Association between weight-adjusted-waist index and risk of cardiovascular diseases in United States adults: a cross-sectional study.

BACKGROUND: As a new obesity-related index, the weight-adjusted-waist index (WWI) appears to be a good predictor of cardiovascular disease (CVD) in East Asian populations. This study aimed to validate the association between WWI and CVD in United States (US) adults and also evaluate its relationships with the prevalence of specific CVDs. METHODS: The data were obtained from the 2009-2016 National Health and Nutrition Examination Survey. WWI was calculated as waist circumference divided by the square root of weight, and CVD was ascertained based on self-reported physician diagnoses. Multivariable logistic regression models and subgroup analyses were performed to evaluate the association between WWI and CVD. RESULTS: A total of 21,040 participants were included. There was a positive linear relationship between WWI and the odds of CVD (P = 0.310). After adjusting for all covariates, each unit of increased WWI was associated with 48% increased risk of CVD (odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.25-1.74). Moreover, compared with the lowest quintile (< 10.3 cm/√kg), the multivariable-adjusted OR was 3.18 (95% CI: 1.80-5.59) in the highest quintile (≥ 11.8 cm/√kg). Besides, positive associations were also found between WWI and increased prevalence of congestive heart failure (OR: 1.47, 95% CI: 1.11-1.96), coronary heart disease (OR: 1.27, 95% CI: 1.01-1.60), angina (OR: 1.44, 95% CI: 1.06-1.96), heart attack (OR: 1.66, 95% CI: 1.29-2.12), and stroke (OR: 1.32, 95% CI: 1.02-1.70). Subgroup analyses showed that stronger associations between WWI and CVD were detected in participants younger than 50 years of age (P < 0.001). CONCLUSIONS: High levels of WWI were significantly associated with an increased risk of CVD in US adults, particularly in people under 50 years of age. These findings indicate that WWI may be an intervention indicator to reduce the risk of CVD in the general adult population.

Solving the Zero-Sum Control Problem for Tidal Turbine System: An Online Reinforcement Learning Approach.

A novel completely mode-free integral reinforcement learning (CMFIRL)-based iteration algorithm is proposed in this article to compute the two-player zero-sum games and the Nash equilibrium problems, that is, the optimal control policy pairs, for tidal turbine system based on continuous-time Markov jump linear model with exact transition probability and completely unknown dynamics. First, the tidal turbine system is modeled into Markov jump linear systems, followed by a designed subsystem transformation technique to decouple the jumping modes. Then, a completely mode-free reinforcement learning algorithm is employed to address the game-coupled algebraic Riccati equations without using the information of the system dynamics, in order to reach the Nash equilibrium. The learning algorithm includes one iteration loop by updating the control policy and the disturbance policy simultaneously. Also, the exploration signal is added for motivating the system, and the convergence of the CMFIRL iteration algorithm is rigorously proved. Finally, a simulation example is given to illustrate the effectiveness and applicability of the control design approach.

LncRNA GAS5 inhibits NLRP3 inflammasome activation-mediated pyroptosis in diabetic cardiomyopathy by targeting miR-34b-3p/AHR.

Long noncoding RNA GAS5 is down-regulated in cardiomyocytes in diabetic cardiomyopathy (DCM). Here, we studied the involvement of GAS5 in DCM by analyzing its expression in DCM mouse model and cardiac muscle cell line (HL-1 cells). Compared with normal mice, GAS5 was severely down-regulated in heart tissues of DCM mice. GAS5 overexpression improved cardiac function and myocardial hypertrophy in DCM mice. In addition, the expression of NLRP3, caspase-1, Pro-caspase-1, IL-1ß and IL-18 were increased in heart tissues of DCM mice and high glucose-treated HL-1 cells, which was repressed by GAS5 up-regulation. GAS5 overexpression suppressed caspase-1 activity, LDH release and the levels of IL-1ß, IL-18 in the high glucose-treated HL-1 cells. Moreover, GAS5 regulated AHR expression by sponging miR-34b-3p. Furthermore, GAS5 overexpression suppressed NLRP3 inflammasome activation-mediated pyroptosis by regulating miR-34b-3p/AHR axis. In summary, our study demonstrates that GAS5 acts as a competing endogenous RNA to enhance AHR expression by sponging miR-34b-3p, which consequently represses NLRP3 inflammasome activation-mediated pyroptosis to improve DCM. Thus, our data provide a novel lncRNA GAS5 that could be a valuable target for DCM treatment.

Efficacy and safety of sacubitril-valsartan in heart failure: a meta-analysis of randomized controlled trials.

AIMS: Sacubitril-valsartan has been shown to have superior effects over angiotensin-converting enzyme inhibitors and angiotensin receptor blockers in patients with heart failure (HF) and hypertension. The efficacy and safety of sacubitril-valsartan in patients with HF are controversial. We performed a meta-analysis of randomized controlled trials to assess and compare the effect and adverse events of sacubitril-valsartan, valsartan, and enalapril in patients with HF. METHODS AND RESULTS: We conducted a systematic search using PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov. Randomized controlled trials involving the use of sacubitril-valsartan in patients with HF were included. We assessed the pooled odds ratio (OR) of all-cause mortality, cardiovascular mortality, and hospitalization for HF in fixed-effects models and the pooled risk ratio (RR) of symptomatic hypotension, worsening renal function, and hyperkalaemia in fixed-effects models. Of the 315 identified records, six studies involving 14 959 patients were eligible for inclusion. Sacubitril-valsartan reduced the endpoints of all-cause mortality and cardiovascular mortality in patients with HF with reduced ejection fraction (HFrEF) in three trials with pooled ORs of 0.83 (P = 0.0006) and 0.78 (P < 0.0001), respectively. Regarding the composite outcome of hospitalization for HF in five trials, the pooled OR was 0.79 (P < 0.00001). Compared with enalapril or valsartan, sacubitril-valsartan was associated with a high risk of symptomatic hypotension (RR 1.47, P < 0.00001), low risk of worsening renal function (RR 0.81, P = 0.005), and low rate of serious hyperkalaemia (≥6.0 mmol/L) (RR 0.76, P = 0.0007) in all six trials. CONCLUSIONS: Compared with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, sacubitril-valsartan significantly decreased the risk of death from all causes or cardiovascular causes in HFrEF and hospitalization for HF in both patients with HFrEF and HF with preserved ejection fraction. Sacubitril-valsartan reduced the risk of renal dysfunction and serious hyperkalaemia but was associated with more symptomatic hypotension.

Prognostic role of neutrophil-to-lymphocyte ratio in aortic disease: a meta-analysis of observational studies.

OBJECTIVE: Recent studies have reported that neutrophil-to-lymphocyte ratio (NLR) is associated with cardiovascular disease. The aim of the present study was to investigate the prognostic value of NLR in aortic disease. METHODS: We systematically searched electronic databases (Cochrane, PubMed, Elsevier, Medline, and Embase) from their inception to March 2020. Observational studies that evaluated the relationship between NLR and aortic disease were eligible for critical appraisal. Data were extracted from applicable articles, risk ratio (RR), weighted mean differences (MD) and 95% confidence intervals (CI) were calculated by RevMan 5.3, and statistical heterogeneity was assessed by the I2 statistic. RESULTS: Fourteen studies enrolling 4066 individuals were included in the meta-analysis. Compared with the control group, NLR was significantly higher in the aortic disease group (MD 3.44, 95%CI: 0.81-6.07, P = 0.01, I2 = 99%). The NLR was also significantly higher in non-survivors with aortic disease, compared to the survivors (MD 4.62, 95%CI: 2.75-6.50, P < 0.00001, I2 = 60%). Compared with the aortic disease patients with a low NLR, mortality was significantly higher in those with a high NLR (RR 2.63, 95%CI: 1.79-3.86, P < 0.00001, I2 = 67%). CONCLUSION: Based on current evidence, an elevated NLR was associated with aortic disease and in-hospital mortality. Raised NLR also demonstrated a significantly increased the risk of mortality after surgical repair in aortic disease patients. NLR may be a good prognostic biomarker in aortic disease and deserve further research in this area.

Adaptive Optimal Control for a Class of Nonlinear Systems: The Online Policy Iteration Approach.

This paper studies the online adaptive optimal controller design for a class of nonlinear systems through a novel policy iteration (PI) algorithm. By using the technique of neural network linear differential inclusion (LDI) to linearize the nonlinear terms in each iteration, the optimal law for controller design can be solved through the relevant algebraic Riccati equation (ARE) without using the system internal parameters. Based on PI approach, the adaptive optimal control algorithm is developed with the online linearization and the two-step iteration, i.e., policy evaluation and policy improvement. The convergence of the proposed PI algorithm is also proved. Finally, two numerical examples are given to illustrate the effectiveness and applicability of the proposed method.

Role of heat shock protein 22 in the protective effect of geranylgeranylacetone in response to oxidized-LDL.

OBJECTIVE: The aim was to investigate the role and potential mechanism of geranylgeranylacetone (GGA) in the development of atherosclerosis, and to explore the role of heat shock protein 22 (HSP22) in mediating GGA effect. METHODS: Human coronary artery endothelial cell (HCAEC) was used for in vitro study. RNA interference was applied to suppress HSP22 in the cells. Cellular apoptosis and intracellular level of reactive oxygen species (ROS) were detected by flow cytometer, and proteins of HSP22, NF-κB, eNOS, and ICAM-1 were assessed by immunoblotting. HSP22-/-//ApoE-/-, and HSP22+/+//ApoE-/- mice were used to investigate the effect of GGA in the animal model of atherosclerosis. Atherosclerotic lesion of the mice aortas was evaluated by Oil Red O staining and H&E staining. RESULTS: GGA significantly inhibited HCAEC apoptosis in response to oxidized-LDL (ox-LDL), but stimulated HSP22 synthesis in the cells. Transfection of HSP22-siRNA in the cells resulted in complete blockage of the GGA effect on apoptosis. GGA also significantly inhibited ROS, NF-κB, and ICAM-1 in the cells transfected control siRNA, but not in the cells transfected with HSP22-siRNA. Atherosclerotic plaque in the aorta was significantly less in the wild type (WT) animals treated with GGA as stained either by Oil Red O or by H&E staining, but not in the HSP22-KO mice. GGA significantly inhibited expression of NF-κB and ICAM-1 in the WT mice, but not in the HSP22-KO mice. CONCLUSION: GGA-induced HSP22, and inhibited ox-LDL-induced apoptosis as well as expression of NF-κB and ICAM-1 in the HCAECs. GGA also attenuated formation of atherosclerotic plaques in mice aorta. Suppression of HSP22 by siRNA resulted in blockage of the GGA inhibition on apoptosis or stimulation on NF-κB and ICAM-1. These findings suggested that GGA protects endothelial cells from injury in response to ox-LDL and block atherosclerotic development in mice aorta through induction of HSP22.

Atorvastatin downregulates HSP22 expression in an atherosclerotic model in vitro and in vivo.

One of the pathological functions of heat shock protein 22 (HSP22) is the association with inflammatory diseases and atherosclerosis. However, the effects of a high­fat diet (HFD) or oxidized low­density lipoprotein (ox­LDL) combined with atorvastatin (ATV) on HSP22 expression are entirely unknown. The present study investigated the effects of ATV on HSP22 expression in HFD­induced atherosclerotic apolipoprotein E­deficient (ApoE­/­) mice and in ox­LDL­induced human umbilical vein endothelial cells (HUVECs). Furthermore, the influence of HSP22­knockdown on the HFD- or ox­LDL­induced atherosclerotic model was also examined. It was found that HFD or ox­LDL treatment significantly increased HSP22 expression in the serum and aorta, accompanied by decreased phosphorylated (p)­endothelial nitric oxide synthase (p-eNOS) activity and activated p38 mitogen­activated protein kinase (MAPK). However, these effects were suppressed by treatment with ATV. Furthermore, HSP22-knockdown showed reduced ox­LDL­induced lesions, evidenced by increased p­eNOS activity and inactivated p38 MAPK, while suppression of cell proliferation inhibition and cell cycle arrest were also observed. Taken together, the results of this study suggest that HFD or ox­LDL increased the expression of HSP22 and p­p38 MAPK, and decreased the p­eNOS activity in vitro and in vivo, and ATV could reduce the effects by downregulating HSP22 expression.

Network evolution model for supply chain with manufactures as the core.

Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

A network-based method for mechanistic investigation of Shexiang Baoxin Pill's treatment of cardiovascular diseases.

Shexiang Baoxin Pill (SBP), a traditional Chinese medicine formula, is commonly used to treat cardiovascular disease (CVD) in China. However, the complexity of composition and targets has deterred our understanding of its mechanism of action. Using network pharmacology-based approaches, we established the mechanism of action for SBP to treat CVD by analyzing protein-protein interactions and pathways. The computational results were confirmed at the gene expression level in microarray-based studies. Two of the SBP's targets were further confirmed at the protein level by Western blot. In addition, we validated the theory that SBP's plasma absorbed compounds play major therapeutic role in treating CVD.

Prediction of Links and Weights in Networks by Reliable Routes.

Link prediction aims to uncover missing links or predict the emergence of future relationships from the current network structure. Plenty of algorithms have been developed for link prediction in unweighted networks, but only a few have been extended to weighted networks. In this paper, we present what we call a "reliable-route method" to extend unweighted local similarity indices to weighted ones. Using these indices, we can predict both the existence of links and their weights. Experiments on various real-world networks suggest that our reliable-route weighted resource-allocation index performs noticeably better than others with respect to weight prediction. For existence prediction it is either the highest or very close to the highest. Further analysis shows a strong positive correlation between the clustering coefficient and prediction accuracy. Finally, we apply our method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks. Once again, our reliable-route method shows the highest accuracy.

Analysis of Cynandione A's Anti-Ischemic Stroke Effects from Pathways and Protein-Protein Interactome.

Ischemic stroke is the third leading cause of death in the world. Our previous study found that cynandione A (CYNA), the main component from the root of Cynanchum bungei, exhibits anti-ischemic stroke activity. In this work, we investigated the therapeutic mechanisms of CYNA to ischemic stroke at protein network level. First, PC12 cells and cerebellar granule neurons were prepared to validate the effects of CYNA against glutamate injury. Our experiments suggested that CYNA could dose-dependently mitigate glutamate-induced neurons neurotoxicity and inhibit glutamate-induced upregulation of KHSRP and HMGB1, further confirming the neuroprotective effects of CYNA in vivo. Then, on the pathway sub-networks, which present biological processes that can be impacted directly or in periphery nodes by drugs via their targets, we found that CYNA regulates 11 pathways associated with the biological process of thrombotic or embolic occlusion of a cerebral artery. Meanwhile, by defining a network-based anti-ischemic stroke effect score, we showed that CYNA has a significantly higher effect score than random counterparts, which suggests a synergistic effect of CYNA to ischemic stroke. This study may shed new lights on the study of network based pharmacology.

Degree-adjusted algorithm for prioritisation of candidate disease genes from gene expression and protein interactome.

Computational methods play an important role in the disease genes prioritisation by integrating many kinds of data sources such as gene expression, functional annotations and protein-protein interactions. However, the existing methods usually perform well in predicting highly linked genes, whereas they work quite poorly for loosely linked genes. Motivated by this observation, a degree-adjusted strategy is applied to improve the algorithm that was proposed earlier for the prediction of disease genes from gene expression and protein interactions. The authors also showed that the modified method is good at identifying loosely linked disease genes and the overall performance gets enhanced accordingly. This study suggests the importance of statistically adjusting the degree distribution bias in the background network for network-based modelling of complex diseases.

Bioinformatics analysis for the antirheumatic effects of huang-lian-jie-du-tang from a network perspective.

Huang-Lian-Jie-Du-Tang (HLJDT) is a classic TCM formula to clear "heat" and "poison" that exhibits antirheumatic activity. Here we investigated the therapeutic mechanisms of HLJDT at protein network level using bioinformatics approach. It was found that HLJDT shares 5 target proteins with 3 types of anti-RA drugs, and several pathways in immune system and bone formation are significantly regulated by HLJDT's components, suggesting the therapeutic effect of HLJDT on RA. By defining an antirheumatic effect score to quantitatively measure the therapeutic effect, we found that the score of each HLJDT's component is very low, while the whole HLJDT achieves a much higher effect score, suggesting a synergistic effect of HLJDT achieved by its multiple components acting on multiple targets. At last, topological analysis on the RA-associated PPI network was conducted to illustrate key roles of HLJDT's target proteins on this network. Integrating our findings with TCM theory suggests that HLJDT targets on hub nodes and main pathway in the Hot ZENG network, and thus it could be applied as adjuvant treatment for Hot-ZENG-related RA. This study may facilitate our understanding of antirheumatic effect of HLJDT and it may suggest new approach for the study of TCM pharmacology.