Structure, morphology and magnetic properties of flowerlike gamma-Fe2O3@NiO core/shell nanocomposites synthesized from different precursor concentrations

The flowerlike gamma-Fe2O3@NiO core/shell nanocomposites are synthesized by the two-step method. Their structure and morphology can be controlled by tuning the precursor concentration. Microstructural analysis reveals that all the samples have distinct core/shell structure without impurities, and the NiO shells are built of many irregular nanosheets which enclose the surface of gamma-Fe2O3 core. As the precursor concentration decreases (i.e., more NiO content), the NiO grain grows significantly, and the thickness of NiO shells increases. Magnetic experiments are performed to analyze the influences of different microstructures on magnetic properties of samples and we have the following two results. First, at 5 K, along with increasing thickness of NiO shell, the saturation magnetization increases, while the residual magnetization decreases slightly. Second, the hysteresis loops under cooling field demonstrate that the value of exchange bias effect fluctuates between 13 Oe and 17 Oe. This is mainly because of the NiO shell that (i) is composed of irregular nanosheets with disordered orientations, and (ii) does not form a complete coating around gamma-Fe2O3 core

Natural foods resources and dietary ingredients for the amelioration of Helicobacter pylori infection

Helicobacter pylori (H. pylori) is a gastric-persistent pathogen that can cause peptic ulcer disease, gastric cancer, and mucosal-associated lymphoid tissue lymphoma. This pathogen is commonly treated with antibiotic-based triple or quadruple therapy. However, antibiotic therapy could result in the bacterial resistance, imbalance of gut microbiota, and damage to the liver and kidneys, etc. Therefore, there is an urgent need for alternative therapeutic strategies. Interestingly, natural food resources, like vegetables, fruits, spices, and edible herbs, have potent inhibitory effects on H. pylori. In this review, we systematically summarized these foods with supporting evidence from both animal and clinical studies. The results have indicated that natural foods may possess temporary inhibition effect on H. pylori rather than durable eradication, and may help to reduce H. pylori colonization, enhance the effect of antibiotics and modulate the host’s immune response

Pan-cancer analysis reveals potential of FAM110A as a prognostic and immunological biomarker in human cancer

BackgroundDespite great success, immunotherapy still faces many challenges in practical applications. It was previously found that family with sequence similarity 110 member A (FAM110A) participate in the regulation of the cell cycle and plays an oncogenic role in pancreatic cancer. However, the prognostic value of FAM110A in pan-cancer and its involvement in immune response remain unclear.MethodsThe Human Protein Atlas (HPA) database was used to detect the expression of FAM110A in human normal tissues, the Tumor Immune Estimation Resource (TIMER) and TIMER 2.0 databases were used to explore the association of FAM110A expression with immune checkpoint genes and immune infiltration, and the Gene Set Cancer Analysis (GSCA) database was used to explore the correlation between FAM110A expression and copy number variations (CNV) and methylation. The LinkedOmics database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Statistical analysis and visualization of data from the The Cancer Genome Atlas (TCGA) or the Genotype–Tissue Expression (GTEx) databases were performed using the R software (version 3.6.3). Clinical samples were validated using immunohistochemistry.ResultsFAM110A expression was elevated in most tumor tissues compared with that in normal tissues. CNV and methylation were associated with abnormal FAM110A mRNA expression in tumor tissues. FAM110A affected prognosis and was associated with the expression of multiple immune checkpoint genes and abundance of tumor-infiltrating immune cells across multiple types of cancer, especially in liver hepatocellular carcinoma (LIHC). FAM110A-related genes were involved in multiple immune-related processes in LIHC.ConclusionFAM110A participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in LIHC. FAM110A may serve as a prognostic and immunological biomarker for human cancer

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Synthesis of α-Heterosubstituted Ketones Through Sulfur Mediated Difunctionalization of Internal Alkynes

Synthesis of α-heterosubstituted ketones was achieved through sulfur mediated difunctionalization of internal alkynes in one-pot. The reaction design involves: phenyl substituted internal alkyne attacking the triflic anhydride activated diphenyl sulfoxide to give a sulfonium vinyl triflate intermediate, hydrolysis to give the α-sulfonium ketone, and then substitution with various nucleophiles. This method provides a unified route to access α-amino ketones, α-acyloxy ketones, α-thio ketones, α-halo ketones, α-hydroxy ketones, and related heterocyclic structures, in a rapid fashion.<br /

Non-linear and multi-domain modelling of a permanent magnet linear synchronous machine for free piston engine generators

Brosnan P, Tian G, Zhang H, Wu Z, Jin Y. Non-linear and multi-domain modelling of a permanent magnet linear synchronous machine for free piston engine generators. Energy Conversion and Management: X. 2022;14: 100195.The Free Piston Engine (FPE) can be considered a viable and promising option in future low-carbon technology development. When coupled to the Linear Electric Machine (LEM) to produce electrical energy, its characteristic non-linear dynamics typically have been described as linear when considering a systems-level modelling approach. This paper presents a multi-domain model of a Permanent Magnet Linear Synchronous Machine (PMLSM) for Free Piston Engine Generators (FPEG) and offers a detailed non-linear mathematical description of the machine dynamics. The model was implemented in a free-piston expander system and validated against experimental data from a test rig that has identical parameters. The simulation results indicate a strong correlation to the experimental data, which captured the dominant dynamics of the PMLSM and prove the satisfactory accuracy and performance of the model, together with a similar voltage and current output trace, indicating a cyclic energy output error of approximately 10 %. This paper aims to extend the current knowledge and literature within FPEG PMLSM design by considering the inherent non-linearity and multi-directional nature of the system dynamics and its interactions with multi-physical domains

Up-regulation of alpha-smooth muscle actin in cardiomyocytes from non-hypertrophic and non-failing transgenic mouse hearts expressing N-terminal truncated cardiac troponin I

We previously reported that a restrictive N-terminal truncation of cardiac troponin I (cTnI-ND) is up-regulated in the heart in adaptation to hemodynamic stresses. Over-expression of cTnI-ND in the hearts of transgenic mice revealed functional benefits such as increased relaxation and myocardial compliance. In the present study, we investigated the subsequent effect on myocardial remodeling. The alpha-smooth muscle actin (α-SMA) isoform is normally expressed in differentiating cardiomyocytes and is a marker for myocardial hypertrophy in adult hearts. Our results show that in cTnI-ND transgenic mice of between 2 and 3 months of age (young adults), a significant level of α-SMA is expressed in the heart as compared with wild-type animals. Although blood vessel density was increased in the cTnI-ND heart, the mass of smooth muscle tissue did not correlate with the increased level of α-SMA. Instead, immunocytochemical staining and Western blotting of protein extracts from isolated cardiomyocytes identified cardiomyocytes as the source of increased α-SMA in cTnI-ND hearts. We further found that while a portion of the up-regulated α-SMA protein was incorporated into the sarcomeric thin filaments, the majority of SMA protein was found outside of myofibrils. This distribution pattern suggests dual functions for the up-regulated α-SMA as both a contractile component to affect contractility and as possible effector of early remodeling in non-hypertrophic, non-failing cTnI-ND hearts

Performance Investigation of Single–Piston Free Piston Expander–Linear Generator with Multi–Parameter Based on Simulation Model

The structural design and operating strategy of a free piston expander–linear generator (FPE–LG) has a major impact on performance. In this paper, the simulation model of single–piston FPE–LG was built and verified by combining the structural parameters of the existing test rig with a set of kinetic and thermodynamic equations. On this basis, the influence of the design and operating parameters of the device on the performance was studied, while keeping other parameters fixed. Then, a sensitivity analysis of power output and operating frequency was carried out. The results show that within a certain range of external load and intake beginning position, increasing the diameter of the intake and exhaust pipes, or reducing the piston rod diameter can improve the power output. Within a certain range of frictional coefficient and intake time, increasing the cylinder diameter and intake pressure, or reducing the piston assembly mass and back electromotive force (EMF) constant can increase the operating frequency. Both the power output and the operating frequency are most sensitive to the cylinder diameter among the design parameters. Among the operating parameters, power output is the most sensitive to intake pressure, and operating frequency is the most sensitive to intake beginning position. The optimization of structural design and operation strategy in expander provides important guiding significance for ORC waste heat recovery system

Codon optimization with deep learning to enhance protein expression

Abstract Heterologous expression is the main approach for recombinant protein production ingenetic synthesis, for which codon optimization is necessary. The existing optimization methods are based on biological indexes. In this paper, we propose a novel codon optimization method based on deep learning. First, we introduce the concept of codon boxes, via which DNA sequences can be recoded into codon box sequences while ignoring the order of bases. Then, the problem of codon optimization can be converted to sequence annotation of corresponding amino acids with codon boxes. The codon optimization models for Escherichia Coli were trained by the Bidirectional Long-Short-Term Memory Conditional Random Field. Theoretically, deep learning is a good method to obtain the distribution characteristics of DNA. In addition to the comparison of the codon adaptation index, protein expression experiments for plasmodium falciparum candidate vaccine and polymerase acidic protein were implemented for comparison with the original sequences and the optimized sequences from Genewiz and ThermoFisher. The results show that our method for enhancing protein expression is efficient and competitive