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.

The clinical application of chemotherapy is impeded by the unsatisfactory efficacy and severe side effects. Chemodynamic therapy (CDT) has emerged as an efficient strategy for cancer treatment utilizing Fenton chemistry to destroy cancer cells by converting endogenous H2O2 into highly toxic reactive oxygen species. Apart from the chemotherapeutic effect, cisplatin is able to act as an artificial enzyme to produce H2O2 for CDT through cascade reactions, thus remarkably improving the anti‐tumor outcomes. Herein, an organic theranostic nanomedicine (PTCG NPs) is constructed with high loading capability using epigallocatechin‐3‐gallate (EGCG), phenolic platinum(IV) prodrug (Pt‐OH), and polyphenol modified block copolymer (PEG‐b‐PPOH) as the building blocks. The high stability of PTCG NPs during circulation stems from their strong metal–polyphenol coordination interactions, and efficient drug release is realized after cellular internalization. The activated cisplatin elevates the intracellular H2O2 level through cascade reactions. This is further utilized to produce highly toxic reactive oxygen species catalyzed by an iron‐based Fenton reaction. In vitro and in vivo investigations demonstrate that the combination of chemotherapy and chemodynamic therapy achieves excellent anticancer efficacy. Meanwhile, systemic toxicity faced by platinum‐based drugs is avoided through this nanoformulation. This work provides a promising strategy to develop advanced nanomedicine for cascade cancer therapy.

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, leading to a large global cancer burden. Hepatocyte growth factor (HGF) and its highaffinity receptor, mesenchymal epithelial transition factor (c-Met), are closely related to the onset, progression, and metastasis of multiple tumors. The HGF/c-Met axis is involved in cell proliferation, movement, differentiation, invasion, angiogenesis, and apoptosis by activating multiple downstream signaling pathways. In this review, we focus on the function of the HGF/c-Met axis in HCC. The HGF/c-Met axis promotes the onset, proliferation, invasion, and metastasis of HCC. Moreover, it can serve as a biomarker for diagnosis and prognosis, as well as a therapeutic target for HCC. In addition, it is closely related to drug resistance during HCC treatment.

Background: Osteosarcoma (OS) is the most common primary bone tumor. The disease has a poor prognosis due to the delay in the diagnosis and the development of metastasis. N6-Methyladenosine (m6A)-related regulators play an essential role in various tumors. In this study, a comprehensive analysis was conducted to elucidate the relationship between the expression profiles of m6A-related molecules and the clinical outcome of OS patients. Materials and Methods: Public genome datasets and a tissue microarray (TMA) cohort were used to analyze the mRNA and protein expression levels of m6A regulators. Next, immunofluorescence (IF) analysis was used to determine the subcellular localization of m6A-related molecules. Kaplan-Meier and Cox regression analyses were performed to confirm the prognostic value of m6A-related molecules in OS. A comprehensive bioinformatic analysis was conducted to identify the potential molecular mechanisms mediated by m6A modification in OS. Results: We found that m6A-related regulator expression was dysregulated in OS tissues, especially in metastatic tumor tissues. Low expression of METTL3, METTL14, and YTHDF2 and high expression of KIAA1429 and HNRNPA2B1 were significantly associated with poor prognosis in the TMA cohort. Simultaneously, the genome metacohort analysis revealed that low expression of FTO and METTL14 and high expression of METTL3, HNRNPA2B1, and YTHDF3 were associated with poor prognosis in OS. Cox regression analysis showed that HNRNPA2B1 might be an independent risk factor for OS. Bioinformatic analysis indicated that m6A regulators might be involved in OS progression through humoral immune response and cell cycle pathways. Conclusion: M6A-related regulators are frequently dysregulated and correlate with metastasis and prognosis in OS. M6A-related regulators may serve as novel therapeutic targets and prognostic biomarkers for OS.

Respiratory tract microbiome is closely related to respiratory tract infections, while characterization of oropharyngeal microbiome in recovered coronavirus disease 2019 (COVID-19) patients is not studied. Herein, oropharyngeal swabs are collected from confirmed cases (CCs) with COVID-19 (73 subjects), suspected cases (SCs) (36), confirmed cases who recovered (21), suspected cases who recovered (36), and healthy controls (Hs) (140) and then completed MiSeq sequencing. Oropharyngeal microbial 𝜶-diversity is markedly reduced in CCs versus Hs. Opportunistic pathogens are increased, while butyrate-producing genera are decreased in CCs versus Hs. The classifier based on eight optimal microbial markers is constructed through a random forest model and reached great diagnostic efficacy in both discovery and validation cohorts. Notably, the classifier successfully diagnosed SCs with positive IgG antibody as CCs and is demonstrated from the perspective of the microbiome. Importantly, several genera with significant differences gradually increase and decrease along with recovery from COVID-19. Forty-four oropharyngeal operational taxonomy units (OTUs) are closely correlated with 11 clinical indicators of SARS-CoV-2 infection and Hs based on Spearman correlation analysis. Together, this research is the first to characterize oropharyngeal microbiota in recovered COVID-19 cases and suspected cases, to successfully construct and validate the diagnostic model for COVID-19 and to depict the correlations between microbial OTUs and clinical indicators.

Objective: The intestinal microbiome is associated with various autoimmune diseases. Regional difference is the main influencing factor of intestinal microbial difference. This study aimed to identify the differences in fecal microbiome between autoimmune hepatitis (AIH) patients and healthy controls (HCs) in Central China, and to validate the efficacy of fecal microbiome as a diagnostic tool for AIH. Design: We collected 115 fecal samples from AIH patients (N = 37) and HCs (N = 78) in Central China and performed gene sequencing. Fecal microbiomes were characterized and microbial markers for AIH were identified. Results: Fecal microbial diversity showed a downward trend in AIH compared with HCs. Fecal microbial communities significantly differed between both groups. At the phylum level, Verrucomicrobia abundance was significantly increased, while Lentisphaerae and Synergistetes were significantly decreased in the AIH patients vs. the HCs. Compared to the HCs, 15 genera, including Veillonella, Faecalibacterium, and Akkermansia, were enriched, while 19 genera, such as Pseudobutyrivibrio, Lachnospira, and Ruminococcaceae, were decreased in the AIH patients. Ten genera, including Veillonella, Faecalibacterium, and Akkermansia, predominated in the AIH patients. Five microbial biomarkers were deemed optimal diagnostic tools for AIH. The probability of disease was significantly increased in AIH group vs. HCs, achieving 83.25% value of area under the curve. Lou et al. Fecal Microbiome in Autoimmune Hepatitis Conclusion: We present the characteristics of AIH patients in Central China for the first time. Five microbial biomarkers, including Lachnospiraceae, Veillonella, Bacteroides, Roseburia, and Ruminococcaceae, achieved a high potential distinguishing AIH patients from HCs.

Background Due to the outbreak and rapid spread of coronavirus disease 2019 (COVID-19), more than 160 million patients have become convalescents worldwide to date. Significant alterations have occurred in the gut and oral microbiome and metabonomics of patients with COVID-19. However, it is unknown whether their characteristics return to normal after the 1-year recovery. Methods We recruited 35 confirmed patients to provide specimens at discharge and one year later, as well as 160 healthy controls. A total of 497 samples were prospectively collected, including 219 tongue-coating, 129 stool and 149 plasma samples. Tongue-coating and stool samples were subjected to 16S rRNA sequencing, and plasma samples were subjected to untargeted metabolomics testing. Results The oral and gut microbiome and metabolomics characteristics of the 1-year convalescents were restored to a large extent but did not completely return to normal. In the recovery process, the microbial diversity gradually increased. Butyric acid-producing microbes and Bifidobacterium gradually increased, whereas lipopolysaccharide-producing microbes gradually decreased. In addition, sphingosine-1-phosphate, which is closely related to the inflammatory factor storm of COVID-19, increased significantly during the recovery process. Moreover, the predictive models established based on the microbiome and metabolites of patients at the time of discharge reached high efficacy in predicting their neutralizing antibody levels one year later. Conclusions This study is the first to characterize the oral and gut microbiome and metabonomics in 1-year convalescents of COVID-19. The key microbiome and metabolites in the process of recovery were identified, and provided new treatment ideas for accelerating recovery. And the predictive models based on the microbiome and metabolomics afford new insights for predicting the recovery situation which benefited affected individuals and healthcare.

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