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Given the significant impact of transportation-related carbon emissions on air quality and climate change, understanding the regional dynamics of these emissions is crucial. Despite numerous studies on carbon emissions, there is a lack of comprehensive analysis of China's interprovincial transport carbon emission correlation network. Based on China's provincial data from 2007 to 2021, we analyzed the network's basic structural characteristics and categorized it into four significant plates to investigate their interactions. Subsequently, motif analysis is employed to examine the micro-correlation patterns within the network, and the Exponential random graph model (ERGM) is utilized to analyze the network's formation mechanism. Findings reveal that: (1) Provinces with high correlation intensity are predominantly concentrated in the eastern region, such as Shanghai and Beijing. Additionally, provinces in the eastern region assume a central role in the transport carbon emission correlation network, mainly receiving carbon emissions from other provinces. In contrast, the western region primarily emits carbon emissions to other provinces, continuously converging towards the center. (2) The network is segmented into net beneficiary plate, net overflow plate, bidirectional spillover plate, and broker plate, with distinct roles and influences across different years. (3) Bidirectional correlation motif structures emerge as primary influencers within the network, although specific structures impede interregional communication and collaborative emission reduction. (4) Internal network's structural variables, such as mutuality, cyclic triple, and geometrically weighted edgewise shared partner, along with influencing factors including government intervention, urbanization rate, openness, fiscal expenditure on transport, and province adjacency significantly impact the formation of the transport carbon emission correlation network. The above transportation network research provides a theoretical basis for the country to promote low-carbon transportation and improve air quality, and also has important guiding significance for the cross-regional collaborative emission reduction work of provinces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

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., 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 © 2024 Qu, Ou, Zhang, Li, Xia, Yang, Liu, Ma, Jiang, Wang, Chen, Yu, Qi and Xu.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate the biological activity of molecules with their chemical structures, which can be useful in the field of pharmacology., Objective: This article's goal is to develop analytically closed computing formulas for eccentricitybased descriptors of the second type of dominating David-derived network. Thermodynamic characteristics, physicochemical properties, and chemical and biological activities of chemical graphs are just a few of the many properties that may be determined using these computation formulas., Methods: Vertex sets were initially divided according to their degrees, eccentricities, and cardinalities of occurrence. The eccentricity-based indices are then computed using some combinatorics and these partitions., Results: Total eccentricity, average eccentricity, and the Zagreb index are distance-based topological indices utilized in this study for the second type of dominating David-derived network, denoted as D2(m)., Conclusion: These calculations will assist the readers in estimating the fractal and difficult-tohandle thermodynamic and physicochemical aspects of chemical structure. Apart from configuration and impact resistance, the D2(m) design has been used for fundamental reasons in a variety of technical and scientific advancements., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Cheminformatics is a fascinating emerging subfield of chemical graph theory that studies quantitative structure-activity and property relationships of molecules and, in turn, uses these to predict the physical and chemical properties, which are extremely useful in drug discovery and optimization. Knowledge discovery can be put to use in pharmaceutical data matching to help in finding promising lead compounds., Method: Topological descriptors are numerical quantities corresponding to the chemical structures that are used in the study of these phenomena., Result: This paper is concerned with developing the generalized analytical expression of topological descriptors for zeolite ACO structures with underlying degree and degree-sum parameters., Conclusion: To demonstrate improved discrimination power between the topological descriptors, we have further modified Shannon's entropy approach and used it to calculate the entropy measures of zeolite ACO structures., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.

Entropy is a measure of a system's molecular disorder or unpredictability since work is produced by organized molecular motion. Shannon's entropy metric is applied to represent a random graph's variability. Entropy is a thermodynamic function in physics that, based on the variety of possible configurations for molecules to take, describes the randomness and disorder of molecules in a given system or process. Numerous issues in the fields of mathematics, biology, chemical graph theory, organic and inorganic chemistry, and other disciplines are resolved using distance-based entropy. These applications cover quantifying molecules' chemical and electrical structures, signal processing, structural investigations on crystals, and molecular ensembles. In this paper, we look at K -Banhatti entropies using K -Banhatti indices for C6H6 embedded in different chemical networks. Our goal is to investigate the valency-based molecular invariants and K -Banhatti entropies for three chemical networks: the circumnaphthalene (CNBn), the honeycomb (HBn), and the pyrene (PYn). In order to reach conclusions, we apply the method of atom-bond partitioning based on valences, which is an application of spectral graph theory. We obtain the precise values of the first K -Banhatti entropy, the second K -Banhatti entropy, the first hyper K -Banhatti entropy, and the second hyper K -Banhatti entropy for the three chemical networks in the main results and conclusion.

Background: High D-dimer (DD) is associated with short-term adverse outcomes in patients with acute coronary syndrome (ACS). In ACS patients who underwent percutaneous coronary intervention (PCI), however, the value of DD (or combined with neutrophil to lymphocyte ratio [NLR]) to predict long-term major adverse cardiovascular events (MACEs) has not been fully evaluated., Methods: Patients diagnosed with ACS and receiving PCI were included. The primary outcome was MACEs. Cox proportional hazards regression and logistic regression were used to illustrate the relationship between clinical risk factors, biomarkers and MACEs. Survival models were developed based on significant factors and evaluated by the Concordance-index (C-index)., Results: The final study cohort was comprised of 650 patients (median age, 64 years; 474 males), including 98 (15%) with MACEs during a median follow-up period of 40 months. According to the cut-off value of DD and NLR, the patients were separated into four groups: high DD or nonhigh DD with high or nonhigh NLR. After adjusting for confounding variables, DD (adjusted hazard ratio [aHR]: 2.39, 95% confidence interval [CI]: 1.52-3.76) and NLR (aHR: 2.71, 95% CI: 1.78-4.11) were independently associated with long-term MACEs. Moreover, patients with both high DD and NLR had a significantly higher risk in MACEs when considering patients with nonhigh DD and NLR as reference (aHR: 6.19, 95% CI: 3.30-11.61). The area under curve increased and reached 0.70 in differentiating long-term MACEs when DD and NLR were combined, and survival models incorporating the two exhibited a stronger predictive power (C-index: 0.75)., Conclusions: D-dimer (or combined with NLR) can be used to predict long-term MACEs in ACS patients undergoing PCI.

A topological index as a graph parameter was obtained mathematically from the graph's topological structure. These indices are useful for measuring the various chemical characteristics of chemical compounds in the chemical graph theory. The number of atoms that surround an atom in the molecular structure of a chemical compound determines its valency. A significant number of valency-based molecular invariants have been proposed, which connect various physicochemical aspects of chemical compounds, such as vapour pressure, stability, elastic energy, and numerous others. Molecules are linked with numerical values in a molecular network, and topological indices are a term for these values. In theoretical chemistry, topological indices are frequently used to simulate the physicochemical characteristics of chemical molecules. Zagreb indices are commonly employed by mathematicians to determine the strain energy, melting point, boiling temperature, distortion, and stability of a chemical compound. The purpose of this study is to look at valency-based molecular invariants for SiO4 embedded in a silicate chain under various conditions. To obtain the outcomes, the approach of atom-bond partitioning according to atom valences was applied by using the application of spectral graph theory, and we obtained different tables of atom-bond partitions of SiO4. We obtained exact values of valency-based molecular invariants, notably the first Zagreb, the second Zagreb, the hyper-Zagreb, the modified Zagreb, the enhanced Zagreb, and the redefined Zagreb (first, second, and third). We also provide a graphical depiction of the results that explains the reliance of topological indices on the specified polynomial structure parameters.

Entropy is a thermodynamic function in chemistry that reflects the randomness and disorder of molecules in a particular system or process based on the number of alternative configurations accessible to them. Distance-based entropy is used to solve a variety of difficulties in biology, chemical graph theory, organic and inorganic chemistry, and other fields. In this article, the characterization of the crystal structure of niobium oxide and a metal-organic framework is investigated. We also use the information function to compute entropies by building these structures with degree-based indices including the K -Banhatti indices, the first redefined Zagreb index, the second redefined Zagreb index, the third redefined Zagreb index, and the atom-bond sum connectivity index.

Chemical descriptors are numeric numbers that capture the whole graph structure and comprise a basic chemical structure. As a topological descriptor, it correlates with certain physical aspects in addition to its chemical representation of underlying chemical substances. In the modelling and design of any chemical network, the graph is important. A number of chemical indices have been developed in theoretical chemistry, including the Wiener index, the Randić index, and many others. In this paper, we look at the benzenoid networks and calculate the exact topological indices based on the degrees of the end vertices.

Abnormal target detection in hyperspectral remote sensing image is one of the hotspots in image research. The image noise generated in the detection process will lead to the decline of the quality of hyperspectral remote sensing image. In view of this, this paper proposes an abnormal target detection method of hyperspectral remote sensing image based on the convolution neural network. Firstly, the deep residual learning network model has been used to remove the noise in hyperspectral remote sensing image. Secondly, the spatial and spectral features of hyperspectral remote sensing images were used to optimize the clustering dictionary, and then the image segmentation containing target information is completed. Finally, the image was input into the deep convolution neural network with a dual classifier, and the network detects the abnormal target in the image. The test results of this algorithm show that the structural similarity of the denoised image is higher than 0.86, which shows that this method has good noise reduction performance, image details will not damage, segmentation effect is good, and it can obtain high-definition target image information and accurately detect abnormal targets in the image., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Yun Liu and Jia-Bao Liu.)

By taking the 16 cities in Anhui Province for evaluation, the main influencing factors and indicator system for integrated urban-rural development in the new era were explored, to build the BCC model, cross-efficiency model, and game cross-efficiency model of DEA. The above models were applied for empirical analysis and comparative study on the rural revitalization and urban-rural integration efficiency in Anhui Province, to summarize the conclusions efficiency and give suggestions based on the above calculations., Competing Interests: The authors declare there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Shanhui Sun et al.)

Based on the Chinese General Social Survey database (2010-2015), this article explores the relationship between income inequality and residents' subjective well-being from the perspective of inequality of opportunity and inequality of effort. We find that inequality of opportunity has a negative impact on subjective well-being in China, where inequality of effort has a positive impact. Our empirical results are robust for changing the inequality indicators. In the sub-sample studies, consistent conclusions are obtained in rural areas, whereas in urban areas only inequality of effort has a significant impact. The results of mechanism study show that inequality of opportunity decreases residents' sense of fairness, and inequality of effort increases residents' sense of fairness, thus affecting their subjective well-being. The results of this study provide a good response to the inconclusive research findings on the impact of income inequality on subjective well-being., 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 © 2022 He, Tong and Liu.)

With the popularization of higher education and the promotion of college enrollment expansion, the number of college graduates increases sharply. At the same time, the continuous transformation and upgrading of the industrial structure put forward higher requirements on the employability of college students, which leads to the imbalance between supply and demand in the labor market. The key to dealing with employment difficulties lie in the improvement of college students' employability. Therefore, we make a regression analysis of 263 valid samples from universities in Anhui Province and extract the factors that influence the improvement of college students' employability in the process of talent cultivation in university. The result shows that there is a positive correlation between course setting, course teaching, club activities, and college students' employability, among which the course teaching and club activities are the most critical factors which may influence college students' employability. In addition, from the viewpoint of individual college students, the overall grades of college students and the time of participating in the internship are also closely related to their employability, i.e., college students with good overall grades and long internship time should also have stronger employability., 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 © 2022 Zhang, Zhang, Xiong, Liu and Zhai.)

Objective: To investigate the short-term clinical effect of lumbar nerve root canal injection under X-ray angiography in the treatment of sciatica., Methods: The clincal data of 78 patients with sciatica underwent lumbar nerve root canal injection under X-ray angiography from December 2017 to February 2020 was retrospectively analyzed. Including 31 males and 47 females, aged from 22 to 88 years old with a median of 65 years. There were 55 cases of lumbar disc herniation and 23 cases of lumbar spinal stenosis, the course of disease ranged from 1 to 8 weeks with a median of 3 weeks. There were 71 cases of single segment disc herniation or stenosis, including L 3,4 of 5 cases, L 4,5 of 61 cases, L 5 S 1 of 5 cases, and 7 cases of multisegment herniation or stenosis. The pain visual analogue scale (VAS) was recorded and Macnab was used to evaluate the clinical effect., Results: All patients completed standardized treatment without serious adverse reactions. VAS were (3.21±0.76) scores immediately after treatment, (2.89±0.33) scores 1 hour after treatment, (1.80±0.27) scores 6 hours after treatment, (1.10±0.20) scores 24 hours after treatment, (2.53±0.35) scores 1 week after treatment and (4.27±0.36) scores 1 month after treatment. There were significant differences in VAS between before treatment(7.83±0.56) and each time period after treatment( P <0.05). According to Macnab low back pain evaluation standard, 42 cases were effective, 34 cases were markedly effective and 2 cases were ineffective within 24 hours after treatment, with an effective rate of 97.4%;38 cases were effective, 25 cases were markedly effective, 15 cases were ineffective within one week after treatment, the effective rate was 80.0%;32 cases were effective, 22 cases were markedly effective, 24 cases were ineffective within one month after treatment, the effective rate was 69.2%., Conclusion: The short-term clinical effect of nerve root canal injection under X-ray radiography in the treatment of sciatica is good and it is an effective method to relieve sciatica.

In order to fully implement the new development concept, bring into full play the potential of sports development, and maintain the resilience of China's sports development. This paper studies the resilience evaluation and spatial correlation of Chinese sports development under the new development concept. First, we constructed Resilience Evaluation Indexes System for Sports Development in China based on the analysis of the resilience features of sports development and the DPSIR model, which is from the five aspects of "driving force - pressure - state - influence - response." Second, used Coefficient of Variation and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) Method to measure the resilience level of sports development in 31 provinces in China from 2013 to 2017. Then, we introduced the obstacle degree model to identify the obstacle factors that hinder the resilience of Chinese sports development in different periods. Finally, we used the global and local Moran indexes to analyze the spatial correlation of China sports regional development. The results showed that: (1) overall, the development level of sports resilience in 31 provinces in China showed an upward trend from 2013 to 2017, while some provinces showed obvious fluctuations. (2) The obstacles to the development of sports resilience in China mainly include sports scientific research equipment, the number of national fitness monitoring stations, the number of national fitness centers, the full-time equivalent of (R&D) personnel, and the number of sports scientific research projects. The response subsystem is the main obstacle factor that affects the improvement of the resilience level of sports development in China. (3) There is a positive spatial autocorrelation between the resilience level of sports development and regional spatial distribution, and the correlation shows a weakening trend, and the internal difference is significant. Finally, we concluded that we must take the new development philosophy as the guiding principle. First, we should stick to innovation-driven development to fully upgrade the resilience of China's sports development. Second, we should adhere to the principle of coordinated development to promote the overall and balanced development of sports. Lastly, we should promote shared development so as to deliver benefits for all in an equal way., 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 © 2022 Zhang, Gan, Wu, Liu, Zhang and Shao.)

Background: A topological index is a real number associated with a graph that provides information about its physical and chemical properties and their correlations. Topological indices are being used successfully in Chemistry, Computer Science, and many other fields., Methods: In this article, we apply the well-known Cartesian product on F-sums of connected and finite graphs. We formulate sharp limits for some famous degree-dependent indices., Results: Zagreb indices for the graph operations T(G), Q(G), S(G), R(G), and their F-sums have been computed. By using orders and sizes of component graphs, we derive bounds for Zagreb indices, F-index, and Narumi-Katayana index., Conclusion: The formulation of expressions for the complicated products on F-sums, in terms of simple parameters like maximum and minimum degrees of basic graphs, reduces the computational complexities., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Introduction: In this paper, we present a novel hybrid model m-polar Diophantine fuzzy N-soft set and define its operations., Methods: We generalize the concepts of fuzzy sets, soft sets, N-soft sets, fuzzy soft sets, intuitionistic fuzzy sets, intuitionistic fuzzy soft sets, Pythagorean fuzzy sets, Pythagorean fuzzy soft sets and Pythagorean fuzzy N-soft sets by incorporating our proposed model. Additionally, we define three different sorts of complements for Pythagorean fuzzy N-soft sets and examine few outcomes, which do not hold in Pythagorean fuzzy N-soft sets complements unlike to crisp set. We further discuss (α, β, γ) -cut of m-polar Diophantine fuzzy N-soft sets and their properties. Lastly, we prove our claim that the defined model is a generalization of the soft set, N-soft set, fuzzy Nsoft set, intuitionistic fuzzy N soft set, and Pythagorean fuzzy N-soft set., Results: m-polar Diophantine fuzzy N-soft set is more efficient and an adaptable model to manage uncertainties as it also overcomes drawbacks of existing models, which are to be generalized., Conclusion: We introduced the novel concept of m-polar Diophantine fuzzy N-soft sets (MPDFNS sets)., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Aims and Objective: The idea of partition and resolving sets play an important role in various areas of engineering, chemistry and computer science such as robot navigation, facility location, pharmaceutical chemistry, combinatorial optimization, networking, and mastermind game., Methods: In a graph, to obtain the exact location of a required vertex, which is unique from all the vertices, several vertices are selected; this is called resolving set, and its generalization is called resolving partition, where selected vertices are in the form of subsets. A minimum number of partitions of the vertices into sets is called partition dimension., Results: It was proved that determining the partition dimension of a graph is a nondeterministic polynomial time (NP) problem. In this article, we find the partition dimension of convex polytopes and provide their bounds., Conclusion: The major contribution of this article is that due to the complexity of computing the exact partition dimension, we provide the bounds and show that all the graphs discussed in the results have partition dimensions either less or equals to 4, but not greater than 4., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Aim and Objective: Nanostructures are objects whose sizes vary between microscopic and molecular. The most significant of these new elements are carbon nanotubes. These elements have extraordinary microelectronic properties and many other exclusive physiognomies. Recently, researchers have given attention to the mathematical properties of these materials. The aim and objective of this research article is to investigate the most important molecular descriptors namely Wiener, edge-Wiener, vertex-edge-Wiener, vertex-Szeged, edge-Szeged, edge-vertex-Szeged, total-Szeged, PI, Schultz, Gutman, Mostar, edge-Mostar, and total-Mostar indices of three-layered single-walled titania nanosheets. By computing these topological indices, material science researchers can have a better understanding of structural and physical properties of titania nanosheets, thereby synthesizing more easily new variants of titania nanosheets with more amenable physicochemical properties., Methods: The cut method turned out to be extremely handy when dealing with distance-based graph invariants which are in turn among the central concepts of chemical graph theory. In this method, we use the Djokovi-Winkler relation to find the suitable edge cuts to leave the graph into exactly two components. Based on the graph theoretical measures of the components, we obtain the desired topological indices by mathematical computations., Results: In this paper, distance-based indices for three-layered single-walled titania nanosheets were investigated and given the exact expressions for various dimensions of three-layered singlewalled titania nanosheets. These indices may be useful in synthesizing new variants of titania nanosheets and the computed topological indices play an important role in studies of Quantitative structure-activity relationship (QSAR) and Quantitative structure-property relationship (QSPR)., Conclusion: In this paper, we have obtained the closed expressions of several distance-based topological indices of three-layered single-walled titania nanosheet TNS 3 [m, n] molecular graph for the cases m > n and m < n. The graphical validations for the computed indices are done and we observe that the Wiener types, Schultz and Gutman indices perform in a similar way whereas PI and Mostar type indices perform in the same way., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: A topological index of a molecular graph is the numeric quantity which can predict certain physical and chemical properties of the corresponding molecule. Xu et al. introduced some graph transformations which increase or decrease the first and second multiplicative Zagreb indices and proposed a unified approach to characterize extremal (n, m)- graphs., Method: Graph transformations are used to find the extremal graphs, these transformations either increase or decrease the general multiplicative Zagreb indices. By applying the transformations which increase the general multiplicative Zagreb indices we find the graphs with maximal general multiplicative Zagreb indices and for minimal general Zagreb indices we use the transformations which decrease the index., Result: In this paper, we extend the Xu's results and show that the same graph transformations increase or decrease the first and second general multiplicative Zagreb indices for . As an application, the extremal acyclic, unicyclic and bicyclic graphs are presented for general multiplicative Zagreb indices., Conclusion: By applying the transformation we investigated that in the class of acyclic, unicyclic and bicyclic graphs, which graph gives the minimum and the maximum general multiplicative Zagreb indices., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species was established, thereby revealing the internal mechanism of fungal decomposition activity in a complex environment. Second, based on the linear regression method and the principle of biodiversity, a model of fungal decomposition rate was constructed, and it was concluded that the interaction between mycelial elongation and moisture resistance could increase the fungal decomposition rate. Third, the differential equations are used to quantify the competitive relationship between different bacterial species, divide the boundaries of superior and inferior species, and simulate the long-term and short-term evolution trends of the community under the same initial environment. And an empirical analysis is made by taking the sudden change of the atmosphere affecting the evolution of the colony as an example. Finally, starting from summer, combining soil temperature, humidity, and fungal species data in five different environments such as arid and semiarid, a three-dimensional model and RBF neural network are introduced to predict community evolution. The study concluded that under given conditions, different strains are in short-term competition, and in the long-term, mutually beneficial symbiosis. Biodiversity is important for the biological regulation of nature., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 Xiao-Wei Cai et al.)

Based on the theoretical mechanism analysis of FDI, regional innovation, and green economic efficiency, this article uses China's provincial panel data to calculate the provincial green economic efficiency level based on the three-stage DEA method and uses the system GMM model, intermediary effect model, and threshold model to empirically test the specific effects and transmission paths of FDI on the efficiency of the green economy. Research shows that FDI is one of the important factors that promote the improvement of green economic efficiency. Subregional tests have found that FDI has a significant regional heterogeneity in promoting the efficiency of the green economy. The mediation effect test found that the mediation effect of regional innovation is significant, and FDI can significantly promote the growth of green economic efficiency through regional innovation. The threshold effect analysis found that there are significant and effective double thresholds for regional economic levels, and the impact of FDI on green economic efficiency is heterogeneous within different threshold intervals. The research conclusions provide new inspiration for China to allocate FDI more rationally and efficiently under the new development pattern., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 You-Qun Wu et al.)

The entire world is struggling to control the spread of coronavirus (COVID-19) as there are no proper drugs for treating the disease. Under clinical trials, some of the repurposed antiviral drugs have been applied to COVID-19 patients and reported the efficacy of the drugs with the diverse inferences. Molecular topology has been developed in recent years as an influential approach for drug design and discovery in which molecules that are structurally related show similar pharmacological properties. It permits a purely mathematical description of the molecular structure so that in the development of identification of new drugs can be found through adequate topological indices. In this paper, we study the structural properties of the several antiviral drugs such as chloroquine, hydroxychloroquine, lopinavir, ritonavir, remdesivir, theaflavin, nafamostat, camostat, umifenovir and bevacizumab by considering the distance and bond measures of chemical compounds. Our quantitative values of the topological indices are extremely useful in the recent development of designing new drugs for COVID-19., (© 2021 Wiley Periodicals LLC.)

Overproduction of pro‑inflammatory cytokines in the aged, which is called inflammaging, leads to the deterioration of periodontitis. Toll‑like receptor 4 (TLR4) plays a role in the regulation of cellular senescence, and its expression increases with age. However, there has been limited research into the molecular mechanisms underlying the onset of periodontal inflammaging, and the interplay between TLR4 and inflammaging. In the present study, wild‑type and TLR4 gene knockout mice were used to investigate the activation of the TLR4 pathway in mouse periodontitis and the expression of the nucleotide‑binding and oligomerization domain‑like receptor 3 (NLRP3) inflammasome, an upstream immune checkpoint during the development of inflammaging. Activation of TLR4 in a mouse model of periodontitis enhanced the expression of a senescence‑associated secretory phenotype (SASP), which boosted the inflammaging process. Conversely, TLR4 activation downregulated the expression of B cell‑specific Moloney murine leukemia virus integration site 1 (Bmi‑1) and promoted the priming of NLRP3 inflammasome, both of which are regulators of SASP. Treating gingival fibroblasts with Bmi‑1 inhibitor PTC209, it was demonstrated that TLR4 activated the NLRP3 pathway and the inflammaging process by suppressing Bmi‑1. In addition, there was a significant reduction in the expression of Bmi‑1 expression in the gingiva of patients with periodontitis compared with healthy controls. In conclusion, the present study demonstrated that TLR4 acted by inhibiting Bmi‑1 to enhance the NLRP3 pathway and SASP factors. This cascade of reactions may contribute to the senescence of the periodontium.

Energies and spectrum of graphs associated to different linear operators play a significant role in molecular chemistry, polymerisation, pharmacy, computer networking and communication systems. In current article, we compute closed forms of signless Laplacian and Laplacian spectra and energies of multi-step wheel networks W n,m . These wheel networks are useful in networking and communication, as every node is one hoop neighbour to other. We also present our results for wheel graphs as particular cases. In the end, correlation of these energies on the involved parameters m ≥ 3 and n is given graphically. Present results are the natural generalizations of the already available results in the literature.

The universality of M-polynomial paves way towards establishing closed forms of many leading degree-based topological indices as it is done by Hosoya polynomial for distance-based indices. The study of topological indices is recently one of the most active research areas in chemical graph theory. The aim of this paper is to establish closed formulas for M-polynomials of Linear chains of benzene, napthalene, and anthracene graphs. From this polynomial we also compute as many as nine degree-based topological indices for these three chains. Our results will potentially play an important role in pharmacy, drug design, and many other applied areas of molecular sciences.

Nanoparticle (NP)-based hydrogels that can introduce synergistic advantages to the novel three-dimensional scaffold have garnered much attention recently. However, the application of NP-crosslinked hydrogels still remains challenging due to the complicated synthesis and/or modification of the NPs and the changed properties of the NPs after gelation. Herein, a novel palladium nanosheet (Pd NS)-based hydrogel (Pd Gel) with Pd NSs as crosslinkers was obtained by simply mixing Pd NSs with thiol-terminated four-arm polyethylene glycol (4arm-PEG-thiol). It was found that the formed Pd Gel was injectable, possibly due to the dynamic Pd-S bonds formed between Pd NSs and 4arm-PEG-thiol. In addition, compared with free Pd NSs, the Pd NSs within the hydrogel exhibited a significantly higher stability. We have further demonstrated that the formed hydrogel could encapsulate the commonly used anticancer drug doxorubicin (DOX) to form DOX@Pd Gel for combined chemo-photothermal therapy. Particularly, Pd NSs with a high absorption in the near-infrared (NIR) region could convert the energy of NIR laser into heat with a high efficiency, which is beneficial for photothermal therapy. Moreover, DOX@Pd Gel could maintain a sustainable release of DOX and the NIR laser irradiation could accelerate this drug release process. Then, the explosively released DOX and the hyperthermia generated from Pd NSs under NIR laser irradiation acted in a synergistic way to realize the combined therapeutic effect of the chemo-photothermal treatment. Finally, the in vivo anticancer effect and safety of the combined therapy were also verified by the tumor-bearing mouse model. Taken together, this work constructs a NP-crosslinked, NIR laser-activatable and injectable photothermal hydrogel via dynamic Pd-S bonding, and demonstrates that the hydrogel allows us to release DOX more precisely, eliminate tumor more effectively and inhibit tumor metastasis more persistently, which will advance the development of novel anticancer strategies.

Emerging nanotechnologies for radiotherapy are attracting increasing interest from researchers in recent years. To improve the radiotherapeutic performance, developing nanoparticles that can efficiently generate toxic reactive oxygen species (ROS) under X-ray irradiation are highly desirable. Here, we investigate the potential of copper oxide nanoparticles (CuO NPs) as nanoradiosensitizers. Increased cancer cell inhibition is observed in colony formation assay and real-time cell analysis after the combined treatment with CuO NPs and X-ray irradiation, whereas the CuO NPs alone do not have any negative influence on cell viability, indicating the radiosensitization effect of CuO NPs. Importantly, the significantly increased ROS level in cells contributes to the enhanced damage to cancer cells under the combined treatment. Besides, the cell cycle is regulated to the X-ray-sensitive phase (G 2 /M phase) by CuO NPs, which may also account for the inhibited proliferation of cancer cells. Furthermore, results from Western blot analysis and colony formation assay reveal that the increased cell death may be mainly attributed to the excessive autophagy induced by both CuO NPs and X-ray irradiation. Moreover, in vivo experiments verify the radiosensitization of CuO NPs and their favorable biosafety. The current study suggests that CuO NPs can be utilized as nanoradiosensitizers for increasing the efficiency of cancer radiotherapy.

Background and Purpose: Stable angina pectoris is a common symptom imperiling patients' life quality. The purpose of this meta-analysis is to assess the effectiveness of acupuncture alone or acupuncture plus medicine for the treatment of stable angina pectoris., Methods: Seven databases were searched ranging from 1959 to February 2018. Quantitative analysis of randomized controlled trials (RCTs) was performed by RevMan 5.3 software and STATA 12.0 program, and Cochrane criteria for risk-of-bias was used to assess the methodological quality of the trials., Results: A total of 12 RCTs involving 974 patients were enrolled in this study. The pooled results showed that both acupuncture group (RR: 0.35, P < 0.00001; RR: 0.49, P < 0.00001) and acupuncture plus medicine group (RR: 0.26, P < 0.00001; RR: 0.52, P = 0.03) were associated with a higher percentage of improved anginal symptoms as well as electrocardiographic (ECG) results compared to medicine group. The acupuncture plus medicine group also had a lower intake rate of nitroglycerin than medicine group (Non-event RR: 0.79, P = 0.03). However, there was no significant difference in the reduction or discontinuation of nitroglycerin intake between acupuncture group and medicine group. No acupuncture-related adverse effects were observed or reported in the included trials., Conclusion: Acupuncture therapy may improve anginal symptoms and ECG results in patients with stable angina pectoris, and can serve as an adjunctive treatment for this condition., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Eight new triterpenoid saponins, including four ursane-type saponins, ilexchinenosides J-M (1-4), and four oleanane-type saponins, ilexchinenosides N-Q (5-8), along with three known triterpenoid saponins (9-11) were isolated from the leaves of Ilex chinensis Sims. Their structures were established by 1D, 2D NMR and MS spectroscopic analyses and through comparisons with known compounds. Moreover, compounds 1, 3, 5, 7-9 and 11 exhibited significant levels of hepatoprotective activity against N-acetyl-p-aminophenol (APAP)-induced HepG2 cell damage in in vitro assays while compound 10 had moderately inhibitory effects on the NO production of lipopolysaccharide (LPS)-induced murine macrophages., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The Cartesian product and join are two classical operations in graphs. Let dL(G)(e) be the degree of a vertex e in line graph L(G) of a graph G. The edge versions of atom-bond connectivity (ABCe) and geometric arithmetic (GAe) indices of G are defined as ∑ef∈E(L(G))dL(G)(e)+dL(G)(f)-2dL(G)(e)×dL(G)(f) and ∑ef∈E(L(G))2dL(G)(e)×dL(G)(f)dL(G)(e)+dL(G)(f), respectively. In this paper, ABCe and GAe indices for certain Cartesian product graphs (such as Pn□Pm, Pn□Cm and Pn□Sm) are obtained. In addition, ABCe and GAe indices of certain join graphs (such as Cm+Pn+Sr, Pm+Pn+Pr, Cm+Cn+Cr and Sm+Sn+Sr) are deduced. Our results enrich and revise some known results.

In recent years, the discovery of suitable catalyst to oxidation of sulfur monoxide (SO) in normal temperature is a major concern in the industry. In this study, in first step; the boron nitride nanocone (BNNC) with Ge were doped and the surface of Ge-BNNC by using of the O2 molecule were activated. In second step; oxidation of SO on surface of Ge-BNNC through the Langmuir Hinshelwood (LH) and Eley Rideal (ER) mechanisms was investigated. Calculated data reveal that surface of O2-Ge-BNNC oxide the SO molecule with Ge-BNNC-O-O* + SO → Ge-BNNC-O-O*-SO → Ge-BNNC-O* + SO2 and Ge-BNNC-O* + SO → Ge-BNNC + SO2 reactions. It can be concluded, the energy barrier of LH mechanism to oxidation of SO on Ge-BNNC is lower than ER mechanism. Finally, the Ge-BNNC is acceptable catalyst with low price and high performance to oxidation of SO in normal temperature.

Eleven previously undescribed compounds including two triterpenes, ilexchinenin A and ilexchinenin B, and nine triterpenoid saponins, ilexchinenosides A-I, along with twelve known triterpenoids were isolated from the leaves of Ilex chinensis Sims (Aquifoliaceae). Their structures were elucidated by spectroscopic analysis and comparison with known compounds. Furthermore, eight compounds exhibited significant inhibitory effects on NO production of lipopolysaccharide (LPS)-induced murine macrophages, while nine compounds exhibited potent hepatoprotective activity against N-acetyl-p-aminophenol (APAP)-induced HepG2 cell damage in in vitro assays., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Long noncoding RNAs (lncRNAs) are a new class of cancer regulators. Here, we aimed to investigate the diagnostic and therapeutic values of an lncRNA, differentiation antagonizing noncoding RNA (DANCR), in lung cancer., Methods: Real-time polymerase chain reaction was used to compare DANCR levels in normal and cancerous lung tissues as well as lung cancer cells. Lentiviral transduction was used to induce DANCR overexpression or silencing in vitro, followed by monitoring cell proliferation, colony formation, and changes in microRNA-216a (miR-216a) expression. DANCR-specific small hairpin RNA transduction was used to establish cells with stable DANCR knockdown, and silenced cells were used to initiate lung tumor xenografts, followed by monitoring tumor growth., Results: DANCR upregulation was seen in lung cancer, particularly in high-grade lung cancer tissues and aggressive cancer cells. Ectopic DANCR expression induced lung cancer cell proliferation and colony formation, whereas DANCR silencing induced opposing effects. The miR-216a level in cancer cells was negatively correlated with DANCR expression. The DANCR knockdown reduced the growth of tumor xenografts in vivo., Conclusion: DANCR upregulation is a potential indicator of aggressive lung cancer. Silencing of DANCR has great potential as a potent therapeutic strategy in lung cancer.

Oesophageal cancer (OC) is one of the most fatal malignancies in the world, and chemoresistance restricts the therapeutic outcome of OC. Long noncoding RNA (lncRNA) was reported to play roles in multiple cancer types. Yet, the function of lncRNA in chemoresistance of OC has not been reported. A lncRNA gene, PCAT-1, showed higher expression in OC tissues, especially higher in secondary OC compared with normal mucosa tissues. Overexpression of PCAT-1 increased the proliferation rate and growth of OC cells. Inhibition of PCAT-1 decreased proliferation and growth of OC cells, and increased cisplatin chemosensitivity. In a mouse OC xenograft model, PCAT-1 inhibition repressed OC growth in vivo. Therefore, PCAT-1 may potentially serve as a therapeutic target for treating OC. PCAT-1 promotes development of OC and represses the chemoresistance of OC to cisplatin, and silencing of PCAT-1 may be a therapeutic strategy for treating OC., (Copyright © 2018 John Wiley & Sons, Ltd.)

Let G be a connected graph of order n with Laplacian eigenvalues [Formula: see text]. The Laplacian-energy-like invariant of G, is defined as [Formula: see text]. In this paper, we investigate the asymptotic behavior of the 3.6.24 lattice in terms of Laplacian-energy-like invariant as m, n approach infinity. Additionally, we derive that [Formula: see text], [Formula: see text] and [Formula: see text] have the same asymptotic Laplacian-energy-like invariants.

This paper mainly studies the Laplacian-energy-like invariants of the modified hexagonal lattice, modified Union Jack lattice, and honeycomb lattice. By utilizing the tensor product of matrices and the diagonalization of block circulant matrices, we derive closed-form formulas expressing the Laplacian-energy-like invariants of these lattices. In addition, we obtain explicit asymptotic values of these invariants with software-aided computations of some integrals.

This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost.

Global asymptotic stability and synchronization of a class of fractional-order memristor-based delayed neural networks are investigated. For such problems in integer-order systems, Lyapunov-Krasovskii functional is usually constructed, whereas similar method has not been well developed for fractional-order nonlinear delayed systems. By employing a comparison theorem for a class of fractional-order linear systems with time delay, sufficient condition for global asymptotic stability of fractional memristor-based delayed neural networks is derived. Then, based on linear error feedback control, the synchronization criterion for such neural networks is also presented. Numerical simulations are given to demonstrate the effectiveness of the theoretical results., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Twelve hydrolyzable tannins were obtained from the twigs of Myricaria bracteata, including two new hellinoyl-type dimers, bracteatinins D1 (1) and D2 (2); a new hellinoyl-type trimer, bracteatinin T1 (3); two known monomers, nilotinin M4 (4) and 1,3-di-O-galloyl-4,6-O-(aS)-hexahydroxydiphenoyl-β-d-glucose (5); six known dimers, tamarixinin A (6), nilotinin D8 (7), hirtellins A (10), B (9), and E (8), and isohirtellin C (11); and a known trimer, hirtellin T3 (12). The structures of the tannins were elucidated by spectroscopic data analysis and comparisons to known tannins. All compounds were evaluated as free radical scavengers using 1,1-diphenyl-2-picrylhydrazyl and hydroxy radicals and compared to the activity of BHT and Trolox. Compound 6 showed a significant anti-inflammatory effect on croton oil-induced ear edema in mice (200 mg/kg, inhibition rate 69.8%) and on collagen-induced arthritis in DBA/1 mice (20 mg/kg, inhibition rate 46.0% at day 57).

Mutations in epidermal growth factor receptor (EGFR) rendering it constitutively active is one of the major causes for metastatic non-small-cell lung cancer (NSCLC), and EGFR-targeted therapies utilizing tyrosine kinase inhibitors (TKIs) are often used clinically as the first-line treatment. But approximately half of NSCLC patients develop resistance to these therapies, where the MET proto-oncogene is amplified by EGFR through the hypoxia-inducible factor (HIF)-1α. Here we report that endothelial PAS domain-containing protein 1 (EPAS1), with 48% sequence identity to HIF-1α, specifically binds to TKI-resistant T790M EGFR, but not to wild-type EGFR, in NSCLC cell lines. Expression of EPAS1 enhances amplification of MET when simultaneously expressed with T790M EGFR but not with wild-type EGFR, and this enhancement is independent of ligand binding domain of EGFR. MET amplification requires EPAS1, since EPAS1 knock-down reduced MET levels. When NSCLC cells expressing T790M EGFR were treated with TKIs, reduced EPAS1 levels significantly enhanced the drug effect, whereas over-expression of EPAS1 increased the drug resistant effect. This EPAS1-dependent TKI-resistance was abolished by knocking-down MET, suggesting that EPAS1 does not cause TKI-resistance itself but functions to bridge EGFR and MET interactions. Our findings suggest that EPAS1 is a key factor in the EGFR-MET crosstalk in conferring TKI-resistance in NSCLC cases, and could be used as a potential therapeutic target in TKI-resistant NSCLC patients.

Cardiac troponin I (cTnI) is the only sarcomeric protein identified to date that is expressed exclusively in cardiac muscle. Its expression in cancer tissues has not been reported. Herein, we examined cTnI expression in non-small cell lung cancer (NSCLC) tissues, human adenocarcinoma cells SPCA-1 (lung) and BGC 823 (gastric) by immunohistochemistry, western blot analysis and real-time PCR. Immunopositivity for cTnI was demonstrated in 69.4% (34/49) NSCLC tissues evaluated, and was strong intensity in 35.3% (6/17) lung squamous cell carcinoma cases. The non-cancer-bearing lung tissues except tuberculosis (9/9, 100%) showed negative staining for cTnI. Seven monoclonal antibodies (mAbs) against human cTnI were applied in immunofluorescence. The result showed that the staining pattern within SPCA-1 and BGC 823 was dependent on the epitope of the cTnI mAbs. The membrane and nucleus of cancer cells were stained by mAbs against N-terminal peptides of cTnI, and cytoplasm was stained by mAbs against the middle and C-terminal peptides of cTnI. A ~25 kD band was identified by anti-cTnI mAb in SPCA-1 and BGC 823 extracts by western blot, as well as in cardiomyocyte extracts. The cTnI mRNA expressions in SPCA-1 and BGC 823 cells were about ten thousand times less than that in cardiomyocytes. Our study shows for the first time that cTnI protein and mRNA were abnormally expressed in NSCLC tissues, SPCA-1 and BGC 823 cells. These findings challenge the conventional view of cTnI as a cardiac-specific protein, enabling the potential use of cTnI as a diagnostic marker or targeted therapy for cancer.