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Nicotinamide adenine dinucleotide (NAD+) is a central and pleiotropic metabolite involved in cellular energy metabolism, cell signaling, DNA repair, and protein modifications. Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Metabolic stress and aging directly affect the cardiovascular system. Compelling data suggest that NAD + levels decrease with age, obesity, and hypertension, which are all notable risk factors for CVD. In addition, the therapeutic elevation of NAD + levels reduces chronic low-grade inflammation, reactivates autophagy and mitochondrial biogenesis, and enhances oxidative metabolism in vascular cells of humans and rodents with vascular disorders. In preclinical models, NAD + boosting can also expand the health span, prevent metabolic syndrome, and decrease blood pressure. Moreover, NAD + storage by genetic, pharmacological, or natural dietary NAD + -increasing strategies has recently been shown to be effective in improving the pathophysiology of cardiac and vascular health in different animal models, and human health. Here, we review and discuss NAD + -related mechanisms pivotal for vascular health and summarize recent experimental evidence in NAD + research directly related to vascular disease, including atherosclerosis, and coronary artery disease. Finally, we comparatively assess distinct NAD + precursors for their clinical efficacy and the efficiency of NAD + elevation in the treatment of major CVD. These findings may provide ideas for new therapeutic strategies to prevent and treat CVD in the clinic.

Introductionβ-nicotinamide mononucleotide (β-NMN) is an essential precursor of nicotinamide adenine dinucleotide (NAD+) and plays a key role in supplying NAD+ and maintaining its levels. Existing methods for NMN production have some limitations, including low substrate availability, complex synthetic routes, and low synthetic efficiency, which result in low titers and high costs.MethodsWe constructed high-titer, genetically engineered strains that produce NMN through a new pathway. Bacillus subtilis WB600 was used as a safe chassis strain. Multiple strains overexpressing NadE, PncB, and PnuC in various combinations were constructed, and NMN titers of different strains were compared via shake-flask culture.ResultsThe results revealed that the strain B. subtilis PncB1-PnuC exhibited the highest total and extracellular NMN titers. Subsequently, the engineered strains were cultured in a 5-L fermenter using batch and fed-batch fermentation. B. subtilis PncB1-PnuC achieved an NMN titer of 3,398 mg/L via fed-batch fermentation and glucose supplementation, which was 30.72% higher than that achieved via batch fermentation.DiscussionThis study provides a safe and economical approach for producing NMN on an industrial scale.

The electrocardiogram (ECG) is a widely used diagnostic tool for cardiovascular diseases. However, ECG recording is often subject to various noises, which can limit its clinical evaluation. To address this issue, we propose a novel Transformer-based convolutional neural network framework with adaptively parametric ReLU (APtrans-CNN) for ECG signal denoising. The proposed APtrans-CNN architecture combines the strengths of transformers in global feature learning and CNNs in local feature learning to address the inadequacy of learning with long sequence time-series features. By fully exploiting the global features of ECG signals, our framework can effectively extract critical information that is necessary for signal denoising. We also introduce an adaptively parametric ReLU that can assign a value to the negative information contained in the ECG signal, thereby overcoming the limitation of ReLU to retain negative information. Additionally, we introduce a dynamic feature aggregation module that enables automatic learning and retention of valuable features while discarding useless noise information. Results obtained from two datasets demonstrate that our proposed APtrans-CNN can accurately extract pure ECG signals from noisy datasets and is adaptable to various applications. Specifically, when the input consists of ECG signals with a signal-to-noise ratio (SNR) of -4 dB, APtrans-CNN successfully increases the SNR to more than 6 dB, resulting in the diagnostic model's accuracy exceeding 96%.

The preparation of ceramic materials with complex porous structures through photopolymerization-based 3D printing requires the development of stable and printable slurries. In this study, zirconium acetylacetonate was incorporated into the thiol vinyl organosilicon prepolymer to create a photosensitive Si–Zr–O–C slurry. Regarding the natural bone structures and the Tyson polygon principle, a gradient pore structure was designed and then printed using a digital light processing 3D printer. After printing, the effects of sintering temperatures on the phase composition and structure of Si–Zr–O–C ceramics were systematically investigated. Subsequently, a comparative analysis of structure and properties was performed on sintered samples with different zirconium acetylacetonate contents. The results revealed that the sample containing 30 wt. % zirconium acetylacetonate exhibited a higher compressive strength of 9.70 ± 0.28 MPa and a lower room temperature thermal conductivity of 0.528 W m−1 K−1. This study confirmed the significant potential of using 3D printing technology to prepare Si–Zr–O–C precursor ceramics with a porous structure.

Over the years, microbial community composition in the rhizosphere has been extensively studied as the most fascinating topic in microbial ecology. In general, plants affect soil microbiota through rhizodeposits and changes in abiotic conditions. However, a consensus on the response of microbiota traits to the rhizosphere and bulk soils in various ecosystems worldwide regarding community diversity and structure has not been reached yet. Here, we conducted a meta-analysis of 101 studies to investigate the microbial community changes between the rhizosphere and bulk soils across various plant species (maize, rice, vegetables, other crops, herbaceous, and woody plants). Our results showed that across all plant species, plant rhizosphere effects tended to reduce the rhizosphere soil pH, especially in neutral or slightly alkaline soils. Beta-diversity of bacterial community was significantly separated between into rhizosphere and bulk soils. Moreover, r-strategists and copiotrophs (e.g. Proteobacteria and Bacteroidetes) enriched by 24-27% in the rhizosphere across all plant species, while K-strategists and oligotrophic (e.g. Acidobacteria, Gemmatimonadete, Nitrospirae, and Planctomycetes) decreased by 15-42% in the rhizosphere. Actinobacteria, Firmicutes, and Chloroflexi are also depleted by in the plant rhizosphere compared with the bulk soil by 7-14%. The Actinobacteria exhibited consistently negative effect sizes across all plant species, except for maize and vegetables. In Firmicutes, both herbaceous and woody plants showed negative responses to rhizosphere effects, but those in maize and rice were contrarily enriched in the rhizosphere. With regards to Chloroflexi, apart from herbaceous plants showing a positive effect size, the plant rhizosphere effects were consistently negative across all other plant types. Verrucomicrobia exhibited a significantly positive effect size in maize, whereas herbaceous plants displayed a negative effect size in the rhizosphere. Overall, our meta-analysis exhibited significant changes in microbial community structure and diversity responding to the plant rhizosphere effects depending on plant species, further suggesting the importance of plant rhizosphere to environmental changes influencing plants and subsequently their controls over the rhizosphere microbiota related to nutrient cycling and soil health.

Abstract Background Increased expression of the transcription factor Forkhead box M1 (FOXM1) has been reported to play an important role in the progression and development of multiple tumors, but the molecular mechanisms that regulate FOXM1 expression remain unknown, and the role of FOXM1 in aerobic glycolysis is still not clear. Methods The expression of FOXM1 and NADPH oxidase 4 (NOX4) in normal brain tissues and glioma was detected in data from the TCGA database and in our specimens. The effect of NOX4 on the expression of FOXM1 was determined by Western blot, qPCR, reactive oxygen species (ROS) production assays, and luciferase assays. The functions of NOX4 and FOXM1 in aerobic glycolysis in glioblastoma cells were determined by a series of experiments, such as Western blot, extracellular acidification rate (ECAR), lactate production, and intracellular ATP level assays. A xenograft mouse model was established to test our findings in vivo. Results The expression of FOXM1 and NOX4 was increased in glioma specimens compared with normal brain tissues and correlated with poor clinical outcomes. Aberrant mitochondrial reactive oxygen species (ROS) generation of NOX4 induced FOXM1 expression. Mechanistic studies demonstrated that NOX4-derived MitoROS exert their regulatory role on FOXM1 by mediating hypoxia-inducible factor 1α (HIF-1α) stabilization. Further research showed that NOX4-derived MitoROS-induced HIF-1α directly activates the transcription of FOXM1 and results in increased FOXM1 expression. Overexpression of NOX4 or FOXM1 promoted aerobic glycolysis, whereas knockdown of NOX4 or FOXM1 significantly suppressed aerobic glycolysis, in glioblastoma cells. NOX4-induced aerobic glycolysis was dependent on elevated FOXM1 expression, as FOXM1 knockdown abolished NOX4-induced aerobic glycolysis in glioblastoma cells both in vitro and in vivo. Conclusion Increased expression of FOXM1 induced by NOX4-derived MitoROS plays a pivotal role in aerobic glycolysis, and our findings suggest that inhibition of NOX4-FOXM1 signaling may present a potential therapeutic target for glioblastoma treatment.

Turnouts are the weak spot in high-speed rail systems, and it is simple for the phenomenon of the wheel–rail force and the carbody lateral acceleration over-limit to arise when the train passes through, which affects the service life of the rail and the running stability of the train. In this paper, the turnout with wheel–rail force over-limit and carbody lateral acceleration over-limit is selected for analysis, and the profiles of the wheel and rail are monitored. Then, the vehicle–turnout coupled multi-body dynamics model is simulated. Additionally, the portable vibration analyzer, the comprehensive inspection train, and the wheel–rail contact dynamic stress tester monitors the data and evaluates the impact of rail grinding on high-speed railway. The results of this study demonstrated that the turnout profiles are in good agreement with the standard wheel profiles following grinding, and the wheel–rail contact point and equivalent conicity both improved. When the train passes the ground turnout at high speed with and without the wheel polygonal wear, the wheel–rail force and the carbody acceleration were clearly improved. Using the wheel–rail contact dynamic stress tester, the comprehensive inspection train, and the portable vibration analyzer monitoring the changes in the carbody acceleration, the wheel–rail force and the carbody acceleration are definitely better after grinding. Similar to the pattern in the simulation, the train’s running steadiness increased by grinding.

Abstract Forkhead box (Fox) transcription factors play important roles in mammalian development and disease. However, their function in mouse somatic cell reprogramming remains unclear. Here, we report that FoxD subfamily and FoxG1 accelerate induced pluripotent stem cells (iPSCs) generation from mouse fibroblasts as early as day4 while FoxA and FoxO subfamily impede this process obviously. More importantly, FoxD3, FoxD4 and FoxG1 can replace Oct4 respectively and generate iPSCs with germline transmission together with Sox2 and Klf4. On the contrary, FoxO6 almost totally blocks reprogramming through inhibiting cell proliferation, suppressing the expression of pluripotent genes and hindering the process of mesenchymal to epithelial transition (MET). Thus, our study uncovers unexpected roles of Fox transcription factors in reprogramming and offers new insights into cell fate transition.

Intracranial dissemination is rare among patients with glioblastoma multiforme (GBM). Very few GBM patients develop symptoms from intracranial dissemination, as most do not surviving long enough for intracranial dissemination to become clinically evident. Herein, we report a case of GBM in a 39-year-old woman who underwent surgical resection, concomitant chemoradiotherapy, and seven courses of adjuvant chemotherapy with temozolomide. The patient then complained of an instable gait and hearing loss. Imaging studies demonstrated that although the primary intracranial tumors were well-controlled by treatment, contralateral cerebellopontine angle seeding dissemination was present. The patient died 3 months after the diagnosis of seeding dissemination. In light of a previous report and our current case, heightened awareness could promote surgical strategies that minimize the possibility of dissemination, including avoiding ventricular entry or a no-touch strategy.

In recent years, deep-learning-based hyperspectral image (HSI) classification networks have become one of the most dominant implementations in HSI classification tasks. Among these networks, convolutional neural networks (CNNs) and attention-based networks have prevailed over other HSI classification networks. While convolutional neural networks with perceptual fields can effectively extract local features in the spatial dimension of HSI, they are poor at capturing the global and sequential features of spectral–spatial information; networks based on attention mechanisms, for example, Transformer, usually have better ability to capture global features, but are relatively weak in discriminating local features. This paper proposes a fusion network of convolution and Transformer for HSI classification, known as FusionNet, in which convolution and Transformer are fused in both serial and parallel mechanisms to achieve the full utilization of HSI features. Experimental results demonstrate that the proposed network has superior classification results compared to previous similar networks, and performs relatively well even on a small amount of training data.

Abstract Background Cancer cells maintain energy metabolism mainly by glycolysis, even under sufficient oxygen conditions. It gives cancer cells better growth advantages under complicated internal environment. KPNA2 is a novel oncogene that has received much attention in recent years, but the exact mechanisms of KPNA2 in tumorigenesis and progression are largely unknown. Especially its potential roles in the metabolic transformation of tumors still remain to be explored. Methods The expressions of KPNA2 in glioblastoma and normal human brain samples were analyzed by immunohistochemical analysis. The activities of key enzymes in glycolysis, the production of lactate acid and glucose uptake were investigated by colorimetry. GLUT-1 expression was measured by flow cytometry. CCK8 was used to examine the cell viability in vitro, and the xenograft models in nude mice were established to explore the roles of KPNA2 in vivo. In addition, Co-IP, subcellular fractionation, western blot, immunofluorescence and luciferase assay were used to investigate the internal connection between KPNA2, c-myc and E2F1. Results In the present study, we found that KPNA2 was highly expressed in the glioma compared to the normal brain tissues. Level of KPNA2 was an independent predictor of prognosis in the glioma patients. Knockdown of KPNA2 in the glioblastoma cell lines U87 and U251 decreased deoxyglucose uptake, activities of the key glycolytic enzymes and lactate production. The level of oxidative phosphorylation (OXPHOS) was moderately decreased. Additioanlly, tumor proliferation and invasiveness were concomitantly downregulated. We have identified c-myc as a potential mediator of KPNA2. Aberrant expression of KPNA2 significantly changed the subcellular distribution of c-myc as well as its expression level. E2F1, another key cargo protein of KPNA2, was further identified to play a potential role in regulating the transcription of c-myc by KPNA2. Conclusions Our findings suggested that KPNA2, a potential tumor oncogene, performs its function in part via regulating cellular metabolism through c-myc signaling axis. It would provide a possible explanation for Warburg effect and thus offer a new perspective to the roles of KPNA2 in gliomagenesis.

To improve the performance of the governing system as well as the stability of the power system, the authors propose grey prediction extension control (GPEC) in the design of generator governing system. Comparing with the conventional control strategy such as conventional proportional–integral–derivative control and simple extension control, GPEC is more suitable for the complex, huge‐dimension and time‐varying modern power systems. Both a simple hydropower system and a typical multi‐machine system are studied, respectively. The simulation results indicate that the proposed GPEC governor controller performs better in reducing overshoot and adjusting time with superiority in leading the system into a stable state.

Wire arc additive manufacturing (WAAM) of aluminum-magnesium (Al–Mg) ER5356 alloy deposits is accomplished by cold metal transfer (CMT). During the process, the temperature change of the alloy deposits has a great influence on molding quality, and the microstructure and properties of alloy deposits are also affected by the complex thermal history of the additive manufacturing process. Here, we used an inter-layer cooling process and controlled the heat input process to attempt to reduce the influence of thermal history on alloy deposits during the additive process. The results showed that inter-layer cooling can optimize the molding quality of alloy deposits, but with the disadvantages of a long test time and slow deposition rate. A simple and uniform reduction of heat input makes the molding quality worse, but controlling the heat input by regions can optimize the molding quality of the alloy deposits. The thermophysical properties of Al-Mg alloy deposits were measured, and we found that the specific heat capacity and thermal diffusivity of alloy deposits were not obviously affected by the temperature. The microstructure and morphology of the deposited specimens were observed and analyzed by microscope and electron back-scatter diffraction (EBSD). The process of controlled heat input results in a higher deposition rate, less side-wall roughness, minimum average grain size, and less coarse recrystallization. In addition, different thermal histories lead to different texture types in the inter-layer cooling process. Finally, a controlled heat input process yields the highest average microhardness of the deposited specimen, and the fluctuation range is small. We expect that the process of controlling heat input by model height region will be widely used in the WAAM field.

Resonant tunneling can lead to inverse tunnel magnetoresistance when impurity levels rather than direct tunneling dominate the transport process. We fabricated hybrid magnetic tunnel junctions of CoFe/LiF/EuS/Ti, with an epitaxial LiF energy barrier joined with a polycrystalline EuS spin-filter barrier. Due to the water solubility of LiF, the devices were fully packaged in situ. The devices showed sizeable positive TMR up to 16% at low bias voltages but clearly inverted TMR at higher bias voltages. The TMR inversion depends sensitively on the thickness of LiF, and the tendency of inversion disappears when LiF gets thick enough and recovers its intrinsic properties.