression were used to assess the difference in physical growth between children in urban and rural areas and the association between socioeconomic index and secular growth changes. RESULTS: A height and weight difference was found between urban and rural children aged 0-6 years during the first two decades of our research (1985-2005), which gradually narrowed in both sex groups over time. By the end of 2015, elder boys (age group ≥5 year) and girls (age group ≥4 year) in rural areas were taller than their counterparts in urban areas (p < 0.05).The same trend could be witnessed in the weight of children aged 6 years, with a - 1.30 kg difference (P = 0.03) for boys, and a - 0.05 difference (P = 0.82) for girls. When GDP increased, the gap in boys' weight-for-age z-score (WAZ from 0.25 to 0.01) and height-for-age z-score (HAZ from 0.55 to 0.03) between urban and rural areas diminished, and disappeared when the GDP per capita (USD) approached 25,000. In either urban or rural areas, the urbanization rate and GDP were positively associated with the prevalence of obesity (all R > 0.90 with P < 0.05) and negatively correlated with the prevalence of stunted growth (all R < -0.87 with P < 0.05). CONCLUSION: Growth inequalities gradually decreased with economic development and urbanization, while new challenges such as obesity emerged. To eliminate health problems due to catch-up growth among rural children, comprehensive intervention programs for early child growth should be promoted in rural areas.