Search

Background: We aimed to explore the relationship between the serum Soluble Scavenger with 5 Domains (SSC5D) levels and heart failure (HF). Methods and Results: We retrospectively enrolled 276 patients diagnosed with HF or normal during hospitalization in Shanghai General Hospital between September 2020 and December 2021. Previously published RNA sequencing data were reanalyzed to confirm the expression profile of SSC5D in failing and non-failing human and mouse heart tissues. Quantitative real-time polymerase chain reaction assay was used to quantify Ssc5d mRNA levels in murine heart tissue after myocardial infarction and transverse aortic constriction surgery. To understand the HF-induced secreted proteins profile, 1,755 secreted proteins were investigated using human dilated cardiomyopathy RNA-seq data, and the results indicated that SSC5D levels were significantly elevated in failing hearts compared to the non-failing. Using single-cell RNA sequencing data, we demonstrated that Ssc5d is predominantly expressed in cardiac fibroblasts. In a murine model of myocardial infarction or transverse aortic constriction, Ssc5d mRNA levels were markedly increased compared with those in the sham group. Similarly, serum SSC5D levels were considerably elevated in the HF group compared with the control group [15,789.35 (10,745.32–23,110.65) pg/ mL, 95% CI (16,263.01–19,655.43) vs. 8,938.72 (6,154.97–12,778.81) pg/mL, 95% CI (9,337.50–11,142.93); p < 0.0001]. Moreover, serum SSC5D levels were positively correlated with N-terminal pro-B-type natriuretic peptide (R = 0.4, p = 7.9e-12) and inversely correlated with left ventricular ejection fraction (R = −0.46, p = 9.8e-16). Conclusion: We concluded that SSC5D was a specific response to HF. Serum SSC5D may function as a novel biomarker and therapeutic target for patients with HF. [ABSTRACT FROM AUTHOR]

Abstract: Tillandsia usneoides (Spanish moss) is a natural “air plant” characterised with rootless and soilless. It can be intertwined into plant curtain of arbitrary shape installed in the air cavity of double skin façade (DSF) as intermediate shade. The research project aims in researching Tillandsia usneoides (TU) plant curtain and defining the shading effect and thermal performance of the double skin façade with Tillandsia usneoides plant curtain in hot summer in Shanghai, China. The instantaneous solar heat gain and the instantaneous solar heat gain coefficient (ISHGC) of double skin façade with different Tillandsia usneoides density were obtained. The experimental data prove that the ISHGC decreases with the increase of plant density and solar radiation of outside environment. The minimum value of instantaneous solar heat gain coefficient is 0.24 for double skin façade with plant density of 750g/m2. Further analysis on temperature distribution of each layer of double skin façade indicates that plant curtain can contribute to creation of comfortable indoor climate and energy saving because it decreases the temperature of interior façade. The change of plant density will not influence the temperature stratification of double skin façade. However, the increase of plant density exacerbated the overheating of outside air cavity of DSF. More effective measures such like watering the TU plant curtain should be considered to solve this problem. [Copyright &y& Elsevier]

In this work, a detrending-moving-average- (DMA) based bivariate linear regression analysis method is proposed. The method is combination of detrended moving average analysis and standard regression methodology, which allows us to estimate the scale-dependent regression coefficients for nonstationary and power-law correlated time series. By using synthetic simulations with error of estimation for different position parameter θ of detrending windows, we test our DMA-based bivariate linear regression algorithm and find that the centered detrending technique (θ=0.5) is of best performance, which provides the most accurate estimates. In addition, the estimated regression coefficients are in good agreement with the theoretical values. The center DMA-based bivariate linear regression estimator is applied to analyze the return series of Shanghai stock exchange composite index, the Hong Kong Hangseng index and the NIKKEI 225 index. The dependence among the Asian stock market across timescales is confirmed. Furthermore, two statistics based on the scale-dependent t statistic and the partial detrending-moving-average cross-correlation coefficient are used to demonstrate the significance of the dependence. The scale-dependent evaluation parameters also show that the DMA-based bivariate regression model can provide rich information than standard regression analysis. [ABSTRACT FROM AUTHOR]