Co-Loan Network of Chinese Banking System Based on Listed Companies’ Loan Data

Based on the loan data of Chinese listed companies from 2008 to 2016, this paper constructs a co-loan network of the Chinese banking system and analyzes the topological structures and corresponding evolvement characteristics from the perspective of complex network. Through the empirical studies, we find that the co-loan network always displays a core-periphery structure; for example, ten banks including four state banks and six large commercial banks are always in the core region of the Chinese banking system for nine consecutive years. Furthermore, the co-loan network is a small-world network lasting for nine years

Crop pest image classification based on improved densely connected convolutional network

IntroductionCrop pests have a great impact on the quality and yield of crops. The use of deep learning for the identification of crop pests is important for crop precise management.MethodsTo address the lack of data set and poor classification accuracy in current pest research, a large-scale pest data set named HQIP102 is built and the pest identification model named MADN is proposed. There are some problems with the IP102 large crop pest dataset, such as some pest categories are wrong and pest subjects are missing from the images. In this study, the IP102 data set was carefully filtered to obtain the HQIP102 data set, which contains 47,393 images of 102 pest classes on eight crops. The MADN model improves the representation capability of DenseNet in three aspects. Firstly, the Selective Kernel unit is introduced into the DenseNet model, which can adaptively adjust the size of the receptive field according to the input and capture target objects of different sizes more effectively. Secondly, in order to make the features obey a stable distribution, the Representative Batch Normalization module is used in the DenseNet model. In addition, adaptive selection of whether to activate neurons can improve the performance of the network, for which the ACON activation function is used in the DenseNet model. Finally, the MADN model is constituted by ensemble learning.ResultsExperimental results show that MADN achieved an accuracy and F1Score of 75.28% and 65.46% on the HQIP102 data set, an improvement of 5.17 percentage points and 5.20 percentage points compared to the pre-improvement DenseNet-121. Compared with ResNet-101, the accuracy and F1Score of MADN model improved by 10.48 percentage points and 10.56 percentage points, while the parameters size decreased by 35.37%. Deploying models to cloud servers with mobile application provides help in securing crop yield and quality

Knockdown of PKM2 enhances radiosensitivity of cervical cancer cells

Abstract Background Pyruvate kinase isozyme type M2 (PKM2) catalyzes the final step in glycolysis and has been found to be up-regulated in multiple human malignancies. However, whether PKM2 regulates the radiosensitivity of human cervical cancer (CC) remains unknown. Methods The expression of PKM2 in 94 patients with CC in the complete response (CR) and noncomplete response (nCR) groups, was evaluated by immunohistochemistry. The effect of PKM2 inhibition on radiosensitivity, the cell cycle, DNA damage, and apoptosis was evaluated by immunofluorescence analysis, colony formation assay, flow cytometry analysis and Western blotting. Results PKM2 expression was more highly expressed in the nCR group than that in CR group and PKM2 expression was enhanced in CC cells after ionizing radiation (IR). In addition, knockdown of PKM2 combined with IR significantly reduced cell growth, promoted apoptosis, and enhanced radiosensitivity. Additionally, knockdown of PKM2 with IR resulted in increased phosphorylation of DNA repair checkpoint proteins (ATM) and phosphorylated-H2AX. Moreover, knockdown of PKM2 combined with IR significantly increased the expression of cleaved caspase 3 and caspase 9, whereas Bcl2 expression was suppressed. Furthermore, knockdown of PKM2 combined with IR markedly reduced the expression of several cancer stem cell biomarkers in vitro, including NANOG, OCT4, SOX2, and Bmi1. Conclusions The results of our study suggests that PKM2 might be involved in mediating CC radiosensitivity and is identified as a potentially important target to enhance radiosensitivity in patients with CC

The interaction of macrophages and CD8 T cells in bronchoalveolar lavage fluid is associated with latent tuberculosis infection

ABSTRACTMycobacterium tuberculosis (Mtb) infection, including active tuberculosis (TB) and latent Mtb infection (LTBI), leads to diverse outcomes owing to different host immune responses. However, the immune mechanisms that govern the progression from LTBI to TB remain poorly defined in humans. Here, we profiled the lung immune cell populations within the bronchoalveolar lavage fluid (BALF) from patients with LTBI or TB using single-cell RNA sequencing (scRNA-seq). We found that Mtb infection substantially changed the immune cell compartments in the BALF, especially for the three subsets of macrophages, monocyte macrophage (MM)-CCL23, MM-FCN1, and MM-SPP1, which were found to be associated with the disease status of TB infection. Notably, MM-CCL23 cells derived from monocytes after stimulation with Mtb were characterized by high levels of chemokine (CCL23 and CXCL5) production and might serve as a marker for Mtb infection. The MM-CCL23 population mainly recruited CD8-CCR6 T cells through CCL20/CCR6, which was a prominent feature associated with protection immunity in LTBI. This study improves our understanding of the lung immune landscape during Mtb infection, which may inform future vaccine design for protective immunity

Isoreticular Contraction of Cage-like Metal–Organic Frameworks with Optimized Pore Space for Enhanced C₂H₂/CO₂ and C₂H₂/C₂H₄ Separations

The C2H2 separation from CO2 and C2H4 is of great importance yet highly challenging in the petrochemical industry, owing to their similar physical and chemical properties. Herein, the pore nanospace engineering of cage-like mixed-ligand MFOF-1 has been accomplished via contracting the size of the pyridine- and carboxylic acid-functionalized linkers and introducing a fluoride- and sulfate-bridging cobalt cluster, based on a reticular chemistry strategy. Compared with the prototypical MFOF-1, the constructed FJUT-1 with the same topology presents significantly improved C2H2 adsorption capacity, and selective C2H2 separation performance due to the reduced cage cavity size, functionalized pore surface, and appropriate pore volume. The introduction of fluoride- and sulfate-bridging cubane-type tetranuclear cobalt clusters bestows FJUT-1 with exceptional chemical stability under harsh conditions while providing multiple potential C2H2 binding sites, thus rendering the adequate ability for practical C2H2 separation application as confirmed by the dynamic breakthrough experiments under dry and humid conditions. Additionally, the distinct binding mechanism is suggested by theoretical calculations in which the multiple supramolecular interactions involving C–H···O, C–H···F, and other van der Waals forces play a critical role in the selective C2H2 separation