Association of renin–angiotensin system inhibitors use with short- and long-term mortality in patients with aortic stenosis: A systematic review and meta-analysis

PurposeThe present study aimed to investigate the association of renin–angiotensin system inhibitors (RASi) with short- and long-term mortality in patients with aortic stenosis (AS).MethodsA systematic search was performed in PubMed, Embase, and Cochrane library databases for relevant studies published before March 2022. Studies meeting the inclusion criteria were included to assess the effect of RASi on short-term (≤30 days) and long-term (≥1 year) mortality in patients with AS.ResultsA total of 11 studies were included in the meta-analysis. Our results demonstrated that RASi reduced short-term mortality (OR = 0.76, 95% CI 0.63–0.93, p = 0.008) after aortic valve replacement (AVR). Subgroup analysis revealed that RASi was still associated with lower short-term mortality after transcatheter aortic valve replacement (TAVR); however, the association was relatively weak in patients who underwent surgical aortic valve replacement (SAVR). For long-term mortality, the pooled OR was 1.04 (95% CI 0.88–1.24, p = 0.63) after sensitivity analysis in patients who did not undergo AVR. In addition, our study confirmed that RASi significantly reduced long-term mortality (OR = 0.57, 95% CI 0.44–0.74, p < 0.0001) in patients who underwent AVR. Subgroup analysis showed that both TAVR and SAVR groups treated with RASi had lower long-term mortality.ConclusionRenin–angiotensin system inhibitors did not change long-term mortality in AS patients who did not undergo AVR. However, RASi reduced short- and long-term mortality in patients who underwent AVR

Inhibition of Histone Deacetylases Prevents Cardiac Remodeling After Myocardial Infarction by Restoring Autophagosome Processing in Cardiac Fibroblasts

Background/Aims: Histone deacetylases (HDACs) play a critical role in the regulation of gene transcription, cardiac development, and diseases. The aim of this study was to investigate whether the inhibition of HDACs improves cardiac remodeling and its underlying mechanisms in a mouse myocardial infarction (MI) model. Methods: The HDAC inhibitor trichostatin A (TSA, 0.1 mg/kg/day) was administered via daily intraperitoneal injections for 8 consecutive weeks after MI in C57/BL mice. Echocardiography and tissue histopathology were used to assess cardiac function. Cultured neonatal rat cardiac fibroblasts (NRCFs) were subjected to simulated hypoxia in vitro. Autophagic flux was measured using the tandem fluorescent mCherry-GFP-LC3 assay. Western blot was used to detect autophagic biomarkers. Results: After 8 weeks, the inhibition of HDACs in vivo resulted in improved cardiac remodeling and hence better ventricular function. MI was associated with increased LC3-II expression and the accumulation of autophagy adaptor protein p62, indicating impaired autophagic flux, which was reversed by TSA treatment. Cultured NRCFs exhibited increased cell death after simulated hypoxia in vitro. Increased cell death was associated with markedly increased numbers of autophagosomes but not autolysosomes, as assessed by punctate dual fluorescent mCherry-green fluorescent protein tandem-tagged light chain-3 expression, indicating that hypoxia resulted in impaired autophagic flux. Importantly, TSA treatment reversed hypoxia-induced impaired autophagic flux and led to a 40% decrease in cell death. This was accompanied by improved mitochondrial membrane potential. The beneficial effects of TSA therapy were abolished by RNAi intervention targeting LAMP2; likewise, in vivo delivery of chloroquine abolished the TSA-mediated cardioprotective effects. Conclusion: Our results provide evidence that the HDAC inhibitor TSA prevents cardiac remodeling after MI and is dependent on restoring autophagosome processing of cardiac fibroblasts

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Discovering Novel Therapeutics for Triple Negative Breast Cancer

Triple negative breast cancer (TNBC), associated with aggressive tumor behavior and worse outcomes, is the most challenging subtype in breast cancer. Chemotherapy remains the major treatment for TNBC, due to the lack of recognized molecular targets for therapy and the ineffectiveness of common treatments. Therefore, there is still an unmet need to discover novel TNBC therapies. A first-of-a-kind efficacy-based fingerprinting approach to identify potent anticancer candidates from natural products without the need for isolating individual components from the extracts is proposed. The fingerprint profiles of 22 ginger samples using liquid chromatography-mass spectroscopy were characterized and the anti-proliferative effects (IC50) of these samples on TNBC cells were evaluated. The supervised principal component analysis identified a subset of analytes whose abundance strongly associated with the IC50 values of the ginger extracts, providing a link between ginger extract composition and in vitro anticancer efficacy. Next, the effects of PIK75, a small molecule p110α and DNA-PK dual inhibitor, on TNBC treatment were evaluated. PIK75 showed potent inhibition effects in vitro on the growth, colony formation and cellular mobilization of TNBC cells, and decreased tumor growth in a mouse model. However, drug combination treatments on TNBC cells using single p110α and DNA-PK inhibitors did not show synergistic effects. Thus, there might be other pathways involved in the inhibition effects of PIK75 other than these two proteins. The discovery of novel lead compounds from natural products for TNBC based on NCI-60 human tumor cell lines screen data was investigated. Two series of compounds isolated or derived from Bridelia balansae Tutcher and Miliusa plants were tested for their anti-TNBC effects since they possess structural similarity with compounds recorded in NCI-60. Two miliusanes were chosen for anti-TNBC efficacy and mechanism study. The direct protein binding target of K1 was also identified. Overall, this dissertation demonstrated that alternative therapeutics can be found for treating TNBC. It focused on the discovery and development of TNBC novel therapeutics from both natural products and kinase inhibitors, which improved the drug discovery efficiency from natural products and could serve as pre-clinical profiles of the lead compounds

Nuclear Mass Predictions of the Relativistic Density Functional Theory with the Kernel Ridge Regression and the Application to <i>r</i>-Process Simulations

The kernel ridge regression (KRR) and its updated version taking into account the odd-even effects (KRRoe) are employed to improve the mass predictions of the relativistic density functional theory. Both the KRR and KRRoe approaches can improve the mass predictions to a large extent. In particular, the KRRoe approach can significantly improve the predictions of the one-nucleon separation energies. The extrapolation performances of the KRR and KRRoe approaches to neutron-rich nuclei are examined, and the impacts of the KRRoe mass corrections on the r-process simulations are studied. It is found that the KRRoe mass corrections for the nuclei in the r-process path are remarkable in the light mass region, e.g., A150, and this could influence the corresponding r-process abundances

Nuclear Mass Predictions of the Relativistic Density Functional Theory with the Kernel Ridge Regression and the Application to r-Process Simulations

The kernel ridge regression (KRR) and its updated version taking into account the odd-even effects (KRRoe) are employed to improve the mass predictions of the relativistic density functional theory. Both the KRR and KRRoe approaches can improve the mass predictions to a large extent. In particular, the KRRoe approach can significantly improve the predictions of the one-nucleon separation energies. The extrapolation performances of the KRR and KRRoe approaches to neutron-rich nuclei are examined, and the impacts of the KRRoe mass corrections on the r-process simulations are studied. It is found that the KRRoe mass corrections for the nuclei in the r-process path are remarkable in the light mass region, e.g., A&lt;150, and this could influence the corresponding r-process abundances

Enhanced Mechanical and Microstructural Properties of Portland Cement Composites Modified with Submicron Metakaolin

This work aims to study the influence of submicron metakaolin (SMK) on the mechanical strength, pore structure, and microstructural properties of hardened cement-based slurry (HCS). Portland cement was replaced by SMK at a proportion of 1, 3, 5, and 7 wt%. The compressive strength and flexural strength of the HCS samples were tested at a curing period of 3, 7, 14, and 28 days, and the pore structure of the specimens was analyzed by mercury intrusion porosimetry (MIP) at a curing period of 3 and 28 days. The microstructure characteristics of the hardened samples were investigated by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). Thermogravimetric analysis (TGA) was also employed to analyze the change in the chemical composition of the HCS. The results showed that the SMK could accelerate the hydration rate of the cement and could improve the mechanical properties of the HCS; the compressive strength and flexural strength of the HCS samples were remarkably enhanced, compared to those of the plain cement, by 67 and 46%, respectively, at a curing period of 3 days and by 33 and 35%, respectively, at a curing period of 28 days. The SMK had a significant impact on the internal pore structure of the hardened samples, and the number of pores with a diameter of larger than 3000 nm significantly decreased. Because the hydration products filled the pores, the microstructure of the HCS was further refined and densified with the addition of SMK. Submicron metakaolin has a simple process and high activity, which can significantly improve the performance of the cement slurry. Therefore, submicron metakaolin has the potential for practical engineering applications

Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios

Research on Agricultural Machine Scheduling in Hilly Areas Based on Improved Non-Dominated Sorting Genetic Algorithm-III

To address the problem of inefficient continuous multi-task scheduling operations, a scheduling model was established with the optimization objective of minimum total scheduling time to solve the problem of agricultural machinery continuous performing multiple tasks in agricultural production in hilly areas. An Improved Non-dominated Sorting Genetic Algorithm-III (Improved NSGA-III) was proposed to solve the agricultural machinery scheduling problem. The algorithm employed a two-stage coding mechanism to ensure the uniform distribution of the population and reduce the search solution space. The selection of paternal individuals is based on crowding degree, enabling individuals with better genes to participate in evolution. The domain search strategy of partial solution was introduced to improve the global search ability of the algorithm. The performance of the Improved NSGA-III algorithm and the other three algorithms was compared using farmland data from the experimental area. Results showed that the Improved NSGA-III algorithm outperforms the other three algorithms in terms of minimum total scheduling time, with reductions of 13.89&#x0025;, 43.81&#x0025; and 57.19&#x0025;, respectively, verifying the effectiveness and reliability of the algorithm