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Background: Epstein-Barr virus (EBV) is widely infected in humans and causes various diseases. Among them, microRNAs of EBV play a key role in the progression of EBV-associated febrile diseases. There're few specific indicators for rapid differential diagnosis of various febrile diseases associated with EBV, and the lack of more reliable screening methods with high diagnostic utility has led to spaces for improvement in the accurate diagnosis and efficient treatment of relevant patients, making EBV infection a complicated clinical problem. With recent advances in plasma microRNA testing, the apparent presence of EBV microRNAs in plasma can help screen for EBV infection. The gene networks targeted by these microRNAs can also indicate potential biomarkers of EBV-associated febrile diseases. This study aimed to identify some novel miRNAs as potential biomarkers for early diagnosis of respectively EBV-associated febrile diseases. Materials and methods: A total of 110 participants were recruited for this task. First, we performed high-throughput sequencing and preliminary PCR validation of differentially expressed miRNAs in 15 participants with EBV-associated fever (divided into 5 groups, common EBV carriers, infectious mononucleosis (IM) and chronic active EBV infection (CAEBV), EBV-associated Hemophagocytic Lymphohistiocytosis (EBV-HLH), and 3 healthy individuals). After a comprehensive analysis, 10 miRNAs with abnormal expression were screened, and then qRT-PCR was performed in the rest of 95 participants to detect the validation of miRNAs expression in plasma samples. Thereafter, we further investigated their potential for clinical application in EBV-related febrile diseases by using a combination of Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Protein-protein interaction network analysis. Results: Through identification and detailed analysis of the obtained data, we found significant differences in the expression of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in blood samples from patients with different EBV-related febrile diseases. We found that the expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in plasma are indicative of determining different disease types of EBV-related febrile diseases, while EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets. Conclusion: The expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p suggest that they may be used as transcriptional features for early differential diagnosis of EBV-related febrile diseases, and EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets.

The logistics industry and the manufacturing industry are mutually productive factors and service objects, which determines that the two must develop cooperatively. In the increasingly fierce market competition, open collaborative innovation is more conducive to improving the level of linkage between the logistics industry and the manufacturing industry, and promoting industrial development. Based on the patent data of 284 prefecture-level cities in China from 2006 to 2020, this paper uses Gis spatial analysis, spatial Dubin model and other methods to analyze the collaborative innovation between the logistics industry and manufacturing industry. The results lead to several conclusions. (i) The overall collaborative innovation level is not high, and in terms of the evolution cycle, collaborative innovation has experienced three stages: embryo, rapid development and stable development. (ii) The spatial agglomeration characteristics of the collaborative innovation between the two industries are more and more obvious, and the Yangtze River Delta urban agglomeration and the middle reaches of the Yangtze River urban agglomeration play an important role in the collaborative innovation between the two industries. (iii) The hot spots of collaborative innovation between the two industries are concentrated in the eastern and northern coastal areas, while the cold spots are concentrated in the south of the northwest and southwest areas in the late stage of the study. (iiii) The positive influencing factors of local collaborative innovation between the two industries include economic development, scientific and technological level, government behavior, and employment, while the negative influencing factors include information technology level, and logistics infrastructure. Economic development has a negative spatial spillover effect on surrounding areas, while the spatial spillover effect of scientific and technological level is significantly positive. This article aims to explore the current situation and influencing factors of collaborative innovation between the two industries, with a view to proposing countermeasures and suggestions for improving the level of collaborative innovation between the two industries, and also providing new ideas for research on cross industry collaborative innovation.

The advanced manufacturing industry is located at the top of the manufacturing value chain. Its development is restricted by supply chain collaboration (SCC), the level of which is affected by many factors. Few studies comprehensively summarize what influences SCC and distinguish the impact level of each factor. Practitioners have difficulty isolating the primary factors that affect SCC and managing them effectively. Therefore, based on synergetics and the theory of comparative advantage, this study analyzes what influences SCC in the advanced manufacturing industry and how these influencing factors work, using data from 94 manufacturing enterprises and the Haken model to identify the influencing factors. The results show that China's advanced manufacturing supply chain underwent a phase change and entered a new stage during 2017-2018. In the new stage, the competitive advantages of enterprises are one order parameter (slow variable) and are primary factors affecting SCC. The interest demands of enterprises are a fast variable and are secondary factors affecting SCC. The competitive advantages of enterprises dominate the interests of enterprises in affecting the collaboration level of China's advanced manufacturing supply chain. In addition, in the process of influencing SCC, there is a positive correlation between the competitive advantages of enterprises and the interest demands of enterprises, and the two factors have a positive feedback mechanism. Finally, when the enterprises in the supply chain cooperate based on their differential advantages, the collaboration capability of the supply chain is at the highest level, and the overall operation of the supply chain is orderly. In terms of theoretical contribution, this study is the first to propose a collaborative motivation framework that conforms to the characteristics of sequential parameters, which provides a theoretical reference for subsequent studies on SCC. In addition, the theory of comparative advantage and synergetics are linked for the first time in this study, and both of them are enriched and developed. Equally importantly, this study compares the bidirectional influence between firms' competitive advantages and firms' interest demands and the ability of both to influence SCC, enriching previous validation studies of unidirectional influence. In terms of practical implications, this study guides top managers to focus on the management practice of collaborative innovation in the supply chain and advises purchasing managers and sales managers on selecting supply chain partnerships.

In order to explore bacteria resources that are applicable for purification of viaduct rainwater, a carbon-fixing bacteria strain numbered 1C-1 was isolated from the sediment of a viaduct rainwater tank. The strain was identified through morphological characteristics and 16S rDNA sequences. The effects of three main factors (the simulated viaduct rainwater concentration, the carbon source dosage, and the inoculation amount) on the nitrogen and phosphorus removal rate of the strain were tested using simulated viaduct rainwater. Based on this, the nitrogen and phosphorus removal efficiencies for the actual viaduct rainwater were verified. The results showed that the strain belonged to Streptomyces sp. Under different simulated viaduct rainwater concentrations, the strain exhibited relatively high efficiency for nitrogen and phosphorus removal at the original concentration of simulated viaduct rainwater; other conditions remaining unchanged, the purification efficiency was relatively high when the glucose dosage was 800 mg, and the removal rates of ammonia nitrogen (NH4+-N), total nitrogen (TN), and total phosphorus (TP) were 71.48%, 47.86%, and 10.43%, respectively; other conditions remaining unchanged, the purification efficiency was relatively high when the inoculation amount was 1%, and the removal rates of NH4+-N, TN, and TP reached 58.62%, 58.35%, and 27.32%, respectively. Under the above optimal process conditions of an original concentration of viaduct rainwater, a carbon source dosage of 800 mg, and an inoculation amount of 1%, the strain removed 92.62%, 6.98%, and 6.16% of NH4+-N, TN, and TP, respectively from the actual viaduct rainwater; more interestingly, the removal rates of NH4+-N and TN were 43.26% and 78.02%, respectively, even without carbon source addition. It seems that there is no need for carbon source addition to remove nitrogen from the actual viaduct rainwater for the strain. To sum up, the carbon-fixing bacteria 1C-1 presents an obvious nitrogen and phosphorus removal effect (especially for nitrogen) for viaduct rainwater treatment and has application potential.

The development of the pallet rental industry is moving at a rapid pace. However, there is no literature on the performance evaluation of pallet rental companies except our previous study. This paper contributes to extending our previous super-efficiency integer-valued DEA (data envelope analysis) model to a group of integer-valued DEA models with generalized reference sets (G-IDEA). According to the proposed approach, the reference sets for decision-making units (DMUs) are composed of proper efficient sample units instead of efficient DMUs. These sample units, which may or may not be the same as DMUs, can be selected by decision-makers according to their demand. The advantages of the G-IDEA models are as follows: (1) they can be applied to find the projections of pallet rental companies with real-valued and integer-valued variables on the efficient frontier; (2) they are able to help the decision-makers in inefficient pallet rental companies make a step by step efficiency improvement scheme. Particularly, we develop a non-oriented integer-valued DEA model with generalized reference sets (NG-IDEA). The NG-IDEA model can be used to figure out how to improve the performance of inefficient pallet rental companies by simultaneously decreasing inputs and increasing outputs. The proposed models are applied to the performance evaluation of ten pallet rental companies. The results of the case study prove the effectiveness of our models. Furthermore, some valuable suggestions on how to improve the efficiency of inefficient pallet rental companies are presented based on the results.

Chrysomycin A, a compound derived from marine microorganisms, proved to have a specific great in vitro inhibitory effect on methicillin-resistant Staphylococcus aureus (MRSA). It exhibits high safety for the skin, as well as a better therapeutic effect than the current clinical drug, vancomycin. Nevertheless, its poor water solubility highly limits the application and reduces the bioavailability. In view of this, we developed a cream of chrysomycin A (CA) to enhance the solubility for the treatment of skin infection, while avoiding the possible toxicity caused by systemic administration. A comprehensive orthogonal evaluation system composed of appearance, spreading ability, and stability was established to find the optimal formula under experimental conditions. The final product was odorless and easy to be spread, with a lustrous, smooth surface. The particle size of the product met Chinese Pharmacopoeia specifications and the entire cream showed long-term stability in destructive tests. The in vitro and in vivo studies indicated that CA cream had a similar anti-MRSA activity to commercially available mupirocin, showing its potential as an efficacious topical delivery system for skin infections treatment.

Traditional data envelopment analysis (DEA) models assume that all the inputs and outputs data are available. However, missing data is a common problem in data analysis. Although several scholars have developed techniques to conduct DEA with missing data, these techniques have some disadvantages. A multi-criteria evaluation approach is proposed to measure the efficiency of decision making units (DMUs) with missing data. In this approach, analysts first estimate the upper and lower bounds of DMUs' efficiency using the proposed I-addIDEA-U models (interval additive integer-valued DEA models with undesirable outputs) that can be applied to address integer-valued variables and undesirable outputs. Then, DMUs' "relative" efficiency is evaluated using the proposed "Halo + Hot deck" DEA method (if there is no correlation between variables) or regression DEA techniques (if there is a correlation between variables). Finally, the multi-index comprehensive evaluation method is applied to determine which scenario (the lower bound of efficiency, the "relative" efficiency, or the upper bound of efficiency) should be selected. With a case study, it is shown that the proposed multi-criteria evaluation approach is more effective than traditional approaches such as the mean imputation DEA method, the deletion DEA method, and the dummy entries DEA method.