Salvia miltiorrhiza injection ameliorates myocardial ischemia-reperfusion injury via downregulation of PECAM-1

Purpose: To investigate the effect of Salvia miltiorrhiza injection on myocardial ischemia-reperfusion injury and PECAM-1 related pathways. Method: Male Wistar rats were used for establishment of myocardial ischemia-reperfusion model. The rats were randomly assigned to four groups: experimental group, low dose group (Salvia miltiorrhiza injection, 10 mL/kg/day), moderate dose group (Salvia miltiorrhiza injection, 20 mL/kg/day) and high dose group (Salvia miltiorrhiza injection, 40 mL/kg/day). Myocardial ischemia-reperfusion model was established in the four groups. Evans-TTC staining was used to assess relative area of ischemiareperfusion injury. Blood samples were collected for assay of PECAM-1 expression using enzymelinked immunosorbent assay (ELISA). Fresh blood platelets were collected in all groups, and divided into two groups - control group (normal culture) and experimental group (Salvia miltiorrhiza injection). The expression of PECAM-1 in blood platelets was assayed using Western blot. Result: Compared with the experimental group, Salvia miltiorrhiza injection ameliorated myocardial ischemia-reperfusion injury, and decreased the infarction area seen in Evans/TTC staining. PECAM-1 expression in blood was decreased by Salvia miltiorrhiza injection. Blood platelets dysfunction was induced after myocardial ischemia-reperfusion, and the level of PECAM-1 increased. However, Salvia miltiorrhiza injection treatment downregulated the expression of PECAM-1 after myocardial ischemiareperfusion. Conclusion: Salvia miltiorrhiza injection maintains normal function of blood platelets and ameliorates myocardial ischemia-reperfusion injury by decreasing expression of PECAM-1

Physical Information Neural Networks for Solving High-index Differential-algebraic Equation Systems Based on Radau Methods

As is well known, differential algebraic equations (DAEs), which are able to describe dynamic changes and underlying constraints, have been widely applied in engineering fields such as fluid dynamics, multi-body dynamics, mechanical systems and control theory. In practical physical modeling within these domains, the systems often generate high-index DAEs. Classical implicit numerical methods typically result in varying order reduction of numerical accuracy when solving high-index systems.~Recently, the physics-informed neural network (PINN) has gained attention for solving DAE systems. However, it faces challenges like the inability to directly solve high-index systems, lower predictive accuracy, and weaker generalization capabilities. In this paper, we propose a PINN computational framework, combined Radau IIA numerical method with a neural network structure via the attention mechanisms, to directly solve high-index DAEs. Furthermore, we employ a domain decomposition strategy to enhance solution accuracy. We conduct numerical experiments with two classical high-index systems as illustrative examples, investigating how different orders of the Radau IIA method affect the accuracy of neural network solutions. The experimental results demonstrate that the PINN based on a 5th-order Radau IIA method achieves the highest level of system accuracy. Specifically, the absolute errors for all differential variables remains as low as $10^{-6}$, and the absolute errors for algebraic variables is maintained at $10^{-5}$, surpassing the results found in existing literature. Therefore, our method exhibits excellent computational accuracy and strong generalization capabilities, providing a feasible approach for the high-precision solution of larger-scale DAEs with higher indices or challenging high-dimensional partial differential algebraic equation systems

Synergistic Computational–Experimental Discovery of Highly Selective PtCu Nanocluster Catalysts for Acetylene Semihydrogenation

Semihydrogenation of acetylene (SHA) in an ethylene-rich stream is an important process for polymer industries. Presently, Pd-based catalysts have demonstrated good acetylene conversion (XC2H2), however, at the expense of ethylene selectivity (SC2H4). In this study, we have employed a systematic approach using density functional theory (DFT) to identify the best catalyst in a Cu–Pt system. The DFT results showed that with a 55 atom system at ∼1.1 Pt/Cu ratio for Pt28Cu27/Al2O3, the d-band center shifted −2.2 eV relative to the Fermi level leading to electron-saturated Pt, which allows only adsorption of ethylene via a π-bond, resulting in theoretical 99.7% SC2H4 at nearly complete XC2H2. Based on the DFT results, Pt–Cu/Al2O3 (PtCu) and Pt/Al2O3 (Pt) nanocatalysts were synthesized via cluster beam deposition (CBD), and their properties and activities were correlated with the computational predictions. For bimetallic PtCu, the electron microscopy results show the formation of alloys. The bimetallic PtCu catalyst closely mimics the DFT predictions in terms of both electronic structure, as confirmed by X-ray photoelectron spectroscopy, and catalytic activity. The alloying of Pt with Cu was responsible for the high C2H4 specific yield resulting from electron transfer between Cu and Pt, thus making PtCu a promising catalyst for SHA

The Sediment Selectivity of Perinereis aibuhitensis Larvae: Active or Passive?

The selectivity of Perinereis aibuhitensis larvae on different sediment types was studied using an experimental behavioral device in the lab. There were six types of sediment with different organic matter content: 2.19, 2.30, 2.86, 3.25, 3.51, and 5.52%. The results indicated significant differences in the six treatments’ organic matter content (p < 0.05). When the P. aibuhitensis larvae initially attached to the sediment, the larvae’s density showed no significant difference among the six treatments. The density of larvae decreased gradually during the experimental period. It increased with the increasing organic matter content in sediment at every sampling time, but there was no significant difference (p > 0.05). The larvae’s specific growth rate in the first month was significantly higher than those in the second and third months (p < 0.05). The mortality showed no significance at different sediments in equal sampling times, but the mortality was lower in high organic matter content sediments. This study showed that the P. aibuhitensis larvae did not make an active selection; random selection happened when initially attached to the sediment with different organic matter contents. Higher organic matter content in the sediment was more conducive to larvae survival, and the organic matter content is the limitation factor on the mortality and the density. The different densities in the natural habitat of P. aibuhitensis might occur due to the passive selection by the environment

Seroprevalence of Pandemic (H1N1) 2009 in Pregnant Women in China: An Observational Study

BACKGROUND: We investigated the seropositive rates and persistence of antibody against pandemic (H1N1) 2009 virus (pH1N1) in pregnant women and voluntary blood donors after the second wave of the pandemic in Nanjing, China. METHODOLOGY/PRINCIPAL FINDINGS: Serum samples of unvaccinated pregnant women (n = 720) and voluntary blood donors (n = 320) were collected after the second wave of 2009 pandemic in Nanjing. All samples were tested against pH1N1 strain (A/California/7/2009) with hemagglutination inhibition assay. A significant decline in seropositive rates, from above 50% to about 20%, was observed in pregnant women and voluntary blood donors fifteen weeks after the second wave of the pandemic. A quarter of the samples were tested against a seasonal H1N1 strain (A/Brisbane/59/2007). The antibody titers against pH1N1 strain were found to correlate positively with those against seasonal H1N1 strain. The correlation was modest but statistically significant. CONCLUSIONS AND SIGNIFICANCE: The high seropositive rates in both pregnant women and voluntary blood donors suggested that the pH1N1 virus had widely spread in these two populations. Immunity derived from natural infection seemed not to be persistent well

Chemoenzymatic Conversion of Biomass-Derived D-Xylose to Furfuryl Alcohol with Corn Stalk-Based Solid Acid Catalyst and Reductase Biocatalyst in a Deep Eutectic Solvent–Water System

In this work, the feasibility of chemoenzymatically transforming biomass-derived D-xylose to furfuryl alcohol was demonstrated in a tandem reaction with SO42−/SnO2-CS chemocatalyst and reductase biocatalyst in the deep eutectic solvent (DES)–water media. The high furfural yield (44.6%) was obtained by catalyzing biomass-derived D-xylose (75.0 g/L) in 20 min at 185 °C with SO42−/SnO2-CS (1.2 wt%) in DES ChCl:EG–water (5:95, v/v). Subsequently, recombinant E.coli CF cells harboring reductases transformed D-xylose-derived furfural (200.0 mM) to furfuryl alcohol in the yield of 35.7% (based on D-xylose) at 35 °C and pH 7.5 using HCOONa as cosubstrate in ChCl:EG–water. This chemoenzymatic cascade catalysis strategy could be employed for the sustainable production of value-added furan-based chemical from renewable bioresource

Investigation of Low Heat Accumulation Asphalt Mixture and Its Impact on Urban Heat Environment.

This study is focused on investigating the effectiveness of low heat accumulation asphalt mixture and its impact on the urban heat environment. Infrared radiation experiments showed that the temperature of the asphalt mixture decreased with the increase in far-infrared radiant material. The results also revealed that, compared to asphalt with 0% far-infrared radiant content, the asphalt material with a certain ratio of far-infrared radiation material had higher stability at high and low temperatures as well as good water absorption capacity. The Marshall stability of the specimen mixed with 6% far-infrared radiant was higher by 12.2% and had a residual stability of up to 98.9%. Moreover, the low-temperature splitting tensile strength of the asphalt mixture with 6% far-infrared radiation material increased by 21.3%. The friction coefficient of the asphalt mixtures with 6% and 12% far-infrared radiation material increased by 17.7% and 26.9%, respectively

Associations between interleukin-1 gene polymorphisms and coronary heart disease risk: a meta-analysis.

OBJECTIVE: A great number of studies regarding the associations between IL-1B-511, IL-1B+3954 and IL-1RN VNTR polymorphisms within the IL-1gene cluster and coronary heart disease (CHD) have been published. However, results have been inconsistent. In this study, a meta-analysis was performed to investigate the associations. METHODS: Published literature from PubMed and Embase databases were searched for eligible publications. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random- or fixed- effect model. RESULTS: Thirteen studies (3,219 cases/2,445 controls) for IL-1B-511 polymorphism, nine studies (1,828 cases/1,818 controls) for IL-1B+3954 polymorphism and twelve studies (2,987 cases/ 2,208 controls) for IL-1RN VNTR polymorphism were included in this meta analysis. The results indicated that both IL-1B-511 and IL-1B+3954 polymorphisms were not associated with CHD risk (IL-1B-511 T vs. C: OR = 0.98, 95%CI 0.87-1.09; IL-1B+3954 T vs. C: OR = 1.06, 95%CI 0.95-1.19). Similarly, there was no association between IL-1RN VNTR polymorphism and CHD risk (*2 vs. L: OR = 1.00, 95%CI 0.85-1.17). CONCLUSIONS: This meta-analysis suggested that there were no associations between IL-1 gene cluster polymorphisms and CHD

Relationship between optimum asphalt aggregate ratio and infrared powder content.

<p>Relationship between optimum asphalt aggregate ratio and infrared powder content.</p