Effects of IRF5 Lupus Risk Haplotype on Pathways Predicted to Influence B Cell Functions

Both genetic and environmental interactions affect systemic lupus erythematosus (SLE) development and pathogenesis. One known genetic factor associated with lupus is a haplotype of the interferon regulatory factor 5 (IRF5) gene. Analysis of global gene expression microarray data using gene set enrichment analysis identified multiple interferon- and inflammation-related gene sets significantly overrepresented in cells with the risk haplotype. Pathway analysis using expressed genes from the significant gene sets impacted by the IRF5 risk haplotype confirmed significant correlation with the interferon pathway, Toll-like receptor pathway, and the B-cell receptor pathway. SLE patients with the IRF5 risk haplotype have a heightened interferon signature, even in an unstimulated state (P = 0.011), while patients with the IRF5 protective haplotype have a B cell interferon signature similar to that of controls. These results identify multiple genes in functionally significant pathways which are affected by IRF5 genotype. They also establish the IRF5 risk haplotype as a key determinant of not only the interferon response, but also other B-cell pathways involved in SLE

Mobile Mapping,Geographic Information Update and Urban Management Intelligence

The foundation of urban management intelligence is internet,geographic information platform and cloud computing platform.Data updating is the soul of geographic information platform.The rapid updating of urban geographic information involves concepts,funds and techniques.These three factors constitute the historic challenge of urban surveying and mapping,and also the reality bottleneck of the implementation of urban management intelligence.This paper presents a city natural data model(CNDM)that is based on the color laser point cloud.Based on vehicle borne mobile mapping,unmanned aerial vehicle (UAV) aerial photograph,mobile phone taking,HD video surveillance and cloud computing platform,a fast updating system of CNDM is formed.City geographic information platform for city actuality is constructed based on the real-time update of CNDM,which is to establish the base data of urban management intelligence

Relaxed Adaptive Lasso and Its Asymptotic Results

This article introduces a novel two-stage variable selection method to solve the common asymmetry problem between the response variable and its influencing factors. In practical applications, we cannot correctly extract important factors from a large amount of complex and redundant data. However, the proposed method based on the relaxed lasso and the adaptive lasso, namely, the relaxed adaptive lasso, can achieve information symmetry because the variables it selects contain all the important information about the response variables. The goal of this paper is to preserve the relaxed lasso’s superior variable selection speed while imposing varying penalties on different coefficients. Additionally, the proposed method enjoys favorable asymptotic properties, that is, consistency with a fast rate of convergence with Opn−1. The simulation demonstrates that the proper variable recovery, i.e., the number of significant variables selected, and prediction accuracy of the relaxed adaptive lasso in a limited sample is superior to the regular lasso, relaxed lasso and adaptive lasso estimators

Relaxed Adaptive Lasso and Its Asymptotic Results

This article introduces a novel two-stage variable selection method to solve the common asymmetry problem between the response variable and its influencing factors. In practical applications, we cannot correctly extract important factors from a large amount of complex and redundant data. However, the proposed method based on the relaxed lasso and the adaptive lasso, namely, the relaxed adaptive lasso, can achieve information symmetry because the variables it selects contain all the important information about the response variables. The goal of this paper is to preserve the relaxed lasso’s superior variable selection speed while imposing varying penalties on different coefficients. Additionally, the proposed method enjoys favorable asymptotic properties, that is, consistency with a fast rate of convergence with Opn−1. The simulation demonstrates that the proper variable recovery, i.e., the number of significant variables selected, and prediction accuracy of the relaxed adaptive lasso in a limited sample is superior to the regular lasso, relaxed lasso and adaptive lasso estimators

Polyphasic Characterization of Yeasts and Lactic Acid Bacteria Metabolic Contribution in Semi-Solid Fermentation of Chinese Baijiu (Traditional Fermented Alcoholic Drink): Towards the Design of a Tailored Starter Culture

Chinese Baijiu is principally produced through a spontaneous fermentation process, which involves complex microorganism communities. Among them, yeasts and lactic acid bacteria (LAB) are important communities. The study examined the isolated strains from fermented grains of Baijiu regarding their activity of α-amylase and glucoamylase, ethanol tolerance, glucose utilization, as well as metabolite production in the process of laboratory-scale sorghum-based fermentation. Selected strains (Saccharomycopsis fibuligera 12, Saccharomyces cerevisiae 3, and Pediococcus acidilactici 4) were blended in different combinations. The influence of selected strains on the metabolic variation in different semi-solid fermentations was investigated by gas chromatography−mass spectrometry (GC−MS) accompanied by multivariate statistical analysis. According to the principal component analysis (PCA), the metabolites produced varied in different mixtures of pure cultures. S. fibuligera produced various enzymes, particularly α-amylase and glucoamylase, and exhibited a better performance compared with other species regarding the ability to convert starch to soluble sugars and positively affect the production process of volatile compounds. S. cerevisiae had a high fermentation capacity, thereby contributing to substrates utilization. Lactic acid bacteria had a good ability to produce lactic acid. This study attaches importance to the special functions of S. fibuligera, S. cerevisiae, and P. acidilactici in Chinese Baijiu making, and investigates their metabolic characteristics in the process of lab-scale semi-solid fermentation

Robust Variable Selection Based on Relaxed Lad Lasso

Least absolute deviation is proposed as a robust estimator to solve the problem when the error has an asymmetric heavy-tailed distribution or outliers. In order to be insensitive to the above situation and select the truly important variables from a large number of predictors in the linear regression, this paper introduces a two-stage variable selection method named relaxed lad lasso, which enables the model to obtain robust sparse solutions in the presence of outliers or heavy-tailed errors by combining least absolute deviation with relaxed lasso. Compared with lasso, this method is not only immune to the rapid growth of noise variables but also maintains a better convergence rate, which is Opn−1/2. In addition, we prove that the relaxed lad lasso estimator has the property of consistency at large samples; that is, the model selects the number of important variables with a high probability of convergence to one. Through the simulation and empirical results, we further verify the outstanding performance of relaxed lad lasso in terms of prediction accuracy and the correct selection of informative variables under the heavy-tailed distribution

Robust Variable Selection Based on Relaxed Lad Lasso

Least absolute deviation is proposed as a robust estimator to solve the problem when the error has an asymmetric heavy-tailed distribution or outliers. In order to be insensitive to the above situation and select the truly important variables from a large number of predictors in the linear regression, this paper introduces a two-stage variable selection method named relaxed lad lasso, which enables the model to obtain robust sparse solutions in the presence of outliers or heavy-tailed errors by combining least absolute deviation with relaxed lasso. Compared with lasso, this method is not only immune to the rapid growth of noise variables but also maintains a better convergence rate, which is Opn−1/2. In addition, we prove that the relaxed lad lasso estimator has the property of consistency at large samples; that is, the model selects the number of important variables with a high probability of convergence to one. Through the simulation and empirical results, we further verify the outstanding performance of relaxed lad lasso in terms of prediction accuracy and the correct selection of informative variables under the heavy-tailed distribution

Persistent Ependymal Tumor Arising from an Immature Ovarian Teratoma: A Rare Case

Primary ovarian ependymoma is a rare neuroectodermal neoplasm that can arise from immature ovarian teratoma. Due to the paucity of this entity, a complete molecular analysis of these tumors has not been done, thus creating a challenge for finding an effective and safe therapeutic treatment. In the limited literature, patients with primary ovarian ependymoma showed various responses to an array of individualized therapies, ranging from surgeries to chemotherapies. Here, we present a 38-year-old female with persistent ovarian ependymoma, with a molecular profile similar to traditional central nervous system ependymoma that is irresponsive to multiple cytoreduction and clinical experimental therapies. Therefore, a prompt recognition and reporting of this entity can greatly aid in expanding the understanding and standardization of therapies for this neoplasm

miR-143-3p Promotes Ovarian Granulosa Cell Senescence and Inhibits Estradiol Synthesis by Targeting UBE2E3 and LHCGR

The ovary is a highly susceptible organ to senescence, and granulosa cells (GCs) have a crucial role in oocyte development promotion and overall ovarian function maintenance. As age advances, GCs apoptosis and dysfunction escalate, leading to ovarian aging. However, the molecular mechanisms underpinning ovarian aging remain poorly understood. In this study, we observed a correlation between the age-related decline of fertility and elevated expression levels of miR-143-3p in female mice. Moreover, miR-143-3p was highly expressed in senescent ovarian GCs. The overexpression of miR-143-3p in GCs not only hindered their proliferation and induced senescence-associated secretory phenotype (SASP) but also impeded steroid hormone synthesis by targeting ubiquitin-conjugating enzyme E2 E3 (Ube2e3) and luteinizing hormone and human chorionic gonadotropin receptor (Lhcgr). These findings suggest that miR-143-3p plays a substantial role in senescence and steroid hormone synthesis in GCs, indicating its potential as a therapeutic target for interventions in the ovarian aging process

Inhibition of <i>miR-143-3p</i> Restores Blood–Testis Barrier Function and Ameliorates Sertoli Cell Senescence

Due to the increasing trend of delayed childbirth, the age-related decline in male reproductive function has become a widely recognized issue. Sertoli cells (SCs) play a vital role in creating the necessary microenvironment for spermatogenesis in the testis. However, the mechanism underlying Sertoli cell aging is still unclear. In this study, senescent Sertoli cells showed a substantial upregulation of miR-143-3p expression. miR-143-3p was found to limit Sertoli cell proliferation, promote cellular senescence, and cause blood–testis barrier (BTB) dysfunction by targeting ubiquitin-conjugating enzyme E2 E3 (UBE2E3). Additionally, the TGF-β receptor inhibitor SB431542 showed potential in alleviating age-related BTB dysfunction, rescuing testicular atrophy, and reversing the reduction in germ cell numbers by negatively regulating miR-143-3p. These findings clarified the regulatory pathways underlying Sertoli cell senescence and suggested a promising therapeutic approach to restore BTB function, alleviate Sertoli cell senescence, and improve reproductive outcomes for individuals facing fertility challenges