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Studies have shown that antidiabetic drugs can alter the gut microbiota. The hypoglycemic effects of the drugs can be attributed in part to certain species in the gut microbiome that help the drugs work more effectively. In addition, increasing energy expenditure via the induction of adipose tissue browning has become an appealing strategy to treat obesity and associated metabolic complications. Currently, glucagon‐like peptide‐1 receptor agonist (GLP‐1 RA) treatment for metabolic disorders such as obesity and type 2 diabetes has been widely studied. To determine the mechanism of a long‐acting GLP‐1 RA affects adipose tissue browning and the gut microbiome, we treated high‐fat diet mice with GLP‐1 RA and demonstrated that the drug can regulate adipose tissue browning. 16S rRNA and untargeted metabolomics assays suggested that it increased the abundance of bacterium Lactobacillus reuteri and decreased serum ceramide levels in mice. L. reuteri was negatively correlated with ceramide. We found that the mechanism of ceramide decline was alkaline ceramidase 2 (Acer2) overexpression. Moreover, L. reuteri can play a therapeutic synergistic role with GLP‐1 RA, suggesting that gut microbiota can be used as a part of the treatment of diabetes. [ABSTRACT FROM AUTHOR]

In situ vaccination is a desirable strategy for cancer immunotherapy due to its convenience and capacity to target tumor antigens. Here, an in situ nanovaccine based on a cationic peptide with cholesterol‐modified, DP7‐C, for cancer immunotherapy is rationally designed, and developed a cancer nanovaccine that is easy to preparate. The nanovaccine includes cocktail small interfering RNAs (siRNAs) and immunologic adjuvant CpG ODNs, has synergistic effect in the cancer treatment. This nanovaccine can induce tumor cell death, promote antigen presentation and relieve immune suppression in the tumor microenvironment (TME). Moreover, this nanovaccine is administered to CT26 (hot) and B16F10 (cold) tumor model mice, in which it targeted the primary tumors and induced systemic antitumor immunity to inhibit metastasis. It is validated that the nanovaccine can convert cold tumors into hot tumors. Furthermore, the nanovaccine increased the immune response to anti‐PD‐1 therapy by modulating the TME in both CT26‐ and B16F10‐tumor‐bearing mice. The siRNA cocktail/CpG ODN/self‐assembling peptide nanovaccine is a simple and universal tool that can effectively generate specific tumor cell antigens and can be combined with immuno‐oncology agents to enhance antitumor immune activity. The versatile methodology provides an alternative approach for developing cancer nanovaccines. [ABSTRACT FROM AUTHOR]

The clinical efficacy of personalized cancer vaccines still needs to be improved due to their insufficient immune effect. The development of innovative adjuvants and lymph node‐targeted delivery systems is the key to improving the clinical efficacy of personalized vaccines. However, there is still a lack of an adjuvant delivery system that is simple in preparation and capable of mass production and integrates adjuvant and lymph node targeted delivery functions. Here, this work reports that a simple dendrimer polypeptide (KK2DP7) nanoparticle enhances the immune efficacy of an OVA/neoantigen‐based vaccine. Due to its multiple functions as a delivery vehicle, immune adjuvant, and facilitator of dendritic cell migration, KK2DP7 efficiently increases the efficiency of antigen uptake and cross‐presentation by antigen‐presenting cells (APCs) and delivers antigens to lymph nodes via APCs. Strikingly, the antitumor effect of KK2DP7/OVA is superior to that of commonly used adjuvants such as poly(I:C), CpG, and aluminum adjuvant combined with OVA. Furthermore, KK2DP7/OVA combined with anti‐PD‐1 antibody is able to prevent tumor recurrence in a postoperative recurrent tumor model. Thus, KK2DP7‐based cancer vaccines alone or in combination with immune checkpoint blockade therapies to treat tumors or postoperative tumor recurrence are a powerful strategy to enhance antitumor immunity. [ABSTRACT FROM AUTHOR]

Rituximab (RTX) is a widely used anticancer drug with gastrointestinal side effects, such as nausea, vomiting, and diarrhea. The reason for these side effects is still poorly understood. Previous studies have reported that the intestinal microbiota is associated with the occurrence of disease and the therapeutic effect of drugs. In this study, we observed mucosal damage, inflammatory cell infiltration and increased intestinal inflammatory factor expression in RTX-treated mice. RTX also changed the diversity of the intestinal microbiota in mice, and decreased abundance of Lactobacillus reuteri was observed in RTX-treated mice. Further experiments revealed that intragastric administration of L. reuteri in RTX-treated mice attenuated the intestinal inflammatory response induced by RTX and regulated the proportion of helper T (Th) cells. In conclusion, our data characterize the effect of the intestinal microbiota on RTX-induced intestinal inflammation, suggesting that modifying the gut microbiota may represent a positive strategy for managing adverse reactions. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the most lethal cancers in humans. The inhibition of peptidyl‐prolyl cis/trans isomerase (Pin1) gene expression may have great potential in the treatment of HCC. N‐Acetylgalactosamine (GalNAc) was used to target the liver. Cholesterol‐modified antimicrobial peptide DP7 (DP7‐C) acts as a carrier, the GalNAc‐siRNA/DP7‐C complex increases the uptake of GalNAc‐siRNA and the escape of endosomes in hepatocytes. In addition, DP7‐C nanoparticles and hydrogel‐assisted GalNAc‐Pin1 siRNA delivery can effectively enhance the stability and prolong the silencing effects of Pin1 siRNA. In an orthotopic liver cancer model, the GalNAc‐Pin1 siRNA/DP7‐C/hydrogel complex can potentially regulate Pin1 expression in hepatocellular carcinoma cells and effectively inhibit tumor progression. Our study proves that Pin1 siRNA is an efficient method for the treatment of HCC and provides a sustainable and effective drug delivery system for the suppression of liver cancer. [ABSTRACT FROM AUTHOR]

Investment estimation is a key component of early decision-making for a construction project, which is crucial to the project cost control. Currently, most investment estimation researches render the point value results, which could lead to considerable uncertainty in the estimation results and increase the risk of decision-making. Therefore, it is essential to explore a type of systematic, accurate, and effective estimation method. This study proposed an innovative estimation method of probability interval prediction based on the distribution of prediction errors. First, the dimension reduction of the construction indexes was conducted by using exploratory factor analysis (EFA). Then, a model was developed based on the fusion of the support vector regression (SVR) and grey wolf optimization (GWO) algorithm. Finally, cost intervals with different confidence levels were obtained on the basis of kernel density estimation (KDE). The case results indicated that when the confidence was 95%, the comprehensive evaluation index coverage width-based criterion (CWC) and the interval coverage rate PICC of the cost estimation were 2.17 and 93.33%, respectively. Hence, the proposed interval prediction model was fairly reliable, which could provide practical guidance for the investment decisions in the early stage of construction projects and give the decision makers more abundant forecasting information. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial peptides are promising alternative antimicrobial agents to combat MDR. DP7, an antimicrobial peptide designed in silico, possesses broad-spectrum antimicrobial activities and immunomodulatory effects. However, the effects of DP7 against Pseudomonas aeruginosa and biofilm infection remain largely unexplored.Objectives: To assess (i) the antimicrobial activity of DP7 against MDR P. aeruginosa; and (ii) the antibiofilm activity against biofilm infection. Also, to preliminarily investigate the possible antimicrobial mode of action.Methods: The MICs of DP7 for 104 clinical P. aeruginosa strains (including 57 MDR strains) and the antibiofilm activity were determined. RNA-Seq, genome sequencing and cell morphology were conducted. Both acute and chronic biofilm infection mouse models were established. Two mutants, resulting from point mutations associated with LPS and biofilms, were constructed to investigate the potential mode of action.Results: DP7, at 8-32 mg/L, inhibited the growth of clinical P. aeruginosa strains and, at 64 mg/L, reduced biofilm formation by 43% to 68% in vitro. In acute lung infection, 0.5 mg/kg DP7 exhibited a 70% protection rate and reduced bacterial colonization by 50% in chronic infection. DP7 mainly suppressed gene expression involving LPS and outer membrane proteins and disrupted cell wall structure. Genome sequencing of the DP7-resistant strain DP7R revealed four SNPs controlling LPS and biofilm production. gshA44 and wbpJ139 mutants displayed LPS reduction and motility deficiency, conferring the reduction of LPS and biofilm biomass of strain DP7R and indicating that LPS was a potential target of DP7.Conclusions: These results demonstrate that DP7 may hold potential as an effective antimicrobial agent against MDR P. aeruginosa and related infections. [ABSTRACT FROM AUTHOR]

This paper deals with the service restoration problem in renewable-powered microgrids that are driven islanded by an unscheduled breakdown from the main grid. The objective is to determine the maximum of the expected restorative loads by choosing the best arrangement of the power network configurations immediately from the beginning of the breakdown all the way to the end of the island mode. The intermittency nature of the renewable power, as well as the uncertainty of the duration of the breakdown pose new challenges to this classic optimization scheduling task. The proposed two scenario-splitting methods can be solved in a two-step solving procedure, in which a Lagrangian technique and dynamic programming are utilized to provide an analytical sub-optimal yet efficient solution to the original problem. Simulation results demonstrate that both methods can find solutions very close to optima effectively; the scheduling plan should be adjusted when the time evolves, especially when the renewable power generation takes a large portion in the power supply; and the energy storage system plays a significant role to reduce the risk of unreliability in the wind power forecasting, even with a small amount of capacity. Finally, the proposed approach can be applied to radially configured systems with other types of distributed generators. [ABSTRACT FROM PUBLISHER]

This paper investigates a pricing strategy to maximize the revenue in future plug-in hybrid electric vehicles' market for battery charging services. Service models are developed for a monopoly market with two typical service classes. The unique characteristics of battery charging result in a piecewise linear quality of service (QoS) model. By resorting to the concept of superdifferential, some theoretical results, including the existence and uniqueness of the subscriber equilibrium and the convergence of the corresponding subscriber dynamics, are established. In the course of developing revenue-maximizing pricing strategies for both service classes, a general tradeoff has been identified between monetization and customer acquisition. [ABSTRACT FROM PUBLISHER]

This paper considers the operation scheduling problem in renewable-powered microgrids, which is used to determine the least-cost unit commitment (UC) and the associated dispatch, while meeting load, environmental, and system operating requirements. The intermittency nature of the renewable energy sources, as well as microgrid’s capacity to operate either in parallel with, or autonomously of, the traditional power grid, pose new challenges to this classic optimization task. A probability-based concept, probability of self-sufficiency (PSS), is introduced to indicate the probability that the microgrid is capable of meeting local demand in a self-sufficient manner. Furthermore, to the best of our knowledge, we make the first attempt in approaching the mixed-integer UC problem from a convex optimization perspective, which leads to an analytical closed-form characterization of the optimal commitment and dispatch solutions. The simulation results show that 1) the proposed method achieves an efficient performance that incurs no loss of optimality with lower complexity than existing algorithms; 2) an energy storage system (ESS) with suitable capacity contributes to the self-sufficiency target of a microgrid, and the stored energy varies less remarkably as the microgrid tends to operate more independently; 3) the proposed method provides guidelines in deciding the ESS size to achieve a desired PSS. [ABSTRACT FROM PUBLISHER]

Obesity has been recognized as a low-grade, chronic inflammatory disease that leads to an increase in obesity-associated disorders, including type 2 diabetes (T2D), fatty liver diseases and cancer. Glucagon-like peptide-1 (GLP-1) is an effective drug for T2D, and it not only has glucose-regulating effects but also has anti-inflammatory effects in obesity. In our previous study, we designed a novel GLP-1 analogue, (E X -4) 2 -Fc, which has been shown to reduce body weight and improve glucose tolerance in vivo. In this study, we observed that (E X -4) 2 -Fc also has anti-inflammatory functions in adipose tissue. After the treatment of diet-induced obesity (DIO) mice with (E X -4) 2 -Fc, we found that the inflammatory response in adipose tissue was significantly attenuated. (Ex-4) 2 -Fc can reduce obesity-associated proinflammatory cytokine levels and macrophage numbers in DIO mice. In addition, (E X -4) 2 -Fc treatment resulted in proinflammatory M1-type macrophages beginning to transform into anti-inflammatory M2-type macrophages. The inflammatory mitogen-activated protein kinase (MAPK) signalling pathway and nuclear factor kappa B (NF-κB) were altered in adipose tissue after (E X -4) 2 -Fc treatment. Leptin has been proven to be closely related to immunity, and we demonstrated that the effect of (E X -4) 2 -Fc on adipocyte inflammation was related to leptin. The data suggested that (E X -4) 2 -Fc could modulate the inflammatory response by inhibiting the expression of leptin in adipose tissue. F0B7 (Ex-4) 2 -Fc could profoundly ameliorate obesity-induced inflammation in the adipose tissues of the DIO mice. F0B7 (Ex-4) 2 -Fc promotes the polarization of M2 macrophages in adipose tissue. F0B7 (Ex-4) 2 -Fc modulates the MAPK and NF-κB signalling pathways in adipose tissue. F0B7 (E X -4) 2 -Fc suppresses obesity-related inflammation by inhibiting leptin secretion. [ABSTRACT FROM AUTHOR]

Methotrexate (MTX) is a preferred disease-modifying anti-rheumatic drug in the management of rheumatoid arthritis (RA). However, the toxicity and inefficiency of MTX limit its clinical application. Gut microbiota has been implicated in the side effects and efficacy of MTX. In this study, the analysis of the gut microbiota in RA patients revealed that the abundances of intestinal Bacteroides fragilis was reduced after MTX treatment. We observed that MTX has no obvious therapeutic effect in the absence of B. fragilis , while transplantation of B. fragilis restored the efficacy of MTX in antibiotics-pretreated collagen-induced arthritis (CIA) mice. In addition, B. fragilis gavage was accompanied by an increase in butyrate. Supplementation of butyrate restored the response to MTX in gut microbiota-deficient mice, to a similar level achieved by B. fragilis gavage. These results show that gut microbiota-regulated butyrate plays an essential role in the efficacy of MTX, which will provide new strategies to improve the effectiveness of methotrexate in RA treatment., 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 Zhou, Dong, Zhao, Lin, Tian, Zhang, Zhu, Xu and Yang.)