Coxiella burnetii inhibits host immunity by a protein phosphatase adapted from glycolysis.

Coxiella burnetii is a bacterial pathogen that replicates within host cells by establishing a membrane-bound niche called the Coxiella-containing vacuole. Biogenesis of this compartment requires effectors of its Dot/Icm type IV secretion system. A large cohort of such effectors has been identified, but the function of most of them remain elusive. Here, by a cell-based functional screening, we identified the effector Cbu0513 (designated as CinF) as an inhibitor of NF-κB signaling. CinF is highly similar to a fructose-1,6-bisphosphate (FBP) aldolase/phosphatase present in diverse bacteria. Further study reveals that unlike its ortholog from Sulfolobus tokodaii, CinF does not exhibit FBP phosphatase activity. Instead, it functions as a protein phosphatase that specifically dephosphorylates and stabilizes IκBα. The IκBα phosphatase activity is essential for the role of CinF in C. burnetii virulence. Our results establish that C. burnetii utilizes a protein adapted from sugar metabolism to subvert host immunity.

Unlocking the double-dividend: Evaluating the impact of SO2 emissions trading scheme on firm's environmental and economic performance.

The optimal design of environmental instruments demands a balance between environmental enhancement and economic growth. Utilizing microdata from the China Environmental Statistics Database and the China Industrial Firm Database, this study employs the difference-in-differences (DD) methodology to explore the dual effects of the SO2 Emissions Trading Scheme (ETS) on the environmental and economic performance of micro-firms. The findings suggest that: (1) The SO2 ETS not only induces emission reduction effects among firms in pilot areas but also improves their industrial added value. (2) The SO2 ETS exhibits heterogeneous impacts across firms of diverse ownership, export status, and size. (3) While the SO2 ETS prompts firms to advance technologically, boosting desulfurization capacities and subsequently enhancing total factor productivity, it also inadvertently results in companies offsetting some environmental compliance costs by curtailing employee wages.

Association between handgrip strength and depressive symptoms in patients undergoing hemodialysis: a cross-sectional study from a single Chinese center.

BACKGROUND: The relationship between handgrip strength (HGS) and depression in patients undergoing hemodialysis (HD) was unknown. Therefore, we aimed to clarify this association in a cohort of patients. METHODS: HGS was used as a representative indicator of muscle strength and was measured with a handheld dynamometer. Depressive symptoms were assessed with the self-reported Patient Health Questionnaire-9. A multivariable logistic regression model and restricted cubic spline analysis were used to assess the relationship between HGS and depression. RESULTS: The prevalence of depression in our study was 34% in 568 Chinese patients undergoing HD. Compared with patients in the lowest tertiles of absolute and weighted HGS, patients in the highest tertiles of HGS had an approximately 59% lower [odds ratio (OR) = 0.41, 95% confidence interval (CI) = 0.24-0.68; OR = 0.41, 95%CI = (0.24-0.69)] prevalence of depressive symptoms after multivariate adjustments. Besides, the risk of depression in hemodialysis patients decreased by 33% (OR = 0.67, 95%CI = 0.53-0.85) and 32% (OR = 0.68, 95%CI = 0.54-0.85) for each standard deviation increase in absolute HGS and weighted HGS, respectively. The prevalence of depressive symptoms decreased with both increasing absolute HGS and weighted HGS after multivariate adjustments (p for trend < 0.05). Furthermore, a linear dose-response relationship was observed between absolute HGS and weighted HGS and the prevalence of depressive symptoms (pnonlinearity>0.05). CONCLUSIONS: This study suggests that lower handgrip strength, a simple and modifiable parameter, is associated with a higher prevalence of depression in Chinese patients undergoing HD. Considering that depression is often unrecognized or underdiagnosed in HD patients, lowered muscle strength should be an important indicator and incentive for medical staff to screen for depression.

BMP7 Attenuates Neuroinflammation after Spinal Cord Injury by Suppressing the Microglia Activation and Inducing Microglial Polarization Via the STAT3 Pathway.

Excessive activation of pro-inflammatory (M1) microglia phenotypes after spinal cord injury (SCI) disrupts tissue repair and increases the risk of secondary SCI. We previously reported that adeno-associated virus (AAV) mediated delivery of bone morphogenetic protein 7 (BMP7) promotes functional recovery after SCI by reducing oligodendrocyte loss and demyelination; however, little is known about the early effects of BMP7 in ameliorating neuroinflammation in the acute SCI phase. Herein, we demonstrate that treatment with recombinant human BMP7 (rhBMP7) suppresses the viability of LPS-induced HMC3 microglia cells and increases the proportion with the M2 phenotype. Consistently, in a rat SCI model, rhBMP7 decreases the activation of microglia and promotes M2 polarization. After rhBMP7 administration, the STAT3 signaling pathway was activated in LPS-induced HMC3 cells and microglia in spinal cord lesions. Furthermore, the levels of TNF-α and IL-1ß were significantly decreased in cell culture supernatants, lesion sites of injured spinal cords, and cerebrospinal fluid circulation after rhBMP7 administration, thus reducing neuron loss in the injured spinal cord and promoting functional recovery after SCI. These results provide insight into the immediate early mechanisms by which BMP7 may ameliorate the inflammation response to secondary SCI.

Association between serum ß2-microglobulin levels and the risk of all-cause and cardiovascular disease mortality in chinese patients undergoing maintenance hemodialysis.

BACKGROUND: The association between serum ß2-microglobulin (ß2M) levels and the risk of all-cause and cardiovascular disease (CVD) mortality and the incidence of cardiovascular events (CVEs) in patients undergoing maintenance hemodialysis (MHD) is inconclusive. Furthermore, no study has been performed in China on the significance of serum ß2M levels in MHD patients. Therefore, this study investigated the aforementioned association in MHD patients. METHODS: In this prospective cohort study, 521 MHD patients were followed at Dalian Municipal Central Hospital affiliated with Dalian University of Technology from December 2019 to December 2021. The serum ß2M levels were categorized into three tertiles, and the lowest tertile served as the reference group. Survival curves were calculated by the Kaplan-Meier method. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazard models. Sensitivity analysis was performed by excluding patients with CVD at baseline. RESULTS: During the follow-up period of 21.4 ± 6.3 months, there were 106 all-cause deaths, of which 68 were caused by CVD. When excluding CVD patients at baseline, there were 66 incident CVEs. Kaplan-Meier analysis revealed that the risk of all-cause and CVD mortality in the highest tertile of serum ß2M levels was significantly higher than that in the lowest tertile (P < 0.05), but not for the CVEs (P > 0.05). After adjusting for potential confounders, serum ß2M levels were positively associated with the risk of all-cause (HR = 2.24, 95% CI = 1.21-4.17) and CVD (HR = 2.54, 95% CI = 1.19-5.43) mortality, and a linear trend was evident (P < 0.05). Besides, the results of sensitivity analysis were consistent with the main findings. However, we didn't observed the significant association between serum ß2M levels and CVEs (P > 0.05). CONCLUSION: The serum ß2M level may be a significant predictor of the risk of all-cause and CVD mortality in MHD patients. Further studies are needed to confirm this finding.

TFD-IIS-CRMCB: Telecom Fraud Detection for Incomplete Information Systems Based on Correlated Relation and Maximal Consistent Block.

Telecom fraud detection is of great significance in online social networks. Yet the massive, redundant, incomplete, and uncertain network information makes it a challenging task to handle. Hence, this paper mainly uses the correlation of attributes by entropy function to optimize the data quality and then solves the problem of telecommunication fraud detection with incomplete information. First, to filter out redundancy and noise, we propose an attribute reduction algorithm based on max-correlation and max-independence rate (MCIR) to improve data quality. Then, we design a rough-gain anomaly detection algorithm (MCIR-RGAD) using the idea of maximal consistent blocks to deal with missing incomplete data. Finally, the experimental results on authentic telecommunication fraud data and UCI data show that the MCIR-RGAD algorithm provides an effective solution for reducing the computation time, improving the data quality, and processing incomplete data.

Mining Mobile Network Fraudsters with Augmented Graph Neural Networks.

With the rapid evolution of mobile communication networks, the number of subscribers and their communication practices is increasing dramatically worldwide. However, fraudsters are also sniffing out the benefits. Detecting fraudsters from the massive volume of call detail records (CDR) in mobile communication networks has become an important yet challenging topic. Fortunately, Graph neural network (GNN) brings new possibilities for telecom fraud detection. However, the presence of the graph imbalance and GNN oversmoothing problems makes fraudster detection unsatisfactory. To address these problems, we propose a new fraud detector. First, we transform the user features with the help of a multilayer perceptron. Then, a reinforcement learning-based neighbor sampling strategy is designed to balance the number of neighbors of different classes of users. Next, we perform user feature aggregation using GNN. Finally, we innovatively treat the above augmented GNN as weak classifier and integrate multiple weak classifiers using the AdaBoost algorithm. A balanced focal loss function is also used to monitor the model training error. Extensive experiments are conducted on two open real-world telecom fraud datasets, and the results show that the proposed method is significantly effective for the graph imbalance problem and the oversmoothing problem in telecom fraud detection.

A methodologic survey on use of the GRADE approach in evidence syntheses published in high-impact factor urology and nephrology journals.

BACKGROUND: To identify and describe the use of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach for rating the certainty of systematic reviews (SRs) evidence published in urology and nephrology journals. METHODS: SRs that were published in the top ten "urology and nephrology" journals with the highest impact factor according to the 2020 Journal Citation Reports (covering 2016-2020) were systematically searched and evaluated using the GRADE approach. RESULTS: A total of 445 SRs were researched. Sixty SRs of randomized control trials (RCTs) and/or non-randomized studies (NRSs) were evaluated using the GRADE approach. Forty-nine SRs (11%) rated the outcome-specific certainty of evidence (n = 29 in 2019-2020). We identified 811 certainty of evidence outcome ratings (n = 544 RCT ratings) as follows: very low (33.0%); low (32.1%); moderate (24.5%); and high (10.4%). Very low and high certainty of evidence ratings accounted for 55.0% and 0.4% of ratings in SRs of NRSs compared to 23.0% and 15.3% in SRs of RCTs. The certainty of evidence for RCTs and NRSs was downgraded most often for risk of bias and imprecision. CONCLUSIONS: We recommend increased emphasis on acceptance of the GRADE approach, as well as optimal use of the GRADE approach, in the synthesis of urinary tract evidence.

The Subgrouping Structure of Newborns with Heterogenous Brain-Behavior Relationships.

The presence of heterogeneity/subgroups in infants and older populations against single-domain brain or behavioral measures has been previously characterized. However, few attempts have been made to explore heterogeneity at the brain-behavior relationship level. Such a hypothesis posits that different subgroups of infants may possess qualitatively different brain-behavior relationships that could ultimately contribute to divergent developmental outcomes even with relatively similar brain phenotypes. In this study, we aimed to explore such relationship-level heterogeneity and delineate the subgrouping structure of newborns with differential brain-behavior associations based on a typically developing sample of 81 infants with 3-week resting-state functional magnetic resonance imaging scans and 4-year intelligence quotient (IQ) measures. Our results not only confirmed the existence of relationship-level heterogeneity in newborns but also revealed divergent developmental outcomes associated with two subgroups showing similar brain functional connectivity but contrasting brain-behavior relationships. Importantly, further analyses unveiled an intriguing pattern that the subgroup with higher 4-year IQ outcomes possessed brain-behavior relationships that were congruent to their functional connectivity pattern in neonates while the subgroup with lower 4-year IQ not, providing potential explanations for the observed IQ differences. The characterization of heterogeneity at the brain-behavior relationship level may not only improve our understanding of the patterned intersubject variability during infancy but could also pave the way for future development of heterogeneity-inspired, personalized, subgroup-specific models for better prediction.

Increased clearance of indoxyl sulphate in renal failure rats with the addition of water-soluble poly-ß-cyclodextrin to the dialysate.

AIM: Indoxyl sulphate (IS), a protein-bound uremic toxin that dramatically increases in the sera of patients with end-stage renal disease (ESRD), is poorly removed by conventional haemodialysis (HD). The purpose of this study was to explore whether the addition of water-soluble sorbent poly-ß-cyclodextrins (PCDs) to dialysate can increase the clearance of IS in uremic rats in vivo. METHODS: Male SD rats (450-550 g, n = 18) with nephrectomy plus IS injection (10-mg/kg) were randomly divided into three groups: 1. The HD group (n = 6): conventional HD for 4 h; 2. the 2% PCD group: 2% PCD added to the dialysate, HD for 4 h; and 3. the 4% PCD group: 4% PCD added to the dialysate, HD for 4 h. The serum IS levels in model rats were similar to those of ESRD patients. A stable and safe rat HD treatment mode was established by adjusting the vascular access, blood flow rate, dialysate flow rate, dialysis pipe, dialysate configuration, temperature, treatment environment, and other aspects. RESULTS: Our study found that adding 2% PCD to dialysate significantly improved the clearance of IS approximately twofold compared with conventional HD. Further increasing the PCD concentration to 4% did not increase IS clearance. CONCLUSION: Therefore, our study showed that adding water-soluble sorbent PCDs to dialysate significantly improved the clearance of IS in uremic rats in vivo.

Serum Galectin-3 levels and all-cause and cardiovascular mortality in maintenance hemodialysis patients: a prospective cohort study.

BACKGROUND: Higher serum galectin-3 levels are related to adverse outcomes in different disease states. However, the association of galectin-3 with mortality in the maintenance hemodialysis (HD) population has not been fully described. Thus, we aimed to assess the predictive significance of galectin-3 for all-cause and cardiovascular (CV) mortality through a Chinese maintenance HD population. METHODS: A prospective cohort study was conducted in five hundred and six patients with end-stage renal disease who underwent hemodialysis at Dalian Central Hospital before December 31, 2014. Serum galectin-3 levels were measured at baseline and classified as high (> 8.65 ng/ml) or low (≤ 8.65 ng/ml) according to the "X-tile" program. Primary and secondary outcomes were all-cause and CV mortality, respectively. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by the Cox proportional hazards regression models. RESULTS: During the median follow-up of 60 months, there were 188 all-cause deaths and 125 CV deaths. Compared with maintenance HD population with galectin-3 ≤ 8.65 ng/ml, the adjusted HR for all-cause mortality among those with galectin-3 >  8.65 ng/ml was 1.59 (CI: 0.96-2.65, p = 0.07). Furthermore, multivariable analysis showed that maintenance HD patients with galectin-3 >  8.65 ng/ml had a 2.13-fold higher risk of CV death than those with galectin-3 ≤ 8.65 ng/ml (HR = 2.13, 95% CI 1.07-4.26). CONCLUSION: Galectin-3 is an independent predictor of CV mortality in maintenance HD patients.

Serum total indoxyl sulfate levels and all-cause and cardiovascular mortality in maintenance hemodialysis patients: a prospective cohort study.

BACKGROUND: The association between serum total indoxyl sulfate (tIS), and cardiovascular disease (CVD) and all-cause mortality is a matter of debate. In the current study we sought to determine the association, if any, between serum tIS, and all-cause and CVD-associated mortality in patients on maintenance hemodialysis (MHD). METHODS: A prospective cohort study was conducted involving 500 MHD patients at Dalian Municipal Central Hospital from 31 December 2014 to 31 December 2020. Serum tIS levels were measured at baseline and classified as high (≥44.16 ng/ml) or low (< 44.16 ng/ml) according to the "X-tile" program. Besides, the associations between continuous serum tIS and outcomes were also explored. Predictors were tested for colinearity using variance inflation factor analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression models. Restricted cubic spline model was performed to assess dose-response relationships between tIS concentration and all-cause and CVD mortality. RESULTS: During a 58-month median follow-up period, 224 deaths (132 CVD deaths) were documented. After adjustment for potential confounders, the serum tIS level was positively associated with all-cause mortality (HR = 1.02, 95% = 1.01-1.03); however, we did not detect a significant association when tIS was a dichotomous variable. Compared with the MHD population with a serum tIS level < 44.16 ng/ml, the adjusted HR for CVD mortality among those with a serum tIS level ≥ 44.16 ng/ml was 1.76 (95% = 1.10-2.82). Furthermore, we also noted the same association when the serum tIS level was a continuous variable. CONCLUSION: The serum tIS level was associated with higher risk of all-cause and CVD mortality among MHD patients. Further prospective large-scale studies are required to confirm this finding.

Effect of Qishen granules on isoproterenol-induced chronic heart failure in rats evaluated by comprehensive metabolomics.

Qishen granules (QSG), a Chinese herbal formula, has been widely used in the treatment of myocardial ischemic chronic heart failure (CHF) for many years, but its mechanism of action is still unclear. In this study, comprehensive metabolomics was used to investigate the underlying protective mechanisms of QSG in an isoproterenol-induced CHF rat model. A total of 14 biomarkers were identified in serum and 34 biomarkers in urine, which were mainly related to fatty acid metabolism, bile acid metabolism, amino acid metabolism, purine metabolism, vitamin metabolism, and inflammation. Finally, 22 markers were selected for quantitative analysis of serum, urine, and fecal samples to verify the reliability of the results of untargeted metabolomics, and the results were similar to those of untargeted metabolomics. The correlation analysis showed that the targeted quantitative endogenous metabolites and CHF-related indexes were closely related. QSG might alleviate myocardial inflammatory response, oxidative stress, and amino acid metabolism disorder in CHF by regulating the level of endogenous metabolites. This study revealed QSG could regulate potential biomarkers and correlated metabolic pathway, which provided support for the further application of QSG.

TLP-CCC: Temporal Link Prediction Based on Collective Community and Centrality Feature Fusion.

In the domain of network science, the future link between nodes is a significant problem in social network analysis. Recently, temporal network link prediction has attracted many researchers due to its valuable real-world applications. However, the methods based on network structure similarity are generally limited to static networks, and the methods based on deep neural networks often have high computational costs. This paper fully mines the network structure information and time-domain attenuation information, and proposes a novel temporal link prediction method. Firstly, the network collective influence (CI) method is used to calculate the weights of nodes and edges. Then, the graph is divided into several community subgraphs by removing the weak link. Moreover, the biased random walk method is proposed, and the embedded representation vector is obtained by the modified Skip-gram model. Finally, this paper proposes a novel temporal link prediction method named TLP-CCC, which integrates collective influence, the community walk features, and the centrality features. Experimental results on nine real dynamic network data sets show that the proposed method performs better for area under curve (AUC) evaluation compared with the classical link prediction methods.

Hypernetwork Link Prediction Method Based on Fusion of Topology and Attribute Features.

Link prediction aims at predicting missing or potential links based on the known information of complex networks. Most existing methods focus on pairwise low-order relationships while ignoring the high-order interaction and the rich attribute information of entities in the actual network, leading to the low performance of the model in link prediction. To mine the cross-modality interactions between the high-order structure and attributes of the network, this paper proposes a hypernetwork link prediction method for fusion topology and attributes (TA-HLP). Firstly, a dual channel coder is employed for jointly learning the structural features and attribute features of nodes. In structural encoding, a node-level attention mechanism is designed to aggregate neighbor information to learn structural patterns effectively. In attribute encoding, the hypergraph is used to refine the attribute features. The high-order relationship between nodes and attributes is modeled based on the node-attribute-node feature update, which preserves the semantic information jointly reflected by nodes and attributes. Moreover, in the joint embedding, a hyperedge-level attention mechanism is introduced to capture nodes with different importance in the hyperedge. Extensive experiments on six data sets demonstrate that this method has achieved a more significant link prediction effect than the existing methods.

Overexpression of bone morphogenetic protein 7 reduces oligodendrocytes loss and promotes functional recovery after spinal cord injury.

Spinal cord injury (SCI), as a severe disease with no effective therapeutic measures, has always been a hot topic for scientists. Bone morphogenetic protein 7 (BMP7), as a multifunctional cytokine, has been reported to exert protective effects on the nervous system. The present study aimed to investigate the neuroprotective effect and the potential mechanisms of BMP7 on rats that suffered SCI. Rat models of SCI were established by the modified Allen' s method. Adeno-associated virus (AAV) was injected at T9 immediately before SCI to overexpress BMP7. Results showed that the expression of BMP7 decreased in the injured spinal cords that were at the same time demyelinated. AAV-BMP7 partly reversed oligodendrocyte (OL) loss, and it was beneficial to maintain the normal structure of myelin. The intervention group showed an increase in the number of axons and Basso-Beattie-Bresnahan scores. Moreover, double-labelled immunofluorescence images indicated p-Smad1/5/9 and p-STAT3 in OLs induced by BMP7 might be involved in the protective effects of BMP7. These findings suggest that BMP7 may be a feasible therapy for SCI to reduce demyelination and promote functional recovery.

Comparative pharmacokinetics of Ding-Zhi-Xiao-Wan preparation and its single herbs in rats by using a putative multiple-reaction monitoring UPLC-MS/MS method.

INTRODUCTION: The formula of Chinese medicine, Ding-Zhi-Xiao-Wan (DZXW), has the distinct feature of compatibility therapy, which is attributed to the interactions of multi-herbs. However, the quantification problem caused by the absence of pure reference standards is a bottleneck to clarify the compatibility advantages from the perspective of pharmacokinetics (PKs). OBJECTIVE: This study aimed to develop a putative multiple-reaction monitor (PMRM) strategy for exploring the comparative PKs of DZXW and its single herbs. METHODS: First, precursor ion and tandem mass spectrometry (MS/MS) chromatograms were obtained via ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight MS (UHPLC-Q-TOF-MS) under different collision energy (CE) values. Then, the two most abundance ions in the MS/MS chromatograms were chosen as product ions, and CE values were selected according to the abundance of the product ion peaks. Next, a PMRM strategy consisting of optimal MRM parameters was constructed. Finally, the established PMRM parameters were imported to UHPLC coupled with triple quadrupole MS (UHPLC-TQ-MS) for quantification. RESULTS: The strategy was exemplified by the comparative PK study of DZXW and its single herbs. This strategy could extend the PK scopes of multi-components. The quantitative results displayed substantial variations in PK parameters between DZXW and its single herbs. CONCLUSION: The PK parameters indicated that the DZXW formula could increase the exposure levels of most ingredients and reduce the maximum concentration (Cmax ) of Radix Polygala, indicating that herb compatibility could produce synergistic effects and diminish possible toxic effects. This study provides a viable orientation for the compatibility investigation of traditional Chinese medicine.

A multi-task fully deep convolutional neural network for contactless fingerprint minutiae extraction.

With the outbreak and wide spread of novel coronavirus (COVID-19), contactless fingerprint recognition has attracted more attention for personal recognition because it can provide significantly higher user convenience and hygiene than the traditional contact-based fingerprint recognition. However, it is still challenging to achieve a highly accurate recognition due to the low ridge-valley contrast and pose variances of contactless fingerprints. Minutiae points are a kind of ridge flow discontinuities, and robust and accurate extraction is an important step for most automatic fingerprint recognition algorithms. Most of existing methods are based on two stages which locate the minutiae points first and then compute their directions. The two-stage method cannot make full use of location and direction information. In this paper, we propose a multi-task fully deep convolutional neural network for jointly learning the minutiae location detection and its corresponding direction computation which operates directly on the whole gray scale contactless fingerprints. The proposed method consists of offline training and online testing stages. In the training stage, a fully deep convolutional neural network is built for the tasks of minutiae detection and its direction regression, with an attention mechanism to make the direction regression branch concentrate on the minutiae points. A new loss function is proposed to jointly learn the tasks of minutiae detection and its direction regression from the whole fingerprints. In the testing stage, the trained network is applied on the whole contactless fingerprint to generate the minutiae location and direction maps. The proposed multi-task leaning method performs better than the individual single task and it operates directly on the raw gray-scale contactless fingerprints without preprocessing. The results on three contactless fingerprint datasets show the proposed algorithm performs better than other minutiae extraction algorithms and the commercial software.

Fecal metabolomics based on mass spectrometry to investigate the mechanism of qishen granules against isoproterenol-induced chronic heart failure in rats.

Qishen granules, derived from clinical experience formula, has been widely used to improve and treat myocardial ischemic chronic heart failure in China. However, the mechanism of action of Qishen granules in the treatment of chronic heart failure is unclear. This study aimed to discover potential biomarkers of isoproterenol-induced chronic heart failure rats and investigate the potential mechanism of Qishen granules treatment of chronic heart failure. The fecal metabolomics method based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to analyze the therapeutic effect and metabolic changes of Qishen granules on chronic heart failure rats. Totally, 17 potential biomarkers were identified, involving bile acid metabolism, fatty acid metabolism, inflammatory response, and amino acid metabolism. For bile acid metabolism, we selected 12 bile acids (two of which were potential biomarkers in nontargeted metabolomics) for quantitative analysis. The quantitative results of bile acids showed that after Qishen granules treatment, the contents of bile acids such as ursodeoxycholic acid and glycodeoxycholic acid were similar to those of health group. This study helps to understand the pathogenesis of isoproterenol-induced chronic heart failure and the therapeutic mechanism of Qishen granules from the perspective of metabolic pathways.

Effect of changing treatment to high-flux hemodialysis (HFHD) on mortality in patients with long-term low flux hemodialysis (LFHD): a propensity score matched cohort study.

BACKGROUND: The purpose of this study was to explore the effect of changing treatment to high-flux hemodialysis (HFHD) on mortality rate in patients with long-term low flux hemodialysis (LFHD). METHODS: The patients with end-stage renal disease (ESRD) who underwent LFHD with dialysis age more than 36 months and stable condition in our hospital before December 31, 2014 were included in this study. They were divided into control group and observation group. Propensity score matched method was used to select patients in the control group. The hemodialysis was performed 3 times a week for 4 h. The deadline for follow-up is December 31, 2018. End-point event is all-cause death. The survival rates of the two groups were compared and multivariate Cox regression analysis was carried out. RESULTS: K-M survival analysis showed that the 1-year, 2-year, 3-year and 4-year survival rates of HFHD group were 98, 96, 96 and 96%, respectively. The 1-year, 2-year, 3-year and 4-year survival rates of LFHD group were 95, 85, 80 and 78%, respectively. Log-rank test showed that the survival rate of HFHD group was significantly higher than that of LFHD group (x2= 7.278, P = 0.007). Multivariate Cox regression analysis showed that male, age, hemoglobin and low-throughput dialysis were independent predictors of death (P < 0.05). Compared with LFHD, HFHD can significantly reduce the mortality risk ratio of patients, as high as 86%. CONCLUSION: The prognosis of patients with ESRD who performed long-term LFHD can be significantly improved after changing to HFHD.