The coronavirus disease 2019 (COVID-19) pandemic poses a current world-wide public health threat. However, little is known about its hallmarks compared to other infectious diseases. Here, we report the single-cell transcriptional landscape of longitudinally collected peripheral blood mononuclear cells (PBMCs) in both COVID-19- and influenza A virus (IAV)-infected patients. We observed increase of plasma cells in both COVID-19 and IAV patients and XIAP associated factor 1 (XAF1)-, tumor necrosis factor (TNF)-, and FAS-induced T cell apoptosis in COVID-19 patients. Further analyses revealed distinct signaling pathways activated in COVID-19 (STAT1 and IRF3) versus IAV (STAT3 and NFκB) patients and substantial differences in the expression of key factors. These factors include relatively increase of interleukin ( IL ) 6R and IL6ST expression in COVID-19 patients but similarly increased IL-6 concentrations compared to IAV patients, supporting the clinical observations of increased proinflammatory cytokines in COVID-19 patients. Thus, we provide the landscape of PBMCs and unveil distinct immune response pathways in COVID-19 and IAV patients.

SARS-CoV-2 is the cause of the current global pandemic of COVID-19; this virus infects multiple organs, such as the lungs and gastrointestinal tract. The microbiome in these organs, including the bacteriome and virome, responds to infection and might also influence disease progression and treatment outcome. In a cohort of 13 COVID-19 patients in Beijing, China, we observed that the gut virome and bacteriome in the COVID-19 patients were notably different from those of five healthy controls. We identified a bacterial dysbiosis signature by observing reduced diversity and viral shifts in patients, and among the patients, the bacterial/viral compositions were different between patients of different severities, although these differences are not entirely distinguishable from the effect of antibiotics. Severe cases of COVID-19 exhibited a greater abundance of opportunistic pathogens but were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. We replicated our findings in a mouse COVID-19 model, confirmed virome differences and bacteriome dysbiosis due to SARS-CoV-2 infection, and observed that immune/infection-related genes were differentially expressed in gut epithelial cells during infection, possibly explaining the virome and bacteriome dynamics. Our results suggest that the components of the microbiome, including the bacteriome and virome, are affected by SARS-CoV-2 infections, while their compositional signatures could reflect or even contribute to disease severity and recovery processes.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and current treatments exhibit limited efficacy against advanced HCC. The majority of cancer-related deaths are caused by metastasis from the primary tumor, which indicates the importance of identifying clinical biomarkers for predicting metastasis and indicating prognosis. Patient-derived cells (PDCs) may be effective models for biomarker identification. In the present study, a wound healing assay was used to obtain 10 fast-migrated and 10 slow-migrated PDC cultures from 36 HCC samples. MicroRNA (miRNA) signatures in PDCs and PDC-derived exosomes were profiled by microRNA-sequencing. Differentially expressed miRNAs between the low- and fast-migrated groups were identified and further validated in 372 HCC profiles from The Cancer Genome Atlas (TCGA). Six exosomal miRNAs were identified to be differentially expressed between the two groups. In the fast-migrated group, five miRNAs (miR-140-3p, miR-30d-5p, miR-29b-3p, miR-130b-3p and miR-330-5p) were downregulated, and one miRNA (miR-296-3p) was upregulated compared with the slow-migrated group. Pathway analysis demonstrated that the target genes of the differentially expressed miRNAs were significantly enriched in the ‘focal adhesion’ pathway, which is consistent with the roles of these miRNAs in tumor metastasis. Three miRNAs, miR-30d, miR-140 and miR-29b, were significantly associated with patient survival. These findings indicated that these exosomal miRNAs may be candidate biomarkers for predicting HCC cell migration and prognosis and may guide the treatment of advanced HCC.

Hepatocellular carcinoma (HCC), a primary liver cancer, is closely associated with the gut microbiota. However, the role of gut fungi in the development of HCC remains unclear. The aim of this study was to explore the influence of intestinal Candida albicans on HCC. Here, We found that patients with HCC showed significantly decreased diversity of the gut mycobiome and increased abundance of C. albicans, compared to the patients with liver cirrhosis. The gavage of C. albicans in the WT models increased the tumor size and weight and influenced the plasma metabolome, which was indicated by alterations in 117 metabolites, such as L-carnitine and L-acetylcarnitine, and several KEGG enriched pathways, such as phenylalanine metabolism and citrate cycle. Moreover, the expression of nucleotide oligomerization domain-like receptor family pyrin domain containing 6 (NLRP6) in the intestinal tissues and primary intestinal epithelial cells of the WT mice interacted with C. albicans increased. Notably, the colonization of C. albicans had no effect on tumor growth in Nlrp6–/– mice. In conclusion, the abnormal colonization of C. albicans reprogrammed HCC metabolism and contributed to the progression of HCC dependent on NLRP6, which provided new targets for the treatment of HCC.

Aiming at the problem of device-to-device (D2D) communication mode selection and resource optimization under the joint resource allocation mode in the 5G communication network, a probabilistic integrated resource allocation strategy and a quasi-convex optimization algorithm based on channel probability statistical characteristics are proposed. This strategy and algorithm guarantee D2D. Communication maximizes total system throughput while maximizing access. The analysis results show that this algorithm can significantly optimize the total throughput of the system and reduce the communication interference between the users, which proves the rationality and efficiency of the communication model. The research results obtained in Muwen can provide a theoretical basis for analyzing more complex D2D communication systems and provide a numerical basis for designing heuristic algorithms.