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Patients with chronic pain frequently suffer from anxiety symptoms. It has been well established that gut microbiota is associated with the pathogenesis of pain and anxiety. However, it is unknown whether the gut microbiota, particularly the specific bacteria, play a role in the comorbidity of chronic pain and anxiety.Chronic inflammatory pain was induced in mice by a single injection of complete Freund's adjuvant (CFA). Mice were then separated into anxiety-susceptible and anxiety-resilient phenotypes by hierarchical clustering analysis of behaviors. Fecal samples were collected to perform 16S rRNA gene sequencing. Chronic diazepam intervention served as a therapeutic strategy and its effect on the composition of gut microbiota was also determined.α-Diversity and β-diversity both showed significant differences among the groups. A total of 12 gut bacteria were both altered after CFA injection and reversed by chronic diazepam treatment. More importantly, the pain hypersensitivity and anxiety-like behaviors were relieved by chronic diazepam treatment. Interestingly, we also found that Desulfovibrio was increased in anxiety-resilient group compared to control and anxiety-susceptible groups.Abnormal composition of gut microbiota plays an essential role in chronic pain as well as in anxiety. Besides, the increased level of Desulfovibrio in anxiety-resilient mice indicated its therapeutic effects on the comorbidity of pain and anxiety. Collectively, targeting gut microbiota, especially increasing the Desulfovibrio level, might be effective in the alleviation of chronic pain-anxiety comorbidity.

Lymph node metastasis (LNM) is considered as an adverse prognostic indicator for cancer patients. Preoperative knowledge of LNM is valuable for pretreatment decision making. Here, we sought to develop and validate an LNM signature for preoperative prediction of LNM in patients with head and neck squamous cell carcinoma (HNSCC).By studying single cell RNA-sequencing data (scRNA-seq), differentially expressed mRNA were selected and analyzed through univariate logistic regression and least absolute shrinkage and selection operator (LASSO) to identify an LNM signature. Multivariate logistic regression was utilized to establish an LNM nomogram incorporating LNM signature and T-classification.The LNM signature was significantly associated with lymph node status and prognosis. The LNM signature and LNM nomogram displayed a robust predictive effect.Our study reveals that LNM signature is a powerful biomarker for preoperative prediction of LNM in patients with HNSCC, which may be effective to realize individualized outcome prediction.