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To investigate the seismic performance of a wind turbine that is influenced by both the ice load and the seismic load, the research proposes a numerical approach for simulating the seismic behavior of a wind turbine on a monopile foundation. First, the fluid-solid coupled equation for the water-ice-wind turbine is simplified by assigning reasonable boundary conditions and solving the motion equation, and the seismic motion equation of the wind turbine is developed. Then, on this basis, we propose a simplified 3D numerical model that can simulate the interactions among the wind turbine, water and sea ice. By conducting shaking table tests, the results demonstrate that the established numerical model is effective. Finally, we investigate the effect of the boundary range and ice thickness on the seismic performance of a turbine under near-field and far-field seismic actions. Research results illustrate that ice changes the distribution form of the hydrodynamic pressure. Moreover, the thickness of the ice greatly influences the seismic behavior, while the influence of the ice boundary range is only within a certain range. Additionally, the ice load decreases the energy-dissipating capacity of the wind turbine, so the earthquake resilience of the wind turbine is significantly decreased.

Few comparative studies have assessed metabolic brain changes in cognitive impairment among neurodegenerative disorders, and the posterior cingulate cortex (PCC) is a metabolically active brain region with high involvement in multiple cognitive processes. Therefore, in this study, metabolic abnormalities of the PCC were compared in patients with mild cognitive impairment (MCI) due to Parkinson’s disease (PD) or Alzheimer’s disease (AD), as examined by proton magnetic resonance spectroscopy ( 1 H-MRS). Thirty-eight patients with idiopathic PD, including 20 with mild cognitive impairment (PDMCI) and 18 with normal cognitive function (PDN), 18 patients with probable mild cognitive impairment (ADMCI), and 25 healthy elderly controls (HCs) were recruited and underwent PCC 1 H-MRS scans. Compared with HCs, patients with PDMCI exhibited significantly reduced concentrations of N -acetyl aspartate (NAA), total NAA (tNAA), choline (Cho), glutathione (GSH), glutamate + glutamine (Glx) and total creatine (tCr), while ADMCI cases exhibited significantly elevated levels of myo-inositol (Ins) and Ins/tCr ratio, as well as reduced NAA/Ins ratio. No significant metabolic changes were detected in PDN subjects. Compared with ADMCI, reduced NAA, Ins and tCr concentrations were detected in PDMCI. Besides, ROC curve analysis revealed that tCr concentration could differentiate PDMCI from PDN with an AUC of 0.71, and NAA/Ins ratio could differentiate patients with MCI from controls with normal cognitive function with an AUC of 0.74. Patients with PDMCI and ADMCI exhibited distinct PCC metabolic 1 H-MRS profiles. The findings suggested cognitively normal PD patients with low NAA and tCr in the PCC might be at risk of preclinical PDMCI, and Ins and/or NAA/MI ratio in the PCC should be reconsidered a possible biomarker of preclinical MCI in clinical practice. So, comparing PCC’s 1 H-MRS profiles of cognitive impairment among neurodegenerative illnesses may provide useful information for better defining the disease process and elucidate possible treatment mechanisms.

This systematic review aimed to examine the relationship between the oral microbiota and the onset and progression of type 2 diabetes mellitus (T2DM). A systematic review was conducted in accordance with PRISMA guidelines. Three independent reviewers searched relevant literature across multiple databases, including PubMed/Medline, Web of Science, and Scopus, covering publications from April 2000 to April 2025. A total of 1,438 publications were initially identified, of which 34 studies met the inclusion criteria after screening, namely 23 cross-sectional studies and 11 case-control studies. These studies involved 2,062 patients with T2DM and 1,445 non-diabetic controls. All included studies reported a correlation or potential association between the oral microbiota and T2DM. Fifteen studies analyzed alpha diversity, revealing heterogeneous findings: three reported increased diversity in T2DM patients, two reported decreased diversity, and the remainder showed either no significant differences or inconsistent trends. At the phylum level, Firmicutes was consistently elevated in T2DM patients (14 studies), whereas Proteobacteria was often reduced, and findings on Bacteroidetes varied. At the genus level, Streptococcus, Porphyromonas, and Treponema were most frequently enriched in T2DM populations, with Streptococcus significantly elevated in 22 studies. Notably, Porphyromonas gingivalis was repeatedly identified as a potential contributor to systemic inflammation and insulin resistance, indicating a potential pathogenic role in the metabolic dysregulation of T2DM. Species-level analyses further revealed increased abundance of Streptococcus mutans, P. gingivalis, and T. denticola, supporting the hypothesis that oral dysbiosis is linked to T2DM pathogenesis. There is a significant association between oral microbiota composition and T2DM. These findings highlight the potential importance of oral health monitoring as part of preventive and therapeutic strategies in the management of T2DM.

Cholesterol metabolism plays a critical role in the progression of hepatocellular carcinoma (HCC), but it is not clear how cholesterol metabolism is regulated. The tubulin beta class I genes (TUBBs) are associated with the prognosis of many different cancers. To confirm the function of TUBBs in HCC, the Kaplan–Meier method and Cox analyses were performed using TCGA and GSE14520 datasets. A higher expression of TUBB2B is an independent prognostic factor for shorter over survival in HCC patients. Deletion of TUBB2B in hepatocytes inhibits proliferation and promotes tumor cell apoptosis, while over-expression of TUBB2B has the opposite function. This result was confirmed in a mouse xenograft tumor model. Mechanistically, TUBB2B induces the expression of CYP27A1, an enzyme responsible for the conversion of cholesterol to 27-hydroxycholesterol, which leads to the up-regulation of cholesterol and the progression of HCC. In addition, TUBB2B regulates CYP27A1 via human hepatocyte nuclear factor 4alpha (HNF4A). These findings indicated that TUBB2B functions as an oncogene in HCC, and plays a role in promoting cell proliferation and anti-apoptosis through targeting HNF4A/CYP27A1/cholesterol.

An accurate slope prediction model is important for slope reinforcement before the disaster. The k-nearest neighbor (KNN) algorithm, as a simple and effective nonparametric machine learning method, is widely applied in classification recognition. In our study, the k-nearest neighbor (KNN) algorithm is improved to reduce its sample dependence and improve the robustness of the algorithm, and then the prediction model of the slope stability is proposed based on the improved k-nearest neighbor (KNN) algorithm. Extensive experimental results show that our proposed prediction model achieves high prediction performance in this regard. Moreover, a comparison between our proposed prediction model and the finite element method, which is the classical theoretical method of slope stability, was made, which will provide an important approach to predicting the slope stability for slope engineering. Finally, shaking table test of a slope model is conducted to evaluate whether the slope is stable or not, and the experimental results are in good agreement with the prediction results of our proposed prediction model, which further demonstrates its effectiveness.

The reconfigurable equilibrium circuit can take account of the number of components and the conversion efficiency and can easily balance every single cell in the battery pack, but the voltage of the battery pack will fluctuate when the battery pack is balanced. To solve this problem, a reconfigurable equalization circuit with an additional power supply is proposed. By replacing the cell with the additional power supply, the purpose of stabilizing the voltage of the battery pack is achieved. Aiming at the additional power supply, this paper puts forward a method that the additional power supply participates in the charging (discharging) process when the SOC (state of charge) of the battery pack is not lower (higher) than the additional power supply while the battery pack is charging (discharging), to make the charge and discharge capacity of the additional power supply always better than the battery pack. The experimental results show that the proposed equalization circuit can not only retain the advantages of the traditional reconfigurable equilibrium circuit but also maintain the voltage of the battery pack in the equalization process.

The oral microbiota is the second largest microbiota in the human body and has a significant impact on human health. Recent evidence suggests that dysbiosis of the oral microbiota may be associated with the development of metabolism-associated fatty liver disease (MAFLD). This review aimed to validate the relationship between oral microbial diversity and the development of MAFLD. A systematic evaluation was performed based on PRISMA guidelines. Three independent reviewers searched for relevant literature in several databases, including PubMed/Medline, Web of Science, and Scopus, with a search date ranging from the establishment of the databases to June 2024. A total of 1278 publications were initially screened, including five cross-sectional studies, seven case-control studies, one cohort study, and one retrospective study. These studies included a total of 3335 patients with MAFLD, 254 patients with MASH, and 105 patients with liver cirrhosis. All 14 included studies concluded that there was a correlation or potential correlation between oral microbiota and MAFLD. Seven studies found that the composition of the oral microbiota in MAFLD patients differed from that of healthy controls, and specific oral bacteria may be associated with an increased incidence of MAFLD. At the level, several studies found differences in the abundance of the , , and compared to healthy controls. Additionally, a study on oral fungi found significant differences in the phyla and in the genus between patients with MAFLD and healthy controls. At the genus level, was studied most frequently, with all 8 studies identifying infection with as a significant risk factor for pathological progression in MAFLD. Furthermore, a dysbiosis in the ratio of anomalies may be an important marker of MAFLD progression. There is an important association between the diversity of oral microbiota composition and MAFLD. This finding suggests the importance of oral health assessment and monitoring for the prevention or intervention of MAFLD.

Drawing soy protein (DSP) exhibits a well-defined fibrous structure, conferring significant market potential. This study investigates the interactions between DSP and myofibrillar proteins (MP) and their effects on gel properties. Porcine myofibrillar protein (MP) was used as the raw material, and mixed systems were prepared by incorporating different concentrations of DSP at 0%, 2%, 4%, 6%, and 8% to evaluate their physicochemical properties and gel characteristics. The results demonstrated that the addition of DSP enhanced the gel strength, hardness, and water-holding capacity (WHC) of MP, thereby improving the overall properties and water retention of the gels. Among them, the trend of change was most obvious when the addition amount was 6%. The gel strength increased by 196.5%, the water retention capacity improved by 68.3%, and the hardness rose by 33.3%. Furthermore, as the addition amount of DSP increases, the total thiol content decreases, the hydrogen bond content increases, and the surface hydrophobicity enhances. This leads to a more compact arrangement of protein molecules, which is conducive to a denser and more stable solution and improves the stability of the protein solution. The α-helical structures in the proteins progressively transformed into β-turn structures, exposing more amino acid side chains and inducing conformational changes in MP, resulting in denser and more uniform gel network structures. The most pronounced changes were observed at a 6% addition level. These findings contribute to diversifying meat products and provide a theoretical basis for improving the WHC and yield of emulsified meat products in pork processing.

Foodborne pathogenic bacteria in meat pose a serious threat to human health. Traditional detection methods for these bacteria are often time-consuming and labor-intensive. In this study, we applied surface-enhanced Raman scattering (SERS) combined with portable Raman spectroscopy as a rapid and convenient detection technique. SERS is a sensitive and fast method that enhances light scattering on rough metal surfaces. Silver nanoparticles (AgNPs) were used as SERS substrates to identify and analyze four pathogenic bacteria, including Escherichia coli (E. coli) O157:H7, Salmonella typhimurium (S. typhimurium), Staphylococcus aureus (S. aureus), and Listeria monocytogenes (L. monocytogenes), in beef. We optimized the detection conditions of AgNPs and established the limit of detection (LOD) for these four pathogenic bacteria in both pure culture and beef samples. The LODs were as low as 4–23 CFU/mL in beef samples, indicating high detection sensitivity. Linear discriminant analysis (LDA) was used to analyze the SERS spectra, yielding an accuracy of 91.7–97.3%. This study not only provides a rapid and portable detection method for pathogenic bacteria in beef but also overcomes the limitations of traditional methods that are often time-consuming and not suitable for on-site detection. However, the current study is limited to the detection of the four specific pathogenic bacteria, and further research is needed to expand the range of detectable pathogens and to improve the robustness of the detection models for more complex meat samples. Overall, this research demonstrates the potential of SERS combined with portable Raman spectroscopy as a powerful tool for the rapid detection of pathogenic bacteria in meat products, which could significantly enhance food safety monitoring and control.