The Importance of Fatty Acid Precision Nutrition: Effects of Dietary Fatty Acid Composition on Growth, Hepatic Metabolite, and Intestinal Microbiota in Marine Teleost Trachinotus ovatus.

Our recent study demonstrated that diet with blend oil (named BO1) as lipid, which is designed on the base of essential fatty acid requirement of Trachinotus ovatus, achieved good performance. Here, to confirm its effect and investigate the mechanism, three isonitrogenous (45%) and isolipidic (13%) diets (D1-D3) only differing in dietary lipids, which were, respectively, fish oil (FO), BO1, and blend oil 2 (BO2) consisting of FO and soybean oil at 2 : 3, were formulated and used to feed the T. ovatus juveniles (average initial weight: 7.65 g) for 9 weeks. The results showed that the weight gain rate of fish fed D2 was higher than that of fish fed D3 (P < 0.05) and had no significant difference from that of fish fed D1 (P > 0.05). Correspondingly, compared with the D3 group, fish of the D2 group exhibited better oxidative stress parameters such as lower serum malondialdehyde content and inflammatory indexes in the liver such as the lower expression level of genes encoding four interleukin proteins and tumor necrosis factor α, as well as higher hepatic immune-related metabolites such as valine, gamma-aminobutyric acid, pyrrole-2-carboxylic acid, tyramine, l-targinine, p-synephrine, and butyric acid (P < 0.05). Furthermore, the intestinal probiotic (Bacillus) proportion was significantly higher, while the pathogenic bacteria (Mycoplasma) proportion was significantly lower in the D2 group than that in the D3 group (P < 0.05). The main differential fatty acids of diet D2 were close to those of D1, while the levels of linoleic acid and n-6 PUFA, as well as the ratio of DHA/EPA of D3, were higher than those of D1 and D2. These results indicated that the better performance of D2 such as enhancing growth, reducing oxidative stress, and improving immune responses and intestinal microbial communities in T. ovatus may be mainly due to the good fatty acid composition of BO1, which indicated the importance of fatty acid precision nutrition.

A critical assessment of provincial-level variation in agricultural GHG emissions in China.

China is a world leader on agriculture production; with only 8% of global cropland it feeds 20% of the world's population. However, the increasing production capacity comes with the cost of greenhouse gas (GHG) emissions. As a populous country with the highest GHG emissions in the world, determining how to achieve the dual goals of mitigating climate change and ensuring food security is of great significance for the agricultural sector. This requires assessing the spatial variation in agricultural greenhouse gases (GHGs) and their drivers. In this study, we conduct a spatial assessment of agricultural GHGs at the provincial level in China for the years 1997-2017, and then explore the effects of related factors on GHG emissions using a geographically weighted regression (GWR) model. The results suggest the following. 1) There have always been significant interprovincial variations, whether in the total amount, structure, intensity, or per capita level of agricultural GHG emissions. 2) The directions of the effects of selected factors on GHG intensity fall broadly into three categories: negative effects (urbanization, intensity of agricultural practices, and agricultural structure), positive effects (agricultural investment and cropland endowments), and mixed effects, with factors leading to reductions in some provinces and increases in others (economic level, frequency and intensity of disasters, and the level of mechanization). 3) The magnitude of the effects varies by factor and also by province. The results suggest synergetic province- or state-specific reduction policies in agricultural GHG for China, as well as for other developing and emerging economies.

Testing the impact of first-mover advantage on household energy-related carbon emissions: an exploratory study from six urban agglomerations in China.

The household sector has become the second-largest source of energy consumption and CO2 emissions in China. It is important to understand the trends and changing mechanisms of household energy-related CO2 emissions (HECEs) in different social stages for mitigating the impact of climate change. However, the existing trends in HECEs and whether they are congruent with the expectation that HECEs in later developed areas are lower than those in priority areas under the same economic level are unclear. Here, we compared the per capita HECEs (PHECEs) of urban agglomerations under the same economic standards and analyzed the causes of the comparative results. We find that (1) HECEs increased rapidly from 3.65 × 108 t to 12.42 × 108 t during 1995-2017, with an average annual growth rate of 14.19%; (2) urban agglomerations that developed earlier do not have higher PHECEs. The PHECEs of urban agglomerations with moderate and later development do not decrease under increased social, technological, and cognitive conditions; (3) carbon intensity (CI), energy intensity (EI), and per capita regional gross domestic product (PCG) have a positive impact on PHECEs, and the potential impact of EI on PHECEs reduction is greater; (4) the effects of CI, EI, and PCG on PHECEs in different urban agglomerations are various. However, these effects are similar within urban agglomerations. Our study provides a reference for reducing CO2 emissions in the household sector and for the green development of urban agglomerations and emphasizes that the growth of HECE at a reasonable level is necessary when technology does not meet sufficient constraints.

Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China.

The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial-temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran's I index indicates that China's carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.

Spatio-Temporal Comprehensive Measurements of Chinese Citizens' Health Levels and Associated Influencing Factors.

Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens' health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens' health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China's various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens' health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast-southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens' health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens' health status. The Engel coefficient, urban-rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens' health levels, these three factors have played important roles in hindering the improvements of citizen health.