Data Mining in Networks of Differentially Expressed Genes during Sow Pregnancy

Small to moderate gains in Pig fertility can mean large returns in overall efficiency, and developing methods to improve it is highly desirable. High fertility rates depend on completion of successful pregnancies. To understand the molecular signals associated with pregnancy in sows, expression profiling experiments were conducted to identify differentially expressed genes in ovary and myometrium at different pregnancy periods using the Affymetrix Porcine GeneChipTM. A total of 974, 1800, 335 and 710 differentially expressed transcripts were identified in the myometrium during early pregnancy (EP) and late pregnancy (LP), and in the ovary during EP and LP, respectively. Self-Organizing Map (SOM) clusters indicated the differentially expressed genes belonged to 7 different functional groups. Based on BLASTX searches and Gene Ontology (GO) classifications, 129 unique genes closely related to pregnancy showed differential expression patterns. GO analysis also indicated that there were 21 different molecular function categories, 20 different biological process categories, and 8 different cellular component categories of genes differentially expressed during sow pregnancy. Gene regulatory network reconstruction provided us with an interaction model of known genes such as insulin-like growth factor 2 (IGF2) gene, estrogen receptor (ESR) gene, retinol-binding protein-4 (RBP4) gene, and several unknown candidate genes related to reproduction. Several pitch point genes were selected for association study with reproduction traits. For instance, DPPA5 g.363 T>C was found to associate with litter born weight at later parities in Beijing Black pigs significantly (p < 0.05). Overall, this study contributes to elucidating the mechanism underlying pregnancy processes, which maybe provide valuable information for pig reproduction improvement

Genome-wide Association Study of Porcine Hematological Parameters in a Large White × Minzhu F2 Resource Population

Hematological traits, which are important indicators of immune function in animals, have been commonly examined as biomarkers of disease and disease severity in humans and animals. Genome-wide significant quantitative trait loci (QTLs) provide important information for use in breeding programs of animals such as pigs. QTLs for hematological parameters (hematological traits) have been detected in pig chromosomes, although these are often mapped by linkage analysis to large intervals making identification of the underlying mutation problematic. Single nucleotide polymorphisms (SNPs) are the common form of genetic variation among individuals and are thought to account for the majority of inherited traits. In this study, a genome-wide association study (GWAS) was performed to detect regions of association with hematological traits in a three-generation resource population produced by intercrossing Large White boars and Minzhu sows during the period from 2007 to 2011. Illumina PorcineSNP60 BeadChip technology was used to genotype each animal and seven hematological parameters were measured (hematocrit (HCT), hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell count (RBC) and red blood cell volume distribution width (RDW)). Data were analyzed in a three step Genome-wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) method. A total of 62 genome-wide significant and three chromosome-wide significant SNPs associated with hematological parameters were detected in this GWAS. Seven and five SNPs were associated with HCT and HGB, respectively. These SNPs were all located within the region of 34.6-36.5 Mb on SSC7. Four SNPs within the region of 43.7-47.0 Mb and fifty-five SNPs within the region of 42.2-73.8 Mb on SSC8 showed significant association with MCH and MCV, respectively. At chromosome-wide significant level, one SNP at 29.2 Mb on SSC1 and two SNPs within the region of 26.0-26.2 Mb were found to be significantly associated with RBC and RDW, respectively. Many of the SNPs were located within previously reported QTL regions and appeared to narrow down the regions compared with previously described QTL intervals. In current research, a total of seven significant SNPs were found within six candidate genes SCUBE3, KDR, TDO, IGFBP7, ADAMTS3 and AFP. In addition, the KIT gene, which has been previously reported to relate to hematological parameters, was located within the region significantly associated with MCH and MCV and could be a candidate gene. These results of this study may lead to a better understanding of the molecular mechanisms of hematological parameters in pigs

Experimental Modelling for Allocating Recovery Facilities in the Metropolis: Integrated research between Circular Economy and Urban Spatial Structure

The primary aim of this project is to investigate an approach to integrate the study of CE with urban spatial structure, then form a tool to assist the procedure of decision-making by analyzing empirical data

Effects of cerium addition on the microstructure, mechanical properties and strain hardening behaviour of TWIP steel Fe-18Mn-0.6c

The effects of cerium (Ce) on the microstructure, mechanical properties and strain hardening behavior of Fe-18Mn-0.6C twin-induced plasticity (TWIP) steel were investigated by electron backscatter diffraction, X-ray diffraction and transmission electron microscopy. Compared with the addition of Al, the addition of Ce significantly reduced the stacking fault probability of TWIP steel, which promotes the formation of deformation and annealing twins. The dynamic strain aging behavior of TWIP steel was inhibited by Al and Ce atoms during ambient deformation. The optimal mechanical properties were obtained when 0.015 wt.% of Ce was added, resulting in a tensile strength of 1023MPa; and an elongation was 92%. The interaction of twin variants in the Ce-containing alloys exhibited an X shape, which was significantly different from the T shape in the non-Ce containing alloy. This is mainly attributed to the fact that Ce promotes dislocations near grain boundaries, where for the nucleation of deformation twins at grain boundaries is favored. Compared with the T-shaped twin variants, the dynamic Hall-Petch effect caused by the X-shaped staggered twin variants was stronger, which improved the strain hardening ability of TWIP steel

The Combination of Bioinformatics Analysis and Untargeted Metabolomics Reveals Potential Biomarkers and Key Metabolic Pathways in Asthma

Asthma is a complex chronic airway inflammatory disease that seriously impacts patients’ quality of life. As a novel approach to exploring the pathogenesis of diseases, metabolomics provides the potential to identify biomarkers of asthma host susceptibility and elucidate biological pathways. The aim of this study was to screen potential biomarkers and biological pathways so as to provide possible pharmacological therapeutic targets for asthma. In the present study, we merged the differentially expressed genes (DEGs) of asthma in the GEO database with the metabolic genes obtained by Genecard for bioinformatics analysis and successfully screened out the metabolism-related hub genes (HIF1A, OCRL, NNMT, and PER1). Then, untargeted metabolic techniques were utilized to reveal HDM-induced metabolite alterations in 16HBE cells. A total of 45 significant differential metabolites and 5 differential metabolic pathways between the control group and HDM group were identified based on the OPLS-DA model. Finally, three key metabolic pathways, including glycerophospholipid metabolism, galactose metabolism, and alanine, aspartate, and glutamate metabolism, were screened through the integrated analysis of bioinformatics data and untargeted metabolomics data. Taken together, these findings provide valuable insights into the pathophysiology and targeted therapy of asthma and lay a foundation for further research

Green Approach for Post-industrial Urban Regeneration: A case of Economic and Technical Development Zone, China

For cities facing post-industrial transition, urban greenways are proven strategies to activate urban spaces and improve the sustainability of cities. However, significant challenges remain when seeking to link greenways as a greenway network and integrate greenway networks to urban spaces. Given this shortcoming, Yantai National Economic and Technical Development Zone (YEDZ) was selected as a representative case. This paper analyzed the potential role of greenway network and requirements of post-industrial development for the urban environment. It seeks to develop a regeneration approach that integrating urban greenway planning with overall urban reform. Our priorities are providing a pedestrian network with non-utilitarian rhythms by activating former industrial spaces, restructuring urban green spaces, and integrating greenway networks into diverse urban spaces. In this way, it reveals the comprehensive benefits of the urban greenway network and improves overall urban form - multiple benefits, including economic development and social rewards, be created in the regeneration.</p

CogSimulator: A Model for Simulating User Cognition &amp; Behavior with Minimal Data for Tailored Cognitive Enhancement

The interplay between cognition and gaming, notably through educational games enhancing cognitive skills, has garnered significant attention in recent years. This research introduces the CogSimulator, a novel algorithm for simulating user cognition in small-group settings with minimal data, as the educational game Wordle exemplifies. The CogSimulator employs Wasserstein-1 distance and coordinates search optimization for hyperparameter tuning, enabling precise few-shot predictions in new game scenarios. Comparative experiments with the Wordle dataset illustrate that our model surpasses most conventional machine learning models in mean Wasserstein-1 distance, mean squared error, and mean accuracy, showcasing its efficacy in cognitive enhancement through tailored game design

Fabrication and Characterization of Superhydrophobic Al-Based Surface Used for Finned-Tube Heat Exchangers

Enhancing the heat transfer performance of heat exchangers is one of the main methods to reduce energy consumption and carbon emissions in heating, ventilation, air-conditioning and refrigeration (HVAC&amp;R) systems. Wettability modified surfaces developed gradually may help. This study aims to improve the performance of heat exchangers from the perspective of component materials. The facile and cost-effective fabrication method of superhydrophobic Al-based finned-tube heat exchangers with acid etching and stearic acid self-assembly was proposed and optimized in this study, so that the modified Al fins could achieve stronger wettability and durability. The effect of process parameters on the wettability of the Al fins was by response surface methodology (RSM) and variance analysis. Then, the modified fins were characterized by field-emission scanning electron microscopy (FE-SEM), 3D topography profiler, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR), respectively. The durability of the superhydrophobic fins was investigated by air exposure, corrosion resistance, and mechanical robustness experiments. The RSM and variance analysis demonstrated that a water contact angle (WCA) of 166.9&deg; can be obtained with the etching time in 2 mol/L HCl solution of 10.5 min, the self-assembly time in the stearic acid ethanol solution of 48 h, and drying under 73.0 &deg;C. The surface morphology showed suitable micro-nano structures with a mean roughness (Ra) of 467.58 nm and a maximum peak-to-valley vertical distance (Rt) of 4.095 &mu;m. The chemical component demonstrated the self-assembly of an alkyl chain. The WCAs declined slightly in durability experiments, which showed the feasibility of the superhydrophobic heat exchangers under actual conditions