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Among the identified thousands of circular RNAs (circRNA) in humans and animals, Cdr1as (also known as CiRS-7 ) was recently demonstrated to act as a powerful miR-7 sponge/inhibitor in developing midbrain of zebrafish, suggesting a novel mechanism for regulating microRNA functions. MiR-7 is abundantly expressed in islet cells, but overexpressing miR-7 in transgenic mouse β cells causes diabetes. Therefore, we infer that Cdr1as expression may inhibit miR-7 function in islet cells, which in turn improves insulin secretion. Here, we show the first characterization of Cdr1as expression in islet cells, which was upregulated by long-term forskolin and PMA stimulation, but not high glucose, indicating the involvement of cAMP and PKC pathways. Remarkably, both insulin content and secretion were significantly increased by overexpression of Cdr1as in islet cells. We further identified a new target Myrip in the Cdr1as /miR-7 pathway that regulates insulin granule secretion and also another target Pax6 that enhances insulin transcription. Taken together, our findings revealed the effects of the strongly interacting pair of Cdr1as /miR-7 on insulin secretion, which may become a new target for improving β cell function in diabetes.

With the deepening of a new round of technological revolution and industrial reform, digital technology has been continuously innovated and widely penetrated into various economic fields. The digital economy (DE) is gradually becoming the focus of China’s economic development planning and a new engine to enhance national strength. Evaluating the development level of DE in various regions is conducive to timely discover the shortcomings in China’s DE development, as well as provide an important basis for putting forward corresponding policy suggestions. This investigation established a hybrid multi-criteria decision making (MCDM) model for evaluating DE development of 31 provincial level regions in China ranging from 2015 to 2020. Firstly, the evaluation indicator system is established from digital infrastructure, integrated development, social benefits, innovation ability, and electronic-commerce dimensions containing 17 quantitative sub-criteria based on Fuzzy-Delphi method. Secondly, integrated weights of 17 sub-criteria from 2015 to 2020 are computed in terms of objective weights calculated by the anti-entropy weight (AEW) approach from 2015 to 2020 and subjective weights obtained via the best-worst method (BWM). Thirdly, MARCOS model is applied to evaluate the DE development degree of various regions in China ranging from 2015 to 2020. Case analysis illustrates that the DE development of Guangdong, Jiangsu, Zhejiang, and Beijing always maintain in the top four from 2015 to 2020, while the southwest and northwest regions in China are obviously fall behind others. And the DE development degree of various regions is primarily affected under the integrated development performance, innovation ability performance, and social benefits performance. Therefore, the backward regions should emphasize the development of software industry and information technology industry. The robustness of the proposed MCDM model combining Fuzzy-Delphi, AEW, BWM and MARCOS is discussed employing three similarity coefficients of rankings. And it is verified that the proposed MCDM model has superior robustness and validity in evaluating DE development.

Taking the quantum electrodynamics (QED) effect into account, we investigate the geometrical-optics appearance of the Euler–Heisenberg (EH) black hole (BH) under the different accretion flows context, which depends on the BH space-time structure and different sources of light. The more significant magnetic charge leads to the smaller shadow radius for the EH BH, while the different values of the EH parameter do not ruin it. Different features of the corresponding two-dimensional shadow images are derived for the three optically thin accretion flow models. It is shown that the total observed intensity in the static spherical accretion flow scenario leads than that of the infalling spherical accretion flow under same parameters, but the size and position of the EH BH shadows do not change in both of these accretions flows, implying that the BH shadow size depends on the geometric space-time and the shadows luminosities rely on the accretion flow morphology. Of particular interest is that a thin disk accretion model illuminated the BH, we found that the contribution of the lensing ring to the total observed flux is less than 5%, and the photon ring is less than 2%, indicating that the direct emission dominates the optical appearance of the EH BH. It is also believed that the optical appearance of the BH image depends on the accretion disk radiation position in this scenario, which can serve as a probe for the disk structure around the active galactic nucleus (AGN) of M87∗ like.

At the aim of solving the increasing conflicts among the economic growth, resource shortage, and environmental aggravation, the eco-industrial park becomes a significant research issue to achieve sustainable development and circular economy. Therefore, evaluating the comprehensive benefit of eco-industrial parks and providing references and policy formulation in supporting the improvement of construction and management level for eco-industrial parks are of great significance. In this paper, a hybrid framework was proposed to assess the comprehensive benefit of eco-industrial parks in terms of circular economy and sustainability. Firstly, the evaluation index system was constructed by using grey-Delphi method, which included economic benefit criteria, social benefit criteria, and environmental benefit criteria with nine quantitative sub-criteria and four qualitative sub-criteria. Then, a new comparison-based method, namely the best-worst method, was employed to determine the weights of all sub-criteria and the performance values of all selected eco-industrial parks with respect to the qualitative sub-criteria. Finally, five selected representative eco-industrial parks in China were ranked in terms of comprehensive benefit, and the optimal eco-industrial park was selected. According to the results of comprehensive benefit evaluation for eco-industrial parks, the strengths and weaknesses of each eco-industrial park were obvious. At the end, the recommendations for the effective and rapid development of eco-industrial parks were formulated.

Extensive microbial interactions occur within insect hosts. However, the interactions between the Huanglongbing (HLB) pathogen and endosymbiotic bacteria within the Asian citrus psyllid (ACP, Diaphorina citri Kuwayama) in wild populations remain elusive. Thus, this study aimed to detect the infection rates of HLB in the ACP across five localities in China, with a widespread prevalence in Ruijin (RJ, 58%), Huidong (HD, 28%), and Lingui (LG, 15%) populations. Next, microbial communities of RJ and LG populations collected from citrus were analyzed via 16S rRNA amplicon sequencing. The results revealed a markedly higher microbial diversity in the RJ population compared to the LG population. Moreover, the PCoA analysis identified significant differences in microbial communities between the two populations. Considering that the inter-population differences of Bray–Curtis dissimilarity in the RJ population exceeded those between populations, separate analyses were performed. Our findings indicated an increased abundance of Enterobacteriaceae in individuals infected with HLB in both populations. Random forest analysis also identified Enterobacteriaceae as a crucial indicator of HLB infection. Furthermore, the phylogenetic analysis suggested a potential regulatory role of ASV4017 in Enterobacteriaceae for ACP, suggesting its possible attractant activity. This research contributes to expanding the understanding of microbial communities associated with HLB infection, holding significant implications for HLB prevention and treatment.

With the increasing development of renewable resources-based electricity generation and the construction of wind-photovoltaic-energy storage combination exemplary projects, the intermittent and fluctuating nature of renewable resources exert great challenges for the power grid to supply electricity reliably and stably. An energy storage system (ESS) is deemed to be the most valid solution to deal with these challenges. Considering the various types of ESSs, it is necessary to develop a comprehensive assessment framework for selecting appropriate energy storage techniques in establishing exemplary projects combining renewable resources-based electricity generation and an ESS. This paper proposes a multi-criteria decision making (MCDM) model combining a fuzzy-Delphi approach to establish the comprehensive assessment indicator system, the entropy weight determination method, and the best-worst method (BWM) to calculate weights of all sub-criteria, and a Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) comprehensive evaluation model to choose the optimal battery ESS. In accordance with the comprehensive evaluation results, the Li-ion battery is the optimal battery ESS to apply to wind-photovoltaic-energy storage combination exemplary projects. Based on the discussion on the comprehensive evaluation results, policy implications are suggested to improve the applicability of battery ESSs and provide some references for decision makers in related fields.

BackgroundAlthough anti-programmed cell death protein 1 (PD-1) immunotherapy is greatly effective in melanoma treatment, low response rate and treatment resistance significantly hinder its efficacy. Tumor cell ferroptosis triggered by interferon (IFN)-γ that is derived from tumor-infiltrating CD8+ T cells greatly contributes to the effect of immunotherapy. However, the molecular mechanism underlying IFN-γ-mediated ferroptosis and related potentially promising therapeutic strategy warrant further clarification. MicroRNAs (miRNAs) participate in ferroptosis execution and can be delivered systemically by multiple carriers, which have manifested obvious therapeutic effects on cancer.MethodsMiRNAs expression profile in IFN-γ-driven ferroptosis was obtained by RNA sequencing. Biochemical assays were used to clarify the role of miR-21-3p in IFN-γ-driven ferroptosis and the underlying mechanism. MiR-21-3p-loaded gold nanoparticles were constructed and systemically applied to analyze the role of miR-21-3p in anti-PD-1 immunotherapy in preclinical transplanted tumor model.ResultsMiRNAs expression profile of melanoma cells in IFN-γ-driven ferroptosis was first obtained. Then, upregulated miR-21-3p was proved to facilitate IFN-γ-mediated ferroptosis by potentiating lipid peroxidation. miR-21-3p increased the ferroptosis sensitivity by directly targeting thioredoxin reductase 1 (TXNRD1) to enhance lipid reactive oxygen species (ROS) generation. Furthermore, miR-21-3p overexpression in tumor synergized with anti-PD-1 antibody by promoting tumor cell ferroptosis. More importantly, miR-21-3p-loaded gold nanoparticles were constructed, and the systemic delivery of them increased the efficacy of anti-PD-1 antibody without prominent side effects in preclinical mice model. Ultimately, ATF3 was found to promote miR-21-3p transcription in IFN-γ-driven ferroptosis.ConclusionsMiR-21–3 p upregulation contributes to IFN-γ-driven ferroptosis and synergizes with anti-PD-1 antibody. Nanoparticle delivery of miR-21–3 p is a promising therapeutic approach to increase immunotherapy efficacy without obvious systemic side effects.

Melanoma is a type of skin cancer, which originates from the malignant transformation of epidermal melanocytes, with extremely high lethality. Ferroptosis has been documented to be highly related to cancer pathogenesis and the effect of immunotherapy. In addition, the dysregulation of lncRNAs is greatly implicated in melanoma progression and ferroptosis regulation. However, the significance of ferroptosis-related lncRNA in melanoma treatment and the prognosis of melanoma patients remains elusive. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis in the TCGA SKCM database, a cutaneous melanoma risk model was established based on differentially-expressed ferroptosis-related lncRNAs (DEfrlncRNAs). The nomogram, receiver operating characteristic (ROC) curves, and calibration plots were conducted to examine the predictive performance of this model. Sequentially, we continued to analyze the differences between the high- and low-risk groups, in terms of clinical characteristics, immune cell infiltration, immune-related functions, and chemotherapy drug sensitivity. Moreover, the expressions of DEfrlncRNAs, PD-L1, and CD8 were also examined by qRT-PCR and immunohistochemical staining in melanoma tissues to further confirm the potential clinical implication of DEfrlncRNAs in melanoma immunotherapy. 16 DEfrlncRNAs were identified, and a representative risk score for patient survival was constructed based on these 16 genes. The risk score was found to be an independent prognostic factor for the survival of melanoma patients. In addition, the low-risk group of patients had higher immune cell infiltration in the melanoma lesions, higher sensitivity to chemotherapeutic agents, and a better survival prognosis. Besides, the high expression of the identified 5 DEfrlncRNA in the low-risk group might suggest a higher possibility to benefit from immune checkpoint blockade therapy in the treatment of melanoma. The DEfrlncRNA risk prediction model related to ferroptosis genes can independently predict the prognosis of patients with melanoma and provide a basis for evaluating the response of clinical treatment in melanoma.

Sheath blight (ShB), caused by Rhizoctonia solani AG1-I, is one of the most important diseases in rice worldwide. The symptoms of ShB primarily develop on leaf sheaths and leaf blades. Hyperspectral remote sensing technology has the potential of rapid, efficient and accurate detection and monitoring of the occurrence and development of rice ShB and other crop diseases. This study evaluated the spectral responses of leaf blade fractions with different development stages of ShB symptoms to construct the spectral feature library of rice ShB based on “three-edge” parameters and narrow-band vegetation indices to identify the disease on the leaves. The spectral curves of leaf blade lesions have significant changes in the blue edge, green peak, yellow edge, red valley, red edge and near-infrared regions. The variables of the normalized index between green peak amplitude and red valley amplitude (Rg − Ro)/(Rg + Ro), the normalized index between the yellow edge area and blue edge area (SDy − SDb)/(SDy + SDb), the ratio index of green peak amplitude and red valley amplitude (Rg/Ro) and the nitrogen reflectance index (NRI) had high relevance to the disease. At the leaf scale, the importance weights of all attributes decreased with the effect of non-infected areas in a leaf by the ReliefF algorithm, with Rg/Ro being the indicator having the highest importance weight. Estimation rate of 95.5% was achieved in the decision tree classifier with the parameter of Rg/Ro. In addition, it was found that the variety degree of absorptive valley, reflection peak and reflecting steep slope was different in the blue edge, green and red edge regions, although there were similar spectral curve shapes between leaf sheath lesions and leaf blade lesions. The significant difference characteristic was the ratio index of the red edge area and green peak area (SDr/SDg) between them. These results can provide the basis for the development of a specific sensor or sensors system for detecting the ShB disease in rice.

Electricity market reform is in progress in China, and the operational performance of power grid enterprises are vital for its healthy and sustainable development in the current electricity market environment. In this paper, a hybrid multi-criteria decision-making (MCDM) framework for operational performance evaluation of a power grid enterprise is proposed from the perspective of sustainability. The latest MCDM method, namely the best-worst method (BWM) was employed to determine the weights of all criteria, and the technique for order preference by similarity to an ideal solution (TOPSIS) was applied to rank the operation performance of a power grid enterprise. The evaluation index system was built based on the concept of sustainability, which includes three criteria (namely economy, society, and environment) and seven sub-criteria. Four power grid enterprises were selected to perform the empirical analysis, and the results indicate that power grid enterprise A1 has the best operation performance. The proposed hybrid BWM-TOPSIS-based framework for operation performance evaluation of a power grid enterprise is effective and practical.