Combination of Quantitative Computed Tomography and Blood Biochemistry for Evaluating the Relationship Between Nutrition and Bone Mineral Density in Patients on Maintenance Hemodialysis

PurposeTo investigate the effect of nutritional factors on bone mineral density (BMD) using quantitative computed tomography combined with blood biochemistry in patients on maintenance hemodialysis (MHD).MethodsSixty patients on MHD were divided into osteopenia (n = 20) and nonosteopenia (n = 40) groups. BMD, fat, and muscle mass were measured by quantitative computed tomography. The calcification of coronary artery and hilar lymph node and computed tomography attenuation values of the liver and spleen were also analyzed. Differences between the two groups were compared, and the risk factors for osteopenia were analyzed by logistic regression analysis.ResultsPatients in the osteopenia group had lower albumin levels than those in the nonosteopenia group (37.84 ± 3.00 vs 42.03 ± 4.05 g/L; P < .001). Logistic regression showed that patients with lower albumin levels had a higher risk of osteopenia (odds ratio, 1.462; 95% confidence interval, 1.313–1.801; P = .003). BMD was negatively correlated with fat mass (r = ?0.365, P = .004) and positively correlated with the ratio of muscle mass to fat mass (r = 0.431, P = .001). There was no significant difference in the rate of calcification of coronary artery or hilar lymph nodes between the two groups. Computed tomography values of the liver and spleen were positively correlated with the duration of dialysis (r = 0.55, P = .001; r = 0.42, P < .001, respectively).ConclusionLow albumin levels are associated with an increased risk of osteopenia in patients on MHD. Abdominal fat is a risk factor for reduction in BMD in MHD patients, and the ratio of abdominal muscle mass to fat mass is a protective factor for BMD.     

中国社区老年人脑认知相关生活方式对早期认知功能下降的影响

目的 了解中国社区老年人脑认知相关生活方式的分布特征,并探讨其综合评分对早期认知功能下降的影响。方法 研究对象来自老年期重点疾病预防和干预项目。纳入2015年基线调查及2017年随访调查均完成认知功能状况评定,且基线未患痴呆的2 537名≥60岁的社区老年人。通过问卷调查收集其脑认知相关生活方式信息（体育锻炼、社会交往、脑力休闲活动、睡眠质量、吸烟状况与饮酒状况）并计算综合评分。通过多因素logistic回归模型分析脑认知相关生活方式综合评分与早期认知功能下降的关联。结果 2 537名社区老年人群中,评分5~6分者占28.7%,6项脑认知相关生活方式因子均健康者仅占4.8%。男性与女性的健康生活方式因子分布存在差异。多因素logistic回归模型结果显示,与评分0~3分组相比,评分4分和5~6分组早期认知功能下降的风险降低（OR=0.683,95%CI：0.457~1.019;OR=0.623,95%CI：0.398~0.976;趋势P=0.030）。在女性中,与评分0~3分组相比,评分4分和5~6分组的早期认知功能下降的风险降低（OR=0.491,95%CI：0.297~0.812;OR=0.556,95%CI：0.332~0.929;趋势P=0.024）。结论 脑认知相关综合健康生活方式与早期认知功能下降风险降低密切相关,在女性群体中尤为显著。     

Role of Toll-like receptor 2 against Streptococcus uberis infection in primary mouse mammary epithelial cells

Mammary epithelial cells (MECs) play an important role against Streptococcus uberis infection which is one of the main causes of bovine mastitis and a potential threat to human health. Toll-like receptors (TLRs) and their mediated signaling pathways are critical in both innate and infection responses, yet their roles in anti-S. uberis infection in MECs remains poorly defined. In this work we investigated the regulatory mechanisms of TLR2 in inflammatory responses, where WT and TLR2^−/− mice were euthanized at 15–18 days gestation, and mammary gland tissues were collected aseptically. The mouse MECs (MMECs) were isolated by combined digestion with type I collagenase, hyaluronidase and trypsin. We challenged MMECs with S. uberis and quantified antioxidant capacity as well as reactive oxygen species (ROS), proinflammatory cytokines and cell damage at different times. The loss of TLR2 function in MMECs results in more serious cell damage, increased cell adhesion, and significantly decreased ROS and mitochondrial ROS (mROS) with bactericidal function in response to S. uberis infection. Moreover, it was observed that the antioxidant capacity declined, and the production of TLR2-mediated cytokines (except CXC ligand 15) also were reduced. We demonstrated that TLR2 can mediate cellular anti-infective processes in MMECs by regulating the production of ROS and mROS and the secretion of cytokines. The results suggest an unpredicted role of TLR2 in MMECs in response to S. uberis infection.     

miR-200bc/429 cluster alleviates inflammation in IgA nephropathy by targeting TWEAK/Fn14

Immunoglobulin A nephropathy (IgAN) is one of the most common glomerular diseases worldwide. Various studies have identified a host of microRNAs (miRNAs) abnormally expressed in IgAN and might affect the pathogenesis and progression of IgAN. However, miR-200bc/429 cluster in the pathopoiesis of IgAN remains poorly understood. For this study, we found that miR-200bc/429 cluster is downregulated in IgAN tissues and IgAN podocytes and HK2 cells compared with their matched controls respectively. In addition, overexpression of miR-200bc/429 cluster in IgAN podocytes and HK2 cells could attenuate the release of inflammatory cytokines MCP-1, IL-6 and RANTES. Moreover, the 3′ untranslated region (UTR) of TNF-like weak inducer of apoptosis (TWEAK) was identified to be a direct target of miR-200bc/429 cluster. Furthermore, our results showed that miR-200bc/429 cluster can inhibit TWEAK mediated NF-κB pathway activation in IgAN. Overall, our findings revealed that miR-200bc/429 cluster alleviates inflammation in IgAN through TWEAK/Fn14 system and might serve as a biomarker as well as a promising therapeutic target for IgAN.     

Development and validation of a model for the early prediction of the RRT requirement in patients with rhabdomyolysis

IntroductionRhabdomyolysis (RM) is a complex set of clinical syndromes involving the rapid dissolution of skeletal muscles. The early detection of patients who need renal replacement therapy (RRT) is very important and may aid in delivering proper care and optimizing the use of limited resources.MethodsRetrospective analyses of the following three databases were performed: the eICU Collaborative Research Database (eICU-CRD), the Medical Information Mart for Intensive Care III (MIMIC-III) database and electronic medical records from the First Medical Centre of the Chinese People's Liberation Army General Hospital (PLAGH). The data from the eICU-CRD and MIMIC-III datasets were merged to form the derivation cohort. The data collected from the Chinese PLAGH were used for external validation. The factors predictive of the need for RRT were selected using a LASSO regression analysis. A logistic regression was selected as the algorithm. The model was built in Python using the ML library scikit-learn. The accuracy of the model was measured by the area under the receiver operating characteristic curve (AUC). R software was used for the LASSO regression analysis, nomogram, concordance index, calibration, and decision and clinical impact curves.ResultsIn total, 1259 patients with RM (614 patients from eICU-CRD, 324 patients from the MIMIC-III database and 321 patients from the Chinese PLAGH) were eligible for this analysis. The rate of RRT was 15.0% (92/614) in the eICU-CRD database, 17.6% (57/324) in the MIMIC-III database and 5.6% in the Chinese PLAGH (18/321). After the LASSO regression selection, eight variables were included in the RRT prediction model. The AUC of the model in the training dataset was 0.818 (95% CI 0.78–0.87), the AUC in the test dataset was 0.794 (95% CI 0.72–0.86), and the AUC in the Chinese PLAGH dataset (external validation dataset) was 0.820 (95% CI 0.70–0.86).ConclusionsWe developed and validated a model for the early prediction of the RRT requirement among patients with RM based on 8 variables commonly measured during the first 24 h after admission. Predicting the need for RRT could help ensure appropriate treatment and facilitate the optimization of the use of medical resources.     

Mendelian randomization as a tool to gain insights into the mosaic causes of autoimmune diseases

Autoimmune diseases (ADs) are a broad range of disorders which are characterized by long-term inflammation and tissue damage arising from an immune response against one's own tissues. It is now widely accepted that the causes of ADs include environmental factors, genetic susceptibility and immune dysregulation. However, the exact etiology of ADs has not been fully elucidated to date. Because observational studies are plagued by confounding factors and reverse causality, no firm conclusions can be drawn about the etiology of ADs. Over the years, Mendelian randomization (MR) analysis has come into focus, offering unique perspectives and insights into the etiology of ADs and promising the discovery of potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly dispensed during meiosis, usually irrespective of environmental or lifestyle factors) is used instead of modifiable exposure to explore the link between exposure factors and disease or other outcomes. Therefore, MR analysis can provide a valuable method for exploring the causal relationship between different risk factors and ADs when its inherent assumptions and limitations are fully considered. This review summarized the recent findings of MR in major ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1DM), focused on the effects of different risk factors on ADs risks. In addition, we also discussed the opportunities and challenges of MR methods in ADs research.