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The yield strength and Young's modulus of lattice structures are essential mechanical parameters that influence the utilization of materials in the aerospace and medical fields. Currently, accurately determining the Young's modulus and yield strength of lattice structures often requires conduction of a large number of experiments for prediction and validation purposes. To save time and effort to accurately predict the material yield strength and Young's modulus, based on the existing experimental data, finite element analysis is employed to expand the dataset. An artificial neural network algorithm is then used to establish a relationship model between the topology of the lattice structure and Young's modulus (the yield strength), which is analyzed and verified. The Gibson–Ashby model analysis indicates that different lattice structures can be classified into two main deformation forms. To obtain an artificial neural network model that can accurately predict different lattice structures and be deployed in the prediction of BCC-FCC lattice structures, the artificial network model is further optimized and validated. Concurrently, the topology of disparate lattice structures gives rise to a certain discrete form of their dominant deformation, which consequently affects the neural network prediction. In conclusion, the prediction of Young's modulus and yield strength of lattice structures using artificial neural networks is a feasible approach that can contribute to the development of lattice structures in the aerospace and medical fields. [ABSTRACT FROM AUTHOR]

3D printed energy storage materials and devices (3DP‐ESMDs) have become an emerging and cutting‐edge research branch in advanced energy fields. To achieve satisfactory electrochemical performance, energy storage interfaces play a decisive role in burgeoning ESMD‐based 3D printing. Hence, it is imperative to develop effective interface engineering routes toward desirable 3DP‐ESMDs. In this tutorial review, recent advances in interface engineering for 3DP‐ESMDs are comprehensively provided and in‐depth discussion is offered. To begin with, basic interface engineering principles are introduced. Critical interface engineering strategies including 3D printing‐enabled structural design, composition modification, protective layer design, and 3D printed device optimization are then summarized and illustrated, accompanied by a discussion of pioneering work on 3D printed rechargeable batteries and electrochemical capacitors that has been made through significant interface engineering strategies. Finally, perspectives on interface engineering approaches in future 3DP‐ESMDs are presented. [ABSTRACT FROM AUTHOR]

A unique configuration based on internally integrated electrodes is proposed for flexible hybrid zinc-ion capacitor (HZIC) devices. An in-depth charge storage process is studied, confirming the high electrochemical promise of HZICs for future practical applications. [ABSTRACT FROM AUTHOR]

In this work, a novel nanocomposite of highly-dispersed MoS2 nanosheets supported on alkali-activated halloysite nanotubes (a-HNTs) was fabricated via a simple hydrothermal method. The alkali (5 M NaOH herein) could attack the inert outer surface of HNTs and thus abundant surface defects were created, while the crystal structure and tube morphology of HNTs were still preserved. Electron microscopy also evidenced that few MoS2 sheets could grow on the outer surface of raw HNTs while they were uniformly assembled on both the outer surface and inner lumen of the a-HNTs. The above phenomenon suggested that both the defects at the outer surface and Al–OH at the lumen could serve as nucleation sites for the growth of MoS2 nanosheets. Furthermore, the as-prepared MoS2/a-HNT nanocomposite exhibited significantly improved photocatalytic performance for rhodamine B (RhB) degradation, compared with the MoS2/HNTs and pristine MoS2 microspheres, and photogenerated holes (h+) played a more important role than hydroxyl radicals (˙OH) and superoxide radicals (˙O2−) during the photocatalysis, which was confirmed by radical trapping experiments. This work provides a low-cost fabrication of high-performance 2D materials by using modified natural minerals as carriers. [ABSTRACT FROM AUTHOR]

Yiqi Fumai lyophilized injection (YQFM), a compound traditional Chinese medicine prescription derived from "Sheng Mai Powder," is approved for the treatment of cardiovascular diseases. YQFM is usually prescribed in combination with some Western medicines to treat patients, such as aspirin, nifedipine, and clopidogrel. However, the herb-drug interactions (HDIs) of YQFM are still unclear. We determined the effect of YQFM on drug metabolism-related CYP450 enzymes by in vitro assays. And the effects of YQFM on the pharmacokinetics of aspirin, nifedipine, or clopidogrel were analyzed in rats, as well as the effect of YQFM on the prothrombin time of aspirin or clopidogrel, to evaluate the safety and efficacy of co-administration. Our study indicated that the clinical dose of YQFM did not significantly influence the relevant CYP450 isoenzymes. Besides, YQFM had no effect on the pharmacokinetics of aspirin, nifedipine, or clopidogrel single and multiple administrations in rats. In pharmacodynamics study, YQFM also had no impact on prothrombin time of aspirin or clopidogrel. Based on the results of pharmacogenomics, pharmacokinetics, and pharmacodynamics, the HDIs of YQFM have a good safety profile, and the combination with the above three drugs might have synergistic effects due to the different efficacy of YQFM-quality markers., (© 2024 John Wiley & Sons Ltd.)

In this study, we reported the first long-term monitoring of SARS-CoV-2 in wastewater in Mainland China from November 2021 to October 2023. The city of Shijiazhuang was employed for this case study. We developed a triple reverse transcription droplet digital PCR (RT-ddPCR) method using triple primer-probes for simultaneous detection of the N1 gene, E gene, and Pepper mild mottle virus (PMMoV) to achieve accurate quantification of SARS-CoV-2 RNA in wastewater. Both the RT-ddPCR method and the commercial multiplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) method were implemented for the detection of SARS-CoV-2 in wastewater in Shijiazhuang City over a 24-month period. Results showed that SARS-CoV-2 was detected for the first time in the wastewater of Shijiazhuang City on 10 November 2022. The peak of COVID-19 cases occurred in the middle of December 2022, when the concentration of SARS-CoV-2 in the wastewater was highest. The trend of virus concentration increases and decreases forming a "long-tailed" shape in the COVID-19  outbreak and recession cycle. The results indicated that both multiplex RT-ddPCR and RT-qPCR are effective in detecting SARS-CoV-2 in wastewater, but RT-ddPCR is capable of detecting low concentrations of SARS-CoV-2 in wastewater which is more efficient. The SARS-CoV-2 abundance in wastewater is correlated to clinical data, outlining the public health utility of this work.HighlightsFirst long-term monitoring of SARS-CoV-2 in wastewater in Mainland ChinaCOVID-19 outbreak was tracked in Shijiazhuang City from outbreak to containmentWastewater was monitored simultaneously using RT-ddPCR and RT-qPCR methodsTriple primer-probe RT-ddPCR detects N1 and E genes of SARS-CoV-2 and PMMoV.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus that undergoes rapid mutation. Based on viral whole genome sequencing analysis in Hebei Province, China, we identified several essential single nucleotide variants (SNVs) on primer-probe regions accumulating within some Omicron variants' genomes. In this study, we focused on three SNVs, C28290T, T28297C, and C28311T emerging on 2019-nCoV-N1 (CDC-N1) primer-probe regions, recommended by CDC in 2020, and two SNVs, C26270T, A26275G emerging on E (Charité-E) primer-probe regions recommended by Charité, Germany. Our findings revealed that the presence of one or two SNVs in the primer or probe region affected the sensitivity of reverse transcription-quantitative polymerase chain reaction and droplet digital PCR to varying extents. This discovery underscores the importance of continuously monitoring the whole genome sequences of SARS-CoV-2 variants, especially the primer-probe targeting regions, and correspondingly updating commercial test kits or recommended primer-probe sequence sets., Importance: The emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has resulted in a growing number of mutations in its genome, presenting new challenges for the diagnosis of SARS-CoV-2 using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and droplet digital PCR (RT-ddPCR) methods. There is an urgent need to develop refined methods for modifying primers and probes to improve the detection of these emerging variants. In this study, our focus was on the SNVs that have emerged in the CDC-N1 and Charité-E primer-probe regions. Our research has confirmed that the presence of these SNVs in the primer or probe region can significantly affect the results of coronavirus disease 2019 tests. we have developed and validated a modified detection method that can provide higher sensitivity and specificity. This study emphasizes the importance of refining the primer-probe sets to ensure the diagnostic accuracy of RT-qPCR and RT-ddPCR detection., Competing Interests: The authors declare no conflict of interest.