Polymorphism in Growth Hormone Gene and its Association with Growth Traits in Siniperca chuatsi

Growth hormone (GH) is a candidate gene for growth traits in fish. In this study, we assessed associations between single nucleotide polymorphisms (SNPs) in GH gene with growth traits in 357 Siniperca chuatsi individuals using high-resolution melting. Two SNPs were identified in GH gene, with one mutation in exon 5 (g.5045T>C), and one mutation in intron 5 (g.5234T>G). The corrections analysis of SNPs with the four growth traits was carried out using General Linear Model (GLM) estimation. Results showed that both of them were significantly associated with growth performance in S. chuatsi. For g.5234T>G, it was significantly associated with body weight (P＜0.01), body length (P＜0.05), body depth (P＜0.01), and body width (P＜0.01), and the individuals of genotype GG grew faster than those of genotypes TT and TG (P＜0.05). A further diplotype-trait association analysis confirmed that in fish with H3H2 (TC-GG) diplotype body weight, body length, and body width was greater than in those with other diplotypes (P＜0.05). These results demonstrated GH gene SNPs could be used as potential genetic markers in future marker assisted selection of S. chuatsi

A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management

ObjectiveThis study aimed to establish a risk prediction model for diabetic retinopathy (DR) in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators and to propose suggestions for chronic disease management.MethodsThis multi-centered retrospective cross-sectional study was conducted among 2,385 patients with T2DM. The predictors of the training set were, respectively, screened by extreme gradient boosting (XGBoost), a random forest recursive feature elimination (RF-RFE) algorithm, a backpropagation neural network (BPNN), and a least absolute shrinkage selection operator (LASSO) model. Model I, a prediction model, was established through multivariable logistic regression analysis based on the predictors repeated ≥3 times in the four screening methods. Logistic regression Model II built on the predictive factors in the previously released DR risk study was introduced into our current study to evaluate the model’s effectiveness. Nine evaluation indicators were used to compare the performance of the two prediction models, including the area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, F1 score, balanced accuracy, calibration curve, Hosmer-Lemeshow test, and Net Reclassification Index (NRI).ResultsWhen including predictors, such as glycosylated hemoglobin A1c, disease course, postprandial blood glucose, age, systolic blood pressure, and albumin/urine creatinine ratio, multivariable logistic regression Model I demonstrated a better prediction ability than Model II. Model I revealed the highest AUROC (0.703), accuracy (0.796), precision (0.571), recall (0.035), F1 score (0.066), Hosmer-Lemeshow test (0.887), NRI (0.004), and balanced accuracy (0.514).ConclusionWe have built an accurate DR risk prediction model with fewer indicators for patients with T2DM. It can be used to predict the individualized risk of DR in China effectively. In addition, the model can provide powerful auxiliary technical support for the clinical and health management of patients with diabetes comorbidities

Negative Regulation of Schistosoma japonicum Egg-Induced Liver Fibrosis by Natural Killer Cells

The role of natural killer (NK) cells in infection-induced liver fibrosis remains obscure. In this study, we elucidated the effect of NK cells on Schistosoma japonicum (S. japonicum) egg-induced liver fibrosis. Liver fibrosis was induced by infecting C57BL/6 mice with 18–20 cercariae of S. japonicum. Anti-ASGM1 antibody was used to deplete NK cells. Toll-like receptor 3 ligand, polyinosinic-polycytidylic acid (poly I∶C) was used to enhance the activation of NK cells. Results showed that NK cells were accumulated and activated after S. japonicum infection, as evidenced by the elevation of CD69 expression and IFN-γ production. Depletion of NK cells markedly enhanced S. japonicum egg-induced liver fibrosis. Administration of poly I∶C further activated NK cells to produce IFN-γ and attenuated S. japonicum egg-induced liver fibrosis. The observed protective effect of poly I∶C on liver fibrosis was diminished through depletion of NK cells. Disruption of IFN-γ gene enhanced liver fibrosis and partially abolished the suppression of liver fibrosis by poly I∶C. Moreover, expression of retinoic acid early inducible 1 (RAE 1), the NKG2D ligand, was detectable at high levels on activated hepatic stellate cells derived from S. japonicum-infected mice, which made them more susceptible to hepatic NK cell killing. In conclusion, our findings suggest that the activated NK cells in the liver after S. japonicum infection negatively regulate egg-induced liver fibrosis via producing IFN-γ, and killing activated stellate cells

The application of improved differential evolution algorithm in electromagnetic fracture monitoring

  Hydraulic fracturing is a pivotal technology in the development of unconventional tight reservoirs, in which accurate monitoring of fracture parameters is significant. This paper proposes an improved differential evolution algorithm (EMDE) to calculate the Effective Propped Volume (EPV) accurately. The forward simulation results demonstrate that when the transmitting source plane is in a particular position, the relationship between signals and a specific parameter is the most obvious, providing a basis for the application of inversion algorithms. Furthermore, the difference between the population center and the individual is added to accelerate the convergence of the EMDE algorithm. A simplified selection strategy of the simulated annealing algorithm is used to enhance the convergence speed and the ability to find the global optimal value of the objective function simultaneously. The one-stage and two-stages inversion strategies are designed to calculate the parameters. In the two-stage inversion, the second-stage is constrained by the forward simulation and the first-stage results. It indicates that the errors of the two-stages inversion can be controlled within 5%. Through the inversion simulation proposed in this paper, the feasibility of the electromagnetic method to monitor the EPV is verified, and it provides a theoretical guidance for subsequent fracturing construction adjustments.Cited as: Qi, J., Zhang, L., Zhang, K., Li, L., Sun, J. The application of improved differential evolution algorithm in electromagnetic fracture monitoring. Advances in Geo-Energy Research, 2020, 4(3): 233-246, doi: 10.46690/ager.2020.03.0

Oxygen Consumption and Lethal Dissolved Oxygen Level of Hybrids of Siniperca chuatsi♀ × S. scherzeri♂

Oxygen consumption rate (OCR) and lethal dissolved oxygen levels (DO) of the hybrids (225.3 ± 4.6 g) of Siniperca chuatsi ♀ × S. scherzeri ♂, were determined after acclimating the fish to 15, 20, 26 and 30°C for 20 days. The same parameters were measured for hybrids with different body weight (146.8 ± 6.3 g, 234.3 ± 8.4 g, 273.9 ± 3.3 g, 327 ± 5.1 g) at 26 °C. OCR increased significantly (P <0.05) with increasing acclimation temperature between 20-26°C, and decreased with increasing body weight. Final preferred temperature estimated from the Q10 was between 26-30°C. The lethal DO concentration for the hybrids at 30°C was significantly higher (P <0.05) than at other temperatures. OCR over the daily cycle under natural lighting conditions was also determined at 26°C. It showed a circadian rhythm with the lowest point at 0830 and peak rates at 1430. Results show that the hybrid has a higher stress tolerance and higher stocking density than the female parent S. chuatsi and indicate their culture potential in subtropical freshwater regions

Effects of Loading Frequency and Loading Type on High-Cycle and Very-High-Cycle Fatigue of a High-Strength Steel

High-cycle and very-high-cycle fatigue tests via rotary bending (52.5 Hz), electromagnetic resonance (120 Hz) axial cycling, and ultrasonic (20 kHz) axial cycling were performed for a high-strength steel with three heat treatment conditions, and the effects of loading frequency and loading type on fatigue strength and fatigue life were investigated. The results revealed that the loading frequency effect is caused by the combined response of strain rate increase and induced temperature rise. A parameter &eta; was proposed to judge the occurrence of loading frequency effect, and the calculated results were in agreement with the experimental data. In addition, a statistical method based on the control volume was used to reconcile the effect of loading type, and the predicted data were consistent with the experimental results

Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment

Abstract Background Previous studies have demonstrated that high-density lipoprotein cholesterol (HDL-C) plays an anti-atherosclerosis role through reverse cholesterol transport. Several studies have validated the efficacy and safety of natural products in treating atherosclerosis (AS). However, the study of raising HDL-C levels through natural products to treat AS still needs to be explored. Methods The gene sets associated with AS were collected and identified by differential gene analysis and database query. By constructing a protein–protein interaction (PPI) network, the core submodules in the network are screened out. At the same time, by calculating node importance (Nim) in the PPI network of AS disease and combining it with Kyoto Encyclopedia of genes and genomes (KEGG) pathways enrichment analysis, the key target proteins of AS were obtained. Molecular docking is used to screen out small natural drug molecules with potential therapeutic effects. By constructing an in vitro foam cell model, the effects of small molecules on lipid metabolism and key target expression of foam cells were investigated. Results By differential gene analysis, 451 differential genes were obtained, and a total of 313 disease genes were obtained from 6 kind of databases, then 758 AS-related genes were obtained. The enrichment analysis of the KEGG pathway showed that the enhancement of HDL-C level against AS was related to Lipid and atherosclerosis, Cholesterol metabolism, Fluid shear stress and atherosclerosis, PPAR signaling pathway, and other pathways. Then we intersected 31 genes in the core module of the PPI network, the top 30 genes in Nims, and 32 genes in the cholesterol metabolism pathway, and finally found 3 genes. After the above analysis and literature collection, we focused on the following three related gene targets: APOA1, LIPC, and CETP. Molecular docking showed that Genistein has a good binding affinity for APOA1, CETP, and LIPC. In vitro, experiments showed that Genistein can up-regulated APOA1, LIPC, and CETP levels. Conclusions Based on our research, Genistein may have the effects of regulating HDL-C and anti-atherosclerosis. Its mechanism of action may be related to the regulation of LIPC, CETP, and APOA1 to improve lipid metabolism

Interpreting the Molecular Mechanisms of Yinchenhao Decoction on Hepatocellular Carcinoma through Absorbed Components Based on Network Pharmacology

To investigate the mechanisms through which Yinchenhao decoction (YCHD) inhibits hepatocellular carcinoma (HCC), we analyzed YCHD ingredients absorbed into the bloodstream by using network pharmacology. We conducted a weighted gene coexpression network analysis on gene expression data collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases to derive an HCC gene set; moreover, we used four online prediction system databases to predict the potential targets of YCHD ingredients absorbed into the bloodstream. We discovered that YCHD directly interfered with 17 HCC-related disease targets. Subsequent gene ontology enrichment analyses of these 17 disease targets revealed that YCHD exhibited effects through 17 biological processes, 7 molecular functions, and 9 cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated 14 pathways through which YCHD inhibits HCC. We observed similar trends in how the 17 small molecules interfered with the key target set. We surmised that YCHD inhibits HCC by regulating inflammatory and metabolic pathways. Network pharmacological analysis of YCHD ingredients absorbed into the bloodstream may provide new insights and serve as a new method for discovering the molecular mechanisms through which YCHD inhibits HCC

Spatial Variation in Bacterioplankton Communities in the Pearl River, South China: Impacts of Land Use and Physicochemical Factors

River ecosystems are critical for human and environmental health, with bacterioplankton playing a vital role in biogeochemical cycles. Unveiling the spatial patterns of bacterioplankton communities in relation to environmental factors is important for understanding the processes of microbial variation and functional maintenance. However, our understanding of the correlations among bacterioplankton communities, physicochemical factors, and land use, especially in large rivers affected by intensive anthropogenic activities, remains relatively poor. Here, we investigated the bacterioplankton communities in July 2018 in three main tributaries of the Pearl River, i.e., Beijiang, Xijiang, and Pearl River Delta, based on 16S rRNA high-throughput sequencing. Results showed that the most dominant phyla, Proteobacteria, Actinobacteria, Cyanobacteria, and Planctomycetes accounted for 33.75%, 22.15%, 11.65%, and 10.48% of the total abundance, respectively. The bacterioplankton communities showed remarkable differences among the three tributaries in terms of composition, structure, diversity, and predictive functional profiles. Mantel and partial Mantel tests revealed that the bacterioplankton communities were affected by physicochemical variables (p &lt; 0.01) and land use (p &lt; 0.01). Redundancy analysis identified specific conductivity, dissolved oxygen, agricultural land, ammonium, urban land, and water transparency as the dominant environmental factors influencing the bacterioplankton communities in the Pearl River. Variation partitioning analysis indicated that both physicochemical factors and land use had direct effects on the bacterioplankton community, and that land use may also shape bacterioplankton communities through indirect effects of physicochemical factors on riverine ecosystems. This study provides fundamental information on the diversity, spatial patterns, and influencing factors of bacterioplankton communities in the Pearl River, which should enhance our understanding of how such communities change in response to environmental gradients and anthropogenic activities

Distilled Spirits Lees Ash as Cement Additive

The voluminous generation of distilled spirits lees (DSL) in China presents a challenge for proper disposal and potential environmental pollution. In an effort to address this issue, this study aimed to find a resourceful solution for DSL utilization. The application of incinerated rice husk ash as a mortar supplementary material in cement provides an innovative solution for the disposal of DSL. Five samples of distilled spirits lees ash (DSLA) were produced using both muffle furnace (MF) and fluidized bed (FB) combustion at different temperatures. The properties of DSLA were characterized through measurements of specific surface area and observations using scanning electron microscopy (SEM). Mortar specimens were prepared by replacing 10% of cement with DSLA, and strength tests were conducted. The SEM results revealed the crisscross mesh structures in the DSLA samples. Additionally, the findings indicated a strong connection between the specific surface areas and the micromorphology. In this work, all DSLA samples, except for the one produced in FB at 800 °C, could improve compressive and flexural strengths in the prepared mortar specimens and were suitable for employment as cement additives