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Dysregulation of circadian rhythm genes is related to the increased risk of development of various human cancers. This study investigated the biological roles of Period circadian regulator 3 (PER3) in the development and progression of lung adenocarcinoma and related underlying mechanisms. The expression of PER3 was decreased in lung adenocarcinoma and its low expression was correlated with advanced disease stages. Lentiviral-transduced overexpression of PER3 inhibited but PER3 silencing promoted proliferation, migration and invasion of lung adenocarcinomatous cells, suggesting that it played an anti-carcinogenic role in the development and progression of lung adenocarcinoma. Mechanistically, PER3 overexpression elevated the phosphorylation level of AMPK and reduced the phosphorylation level of mTOR, but PER3 silencing produced the opposite effects. More importantly, the inhibitory effects of PER3 overexpression on cellular proliferation, migration and invasion were partially reversed by the AMPK/mTOR pathway inhibitor. Correspondingly, the promoting effects of PER3 silencing on proliferation, migration and invasion was partially reversed by the AMPK/mTOR pathway activator. These findings collectively suggest that PER3 regulated biological behaviors of lung adenocarcinomatous cells through activating the AMPK/mTOR pathway. PER3 may be a promising biomarker and therapeutic target for lung adenocarcinoma.

In recent years, the simplified computation of position and velocity changes in nonlinear systems using Lie groups and Lie algebra has been widely used in the study of robot localization systems. The unscented Kalman filter (UKF) can effectively deal with nonlinear systems through the unscented transformation, and in order to more accurately describe the robot localization system, the UKF method based on Lie groups has been studied successively. The computational complexity of the UKF on Lie groups is high, and in order to simplify its computation, the Lie groups are applied to the manifold, which efficiently handles the state and uncertainty and ensures that the system maintains the geometric constraints and computational simplicity during the updating process. In this paper, a multi-sensor fusion localization method based on an unscented Kalman filter on manifolds (UKF-M) is investigated. Firstly, a system model and a multi-sensor model are established based on an Autonomous Underwater Vehicle (AUV), and a corresponding UKF-M is designed for the system. Secondly, the multi-sensor fusion method is designed, and the fusion method is applied to the UKF-M. Finally, the proposed method is validated using an underwater cave dataset. The experiments demonstrate that the proposed method is suitable for underwater environments and can significantly correct the cumulative error in the trajectory estimation to achieve accurate underwater localization.

Starch is a natural polymer. It is also an important food nutrient. Studies related to starch content testing can provide basic data for starch intake assessments and correlation studies. Meanwhile, data on the starch content in food are important for guiding the population to have a reasonable diet. Starch content directly affects the nutritional value, consumption quality, and processing quality of food. This paper summarized the common starch content detection techniques in food in the past five years, such as titration, spectrophotometry, near-infrared spectroscopy, and other methods. The principles, advantages, and disadvantages of these starch content detection techniques were described and discussed. Their problems in real sample detection (e.g., time-consuming, cumbersome operation, over-reliance on modeling algorithms, etc.) were analyzed. Challenges and future trends are also presented with the expectation of providing useful references for future research and practical applications. This paper provides a direction and research basis for the development of starch content detection techniques for food. It also provides value to related work in starch research.

Breast cancer is the most common female malignancy worldwide. Ubiquitin-specific peptidase 53 (USP53) has been shown to exert cancer-suppressing functions in several solid tumors, but its role and the underlying mechanism in breast cancer has not been clearly elucidated. Therefore, we have carried out a series of detailed studies on this matter at the levels of bioinformatics, clinical tissue, cell function and animal model. We found that USP53 expression was downregulated in breast cancer specimens and was negatively correlated with the clinical stages. Gain- and loss-of-function experiments demonstrated USP53 inhibited proliferation, clonogenesis, cell cycle and xenograft growth, as well as induced apoptosis and mitochondrial damage of breast cancer cells. Co-immunoprecipitation data suggested that USP53 interacted with zinc finger MYND-type containing 11 (ZMYND11), and catalyzed its deubiquitination and stabilization. The 33–50 amino acid Cys-box domain was key for USP53 enzyme activity, but not essential for its binding with ZMYND11. The rescue experiments revealed that the anti-tumor role of USP53 in breast cancer cells was at least partially mediated by ZMYND11. Both USP53 and ZMYND11 were prognostic protective factors for breast cancer. USP53-ZMYND11 axis may be a good potential biomarker or therapeutic target for breast cancer, which can provide novel insights into the diagnosis, treatment and prognosis. Keypoints 1. USP53 has been shown to play an anticancer role in a variety of solid malignancies, but its role in breast cancer and its mechanism remain unclear. 2. Our results suggested that USP53 was low expressed in breast cancer and negatively correlated with TNM stage; USP53 suppressed proliferation and triggered apoptosis of breast cancer cells; USP53 inhibited breast cancer in vitro and in vivo by deubiquitinating ZMYND11. 3. USP53-ZMYND11 axis may be a potential breast cancer marker and therapeutic target.

This paper selects three indicators of urbanization, industrial structure and urban-rural income gap to construct a three-dimensional VAR model. Through Granger causality test, impulse response function and variance decomposition methods, a dynamic analysis of urbanization and industrial structure on urban-rural income gap in Sichuan Province has been carried out. The research shows that: urbanization and industrial structure have an important impact on the urban-rural income gap in Sichuan Province. Urbanization and the urban-rural income gap present a “U-shaped” relationship, that is, in the initial stage when the level of urbanization increases, the urban-rural income gap will be narrowed, and when urbanization develops to a certain degree, the gap will gradually be widened. The relationship between the industrial structure and the urban-rural income gap is an “inverted U-shaped” relationship, that is, the urban-rural income gap will be widened when the industrial structure is at a lower level. As the industrial structure is optimized and upgraded, the gap will gradually be narrowed.

To address the issue of machining errors in large rotary workpieces caused by geometric errors of heavy vertical lathes, this study focuses on measuring and modeling geometric errors of such lathes. By identifying the specific geometric errors that impact the machining accuracy of heavy vertical lathes and extracting the crucial ones, the study investigates the contribution degree of the error of geometric errors during the machining process of the wind turbine bearing raceways. The study combines the geometric error fitting function to predict the position error and profile error of feature points on the bearing raceway cross-sectional curve. It also performs an inverse evaluation of the contact angle of the wind turbine bearing raceways. The study aims to clarify the influence of crucial geometric errors in heavy vertical lathes on machining errors during the machining process of wind turbine bearings. The findings provide theoretical and practical guidance for the subsequent design and manufacture of heavy machine tools and the vertical turning process of large rotary workpieces.

Corn is one of the global staple grains and the largest grain crop in China. During harvesting, grain separation, and corn production, corn is susceptible to mechanical damage including surface cracks, internal cracks, and breakage. However, the internal cracks are difficult to observe. In this study, hyperspectral imaging was used to detect mechanical damage in corn seeds. The corn seeds were divided into four categories that included intact, broken, internally cracked, and surface-crackedtv. This study compared three feature extraction methods, including principal component analysis (PCA), kernel PCA (KPCA), and factor analysis (FA), as well as a joint feature extraction method consisting of a combination of these methods. The dimensionality reduction results of the three methods (FA + KPCA, KPCA + FA, and PCA + FA) were combined to form a new combined dataset and improve the classification. We then compared the effects of six classification models (ResNet, ShuffleNet-V2, MobileNet-V3, ResNeSt, EfficientNet-V2, and MobileNet-V4) and proposed a ResNeSt_E network based on the ResNeSt and efficient multi-scale attention modules. The accuracy of ResNeSt_E reached 99.0%, and this was 0.4% higher than that of EfficientNet-V2 and 0.7% higher than that of ResNeSt. Additionally, the number of parameters and memory requirements were reduced and the frames per second were improved. We compared two dimensionality reduction methods: KPCA + FA and PCA + FA. The classification accuracies of the two methods were the same; however, PCA + FA was much more efficient than KPCA + FA and was more suitable for practical detection. The ResNeSt_E network could detect both internal and surface cracks in corn seeds, making it suitable for mobile terminal applications. The results demonstrated that detecting mechanical damage in corn seeds using hyperspectral images was possible. This study provides a reference for mechanical damage detection methods for corn.

As the key component of a five-axis CNC planer-type milling machine, the integral mechanical property of the A/C swing angle milling head directly affects the machining accuracy and stability of the milling machine. Taking the mechanical A/C swing-angle milling head of a five-axis numerical-control gantry milling machine as the research object, the stress deformation characteristics and natural frequency of the swing-angle milling head under actual working conditions were studied using finite-element analysis. Based on the analytical results, it was determined that the cardan frame, with its large mass proportion and strong rigidity of the whole milling head, is the object to be optimized. The topological optimization of the cardan frame, in which achieving the minimum flexibility was the optimization objective, was carried out to determine the quality reduction area. By comparing the simulation results of the cardan frames of three different rib plate structures, it was shown that the cardan frame performance of the ten-type rib plate structure was optimal. The analytical results showed that, when the cardan frame met the design requirements for stiffness and strength, the mass after optimization was reduced by 13.67% compared with the mass before optimization, the first-order natural frequency was increased by 7.9%, and the maximum response amplitude was reduced in all directions to avoid resonance, which was beneficial to the improvement of the dynamic characteristics of the whole machine. At the same time, the rationality and effectiveness of the lightweight design method of the cardan frame were verified, which has strong engineering practicality. The research results provide an important theoretical basis for the optimization of other machine tool gimbals and have important practical significance and application value.

Particulate matter 2.5 (PM2.5)-induced pulmonary inflammation is an important issue worldwide. NLRP3 inflammasome activation has been found to be involved in pulmonary inflammation development. However, whether PM2.5 induces pulmonary inflammation by activating the NLRP3 inflammasome has not yet been fully elucidated. This study researched whether PM2.5 induces the NLRP3 inflammasomes activation to trigger pulmonary inflammation. Mice and MH-S cells were exposed to PM2.5, BOX5, and Rapamycin. Hematoxylin and eosin staining was performed on the lung tissues of mice. M1 macrophage marker CD80 expression in the lung tissues of mice and LC3B expression in MH-S cells was detected by immunofluorescence. IL-1β level in the lavage fluid and MH-S cells were detected by enzyme-linked immunosorbent assay. Protein expression was detected by Western blot. Autophagy assay in MH-S cells was performed by LC3B-GFP punctae experiment.PM2.5 exposure induced the lung injury of mice and increased NLRP3, P62, Wnt5a, LC3BII/I, and CD80 expression and IL-1β release in the lung tissues. PM2.5 treatment increased NLRP3, pro-caspase-1, cleaved caspase-1, Pro-IL-1β, Pro-IL-18, P62, LC3BII/I, and Wnt5a expression, IL-1β release, and LC3B-GFP punctae in MH-S cells. However, BOX5 treatment counteracted this effect of PM2.5 on lung tissues of mice and MH-S cells. Rapamycin reversed the effect of BOX5 on PM2.5-induced lung tissues of mice and MH-S cells.PM2.5 activated the NLRP3 inflammasome and IL-1β release in MH-S cells by facilitating the autophagy via activating Wnt5a. The findings of this study provided a new clue for the treatment of pulmonary inflammation caused by PM2.5.

Background Evidence suggests that enolase-phosphatase 1 (ENOPH1) is involved in the progression of some certain types of cancers and acts as an oncogenic factor in tumor progression. The present study aimed to identify the central role of ENOPH1 in the progression of breast cancer (BC), a highly proliferative and aggressive disease. Methods and results ENOPH1 expression in BC tissues was explored based on the online resource and 40 paired fresh BC and para-carcinoma samples. Functional assays were performed to evaluate the biological effect of ENOPH1 on cell proliferation and migration in ENOPH1-silenced or overexpressing BC cell lines. Blockade of NF-κB by BAY11-7082 was performed to evaluate whether ENOPH1 exerted tumor-promoting properties via regulating the NF-κB signaling pathway. Results of the present study demonstrated that ENOPH1 expression was profoundly upregulated in BC tissues compared with adjacent breast tissues, and ENOPH1 expression was associated with cancer stage, node metastasis status, and overall survival. Functional assays demonstrated that ENOPH1 overexpression significantly accelerated BC cell proliferation, migration, and invasion, while genetic knockdown of ENOPH1 yielded the opposite effects. Mechanistically, ENOPH1 activated the NF-κB pathway, as evidenced by increased expression of NF-κB downstream genes and enhanced NF-κB p65 nuclear translocation. Furthermore, the oncogenic properties of ENOPH1 in proliferation, migration, and invasion were restrained following inhibition of the NF-κB signaling pathway. Conclusions These findings indicated the significance of ENOPH1 in promoting cell proliferation and invasion, mainly through activating the NF-κB pathway, suggesting that ENOPH1 might be an attractive prognostic factor and a potential target for BC therapy.