Capturing the Spectrum of Interaction Effects in Genetic Association Studies by Simulated Evaporative Cooling Network Analysis

Evidence from human genetic studies of several disorders suggests that interactions between alleles at multiple genes play an important role in influencing phenotypic expression. Analytical methods for identifying Mendelian disease genes are not appropriate when applied to common multigenic diseases, because such methods investigate association with the phenotype only one genetic locus at a time. New strategies are needed that can capture the spectrum of genetic effects, from Mendelian to multifactorial epistasis. Random Forests (RF) and Relief-F are two powerful machine-learning methods that have been studied as filters for genetic case-control data due to their ability to account for the context of alleles at multiple genes when scoring the relevance of individual genetic variants to the phenotype. However, when variants interact strongly, the independence assumption of RF in the tree node-splitting criterion leads to diminished importance scores for relevant variants. Relief-F, on the other hand, was designed to detect strong interactions but is sensitive to large backgrounds of variants that are irrelevant to classification of the phenotype, which is an acute problem in genome-wide association studies. To overcome the weaknesses of these data mining approaches, we develop Evaporative Cooling (EC) feature selection, a flexible machine learning method that can integrate multiple importance scores while removing irrelevant genetic variants. To characterize detailed interactions, we construct a genetic-association interaction network (GAIN), whose edges quantify the synergy between variants with respect to the phenotype. We use simulation analysis to show that EC is able to identify a wide range of interaction effects in genetic association data. We apply the EC filter to a smallpox vaccine cohort study of single nucleotide polymorphisms (SNPs) and infer a GAIN for a collection of SNPs associated with adverse events. Our results suggest an important role for hubs in SNP disease susceptibility networks. The software is available at http://sites.google.com/site/McKinneyLab/software

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction

Click-Through Rate (CTR) prediction is one of the most important machine learning tasks in recommender systems, driving personalized experience for billions of consumers. Neural architecture search (NAS), as an emerging field, has demonstrated its capabilities in discovering powerful neural network architectures, which motivates us to explore its potential for CTR predictions. Due to 1) diverse unstructured feature interactions, 2) heterogeneous feature space, and 3) high data volume and intrinsic data randomness, it is challenging to construct, search, and compare different architectures effectively for recommendation models. To address these challenges, we propose an automated interaction architecture discovering framework for CTR prediction named AutoCTR. Via modularizing simple yet representative interactions as virtual building blocks and wiring them into a space of direct acyclic graphs, AutoCTR performs evolutionary architecture exploration with learning-to-rank guidance at the architecture level and achieves acceleration using low-fidelity model. Empirical analysis demonstrates the effectiveness of AutoCTR on different datasets comparing to human-crafted architectures. The discovered architecture also enjoys generalizability and transferability among different datasets

Influence of installation height of a submersible mixer on solid‒liquid two‒phase flow field

With the increasingly severe situation of water pollution control, optimal design of the mixing flow field of submersible mixers and improving the mixing uniformity of activated sludge have become key research issues. At present, the research on the submersible mixer is mostly focused on water as the medium, and the flow field characteristics of solid-liquid two-phase flow, which is closer to the actual scene, still need more systematic research. This paper presented numerical simulations of the solid‒liquid two‒phase flow problem at various installation heights based on the coupled CFD‒DEM method in the Euler‒Lagrange framework. The velocity distribution, dead zone distribution, particles’ velocity development, particles’ mixing degree, and particles’ aggregation of the flow field were compared and analyzed for different installation heights. The results show that the flow field has two flow patterns: single‒ and double‒circulation, due to different installation heights, in which the velocity and turbulent kinetic energy of the flow field of the double‒circulation flow pattern are more uniform. The installation height affects the moment particles enter the impeller and the core jet zone, thus affecting the degree of particle mixing and the mixing time. The adjustment of the installation height also has an impact on particle aggregation. These findings indicate that the installation height significantly affects the flow field characteristics and the particle motion distribution. The coupled CFD‒DEM method can analyze the macroscopic phenomenon of the solid‒liquid two‒phase flow field of the submersible mixer from the scale of microscopic particles, which provides a theoretical approach for the optimal design of the mixing flow field. It can provide better guidance for engineering practice

A study on the multi-objective optimization method and characteristic analysis of installation locations of submersible mixer for sewage

In this study, the performance of submersible mixers in sewage treatment was improved by optimizing the installation position parameters of the mixer. The aim was to enhance the average flow velocity and mixing efficiency in the pool. The study employed ISIGHT software, integrated with Creo Parametric 6.0 software and ANSYS Workbench 2020 software, to analyze the factors affecting mean flow velocity and completed a multi-objective optimized design using Non-dominated Sorting Genetic Algorithm (NSGA-II). The study used the ISIGHT software to analyze the factors affecting mean flow velocity in the pool. The installation position parameters of the submersible mixer were selected as design variables. The study employed Creo Parametric 6.0 software to create a three-dimensional model of the pool and the submersible mixer. ANSYS Workbench 2020 software was used to simulate fluid flow in the pool. The Non-dominated Sorting Genetic Algorithm (NSGA-II) was used for multi-objective optimization. The results of the study indicated an increase of approximately 0.021 m/s in average flow velocity and an improvement of approximately 0.47% in mixing efficiency compared to pre-optimization values. The effective axial propulsion distance and effective radial diffusion radius were significantly increased by 6.71% and 8.33%, respectively, after optimization. The fluid distribution in the pool became more uniform, and the low-speed zone was greatly reduced, resulting in an enhanced flow state of the fluid in the pool and a strengthened mixing effect. The study provides insights into the control of the submersible mixer’s installation position to improve the average flow velocity inside the pool. Automatic optimization of submersible mixer installation locations using the ISIGHT software can effectively improve mixing efficiency, overall plant operating efficiency, and economic benefits in sewage treatment plants. The multi-objective optimization platform based on the ISIGHT platform for wastewater treatment mixer installation location can be successfully applied in engineering practice

Fibroblast growth factor (FGF21) protects mouse liver against D-galactose-induced oxidative stress and apoptosis via activating Nrf2 and PI3K/Akt pathways

FGF21 is recently discovered with pleiotropic effects on glucose and lipid metabolism. However, the potential protective effect of FGF21 against D-gal-induced injury in the liver has not been demonstrated. The aim of this study is to investigate the pathophysiological role of FGF21 on hepatic oxidative injury and apoptosis in mice induced by D-gal. The 3-month-old Kunming mice were subcutaneously injected with D-gal (180 mg kg(-1) d(1)) for 8 weeks and administered simultaneously with FGF21 (5 or 1 mg kg(-1) d(1)). Our results showed that the administration of FGF21 significantly alleviated histological lesion including structure damage, degeneration, and necrosis of hepatocytes induced by D-gal, and attenuated the elevation of liver injury markers, serum AST, and ALP in a dosedependent manner. FGF21 treatment also suppressed D-galinduced profound elevation of ROS production and oxidative stress, as evidenced by an increase of the MDA level and depletion of the intracellular GSH level in the liver, and restored the activities of antioxidant enzymes SOD, CAT, GSH-Px, and T-AOC. Moreover, FGF21 treatment increased the nuclear abundance of Nrf2 and subsequent up regulation of several antioxidant genes. Furthermore, a TUNEL assay showed that D-gal-induced apoptosis in the mouse liver was significantly inhibited by FGF21. The expression of caspase-3 was markedly inhibited by the treatment of FGF21 in the liver of D-gal-treated mice. The levels of PI3K and PBK/Akt were also largely enhanced, which in turn inactivated pro-apoptotic signaling events, restoring the balance between pro-and anti-apoptotic Bcl-2 and Bax proteins in the liver of D-gal-treated mice. In conclusion, these results suggest that FGF21 protects the mouse liver against D-gal-induced hepatocyte oxidative stress via enhancing Nrf2-mediated antioxidant capacity and apoptosis via activating PI3K/Akt pathway

National wetland mapping in China: a new product resulting from object-based and hierarchical classification of Landsat 8 OLI images

Spatially and thematically explicit information of wetlands is important to understanding ecosystem functions and services, as well as for establishment of management policy and implementation. However, accurate wetland mapping is limited due to lacking an operational classification system and an effective classification approach at a large scale. This study was aimed to map wetlands in China by developing a hybrid object-based and hierarchical classification approach (HOHC) and a new wetland classification system for remote sensing. Application of the hybrid approach and the wetland classification system to Landsat 8 Operational Land Imager data resulted in a wetland map of China with an overall classification accuracy of 95.1%. This national scale wetland map, so named CAS_Wetlands, reveals that China’s wetland area is estimated to be 451,084 ± 2014 km2, of which 70.5% is accounted by inland wetlands. Of the 14 sub-categories, inland marsh has the largest area (152,429 ± 373 km2), while coastal swamp has the smallest coverage (259 ± 15 km2). Geospatial variations in wetland areas at multiple scales indicate that China’s wetlands mostly present in Tibet, Qinghai, Inner Mongolia, Heilongjiang, and Xinjiang Provinces. This new map provides a new baseline data to establish multi-temporal and continuous datasets for China’s wetlands and biodiversity conservation

Expression of miR-425-5p in Pancreatic Carcinoma and Its Correlation with Tumor Immune Microenvironment

Background: Pancreatic carcinoma (PC) is a global health threat with a high death rate. miRNAs are implicated in tumor initiation and progression. This study explored the expression of miR-425-5p in PC patients and its correlation with tumor immune microenvironment (TIME). Method: miR-425-5p expression in cancer tissues and adjacent non-tumor tissues of PC patients was examined by RT-qPCR. The levels of immune cells and cytokines were measured by flow cytometry and ELISA. The correlation of miR-425-5p with TNM stage and TIME was assessed by Spearman method. The death of PC patients was recorded through 36-month follow-ups. The prognosis of patients was assessed by Kaplan-Meier curves. Results: miR-425-5p expression was upregulated in PC tissues and elevated with increasing TNM stage. miR-425-5p expression was positively correlated with TNM stage. The PC tissues had decreased levels of CD3+, CD4+, CD8+, and natural killer (NK) cells, CD4+/CD8+ ratio, IL-2, and INF-γ, but increased levels of Tregs, IL-4, IL-10, and TGF-β. miR-425-5p level in cancer tissues was positively correlated with Tregs/IL-10/TGF-β, but negatively related to CD3+/CD4+/CD8+/NK cells and IL-2/INF-γ. Moreover, high miR-425-5p expression predicted a poor prognosis in PC patients. Conclusion: miR-425-5p is upregulated in PC patients and is prominently associated with the TIME, and high miR-425-5p predicts a poor prognosis in PC patients

Microporous Aluminophosphate ULM-6: Synthesis, NMR Assignment, and Its Transformation to AlPO4-14 Molecular Sieve

A pure fluorinated aluminophosphate [A1(8)P(8)O(32)F(4)center dot(C3H12N2)(2)(H2O)(2)] (ULM-6) has been synthesized via an aminothermal strategy, in which triisopropanolamine (TIPA) is used as the solvent together with the addition of propyleneurea and HF. The C-13 NMR spectrum demonstrates that 1,3-diaminopropane, the in situ decomposer of propyleneurea, is the real structure-directing agent (SDA) for ULM-6 crystals. The local Al, P, and F environments of the dehydrated ULM-6 are investigated by 1D and 2D solid-state NMR spectroscopy. The spatial proximities are extracted from F-19{Al-27}, F-19{P-31}, Al-27-{F-19}, and P-31{F-19} rotational-echo double resonance (REDOR) NMR experiments as well as F-19 -> P-31 heteronuclear correlation (HETCOR) NMR and {P-31}Al-27 HMQC NMR experiments, allowing a full assignment of all the F-19, Al-27, and P-31 resonances to the corresponding crystallographic sites. Moreover, it is found that the structure of ULM-6 is closely related to that of AIPO(4)-14. A combination of high-temperature powder XRD, thermal analysis, and F-19 NMR reveals that the removal of fluorine atoms at higher temperature is crucial to the phase transformation of ULM-6 to AlPO4-14. The calcined product shows high CO2/CH4 and CO2/N-2 selectivity with ratios of 15.5 and 29.1 (101 kPa, 25 degrees C), respectively

Transcriptome Dynamic Analysis Reveals New Candidate Genes Associated with Resistance to Fusarium Head Blight in Two Chinese Contrasting Wheat Genotypes

In recent years, Fusarium head blight (FHB) has developed into a global disease that seriously affects the yield and quality of wheat. Effective measures to solve this problem include exploring disease-resistant genes and breeding disease-resistant varieties. In this study, we conducted a comparative transcriptome analysis to identify the important genes that are differentially expressed in FHB medium-resistant (Nankang 1) and FHB medium-susceptible (Shannong 102) wheat varieties for various periods after Fusarium graminearum infection using RNA-seq technology. In total, 96,628 differentially expressed genes (DEGs) were identified, 42,767 from Shannong 102 and 53,861 from Nankang 1 (FDR 1). Of these, 5754 and 6841 genes were found to be shared among the three time points in Shannong 102 and Nankang 1, respectively. After inoculation for 48 h, the number of upregulated genes in Nankang 1 was significantly lower than that of Shannong 102, but at 96 h, the number of DEGs in Nankang 1 was higher than that in Shannong 102. This indicated that Shannong 102 and Nankang 1 had different defensive responses to F. graminearum in the early stages of infection. By comparing the DEGs, there were 2282 genes shared at the three time points between the two strains. GO and KEGG analyses of these DEGs showed that the following pathways were associated with disease resistance genes: response to stimulus pathway in GO, glutathione metabolism, phenylpropanoid biosynthesis, plant hormone signal transduction, and plant–pathogen interaction in KEGG. Among them, 16 upregulated genes were identified in the plant–pathogen interaction pathway. There were five upregulated genes, TraesCS5A02G439700, TraesCS5B02G442900, TraesCS5B02G443300, TraesCS5B02G443400, and TraesCS5D02G446900, with significantly higher expression levels in Nankang 1 than in Shannong 102, and these genes may have an important role in regulating the resistance of Nankang 1 to F. graminearum infection. The PR proteins they encode are PR protein 1-9, PR protein 1-6, PR protein 1-7, PR protein 1-7, and PR protein 1-like. In addition, the number of DEGs in Nankang 1 was higher than that in Shannong 102 on almost all chromosomes, except chromosomes 1A and 3D, but especially on chromosomes 6B, 4B, 3B, and 5A. These results indicate that gene expression and the genetic background must be considered for FHB resistance in wheat breeding