Efficiency evaluation of China's transportation system considering carbon emissions: Evidence from big data analytics methods.

China's transportation sector is a vital link between production and consumption, but it also has issues with low efficiency, high carbon emissions, and technological bottlenecks. To improve efficiency and provide actionable recommendations and strategies, this study first constructs a comprehensive evaluation index system to gauge the transportation sector's inputs using panel data from different Chinese provinces from 2007 to 2021. Within the assessment system, the principal component analysis (PCA) method is used to reduce the dimension of the indexes, thereby yielding a set of adjusted inputs. Subsequently, the transportation system efficiency (TSE) is evaluated using the super-efficiency SBM-DEA model, which includes unexpected outputs such as carbon emissions, and three-stage DEA modifies the efficiency. Then, we calculate the Malmquist-Luenberger index (TML) and its components: technological change (TTC) and technological efficiency change (TEC). Lastly, the influential factors impacting TSE are analyzed via a truncated regression Tobit model. The following are the conclusions: (1) The transportation industry in China exhibits inefficiency, and the average TSE in Stage I and III is 0.91 and 0.93, respectively. TSE is underestimated due to the influence of external environmental factors and inefficiencies in management in Stage I. (2) TSE in the eastern area also produces significant carbon emissions that surpass the national average. At the same time, other regions face efficiency limitations due to geographical constraints and management obstacles. (3) Insufficient technical capacity is a major cause of inefficiency in the transport sector and is prevalent in the northeast, west, and central regions. (4) Population growth and income per capita advancements foster transportation industry development, while increased GDP, fiscal revenues, and traffic accidents contribute to declining efficiency. The study above findings serve as a foundation for regional and national management initiatives and policies to enhance transportation effectiveness.

Prediction of carbon emissions in China's construction industry using an improved grey prediction model.

As a significant source of global energy consumption and greenhouse gas emissions, the construction industry garners widespread attention due to its high carbon emissions. Anticipating its development trends is crucial for energy conservation and emission reduction. In this paper, we utilize the carbon emission data from China's national and provincial construction sectors from 2012 to 2021, employ the grey prediction model optimized by the particle swarm optimization algorithm, coupled with a metabolic algorithm, to forecast the carbon emissions of the construction industry across China and its provinces. The results demonstrate that: (1) The dynamic grey prediction model combined with the metabolism algorithm has a better prediction effect than the classical model, and the relative error is reduced from 5.103 % to 0.874 %. (2) The carbon emissions of China's construction industry will continue to rise in the next decade, but the growth rate will decrease, and the proportion of indirect carbon emissions continues to increase. (3) There is a marked regional disparity in carbon emissions, with the eastern region exhibiting higher emission levels yet slower growth. In contrast, the western region has lower emission levels but experiences faster growth. These studies provide valuable insights for both the existing approaches to energy conservation and emission reduction, as well as for future policy improvements.

MicroRNA-18a regulates the Pyroptosis, Apoptosis, and Necroptosis (PANoptosis) of osteoblasts induced by tumor necrosis factor-α via hypoxia-inducible factor-1α.

BACKGROUND: Tumor necrosis factor-α (TNF-α) is involved in inflammatory responses and promotes cell death and the inhibition of osteogenic differentiation. MicroRNA (miRNA) plays a crucial role in the infected bone diseases, however, the biological role of miRNAs in inflammation-induced impaired osteogenic differentiation remains unclear. This study aimed to explore the role of miRNA-18a-5p (miR-18a) in regulating PANoptosis and osteogenic differentiation in an inflammatory environment via hypoxia-inducible factor-1α (HIF1-α). METHODS: The expression of miR-18a in MC3T3-E1 cells was analyzed using quantitative reverse transcription-polymerase chain reaction in an inflammatory environment induced by TNF-α. The expression of HIF1-α and NLRP3 in LV-miR-18a or sh-miR-18a cells was analyzed using western blotting. Fluorescence imaging for cell death, flow cytometry, and alkaline phosphatase activity analysis were used to analyze the role of miR-18a in TNF-α-induced PANoptosis and the inhibition of osteogenic differentiation. An animal model of infectious bone defect was established to validate the regulatory role of miR-18a in an inflammatory environment. RESULTS: The expression of miRNA-18a in the MC3T3-E1 cell line was significantly lower under TNF-α stimulation than in the normal environment. miR-18a significantly inhibited the expression of HIF1-α and NLRP3, and inhibition of HIF1-α expression further inhibited NLRP3 expression. Furthermore, inhibition of miR-18a expression promoted the TNF-α-induced PANoptosis and inhibition of osteogenic differentiation, whereas miR-18a overexpression and the inhibition of both HIF1-α and NLRP3 reduced the effects of TNF-α. These findings are consistent with those of the animal experiments. CONCLUSION: miRNA-18a negatively affects HIF1-α/NLRP3 expression, inhibits inflammation-induced PANoptosis, and impairs osteogenic differentiation. Thus, it is a potential therapeutic candidate for developing anti-inflammatory strategies for infected bone diseases.

Microbiological profile of diabetic foot infections in China and worldwide: a 20-year systematic review.

Introduction: Pathogens causing diabetic foot infections (DFIs) vary by region globally; however, knowledge of the causative organism is essential for effective empirical treatment. We aimed to determine the incidence and antibiotic susceptibility of DFI pathogens worldwide, focusing on Asia and China. Methods: Through a comprehensive literature search, we identified published studies on organisms isolated from DFI wounds from January 2000 to December 2020. Results: Based on our inclusion criteria, we analyzed 245 studies that cumulatively reported 38,744 patients and 41,427 isolated microorganisms. DFI pathogens varied according to time and region. Over time, the incidence of Gram-positive and Gram-negative aerobic bacteria have decreased and increased, respectively. America and Asia have the highest (62.74%) and lowest (44.82%) incidence of Gram-negative bacteria, respectively. Africa has the highest incidence (26.90%) of methicillin-resistant Staphylococcus aureus. Asia has the highest incidence (49.36%) of Gram-negative aerobic bacteria with species infection rates as follows: Escherichia coli, 10.77%; Enterobacter spp., 3.95%; and Pseudomonas aeruginosa, 11.08%, with higher local rates in China and Southeast Asia. Linezolid, vancomycin, and teicoplanin were the most active agents against Gram-positive aerobes, while imipenem and cefoperazone-sulbactam were the most active agents against Gram-negative aerobes. Discussion: This systematic review showed that over 20 years, the pathogens causing DFIs varied considerably over time and region. This data may inform local clinical guidelines on empirical antibiotic therapy for DFI in China and globally. Regular large-scale epidemiological studies are necessary to identify trends in DFI pathogenic bacteria. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023447645.

Global trends in publications regarding macrophages-related diabetic foot ulcers in the last two decades.

BACKGROUND: Diabetic foot ulcers (DFUs) are one of the most severe and popular complications of diabetes. The persistent non-healing of DFUs is the leading cause of ampu-tation, which causes significant mental and financial stress to patients and their families. Macrophages are critical cells in wound healing and perform essential roles in all phases of wound healing. However, no studies have been carried out to systematically illustrate this area from a scientometric point of view. Although there have been some bibliometric studies on diabetes, reports focusing on the investigation of macrophages in DFUs are lacking. AIM: To perform a bibliometric analysis to systematically assess the current state of research on macrophage-related DFUs. METHODS: The publications of macrophage-related DFUs from January 1, 2004, to December 31, 2023, were retrieved from the Web of Science Core Collection on January 9, 2024. Four different analytical tools: VOSviewer (v1.6.19), CiteSpace (v6.2.R4), HistCite (v12.03.07), and Excel 2021 were used for the scientometric research. RESULTS: A total of 330 articles on macrophage-related DFUs were retrieved. The most published countries, institutions, journals, and authors in this field were China, Shanghai Jiao Tong University of China, Wound Repair and Regeneration, and Aristidis Veves. Through the analysis of keyword co-occurrence networks, historical direct citation networks, thematic maps, and trend topics maps, we synthesized the prevailing research hotspots and emerging trends in this field. CONCLUSION: Our bibliometric analysis provides a comprehensive overview of macrophage-related DFUs research and insights into promising upcoming research.