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ObjectiveTo characterise gut microbiome in patients with hepatocellular carcinoma (HCC) and evaluate the potential of microbiome as non-invasive biomarkers for HCC.DesignWe collected 486 faecal samples from East China, Central China and Northwest China prospectively and finally 419 samples completed Miseq sequencing. We characterised gut microbiome, identified microbial markers and constructed HCC classifier in 75 early HCC, 40 cirrhosis and 75 healthy controls. We validated the results in 56 controls, 30 early HCC and 45 advanced HCC. We further verified diagnosis potential in 18 HCC from Xinjiang and 80 HCC from Zhengzhou.ResultsFaecal microbial diversity was increased from cirrhosis to early HCC with cirrhosis. Phylum Actinobacteria was increased in early HCC versus cirrhosis. Correspondingly, 13 genera including Gemmiger and Parabacteroides were enriched in early HCC versus cirrhosis. Butyrate-producing genera were decreased, while genera producing-lipopolysaccharide were increased in early HCC versus controls. The optimal 30 microbial markers were identified through a fivefold cross-validation on a random forest model and achieved an area under the curve of 80.64% between 75 early HCC and 105 non-HCC samples. Notably, gut microbial markers validated strong diagnosis potential for early HCC and even advanced HCC. Importantly, microbial markers successfully achieved a cross-region validation of HCC from Northwest China and Central China.ConclusionsThis study is the first to characterise gut microbiome in patients with HCC and to report the successful diagnosis model establishment and cross-region validation of microbial markers for HCC. Gut microbiota-targeted biomarkers represent potential non-invasive tools for early diagnosis of HCC.

The long non-coding RNA PVT1 (lncRNA PVT1) has been reported to act as an oncogenic regulator of several cancers. However, its expression and function in gallbladder cancer (GBC) remain largely unknown. In situ hybridization (ISH) and quantitative real-time PCR (qPCR) were performed to detect the expression of PVT1 and miR-143 in GBC tissues and cell lines. Immunohistochemistry (IHC) assays were performed to assess the expression of the hexokinase 2 (HK2) protein. The relationships among PVT1, miR-143 and HK2 were evaluated using dual-luciferase reporter, RNA immunoprecipitation (RIP) and biotin pull-down assays. The biological functions of PVT1, miR-143 and HK2 in GBC cells were explored with cell counting kit 8 (CCK-8), 5-ethynyl-20-deoxyuridine (EdU), colony formation, transwell, wound healing and glucose metabolism assays in vitro. For in vivo experiments, a xenograft model was used to investigate the effects of PVT1 and HK2 on GBC. PVT1 was upregulated in GBC tissues and cells and was positively associated with malignancies and worse overall survival. PVT1 knockdown inhibited cell proliferation, migration, and invasion in vitro and restrained tumor growth in vivo. Further studies demonstrated that PVT1 positively regulated HK2 expression via its competing endogenous RNA (ceRNA) activity on miR-143. Additionally, HK2 expression and function were positively correlated with PVT1. Furthermore, we observed that the PVT1/miR-143/HK2 axis promoted cell proliferation and metastasis by regulating aerobic glucose metabolism in GBC cells. The results of our study reveal a potential ceRNA regulatory pathway in which PVT1 modulates HK2 expression by competitively binding to endogenous miR-143 in GBC cells, which may provide new insights into novel molecular therapeutic targets for GBC.

ObjectiveTo characterise the oral microbiome, gut microbiome and serum lipid profiles in patients with active COVID-19 and recovered patients; evaluate the potential of the microbiome as a non-invasive biomarker for COVID-19; and explore correlations between the microbiome and lipid profile.DesignWe collected and sequenced 392 tongue-coating samples, 172 faecal samples and 155 serum samples from Central China and East China. We characterised microbiome and lipid molecules, constructed microbial classifiers in discovery cohort and verified their diagnostic potential in 74 confirmed patients (CPs) from East China and 37 suspected patients (SPs) with IgG positivity.ResultsOral and faecal microbial diversity was significantly decreased in CPs versus healthy controls (HCs). Compared with HCs, butyric acid-producing bacteria were decreased and lipopolysaccharide-producing bacteria were increased in CPs in oral cavity. The classifiers based on 8 optimal oral microbial markers (7 faecal microbial markers) achieved good diagnostic efficiency in different cohorts. Importantly, diagnostic efficacy reached 87.24% in the cross-regional cohort. Moreover, the classifiers successfully diagnosed SPs with IgG antibody positivity as CPs, and diagnostic efficacy reached 92.11% (98.01% of faecal microbiome). Compared with CPs, 47 lipid molecules, including sphingomyelin (SM)(d40:4), SM(d38:5) and monoglyceride(33:5), were depleted, and 122 lipid molecules, including phosphatidylcholine(36:4p), phosphatidylethanolamine (PE)(16:0p/20:5) and diglyceride(20:1/18:2), were enriched in confirmed patients recovery.ConclusionThis study is the first to characterise the oral microbiome in COVID-19, and oral microbiomes and lipid alterations in recovered patients, to explore their correlations and to report the successful establishment and validation of a diagnostic model for COVID-19.

Emerging evidence has shown that microRNA-126 (miR-126) is aberrantly downregulated and plays a vital role in carcinogenesis in various cancers, including HCC. However, the underlying biological mechanisms of miR-126 in HCC are still largely unknown. In present study, we found that miR-126 was downregulated both in HCC tissues and cell lines. Low expression level of miR-126 was associated with poor overall survival (OS), late TNM stage and the presence of recurrence. Overexpression of miR-126 significantly decreased cell proliferation, metastasis and promoted apoptosis in vitro. Additional, high miR-126 expression reduced the tumor growth in vivo. Further we discovered that PLK (polo-like kinases)-4, a critical regulator in cell cycle, was a target of miR-126. PLK-4 overexpression could rescue the inhibitory effects of miR-126 on cell proliferation and invasion. Moreover, PLK-4 mRNA and protein levels were significantly upregulated in HCC tissues and positively associated with malignancies and poor OS. Knockdown PLK-4 significantly inhibited cell proliferation, invasion and promoted cell apoptosis in vitro whereas decreased tumor growth in vivo. More importantly, bioinformatics analysis combined with validation experiments in vitro and in vivo showed that activation of the ATR/CHEK1 pathway was involved in the oncogenic functions of PLK4 in HCC. We also validated that PLK4 could directly interact with ATR through CoIP assay. Taken together, we demonstrate that miRNA-126/PLK-4 axis is critical for tumorigenesis and progression of HCC, and the newly identified PLK-4/ATR/CHEK1 pathway may be a potential therapeutic target for HCC treatment.

Hepatic fibrosis, a critical progression in liver disease, has been widely studied. While the activation of stellate cells and the accumulation of extracellular matrix components are recognized as key mechanisms, additional research is necessary to uncover further complexities. Recent investigations underscore the pivotal role of post-translational modifications (PTMs) in hepatic fibrosis. This study explores nine PTMs—methylation, acetylation, SUMOylation, Neddylation, phosphorylation, crotonylation, glycosylation, lactylation, and ubiquitination—each implicated in the pathogenesis of hepatic fibrosis. Furthermore, six classes of drugs—ACC inhibitors, ASK1 inhibitors, Akt activators, FXR agonists, PTP1B inhibitors, and HDAC inhibitors—are reviewed for their therapeutic potential in targeting PTMs to treat hepatic fibrosis.

: Gastric cancer (GC) is a primary cause of cancer-associated mortality worldwide. N6-methyladenosine (m6A) is one of the most common RNA modifications that involves in the progression of numerous cancers. However, the expression status and function of m6A-related genes in gastric cancer is still not well understood. The current study is aimed to investigate the expression status and determinate prognostic value of m6A-related genes in gastric cancer. : m6A-asssociated gene expression was evaluated via analyzing the expression data of GC patients from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The protein expression levels of m6A-associated molecules were further validated by immunohistochemical (IHC) staining data from GC tissue microarray (TMA) cohort and Human Protein Atlas (HPA) database. Kaplan-Meier analysis was performed to assess the prognostic value of m6A-associated genes in gastric cancer. Risk score model was established by lasso COX regression analysis and its prognostic predicted efficiency was assessed by the receiver-operator characteristic (ROC) curve. Cox regression analyses were used for exploring risk factors related to GC patient prognosis. : Most of m6A-related genes were upregulated at both mRNA and protein levels in gastric cancer tissues compared with that in normal gastric tissues. The expression levels of m6A-related genes were associated with clinicopathological features including race, age and TNM stage. High expression of WTAP and FTO predicted poor prognosis of GC patients. Survival analysis demonstrated that patients with high-risk scores had worse overall survival (OS) and ROC curves suggested the prediction performance for gastric patients. Moreover, Cox regression analyses indicated that m6A risk model score was a prognostic factor for OS and FTO upregulation might be a potential independent prognostic factor for recurrence-free survival (RFS) in gastric cancer patients. : m6A-related genes were dysregulated in GC and were closely associated with prognosis of GC patients. FTO might serve as a novel prognostic biomarker for gastric cancer, while the m6A-related risk score might be informative for risk assessment and prognostic stratification.

How to comprehensively explore, improve and deploy multimedia social networks (MSNs) has become a hot topic in the era of emerging pervasive mobile multimedia. More and more MSNs offer a great number of convenient tools, services, and applications for multimedia contents including video and audio that users share willingly and on demand. However, concerns with digital rights management (DRM)-oriented multimedia security, as well as the efficiency of multimedia usage and sharing are meanwhile intensified due to easier distribution and reproduction of multimedia content in a wide range of social networks. The paper proposes a comprehensive framework for multimedia social network, and realized a cross-platform MSN prototype system, named as CyVOD, to support two kinds of DRM modes. The proposed framework effectively protects copyrighted multimedia contents against piracy, and supports a more efficient recommendation system for its better handling of the tradeoff between multimedia security and ease of use.

Corona Virus Disease (COVID-19) has become a global public health crisis, and the Omicron variant has rapidly taken over as soon as it was detected Serum circulating metabolites can provide extensive insights into the pathogenesis and diagnosis of many diseases. We included 336 omicron variant cases (OC), 216 recovered cases (RC), and 380 healthy controls (HC) for untargeted metabolomics analysis and analyzed their serum metabolic profiles by liquid chromatography-tandem mass spectrometry. Principal component analysis, orthogonal partial least squares discriminant analysis, t-test analysis and false discovery rate were used to characterize the serum metabolites of OC and RC. In addition, a noninvasive diagnostic model for OC was developed using Receiver operating characteristic analysis. Finally, a correlation analysis was performed using data from our published articles. The results showed that compared with HC, five metabolites, including DL-stachydrine, D-(+)-pipecolinic acid, furazolidone, L-arginine and 5α-dihydrotestosterone glucuronide were significantly elevated and one metabolite, prenylcysteine, was significantly decreased in the serum of OC, and that the increase in L-arginine and the decrease in prenylcysteine led to impaired urea cycling and a high risk of developing atherosclerosis, respectively. These metabolites were not fully restored to healthy human levels in recovered cases. In addition, we constructed a noninvasive diagnostic model for distinguishing Omicron variant patients from healthy individuals based on the six differential metabolites, and achieved high diagnostic efficacy in both the discovery and validation cohorts. Finally, the results of the correlation analysis showed a strong correlation between the alterations in the oropharyngeal microbiome and serum metabolome and the clinical indicators in the omicron variant cases. This study was the first to characterize serum metabolites in OC and RC based on a large clinical cohort, and successfully constructed and validated a noninvasive diagnostic model for Omicron variant patients.

Oropharyngeal microbiomes play a significant role in the susceptibility and severity of COVID-19, yet the role of these microbiomes play for the development of COVID-19 Omicron variant have not been reported. A total of 791 pharyngeal swab samples were prospectively included in this study, including 297 confirmed cases of Omicron variant (CCO), 222 confirmed case of Omicron who recovered (CCOR), 73 confirmed cases of original strain (CCOS) and 199 healthy controls (HC). All samples completed MiSeq sequencing. The results showed that compared with HC, conditional pathogens increased in CCO, while acid-producing bacteria decreased. Based on six optimal oropharyngeal operational taxonomy units (OTUs), we constructed a marker microbial classifier to distinguish between patients with Omicron variant and healthy people, and achieved high diagnostic efficiency in both the discovery queue and the verification queue. At same time, we introduced a group of cross-age infection verification cohort and Omicron variant subtype XBB.1.5 branch, which can be accurately distinguished by this diagnostic model. We also analyzed the characteristics of oropharyngeal microbiomes in two subgroups of Omicron disease group—severity of infection and vaccination times, and found that the change of oropharyngeal microbiomes may affect the severity of the disease and the efficacy of the vaccine. In addition, we found that some genera with significant differences gradually increased or decreased with the recovery of Omicron variant infection. The results of Spearman analysis showed that 27 oropharyngeal OTUs were closely related to 6 clinical indexes in CCO and HC. Finally, we found that the Omicron variant had different characterization of oropharyngeal microbiomes from the original strain. Our research characterizes oropharyngeal microbiomes of Omicron variant cases and rehabilitation cases, successfully constructed and verified the non-invasive diagnostic model of Omicron variant, described the correlation between microbial OTUs and clinical indexes. It was found that the infection of Omicron variant and the infection of original strain have different characteristics of oropharyngeal microbiomes.

As we all known, estimating the proportion of passenger route choice is of great significance in almost every aspect of urban rail transit control system, including passenger allocation, fare clearing and flow control strategies. Existing researches only pay attention to the route choice through travel time, but usually ignore the influence in different periods of the day. Therefore, this paper proposes a novel estimation method for the proportion of passenger route choice in different periods. Firstly, by introducing the normalized value of passenger flow and the standard coefficient of peak passenger flow, the train operation time is divided into peak and flat periods. Secondly, the travel time distribution of each route can be obtained by estimating the expected value and standard deviation of passenger travel time in each different period. The Naïve Bayes algorithm is further employed to realize the identification of the proportion of passenger route choices. Finally, this proposed algorithm is applied to Hangzhou Metro. The result shows that by using the segmented estimation, the error can be reduced by more than 60% compared with the whole-day experiment, which indicates the superiority of the method.