Factors associated with psychological insulin resistance among patients with type 2 diabetes in China

ObjectiveThe aim of this study was to understand the psychological insulin resistance status among Chinese patients with type 2 diabetes and investigate its associated factors in these patients.MethodsA multi-stage stratified random sampling was performed to randomly select patients with type 2 diabetes from the eastern, central, and western regions in Shandong Province, China, and 660 valid questionnaires were collected. Psychological insulin resistance was assessed by the scale of My Opinion on Insulin (MOI). Factors associated with psychological insulin resistance were examined in a binary logistic model.ResultsFour-fifths of the patients with type 2 diabetes (82.1%) had psychological insulin resistance. Being female (OR = 1.770, 95% CI: 1.063–2.950, p < 0.05), having a monthly income of greater than 4,000 Renminbi (approximately $1,540) (OR = 0.444, 95% CI: 0.216–0.915, p < 0.05), living with type 2 diabetes for 11 years or more (OR = 0.387, 95% CI: 0.238–0.630, p < 0.05), self-rated poor health (OR = 1.706, 95% CI: 1.092–2.664, p < 0.05), and moderate discrimination against type 2 diabetes (OR = 1.924, 95% CI: 1.166–3.175, p < 0.05) were associated with psychological insulin resistance.ConclusionsThe prevalence of psychological insulin resistance among Chinese patients with type 2 diabetes is relatively high. Approaches are needed to address the issue of psychological insulin resistance of type 2 diabetes

Genome-Wide Identification, Sequence Variation, and Expression of the Glycerol-3-Phosphate Acyltransferase (GPAT) Gene Family in Gossypium

Cotton is an economically important crop grown for natural fiber and seed oil production. Cottonseed oil ranks third after soybean oil and colza oil in terms of edible oilseed tonnage worldwide. Glycerol-3-phosphate acyltransferase (GPAT) genes encode enzymes involved in triacylglycerol biosynthesis in plants. In the present study, 85 predicted GPAT genes were identified from the published genome data in Gossypium. Among them, 14, 16, 28, and 27 GPAT homologs were identified in G. raimondii, G. arboreum, G. hirsutum, and G. barbadense, respectively. Phylogenetic analysis revealed that a total of 108 GPAT genes from cotton, Arabidopsis and cacao could be classified into three groups. Furthermore, through comparison, the gene structure analyses indicated that GPAT genes from the same group were highly conserved between Arabidopsis and cotton. Segmental duplication could be the major driver for GPAT gene family expansion in the four cotton species above. Expression patterns of GhGPAT genes were diverse in different tissues. Most GhGPAT genes were induced or suppressed after salt or cold stress in Upland cotton. Eight GhGPAT genes were co-localized with oil and protein quantitative trait locus (QTL) regions. Thirty-two single nucleotide polymorphisms (SNPs) were detected from 12 GhGPAT genes, sixteen of which in nine GhGPAT genes were classified as synonymous, and sixteen SNPs in ten GhGPAT genes non-synonymous. Two SNP markers of the GhGPAT16 and GhGPAT26 genes were significantly correlated with cotton oil content in one of the three field tests. This study shed lights on the molecular evolutionary properties of GPAT genes in cotton, and provided reference for improvement of cotton response to abiotic stress and the genetic improvement of cotton oil content

Genome-Scale Analysis of the WRI-Like Family in Gossypium and Functional Characterization of GhWRI1a Controlling Triacylglycerol Content

Cotton (Gossypium spp.) is the most important natural fiber crop and the source of cottonseed oil, a basic by-product after ginning. AtWRI1 and its orthologs in several other crop species have been previously used to increase triacylglycerols in seeds and vegetative tissues. In the present study, we identified 22, 17, 9, and 11 WRI-like genes in G. hirsutum, G. barbadense, G. arboreum, and G. raimondii, respectively. This gene family was divided into four subgroups, and a more WRI2-like subfamily was identified compared with dicotyledonous Arabidopsis. An analysis of chromosomal distributions revealed that the 22 GhWRI genes were distributed on eight At and eight Dt subgenome chromosomes. Moreover, GhWRI1a was highly expressed in ovules 20–35 days after anthesis and was selected for further functional analysis. Ectopic expression of GhWRI1a rescued the seed phenotype of a wri1-7 mutant and increased the oil content of Arabidopsis seeds. Our comprehensive genome-wide analysis of the cotton WRI-like gene family lays a solid foundation for further studies

A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations

The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation

The Complexity and Entropy Analysis for Service Game Model Based on Different Expectations and Optimal Pricing

The internet has provided a new means for manufacturers to reach consumers. On the background of the widespread multichannel sales in China, based on a literature review of the service game and multichannel supply chain, this paper builds a multichannel dynamic service game model where the retailer operates an offline channel and the manufacturer operates an online channel and offers customers the option to buy online and pick up from the retailer’s store (BOPS). The manufacturer and the retailer take maximizing the channel profits as their business objectives and make channel service game under optimal pricing. We carry on theoretical analysis of the model and perform numerical simulations from the perspective of entropy theory, game theory, and chaotic dynamics. The results show that the stability of the system will weaken with the increase in service elasticity coefficient and that it is unaffected by the feedback parameter adjustment of the retailer. The BOPS channel strengthens the cooperation between the manufacturer and the retailer and moderates the conflict between the online and the offline channels. The system will go into chaotic state and cause the system’s entropy to increase when the manufacturer adjusts his/her service decision quickly. In a chaotic state, the system is sensitive to initial conditions and service input is difficult to predict; the manufacturer and retailer need more additional information to make the system clear or use the method of feedback control to delay or eliminate the occurrence of chaos

Genome-Wide Association Study of Major Agronomic Traits Related to Domestication in Peanut

Peanut (Arachis hypogaea) consists of two subspecies, hypogaea and fastigiata, and has been cultivated worldwide for hundreds of years. Here, 158 peanut accessions were selected to dissect the molecular footprint of agronomic traits related to domestication using specific-locus amplified fragment sequencing (SLAF-seq method). Then, a total of 17,338 high-quality single nucleotide polymorphisms (SNPs) in the whole peanut genome were revealed. Eleven agronomic traits in 158 peanut accessions were subsequently analyzed using genome-wide association studies (GWAS). Candidate genes responsible for corresponding traits were then analyzed in genomic regions surrounding the peak SNPs, and 1,429 genes were found within 200 kb windows centerd on GWAS-identified peak SNPs related to domestication. Highly differentiated genomic regions were observed between hypogaea and fastigiata accessions using FST values and sequence diversity (π) ratios. Among the 1,429 genes, 662 were located on chromosome A3, suggesting the presence of major selective sweeps caused by artificial selection during long domestication. These findings provide a promising insight into the complicated genetic architecture of domestication-related traits in peanut, and reveal whole-genome SNP markers of beneficial candidate genes for marker-assisted selection (MAS) in future breeding programs

The Association between Gut Microbiome and Pregnancy-Induced Hypertension: A Nested Case–Control Study

(1) Background: Pregnancy-induced hypertension (PIH) is associated with obvious microbiota dysbiosis in the third trimester of pregnancy. However, the mechanisms behind these changes remain unknown. Therefore, this study aimed to explore the relationship between the gut microbiome in early pregnancy and PIH occurrence. (2) Methods: A nested case–control study design was used based on the follow-up cohort. Thirty-five PIH patients and thirty-five matched healthy pregnant women were selected as controls. The gut microbiome profiles were assessed in the first trimester using metagenomic sequencing. (3) Results: Diversity analyses showed that microbiota diversity was altered in early pregnancy. At the species level, eight bacterial species were enriched in healthy controls: Alistipes putredinis, Bacteroides vulgatus, Ruminococcus torques, Oscillibacter unclassified, Akkermansia muciniphila, Clostridium citroniae, Parasutterella excrementihominis and Burkholderiales bacterium_1_1_47. Conversely, Eubacterium rectale, and Ruminococcus bromii were enriched in PIH patients. The results of functional analysis showed that the changes in these different microorganisms may affect the blood pressure of pregnant women by affecting the metabolism of vitamin K2, sphingolipid, lipid acid and glycine. (4) Conclusion: Microbiota dysbiosis in PIH patients begins in the first trimester of pregnancy, and this may be associated with the occurrence of PIH. Bacterial pathway analyses suggest that the gut microbiome might lead to the development of PIH through the alterations of function modules

Determination of the optimal dose reduction level via iterative reconstruction using 640-slice volume chest CT in a pig model.

To determine the optimal dose reduction level of iterative reconstruction technique for paediatric chest CT in pig models.27 infant pigs underwent 640-slice volume chest CT with 80kVp and different mAs. Automatic exposure control technique was used, and the index of noise was set to SD10 (Group A, routine dose), SD12.5, SD15, SD17.5, SD20 (Groups from B to E) to reduce dose respectively. Group A was reconstructed with filtered back projection (FBP), and Groups from B to E were reconstructed using iterative reconstruction (IR). Objective and subjective image quality (IQ) among groups were compared to determine an optimal radiation reduction level.The noise and signal-to-noise ratio (SNR) in Group D had no significant statistical difference from that in Group A (P = 1.0). The scores of subjective IQ in Group A were not significantly different from those in Group D (P>0.05). There were no obvious statistical differences in the objective and subjective index values among the subgroups (small, medium and large subgroups) of Group D. The effective dose (ED) of Group D was 58.9% lower than that of Group A (0.20±0.05mSv vs 0.48±0.10mSv, p <0.001).In infant pig chest CT, using iterative reconstruction can provide diagnostic image quality; furthermore, it can reduce the dosage by 58.9%