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We demonstrated a novel “donor–acceptor” strategy for boosting the aerobic visible-light photocatalytic C–H oxygenation of unactivated alkanes, through the protonation of anthraquinones by Brønsted acids.

Innovation is the primary driving force and important support for Northeast China’s revitalisation strategy to move toward ‘high-quality development’. Based on 1985–2016 data, this study aimed to e...

Background: Choroidal melanoma (CM) accounts for 70% of uveal melanomas and is prone to metastasize and invade. Previous studies have reported that forkhead box protein 3 (FOXP3) is associated with carcinogenesis, however, the effect of FOXP3 on CM remains unclear. The purpose of the study is to explore the role of FOXP3 in the progression of CM and to elucidate its related mechanisms. Methods: FOXP3 protein expression was detected in CM clinical specimens and CM cells. We then established a cell line with stable FOXP3 knockout as well as a cell line that transiently overexpressed FOXP3, and their transfection efficiencies were detected by Western blotting (WB). The effects of FOXP3 on cell biological functions and epithelial-mesenchymal transition (EMT) in CM were verified via the CCK-8 assay, monoclonal formation assay, migration and invasion assays, WB and tumorigenesis assay in nude mice in vivo. We also demontrated that FOXP3 promoted CM development through the Wnt5a/CaMKII signaling pathway. Results: The level of FOXP3 was found to be upregulated in CM clinical specimens and CM cells. The overexpression of FOXP3 promoted the proliferation, migration, invasion, and EMT process of CM cells in vitro, while the knockdown of FOXP3 inhibited these cell functions in vitro and tumor growth in vivo. In addition, FOXP3 was found promoting the progression of CM, including EMT, through the Wnt5a/CaMKII signaling pathway. Conclusion: This study demonstrated that FOXP3 promoted the development of choroidal melanoma through the Wnt5a/CaMKII signaling pathway as an oncogenic factor of CM, and thereby provides a novel potential target for the pathogenesis of CM.

Breast cancer (BC) ranks first in morbidity and mortality among female malignant tumors worldwide. This study is aimed at clarifying clinical value of contrast-enhanced ultrasound (CEUS) in the diagnosis and differentiation of BC. A total of 108 BC patients admitted to our hospital from January 2019 to December 2021 were enrolled. All patients underwent conventional color Doppler ultrasound and CEUS imaging examination. All ultrasound images were analyzed by a senior (5+ years) sonographer. The lesion location, echo, size, and color Doppler flow imaging (CDFI) blood flow distribution of benign and malignant BC were assessed. The transverse and longitudinal diameters of malignant BC presented significant elevation compared with the control group ( P < 0.05 ). CEUS is more reliable than conventional ultrasound in the differentiation of benign and malignant breast lesions, and CEUS has the best reliability. The comparison of CEUS observation indicators between benign and malignant groups demonstrated that CEUS enhancement patterns (time and intensity) and morphological features (lesion boundary, shape, range, homogeneity, and filling defect) presented statistical significance ( P < 0.01 ). Irregular shape and range expansion were high-specificity indicators (all >90.00%); fast-forward, high enhancement, clear boundary, and range expansion were high-sensitivity (all >90.00%); and fast-forward, high enhancement, and clear boundary were low-specificity indicators (all 80.00%). The area under curve of CEUS ( 0.735 ± 0.053 ) presented elevation relative to conventional ultrasound ( 0.901 ± 0.024 ), with statistical significance ( Z 1 = 2.462 , P < 0.05 ). Relative to conventional ultrasound, the specificity and positive predictive value of CEUS presented elevation ( P < 0.05 ). In conclusion, in the differentiation of benign and malignant breast lesions, CEUS has better diagnostic accuracy and reliability than conventional ultrasound. The diagnostic advantages of CEUS are to elevate the diagnostic specificity and positive predictive value and reduce the misdiagnosis rate.

This study aimed to explore the effects of knocking down both vascular endothelial growth factor (VEGF) and platelet derived growth factor (PDGF) on vasculogenic mimicry (VM) formation in choroidal melanoma (CM) cells.Cell counting Kit (CCK)-8, monoclonal formation, wound healing, transwell and flow cytometry assays were used to observe the cell effects in CM cell line, ocular choroidal melanoma-1 cells (OCM-1) with respect to proliferation, migration, invasion and apoptosis. Three-dimensional (3D) cultures were also used to characterize VM tube structural effects in OCM-1 cells and western blotting was used to characterize protein expression changes in VM-related markers.Dual VEGF/PDGF knockdown suppressed cell proliferation, migration and invasion, but promoted cell apoptosis. It also reduced VM tube structures in OCM-1 cells. VM associated markers including, VE-cadherin, EphA2 and MT1-MMP were also down-regulated in OCM-1 cells. Similarly, Wnt5a, β-catenin and phosphorylated-AKT levels were also down-regulated. Western blotting and 3D cultures further demonstrated that combined Wnt5a silencing with dual VEGF/PDGF knockdown significantly decreased VE-cadherin and EphA2 levels and reduced VM tube structures in OCM-1 cells.Dual VEGF/PDGF knockdown suppressed cell growth and metastasis in OCM-1 cells, and blocked the Wnt5a/β-catenin/AKT signaling pathway thereby inhibiting VM formation.

Angiogenesis and vasculogenic mimicry (VM) are considered to be the main processes to ensure tumor blood supply during the proliferation and metastasis of choroidal melanoma (CM). The traditional antimalarial drug artesunate (ART) has some potential anti-CM effects; however, the underlying mechanisms remain unclarified. Recent studies have shown that the Wnt5a/calmodulin-dependent kinase II (CaMKII) signaling pathway has a close correlation with angiogenesis and VM formation. This study demonstrated that ART eliminated VM formation by inhibiting the aforementioned signaling pathway in CM cells. The microvessel sprouting of the mouse aortic rings and the microvessel density of chicken chorioallantoic membrane (CAM) decreased significantly after ART treatment. VM formation assay and periodic acid schiff (PAS) staining revealed that ART inhibited VM formation in CM. Moreover, ART downregulated the expression levels of the angiogenesis-related proteins vascular endothelial growth factor receptor (VEGFR) 2, platelet-derived growth factor receptor (PDGFR) and vascular endothelial growth factor (VEGF) A, and VM-related proteins ephrin type-A receptor (EphA) 2 and vascular endothelial (VE)-cadherin. The expression of hypoxia-inducible factor (HIF)-1α, Wnt5a, and phosphorylated CaMKII was also downregulated after ART treatment. In addition, we further demonstrated that ART inhibited the proliferation, migration, and invasion of OCM-1 and C918 cells. Collectively, our results suggested that ART inhibited angiogenesis and VM formation of choroidal melanoma likely by regulating the Wnt5a/CaMKII signaling pathway. These findings further supported the feasibility of ART for cancer therapy.

We downloaded gene expression data, clinical data, and somatic mutation data of cervical squamous cell carcinoma (CSCC) patients from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Predictive lncRNAs were screened using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and risk scores were calculated for each patient according to the expression levels of lncRNAs and regression coefficients to establish a risk model that could be a novel signature. We assessed the correlation between immune infiltration status, chemotherapeutics sensitivity, immune checkpoint proteins (ICP), and the signature. Therefore, we selected 11 immune-related lncRNAs (WWC2,AS2, STXBP5.AS1, ERICH6.AS1, USP30.AS1, LINC02073, RBAKDN, IL21R.AS1, LINC02078, DLEU1, LINC00426, BOLA3.AS1) to construct the risk model. Patients who were in the high-risk group had a shorter survival time than those in the low-risk group (p 0.001). Risk scores in the signature were negatively correlated with macrophage M1, macrophage M2, and T cell CD8 + ; what's more, T cell CD8 + was higher in the low-risk group. The expression levels of ICP such as PD-L1, PD-1, CTLA-4, TIGIT, LAG-3, and TIM-3 were substantially higher in the low-risk group. For chemotherapeutic agents, high-risk scores were associated with higher half-inhibitory concentrations (IC50) of cisplatin. These findings suggested that the risk model can be a novel signature for predicting CSCC patients' prognosis, and it also can be used to formulate clinical treatment plans for CSCC patients.

How to promote and improve the level of urban innovation cooperation is a major issue in China’s current high-quality economic development. Thus, enhancing innovation ability is essential to achieving high-quality economic growth under the "new normal". Based on the data of Chinese invention patents from 1985 to 2017, this paper analyzes the characteristics of China’s urban innovation cooperation network and the different roles of proximity by using social network analysis and exploratory spatial data analysis methods. The analysis results show that: (1) On the whole, the development of China’s urban innovation cooperation network is characterized by stages (initial development stage, rapid development stage, and gradual decline stage); The urban innovation cooperation network has strong connectivity and centripetal concentration but its imbalance needs to be further improved; The degree of urban participation has gradually increased, consolidating the stability of the network structure. (2) The centrality of urban innovation cooperation network has obvious characteristics of administrative center orientation, coastal areas orientation, and ‘strong east and weak west’; Beijing is the center and bridge of the network, and the network flattening characteristics are obvious; A hierarchical ‘core-edge’ structure is gradually formed for the urban innovation cooperation network, and the pyramid structure with Beijing standing at the top is being consolidated. (3) The geographical proximity presents a significant global spatial positive correlation, while the network proximity and pure network proximity have a more significant global spatial negative correlation; The local spatial autocorrelation of China’s urban innovation cooperation system based on network proximity is more obvious and identifiable than that based on the geographical proximity, which better reflects the new development model of "relationship economy".

We study the problem of task offloading and resource allocation (TORA) in wireless networks, where mobile devices (MDs) with insufficient resources, e.g., energy and computing resources, can offload their computation tasks to other available MDs using device to device (D2D) communications. The TORA problem is formulated as a Mixed Integer Non-linear Programming (MINLP) problem, which aims at minimizing the overall overhead of task completion time and energy consumption. Since the problem is NP hard, it is very challenging to solve it using conventional methods with the number of MDs increasing. To address this issue, we first decouple the primal problem into (i) a resource allocation problem with fixed offloading decision, and (ii) a task offloading problem with an optimal-value function of resource allocation problem. Next, we address them with quasi-convex and convex optimization techniques, respectively. Finally, we design a TORA algorithm to solve the primal problem and obtain the solution of primal problem. Simulation results show that the proposed scheme can reduce the overall overhead.

In this paper, we study the computation offloading problem in a mobile ad hoc network (MANET) scenario, where the network nodes can cooperatively help each other to fulfill computation tasks, and the energy-harvesting technology is also considered to overcome possible energy-exhausted issues. To tradeoff energy-harvesting and consumption, the problem of task offloading and energy-harvesting is formulated as a stochastic time-average profit maximization problem, in which the objective is to achieve optimal values of offloading policy and the length of energy-harvesting phase at each time slot. Owing to the lack of future information, e.g., task arrival, link bandwidth and ability of energy-harvesting, an online task offloading algorithm based on Lyapunov optimization is developed, which can convent the primal problem into a drift-minus-profit infimum bound minimization problem. Simulation results show that the proposed approach achieves a near-optimal solution.

The sustainability and complexity of logistics networks come from the temporally and spatially uneven distributions of freight demand and supply. Operation strategies without considering the sustainability and complexity could dramatically increase the economic and environmental costs of logistics operations. This paper explores how the unevenly distributed demand and supply can be optimally matched through collaborations, and formulates and solves a Collaborative Pickup and Delivery Problem under Time Windows (CPDPTW) to optimize the structures of logistics networks and improve city sustainability and liverability. The CPDPTW is a three-stage framework. First, a multi-objective linear optimization model that minimizes the number of vehicles and the total cost of logistics operation is developed. Second, a composite algorithm consisting of improved k-means clustering, Demand-and-Time-based Dijkstra Algorithm (DTDA) and Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is devised to solve the optimization model. The clustering algorithm helps to identify the feasible initial solution to INSGA-II. Third, a method based on improved Shapley value model is proposed to obtain the collaborative alliance strategy that achieves the optimal profit allocation strategy. The proposed composite algorithm outperforms existing algorithms in minimizing terms of the total cost and number of electro-tricycles. An empirical case of Chongqing is employed to demonstrate the efficiency of the proposed mechanism for achieving optimality for logistics networks and realizing a win-win situation between suppliers and consumers.

In this work, we fabricated the ternary bulk hetero junction (BHJ) polymer solar cells (PSCs) by doping a phosphorescent small molecule bis[2-(4-tertbutylphenyl)benzothiazolato-N,C2′] iridium(acetylacetonate)[(tbt)2Ir(acac)] into the conventional active layer of poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C71-butyric acid methyl ester (PC71BM). After doping (tbt)2Ir(acac), the short circuit current and fill factor are simultaneously enhanced compared with binary device and the power conversion efficiency (PCE) of P3HT:PC71BM based ternary devices is improved from 2.99% to 4.14%. More excellent photovoltaic performance of ternary PSCs is mainly attributed to enhanced charge transportation by appropriate energy cascade alignment and enhanced exciton harvesting by Foerster resonance energy transfer from (tbt)2Ir(acac) to P3HT.

In this study, we report the ternary organic solar cells by doping a thermally activated delayed fluorescence (TADF) material (4 s ,6 s )-2,4,5,6-tetra( 9H -carbazol-9-yl) isophthalonitrile (4CzIPN) in the binary poly(3-hexylthiophene) (P3HT) :[6,6]-phenyl-C71-butyric acid methyl ester (PC71BM) blends. Given the complementary absorption with P3HT, 4CzIPN was doped into (P3HT:PC71BM)-based binary blends, and ternary OSCs were developed, The ternary OSCs with 1.0 wt% of 4CzIPN displayed better phase separation of active layer, thus leading to an impressive efficiency of 3.94 % with open-circuit voltage of 0.54 V, short-circuit density of 11.58 mA/cm-2 and fill factor of 63.32%.

Collaboration among logistics facilities in a multicenter logistics delivery network can significantly improve the utilization of logistics resources through resource sharing including logistics facilities, vehicles, and customer services. This study proposes and tests different resource sharing schemes to solve the optimization problem of a collaborative multicenter logistics delivery network based on resource sharing (CMCLDN-RS). The CMCLDN-RS problem aims to establish a collaborative mechanism of allocating logistics resources in a manner that improves the operational efficiency of a logistics network. A bi-objective optimization model is proposed with consideration of various resource sharing schemes in multiple service periods to minimize the total cost and number of vehicles. An adaptive grid particle swarm optimization (AGPSO) algorithm based on customer clustering is devised to solve the CMCLDN-RS problem and find Pareto optimal solutions. An effective elite iteration and selective endowment mechanism is designed for the algorithm to combine global and local search to improve search capabilities. The solution of CMCLDN-RS guarantees that cost savings are fairly allocated to the collaborative participants through a suitable profit allocation model. Compared with the computation performance of the existing nondominated sorting genetic algorithm-II and multi-objective evolutionary algorithm, AGPSO is more computationally efficient. An empirical case study in Chengdu, China suggests that the proposed collaborative mechanism with resource sharing can effectively reduce total operational costs and number of vehicles, thereby enhancing the operational efficiency of the logistics network.

Background Cervical squamous cell carcinoma (CESC) is one of the most common malignancies associated with mortality in females. Its onset and prognosis are primarily concerned with persistent infection with high-risk types of human papillomavirus (HPV). However, the molecular mechanisms of HPV-positive CESC remain unclear. Methods In this study, we conducted a high-throughput sequencing to identify differentially expressed miRNAs (DEMs). Besides, three series were selected from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Then the miRNA-TF-gene regulatory network was constructed using bioinformatic methods. Genes in the network were performed functional enrichment analysis and protein-protein interaction (PPI) network analysis. Ultimately, the expression levels of six key miRNAs, TFs, and mRNAs were validated by 20 HPV-positive CESC tissues and 15 normal cervical samples. Results A total of 52 DEMs and 300 DEGs differed between the HPV-positive CESC and normal cervical samples. Then the miRNA-TF-gene regulatory network was constructed consisting of 22 miRNAs, 6 TFs, and 76 corresponding genes, among which miR-149-5p, miRNA-1248 and E2F4 acted as key regulators. PPI network analysis showed that ten genes including TOP2A, AURKA, CHEK1, KIF11, MCM4, MKI67, DTL, FOXM1, SMC4, and FBXO5 were recognized as hub genes with the highest connectivity degrees. Besides, five key molecules miRNA-149-5p, E2F4, KIF11, DTL, and SMC4 were suggested to play crucial roles in the development of HPV-positive CESC. Conclusion These results present a unique insight into the pathological mechanisms of HPV-positive CESC and possibly provides potential therapeutic targets.

Collaboration among service providers in a logistics network can greatly increase their operation efficiencies and reduce transportation emissions. This study proposes, formulates and solves a collaborative two-echelon multicenter vehicle routing problem based on a state–space–time (CTMCVRP-SST) network to facilitate collaboration and resource sharing in a multiperiod state–space–time (SST) logistics network. The CTMCVRP-SST aims to facilitate collaboration in logistics networks by leveraging the spatial-temporal properties of logistics demands and resources to optimize the distribution of logistics resources in space and time to meet logistics demands. A three-component solution framework is proposed to solve CTMCVRP-SST. First, a bi-objective linear programming model based on resource sharing in a multiperiod SST network is formulated to minimize the number of vehicles and the total cost of the collaborative operation. Second, an integrated algorithm consisting of SST-based dynamic programming (DP), improved K-means clustering and improved non-dominated sorting genetic algorithm-II (Im-NSGAII) is developed to obtain optimal routes. Third, a cost gap allocation model is employed to design a collaborative mechanism that encourages cooperation among logistics service providers. Using this solution framework, the coalition sequences (i.e., the order of each logistics provider joining a collaborative coalition) are designed and the stability of the coalitions based on profit allocations is studied. Results show that the proposed algorithm outperforms existing algorithms in minimizing the total cost with all other constraints being the same. An empirical case study of a logistics network in Chongqing suggests that the proposed collaboration mechanism with SST network representation can reduce costs, improve transportation efficiency, and contribute to efficient and sustainable logistics network operations.