Aurantio­obtusin regulates lipogenesis and ferroptosis of liver cancer cells through inhibiting SCD1 and sensitizing RSL3.

Ferroptosis, characterized by iron­mediated non­apoptotic cell death and alterations in lipid redox metabolism, has emerged as a critical process implicated in various cellular functions, including cancer. Aurantio­obtusin (AO), a bioactive compound derived from Cassiae semen (the dried mature seeds of Cassie obtusifolia L. or Cassia toral L.), has anti­hyperlipidemic and antioxidant properties; however, to the best of our knowledge, the effect of AO on liver cancer cells remains unclear. The Cell Counting Kit­8, EdU staining and migration assays were employed to assess the anti­liver cancer activity of AO. Intracellular levels of glutathione peroxidase 4 protein and lipid peroxidation were measured as indicators of ferroptotic status. Immunohistochemical analyses, bioinformatics analyses and western blotting were conducted to evaluate the potential of stearoyl­CoA desaturase 1 (SCD1) in combination with ferroptosis inducers for the personalized treatment of liver cancer. The present study revealed that AO significantly inhibited the proliferation of liver cancer cells in vitro and in vivo. Mechanistically, AO inhibited AKT/mammalian target of rapamycin (mTOR) signaling, suppressed sterol regulatory element­binding protein 1 (SREBP1) expression, and downregulated fatty acid synthase expression, thereby inhibiting de novo fatty acid synthesis. Further investigations demonstrated that AO suppressed glutathione peroxidase 4 protein expression through the nuclear factor erythroid 2­related factor 2/heme oxygenase­1 pathway, induced ferroptosis in liver cancer cells, and simultaneously inhibited lipogenesis by suppressing SCD1 expression through the AKT/mTOR/SREBP1 pathway. Consequently, this increased the sensitivity of liver cancer cells to the ferroptosis inducer RSL3. Additionally, the enhanced effects of AO and RSL3, which resulted in significant tumor suppression, were confirmed in a xenograft mouse model. In conclusion, the present study demonstrated that AO induced ferroptosis, downregulated the expression of SCD1 and enhanced the sensitivity of liver cancer cells to the ferroptosis inducer RSL3. The synergistic use of AO and a ferroptosis inducer may have promising therapeutic effects in liver cancer cells.

Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.

Background: The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. Methods: The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Results: Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. Conclusion: The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.

[Advantage analysis of flow-through cell method in quality evaluation of Chinese patent medicine: a case study of Danshen Tablets].

To explore the quality consistency evaluation method for multi-component traditional Chinese medicine and establish a dissolution evaluation method suitable for the characteristics of multi-component Chinese patent medicine, this study discussed the characteristics and advantages of the flow-through cell method in the dissolution evaluation of Chinese patent medicine by comparing the impact of the small cup method and the flow-through cell method on the dissolution behavior of water-soluble and lipid-soluble major active components of Danshen Tablets. Dissolution tests were performed using the small cup method as described in the 2020 edition of the Chinese Pharmacopoeia and the newly introduced flow-through cell method(closed-loop method) with water solution containing 0.5% SDS as dissolution medium. Cumulative dissolution curves of the water-soluble component salvianolic acid B and the lipid-soluble component tanshinone Ⅱ_A in Danshen Tablets were plotted, and fitting and similarity analysis of the dissolution models was conducted to identify the characteristics and advantages of the flow-through cell method. For the small cup method, 150 mL of water containing 0.5% SDS was used as the dissolution medium, with a rotation speed of 75 r·min~(-1) and a temperature of(37±0.5) ℃, and 3 mL of samples were taken at 15, 30 min, 1, 2, and 4 h, with fresh dissolution medium added at the same temperature and volume. For the flow-through cell method, a closed-loop system was used. Danshen Tablets were placed in the flow-through cell with approximately 6.7 g of glass beads, and 150 mL of water containing 0.5% SDS was used as the dissolution medium. The flow rate was set at 20 mL·min~(-1), and the temperature and sampling were the same as the small cup method. The results showed that compared with the small cup method, the flow-through cell method had stronger discriminative power and higher sensitivity in distinguishing the dissolution behavior of the two components, and could better reflect the differences in formulation quality, especially for water-insoluble lipid-soluble components. Given that there were no essential differences in the in vitro release kinetics between the two methods, the flow-through cell method could not only replace the traditional small cup method but also better guide the formulation development and identify quality issues of formulations.

A Mendelian randomization study for drug repurposing reveals bezafibrate and fenofibric acid as potential osteoporosis treatments.

Background: Lipid pathways have been implicated in the pathogenesis of osteoporosis (OP). Lipid-lowering drugs may be used to prevent and treat OP. However, the causal interpretation of results from traditional observational designs is controversial by confounding. We aimed to investigate the causal association between genetically proxied lipid-lowering drugs and OP risk. Methods: We conducted two-step Mendelian randomization (MR) analyses to investigate the causal association of genetically proxied lipid-lowering drugs on the risk of OP. The first step MR was used to estimate the associations of drug target genes expression with low-density lipoprotein cholesterol (LDL-C) levels. The significant SNPs in the first step MR were used as instrumental variables in the second step MR to estimate the associations of LDL-C levels with forearm bone mineral density (FA-BMD), femoral neck BMD (FN-BMD), lumbar spine BMD (LS-BMD) and fracture. The significant lipid-lowering drugs after MR analyses were further evaluated for their effects on bone mineralization using a dexamethasone-induced OP zebrafish model. Results: The first step MR analysis found that the higher expression of four genes (HMGCR, NPC1L1, PCSK9 and PPARG) was significantly associated with a lower LDL-C level. The genetically decreased LDL-C level mediated by the PPARG was significantly associated with increased FN-BMD (BETA = -1.38, p = 0.001) and LS-BMD (BETA = -2.07, p = 3.35 × 10-5) and was marginally significantly associated with FA-BMD (BETA = -2.36, p = 0.008) and reduced fracture risk (OR = 3.47, p = 0.008). Bezafibrate (BZF) and Fenofibric acid (FBA) act as PPARG agonists. Therefore genetically proxied BZF and FBA had significant protective effects on OP. The dexamethasone-induced OP zebrafish treated with BZF and FBA showed increased bone mineralization area and integrated optical density (IOD) with alizarin red staining. Conclusion: The present study provided evidence that BZF and FBA can increase BMD, suggesting their potential effects in preventing and treating OP. These findings potentially pave the way for future studies that may allow personalized selection of lipid-lowering drugs for those at risk of OP.

Functional Enrichment Analysis Identifying Regulatory Information Associated with Human Fracture.

Dozens of loci associated with fracture have been identified by genome-wide association studies (GWASs). However, most of these variants are located in the noncoding regions including introns, long terminal repeats, and intergenic regions. Although combining regulation information helps to identify the causal SNPs and interpret the involvement of these variants in the etiology of human fracture, regulation information which was truly associated with fracture was unknown. A novel functional enrichment method GARFIELD (GWAS Analysis of Regulatory of Functional Information Enrichment with LD correction) was applied to identify fracture-associated regulation information, including transcript factor binding sites, expression quantitative trait loci (eQTLs), chromatin states, enhancer, promoter, dyadic, super enhancer and Epigenome marks. Fracture SNPs were significantly enriched in exon (Bonferroni correction, p value < 7.14 × 10-3) at two GWAS p value thresholds through GARFIELD. High level of fold-enrichment was observed in super enhancer of monocyte and the enhancer of chondrocyte (Bonferroni correction, p value < 4.45 × 10-3). eQTLs of 44 tissues/cells and 10 transcription factors (TFs) were identified to be associated with human fracture. These results provide new insight into the etiology of human fracture, which might increase the identification of the causal SNPs through the fine-mapping study combined with functional annotation, as well as polygenic risk score.

Dissection of Cellular Communication between Human Primary Osteoblasts and Bone Marrow Mesenchymal Stem Cells in Osteoarthritis at Single-Cell Resolution.

Background and Objectives: Osteoblasts are derived from bone marrow mesenchymal stem cells (BMMSCs) and play important role in bone remodeling. While our previous studies have investigated the cell subtypes and heterogeneity in osteoblasts and BMMSCs separately, cell-to-cell communications between osteoblasts and BMMSCs in vivo in humans have not been characterized. The aim of this study was to investigate the cellular communication between human primary osteoblasts and bone marrow mesenchymal stem cells. Methods and Results: To investigate the cell-to-cell communications between osteoblasts and BMMSCs and identify new cell subtypes, we performed a systematic integration analysis with our single-cell RNA sequencing (scRNA-seq) transcriptomes data from BMMSCs and osteoblasts. We successfully identified a novel preosteoblasts subtype which highly expressed ATF3, CCL2, CXCL2 and IRF1. Biological functional annotations of the transcriptomes suggested that the novel preosteoblasts subtype may inhibit osteoblasts differentiation, maintain cells to a less differentiated status and recruit osteoclasts. Ligand-receptor interaction analysis showed strong interaction between mature osteoblasts and BMMSCs. Meanwhile, we found FZD1 was highly expressed in BMMSCs of osteogenic differentiation direction. WIF1 and SFRP4, which were highly expressed in mature osteoblasts were reported to inhibit osteogenic differentiation. We speculated that WIF1 and sFRP4 expressed in mature osteoblasts inhibited the binding of FZD1 to Wnt ligand in BMMSCs, thereby further inhibiting osteogenic differentiation of BMMSCs. Conclusions: Our study provided a more systematic and comprehensive understanding of the heterogeneity of osteogenic cells. At the single cell level, this study provided insights into the cell-to-cell communications between BMMSCs and osteoblasts and mature osteoblasts may mediate negative feedback regulation of osteogenesis process.

Prediction and analysis of osteoarthritis hub genes with bioinformatics.

Background: Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA. Methods: The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold of log2[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape. Results: A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors. Conclusions: Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.

[Degradation kinetics of ß-nicotinamide mononucleotide based on reliable HPLC quantitative method].

To explore the stability characteristics of ß-nicotinamide mononucleotide(NMN) and provide data support for NMN production, preparation, and related product development, this study established a simple HPLC content determination method for NMN in simple substrate and investigated the degradation behavior, degradation products, and degradation kinetics of NMN under various chemical, physical, and biological conditions. The HPLC method employed a Welch Xtimate AQ-C_(18) column(4.6 mm×250 mm, 5 µm), a detection wavelength of 266 nm, a column temperature of 30 ℃, a flow rate of 1.0 mL·min~(-1), an injection volume of 5 µL, and a mobile phase consisting of methanol(A) and a 10 mmol·L~(-1) ammonium formate aqueous solution(B) with a gradient elution(0-6.7 min, 0-4% A; 6.7-13 min, 4%-18% A; 13-14.2 min, 18% A; 14.2-15 min, 18%-0 A; 15-22 min, 0 A). This method provided good separation between NMN and potential impurities and degradation products, and had a wide linear range, short analysis time, good durability, high accuracy, an average sample recovery rate of 98.71%, and an RSD of 1.2%. The instrument precision had an RSD of 0.26%, and the linearity within the examined range was excellent(R~2≥0.999 9). This method can be applied for NMN content determination in simple substrate. The degradation process of NMN in aqueous solution followed apparent first-order kinetics, with the degradation rate primarily influenced by high temperature and pH. NMN was more stable in low-temperature, neutral, or weakly acidic/alkaline environments. Strong acids or strong alkalis could accelerate its degradation, and its degradation rate was less affected by pepsin and trypsin. In an aqueous solution at room temperature, it followed the kinetic equation lg C_t=0.005 7t + 4.817 2, with t_(0.9) and t_(1/2) values of 95.58, 860.26 h, respectively. The results suggest that pH and temperature are the main factors affecting the stability of NMN in aqueous solution, and low temperature, moisture protection, and a weakly acidic environment are more conducive to the storage and application of NMN and its products.

Imputation of Human Primary Osteoblast Single Cell RNA-Seq Data Identified Three Novel Osteoblastic Subtypes.

BACKGROUND: Recently, single-cell RNA sequencing (scRNA-seq) technology was increasingly used to study transcriptomics at a single-cell resolution, scRNA-seq analysis was complicated by the "dropout", where the data only captures a small fraction of the transcriptome. This phenomenon can lead to the fact that the actual expressed transcript may not be detected. We previously performed osteoblast subtypes classification and dissection on freshly isolated human osteoblasts. MATERIALS AND METHODS: Here, we used the scImpute method to impute the missing values of dropout genes from a scRNA-seq dataset generated on freshly isolated human osteoblasts. RESULTS: Based on the imputed gene expression patterns, we discovered three new osteoblast subtypes. Specifically, these newfound osteoblast subtypes are osteoblast progenitors, and two undetermined osteoblasts. Osteoblast progenitors showed significantly high expression of proliferation related genes (FOS, JUN, JUNB and JUND). Analysis of each subtype showed that in addition to bone formation, these undetermined osteoblasts may involve osteoclast and adipocyte differentiation and have the potential function of regulate immune activation. CONCLUSIONS: Our findings provided a new perspective for studying the osteoblast heterogeneity and potential biological functions of these freshly isolated human osteoblasts at the single-cell level, which provides further insight into osteoblasts subtypes under various (pathological) physiological conditions.

Prokineticins as a Prognostic Biomarker for Low-Grade Gliomas: A Study Based on The Cancer Genome Atlas Data.

Lower-grade glioma (LGG) is a crucial pathological type of glioma. Prokineticins have not been reported in LGG. Prokineticins as a member of the multifunctional chemokine-like peptide family are divided into two ligands: PROK1 and PROK2. We evaluated the role of PROK1 and PROK2 in LGG using TCGA database. We downloaded the datasets of LGG from TCGA and evaluated the influence of prokineticins on LGG survival by survival module. Correlations between clinical information and prokineticins expression were analyzed using logistic regression. Univariable survival and multivariate Cox analysis was used to compare several clinical characteristics with survival. Correlation between prokineticins and cancer immune infiltrates was explored using CIBERSORT and correlation module of GEPIA. We analyzed genes of PROK1 and PROK2 affecting LGG, screened differentially expressed genes (DEGs), interacted protein-protein with DEGs through the STRING website, then imported the results into the Cytospace software, and calculated the hub genes. To analyze whether hub genes and prokineticins are related, the relationship between PROK1 and PROK2 and hub genes was assessed and shown by heat map. In addition, gene set enrichment analysis (GSEA) was performed using the TCGA dataset. The univariate analysis using logistic regression and PROK1 and PROK2 showed opposite expression differences between tumor and normal tissues (p < 0.05). PRO1 and PROK2 expressions showed significant differences in tumor grade, age, Iiscitrate DeHydrogenase (IDH) status, histological type, and 1P/19q codeletion. Multivariate analysis revealed that the up-regulated PROK1 and PROK2 expression is an independent prognostic factor for bad prognosis. Specifically, prokineticin expression level has significant correlations with infiltrating levels of Th1 cells, NK CD 56bright cells, and Mast cells in LGG. We screened 21 DEGs and obtained 5 hub genes (HOXC10, HOXD13, SOX4, GATA4, HOXA9). GSEA-identified FCMR activation, creation of C4 and C2 activators, and CD22-mediated BCR regulation in gene ontology (GO) were differentially enriched in high PROK1 and PROK2 expression phenotype pathway, cytoplasmic ribosomal proteins, and ribosome and were differentially enriched in the low PROK1 and PROK2 expression phenotype pathway. Prokineticins are a prognostic biomarker and the correlation between hub genes and LGG requires further attention.

Effect of central screw taper angles on the loosening performance and fatigue characteristics of dental implants.

Biomechanical performance plays an important role in the long-term service of dental implants. Loosening and fatigue damage of the central screw are the most common problems. This research investigated the effect of the central screw taper angle on the loosening performance and fatigue characteristics of dental implants. Central screws with four taper angles, 30°, 60°, 90° and 180°, were processed and tested. The loosening performance of the screws under initial and postload conditions was compared. Then, the fatigue characteristics of dental implants was measured. Finally, the wear and fracture modes of the screws were observed. The damage locations were verified by finite element analysis (FEA). The results showed that the central screws with 30° taper had substantially better anti-loosening performance and less fretting wear. The central screws with 180° taper had a higher preload, resulting in a longer fatigue life. Furthermore, the fatigue fracture of the central screw occurred at the level of the first thread position, consistent with the FEA results. In the future clinical applications, central screws with a 30° taper angle may improve anti-loosening performance and prolong fatigue life by increasing the tightening torque.

Genome-wide meta-analysis of alcohol use disorder in East Asians.

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. Genome-wide association studies (GWAS) have identified ~30 AUD risk genes in European populations, but many fewer in East Asians. We conducted GWAS and genome-wide meta-analysis of AUD in 13,551 subjects with East Asian ancestry, using published summary data and newly genotyped data from five cohorts: (1) electronic health record (EHR)-diagnosed AUD in the Million Veteran Program (MVP) sample; (2) DSM-IV diagnosed alcohol dependence (AD) in a Han Chinese-GSA (array) cohort; (3) AD in a Han Chinese-Cyto (array) cohort; and (4) two AD Thai cohorts. The MVP and Thai samples included newly genotyped subjects from ongoing recruitment. In total, 2254 cases and 11,297 controls were analyzed. An AUD polygenic risk score was analyzed in an independent sample with 4464 East Asians (Genetic Epidemiology Research in Adult Health and Aging (GERA)). Phenotypes from survey data and ICD-9-CM diagnoses were tested for association with the AUD PRS. Two risk loci were detected: the well-known functional variant rs1229984 in ADH1B and rs3782886 in BRAP (near the ALDH2 gene locus) are the lead variants. AUD PRS was significantly associated with days per week of alcohol consumption (beta = 0.43, SE = 0.067, p = 2.47 × 10-10) and nominally associated with pack years of smoking (beta = 0.09, SE = 0.05, p = 4.52 × 10-2) and ever vs. never smoking (beta = 0.06, SE = 0.02, p = 1.14 × 10-2). This is the largest GWAS of AUD in East Asians to date. Building on previous findings, we were able to analyze pleiotropy, but did not identify any new risk regions, underscoring the importance of recruiting additional East Asian subjects for alcohol GWAS.

Identification of novel pleiotropic gene for bone mineral density and lean mass using the cFDR method.

Bone mineral density (BMD) and whole-body lean mass (WBLM) are two important phenotypes of osteoporosis and sarcopenia. Previous studies have shown that BMD and lean mass were phenotypically and genetically correlated. To identify the novel common genetic factors shared between BMD and WBLM, we performed the conditional false discovery rate (cFDR) analysis using summary data of the genome-wide association study of femoral neck BMD (n = 53,236) and WBLM (n = 38,292) from the Genetic Factors for Osteoporosis Consortium (GEFOS). We identified eight pleiotropic Single Nucleotide Polymorphism (SNPs) (PLCL1 rs11684176 and rs2880389, JAZF1 rs198, ADAMTSL3 rs10906982, RFTN2/MARS2 rs7340470, SH3GL3 rs1896797, ST7L rs10776755, ANKRD44/SF3B1 rs11888760) significantly associated with femoral neck BMD and WBLM (ccFDR < 0.05). Bayesian fine-mapping analysis showed that rs11888760, rs198, and rs1896797 were the possible functional variants in the ANKRD44/SF3B1, JAZF1i, and SH3GL3 loci, respectively. Functional annotation suggested that rs11888760 was likely to comprise a DNA regulatory element and linked to the expression of RFTN2 and PLCL1. PLCL1 showed differential expression in laryngeal posterior cricoarytenoid muscle between rats of 6 months and 30 months of age. Our findings, together with PLCL1's potential functional relevance to bone and skeletal muscle function, suggested that rs11888760 was the possible pleiotropic functional variants appearing to coregulate both bone and muscle metabolism through regulating the expression of PLCL1. The findings enhanced our knowledge of genetic associations between BMD and lean mass and provide a rationale for subsequent functional studies of the implicated genes in the pathophysiology of diseases, such as osteoporosis and sarcopenia.

B-cell Deficiency Attenuates Transplant Glomerulopathy in a Rat Model of Chronic Active Antibody-mediated Rejection.

BACKGROUND: Transplant glomerulopathy (TG) is a pathological feature of chronic active antibody-mediated rejection (cAMR) and is associated with renal allograft failure. The specific role of B cells in the pathogenesis of TG is unclear. METHODS: We used a minor mismatched rat kidney transplant model with B cell-deficient recipients, generated by clustered regularly interspaced short palindromic repeats/Cas9 technology, to investigate the impact of B-cell depletion on the pathogenesis of TG. We hypothesized that B-cell deficiency would prevent TG in the rat kidney transplant model of cAMR. Treatment groups included syngeneic, allogeneic, sensitized allogeneic, and B cell-deficient allogeneic transplant recipients. RESULTS: B cell-deficient recipients demonstrated reduced TG lesions, decreased microvascular inflammation, reduced allograft infiltrating macrophages, and reduced interferon gamma transcripts within the allograft. Allograft transcript levels of interferon gamma, monocyte chemoattractant protein-1, and interleukin-1ß correlated with numbers of intragraft macrophages. B cell-deficient recipients lacked circulating donor-specific antibodies and had an increased splenic regulatory T-cell population. CONCLUSIONS: In this model of cAMR, B-cell depletion attenuated the development of TG with effects on T cell and innate immunity.

Changes in empathy of nurses from 2009 to 2018: A cross-temporal meta-analysis.

The empathy of nurses is associated with self-care and self-compassion, which may enhance the quality of the nurse-patient relationship. Yet, research on the empathy of nursing staff has mostly used cross-sectional designs, which cannot capture the degree of empathy changes over time. To explore changes in empathy among nurses in China from 2009 to 2018. A cross-temporal meta-analysis was used to examine continuous changes in the empathy of nurses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to conduct this cross-temporal meta-analysis of 57 samples of nurses in China who completed the three subscales (perspective-taking, compassionate care, and walking in the patient's shoes) of the Jefferson Scale of Empathy-Health Professionals from 2009 to 2018 (N = 13,825). This meta-analysis was conducted following good scientific practice in every phase, and approval by ethics committees was not required according to the local regulations in China. The findings suggest that the nurses' mean total scores of empathy and perspective-taking on the Jefferson Scale of Empathy-Health Professionals declined significantly over time, but the trend in compassionate care and walking in the patient's shoes was not significant. No significant changes were found in the overall empathy or the three dimensions of empathy of the nurses in the Eastern region across time, whereas a significant decline was found on the total empathy and perspective-taking scores of the nurses in other regions (i.e. the Central and Western regions). The mean total score of empathy and walking in the patient's shoes of the nurses who worked in the intensive care units showed a significant decrease over time. Furthermore, these findings indicate that the empathy of Chinese nurses has decreased steadily over the past 10 years. High levels of empathy can effectively reduce healthcare risks, errors, and disputes among nursing staff and enhance patient satisfaction and well-being.

Rehabilitation Training Following Retroperitoneal Haemorrhage: A Case Report and Review of the Literature.

We report a case of a Chinese man who developed retroperitoneal haemorrhage almost 1 year after surgery for pelvic fracture (1). To the best of our knowledge, this type of delayed haemorrhaging is rarely observed in clinical practice. We also review the literature to identify the common causes of retroperitoneal haemorrhage in patients undergoing surgery for pelvic fracture and to examine the aetiology of this case.

Identification of novel variants associated with osteoporosis, type 2 diabetes and potentially pleiotropic loci using pleiotropic cFDR method.

AIMS: Clinical and epidemiological findings point to an association between type 2 diabetes (T2D) and osteoporosis. Genome-wide association studies (GWASs) have been fruitful in identifying some loci potentially associated with osteoporosis and T2D respectively. However, the total genetic variance for each of these two diseases and the shared genetic determination between them are largely unknown. The aim of this study was to identify novel genetic variants for osteoporosis and/or T2D. METHODS: First, using a pleiotropic conditional false discovery rate (cFDR) method, we analyzed two GWAS summary data of femoral neck bone mineral density (FN_BMD, n = 53,236) and T2D (n = 159,208) to identify novel shared genetic loci. FN_BMD is an important risk factor for osteoporosis. Next, to explore the potential functions of the identified potential pleiotropic genes, differential expression analysis was performed for them in monocytes and peripheral blood mononuclear cells (PBMCs) as these cells are relevant to the etiology of osteoporosis and/or T2D. Further, weighted gene co-expression analysis (WGCNA) was conducted to identify functional connections between novel pleiotropic genes and known osteoporosis/T2D susceptibility genes by using transcriptomic expression datasets in bone biopsies (E-MEXP-1618) and pancreatic islets (GSE50397). Finally, multi-trait fine mapping for the detected pleiotropic risk loci were conducted to identify the SNPs that have the highest probability of being causal for both FN_BMD and T2D. RESULTS: We identified 27 significant SNPs with cFDR<0.05 for FN_BMD and 61 SNPs for T2D respectively. Four loci, rs7068487 (PLEKHA1), rs10885421 (TCF7L2), rs944082 (GNG12-AS1 (WLS)) and rs2065929 (PIFO||PGCP1), were found to be potentially pleiotropic and shared between FN_BMD and T2D (ccFDR<0.05). PLEKHA1 was found differentially expressed in circulating monocytes between high and low BMD subjects, and PBMCs between diabetic and non-diabetic conditions. WGCNA showed that PLEKHA1 and TCF7L2 were interconnected with multiple osteoporosis and T2D associated genes in bone biopsy and pancreatic islets, such as JAG, EN1 and CPE. Fine mapping showed that rs11200594 was a potentially causal variant in the locus of PLEKHA1. rs11200594 is also an eQTL of PLEKHA1 in multiple tissue (e.g. peripheral blood cells, adipose and ovary) and is in strong LD with a number of functional variants. CONCLUSIONS: Four potential pleiotropic loci were identified for shared genetic determination of osteoporosis and T2D. Our study highlights PLEKHA1 as an important potentially pleiotropic gene. The findings may help us gain a better understanding of the shared genetic determination between these two important disorders.

Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions.

PURPOSE: Osteoporosis is a common global health problem characterized by low bone mineral density (BMD) and increased risk of fracture. Genome-wide association studies (GWAS) have identified >100 genetic loci associated with BMD. However, the functional genes responsible for most associations remain largely unknown. We conducted an innovative summary statistic data-based Mendelian randomization (SMR) analysis to identify novel causal genes associated with BMD and explored their potential functional significance. METHODS: After quality control of the largest GWAS meta-analysis data of BMD and the largest expression quantitative trait loci (eQTL) meta-analysis data from peripheral blood samples, 5967 genes were tested using the SMR method. Another eQTL data was used to verify the results. Next we performed a fine-mapping association analysis to investigate the functional SNP in the identified loci. Weighted gene co-expression network analysis (WGCNA) was used to explore functional relationships for the identified novel genes with known putative osteoporosis genes. Further, we assessed functions of the identified genes through in vitro cellular study or previous functional studies. RESULTS: We identified two potentially causal genes (ASB16-AS1 and SYN2) associated with BMD. SYN2 was a novel osteoporosis candidate gene and ASB16-AS1 locus was known to be associated with BMD but was not the nearest gene to the top GWAS SNP. Fine-mapping association analysis showed that rs184478 and rs795000 was predicted to be possible causal SNPs in ASB16-AS1 and SYN2, respectively. ASB16-AS1 co-expressed with several known putative osteoporosis risk genes. In vitro cellular study showed that over-expressed ASB16-AS1 increased the expression of osteoblastogenesis related genes (BMP2 and ALPL), indicating its functional significance. CONCLUSION: Our findings support that ASB16-AS1 and SYN2 may represent two novel functional genes underlying BMD variation. The findings provide a basis for further functional mechanistic studies.

Genome-wide association study of lncRNA polymorphisms with bone mineral density.

Recent studies suggested that long noncoding RNAs (lncRNAs) were widely transcribed in the genome, but their potential roles in the genetic complexity of human disorders required further exploration. The purpose of the present study was to explore genetic polymorphisms of lncRNAs associated with bone mineral density (BMD) and its potential value. Based on the lncRNASNP database, 55,906 lncSNPs were selected to conduct a genome-wide association study meta-analysis among 11,140 individuals of seven independent studies for BMDs at femoral neck (FN), lumbar spine, and total hip (HIP). Promising results were replicated in Genetic Factors for Osteoporosis Consortium (GEFOS Sequencing, n = 32,965). We found two lncRNA loci that were significantly associated with BMD. MEF2C antisense RNA 1 (MEF2C-AS1) located at 5q14.3 was significantly associated with FN-BMD after Bonferroni correction, and the strongest association signal was detected at rs6894139 (P = 3.03 × 10-9 ). LOC100506136 rs6465531 located at 7q21.3 showed significant association with HIP-BMD (P = 7.43 × 10-7 ). MEF2C-AS1 rs6894139 was replicated in GEFOS Sequencing with P-value of 1.43 × 10-23 . Our results illustrated the important role of polymorphisms in lncRNAs in determining variations of BMD and provided justification and evidence for subsequent functional studies.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.