The tumour microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) comprises multiple cell types, which promote tumour progression and modulate drug resistance and immune cell infiltrations via ligand-receptor (LR) interactions. However, the interactions, expression patterns, and clinical relevance of LR in the TME in ccRCC are insufficiently characterised. This study characterises the complex composition of the TME in ccRCC by analysing the single-cell sequencing (scRNA-seq) data of patients with ccRCC from the Gene expression omnibus database. On analysing the scRNA-seq data combined with the cancer genome atlas kidney renal clear cell carcinoma (TCGA-KIRC) dataset, 46 LR-pairs were identified that were significantly correlated and had prognostic values. Furthermore, a new molecular subtyping model was proposed based on these 46 LR-pairs. Molecular subtyping was performed in two ccRCC cohorts, revealing significant differences in prognosis between the subtypes of the two ccRCC cohorts. Different molecular subtypes exhibited different clinicopathological features, mutational, pathway, and immune signatures. Finally, the LR.score model that was constructed using ten essential LR-pairs that were identified based on LASSO Cox regression analysis revealed that the model could accurately predict the prognosis of patients with ccRCC. In addition, the differential expression of ten LR-pairs in tumour and normal cell lines was identified. Further functional experiments showed that CX3CL1 can exert anti-tumorigenic role in ccRCC cell line. Altogether, the effects of immunotherapy were connected to LR.scores, indicating that potential medications targeting these LR-pairs could contribute to the clinical benefit of immunotherapy. Therefore, this study identifies LR-pairs that could be effective biomarkers and predictors for molecular subtyping and immunotherapy effects in ccRCC. Targeting LR-pairs provides a new direction for immunotherapy regimens and prognostic evaluations in ccRCC.

A disintegrin and metalloprotease 10 (ADAM-10), a member of the ADAM protease family, has biological activities related to TNF-α activation, cell adhesion, and migration, among other functions. Macrophages are important immune cells that are involved in the inflammatory response of the body. ADAM-10 is involved in inflammatory responses, but the specific regulatory mechanisms are not fully understood. In this study, we investigated the regulatory mechanism of ADAM-10 in the lipopolysaccharide-promoted proliferation (LPS) of the macrophage inflammatory response. Differentially expressed or regulated proteins were identified in interfered ADAM-10 (sh ADAM-10) macrophages using tandem mass tag (TMT) proteomics. The changes and regulatory role of ADAM-10 during LPS-induced inflammatory response in normal, interfering, and overexpressing ADAM-10 (EX ADAM-10) cells were determined. Results indicated that ADAM-10 interference affected inflammation-related pathways and reduced matrix metalloproteinase 12 (MMP-12) protein levels, as identified by TMT proteomics. In normal cells, LPS decreased ADAM-10 gene expression, but promoted ADAM-10 secretion, MMP-12 and TNF-α gene expression, and MMP-12, iNOS, IL-10, and cyclinD1 protein expression. Additionally, ADAM-10 knockdown decreased macrophage viability in sh-ADAM-10 cells. Moreover, an MMP-12 inhibitor had no impact on the viability effect of LPS on cells or the expression of ADAM-10. iNOS expression decreased, whereas IL-10 expression increased after ADAM-10 depletion. ADAM-10 knockdown decreased MMP-12, iNOS, TNF-α, IL-1β, and FKN, while overexpression had an opposite effect. ADAM-10 overexpression further increased MMP-12, iNOS, and TNF-α gene expression in response to LPS. Cell viability was increased in EX ADAM-10 cells, and ADAM-10 secretion was further increased in the EX and LPS groups. Flow cytometry and immunofluorescence staining revealed that EX-ADAM 10 cells had increased iNOS expression, which acted as an IL-6 expression driver. In summary, we found that ADAM-10 is activated by LPS and positively participates in LPS-stimulated macrophage inflammatory responses by positively regulating MMP-12 during the inflammatory process.

Background: COVID-19 has a significant impact on dental medicine. The present study aims to overview dental-related research on COVID-19 by visual mapping method.Methods: We analyzed the publications in the “Dentistry Oral Surgery Medicine” category in the Web of Science core collection. On June 10, 2022, we conducted an advanced search using the items TS = (“Novel coronavirus 2019” or “COVID 19” or “Coronavirus disease 2019” or “2019-nCOV” or “SARS-CoV-2” or “coronavirus-2”) and WC = (“Dentistry Oral Surgery medicine”) to screen publications in the dental field that focus on COVID-19 or SARS-CoV-2. The contributions of authors, journals, institutions, and countries were described using Microsoft Excel 2010 and VOSviewer. The keywords co-occurring analysis and references analysis were visualized using VOSviewer and CiteSpace.Results: A total of 1,732 papers were identified between 2020 and 2022. The United States, the United Kingdom, and Brazil were three major contributors to this field. Univ São Paulo (Brazil) ranked first with 55 publications in this field. Martelli Junior, Hercilio from Universidade Jose do Rosario Vellano (Brazil) was the most prolific author with 19 publications. Oral Diseases and British Dental Journal were the two most productive journals. The central topics were dental practice and infection control, oral manifestation related to COVID-19, dental education and online learning, teledentistry, and mental health problems.Conclusion: The growth rate of publications regarding dental research on COVID-19 has risen sharply. Research topics shifted from “Dental practice and infection control, oral manifestation related to COVID-19” in 2020 to “Dental education and online learning, teledentistry, mental health problems,” which are three important research topics for the future.

Chronic hepatitis B virus (HBV) infection via perinatal transmission is common in the Asia-Pacific region, but related quasispecies (QS) characteristics are not yet defined. To investigate the homologous, full-length HBV QS after perinatal infection and their clinical implications, five pairs of mother-daughter patients with chronic HBV infection (one patient with liver cirrhosis, one with immune tolerance, and eight with chronic hepatitis) were included. Full-length HBV were amplified by PCR from serum samples before antiviral treatment and cloned; an average of 17 clones per sample were sequenced, and the QS complexities, diversities, and evolution patterns were analyzed. Full-length HBV sequence similarities within mother-daughter pairs were 91.3 to 98.3%. The QS complexities of full-length HBV were similar between mothers and daughters (median of 0.9734 compared to 0.9688,P> 0.05), as were the diversities (median of 3.396 × 10⁻³compared to 4.617 × 10⁻³substitutions/site,P> 0.05). However, the distribution patterns of QS complexities and diversities within specific genes were different, and QS genetic distances of the mothers were higher than those of daughters, both more evident in pairs with different antiviral responses and different immune phases or stages. The nucleotide substitution rate of full-length HBV was 14.388 × 10⁻⁵substitutions/site/year, whereas the preC/C gene rate was the highest. Mutations and indels were more common in clones from the mothers, which decreased the affinity of epitopes by 6- to 89-fold. The various genes from homologous HBV genomes evolved in different patterns despite numerically comparable full-length QS complexities and diversities. The different patterns may correlate with the immune stages of chronic HBV infection, which warrants further study.

Hepatocellular carcinoma (HCC) is a cancer caused by abnormal cell growth due to faulty signal transduction. Cells secrete tumor suppressor factors in response to potential carcinogenic signals, inducing cellular senescence (CS) as a countermeasure. However, accurately measuring CS levels in different types of tumors is challenging due to tumor heterogeneity and the lack of universal and specific CS markers. Machine learning has revealed unique molecular traits in HCC patients, leading to clinical advantages. More research is needed to understand senescence-related molecular features in these patients. In this study, the gene expression profile features of patients with HCC were analyzed by integrating single-cell RNA sequencing and bulk RNA-seq datasets from HCC samples. The analysis identified the senescence-related pathways exhibiting HCC specificity. Subsequently, genes from these pathways were used to identify senescence-related molecular subtypes in HCC, showing significant variations in biological and clinical attributes. An HCC-specific CS risk model developed in this study revealed substantial associations between the patients’ CS scores and prognosis grouping, clinical staging, immune infiltration levels, immunotherapy response, and drug sensitivity levels. Within the constructed model, G6PD was identified as a key gene, potentially serving as a senescence-related target in liver cancer. Molecular biology experiments demonstrated that overexpression of G6PD effectively promotes the proliferative, invasive, and migration capacities of HepG2 and SK-HEP-1 cells. In conclusion, this analysis offers a valuable framework for understanding senescence in HCC and introduces a new biomarker. These findings improve our understanding of senescence in HCC and have potential for future research.