Photo-assisted natural chalcopyrite activated peracetic acid for efficient micropollutant degradation.

The effective activation of natural chalcopyrite (CuFeS2) on peracetic acid (PAA) to remove organic micropollutants was studied under visible light irradiation. Results showed than an effective sulfamethoxazole (SMX) degradation (95.0 %) was achieved under visible light irradiation for 30 min at pH 7.0. Quenching experiments, electron spin resonance analysis, and LC/MS spectrum demonstrated that HO• and CH3C(O)OO• were the main reactive species for SMX degradation, accounting for 43.3 % and 56.7 % of the contributions, respectively. Combined with X-ray photoelectron spectroscopy analysis, the photoelectrons generated on CuFeS2 activated by visible light enhanced the Fe3+/Fe2+ and Cu2+/Cu+ cycles on the surface, thereby activating PAA to generate HO•/CH3C(O)OO•. The removal rate of SMX decreased with the increase in wavelengths, due to the formation of low energy photons at longer wavelengths. Besides, the optimal pH for degradation of SMX by CuFeS2/PAA/Vis-LED process was neutral, which was attributed to the increasing easily activated anionic form of PAA during the increase in pH and the depletion of Fe species at alkaline conditions. Cl-, HCO3-, and HA slightly inhibited SMX degradation because of reactive species being quenched and/or shielding effect. Furthermore, the degradation efficiency of different pollutants by CuFeS2/PAA/Vis-LED was also measured, and the removal efficiency was different owing to the selectivity of CH3C(O)OO•. Finally, the process exhibited good applicability in real waters. Overall, this study provides new insight into visible light-catalyzed activation of PAA and suggests on further exploration of the intrinsic activation mechanism of PAA.

A machine learning model for identifying systemic lupus erythematosus through laboratory information system and electronic medical record.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Its diagnosis poses significant challenges especially at early stages and in atypical cases. The aim of this study was to develop a machine learning model based on common laboratory tests that can aid SLE diagnosis. METHODS: A standard protocol was developed to collect data of SLE and control immune diseases. A 10-fold cross-validation was performed in the modeling dataset (n=862), and an external dataset (n=198) was used for model validation. Machine learning algorithms were applied to construct a diagnostic model. Performance was evaluated based on area under the curve (AUC) values, F1-score, negative predictive value, positive predictive value, accuracy, sensitivity, and specificity. RESULTS: The optimal model was based on a random forest algorithm with 10 clinical features. Thrombin time, prothrombin activity, and uric acid contributed most to the diagnostic model. The SLE diagnostic model showed sufficient predictive accuracy, with AUC values of 0.8286 in the validation dataset. CONCLUSIONS: Our diagnostic model based on 10 common laboratory tests identified the patients with SLE with high accuracy. An online version of the model can potentially be applied in clinical settings for the differential diagnosis of SLE.

Composite Object Relation Modeling for Few-Shot Scene Recognition.

The goal of few-shot image recognition is to classify different categories with only one or a few training samples. Previous works of few-shot learning mainly focus on simple images, such as object or character images. Those works usually use a convolutional neural network (CNN) to learn the global image representations from training tasks, which are then adapted to novel tasks. However, there are many more abstract and complex images in real world, such as scene images, consisting of many object entities with flexible spatial relations among them. In such cases, global features can hardly obtain satisfactory generalization ability due to the large diversity of object relations in the scenes, which may hinder the adaptability to novel scenes. This paper proposes a composite object relation modeling method for few-shot scene recognition, capturing the spatial structural characteristic of scene images to enhance adaptability on novel scenes, considering that objects commonly co- occurred in different scenes. In different few-shot scene recognition tasks, the objects in the same images usually play different roles. Thus we propose a task-aware region selection module (TRSM) to further select the detected regions in different few-shot tasks. In addition to detecting object regions, we mainly focus on exploiting the relations between objects, which are more consistent to the scenes and can be used to cleave apart different scenes. Objects and relations are used to construct a graph in each image, which is then modeled with graph convolutional neural network. The graph modeling is jointly optimized with few-shot recognition, where the loss of few-shot learning is also capable of adjusting graph based representations. Typically, the proposed graph based representations can be plugged in different types of few-shot architectures, such as metric-based and meta-learning methods. Experimental results of few-shot scene recognition show the effectiveness of the proposed method.

Dataset Bias in Few-Shot Image Recognition.

The goal of few-shot image recognition (FSIR) is to identify novel categories with a small number of annotated samples by exploiting transferable knowledge from training data (base categories). Most current studies assume that the transferable knowledge can be well used to identify novel categories. However, such transferable capability may be impacted by the dataset bias, and this problem has rarely been investigated before. Besides, most of few-shot learning methods are biased to different datasets, which is also an important issue that needs to be investigated deeply. In this paper, we first investigate the impact of transferable capabilities learned from base categories. Specifically, we use the relevance to measure relationships between base categories and novel categories. Distributions of base categories are depicted via the instance density and category diversity. The FSIR model learns better transferable knowledge from relevant training data. In the relevant data, dense instances or diverse categories can further enrich the learned knowledge. Experimental results on different sub-datasets of Imagenet demonstrate category relevance, instance density and category diversity can depict transferable bias from distributions of base categories. Second, we investigate performance differences on different datasets from the aspects of dataset structures and different few-shot learning methods. Specifically, we introduce image complexity, intra-concept visual consistency, and inter-concept visual similarity to quantify characteristics of dataset structures. We use these quantitative characteristics and eight few-shot learning methods to analyze performance differences on multiple datasets. Based on the experimental analysis, some insightful observations are obtained from the perspective of both dataset structures and few-shot learning methods. We hope these observations are useful to guide future few-shot learning research on new datasets or tasks. Our data is available at http://123.57.42.89/dataset-bias/dataset-bias.html.

Suppression of mid-spatial-frequency waviness by a universal random tree-shaped path in robotic bonnet polishing.

Mid-spatial-frequency (MSF) errors seriously damages the imaging performance of optical components. Path pattern is an important factor that affects the generation of MSF waviness in polishing. This paper proposes a versatile pseudo random tree-shaped path (RTSP) generation method imitating the growth rules of tree branch in nature, which can efficiently generate continuous, uniformly distributed and multi-directional paths on a specified surface. Furthermore, the effectiveness of RTSP to suppress MSF waviness is verified by numerical simulation and experimental results. Finally, the RTSP is applied to the polishing of Ti-6Al-4V titanium alloy mirror. Results indicate that grinding marks have been significantly removed, while no obvious MSF waviness is introduced.

Dynamics of Rising Bubbles and Their Impact with Viscoelastic Fluid Interfaces.

Bubble dynamics plays a significant role in a wide range of industrial fields, such as food, pharmacy and chemical engineering. The physicochemical properties of complex fluids can greatly affect the speed with which bubbles rise, and the lifetime of bubbles, which in turn can affect the efficiency of food and drug manufacturing and also sewage purification. Therefore, it is of great scientific and practical significance to study the influence mechanism of nanoparticles and surfactants on bubble rising and impact in a complex fluid interface. This paper selects a mixed dispersion liquid of nanoparticles (SiO2) and a surfactant (SDS) as the objects of the study, observes in real-time the entire processes of bubbles rising, impact at the gas-liquid interface, and rupture, and analyzes the dynamic mechanism of bubble impact in a complex fluid interface. By analyzing the morphological changes of the rising bubbles, the rising velocity and the lifetime of the bubbles, it is found that the surfactant molecules are distributed in the ultrapure water liquid pool and the liquid film surrounding the bubbles. Such distribution can reduce the viscoelasticity between bubbles and the liquid surface, and lower the surface tension of the liquid, which can reduce the rising velocity of bubbles, delay the drainage process of bubbles on a liquid surface, and enhance the lifetime of bubbles. If the liquid surface is covered with nanoparticles, a reticulate structure will be formed on the bubble liquid film, which can inhibit bubble discharge and prolong bubble lifetime. In addition, the influence of such a reticulate structure on liquid surface tension is limited and its function is far smaller than a surfactant.

Genetic Diversity and Signatures of Selection in 15 Chinese Indigenous Dog Breeds Revealed by Genome-Wide SNPs.

There are dozens of recognized indigenous dog breeds in China. However, these breeds have not had extensive studies to describe their population structure, genomic linkage disequilibrium (LD) patterns, and selection signatures. Here, we systematically surveyed the genomes of 157 unrelated dogs that were from 15 diverse Chinese dog breeds. Canine 170K SNP chips were used to compare the genomic structures of Chinese and Western dogs. The genotyping data of 170K SNP chips in Western dogs were downloaded from the LUPA (a European initiative of canine genome project) database. Chinese indigenous dogs had lower LD and shorter accumulative runs of homozygosity (ROH) in the genome. The genetic distances between individuals within each Chinese breed were larger than those within Western breeds. Chinese indigenous and Western dog breeds were clearly differentiated into two separate clades revealed by the PCA and NJ-tree. We found evidence for historical introgression of Western dogs into Chinese Kazakhstan shepherd and Mongolia Xi dogs. We suggested that Greenland sledge dog, Papillon, and European Eurasier have Chinese dog lineages. Selection sweep analysis identified genome-wide selection signatures of each Chinese breed and three breed groups. We highlighted several genes including EPAS1 and DNAH9 that show signatures of natural selection in Qinghai-Tibetan plateau dogs and are likely important for genetic adaptation to high altitude. Comparison of our findings with previous reports suggested RBP7, NMNAT1, SLC2A5, and H6PD that exhibit signatures of natural selection in Chinese mountain hounds as promising candidate genes for the traits of endurance and night vision, and NOL8, KRT9, RORB, and CAMTA1 that show signals of selection in Xi dogs might be candidate genes influencing dog running speed. The results about genomic and population structures, and selection signatures of Chinese dog breeds reinforce the conclusion that Chinese indigenous dogs with great variations of phenotypes are important resources for identifying genes responsible for complex traits.

Hoxa5 alleviates obesity-induced chronic inflammation by reducing ER stress and promoting M2 macrophage polarization in mouse adipose tissue.

Obesity-induced chronic inflammation is associated with endoplasmic reticulum stress (ERS) in adipocytes and changes in both the number and phenotype of adipose tissue macrophages (ATMs). In addition, ERS enhances macrophage activation. So far, the function of Hoxa5 in obesity-induced chronic inflammation has been poorly understood. Herein, we demonstrate the importance of the transcription factor, Hoxa5, in determining adipose tissue macrophage (ATM) polarity and ERS. Hoxa5 decreased bodyweight, reduced inflammatory cytokine secretion and corresponded with an increased number of M2 macrophages in the adipose tissue of high-fat diet (HFD) mice. Transcriptome sequencing data showed that overexpression of Hoxa5 in adipocytes changed expression of endoplasmic reticulum (ER) protein processing-related genes. Based on transcriptome sequencing data and bioinformatics prediction, we have been suggested that Hoxa5 alleviated inflammatory responses by inhibiting ERS and by activating PPARγ pathway in mouse adipose tissue. Hoxa5 alleviated ERS and inflammatory responses by inhibiting the eIF2α/PERK signalling pathway in adipocytes. Hoxa5 also inhibited chronic inflammation of adipocytes by promoting M2 macrophage polarization. In addition, Hoxa5 transcriptionally activated the PPARγ pathway to promote polarization of M2 macrophages, which in turn alleviated chronic inflammation of adipocytes. Taken together, these results shed light on the mechanisms underlying Hoxa5-dependent inhibition of obesity-induced chronic inflammation by reducing ERS and promoting polarization of M2 macrophages. These results suggest that Hoxa5 may be a potential therapeutic target for obesity and other metabolic syndromes.

circNrxn2 Promoted WAT Browning via Sponging miR-103 to Relieve Its Inhibition of FGF10 in HFD Mice.

The accumulation of excess white adipose tissue (WAT) has harmful consequences on metabolic health. WAT browning confers beneficial effects on adiposity, insulin resistance, and hyperlipidemia. In this study, it was found out that circNrxn2 sponged miR-103 and enhanced FGF10 levels in HFD mice WAT. We discovered that circNrxn2 promoted WAT browning and mitochondria functions. Furthermore, circNrxn2 also increased M2 macrophage polarization in HFD mouse adipose tissue, and the PPARγ signaling pathway participated in these biological processes. Moreover, eliminating adipose tissue macrophages (ATMs) by clodronate-crippled circNrxn2 promoted WAT browning, and the simulation co-culture of macrophages and adipocytes results suggested that circNrxn2 promoted WAT browning through increasing M2 macrophage polarization. Our finding revealed that circNrxn2 acted as an endogenous miR-103 sponge, blocked miR-103 effects, and relieved its inhibition of FGF10 expression to promote WAT browning through increasing M2 macrophage polarization. This study provides a good therapeutic strategy for treating obesity and improving obesity-related metabolic disorders.

Fabrication and Dynamic Modeling of Bidirectional Bending Soft Actuator Integrated with Optical Waveguide Curvature Sensor.

Soft robots exhibit many exciting properties due to their softness and body compliance. However, to interact with the environment safely and to perform a task effectively, a soft robot faces a series of challenges such as dexterous motion, proprioceptive sensing, and robust control of its deformable bodies. To address these issues, this article presents a method for fabrication and dynamic modeling of a novel bidirectional bending soft pneumatic actuator that embeds a curvature proprioceptive sensor. The bidirectional bending deformation was generated by two similar chambers with a sinusoidal shape for reducing the internal dampness during bending deformation. An optical waveguide made from flexible poly (methyl methacrylate) material that is immune to the inlet pressure was embedded into the actuator body to measure its bending angle. A dynamic modeling framework based on step response and parameter fitting was proposed to establish a simple differential equation that can describe the nonlinear behavior of the soft actuator. Hence, a sliding mode controller is designed based on this differential equation and the Taylor expansion. The proposed dynamical model and the sliding mode controller were validated by trajectory tracking experiments. The performance of the bidirectional bending soft actuator, such as the linear output of the curvature sensor in different inflating patterns, the proprioceptive sensitiveness to the external environment, the output force, and large bending range under relatively small pressure, was evaluated by relevant experimental paradigms. Prototypes from the novel design and fabrication process demonstrated the soft actuator's potential applications in industrial grasping and hand rehabilitation.

Reduced delivery of epididymal adipocyte-derived exosomal resistin is essential for melatonin ameliorating hepatic steatosis in mice.

Adipocyte-derived exosomes (Exos) serve as bioinformation-containing messengers in cell-to-cell communications, and numerous reports demonstrate that resistin, an adipokine, is strongly associated with hepatic steatosis and other fatty liver diseases, suggesting that adipose dysfunction-generated altered pattern of exosomal cytokines may contribute to shaping the physiological activities in liver. Admittedly, melatonin-mediated positive effects on various tissues/organs have been respectively reported, but regulatory mechanisms of melatonin on the crosstalk between adipose tissue and liver have been investigated rarely. Overall, we hypothesize that the crosstalk originating from adipose tissue may be another worthy regulatory pathway for melatonin ameliorating of hepatic steatosis. Here, we first found the amount of adipocyte-derived exosomal resistin to be significantly decreased by melatonin supplementation. Compared to mice with ExosHFD or Exosresistin treatment, ExosMT remarkably ameliorated hepatic steatosis. Further test demonstrated that resistin was a pivotal cytokine which repressed phosphorylation of 5' adenosine monophosphate-activated protein kinase α (pAMPKα Thr172 ) to trigger endoplasmic reticulum (ER) stress, resulting in hepatic steatosis, whereas ExosMT reversed these risks in hepatocytes. In adipocytes, we identified melatonin to reduce the production of resistin through the brain and muscle arnt-like protein 1 (Bmal1) transcriptional inhibition. Notably, we also confirmed that melatonin enhanced N6 -Methyladenosine (m6 A) RNA demethylation to degrade resistin mRNA in adipocytes. Overall, melatonin decreases traffic volume of adipocyte-generated exosomal resistin from adipocytes to hepatocytes, which further alleviates ER stress-induced hepatic steatosis. Our findings illustrate a novel melatonin-mediated regulatory pathway from adipocytes to hepatocytes, indicating that adipocyte-derived exosome is a new potential target for treating obesity and related hepatorenal syndrome.

Copy number variation in the MSRB3 gene enlarges porcine ear size through a mechanism involving miR-584-5p.

BACKGROUND: The size and type of ears are important conformation characteristics that distinguish pig breeds. A significant quantitative trait locus (QTL) for ear size has been identified on SSC5 (SSC for Sus scrofa chromosome) but the underlying causative gene and mutation remain unknown. Thus, our aim was to identify the gene responsible for enlarged ears in pig. RESULTS: First, we narrowed down the QTL region on SSC5 to a 137.85-kb interval that harbors only the methionine sulfoxide reductase B3 (MSRB3) gene. Then, we identified a 38.7-kb copy number variation (CNV) that affects the last two exons of MSRB3 and could be the candidate causative mutation for this QTL. This CNV showed complete concordance with genotype at the QTL of the founder animals in a white Duroc × Erhualian F2 intercross and was found only in pigs from six Chinese indigenous breeds with large ears and from the Landrace breed with half-floppy ears. Moreover, it accounted for the significant association with ear size on SSC5 across the five pig populations tested. eQTL mapping revealed that this CNV was significantly associated with the expression of the microRNA (miRNA) miR-584-5p, which interacts with MSRB3, one of its target genes. In vivo and in vitro experiments confirmed that miR-584-5p inhibits the translation of MSRB3 mRNA. Taken together, these results led us to conclude that presence of the 38.7-kb CNV in the genome of some pig breeds affects ear size by altering the expression of miR-584-5p, which consequently hinders the expression of one of its target genes (e.g. MSRB3). CONCLUSIONS: Our findings shed insight into the underlying mechanism of development of external ears in mammals and contribute to a better understanding of how the presence of CNV can regulate gene expression.

Homeobox a5 Promotes White Adipose Tissue Browning Through Inhibition of the Tenascin C/Toll-Like Receptor 4/Nuclear Factor Kappa B Inflammatory Signaling in Mice.

Lipopolysaccharide (LPS) induces rapid increase in systemic inflammatory factors. As adipose tissue is a key contributor to the inflammatory response to numerous metabolic stimuli, it is important to understand the mechanism behind the LPS-induced inflammation in white adipose tissue (WAT). Homeobox a5 (Hoxa5) is an important transcription factor, which is highly expressed in adipose tissue, and its mRNA expression is increased at cold exposure in mice. So far, the function of Hoxa5 in adipose tissue browning has been poorly understood. So, the objective of this study was conducted to determine the role of Hoxa5 in adipose inflammatory response and white adipose browning in mice. LPS-induced inflammatory and cold-induced browning model were conducted. We compared the coordinated role of Hoxa5 in inflammation and thermogenesis of mice adipose. Transcriptional and methylation regulation was determined by luciferase assay, electrophoretic mobility shift assay, and bisulfite conversion experiment. Hoxa5 and tenascin C (TNC) were involved in WAT inflammation and browning in mice with LPS injection. Furthermore, Hoxa5 inhibited the TNC-involved activation of Toll-like receptor (TLR) 4/nuclear factor kappa B (NF-κB) signal pathway and promoted WAT browning. Moreover, we found that a BMP4/Smad1 signal, closely related to browning, was activated by Hoxa5. Hoxa5 relieved adipocyte inflammation by decreasing TNC-mediated TLR4 transducer and activator of the NF-κB pathway. Interestingly, descended methylation level increased Hoxa5 expression in cold exposure. Our findings demonstrated that Hoxa5 alleviated inflammation and enhanced browning of adipose tissue via negative control of TNC/TLR4/NF-κB inflammatory signaling and activating BMP4/Smad1 pathway. These findings indicated a novel potential means for the regulation of inflammation in adipocytes to prevent obesity and other inflammatory diseases.

Uncertainty analysis of displacement measurement with Imetrum Video Gauge.

Imetrum Video Gauge is a commercial image-based two-dimensional displacement measurement system which has been widely used. Its uncertainty analysis is presented in this paper. First, the procedure to use Video Gauge is introduced. Then, based on the measurement model, two major sources of uncertainty are identified: (1) the uncertainty associated with the calibration procedure u(C) which is composed of the uncertainty of the known length used in calibration u(L) and the uncertainty of the projection of the known length in the image u(D) and (2) the uncertainty associated with the measurement system itself u(P). Following the Guide to the Expression of Uncertainty in Measurement, the uncertainties can be quantified. In the end, 60 experiments are performed to analyze the relationship between the measurement uncertainty and the working parameters, which are working distance, acquisition frequency and focal length of the lens. In order to ensure the validity of the calculation, two calculation methods are used. The main results of this paper are as follows: (1) the displacement measurement uncertainty increases along with working distance and decreases with the increase of focal length. At the same time, the results indicate that using a longer known length in calibration can also reduce the measurement uncertainty. (2) u(C) is greatly influenced by the known length used in the calibration procedure. It can be reduced when u(L) is reduced. (3) Under the laboratory circumstances, reducing u(C) can greatly reduce the total measurement uncertainty. (4) The displacement measurement uncertainty is more sensitive to the measurement uncertainty of the known length used in calibration than the projection of the known length in the image. (5) As the working distance grows, the sensitivity to the known length is getting weaker and the sensitivity to the projection of the known length in the image is getting stronger. (6) When a longer focal length lens is used, the influence of the working distance to the sensitivity gets weaker. The reported results can help people better understand the characteristics of this system and better use the system for their own purposes.

Genome-Wide Association Analysis for Blood Lipid Traits Measured in Three Pig Populations Reveals a Substantial Level of Genetic Heterogeneity.

Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F2 resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.

A multiobjective evolutionary algorithm based on similarity for community detection from signed social networks.

Various types of social relationships, such as friends and foes, can be represented as signed social networks (SNs) that contain both positive and negative links. Although many community detection (CD) algorithms have been proposed, most of them were designed primarily for networks containing only positive links. Thus, it is important to design CD algorithms which can handle large-scale SNs. To this purpose, we first extend the original similarity to the signed similarity based on the social balance theory. Then, based on the signed similarity and the natural contradiction between positive and negative links, two objective functions are designed to model the problem of detecting communities in SNs as a multiobjective problem. Afterward, we propose a multiobjective evolutionary algorithm, called MEAs-SN. In MEAs-SN, to overcome the defects of direct and indirect representations for communities, a direct and indirect combined representation is designed. Attributing to this representation, MEAs-SN can switch between different representations during the evolutionary process. As a result, MEAs-SN can benefit from both representations. Moreover, owing to this representation, MEAs-SN can also detect overlapping communities directly. In the experiments, both benchmark problems and large-scale synthetic networks generated by various parameter settings are used to validate the performance of MEAs-SN. The experimental results show the effectiveness and efficacy of MEAs-SN on networks with 1000, 5000, and 10,000 nodes and also in various noisy situations. A thorough comparison is also made between MEAs-SN and three existing algorithms, and the results show that MEAs-SN outperforms other algorithms.

Do HIV-positive women receive depression treatment that meets best practice guidelines?

This study addressed whether psychopharmacologic and psychotherapeutic treatment of depressed HIV+ women met standards defined in the best practice literature, and tested hypothesized predictors of standard-concordant care. 1,352 HIV-positive women in the multi-center Women's Interagency HIV Study were queried about depressive symptoms and mental health service utilization using standards published by the American Psychiatric Association and the Agency for Healthcare Research and Quality to define adequate depression treatment. We identified those who: (1) reported clinically significant depressive symptoms (CSDS) using Centers for Epidemiological Studies-Depression Scale scores of ≥16; or (2) had lifetime diagnoses of major depressive disorder (MDD) assessed by World Mental Health Composite International Diagnostic Interviews plus concurrent elevated depressive symptoms in the past 12 months. Adequate treatment prevalence was 46.2 % (n = 84) for MDD and 37.9 % (n = 211) for CSDS. Multivariable logistic regression analysis found that adequate treatment was more likely among women who saw the same primary care provider consistently, who had poorer self-rated role functioning, who paid out-of-pocket for healthcare, and who were not African American or Hispanic/Latina. This suggests that adequate depression treatment may be increased by promoting healthcare provider continuity, outreaching individuals with lower levels of reported role impairment, and addressing the specific needs and concerns of African American and Hispanic/Latina women.

Genetic dissection of blood lipid traits by integrating genome-wide association study and gene expression profiling in a porcine model.

BACKGROUND: Serum concentrations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) are highly heritable traits that are used clinically to evaluate risk for cardiovascular disease in humans. In this study, we applied a genome-wide association study (GWAS) in 1,075 pigs from two populations and gene expression studies on 497 liver samples to dissect the genetic basis of serum lipids in a pig model. RESULTS: We totally identified 8, 5, 2 and 3 genomic loci harboring 109 SNPs that were significantly associated with LDL-C, TC, TG and the ratio of HDL-C/LDL-C in two experimental populations, respectively. In the F2 population, the most prominent SNP was identified at the SSC3: 124,769,847 bp where APOB is the well-known candidate gene. However, in the Sutai population, the most number of significant SNPs was identified at SSC2: 64.97-82.22 Mb where LDLR was identified as the candidate gene. Furthermore, we firstly reported 4 novel genomic loci in pigs harboring the LDL-C-associated SNPs. We also observed obvious population heterogeneity in the two tested populations. Through whole-genome gene expression analysis, we detected 718 trait-correlated expressions. Many of these transcripts correspond to candidate genes for blood lipids in humans. The GWAS mapped 120 cis-eQTLs and 523 trans-eQTLs for these transcripts. One gene encoding the transcript gnl|UG|Ssc#S35330332 stands out to be an important candidate gene for LDL-C by an integrative analysis of GWAS, eQTL and trait-associated expression. CONCLUSIONS: We identified the genomic regions or candidate genes associated with blood lipids by an integrative analysis of GWAS, QTT and eQTL mapping in pigs. The findings would benefit the further identification of the causative genes for blood lipid traits in both pigs and humans.

A genome-wide investigation of expression characteristics of natural antisense transcripts in liver and muscle samples of pigs.

Natural antisense transcripts are endogenous transcripts that are complementary to the sense-strand of DNA. These transcripts have been identified in various eukaryotic species and are involved in a broad range of regulatory events and biological processes. However, their general biological functions, expression characteristics and regulatory mechanisms are still unclear. In this study, 497 liver and 586 muscle samples were harvested from a White Duroc×Erhualian F(2) resource population. The expression profiles of sense and antisense transcripts were determined by tag-based RNA sequencing. We identified 33.7% and 20.4% of transcripts having both sense and antisense expression, and 12.5% and 6.1% of transcripts only expressing antisense transcripts in liver and muscle, respectively. More than 32.2% of imprinting or predicted imprinting genes in the geneimprint database were detected with both sense and antisense expression. The correlations between sense and antisense expression in sense-antisense pairs were diverse in both liver and muscle, showing positive, negative or absent correlation. Antisense expression increases gene expression variability. More interestingly, compared to eQTL mapping of sense transcripts in which more than one eQTL was mapped for a transcript, only one eQTL was identified for each antisense transcript, and the percentage of cis-eQTL in antisense eQTL was higher than that in sense eQTL. This suggests that the expressions of antisense transcripts tend to be cis-regulated by a single genomic locus. To our knowledge, this study is the first systematical investigation of antisense transcription in pigs. The findings improve our understanding of the complexity of porcine transcriptome.