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Pentamode metamaterial (PM) has enormous application potential in the design of lightweight bodies with superior vibration and noise-reduction performance. To offer systematic insights into the investigation of PMs, this paper studies the various effects (i.e., unit cell arrangement, material, and geometry) on bandgap properties through the finite element method (FEM). With regards to the influences of unit cell arrangements on bandgap properties, the results show that the PM with triangular cell arrangement (PMT) possesses better bandgap properties than the others. The effects of material and geometry on bandgap properties are then explored thoroughly. In light of the spring-mass system theory, the regulation mechanism of bandgap properties is discussed. Multi-objective optimization is conducted to further enhance the bandgap properties of PMT. Based on the Latin hypercube design and double-points infilling, a high-accuracy Kriging model, which represents the relationship between the phononic bandgap (PBG), single mode phononic bandgap (SPBG), double-cone width, and node radius, is established to seek the Pareto optimal solution sets, using the non-dominated sorting genetic algorithm (NSGA-II). A fitness function is then employed to obtain the final compromise solution. The PBG and total bandgap of PMT are widened approximately 2.2 and 0.27 times, respectively, while the SPBG is narrowed by about 0.51 times. The research offers important understanding for the investigation of PM with superior acoustic regulation capacity. [ABSTRACT FROM AUTHOR]

Bionic and gradient designs offer promising applications in honeycomb structures. The intersection unit of the beetle elytra is extracted as to enhance regular hexagonal honeycomb (RHH), and several bionic honeycombs are proposed. Finite element (FE) modeling approach is verified through formulae and experiments. Curves of force and displacement of bionic honeycombs present two prominent stages under medium- and low-speed impacts in plateau stage, and several bionic honeycombs exhibit a zero or negative Poisson's ratio. The specific energy absorption (SEA) of INT_6, whose crashworthiness is best in bionic honeycombs. A gradient design of INT_6 is implemented to further increase its crashworthiness. Multi-objective optimization design (MOD), which aims to simultaneously increase the SEA and reduce the peak crushing force, is adopted to determine the optimal parameters of each layer of graded INT_6. The SEA of the optimized graded INT_6 increase 142%, and its peak crushing force decrease by 25.4% compared with those of the INT_6. [ABSTRACT FROM AUTHOR]

In order to improve the crashworthiness of the crash box, the cattle horn is selected as a bionic object. A crash box filled with negative Poisson's ratio honeycomb based on horn structure was designed by extracting its excellent structural characteristics of impact resistance. The axial deformation modes and energy absorption characteristics of bionic crash box are investigated by means of finite element method, and compared with square crash box, diagonal crash box and side-to-side crash box. Under axial impact, the horn-bionic crash box shows significantly better load-carrying and energy-absorbing capacity than the square crash box and the diagonal crash box. On this basis, the thickness parameters, multi-objective optimization design and structure improvement design of horn-bionic crash box are studied successively in this work. The results show that the improved bionic crash box based on horn structure has a typical progressive shrinkage deformation mode. Its SEA reaches 29.9 kJ/kg, which is 2.5 times that of the square crash box, and its PCF is also greatly reduced from 542.4 kN to 391.1 kN. Therefore, the methods of structural improvement such as pre-deformed treatment, constraint beam adjustment and shortening the NPR core can effectively reduce the PCF of the crash box, and improve its energy absorption capacity, so as to obtain better comprehensive crashworthiness. Introducing the key characteristics of the horn structure into the design of the car crash box can effectively improve structural crashworthiness and provide new design guidance for the other energy-absorption components of vehicle. [ABSTRACT FROM AUTHOR]

In order to improve the mapping efficiency of network intelligent mapping algorithm, this paper proposes a secure virtual network intelligent mapping algorithm under cloud computing. Firstly, the network virtualization technology is analyzed, and a network virtualization example diagram is proposed. Then the energy consumption model and network load model of virtual network mapping problem are constructed to analyze the mapping reliability. Finally, the virtual network mapping strategy is optimized by cloud computing technology to realize the research on intelligent mapping algorithm of secure virtual network under cloud computing. Experimental results show that the percentage of nodes used by the proposed algorithm is much lower than that of other mapping algorithms compared, and the energy consumption is about 8100RMB/h at 60,000 unit time point, which is much lower than that of other methods, indicating that the proposed algorithm has high mapping efficiency. [ABSTRACT FROM AUTHOR]

Association of lifestyle behaviors with non-alcoholic fatty liver disease and advanced fibrosis detected by transient elastography among Hispanic/Latinos adults in the U.S. Ethn Health. With great interest, we read the recent study by Kim and coworkers showing that non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of dementia in a nationwide cohort study.1 We thank them for their significant work for clinical practice, but there exist some potential pitfalls which may affect the credibility of the results. Non-alcoholic fatty liver disease does not increase dementia risk although histology data might improve risk prediction. [Extracted from the article]

AbstractUnder compressive loads, shear band formation in lattice structures can lead to stress fluctuations, resulting in a decrease in energy absorption capacity. To specifically suppress shear bands, it is necessary to expound the formation mechanisms. This study used theoretical analysis, experiments, and finite element (FE) simulations to elucidate the mechanism underlying shear band formation in strut-based lattice structures. It was determined that stress concentration at strut joints along the 45° diagonal plane induced shear deformation. Shear bands were most pronounced along the four body diagonals, and their existence diminished as the distance from the diagonal increased. Therefore, a design of oblique graded lattice structure (OGLS) was proposed, and quasi-static compression experiments were performed using FE method. The results showed that the main internal stress of OGLS is combined with the original 45° shear stress and the annular staggered stress produced by the oblique graded design, which constrains each other and avoids mutual dislocation deformation, thus realizing shear band suppression. However, an excessively large graded coefficient excessively weakens the 45° shear stress and results in the appearance of an annular compact band. By optimizing the graded coefficient based on the deformation consistency of the outer contour, the optimized OGLS exhibited significant improvements in yield strength, plateau stress, and energy absorption, which are increased by 36.06%, 39.29%, and 34.41%, respectively. This research offers novel perspectives on how lattice structures can attain stable compression deformation and a high energy absorption capacity. [ABSTRACT FROM AUTHOR]

Abstract In this article, a non-uniform design method mapped by density-based topology optimization is proposed and applied to the classic hexagonal honeycombs. A parametric investigation is conducted to explore the effect of crucial factors on the in-plane and out-of-plane crashing behaviors and energy absorption of the non-uniform honeycomb mapped by topology optimization. Compared to classic hexagonal honeycombs, the in-plane specific energy absorption of the non-uniform honeycomb mapped by topology optimization is improved by 29.1%, and its peak stress is decreased by 16.9%. Meanwhile, the out-of-plane specific energy absorption is increased by 19.8% without a significant rise in peak stress. [ABSTRACT FROM AUTHOR]

Abstract: In order to utilize renewable energy to meet diverse energy requirements, a new combined cooling, heating and power (CCHP) system is proposed to produce cooling output, heating output and power output simultaneously. This proposed system combines a Brayton cycle and a transcritical CO2 refrigeration cycle with ejector-expansion device, which uses solar energy as the heat source to reduce fossil fuel consumption and alleviate environmental problems. A mathematical model is developed to simulate the new CCHP system with transcritical CO2 driven by solar energy under steady-state conditions, and the thermal efficiency and exergy efficiency are used to evaluate the system performance. The effects of several key thermodynamic parameters on the system performance are examined. The results indicate that increasing turbine inlet pressure and ejector inlet temperature could lower the efficiency of the system, and increasing turbine back pressure and turbine inlet temperature could elevate the efficiency of system. In addition, as ejector back pressure increases, the thermal efficiency of system decreases, but the exergy efficiency increases. [Copyright &y& Elsevier]

Ring finger protein 2 (RNF2), as a well-known E3 ligase, has an oncogenic role in various cancers. The role of RNF2 in colon cancer is still unknown. The aim of this work is to determine the biological role of RNF2 in colon cancer. We first examined the expression of RNF2 and interferon regulatory factor 4 (IRF4) in colon cancer patients and colon cancer cell lines (SW480 and HCT116). Compared with normal tumor-adjacent tissues, RNF2 was up-regulated whereas IRF4 was down-regulated in the colon cancer tissues. RNF2 was also up-regulated in colon cancer cells with respect to human fetal colon epithelial cells. RNF2 overexpression enhanced the ability of proliferation, migration and invasion of SW480 cells, whereas RNF2 knockdown caused an opposite result in HCT116 cells. Furthermore, a tumor xenograft model was constructed to verify the impact of RNF2 overexpressed-SW480 cells on tumor growth. RNF2 up-regulation elevated Ki-67 proliferation index, accelerated the growth of tumor tissues, and led to severe colon tissue damage in the tumor xenograft mice. In addition, RNF2 interacted with IRF4, and repressed IRF4 protein expression. IRF4 was a substrate of RNF2, and RNF2 promoted the ubiquitination and degradation of IRF4. RNF2 overexpression increased the ability of proliferation, migration and invasion in SW480 cells by promoting the ubiquitination and degradation of IRF4. In conclusion, this work demonstrated that RNF2 promoted tumor growth in colon cancer by regulating ubiquitination and degradation of IRF4. Thus, RNF2 may be served as a potential therapeutic target for colon cancer. • RNF2 was highly expressed in colon cancer tissues and cells. • RNF2 promoted cell proliferation, migration and invasion of colon cancer cells. • RNF2 accelerated tumor growth of colon cancer in mice. • IRF4 was a substrate of RNF2, and could be ubiquitinated and degraded by RNF2. • RNF2 promoted colon cancer progression by regulating ubiquitination of IRF4. [ABSTRACT FROM AUTHOR]

N6 methyladenosine (m6A), methylation at the sixth N atom of adenosine, is the most common and abundant modification in mammalian mRNAs and non-coding RNAs. Increasing evidence shows that the alteration of m6A modification level could regulate tumour proliferation, metastasis, self-renewal, and immune infiltration by regulating the related expression of tumour genes. However, the role of m6A modification in colorectal cancer (CRC) drug resistance is unclear. Here, MeRIP-seq and RNA-seq techniques were utilized to obtain mRNA, lncRNA expression, and their methylation profiles in 5-Fluorouracil (5-FU)-resistant colon cancer HCT-15 cells and control cells. In addition, we performed detailed bioinformatics analysis as well as in vitro experiments of lncRNA to explore the function of lncRNA with differential m6A in CRC progression and drug resistance. In this study, we obtained the m6A methylomic landscape of CRC cells and resistance group cells by MeRIP-seq and RNA-seq. We identified 3698 differential m6A peaks, of which 2224 were hypermethylated, and 1474 were hypomethylated. Among the lncRNAs, 60 were hypermethylated, and 38 were hypomethylated. GO and KEGG analysis annotations showed significant enrichment of endocytosis and MAPK signalling pathways. Moreover, knockdown of lncRNA ADIRF-AS1 and AL139035.1 promoted CRC proliferation and invasive metastasis in vitro. lncRNA- mRNA network showed that ADIRF-AS1 and AL139035.1 May play a key role in regulating drug resistance formation. We provide the first m6A methylation profile in 5-FU resistance CRC cells and analyse the functions of differential m6A-modified mRNAs and lncRNAs. Our results indicated that differential m6A RNAs were significantly associated with MAPK signalling and endocytosis after induction of 5-FU resistance. Knockdown of LncRNA ADIRF-AS1 and AL139035.1 promotes CRC progression and might be critical in regulating drug resistance formation.

Background: Currently, for patients with colon adenocarcinoma who are diagnosed with local lymph node metastasis, it is typically recommended to undergo neoadjuvant treatment before undergoing curative surgical intervention. Nowadays, the focus of preoperative adjuvant therapy for colon adenocarcinoma patients mainly revolves around chemotherapy, and the impact of preoperative radiotherapy on long-term prognosis remains uncertain., Methods: We extracted data from the Surveillance, Epidemiology, and End Results database for patients with stage III colon adenocarcinoma between 2004 and 2019. Using propensity score matching (PSM), the patients were divided into a preoperative radiotherapy group and a non-preoperative radiotherapy group, and the differences in Kaplan-Meier (KM) survival curves between the two groups were compared. Cox regression analysis was employed to identify clinical factors that influence survival in stage III colon adenocarcinoma, and the prognostic differences between the two groups were compared within specific subgroups of these clinical factors., Results: After PSM, a total of 242 patients were included in the study, divided into the preoperative radiotherapy group and the non-preoperative radiotherapy group. There were no statistically significant differences in important clinical characteristics between the two groups. KM analysis revealed no statistically significant difference in overall survival (OS) between the two groups. Furthermore, age, chemotherapy, T staging, N staging, race, tumor grade, gender, tumor location, and tumor diameter were identified as important factors influencing the prognosis of patients. Within each level of the aforementioned subgroups, there were no differences in OS between the two groups. In fact, in specific subgroups, the non-preoperative radiotherapy group exhibited better OS than the preoperative radiotherapy group., Conclusion: Preoperative radiotherapy does not improve the long-term prognosis of patients with stage III colon adenocarcinoma. In certain patient populations with specific clinical characteristics, preoperative radiotherapy may even lead to a decrease in OS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Xu and Niu.)

Introduction: In this study, we explore the potential benefits of integrating natural cognitive systems (medical professionals' expertise) and artificial cognitive systems (deep learning models) in the realms of medical image analysis and sports injury prediction. We focus on analyzing medical images of athletes to gain valuable insights into their health status., Methods: To synergize the strengths of both natural and artificial cognitive systems, we employ the ResNet50-BiGRU model and introduce an attention mechanism. Our goal is to enhance the performance of medical image feature extraction and motion injury prediction. This integrated approach aims to achieve precise identification of anomalies in medical images, particularly related to muscle or bone damage., Results: We evaluate the effectiveness of our method on four medical image datasets, specifically pertaining to skeletal and muscle injuries. We use performance indicators such as Peak Signal-to-Noise Ratio and Structural Similarity Index, confirming the robustness of our approach in sports injury analysis., Discussion: Our research contributes significantly by providing an effective deep learning-driven method that harnesses both natural and artificial cognitive systems. By combining human expertise with advanced machine learning techniques, we offer a comprehensive understanding of athletes' health status. This approach holds potential implications for enhancing sports injury prevention, improving diagnostic accuracy, and tailoring personalized treatment plans for athletes, ultimately promoting better overall health and performance outcomes. Despite advancements in medical image analysis and sports injury prediction, existing systems often struggle to identify subtle anomalies and provide precise injury risk assessments, underscoring the necessity of a more integrated and comprehensive approach., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Xiao, Zhu, Jiang and Niu.)