The structural integrity of a dentin matrix that has been demineralized by the clinical use of etchants or calcium-depleting endodontic irrigants, such as endodontic ethylenediaminetetraacetic acid (EDTA), is often deteriorated due to the collagenolytic activities of reactivated endogenous enzymes as well as the infiltration of extrinsic bacteria. Therefore, the biomodification of dentin collagen with improved stability and antibacterial activity holds great promise in conservative dentistry. The purpose of this study was to evaluate the effects of the combined application of trimethylated chitosan (TMC) and 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride (EDC) on the biostability and antibacterial activity of the demineralized dentin collagen matrix. The morphological changes in the collagen matrix were observed by scanning electron microscopy (SEM), the amount of TMC adsorbed on the collagen surface was detected by X-ray photoelectron spectroscopy, and the elastic modulus was measured by a three-point bending device. Dry weight loss and amino acid release were detected to evaluate its anti-collagenase degradation performance. The antibacterial performance was detected by confocal microscopy. The TMC-treated group had less collagen space and a more compact collagen arrangement, while the untreated group had a looser collagen arrangement. The combined application of TMC and EDC can increase the elastic modulus, reduce the loss of elastic modulus, and result in good antibacterial performance. The current study proved that a dentin collagen matrix biomodified by TMC and EDC showed improved biodegradation resistance and antibacterial activities.

Objective: This study aims to identify an immune-related signature to predict clinical outcomes of oral squamous cell carcinoma (OSCC) patients. Methods: Gene transcriptome data of both tumor and normal tissues from OSCC and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA). Tumor Immune Estimation Resource algorithm (ESTIMATE) was used to calculate the immune/stromal-related scores. The immune/stromal scores and associated clinical characteristics of OSCC patients were evaluated. Univariate Cox proportional hazards regression analyses, least absolute shrinkage, and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses were performed to assess the prognostic prediction capacity. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) function annotation were used to analysis the functions of TME-related genes. Results: Eleven predictor genes were identified in the immune-related signature and overall survival (OS) in the high-risk group was significantly shorter than in the low-risk group. An ROC analysis showed the TME-related signature could predict the total OS of OSCC patients. Moreover, GSEA and GO function annotation proved that immunity and immune-related pathways were mainly enriched in the high-risk group. Conclusions: We identified an immune-related signature that was closely correlated with the prognosis and immune response of OSCC patients. This signature may have important implications for improving the clinical survival rate of OSCC patients and provide a potential strategy for cancer immunotherapy.