Explore the vast range of titles available.

As an important transportation hub connecting the two sides of the Yellow River, the Yellow River Grand Bridge is of great significance for strengthening regional exchanges and promoting the high-quality development of the Yellow River Basin. However, due to the complex terrain, changeable climate, high sediment concentration, long construction duration, complicated process, strong dynamic, and many factors affecting construction. It often brings many problems, including low quality, waste of resources, and environmental pollution, which makes it difficult to achieve the balance of multiple objectives at the same time. Therefore, it is very important to carry out multi-objective optimization research on the construction of the Yellow River Grand Bridge. This paper takes the Yellow River Grand Bridge on a highway as the research object and combines the concept of “green construction” and the national policy of “carbon neutrality and carbon peaking” to construct six major construction projects, including construction time, cost, quality, environment, resources, and carbon emission. Then, according to the multi-attribute utility theory, the objectives of different attributes are normalized, and the multi-objective equilibrium optimization model of construction time-cost-quality-environment-resource-carbon emission of the Yellow River Grand Bridge is obtained; finally, in order to avoid the shortcomings of a single algorithm, the particle swarm optimization algorithm and the simulated annealing algorithm are combined to obtain the simulated annealing particle swarm optimization (SA-PSO) algorithm. The multi-objective equilibrium optimization model of the construction of the Yellow River Grand Bridge is solved. The optimization result is 108 days earlier than the construction period specified in the contract, which is 9.612 million yuan less than the maximum cost, 6.3% higher than the minimum quality level, 11.1% lower than the maximum environmental pollution level, 4.8% higher than the minimum resource-saving level, and 3.36 million tons lower than the maximum carbon emission level. It fully illustrates the effectiveness of the SA-PSO algorithm for solving multi-objective problems.

In the multi-point incremental launching construction process, without setting temporary piers at the mid-span, it is difficult to ensure the synchronization of the launching equipment at the same pier, which can easily cause the beam to deviate from the design axis, leading to changes in the stress of the beam. Calculating the local maximum stress of the beam when lateral deviation occurs is beneficial for establishing a reasonable and reliable threshold for controlling beam deviations. To address this issue, this paper utilizes a finite element model of the bridge under typical adverse conditions, simulating the lateral deviation and asynchronous jacking of the beam to explore stress variation patterns. The results show that the beam stress increases as the lateral deviation and jacking differences increase, severely affecting the structural safety. To overcome the inefficiency of the finite element modeling method when dealing with multiple working conditions and to establish a reasonable deviation control threshold, this study proposes a beam local stress prediction model under the combined influence of lateral deviation and jacking height differences based on the SSA-SVR algorithm. The model calculates the local maximum stress of the beam for 2500 sets of parameters. An engineering case analysis shows that the prediction model has high calculation accuracy, reliable results, fast computational speed, and high efficiency. Based on the stress prediction results, it is recommended to set the jacking height difference control threshold at 20 mm. When the jacking height difference is less than 20 mm, the local maximum stress value under the combined influence of both parameters should be less than the standard limit. The corresponding lateral deviation control threshold can be dynamically adjusted according to the actual travel difference recorded by the jacking equipment, with the control precision improved to 1 mm.

Objectives The objective of this study is to evaluate the value of S100‐A8 protein as a diagnostic marker for spinal tuberculosis and to explore its role in the potential pathogenesis of spinal tuberculosis (STB). Methods The peripheral blood of 100 spinal tuberculosis patients admitted to the General Hospital of Ningxia Medical University from September 2018 to June 2021 were collected as the observation group, and the peripheral blood of 30 healthy medical examiners were collected as the control group. Three samples from the observation group and three samples from the control group were selected for proteomics detection and screening of differential proteins. Kyoto Encyclopedia of Genes (KEGG) was used to enrich and analyze related signaling pathways to confirm the target protein. The serum expression levels of the target proteins were determined and compared between the two groups using enzyme‐linked immunosorbent assay (ELISA). Statistical methods were used to evaluate the value of target protein as a diagnostic marker for STB. A macrophage model of Mycobacterium tuberculosis infection was constructed and S100‐A8 small interfering RNA was used to investigate the molecular mechanism of the target protein. Results S100‐A8 protein has the value of diagnosing spinal tuberculosis (AUC = 0.931, p < 0.001), and the expression level in the peripheral blood of the observation group (59.04 ± 19.37 ng/mL) was significantly higher than that of the control group (43.16 ± 10.07 ng/mL) (p < 0.05). S100‐A8 protein expression showed a significant positive correlation with both CRP and ESR values (p < 0.01). Its AUCs for combined bacteriological detection, T‐SPOT results, diagnostic imaging, antacid staining results, and pathological results were 0.705 (p < 0.05), 0.754 (p < 0.01), 0.716 (p < 0.01), 0.656 (p < 0.05), and 0.681 (p < 0.01), respectively. Lack of S100‐A8 leads to a significant decrease in the expression levels of TLR4 and IL‐17A in infected macrophages. Conclusion S100‐A8 protein is differentially expressed in the peripheral blood of patients with spinal tuberculosis and healthy individuals and may be a novel candidate biomarker for the diagnosis of spinal tuberculosis. The feedback loop on the S100‐A8‐TLR4‐IL‐17A axis may play an important role in the inflammatory mechanism of spinal tuberculosis. Studying differentially expressed proteins in the STB patients from a proteomic perspective. Apply S100‐A8 protein as a diagnostic marker for STB. Exploring the S100‐A8/TLR4/IL‐17A axis in the pathogenesis of STB.

Objective: To investigate the correlation between the expression of lipopolysaccharide-binding protein (LBP) in peripheral blood of spinal tuberculosis and clinical diagnosis and to evaluate its value as a diagnostic marker of spinal tuberculosis. Methods: In the experimental group, clinical history data and peripheral blood were collected from 100 patients with spinal tuberculosis who were admitted to the Department of Spine Surgery, General Hospital of Ningxia Medical University from May 2017 to May 2020, and peripheral blood was collected from 30 healthy volunteers in the control group. Screening of differential LBP expression by proteomics and ELISA to verify its expression in peripheral blood of spinal tuberculosis patients, f- test, Spearman analysis, linear regression and ROC curve were used to evaluate the diagnostic value of LBP in peripheral blood for spinal tuberculosis. Results: The expression of LBP protein in peripheral blood is significantly higher in patients with spinal tuberculosis than in the normal population; LBP assay values were significantly and positively correlated with CRP and ESR values (P < 0.01); the AUC of LBP in the diagnosis of spinal tuberculosis for pathological examination, bacteriological culture, T-cell spot test for tuberculosis infection (T-SPOT), imaging diagnosis, and acid fast bacillus were, respectively, 0.677 (P < 0.01), 0.707 (P < 0.01), 0.751 (P < 0.01), 0.714 (P < 0.01), and 0.656 (P < 0.05), and there was a correlation between LBP and the diagnostic evaluation of spinal tuberculosis. Conclusion: LBP could be a new candidate biomarker for the diagnosis of spinal tuberculosis. Keywords: spinal tuberculosis, proteomics, LBP, biomarker

Human hexokinase 2 is an essential regulator of glycolysis that couples metabolic and proliferative activities in cancer cells. The binding of hexokinase 2 to the outer membrane of mitochondria is critical for its oncogenic activity. However, the regulation of hexokinase 2 binding to mitochondria remains unclear. Here, we report that SUMOylation regulates the binding of hexokinase 2 to mitochondria. We find that hexokinase 2 can be SUMOylated at K315 and K492. SUMO-specific protease SENP1 mediates the de-SUMOylation of hexokinase 2. SUMO-defective hexokinase 2 preferably binds to mitochondria and enhances both glucose consumption and lactate production and decreases mitochondrial respiration in parallel. This metabolic reprogramming supports prostate cancer cell proliferation and protects cells from chemotherapy-induced cell apoptosis. Moreover, we demonstrate an inverse relationship between SENP1-hexokinase 2 axis and chemotherapy response in prostate cancer samples. Our data provide evidence for a previously uncovered posttranslational modification of hexokinase 2 in cancer cells, suggesting a potentially actionable strategy for preventing chemotherapy resistance in prostate cancer. The oncogenic activity of Hexokinase 2, the first rate-limiting enzyme of glycolysis, requires its mitochondrial localization. Here, the authors show that SUMOylation of hexokinase 2 disrupts its binding to mitochondria and protects cells from tumorigenesis in prostate cancer.

Aqueous zinc‐manganese (Zn–Mn) batteries have promising potential in large‐scale energy storage applications since they are highly safe, environment‐friendly, and low‐cost. However, the practicality of Mn‐based materials is plagued by their structural collapse and uncertain energy storage mechanism upon cycling. Herein, this work designs an amorphous manganese borate (a‐MnBOx) material via disordered coordination to alleviate the above issues and improve the electrochemical performance of Zn–Mn batteries. The unique physicochemical characteristic of a‐MnBOx enables the inner a‐MnBOx to serve as a robust framework in the initial energy storage process. Additionally, the amorphous manganese dioxide, amorphous ZnxMnO(OH)2, and Zn4SO4(OH)6·4H2O active components form on the surface of a‐MnBOx during the charge/discharge process. The detailed in situ/ex situ characterization demonstrates that the heterostructure of the inner a‐MnBOx and surface multicomponent phases endows two energy storage modes (Zn2+/H+ intercalation/deintercalation process and reversible conversion mechanism between the ZnxMnO(OH)2 and Zn4SO4(OH)6·4H2O) phases). Therefore, the obtained Zn//a‐MnBOx battery exhibits a high specific capacity of 360.4 mAh g−1, a high energy density of 484.2 Wh kg−1, and impressive cycling stability (97.0% capacity retention after 10 000 cycles). This finding on a‐MnBOx with a dual‐energy storage mechanism provides new opportunities for developing high‐performance aqueous Zn–Mn batteries. A conceptual amorphous manganese borate material for AZIBs is designed via a disordered coordination strategy. The unique physicochemical characteristic of a‐MnBOx can form the a‐MnO2, ZnxMnO(OH)2, and Zn4SO4(OH)6·4H2O phases, realizing multiple energy storage modes for enhancing the charge storage ability.

With the continuous promotion of digitalization and the global trend toward a low-carbon economy, the issue of whether enterprises can enhance their carbon performance with the assistance of digital technology has aroused widespread attention from both academia and industry. In order to explore whether digital technology can improve the carbon performance of manufacturing enterprises, this study, based on resource orchestration theory and signaling theory, utilizes data from China’s A-share manufacturing enterprises from 2012 to 2021 to empirically investigate the relationship between digital technology and the carbon performance of manufacturing firms. It also explores the mediating conduction path and boundary influencing factors between them. Its findings demonstrate that: digital technology is capable of improving carbon performance; green innovation (including green technology and green collaboration) has partially mediating effects; there is a catalytic role for environmental information disclosure in utilizing digital technology to enhance carbon performance. Building on this, we find that the impacts of digital technology, green innovation, and environmental information disclosure on carbon performance vary due to differences in the nature of industries and the strategic aggressiveness of enterprises. Specifically, the role of digital technology on carbon performance seems somewhat more pronounced among firms in the high-tech industry and those employing defensive and analytical strategies. Additionally, the effects generated by green innovation and environmental information are more pronounced in the high-tech industry and among enterprises that adopt analytical strategies. This study reveals the inherent mechanism of digital technology in enhancing the carbon performance of manufacturing enterprises, which provides empirical evidence for the development of digital technology and the improvement of carbon performance in manufacturing enterprises, thus helping promote low-carbon economic transformation.

As global attention to the issue of climate change grows, the concepts of carbon peaking and carbon neutrality, proposed by China, have increasingly gained traction. In this international context, digital technology and green development are closely interwoven, carving out a distinct path for countries worldwide to achieve carbon emission reduction goals. This study empirically explores the mechanism of how digital transformation impacted the carbon emissions of Chinese A-share listed manufacturing enterprises from 2007 to 2021. The results indicate a significant inverted U-shaped nonlinear connection between digital transformation and carbon emissions within manufacturing enterprises. Green technology innovation, which is among the crucial driving forces for sustainable development, can act as a mediating factor. External environmental regulations positively moderate the relationship between digital transformation and carbon emissions in manufacturing firms. Furthermore, the heterogeneity analysis reveals that the nonlinear impact of digital transformation on carbon emissions in manufacturing enterprises is particularly significant in western regions, non-resource-based cities, light industry sectors, and large-scale enterprises. This paper innovatively verifies, at the micro level, the inverted U-shaped impact of digital transformation on carbon emissions in manufacturing enterprises, as well as its underlying mechanism. It provides theoretical support and practical guidance for the effective implementation of carbon emission reduction in the manufacturing sector. Meanwhile, it also offers valuable insights for manufacturing enterprises to formulate strategies that take both digital development and sustainable development into account, thereby contributing to the achievement of sustainable development.

In recent years, the prevalence of tuberculosis worldwide has increased, and with it, the number of drug-resistant tuberculosis strains. This has brought new challenges towards prevention and control of the disease. Therefore, it is urgent to find reliable and rapid diagnostic methods for tuberculosis in general, and for the drug-resistant forms of the disease. To this aim, we assessed 17 tuberculosis-specific protein candidates for the detection of tuberculosis-specific antibodies. First, we established an indirect ELISA method to detect anti-Mycobacterium tuberculosis IgM and IgG. We tested 453 sera and analyzed the efficacy of the protein candidates for diagnosis of tuberculosis. Next, we screened antigens rich in T cell epitopes for their ability to induce high levels of IFN-γ, in order to define their suitability does develop detection tests based on IFN-γ release assay (IGRAs). The antigens CFP-10, PPE57, 38kDa, and Rv3807 showed higher diagnostic potential for the detection of anti-tuberculosis IgM, whereas PPE57, Ag85B, CFP-10, Rv0220, and 38kDa antigens performed better for anti-tuberculosis IgG detection. Worth noting is that CFP-10, 38kDa, and PPE57 detected efficiently both IgM and IgG. Rv1987, Rv3807, PPE57, Rv0220, and MPT64 proteins alone and combinations of Rv1987 + Rv3807, 16kDa + Rv0220, and MPT64 + Rv1986 tested in IGRAs displayed a good correlation with the positive control constituted by a cocktail of ESAT-6 + CFP-10 + TB7.7 (ECT), known for their stimulating properties (r > 0.5, p < 0.01). Among these antigen candidates, Rv0220 and Rv1987 + Rv3807 were the most potent. We discovered CFP-10, 38kDa, and PPE57 for the detection of anti-M. tuberculosis IgM and IgG, and Rv0220 alone or the combination Rv1987 + Rv3807 as the strongest stimulators in IGRAs. These antigens provide new references for the screening of tuberculosis-specific antibodies and effective stimulation in IGRAs.

Background. Studies on serum uric acid (sUA) levels and hypertension (HTN) are controversial. To investigate the association between the sUA level and the incident of HTN in middle-aged and elderly adults, we performed this study. Methods. 6399 participants aged ≥40 years from the National Health and Nutrition Examination Survey (NHANES) were included. Weighted multiple logistic regression analysis was carried out to evaluate the relationship between the sUA level and the incident of HTN, exploring the potential nonlinear relationship using the fitted smoothing curves. If nonlinearity was observed, the inflection point was further calculated by a recursive algorithm. Results. A positive relationship between the sUA level and the incident of HTN was found. However, it may differ in different race groups, nor between male and female. Moreover, the association between the sUA level and the incident of HTN followed a U-shaped curve in male (turning point: sUA 4.1 mg/dL) and Whites (turning point: sUA 7.9 mg/dL). Conclusions. The results revealed that the sUA level is positively correlated with the incident of HTN, in middle-aged and elderly adults. However, it followed a U-shaped curve in males and Whites.