Search

OBJECTIVE To investigate three features of dietary cooking oil intake, namely, the consumption, cooking style, and composition of fatty acids in relation to several cardiometabolic measurements in an elderly Chinese population. METHODS The elderly (≥ 65 years) participants for this study were recruited from two community health centers in the urban area of Shanghai. A questionnaire was administered to collect information on dietary oil consumption (low, medium and high) and cooking styles (fry or stir-fry vs. others) and the composition of fatty acids (poly-unsaturated vs. mono-unsaturated). The cardiometabolic measurements included anthropometry, blood pressure, fasting plasma glucose and serum lipids. RESULTS The 1186 study participants had a mean age of 70.9 ± 5.4 years. The mean dietary oil consumption was 35.0 g/d, being low (< 25 g/d), medium (25-49 g/d) and high (≥ 50 g/d) in 485,467 and 234 participants, respectively. The proportion of the fry or stir-fry cooking style and oils rich in mono-unsaturated fatty acids was 30.4% and 27.4%, respectively. Both before and after adjustment for sex, age, current smoking and alcohol intake, dietary oil consumption was significantly (P ≤ 0.02) and positively associated with the prevalence of treated hypertension and fasting plasma glucose concentration. With similar adjustments as above and additional adjustment for dietary oil consumption, the fry or stir-fry cooking style was significantly (P ≤ 0.048) and positively associated with body mass index, but inversely with systolic and diastolic blood pressure and serum low-density lipoprotein cholesterol, and the dietary intake of oils rich in mono-unsaturated fat acids was significantly (P ≤ 0.02) and positively associated with diastolic blood pressure, serum triglycerides, total cholesterol and low-density lipoprotein cholesterol, and the prevalence of hypertriglyceridemia and hypercholesterolemia. CONCLUSIONS This study showed that both the consumption and composition of fatty acids of the dietary oils mattered with regard to several cardiometabolic measurements in an elderly Chinese population. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is considered a preclinical stage of Alzheimer's disease (AD). People with MCI have a higher risk of developing dementia than healthy people. As one of the risk factors for MCI, stroke has been actively treated and intervened. Therefore, selecting the high-risk population of stroke as the research object and discovering the risk factors of MCI as early as possible can prevent the occurrence of MCI more effectively. Methods: The Boruta algorithm was used to screen variables, and eight machine learning models were established and evaluated. The best performing models were used to assess variable importance and build an online risk calculator. Shapley additive explanation is used to explain the model. Results: A total of 199 patients were included in the study, 99 of whom were male. Transient ischemic attack (TIA), homocysteine, education, hematocrit (HCT), diabetes, hemoglobin, red blood cells (RBC), hypertension, prothrombin time (PT) were selected by Boruta algorithm. Logistic regression (AUC = 0.8595) was the best model for predicting MCI in high-risk groups of stroke, followed by elastic network (ENET) (AUC = 0.8312), multilayer perceptron (MLP) (AUC = 0.7908), extreme gradient boosting (XGBoost) (AUC = 0.7691), and support vector machine (SVM) (AUC = 0.7527), random forest (RF) (AUC = 0.7451), K-nearest neighbors (KNN) (AUC = 0.7380), decision tree (DT) (AUC = 0.6972). The importance of variables suggests that TIA, diabetes, education, and hypertension are the top four variables of importance. Conclusion: Transient ischemic attack (TIA), diabetes, education, and hypertension are the most important risk factors for MCI in high-risk groups of stroke, and early intervention should be performed to reduce the occurrence of MCI. [ABSTRACT FROM AUTHOR]

BACKGROUND: The diamondback moth (DBM), Plutella xylostella (Lepidoptera: Plutellidae), is a notorious pest of cruciferous plants. In temperate areas, annual populations of DBM originate from adult migrants. However, the source populations and migration trajectories of immigrants remain unclear. Here, we investigated migration trajectories of DBM in China using genome-wide single nucleotide polymorphisms (SNPs) genotyped using double-digest RAD (ddRAD) sequencing. We first analyzed patterns of spatial and temporal genetic structure among southern source and northern recipient populations, then inferred migration trajectories into northern regions using discriminant analysis of principal components (DAPC), assignment tests, and spatial kinship patterns. RESULTS: Temporal genetic differentiation among populations was low, indicating that sources of recipient populations and migration trajectories are stable. Spatial genetic structure indicated three genetic clusters in the southern source populations. Assignment tests linked northern populations to the Sichuan cluster, and central–eastern populations to the southern and Yunnan clusters, indicating that Sichuan populations are sources of northern immigrants and southern and Yunnan populations are sources of central–eastern populations. First-order (full-sib) and second-order (half-sib) kin pairs were always found within populations, but ∼ 35–40% of third-order (cousin) pairs were found in different populations. Closely related individuals in different populations were found at distances of 900–1500 km in ∼ 35–40% of cases, while some were separated by > 2000 km. CONCLUSION: This study unravels seasonal migration patterns in the DBM. We demonstrate how careful sampling and population genomic analyses can be combined to help understand cryptic migration patterns in insects. [ABSTRACT FROM AUTHOR]

Background: The Chinese white wax scale, Ericerus pela Chavannes is economically significant for its role in wax production. This insect has been bred in China for over a thousand years. The wax secreted by the male scale insect during the secondinstar larval stage has been widespread used in wax candle production, wax printing, engraving, Chinese medicine, and more recently in the chemical, pharmaceutical, food, and cosmetics industries. However, little is known about the mechanisms responsible for white wax biosynthesis. The characterization of its larval transcriptome may promote better understanding of wax biosynthesis. Methodology/Principal Findings: In this study, characterization of the transcriptome of E. pela during peak wax secretion was performed using Illumina sequencing technology. Illumina sequencing produced 41,839 unigenes. These unigenes were annotated by blastx alignment against the NCBI Non-Redundant (NR), Swiss-Prot, KEGG, and COG databases. A total of 104 unigenes related to white wax biosynthesis were identified, and 15 of them were selected for quantitative real-time PCR analysis. We evaluated the variations in gene expression across different development stages, including egg, first/second instar larvae, male pupae, and male and female adults. Then we identified five genes involved in white wax biosynthesis. These genes were expressed most strongly during the second-instar larval stage of male E. pela. Conclusion/Significance: The transcriptome analysis of E. pela during peak wax secretion provided an overview of gene expression information at the transcriptional level and a resource for gene mining. Five genes related to white wax biosynthesis were identified. [ABSTRACT FROM AUTHOR]

Background: The pine shoot beetle Tomicus yunnanensis (Coleoptera: Scolytinae) is an economically important pest of Pinus yunnanensis in southwestern China. Developed resistance to insecticides due to chemical pesticides being used for a long time is a factor involved in its serious damage, which poses a challenge for management. In addition, highly efficient adaptation to divergent environmental ecologies results in this pest posing great potential threat to pine forests. However, the molecular mechanisms remain unknown as only limited nucleotide sequence data for this species is available. Methodology/Principal Findings: In this study, we applied next generation sequencing (Illumina sequencing) to sequence the adult transcriptome of T. yunnanensis. A total of 51,822,230 reads were obtained. They were assembled into 140,702 scaffolds, and 60,031 unigenes. The unigenes were further functionally annotated with gene descriptions, Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genome (KEGG). In total, 80,932 unigenes were classified into GO, 13,599 unigenes were assigned to COG, and 33,875 unigenes were found in KO categories. A biochemical pathway database containing 219 predicted pathways was also created based on the annotations. In depth analysis of the data revealed a large number of genes related to insecticides resistance and heat shock protein genes associated with environmental stress. Conclusions/Significance: The results facilitate the investigations of molecular resistance mechanisms to insecticides and environmental stress. This study lays the foundation for future functional genomics studies of important biological questions of this pest. [ABSTRACT FROM AUTHOR]

Part I. Provides information on Cordyceps sinensis Sacc., a fungus highly valued in China as a tonic food and herbal medicine that provides lung protection and kidney improvement. Concepts of the kidney and lung in traditional Chinese medicine; Description of Cordyceps; Information on preclinical studies on the effects of Cordyceps.

The article presents a study which aimed to examine the monoterpenes and some chemical constituents from Inula japonica's aerial parts. Collection of the aerial parts of Inula japonica in Anhui, China was carried out. Results indicate the structure elucidation and isolation of various monoterpenes and some chemical constituents through Inula japonica's aerial parts.

Ganoderma lucidum (GL, or Reishi) and green tea have been used as folk medicines in China for cancer prevention and adjuvant therapy. Screening of commercial GL products showed that ReishiMax (RM) is superior to other commercial products in inhibiting cancer malignancy (Sliva, J Altern Compl Med 2003, 9:491). RM or Tegreen (TG; containing >98% tea polyphenols) inhibits the proliferation, colony formation, migration and invasive behaviors of human breast cancer cells (Silva, Acta Pharmacol Sinica 2006, suppl. 1:338). The inhibitory effects were enhanced profoundly by combining RM & TG. Chemical comparisons showed higher amounts of triterpenes and polysaccharides and more triterpene species in RM. Immune profiling demonstrated that RM enhances proliferations of macrophages, B, T and NK lymphocytes. It increases serum IgA, IgG & IgM, and IL2 secretion, but decreases IL5 secretion. In vivo studies were conducted to confirm the synergistic effects of the 2 anti-cancer herbs in cancer mice inoculated with S180 sarcoma cells. Treatment with RM+TG for 12 days delayed the death of S180-innoculated mice and reduced the death risk in this early malignant phase after S180-inoculation, compared to controls. The data demonstrates synergy in vivo of RM and TG in anti-sarcoma, suggesting potential therapeutic values for cancer prevention and adjuvant cancer treatment in humans. [ABSTRACT FROM AUTHOR]