The preventive effect of photocrosslinked Hep/GelMA hydrogel loaded with PRF on MRONJ.

BACKGROUND: Medication-related osteonecrosis of the Jaw (MRONJ) is a rare but severe side effect in patients treated with medications such as Bisphosphonates (BPs). Its pathophysiological mechanism needs to be more precise. Establishing preventive measures and treatment standards is necessary. This study aimed to develop a composite hydrogel scaffold constituted by methacrylated gelatin (GelMA), methacrylated heparin (HepMA) and PRF, and investigate its potential application value in the prevention of MRONJ. METHODS: GelMA, HepMA, and PRF were prepared using specific ratios for hydrogel scaffolds. Through mechanical properties and biocompatibility analysis, the release rate of growth factors and the ability to promote bone differentiation in vitro were evaluated. To explore the healing-enhancing effects of hydrogels in vivo, the composite hydrogel scaffold was implanted to the MRONJ rat model. Micro-computed tomography (Micro-CT) and histological examination were conducted to evaluate the bone morphology and tissue regeneration. RESULTS: The Hep/GelMA-PRF hydrogel improved the degradation rate and swelling rate. It was also used to control the release rate of growth factors effectively. In vitro, the Hep/GelMA-PRF hydrogel was biocompatible and capable of reversing the inhibitory effect of zoledronic acid (ZOL) on the osteogenic differentiation of MC3T3-E1s. In vivo, the micro-CT analysis and histological evaluation demonstrated that the Hep/GelMA-PRF group exhibited the best tissue reconstruction. Moreover, compared to the ZOL group, the expression of osteogenesis proteins, including osteocalcin (OCN), type collagen I (Col I), and bone morphogenetic protein-2 (BMP-2) in the Hep/GelMA-PRF group were all significantly upregulated (P < 0.05). CONCLUSIONS: The Hep/GelMA-PRF hydrogel scaffold could effectively control the release rate of growth factors, induce osteogenic differentiation, reduce inflammation, and keep a stable microenvironment for tissue repair. It has potential application value in the prevention of MRONJ.

Bioinformatics Analysis to Identify Intersection Genes, Associated Pathways and Therapeutic Drugs between COVID-19 and Oral Candidiasis.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a serious threat to human health. Oral candidiasis (OC) may be one of the causes of morbidity in severe COVID-19 patients. However, there is currently no treatment for oral candidiasis and COVID-19 (OC/COVID-19). The purpose of this study was to use text mining and data analysis to investigate the target genes for treatment and explore potential therapeutic drugs for OC/COVID-19. METHODS: We used the text mining tool pubmed2ensembl to detect genes associated with OC, and the dataset GSE164805 was used for the data analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on two intersection genes using the Database of Annotation, Visualization and Integrated Discovery (DAVID) platform. The protein-protein interaction (PPI) networks were constructed by STRING software, and gene module analysis was performed using Molecular Complex Detection (MCODE), a plug-in in Cytoscape. The most significant genes were selected as hub genes and their functions and pathways were analyzed using Metascape. We revealed the upstream pathway activity of the hub genes. The drug-gene interaction database (DGIdb) and the traditional Chinese medicines integrated database (TCMID) were used to discover potential drugs for the treatment of OC/COVID-19. RESULTS: The analysis indicated that there were 2869 differentially expressed genes (DEGs) in GSE164805. We identified 161 unique genes associated with oral candidiasis through text mining. A total of 20 intersection genes were identified as the therapeutic targets for OC/COVID-19. Based on the bioinformatics analysis, nine genes (TNF, IL1B, IFNG, CSF2, ELANE, CCL2, MMP9, CXCR4, and IL1A) were identified as hub genes that were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, AGE-RAGE signaling pathway in diabetic complications and NOD-like receptor signaling pathway. We identified four of the nine genes that target five existing drugs, including BKT140, mavorixafor, sivelestat, canakinumab, and rilonacept. Furthermore, twenty herb ingredients were also screened as potential drugs. CONCLUSION: In this study, TNF, IL1B, IFNG, CSF2, ELANE, CCL2, MMP9, CXCR4, and IL1A were potentially key genes involved in the treatment of OC/COVID-19. Taken together five drugs and twenty herb ingredients were identified as potential therapeutic agents for OC/COVID-19 treatment and management.

Cuproptosis-Related lncRNAs are Biomarkers of Prognosis and Immune Microenvironment in Head and Neck Squamous Cell Carcinoma.

Background: Cuproptosis is a new type of cell death that induces protein toxic stress and eventually leads to cell death. Hence, regulating cuproptosis in tumor cells is a new therapeutic approach. However, studies on cuproptosis-related long noncoding RNA (lncRNA) in head and neck squamous cell carcinoma (HNSC) have not been found. This study aimed to explore the cuproptosis-related lncRNAs prognostic marker and their relationship to immune microenvironment in HNSC by using bioinformatics methods. Methods: RNA sequencing, genomic mutations, and clinical data of TCGA_HNSC were downloaded from The Cancer Genome Atlas. HNSC patients were randomly assigned to either a training group or a validation cohort. The least absolute shrinkage and selection operator Cox regression and multivariate Cox regression models were used to determine the prognostic model in the training cohort, and its independent prognostic effect was further confirmed in the validation and entire cohorts. Results: Based on previous literature, we collected 19 genes associated with cuproptosis. Afterward, 783 cuproptosis-related lncRNAs were obtained through coexpression. Cox model revealed and constructed eight cuproptosis-related lncRNAs prognostic marker (AL132800.1, AC090587.1, AC079160.1, AC011462.4, AL157888.1, GRHL3-AS1, SNHG16, and AC021148.2). Patients were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier survival curve revealed that the overall survival between the high- and low-risk groups was statistically significant. The receiver operating characteristic curve and principal component analysis demonstrated the accurate prognostic ability of the model. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor. In addition, we used multivariate Cox regression to establish a nomogram of the predictive power of prognostic markers. The tumor mutation burden showed significant differences between the high- and low-risk groups. HNSC patients in the high-risk group responded better to immunotherapy than those in the low-risk group. We also found that risk scores were significantly associated with drug sensitivity in HNSC. Conclusion: In summary, our study identified eight cuprotosis-related lncRNAs signature of HNSC as the prognostic predictor, which may be promising biomarkers for predicting the benefit of HNSC immunotherapy as well as drug sensitivity.

Association between levels of blood trace minerals and periodontitis among United States adults.

Aim: Evidence linking trace minerals and periodontitis is limited. To investigate the relationship between trace minerals (selenium, manganese, lead, cadmium, and mercury) and periodontitis, data from the National Health and Nutrition Examination Survey (NHANES) were analyzed after accounting for potential confounding factors. No known studies have explored the relationship between these five trace minerals and periodontitis. Materials and methods: A total of 4,964 participants who had undergone a full-mouth periodontal examination and laboratory tests for five trace minerals were studied in a cross-sectional study. Clinical attachment loss (CAL) and periodontitis grading were used to measure periodontitis severity. Linear and logistic regression models were used to evaluate the association between trace minerals and periodontitis. Further subgroup analyses were performed. Results: Blood lead and cadmium levels were positively associated with mean CAL, and blood selenium was negatively associated with mean CAL; however, blood mercury, blood manganese, and mean CAL were not significantly associated. The association between trace minerals and mean CAL was more significant in males, the elderly, and patients with diabetes. There was a threshold effect between blood cadmium levels and mean CAL. Among the Black population, the relationship between blood cadmium levels and mean CAL followed an inverted U-shaped curve. There was a saturation effect in the study of blood lead in people aged 45-59 years old. Conclusion: Our study highlighted that blood selenium, lead, and cadmium levels were significantly associated with periodontitis in a nationally representative sample of United States adults.