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Abstract Viral pneumonia is characterized by inflammation in the lungs triggered by respiratory viruses. Dayuan Yin (DYY), a traditional Chinese medicine formula known for treating infectious diseases, is hypothesized to offer therapeutic benefits in treating viral pneumonia, although its specific molecular impacts remain understudied. This study aimed to evaluate the therapeutic effects of DYY in mitigating HCoV-229E virus-induced pneumonia in mice. This study employed an HCoV-229E virus-infected mouse model to investigate the therapeutic potential and underlying molecular mechanisms of DYY on virus-induced pneumonia. The respiratory function and organ indices post-treatment were assessed. Lung tissue and tracheal lesions were evaluated via immunohistochemistry. Spleen immune cell composition was analyzed using flow cytometry. Inflammatory cytokines and viral loads were quantified using hypersensitive multiplex electrochemiluminescence method and PCR analysis, respectively. The expression levels of MAS1, Ras, Raf1, MEK1/2, and ERK1/2 in lung tissues were determined through western blot analysis. DYY significantly improved respiratory function, and reduced organ pathology in infected mice. It effectively decreased viral loads and inflammatory cytokines such as IL-6, IL-1β, and TNF-α in lung tissues. Enhancements in immune response were evidenced by increased CD4/CD8 ratios in the spleen. DYY also notably upregulated MAS1 protein levels and suppressed the activation of the Ras/Raf1/MEK/ERK signaling pathway. DYY enhanced respiratory function and exerted significant antiviral and immunomodulatory effects in mice infected with the HCoV-229E virus, primarily by modulating MAS1 expression and inhibiting the Ras/Raf1/MEK/ERK pathway. Graphical Abstract

The enzyme-linked immunosorbent assay (ELISA) is a powerful and high-throughput method for detecting aflatoxin B1 (AFB1) in food. However, the susceptibility of native enzymes to environmental factors limits their potential applications. This study introduces the combined use of precious metal nanozymes as alternative catalysts to improve the performance of traditional ELISA. Au@Pt can be linked to antibodies to construct recognition probes, onto which platinum nanoparticles (PtNPs) are ingeniously deposited in situ to amplify the detection signal, thereby increasing the sensitivity. The proposed PtNP-enhanced Au@Pt-ELISA exhibited excellent resistance against matrix interference for AFB1 detection in lotus seed powder and achieved a detection limit of 1.6 pg/mL (0.32 μg/kg), which was approximately six times lower than that of traditional ELISA. Furthermore, the results of the proposed approach were strongly correlated with LC–MS/MS analysis results for real samples (r = 0.9888, n = 13). This study offers a new strategy for AFB1 monitoring in a complex matrix.

ABSTRACTWith the large number of atypical cases in the mpox outbreak, which was classified as a global health emergency by the World Health Organization (WHO) on 23 July 2022, rapid diagnosis of mpox and diseases with similar symptoms to mpox such as chickenpox and respiratory infectious diseases in the early stages of viral infection is key to controlling the spread of the outbreak. In this study, antibodies against the monkeypox virus A29L protein were efficiently and rapidly identified by combining rapid mRNA immunization with high-throughput sequencing of individual B cells. We obtained eight antibodies with a high affinity for A29L validated by ELISA, which were was used as the basis for developing an ultrasensitive fluorescent immunochromatographic assay based on multilayer quantum dot nanobeads (SiTQD-ICA). The SiTQD-ICA biosensor utilizing M53 and M78 antibodies showed high sensitivity and stability of detection: A29L was detected within 20 min, with a minimum detection limit of 5 pg/mL. A specificity test showed that the method was non-cross-reactive with chickenpox or common respiratory pathogens and can be used for early and rapid diagnosis of monkeypox virus infection by antigen detection. This antibody identification method can also be used for rapid acquisition of monoclonal antibodies in early outbreaks of other infectious diseases for various studies.

Abstract Background BC001 is a novel fully human immunoglobulin G1 monoclonal antibody blocking VEGFR2. This phase I study aimed to assess BC001 alone and plus chemotherapy in solid tumors. Methods In dose escalation part, BC001 was assessed at dose levels of 2, 4, 8, 12, 16 mg/kg on day 1,15, every 28 days, followed an accelerated titration and “3 + 3” design. BC001 plus paclitaxel was assessed at dose level of 8, 10 mg/kg. The primary endpoints included the DLT, MTD and RDE of BC001. In dose expansion part, it aimed to assess the anti‐tumor activity of BC001 alone and plus chemotherapy in gastric cancer as 2nd line treatment. Results Overall, 53 patients were finally enrolled in this study (phase Ia, n = 28; phase Ib, n = 25). In phase Ia part, 1 DLT (grade 4 neutropenia lasting 4 days) was observed in BC001(8 mg/kg) plus paclitaxel cohort. MTD was not reached. All patients experienced TEAEs of any grade. Twenty‐four of them suffered ≥ grade 3 TEAEs. leukopenia (n = 33, 62.3%), hemoglobin decreased (n = 32, 60.4%), neutropenia (n = 29, 54.7%) were commonly observed hematological toxicities. The half‐life of 140‐240 h. And the PK parameters were not largely influenced by combination with paclitaxel. The serum sVEGFR‐1, VEGF‐A, sVEGFR‐2 could not predict the efficacy. Based on the safety, PK and efficacy data, BC001 of 8 mg/kg was determined as RED. Among the GC patients(n = 21) who receiving BC001 plus paclitaxel as 2nd‐line treatment in phase 1b part, 6 patients achieved PR and 10 patients experienced SD. The ORR was 28.6% (95% CI 11.3%, 52.2%) and the DCR was 76.2% (95% CI 52.8%, 91.8%), with the median PFS of 5.4 months (95% CI 1.9, 7.0) and OS of 9.4 months (95% CI 5.4, NA). The median DoR was 5.1 months (95% CI 2.6, NA). Conclusions BC001 showed acceptable safety profile and preliminary response in both single‐agent and combination with chemotherapy cohorts, especially in GC.

ABSTRACT Guanine nucleotides are required for growth and viability of cells due to their structural role in DNA and RNA, and their regulatory roles in translation, signal transduction, and cell division. The natural antibiotic mycophenolic acid (MPA) targets the rate-limiting step in de novo guanine nucleotide biosynthesis executed by inosine-5´-monophosphate dehydrogenase (IMPDH). MPA is used clinically as an immunosuppressant, but whether in vivo inhibition of bacterial IMPDH (GuaB) is a valid antibacterial strategy is controversial. Here, we describe the discovery of extremely potent small molecule GuaB inhibitors (GuaBi) specific to pathogenic bacteria with a low frequency of on-target spontaneous resistance and bactericidal efficacy in vivo against Acinetobacter baumannii mouse models of infection. The spectrum of GuaBi activity includes multidrug-resistant pathogens that are a critical priority of new antibiotic development. Co-crystal structures of A. baumannii, Staphylococcus aureus, and Escherichia coli GuaB proteins bound to inhibitors show comparable binding modes of GuaBi across species and identifies key binding site residues that are predictive of whole-cell activity across both Gram-positive and Gram-negative clades of Bacteria. The clear in vivo efficacy of these small molecule GuaB inhibitors in a model of A. baumannii infection validates GuaB as an essential antibiotic target.IMPORTANCEThe emergence of multidrug-resistant bacteria worldwide has renewed interest in discovering antibiotics with novel mechanism of action. For the first time ever, we demonstrate that pharmacological inhibition of de novo guanine biosynthesis is bactericidal in a mouse model of Acinetobacter baumannii infection. Structural analyses of novel inhibitors explain differences in biochemical and whole-cell activity across bacterial clades and underscore why this discovery may have broad translational impact on treatment of the most recalcitrant bacterial infections.

Abstract Background Invasive fungal infection (IFI) has become an increasing problem in NICU neonates, and end-organ damage (EOD) from IFI is one of the leading causes of morbidity and mortality in neonates. This study was conducted to summarize clinical data on epidemiology, risk factors, causative pathogens, and clinical outcomes of IFI-associated EOD among neonates in a center in China for the sake of providing references for prevention and treatment of fungal infections in neonates in future. Methods The clinical data of IFI neonates who received treatment in a tertiary NICU of China from January 2009 to December 2022 were retrospectively analyzed, including causative pathogens and the incidence of EOD. The neonates were divided into EOD group and non-EOD (NEOD) group. The general characteristics, risk factors and clinical outcomes of the two groups were compared. Results Included in this study were 223 IFI neonates (137 male and 86 female) with a median gestational age (GA) of 30.71 (29,35) weeks and a median birth weight (BW) of 1470 (1120,2150) g. Of them, 79.4% were preterm infants and 50.2% were born at a GA of ≥ 28,

Objective: Previous studies have shown that Danhong injection (DHI) has a protective effect on the blood-brain barrier (BBB) function after ischemic stroke. However, the role of DHI in protecting the integrity of the BBB after ischemic stroke through endothelial cells is still unclear. The purpose of this study is to explore the role and mechanism of DHI in protecting BBB by interfering with endothelial cells. Methods: We used network pharmacology technology to determine the potential pathways and mechanisms of DHI in treating ischemic stroke through endothelial cells. On account of the network pharmacology results, we assessed the effects of DHI in oxygen-glucose deprivation (OGD) model of mouse brain-derived endothelial (bEnd.3) cells via MTT, and validated the molecular mechanisms of DHI improving BBB injury through Western blot. Results: Network pharmacology analysis suggested that DHI may regulate the PI3K/AKT signaling pathway of endothelial cells in the treatment of ischemic stroke. Cellular experiments showed that DHI stimulates endothelial cell migration and reduces OGD-induced BBB damage via VEGFR2/PI3K/AKT pathway. Conclusion: Network pharmacology analysis and cellular experiments have shown that DHI alleviated the BBB damage by activating the VEGFR2/PI3K/AKT signaling pathway on endothelial cells.

Porcine models are increasingly recognized for their similarities to humans and have been utilized in disease modeling and organ grafting research. While extensive metabolomics studies have been conducted in swine, primarily focusing on conventional cohorts or specific animal models, the composition and functions of fecal metabolites in pigs across different age groups—particularly in the elderly—remain inadequately understood. In this study, an untargeted metabolomics approach was employed to analyze the fecal metabolomes of pigs at three distinct age stages: young (one year), middle-aged (four years), and elderly (eight years). The objective was to elucidate age-associated changes in metabolite composition and functionality under standardized rearing conditions. The untargeted metabolomic analysis revealed a diverse array of age-related metabolites. Notably, L-methionine sulfoxide levels were found to increase with age, whereas cytidine-5-monophosphate levels exhibited a gradual decline throughout the aging process. These metabolites demonstrated alterations across various biological pathways, including energy metabolism, pyrimidine metabolism, lipid metabolism, and amino acid metabolism. Collectively, the identified key metabolites, such as L-methionine sulfoxide and Cholecalciferol, may serve as potential biomarkers of senescence, providing valuable insights into the mechanistic understanding of aging in pigs.

Cytoplasmic effectors with an Arg-any amino acid-Arg-Leu (RxLR) motif are encoded by hundreds of genes within the genomes of oomycete Phytophthora spp. and downy mildew pathogens. There has been a dramatic increase in our understanding of the evolution, function, and recognition of these effectors. Host proteins with a wide range of subcellular localizations and functions are targeted by RxLR effectors. Many processes are manipulated, including transcription, post-translational modifications, such as phosphorylation and ubiquitination, secretion, and intracellular trafficking. This involves an array of RxLR effector modes-of-action, including stabilization or destabilization of protein targets, altering or disrupting protein complexes, inhibition or utility of target enzyme activities, and changing the location of protein targets. Interestingly, approximately 50% of identified host proteins targeted by RxLR effectors are negative regulators of immunity. Avirulence RxLR effectors may be directly or indirectly detected by nucleotide-binding leucine-rich repeat resistance (NLR) proteins. Direct recognition by a single NLR of RxLR effector orthologues conserved across multiple Phytophthora pathogens may provide wide protection of diverse crops. Failure of RxLR effectors to interact with or appropriately manipulate target proteins in nonhost plants has been shown to restrict host range. This knowledge can potentially be exploited to alter host targets to prevent effector interaction, providing a barrier to host infection. Finally, recent evidence suggests that RxLR effectors, like cytoplasmic effectors from fungal pathogen Magnaporthe oryzae, may enter host cells via clathrin-mediated endocytosis. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Moutan Cortex (MC) has been used in treating inflammation-associated diseases and conditions in China and other Southeast Asian countries. However, the active components of its anti-inflammatory effect are still unclear. The study aimed to screen and identify potential cyclooxygenase-2 (COX-2) inhibitors in MC extract. The effect of MC on COX-2 was determined in vitro by COX-2 inhibitory assays, followed by bio-affinity ultrafiltration in combination with ultra-performance liquid chromatography-mass spectrometry (BAUF-UPLC-MS). To verify the reliability of the constructed approach, celecoxib was applied as the positive control, in contrast to adenosine which served as the negative control in this study. The bioactivity of the MC components was validated in vitro by COX-2 inhibitor assay and RAW264.7 cells. Their in vivo anti-inflammatory activity was also evaluated using LPS-induced zebrafish inflammation models. Finally, molecular docking was hired to further explore the internal interactions between the components and COX-2 residues. The MC extract showed an evident COX-2-inhibitory effect in a concentration-dependent manner. A total of 11 potential COX-2 inhibitors were eventually identified in MC extract. The COX-2 inhibitory activity of five components, namely, gallic acid (GA), methyl gallate (MG), galloylpaeoniflorin (GP), 1,2,3,6-Tetra-O-galloyl-β-D-glucose (TGG), and 1,2,3,4,6-Penta-O-galloyl-β-D-glucopyranose (PGG), were validated through both in vitro assays and experiments using zebrafish models. Besides, the molecular docking analysis revealed that the potential inhibitors in MC could effectively inhibit COX-2 by interacting with specific residues, similar to the mechanism of action exhibited by celecoxib. In conclusion, BAUF-UPLC-MS combining the molecular docking is an efficient approach to discover enzyme inhibitors from traditional herbs and understand the mechanism of action.

Introduction: β-glucosidase is one class of pivotal glycosylhydrolase enzyme that can cleavage glucosidic bonds and transfer glycosyl group between the oxygen nucleophiles. Lactobacillus is the most abundant bacteria in the human gut. Identification and characterization of new β-glucosidases from Lactobacillus are meaningful for food or drug industry.Method: Herein, an acid-adapted β-glucosidase (LpBgla) was cloned and characterized from Lactobacillus paracasei. And the insight acid-adapted mechanism of LpBgla was investigated using molecular dynamics simulations.Results and Discussion: The recombinant LpBgla exhibited maximal activity at temperature of 30°C and pH 5.5, and the enzymatic activity was inhibited by Cu2+, Mn2+, Zn2+, Fe2+, Fe3+ and EDTA. The LpBgla showed a more stable structure, wider substrate-binding pocket and channel aisle, more hydrogen bonds and stronger molecular interaction with the substrate at pH 5.5 than pH 7.5. Five residues including Asp45, Leu60, Arg120, Lys153 and Arg164 might play a critical role in the acid-adapted mechanism of LpBgla. Moreover, LpBgla showed a broad substrate specificity and potential application in the bioconversion of glycosides, especially towards the arbutin. Our study greatly benefits for the development novel β-glucosidases from Lactobacillus, and for the biosynthesis of aglycones.

Litter decomposition is key to ecosystem carbon (C) and nutrient cycling, but this process is anticipated to weaken due to projected more extensive and prolonged drought. Yet how litter quality and decomposer community complexity regulate decomposition in response to drought is less understood. Here, in a five-year manipulative drought experiment in a Masson pine forest, leaf litter from four subtropical tree species (Quercus griffithii Hook.f. & Thomson ex Miq., Acacia mangium Willd., Pinus massoniana Lamb., Castanopsis hystrix Miq.) representing different qualities was decomposed for 350 ​d in litterbags of three different mesh sizes (i.e., 0.05, 1, and 5 ​mm), respectively, under natural conditions and a 50% throughfall rain exclusion treatment. Litterbags of increasing mesh sizes discriminate decomposer communities (i.e., microorganisms, microorganisms and mesofauna, microorganisms and meso- and macrofauna) that access the litter and represent an increasing complexity. The amount of litter C and nitrogen (N) loss, and changes in their ratio (C/Nloss), as well as small and medium-sized decomposers including microorganisms, nematodes, and arthropods, were investigated. We found that drought did not affect C and N loss but decreased C/Nloss (i.e., decomposer N use efficiency) of leaf litter irrespective of litter quality and decomposer complexity. However, changes in the C/Nloss and the drought effect on C loss were both dependent on litter quality, while drought and decomposer complexity interactively affected litter C and N loss. Increasing decomposer community complexity enhanced litter decomposition and allowing additional access of meso- and macro-fauna to litterbags mitigated the negative drought effect on the microbial-driven decomposition. Furthermore, both the increased diversity and altered trophic structure of nematode due to drought contributed to the mitigation effects via cascading interactions. Our results show that litter quality and soil decomposer community complexity co-drive the effect of drought on litter decomposition. This experimental finding provides a new insight into the mechanisms controlling forest floor C and nutrient cycling under future global change scenarios.

Nantong Hualushao wine is a special type of traditional Huangjiu, or Chinese yellow wine. It has been added to the list of intangible cultural heritage in Nantong, Jiangsu Province. In this study, the key quality indicators of ten commercial Hualushao wines and five traditional Huangjiu products were determined. The organic acids and sugars were analysed using high-performance liquid chromatography (HPLC), and the colour was measured with a spectrophotometer. By comparing the content of the Hualushao wines and the Huangjiu samples using statistical methods, the differences between these two products were described, and the characteristics of Hualushao wine were clarified. Results revealed that the acetic acid, total sugar, glucose, alcohol, and soluble solid content, as well as the pH value of Hualushao wine, were significantly higher than those of traditional Huangjiu (P

In order to solve the resource allocation problem in scenarios of centralized wireless cellular communication with multiple cells, users and channels, a novel resource allocation algorithm based on joint Deep Deterministic Policy Gradient (DDPG) reinforcement learning and unsupervised learning is proposed. Firstly, the proposed algorithm constructs a channel allocation deep neural network based on DDPG to provide an optimized channel allocation scheme. Secondly, the proposed algorithm constructs a power control deep neural network based on unsupervised learning to provide an optimized power control scheme. In order to make the unsupervised learning have perceptions on dynamic wireless environments, the double experience replay is executed to train the channel allocation deep neural network with the DDPG reinforcement learning and the power control deep neural network with the unsupervised learning, respectively. Since the proposed joint algorithm combines the dynamic perception ability of the DDPG reinforcement learning and the continuous optimization ability of unsupervised learning, the energy efficiency can be effectively maximized. Simulation results show that the proposed algorithm outperforms other algorithms in terms of energy efficiency and transmit rate in time-varying dynamic environments. Furthermore, we discuss the implications of our results and possible future research directions. Our work contributes to the advancement of resource allocation techniques in multi-cell cellular networks to meet the increasing demands of modern wireless communication systems.

In this study the single factor experiments were employed to determine the effects of various factors on extraction rate of triterpenoids in the seeds of S. jambos L. Alston using the yields as indicator. Then Box-Behnken design and response surface methodology were employed to optimize the extraction process using the Design-Expert 12 software. Moreover, the antioxidant activity of triterpenoids in the seeds of S. jambos L. Alston was evaluated by determining the scavenging capacity of DPPH and ABTS free radical. The results showed that the optimal conditions were as follows: Methanol concentration 44.30%, solid-liquid ratio 1:47.18 g/mL, extraction time was 101.07 min (adjusted to 101 min in the experiment). Under these conditions, the deviation between the experimental extraction yield value (12.11 mg/g) and the predicted value (12.28 mg/g) of triterpenoids in the seeds of S. jambos L. Alston was only 1.26% (

IntroductionThe accelerated aging of the global population has emerged as a critical public health concern, with increasing recognition of the influential role played by the microbiome in shaping host well-being. Nonetheless, there remains a dearth of understanding regarding the functional alterations occurring within the microbiota and their intricate interactions with metabolic pathways across various stages of aging.MethodsThis study employed a comprehensive metagenomic analysis encompassing saliva and stool samples obtained from 45 pigs representing three distinct age groups, alongside serum metabolomics and lipidomics profiling.ResultsOur findings unveiled discernible modifications in the gut and oral microbiomes, serum metabolome, and lipidome at each age stage. Specifically, we identified 87 microbial species in stool samples and 68 in saliva samples that demonstrated significant age-related changes. Notably, 13 species in stool, including Clostridiales bacterium, Lactobacillus johnsonii, and Oscillibacter spp., exhibited age-dependent alterations, while 15 salivary species, such as Corynebacterium xerosis, Staphylococcus sciuri, and Prevotella intermedia, displayed an increase with senescence, accompanied by a notable enrichment of pathogenic organisms. Concomitant with these gut-oral microbiota changes were functional modifications observed in pathways such as cell growth and death (necroptosis), bacterial infection disease, and aging (longevity regulating pathway) throughout the aging process. Moreover, our metabolomics and lipidomics analyses unveiled the accumulation of inflammatory metabolites or the depletion of beneficial metabolites and lipids as aging progressed. Furthermore, we unraveled a complex interplay linking the oral-gut microbiota with serum metabolites and lipids.DiscussionCollectively, our findings illuminate novel insights into the potential contributions of the oral-gut microbiome and systemic circulating metabolites and lipids to host lifespan and healthy aging.

This study highlights the drawbacks of current quantum classifiers that limit their efficiency and data processing capabilities in big data environments. The paper proposes a global decision tree paradigm to address these issues, focusing on designing a complete quantum decision tree classification algorithm that is accurate and efficient while also considering classification costs. The proposed method integrates the Bayesian algorithm and the quantum decision tree classification algorithm to handle incremental data. The proposed approach generates a suitable decision tree dynamically based on data objects and cost constraints. To handle incremental data, the Bayesian algorithm and quantum decision tree classification algorithm are integrated, and kernel functions obtained from quantum kernel estimation are added to a linear quantum support vector machine to construct a decision tree classifier using decision directed acyclic networks of quantum support vector machine nodes (QKE). The experimental findings demonstrate the effectiveness and adaptability of the suggested quantum classification technique. In terms of classification accuracy, speed, and practical application impact, the proposed classification approach outperforms the competition, with an accuracy difference from conventional classification algorithms being less than 1%. With improved accuracy and reduced expense as the incremental data increases, the efficiency of the suggested algorithm for incremental data classification is comparable to previous quantum classification algorithms. The proposed global decision tree paradigm addresses the critical issues that need to be resolved by quantum classification methods, such as the inability to process incremental data and the failure to take the cost of categorization into account. By integrating the Bayesian algorithm and the quantum decision tree classification algorithm and using QKE, the proposed method achieves high accuracy and efficiency while maintaining high performance when processing incremental sequences and considering classification costs. Overall, the theoretical and experimental findings demonstrate the effectiveness of the suggested quantum classification technique, which offers a promising solution for handling big data classification tasks that require high accuracy and efficiency.

Abstract Background Raw Moutan Cortex (RMC) has been used in China and other Asian countries for thousands of years. Its medical application is the treatment of cooling blood and promoting blood circulation. However, its therapeutic mechanism is still undefined. Methods In this study, the pharmacokinetics strategy that integrated network analysis was employed to explore the mechanism of RMC in blood-heat and blood stasis syndrome (BHS) model rats. Firstly, Ultra-High performance Liquid Chromatography coupled with Diode Array Detector (UHPLC-DAD) method was developed to determine nine absorbed compounds in rat serum in BHS and normal rats after oral administration of RMC extract respectively. Then the pharmacology network was established based on the relationship between nine compounds absorbed into the blood and BHS targets. Finally, the predicted hub targets were validated experimentally in human umbilical vein endothelial cells (HUVECs). Results Pharmacokinetic study showed that the pharmacokinetic parameters of nine absorbed compounds had significant differences between BHS and normal groups (p

Traditional Chinese medicine is the treasure of Chinese traditional culture. A series of questions should be answered on the base of systematic, comprehensive and in-depth research according to the TCM theory and its own characteristics. For example, how to construct a research framework with clear guidance and route, as well as reasonable plan for elucidating the effective material basis of Traditional Chinese medicine (TCM) formula? How to discover and excavate the effective material basis of TCM, clarify and interpret the related action mechanism? How to clarify the reasonableness of compatibility, the scientificity for usage of medication, as well as the scientific connotation of TCM in preventing and curing disease? Aforementioned questions had been considered as the important frontier scientific problems to be solved in the field of TCM. According to the practice progress and thinking on research of effective material basis and related mechanism in Naomaitong Granule and Dengzhan Shengmai Capsule, a systematic strategy from the perspective of interaction between drug system, intestinal microecosystem and host living system had been proposed and elucidated in three aspects: (1) Discovering the TCM regulated genes and proteins dated from functional metabolites, in order to characterize the biological response of host systematically. (2) Deciphering the effective material basis and related acting mechanism on the base of interaction between TCM formula and intestinal microecosystem. (3) The systematic characterization of material basis of TCM formula by Chemomics.

The article discusses the challenge of finding an efficient decoder for quantum error correction codes for fault-tolerant experiments in quantum computing. The study aims to develop a better decoding scheme based on the flag-bridge fault tolerance experiment. The research compares two decoding algorithms, a deep neural network decoding scheme and a simple decoder, and a recurrent neural network decoding scheme based on the belief propagation algorithm variant MBP4 algorithm. The study improved the syndrome extraction circuit based on the flag-bridge method to meet the requirements of fault-tolerant experiments better. Two decoding schemes were studied, a combination of a deep neural network and a simple decoder and a recurrent neural network structure based on the MBP4 algorithm. The first scheme used neural networks to assist simple decoders in determining whether additional logical corrections need to be added. The second scheme used a recurrent neural network structure designed through the variant MBP4 algorithm, along with a post-processing method to pinpoint the error qubit position for decoding. Experimental results showed that the decoding scheme developed in the study improved the pseudo-threshold by 39.52% compared to the minimum-weight perfect matching decoder. The two decoders had thresholds of approximately 15.8% and 16.4%, respectively. The study’s findings suggest that the proposed decoding schemes could improve quantum error correction and fault-tolerant experiments in quantum computing.

Objective: To investigate the feasibility of CT radiomics analysis for the identification of exon 9 and 11 mutations of c-kit gene in gastrointestinal stromal tumor (GIST). Materials and Methods: We retrospectively analyzed 49 GIST enhanced CT cases with c-kit mutation confirmed by molecular pathology, 9 had exon 9 mutation, and 40 had exon 11 mutation. 105 radiomics features were extracted by using python pyradiomics, and feature selection was performed by LASSO regression. Then, the differences were compared and the identification model was constructed. Results: By LASSO selection, 7 valuable radiomics features were selected, and the logistic regression model had a good performance (area under curve，AUC=0.79). Conclusion: CT radiomics analysis had the potential to distinguish c-kit gene exon 9 and 11 mutations in GIST.

ObjectiveTo identify risk factors for impaired glucose regulation (IGR) and assess their impact on community residents, this study used a questionnaire to conduct cross-sectional surveys and analysis.MethodsOverall, 774 residents of an urban community in northern China (Jian city) participated in this study. Trained investigators conducted surveys using questionnaires. Based on their medical history, respondents were divided into three glucose status groups as follows: normal (NGT), IGR, and diabetes mellitus (DM). Statistical analysis of survey data was performed using SPSS v. 22.0.ResultsAge, hypertension, family history of diabetes (FHD), dyslipidemia, obesity, and cardiovascular and cerebral disease (CVD) were positively correlated with IGR in men and women. IGR was negatively correlated with a sedentary lifestyle in men and positively correlated with being overweight in women. The number of type 2 diabetes mellitus (T2D) risk factors per subject was positively correlated with age in the NGT group. Glucose status deteriorated with increasing age and the number of risk factors. FHD was the strongest risk factor in both men and women.ConclusionsPrevention of IGR includes weight control, physical activity, and prevention of hypertension and dyslipidemia, especially in subjects with FHD.

With the rapid development of science and technology and network technology, the study of information security has become a hot spot, and image encryption has potential value in this regard. In this paper, an image encryption scheme based on controlled zigzag transform and bit-level encryption under the quantum walk environment is proposed. First, the parameters of the alternating quantum walk are obtained using the SHA-256 method, and the probability matrix of the quantum distribution on the two-dimensional lattice is obtained by multiple walk measurements; second, the spatial dislocation and bit-level dislocation of the image are realized by performing controlled zigzag dislocation and three-dimensional tesseract-like rotational dislocation on the color image; finally, after preprocessing the probability matrix of the quantum distribution, the matrix is bitwise with the dislocated image to achieve the encryption protection of image information. The effectiveness of the encryption scheme is verified by simulation experiments, and the scheme has a significant encryption effect. Compared with other encryption schemes, this scheme has better key sensitivity and dislocation effect, which provides a new approach to the field of image quantum encryption.

ObjectiveBesides breast and gastric cancer, HER2 amplification/mutation are also found in lung adenocarcinoma (LUAD). However, the correlation between HER2 variations and the phenotype of immunogenicity and tumor immune microenvironment (TIME) in LUAD compared with breast and gastric cancer has yet to be fully elucidated.MethodsWe integrated public databases (discovery set) and internal data (validated set) of 288 patients representing three distinct HER2-altered tumors. Genomic data were used to identify somatic mutations, copy number variations, and calculate tumor mutational burden (TMB) and microsatellite instability score. RNA sequencing was conducted to estimate immune gene signatures and contents of tumor-infiltrating immune cell populations. Finally, IHC was used to determine PD-L1 expression and the tumoral-infiltration of immune cells in 50 HER2-variant tumor specimens with no prior therapeutic regimens.ResultsCompared with HER2-amplified breast and gastric cancers, patients with HER2-amplified LUAD showed higher immunogenicity, mainly manifested in immune checkpoints expression and tissue/blood TMB. Additionally, HER2-amplified LUAD exhibited an inflamed TIME with remarkably increased genes encoding HLAs, T-cell activity and immune cell-type, and accompanied with tumor‐infiltrating lymphocytes. In LUAD, patients with HER2 amplification possessed higher tissue TMB than HER2 mutation, whereas no difference was observed in PD-L1 expression. HER2 amplification (primary) was associated with significantly higher PD-L1 expression and TMB than acquired HER2 amplification after resistance to EGFR-TKIs.ConclusionPatients with HER2-amplified LUAD have better immunogenicity and/or an inflamed TIME among HER2-aberrant tumors. Our study may provide clues for establishing the benefits and uses of ICIs for patients with this disease.

BackgroundA large number of papers regarding coronavirus disease 2019 (COVID-19) and epilepsy have been published since the declaration of the COVID-19 pandemic. However, there is no bibliometric analysis on these papers. In this study, we aimed to analyze the bibliometric characteristics of these papers, thus identifying the trends and future directions of COVID-19 and epilepsy research.MethodsScientific papers regarding COVID-19 and epilepsy were retrieved through searches of the Web of Science Core Collection database. Title, authors, contributing institute, country, source journal, times cited, and additional information were extracted from each selected paper. Microsoft Excel 2019 and GraphPad Prism 8 were used to analyze the extracted data and export the bar charts and tables whilst VOSviewer software was used to perform and visualize co-authorship analysis and co-occurrence analysis of keywords.ResultsA total of 317 papers regarding COVID-19 and epilepsy were included in the final analysis. Epilepsy & Behavior published the largest number of papers (n = 84). J. Helen Cross and Naoto Kuroda were the most prolific authors (n = 13 each). The United States (n = 88) and the University of London (n = 23) were the country and organization with the most contributions, respectively. The strongest authors' collaborations were between Giovanni Assenza and Jacopo Lanzone and between J. Helen Cross and Nathalie Jette. Selected author keywords were organized into seven clusters, and the keywords in clusters 1 and cluster 4 had the largest average appearing year of any clusters.ConclusionThis is the first bibliometric analysis of papers regarding COVID-19 and epilepsy. Our results showed that the United States was the leading country whilst J. Helen Cross was the most influential scholar in COVID-19 and epilepsy research. psychological consequences of COVID-19, and the safety of COVID-19 vaccines for people with epilepsy, are possible areas for future research on COVID-19 and epilepsy.

Here, using proteomics and cell-based assays, the authors show that HIV accessory protein Vpr mediates the degradation of host lysosomal-associated transmembrane protein 5 (LAPTM5) in monocyte-derived macrophages (MDM) to enhance infection in macrophages.

ABSTRACT In humans, HIV-1 infection induces innate immune responses mediated mainly by type I interferon (IFN). Type I IFN restricts HIV-1 replication by upregulating the expression of IFN-stimulated genes with diverse anti-HIV properties. In this study, we report that the cell membrane protein otoferlin (OTOF) acts as a type I IFN-induced effector, inhibiting HIV-1 entry in myeloid lineage macrophages and dendritic cells (DCs). OTOF is significantly induced by type I IFN in macrophages and DCs but not in CD4+ T lymphocytes. Silencing OTOF abrogates the IFN-mediated suppression of HIV-1 infection in macrophages and DCs. Moreover, OTOF overexpression exhibits anti-HIV activity in macrophages and CD4+ T cells. Further evidence reveals that OTOF inhibits HIV-1 entry into target cells at the cell membrane. Collectively, OTOF is a downstream molecule induced by type I IFN to inhibit HIV-1 entry in macrophages; it is a new potential agent for the treatment of HIV infection. IMPORTANCE In patients with HIV-1 infection, the virus is recognized by innate immune sensors that trigger the production of type I interferons (IFNs), which are well-known cytokines that exert broad antiviral effects by inducing the expression of antiviral genes. By comparing the gene expression profiles of untreated patients and healthy donors, we systematically identified OTOF as a new antiviral gene induced by IFN-α in primary macrophages and dendritic cells (DCs). Additionally, silencing OTOF alleviates IFN-α-induced resistance to HIV-1 infection in both myeloid cell lineage macrophages and DCs. In contrast, OTOF overexpression potently restricts HIV-1 transmission in macrophages. We further explored the molecular mechanism through which OTOF inhibits the HIV-1 virion across the cell membrane. Overall, OTOF is a newly identified type I IFN-induced antiviral factor that inhibits the transmembrane activity of HIV-1 in myeloid cells.

Ischemic/reperfusion (IR) can cause adverse reactions including apoptosis, oxidative stress, and inflammation, but the existing therapeutic strategies have been limited. Moreover, the regulation of microglia plays an important role in brain injury after reperfusion. Hence, it is imperative to find new and effective drugs for modulating microglia to treat IR brain injury. Cyclic peptide compound cyclo-(Phe-Tyr) (Sparganin C, SC) is a compound isolated from Sparganii Rhizoma. However, the protective effects of SC on the central nervous system are rather unclear. In an attempt to elucidate the protective effects and mechanism of SC on cerebral damage induced by the IR, we used a middle cerebral artery occlusion reperfusion (MCAO/R) model in rats and discovered that SC significantly decreased the size of cerebral infarcts, improved neurological scores, and blocked inflammatory and oxidative factor release. Using RNA-Seq and metabolomics association analyses, SC was shown to have a protective impact through the JUNB and SOX5-related pathways. Metabolomic analysis revealed twenty-eight differentially expressed biomarkers. In addition, the detection of SC content in brain tissue using LC/MS revealed that SC had blood-brain barrier penetration. To investigate the mechanism, we established an in vitro BV2 cell oxygen-glucose deprivation/reperfusion (OGD/R) model and used siRNA as well as an inhibitor. The protective effects of SC were dependent on the JUNB and SOX5 to inhibit inflammation and apoptosis in microglia. Our findings revealed for the first that SC against IR injury by reducing inflammation and apoptosis while simultaneously acting as potential therapeutic lead compound for ischemic stroke.

BackgroundFacial seborrheic dermatitis (FSD), also called facial seborrheic eczema, is a common disease affecting both male and female patients worldwide. Tanshinone is the main bioactive component extracted from the Traditional Chinese Medicine Salvia miltiorrhiza Bunge, which is widely used in treating skin inflammatory diseases. It is necessary to evaluate the clinical evidence for tanshinone capsule treatment of FSD. This study aimed to evaluate the safety and effectiveness of tanshinone capsules combined with prednisone in the treatment of facial seborrheic dermatitis and to provide evidence for clinical practice.MethodsStudies were searched in PubMed, the Cochrane Library, the Chinese Biomedical Literature Database, the China National Knowledge Infrastructure, the Chinese Scientific Journal Database, and WanFang Database before October 2021. We also searched for randomized controlled clinical trials (RCT) of tanshinone capsules combined with prednisone on facial seborrheic dermatitis. The meta-analysis was conducted according to the guidelines of the Cochrane Handbook. Two reviewers regulated the research selection, data extraction, and risk of bias assessment, respectively, and a third reviewer was used for consulting when necessary. Review Manager Software 5.3 was used for meta-analysis.ResultsA total of 10 RCTs with 916 participants were included. Nine studies reported total effectiveness, five studies reported symptom score, seven studies reported adverse events, and four studies reported recurrence rate. The duration of treatment was 4 to 8 weeks. Combination therapy showed better clinical effects compared to the prednisone (OR: 5.82; 95% CI: 3.53, 9.59; p < 0.00001). Combination therapy could repair skin lesions (MD: −0.40; 95% CI: −0.51, −0.30; p < 0.00001), reduce skin erythema (MD: −0.58, 95% CI: −0.67, −0.49; p < 0.00001), relieve skin itch (MD: −0.70; 95% CI −0.77, −0.63; p < 0.00001), and desquamation score (MD: −0.64; 95% CI: −0.71, −0.56; p < 0.00001). Furthermore, combination therapy could reduce adverse events (OR: 0.46; 95% CI: 0.26, 0.84; p = 0.01) and control recurrence rate (OR: 0.22; 95% CI: 0.13, 0.36; p < 0.00001).ConclusionsCompared with prednisone, tanshinone capsules combined with prednisone may be effective in the treatment of facial seborrheic dermatitis. However, due to the high risk and ambiguity of bias in the included trials, the conclusion of this study must be interpreted carefully.

In order to increase the security and robustness of quantum images, this study combined the quantum DNA codec with quantum Hilbert scrambling to offer an enhanced quantum image encryption technique. Initially, to accomplish pixel-level diffusion and create enough key space for the picture, a quantum DNA codec was created to encode and decode the pixel color information of the quantum image using its special biological properties. Second, we used quantum Hilbert scrambling to muddle the image position data in order to double the encryption effect. In order to enhance the encryption effect, the altered picture was then employed as a key matrix in a quantum XOR operation with the original image. The inverse transformation of the encryption procedure may be used to decrypt the picture since all the quantum operations employed in this research are reversible. The two-dimensional optical image encryption technique presented in this study may significantly strengthen the anti-attack of quantum picture, according to experimental simulation and result analysis. The correlation chart demonstrates that the average information entropy of the RGB three channels is more than 7.999, the average NPCR and UACI are respectively 99.61% and 33.42%, and the peak value of the ciphertext picture histogram is uniform. It offers more security and robustness than earlier algorithms and can withstand statistical analysis and differential assaults.

A novel TrxR inhibitor Au-24 and its inhibitory ability to hepatocellular carcinoma in vitro and in vivo is reported herein. Au-24 can suppress HepG2 cells from proliferating by lowering mitochondrial membrane potential (MMP) and increasing reactive oxygen species (ROS) levels, resulting in oxidative stress, which causes DNA damage, autophagy, cell cycle arrest, and apoptosis. This compound can also affect the normal function of apoptosis, MAPK, PI3K/AKT/mTOR, NF-κB, STAT3 signaling pathways. In vivo experiments revealed that Au-24 inhibited HepG2 tumor growth more effectively than AA1 (chloro(triethylphosphine)gold(I)) by decreasing Ki67 and CD31 protein expression and promoting tumor cell apoptosis and necrosis lesions. As a result, Au-24 was found to be a promising candidate as a TrxR inhibitor for the treatment of hepatocellular carcinoma (HCC) in both in vivo and in vitro experiments.

Ischemic stroke (IS), as a leading cause of disability worldwide, affects intestinal bacterial communities and their metabolites, while recent discoveries have highlighted the importance of the intestinal microflora in the development of IS. Systematic investigations of complex intestinal bacterial communities and their metabolites during ischemic brain injury contribute to elucidate the promising therapeutic targets for IS. However, the associations between intestinal microbiota and related circulating metabolic processes in IS remained unclear. Hence, to identify the changed microflora and their metabolites in IS of NaoMaiTong (NMT), an effective clinical medication, we established the middle cerebral artery occlusion/reperfusion (MCAO/R) model using conventionalized and pseudo-germ-free (PGF) rats. Subsequently, we systematically screen the microflora and related metabolites changing in IS via an integrated approach of cecal 16S rRNA sequencing combined with plasma metabolomics. We found that NMT relied on intestinal flora to improve stroke outcome in conventionalized rats while the protection of NMT was reduced in PGF rats. Total 35 differential bacterial genera and 26 differential microbial metabolites were regulated by NMT. Furthermore, L-asparagine and indoleacetaldehyde were significantly negatively correlated with Lachnospiraceae_UCG.001 and significantly positively correlated with Lachnoclostridium. Indoleacetaldehyde also presented a negative correlation with Lactobacillus and Bifidobacterium. 2-Hydroxybutyric acid was strongly negatively correlated with Ruminococcus, Lachnospiraceae_UCG.001 and Lachnospiraceae_UCG.006. Creatinine was strongly negatively correlated with Akkermansia. In summary, the research provided insights into the intricate interaction between intestinal microbiota and metabolism of NMT in IS. We identified above differential bacteria and differential endogenous metabolites which could be as prebiotic and probiotic substances that can influence prognosis in stroke and have potential to be used as novel therapeutic targets or exogenous drug supplements.

Recent studies concerning products that originate from natural plants have sought to clarify active ingredients, which both explains the mechanisms of the function and aids in quality control during production. As a traditional functional plant, Curcumae Rhizoma (CR) has been proven to be effective in promoting blood circulation and removing blood stasis. However, the components that play a role in its huge compound library are still unclear. The present study aimed to develop a high-throughput screening method to identify thrombin inhibitors in CR and validate them by in vitro and in vivo experiments. The effect of CR on thrombin in HUVECs cells was determined by ELISA, then an affinity-ultrafiltration-UPLC-Q-Exactive Orbitrap/MS approach was applied. Agatroban and adenosine were used as positive and negative drugs respectively to verify the reliability of the established method. The in vitro activity of the compounds was determined by specific substrate S-2238. The in vivo effect of the active ingredients was determined using zebrafish. Molecular docking was used to understand the internal interactions between compounds and enzymes. ELISA results showed that CR had an inhibitory effect on thrombin. The screening method established in this paper is reliable, by which a total of 15 active compounds were successfully identified. This study is the first to report that C7, 8, and 11 have in vitro thrombin-inhibitory activity and significantly inhibit thrombosis in zebrafish models at a safe dose. Molecular docking studies were employed to analyze the possible active binding sites, with the results suggesting that compound 16 is likely a better thrombin inhibitor compared with the other compounds. Based on the affinity-ultrafiltration-UPLC-Q-Exactive Orbitrap/MS approach, a precisely targeted therapy method using bio-active compounds from CR might be successfully established, which also provides a valuable reference for targeted therapy, mechanism exploration, and the quality control of traditional herbal medicine.

Ulcerative colitis (UC) is considered an immune disease, which is related to the dysbiosis of intestinal microbiota and disorders of the host immune system and metabolism. Sophora flavescens Aiton has been used for the clinical treatment of UC in China and East Asia for thousands of years. It has many traditional prescriptions and modern preparations, and its curative effects are definite. We are the first to report that the flavonoids in Sophora flavescens (S. flavescens) Aiton EtOAc extract (SFE) could potentially attenuate the dextran sodium sulfate–induced UC in mice, which changed the current understanding of considering alkaloids as the only anti-UC pharmacological substances of S. flavescens Aiton. Based on the 16S rRNA gene sequencing and metabolomic analysis, it was found that the anti-UC effects of SFE were due to the regulation of gut microbiota, reversing the abnormal metabolisms, and regulation of the short-chain fatty acids synthesis. Notably, according to the interaction networks of specific bacteria and “bacteria and metabolites” co-expression network, the SFE could enrich the abundance of the commensal bacterium Lactobacillus, Roseburia, norank_f__Muribaculaceae, Anaerotruncus, Candidatus_Saccharimona, and Parasutterella, which are proposed as potentially beneficial bacteria, thereby playing vital roles in the treatment of UC.

In recent years, sparse representation theory and low-rank approximation model have been widely used in signal and image processing fields. In the study of natural image denoising, non-local similarity method can enhance the correlation of grouped image blocks, and a low rank prior is used to devise a bilateral sparse representation of the image matrix, consequently achieving the purpose of removing additive white Gaussian noise. However, problems such as how to select thresholds after a singular value shrinkage, and how to eliminate image artifacts in removing noise especially with high levels, have not been resolved. In this paper, a low rank adaptive singular value thresholding (ASVT) denoising algorithm based on singular value decomposition(SVD) is proposed. Our method uses random matrix and asymptotic matrix reconstruction theory to scientifically select the threshold of singular value thresholding. At the same time, a dual-domain filtering method is used to process the visual artifacts after image denoising by ASVT, which we call collaborative singular value thresholding (CSVT) algorithm. The experimental results show that the proposed algorithm has a certain improvement in subjective visual effects, and objective quantitative indicators compared with some related advanced denoising algorithms.

To reconstruct the missing or damaged parts of images from observed incomplete data, some traditional methods have been researched in recent years. The iterative denoising and backward projections(IDBP)algorithm with a simple parameter mechanism have been recently introduced, which solves the typical inverse problem by utilizing the existing 3D transform-domain collaborative filtering denoising algorithm(BM3D). While this algorithm has simple parameter tuning, the collaborative hard-thresholding applied to the 3D group is greatly restricted in the procedure of denoising. In this paper, we remedy this deficiency using an iteration reweighted shrinkage denoising method. First, the model is obtained by a Plug and Play(P&P) framework. Then, we solve the optimization problem by using a proposed denoising model based on low rank prior and reweighted shrinkage and obtain a closed-form solution. Finally, the closed-form solution is operated iteratively by using the adaptive backward projection technique. Utilizing this novel strategy, the proposed algorithm not only removes the image noise and effectively recovers the degraded image, but also preserves fine structure and texture information of the image. Experimental results indicate that the proposed algorithm is competitive with some state-of-the-art inpainting algorithms in terms of both numerical evaluation and visual quality.

We focus on the problem that the Grover algorithm is not suitable for the completely unknown proportion of target solutions. Considering whether the existing quantum classifier used by the current quantum neural network (QNN) to complete the classification task can solve the problem of the classical classifier, this paper proposes a binary quantum neural network classifical model based on an optimized Grover algorithm based on partial diffusion. Trial and error is adopted to extend the partial diffusion quantum search algorithm with the known proportion of target solutions to the unknown state, and to apply the characteristics of the supervised learning of the quantum neural network to binary classify the classified data. Experiments show that the proposed method can effectively retrieve quantum states with similar features. The test accuracy of BQM retrieval under the depolarization noise at the 20th period can reach 97% when the depolarization rate is 0.1. It improves the retrieval accuracy by about 4% and 10% compared with MSE and BCE in the same environment.

Device-to-device (D2D) technology enables direct communication between devices, which can effectively solve the problem of insufficient spectrum resources in 5G communication technology. Since the channels are shared among multiple D2D user pairs, it may lead to serious interference between D2D user pairs. In order to reduce interference, effectively increase network capacity, and improve wireless spectrum utilization, this paper proposed a distributed resource allocation algorithm with the joint of a deep Q network (DQN) and an unsupervised learning network. Firstly, a DQN algorithm was constructed to solve the channel allocation in the dynamic and unknown environment in a distributed manner. Then, a deep power control neural network with the unsupervised learning strategy was constructed to output an optimized channel power control scheme to maximize the spectrum transmit sum-rate through the corresponding constraint processing. As opposed to traditional centralized approaches that require the collection of instantaneous global network information, the algorithm proposed in this paper used each transmitter as a learning agent to make channel selection and power control through a small amount of state information collected locally. The simulation results showed that the proposed algorithm was more effective in increasing the convergence speed and maximizing the transmit sum-rate than other traditional centralized and distributed algorithms.

Communication between plants and interacting microorganisms requires functional molecule trafficking, which is essential for host defense and pathogen virulence. Extracellular vesicles (EVs) are single membrane-bound spheres that carry complex cargos, including lipids, proteins, and nucleic acids. They mediate cell-to-cell communication via the transfer of molecules between cells. Plant EVs have been isolated from many plant species and play a prominent role in immune system modulation and plant defense response. Recent studies have shown that plant EVs are emerging players in cross-kingdom regulation and contribute to plant immunity by mediating the trafficking of regulatory small RNA into pathogens, leading to the silencing of pathogen virulence-related genes. This review summarizes the current understanding of plant EV isolation technologies, the role of plant EVs in plant immunity, and the mechanism of plant EV biogenesis, as well as approaches for how these findings can be developed into innovative strategies for crop protection.

Background: Influences of fish oil supplementation on body weight and other cardiometabolic factors in overweight or obese children and adolescents remain not fully understood. We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the role of fish oil for these children.Methods: Relevant studies were obtained by search of PubMed, Embase, and Cochrane's Library databases. A random-effect model, which incorporates the potential heterogeneity of the included studies, was used to pool the results.Results: Twelve RCTs including 1,028 overweight or obese children and adolescents were included. Compared to control, fish oil supplementation significantly reduced body mass index [BMI, mean difference (MD): −0.96 kg/m2, 95% confidence interval (CI): −1.69 to −0.23, P = 0.01] but did not significantly reduce body weight or waist circumference (P = 0.68 and 0.76). Moreover, fish oil supplementation significantly reduced serum triglyceride (MD: −0.24 mmol/L, 95% CI: −0.40 to −0.08, P = 0.004) but did not significantly affect serum total cholesterol and high-density or low-density lipoprotein cholesterol (P = 0.83, 0.42, and 0.31, respectively). Additionally, fish oil supplementation significantly lowered systolic blood pressure (SBP, MD: −2.46 mmHg, 95% CI: −4.93 to −0.01, P = 0.04) but did not significantly change diastolic blood pressure (P = 0.22). Supplementation with fish oil did not significantly affect fasting plasma glucose (P = 0.33).Conclusions: In overweight or obese children and adolescents, supplementation with fish oil could reduce BMI, decrease serum triglyceride, and lower SBP, while serum cholesterol and fasting glucose may not be significantly affected.

Lactobacillus strains are considered safe and healthy probiotics for manufacturing “natural food” products; this is due to their ability to produce bioactive compounds that reduce the incidence of various human diseases. Lactobacillus paracasei TK1501 is a novel probiotic strain isolated from naturally fermented congee; and can produce a high yield of genistein, one of the most widely studied isoflavone aglycones with plenty of physiological functions. To better understand the molecular basis of isoflavone aglycones biosynthesis, the complete 2,942,538 bp genome of L. paracasei TK1501 was sequenced and assembled; a group of genes that are involved in isoflavone aglycones production were identified. Of note, a β-glucosidase was analyzed in the L. paracasei TK1501. Moreover, we also found that L. paracasei TK1501 could be used in soymilk fermentation; which would remarkably increase the contents of genistein, daidzein, and glycitein. This work was meaningful to the application of L. paracasei TK1501 and the molecular mechanism analysis of isoflavone aglycones biosynthesis in Lactobacillus strains.

Indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) is an ideal immunoassay method for large-scale screenings to detect mycotoxin contaminants. However, the matrix effect of complicated samples has always been challenging when performing immunoassays, as it leads to false-positive or negative results. In this study, convenient QuEChERS technology combined with optimizing the dilution solvent was ingeniously used to eliminate interference from the sample matrix to greatly improve the detection accuracy, and reliable ic-ELISAs for the two official tolerance levels of 60 and 500 μg/kg were developed to screen zearalenone (ZEN) in edible and medical coix seeds without any further correction. Then, the 122 batches of coix seeds were determined, and the positive rate was up to 97.54%. The contaminated distribution was further analyzed, and risk assessment was subsequently performed for its edible and medical purposes. The findings indicated that consumption of coix seeds with higher ZEN contamination levels may cause adverse health effects for both medical and edible consumption in the adult population; even under the condition of average contamination level, ZEN from coix seeds was the more prominent contributor to the total risk compared to other sources when used as food; thus, effective prevention and control should be an essential topic in the future.

BackgroundDengue fever is a mosquito-borne febrile illness. Southeast Asia experienced severe dengue outbreaks in 2019, and over 1000 cases had been reported in Jiangxi, a previously known low-epidemic region in China. However, the emergence of a dengue virus epidemic in a non-epidemic region remains unclear.MethodsWe enrolled 154 dengue fever patients from four hospitals in Jiangxi, from April 2019 to September 2019. Real-time PCR, NS1 antigen rapid test, and IgM, IgG tests were performed, and 14 samples were outsourced to be sequenced metagenomically.ResultsAmong the 154 cases, 42 were identified as imported and most of them returned from Cambodia. A total of 113 blood samples were obtained and 106 were identified as DENV-1, two as DENV-2, and five were negative through RT-PCR. All DENV-1 strains sequenced in this study were all classified to one cluster and owned a high similarity with a Cambodia strain isolated in 2019. The evolutionary relationships of amino acid were consistent with that of nucleotide genome result. The sequence-based findings of Jiangxi strains were consistent with epidemiological investigation.ConclusionEpidemiological analysis demonstrated that the emergence of dengue cases led to autochthonous transmission in several cities in Jiangxi, a low-epidemic region before. This study emphasized future prevention and control of dengue fever in both epidemic and non-epidemic regions.

ABSTRACT Plants deploy cell surface receptors known as pattern-recognition receptors (PRRs) that recognize non-self molecules from pathogens and microbes to defend against invaders. PRRs typically recognize microbe-associated molecular patterns (MAMPs) that are usually widely conserved, some even across kingdoms. Here, we report an oomycete-specific family of small secreted cysteine-rich (SCR) proteins that displays divergent patterns of sequence variation in the Irish potato famine pathogen Phytophthora infestans. A subclass that includes the conserved effector PcF from Phytophthora cactorum activates immunity in a wide range of plant species. In contrast, the more diverse SCR74 subclass is specific to P. infestans and tends to trigger immune responses only in a limited number of wild potato genotypes. The SCR74 response was recently mapped to a G-type lectin receptor kinase (G-LecRK) locus in the wild potato Solanum microdontum subsp. gigantophyllum. The G-LecRK locus displays a high diversity in Solanum host species compared to other solanaceous plants. We propose that the diversification of the SCR74 proteins in P. infestans is driven by a fast coevolutionary arms race with cell surface immune receptors in wild potato, which contrasts the presumed slower dynamics between conserved apoplastic effectors and PRRs. Understanding the molecular determinants of plant immune responses to these divergent molecular patterns in oomycetes is expected to contribute to deploying multiple layers of disease resistance in crop plants. IMPORTANCE Immune receptors at the plant cell surface can recognize invading microbes. The perceived microbial molecules are typically widely conserved and therefore the matching surface receptors can detect a broad spectrum of pathogens. Here we describe a family of Phytophthora small extracellular proteins that consists of conserved subfamilies that are widely recognized by solanaceous plants. Remarkably, one subclass of SCR74 proteins is highly diverse, restricted to the late blight pathogen Phytophthora infestans and is specifically detected in wild potato plants. The diversification of this subfamily exhibits signatures of a coevolutionary arms race with surface receptors in potato. Insights into the molecular interaction between these potato-specific receptors and the recognized Phytophthora proteins are expected to contribute to disease resistance breeding in potato.

Third body plant fibers have an important influence on the friction and wear properties of metal friction pairs. In this study, wheat straw powder with different particle sizes was prepared, and a pin-on-disk friction tester was employed to evaluate the friction and wear properties of the wheat straw powder third body on steel friction pairs under various conditions. The results show that the straw powder played an isolation role in the steel–steel friction pair, which reduced the contact area between the pin and the disc and thus reduced the friction coefficient. Compared with the large particle size powder, the small particle size powder became embedded in the friction interface or in the groove caused by wear, buffered the friction stress, and reduced the friction coefficient and wear. When lubricants such as lubricating oil or lubricating grease were added, the friction coefficient was significantly reduced. Under the influence of lubricant, the particle size of straw powder had no significant effect on the wear. The results of this study can provide a reference for the third body friction and wear properties of straw powder and the design of friction pairs for metal parts.

Abstract Emerging evidences have linked the gut microbiota to poultry physiology. Gut microbiota composition in Shaoxing ducks were profiled under different rearing conditions: raised on the litter floor and the plastic mesh floor. A total of 46 and 39 luminal content samples from the duodenum, ileum, and cecum of the ducks reared under the two conditions were analyzed by 16S rRNA gene amplicon sequencing analysis. Proteobacteria (48.66%), Proteobacteria (33.38%), and Bacteroidetes (55.35%) were the dominant phyla in the duodenum, ileum, and cecum of the ducks reared on the litter floor respectively, while Firmicutes (30.80%), Firmicutes (66.62%) and Bacteroidetes (47.15%) were the topmost phyla in the duodenum, ileum, and cecum of the ducks reared on the plastic mesh floor. Physiologically, the height of villi and the ratio of villus height to crypt depth in the ileum and duodenum were significantly greater in the ducks reared on plastic mesh floor. Furthermore, our results demonstrate that the gut microbiota was significantly associated with the duck phenotypes, such as chest depth and serum estradiol levels (p

Abstract Background With the increasing prevalence of metabolic syndrome (MS), there is a need to track and predict the development of MS. In this study, we established a Markov model to explore the natural history and predict the risk of MS. Methods A total of 21,777 Chinese individuals who had at least two consecutive health check-ups between 2010 and 2015 were studied. MS was defined using the Chinese Diabetes Society criteria. Twelve metabolic abnormal states (the no component state, four isolated component states, six 2-component states, and the MS state) were contained in each Markov chain. The transition probability was the mean of five probabilities for the transition between any two states in 2 consecutive years. Results The dyslipidemia or overweight/obesity components were most likely to initiate the progress of MS in individuals aged 18–49. However, for individuals over 50 years old, the most likely initiating component of MS was dyslipidemia or hypertension. People who initially had dyslipidemia were most likely to develop the combined state of dyslipidemia with overweight/obesity before the age of 50, but after 50 years of age, the state of dyslipidemia merged with hypertension was the most common. Subjects (with the exception of males over 50 years of age who initially had an isolated state of hyperglycemia) who initially had an isolated state of overweight/obesity, hypertension, or hyperglycemia were most likely to develop a combination of one of these initial states with dyslipidemia. Males who initially had isolated hyperglycemia tended to develop hypertension after age 50. There was a greater chance for subjects who initially had an isolated hyperglycemia state or 2-component state that contained hyperglycemia to develop MS within 10 years compared to those who initially had other abnormal metabolic states. Conclusions The occurrence of MS primarily began with overweight/obesity or dyslipidemia in people aged 18–49. However, for those over 50 years old, MS primarily initiated under the conditions of dyslipidemia or hypertension. When MS started under the conditions of overweight/obesity, hypertension or hyperglycemia, dyslipidemia tended to occur next. People who initially had isolated hyperglycemia or a 2-component state that contained hyperglycemia had a higher risk of developing MS than those with other initiating states.

Plantaricin Q7 is a broad-spectrum antimicrobial peptide produced by Lactobacillus plantarum Q7. The effects of plantaricin Q7 on Listeria monocytogenes and its biofilm were investigated. The results showed that plantaricin Q7 changed the cell membrane permeability and integrity of Listeria monocytogenes significantly. The extracellular lactate dehydrogenase activity increased from 156.74 U/L to 497.62 U/L, and the K+ concentration was increased rapidly from 0.02 g/L to 0.09 g/L. Furthermore, the flagellum motility of Listeria monocytogenes reduced and the relative adhesion rate decreased about 30% after treatment with plantaricin Q7. Meanwhile, the morphology and structure of Listeria monocytogenes cell and biofilm were damaged. These findings suggested that plantaricin Q7 exhibited significant inhibitory effects on not only Listeria monocytogenes cell but also its biofilm, which might be used as a natural and effective biological preservative for food storage.

This paper presents an adaptive, simple, and effective guidance approach for hypersonic entry vehicles with high lift-to-drag (L/D) ratios (e.g., hypersonic gliding vehicles). The core of the constrained guidance approach is a closed-form, easily obtained, and computationally efficient feedback control law that yields the analytic bank command based on the well-known quasi-equilibrium glide condition (QEGC). The magnitude of the bank angle command consists of two parts, i.e., the baseline part and the augmented part, which are calculated analytically and successively. The baseline command is derived from the analytic relation between the range-to-go and the velocity to guarantee the range requirement. Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. The inequality path constraints in the velocity-altitude space are translated into the velocity-dependent bounds for the magnitude of the bank angle based on the QEGC. The sign of the bank command is also analytically determined using an automated bank-reversal logic based on the dynamic adjustment criteria. Finally, a feasible three-degree-of-freedom (3DOF) entry flight trajectory is simultaneously generated by integrating with the real-time updated command. Because no iterations and no or few off-line parameter adjustments are required using almost all analytic processing, the algorithm provides remarkable simplicity, rapidity, and adaptability. A considerable range of entry flights using the vehicle data of the CAV-H is tested. Simulation results demonstrate the effectiveness and performance of the presented approach.