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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.

The incidence and mortality of gastric cancer are in the forefront of the tumor, and the prognosis is poor, especially in the middle and advanced stage. Even with comprehensive treatment, the 5- year survival is very low. The development of precision medicine has extended the survival of patients, and fibroblast growth factor receptor (FGFR) has gradually become a popular target for the treatment of gastric cancer. In this paper, the common FGFR alteration types in gastric cancer and the exploration of FGFR inhibitors in the field of gastric cancer were reviewed, and the challenges were analyzed.