Spatio-Temporal Variation and Influencing Factors of the Coupling Coordination Degree of Production-Living-Ecological Space in China

Territorial space is a multi-functional complex. The coordinated production-living-ecological space (PLES) effectively coordinates the man-land relationship, promotes regional sustainable development, and maximizes territorial space. How to build a high-quality national spatial layout and support system for development has become a hot topic of concern in all sectors of society. However, few studies have explored the coupling coordination considering the various production-living-ecological functions of land use type and its influencing factors of PLES at the county scale in China. To address the gap, based on the connotation of PLES theory, this study established a classification and evaluation system for PLES and analyzed the spatio-temporal characteristics, coupling coordination degree, spatial autocorrelation, and influencing factors of PLES in China from 2000 to 2020. The results are as follows: (1) The production space index and living space index in China showed a continuous increase tendency, while the ecological space index decreased continuously during the study period. The production space and living space were concentrated in the east of Hu Line, and the ecological space indexes in mountainous areas were significantly higher than those in plain areas during the study period. (2) The gravity centers of PLES all migrated to the west of China to different degrees during the study period. (3) From 2000 to 2020, the basically balanced category was the main coupling coordination type, and the number of seriously unbalanced categories accounted for the least. In the west of the Hu Line, the seriously unbalanced category was dominant, while in the east of the Hu Line were the moderately unbalanced categories and above. (4) During the study period, the low-low type was the main relationship type, widely distributed in western China, followed by the high-high type, mainly situated in the North China Plain, Yangtze River Delta, Pearl River Delta, Jianghan Plain, Chengdu Plain, Northeast China Plain, and some provincial capital cities. (5) Regression results showed that natural factors were the main reason restricting the coordinated development of PLES, and socioeconomic factors could effectively promote the coordinated development of PLES. Landscape pattern also significantly influenced the coordinated development of PLES, but varied greatly. The findings of this study can provide a scientific reference for the optimization of territorial space layout and the promotion of high-quality development of territorial space

The Alteration of Carnitine Metabolism in Second Trimester in GDM and a Nomogram for Predicting Macrosomia

Objective. The metabolism of three major nutrients (sugar, lipid, and protein) will change during pregnancy, especially in the second trimester. The present study is aimed at evaluating carnitine alteration in fatty acid metabolism in the second trimester of pregnancy and the correlation between carnitine and GDM. Methods. 450 pregnant women were recruited in the present prospective study. Metabolic profiling of 31 carnitines was detected by LC-MS/MS in these women. Correlation between carnitine metabolism and maternal and neonatal complication with GDM was analyzed. Results. We found the levels of 7 carnitines increased in age>35, BMI≥30, weight gain>20 kg, and ART pregnant groups, but the level of free carnitine (C0) decreased. Nine carnitines were specific metabolites of GDM. Prepregnancy BMI, weight gain, and carnitines (C0, C3, and C16) were independent risk factors associated with GDM and related macrosomia. C0 was negatively correlated with FBG, LDL, TG, and TC. A nomogram was developed for predicting macrosomia in GDM based on carnitine-related metabolic variables. Conclusion. The carnitine metabolism in the second trimester is abnormal in GDM women. The dysfunction of carnitine metabolism is closely related to the abnormality of blood lipid and glucose in GDM. Carnitine metabolism abnormality could predict macrosomia complicated with GDM