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Manufactured sand concrete (MSC) has increasingly applied in engineering. However, how to enhance the thermal crack resistance of MSC has not clearly studied yet, which limits the wide applications of manufactured sand in engineering. We have adopted the method of mixing limestone powder (LP) to make MSC with four mass fractions (wt.%) of 5%, 10%, 15%, and 20% of LP content, designed the mix proportion of concrete, tested their mechanical properties, observed their microstructure by scanning electron microscopy (SEM) and investigated the effect of LP on anti-cracking performance using temperature stress testing machine (TSTM). These findings reveal that the mechanical properties and thermal crack resistance of 15% LP MSC are the best. Our results also provide a research basis for the MSC to be widely used in engineering. [ABSTRACT FROM AUTHOR]

Due to the molding-free property and dry shrinkage of extrusion-based three-dimensional printable concrete (3DPC), the precision issues of 3DPC have not been solved effectively. One of the viable solutions for 3DPC precision improvement is to print using ultra-thin filaments. The challenges of ultra-thin-filament printing are extrudability, flowability, and fast solidification. To overcome these challenges and enhance precision, a customized 3D concrete printer with an ultra-thin diameter nozzle (6 mm) and fully sealed extrusion system was developed, and the mix design of ultra-thin-filament 3DPC (UTF-3DPC) was studied, including ingredients such as fly ash (FA), silica fume (SF), ordinary Portland cement (OPC), sodium dodecyl sulfate and cellulose (SDSC), water reducer, water, and sand. The function of UTF-3DPCs flowability and fast solidification with the proportion of water and SDSC was explored to obtain the optimal mix design. The standard compressive and flexural strengths of UTF-3DPC specimens were compared with the mold-cast vibrated and the mold-cast non-vibrated concrete. Their meso-scale and micro-scale structures were analyzed to expose the strength mechanism, according to the scanning electron microscope (SEM) images. A suitable mix design of UTF-3DPC was obtained and UTF-3DPC strength reached 80% of standard mold-cast concrete. The findings reported here provide a pathway to improve the precision of 3DPC and extend the application of 3D printing technology in engineering. [ABSTRACT FROM AUTHOR]

Background: This study aims to elucidate the role of mitochondrial autophagy in metabolic dysfunction-associated steatohepatitis (MASH) by identifying and validating key mitophagy-related genes and diagnostic models with diagnostic potential. Methods: The gene expression profiles and clinical information of MASH patients and healthy controls were obtained from the Gene Expression Omnibus database (GEO). Limma and functional enrichment analysis were used to identify the mitophagy-related differentially expressed genes (mito-DEGs) in MASH patients. Machine learning models were used to select key mito-DEGs and evaluate their efficacy in the early diagnosis of MASH. The expression levels of the key mito-DEGs were validated using datasets and cell models. A nomogram was constructed to assess the risk of MASH progression based on the expression of the key mito-DEGs. The mitophagy-related molecular subtypes of MASH were evaluated. Results: Four mito-DEGs, namely MRAS, RAB7B, RETREG1, and TIGAR were identified. Among the machine learning models employed, the Support Vector Machine demonstrated the highest AUC value of 0.935, while the Light Gradient Boosting model exhibited the highest accuracy (0.9189), kappa (0.7204), and F1-score (0.9508) values. Based on these models, MRAS, RAB7B, and RETREG1 were selected for further analysis. The logistic regression model based on these genes could accurately predict MASH diagnosis. The nomogram model based on these DEGs exhibited excellent prediction performance. The expression levels of the three mito-DEGs were validated in the independent datasets and cell models, and the results were found to be consistent with the findings obtained through bioinformatics analysis. Furthermore, our findings revealed significant differences in gene expression patterns, immune characteristics, biological functions, and enrichment pathways between the mitophagy-related molecular subtypes of MASH. Subtype-specific small-molecule drugs were identified using the CMap database. Conclusion: Our research provides novel insights into the role of mitophagy in MASH and uncovers novel targets for predictive and personalized MASH treatments. [ABSTRACT FROM AUTHOR]

Characterized by light weight and high strength, composites are widely used as protective materials in dynamic impact loading under extreme conditions, such as high strain rates. Therefore, based on the excellent tensile properties of continuous fiber and the good flexibility and toughness of the bionic spiral structure, this study uses a multi-material 3D printer to incorporate continuous fiber, and then modifies the G-CODE file to control the printing path to achieve the production of a continuous fiber-reinforced Polylactic Acid composite helicoidal (spiral angle 60°) structure (COF-HP). Dynamic behavior under high-strain-rate impact experiments have been conducted using the Split Hopkinson Pressure Bar (SHPB). Stress–strain curves, impact energy curves and high-speed camera photographs with different strain rates at 680 s − 1 and 890 s − 1 have been analyzed to explore the dynamic process and illustrate the damage evolution. In addition, some detailed simulation models considering the incorporation of continuous optical fiber (COF) and different strain rates have been established and verified for deeper investigations. The results show that the COF does enhance the impact resistance of the laminates. When the porosity is reduced, the maximum stress of the continuous fiber-reinforced composite material is 4~7% higher than that of the pure PLA material. Our findings here expand the application of COF and provide a new method for designing protective materials, which have broad application prospects in the aerospace and automotive industries. [ABSTRACT FROM AUTHOR]

Background: While RACGAP1 is identified as a potential oncogene, its specific role in lung adenocarcinoma (LUAD) remains unclear. Methods: First, we conducted a comprehensive analysis of the role of RACGAP1 across 33 types of cancer. Subsequently, we investigated the expression levels of RACGAP1 and its impact on prognosis using data from The Cancer Genome Atlas (TCGA) database. We utilized single-cell sequencing data to explore the tumor-related processes of RACGAP1 in LUAD and validated our findings through experimental verification. Employing a consensus clustering (CC) approach, we subdivided LUAD patients into two subtypes based on RACGAP1 cell cycle-related genes (RrCCGs). These subtypes exhibited significant differences in tumor characteristics, lymph node metastasis, and recurrence. Furthermore, we evaluated the prognostic influence of RrCCGs using univariate Cox regression and least absolute shrinkage and selection operator regression models (LASSO), successfully establishing a prognostic model. Results: RACGAP1 is frequently overexpressed in various tumors and can impact the prognosis of patients with LUAD. Additionally, experimental evidence has demonstrated that low expression of RACGAP1 favors tumor cell apoptosis and restoration of the cell cycle, while high expression promotes invasion and metastasis. Through CC analysis of RrCCGs, patients were classified into two groups, with survival analysis revealing distinct prognoses and stages between the two groups. Furthermore, Cox and LASSO regression successfully constructed a prognostic model with robust predictive capability., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)