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An autoimmune component has been suggested to play a role in pathogenesis of IgA nephropathy (IgAN). And genetic studies have reported the shared susceptibility loci between IgAN and the prototype autoimmune disease systemic lupus erythematosus (SLE). This study was designed to systemically identify and annotate the shared susceptibility genes between IgAN and SLE. We first conducted an imputation-based genome-wide association analysis in 1180 IgAN cases and 899 controls, 1639 SLE cases and 2410 controls. Then we integrated blood expression quantitative trait loci (eQTL) databases and gene expression data to prioritize the potentially functional genes. The results showed that a total of 1928 SNPs mapping to 14 loci were identified to be shared genes between IgAN and SLE. Conditional analysis prioritized 18 independent SNPs, among which alleles of 4 SNPs in HLA and 7 SNPs in non-HLA loci were risk for SLE were protective alleles for IgAN. Most of the shared SNPs and their proxies (r2 ≥ 0.8 in Asians) (181/184, 98.37%) in non-HLA loci were located in non-coding regions. By analyzing two publicly independent blood-eQTL databases, four genes UBE2L3, FCGR2B, ANXA6, and BLK, which seemed to be restricted to PBMC or its subsets were prioritized. Among them only UBE2L3 showed consistent direction between SLE and IgAN, while the others showed opposite directions. Differential gene analysis showed that UBE2L3 was highly expressed in both SLE and IgAN, while FCGR2B and BLK showed marginal significance in SLE and IgAN, respectively. By exploring the pleiotropy of shared genes between IgAN and SLE, our results provide important clues for understanding the shared role of plasmablasts but the distinct role of B cells in pathogenesis of these two diseases.

PurposeVarious blood collection methods were developed and used in the pharmacokinetic evaluation of drugs. However, the influence of different blood sampling methods on plasma drug concentrations has not been clarified. In the present study, we aimed to determine whether the plasma concentration of a target drug changes based on the collection site and elucidate the mechanism responsible for this change.MethodsWe compared three blood sampling methods commonly used in small animals. Eight clinical drugs were selected and administered to rats simultaneously via intracardiac injection or oral gavage. Blood samples were collected from different sites at the same individual, and pharmacokinetic properties of the drugs were then evaluated.ResultsStudy results showed that the maximum plasma concentration or area under the curve of three study drugs was significantly higher in rats when blood was sampled from the carotid artery than when it was sampled from the caudal vein or by tail snip.ConclusionsPharmacokinetics of certain drugs may differ based on the blood sampling site. The acid-base properties of drugs may influence pharmacokinetic evaluation. The rate and extent of drug distribution may also cause such differences and have significant effects on plasma drug levels.

People increasingly depend on the consumer experiences of a virtual community when making purchasing decisions. Potential consumers search for different types of electronic word of mouth when choosing a product to purchase. Social shopping has numerous advantages, including community-based interaction and the sharing of consumer experiences; however, few studies have focused on measuring the effects of social shopping. This study established a conceptual framework for measuring the effects of social shopping activities, comprising the key elements of (1) the perceptions of social shopping activities, (2) collective intelligence and dissonance, and (3) the consequences of social shopping. This study collected 836 valid Internet user responses to an online survey. Partial least squares regression was used to analyze the relationship between the elements and to measure the effects in different social shopping stimuli. The purpose of this study is to build a model of social shopping activities and verified by PLS to establish a theoretical framework. The study found that only cognitive diversity in each path has no significant impact on collective intelligence, management mechanisms on imbalance, and imbalance on community loyalty. Moreover, most of the user perceptions summarized in this research can produce subsequent benefits and behaviors.

In recent years, people have begun to use sharing economy platforms such as Airbnb and Uber. The rapid development of such sharing economy platforms has thus become an important topic. Studies regarding the sharing economy have discussed resource providers but not users. Therefore, this study constructs a model to measure the components of sharing economy drivers and the correlation between those drivers and usage intention, in addition to exploring the differences in the composition of drivers and usage intention between Airbnb and Uber. The survey method was an online questionnaire. The sample analysis uses partial least squares regression to verify the hypothesis and analyze the components that form the sharing economy for drivers. According to the results, sharing economy drivers─Societal drivers, Economic drivers, Technological drivers, affect usage intention, and different combinations of sharing economy components, such as enjoyment, network externalities, perceived quality, cost saving, and efficiency, exist in Airbnb and Uber. For the reference of relevant academic research and practical operation in the future.

With the growing use of social media in the world, a wide variety of social media applications and services have been produced. Popular social media platforms leverage their unique functions to persuade their users to adopt such applications and services, and many enterprises have begun to consider social media operations as a crucial aspect. Thus, since the gradual influence of social media on consumer behavior, a new social commerce model has begun to develop. This research examined both business and social aspects of social commerce sites to establish an evaluation model for measuring their quality and effectiveness. We collected 468 valid samples of online users who had used social commerce site to browse or purchase products and were willing to use again. We used EFA and CFA to confirm the model we constructed, and Partial least squares regression was used to analyze the relationship among the antecedents and consequences of quality evaluation in social commerce sites. According to the result, the consumers’ behaviors were most likely affected by functionality, enjoyment, process, reliability, presence, and identity with a social commerce site. This study not only provided a credible social commerce quality measurement for other scholars to conduct relevant research but also provide conclusions for the marketing strategy of social commerce sites and products as a reference.

Background & Problem: Urinary tract infection (UTI), one of the most common types of healthcare-associated infections, is associated with increased hospital stay durations and healthcare costs. Our unit is located in the internal medicine ward of a medical center. In 2020, infection control data revealed a rise in the UTI rate to 2.03‰, which was higher than the hospital-wide average of 1.52‰. This prompted the initiation of this improvement project. Purpose: The aim of this study was to develop effective solutions to address UTI-related issues, improve the knowledge and skills of nurses and caregivers involved in UTI care, reduce indwelling catheter duration and environmental sources of infection, and, ultimately, decrease the incidence of UTIs in our ward. Resolutions: Through problem analysis, nurses and caregivers were found to lack sufficient UTI-care-related knowledge and skills, leading to an increase in infection cases. A UTI assessment and standardized workflow were developed. Self-learning materials

Urinary tract infection (UTI), one of the most common types of healthcare-associated infections, is associated with increased hospital stay durations and healthcare costs. Our unit is located in the internal medicine ward of a medical center. In 2020, infection control data revealed a rise in the UTI rate to 2.03‱, which was higher than the hospital-wide average of 1.52‱. This prompted the initiation of this improvement project.BACKGROUND & PROBLEMSUrinary tract infection (UTI), one of the most common types of healthcare-associated infections, is associated with increased hospital stay durations and healthcare costs. Our unit is located in the internal medicine ward of a medical center. In 2020, infection control data revealed a rise in the UTI rate to 2.03‱, which was higher than the hospital-wide average of 1.52‱. This prompted the initiation of this improvement project.The aim of this study was to develop effective solutions to address UTI-related issues, improve the knowledge and skills of nurses and care

Aim： Paeoniflorin from Chinese herb Paeoniae Radix has been shown to ameliorate middle cerebral artery occlusion-induced ischemia in rats. The aim of this study was to investigate the mechanisms underlying the neuroprotective action of PF in cultured rat cortical neurons, Methods： Primary cultured cortical neurons of rats were subjected to oxygen-glucose deprivation and reoxygenation （OGD/R） insult. Cell survival was determined using MTT assay. HEK293 cells stably transfected with A1R （HEK293/A1R） were used for detailed analysis. Phosphorylation of the signaling proteins was evaluated by Western blot or immunoprecipitation. Receptor interactions were identified using co-immunoprecipitation and immunofluorescence staining. Results： Paeoniflorin （10 nmol/L to 1 μmol/L） increased the survival of neurons subjected to OGD/R. Furthermore, paeoniflorin increased the phosphorylation of Akt and ERK1/2 in these neurons. These effects were blocked by PI3K inhibitor wortmannin or MEK inhibitor U0126. Paeoniflorin also increased the phosphorylation of Akt and ERK1/2 in HEK293/A1R cells. Both A1R antagonist DPCPX and EGFR inhibitor AG1478 not only blocked paeoniflorin-induced phosphorylation of ERK1/2 and Akt in HEK293/ACR cells, but also paeoniflorin-increased survival of neurons subjected to OGD/R. In addition, paeoniflorin increased the phosphorylation of Src kinase and activation of MMP-2 in HEK293/ACR cells. Both Src inhibitor PP2 and MMP-2/MMP-9 inhibitor BiPs not only blocked paeoniflorininduced phosphorylation of ERK1/2 （and Akt） in HEK293/A1R cells, but also paeoniflorin-increased survival of neurons subjected to OGD/R. Conclusion： Paeoniflorin promotes the survival of cultured cortical neurons by increasing Akt and ERK1/2 phosphorylation via A1R- mediated transactivation of EGFR.

背景：泌尿道感染是醫療照護相關感染中最常見的類型之一，其與增加住院天數和醫療成本有關。本單位為醫學中心內科病房，2020年感染控制中發現泌尿道感染率上升至2.03‰，高於全院均值1.52‰，因此引發了專案的動機。目的：針對泌尿道感染的問題，制定有效的解決方案，提高護理師和照顧者對泌尿道感染照顧的知識和技能，減少導尿管存留天數和環境感染源，從而降低泌尿道感染的發生率。解決方案：通過分析問題，發現護理師和照顧者對泌尿道感染照顧的知識和技能不足，導致感染的發生率增加。因此，制訂了泌尿道感染評估和標準化流程，規劃自學教材並定期考核，設計尿袋標語和錄製雙語會陰清潔影片，並研發減菌床秤減少感染源。結果：在專案執行的六個月後，護理師和照顧者在泌尿道照護方面的正確率顯著提高。導尿管的存留天數平均為4.7天，泌尿道感染率下降至1.48‰，成功達到專案目標。結論：建議將預防泌尿道感染的知識和技能納入職前訓練，推廣減菌床秤的使用，以進一步減少泌尿道感染的發生率。

Security has always been a popular and critical topic. With the rapid development of information technology, it is always attracting people＇s attention. However, since security has a long history, it covers a wide range of topics which change a lot, from classic cryptography to recently popular mobile security. There is a need to investigate security-related topics and trends, which can be a guide for security researchers, security educators and security practitioners. To address the above-mentioned need, in this paper, we conduct a large-scale study on security-related questions on Stack Overflow. Stack Overflow is a popular on-line question and answer site for software developers to communicate, collaborate, and share information with one another. There are many different topics among the numerous questions posted on Stack Overflow and security-related questions occupy a large proportion and have an important and significant position. We first use two heuristics to extract from the dataset the questions that are related to security based on the tags of the posts. And then we use an advanced topic model, Latent Diriehlet Allocation （LDA） tuned using Genetic Algorithm （GA）, to cluster different security-related questions based on their texts. After obtaining the different topics of security-related questions, we use their metadata to make various analyses. We summarize all the topics into five main categories, and investigate the popularity and difficulty of different topics as well. Based on the results of our study, we conclude several implications for researchers, educators and practitioners.