Hydrogel, a functional polymer material, has emerged as a promising technology for therapies for periodontal diseases. It has the potential to mimic the extracellular matrix and provide suitable attachment sites and growth environments for periodontal cells, with high biocompatibility, water retention, and slow release. In this paper, we have summarized the main components of hydrogel in periodontal tissue regeneration and have discussed the primary construction strategies of hydrogels as a reference for future work. Hydrogels provide an ideal microenvironment for cells and play a significant role in periodontal tissue engineering. The development of intelligent and multifunctional hydrogels for periodontal tissue regeneration is essential for future research.

Background Immune checkpoint inhibitor-mediated immunotherapy cannot be carried out on a large scale clinically due to its low universality. In recent years, cyclic guanosine monophosphate synthase/interferon gene stimulating factor (cGAS/STING)-mediated innate immune signaling pathway-mediated immunotherapy has attracted more and more attention. In addition, metabolic inhibitors also show good effects on tumor treatment, but their application is often limited because of their large first pass effect or difficult administration. Methods The particle size and potential parameters were measured by DLS. In order to determine the optimal ratio of the two drugs, we calculated the CI value of different nanoparticles through MTT experiment, and simulated their synergistic effect through Gaussian software. Then the morphology and crystal form of the best proportion of drugs were studied by TEM and XRD. The anti-tumor mechanism of composite nanoparticles was confirmed by the determination of metabolic related indexes, Q-PCR and WB. The antitumor effect and immune activation effect were comprehensively evaluated by in vivo and in vitro experiments. Results Here, we found and synthesized BCP nanoparticles ((BPA + CPI) @ PLGA NPs) which can effectively reduce the metabolism of tumor cells and inhibit cell proliferation. At the same time, the release of mitochondrial DNA (mtDNA) caused by mitochondrial metabolism disorder further activated the cGAS/STING signal pathway in Hepa1–6 cells. We found that the drug-treated Hepa1–6 cells had obvious TBK1 phosphorylation and STING dimerization. Combined with STING agonist, it could effectively promote the activation of CD8 T cells and enhanced the therapeutic effect on liver cancer. Conclusion Our results showed that PLGA nanocarrier can successfully improve the dosage forms of two metabolic inhibitors and show the effect of synergistic therapy. BCP nanoparticles can also activate the innate immunity of tumor cells and significantly enhance tumor inhibition after combined with STING agonists. This study has high reference and transformation value for the combined treatment of immunosuppression and metabolic inhibition. Graphical Abstract

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Background: Characterizing the periodontal status of patients with Alzheimer’s disease (AD), investigating differences in salivary metabolism between patients with and without AD under the same periodontal conditions, and understanding how it is related to oral flora are critical. Objective: We aimed to examine the periodontal condition of patients with AD and to screen salivary metabolic biomarkers from the saliva of individuals with and without AD with matched periodontal conditions. Furthermore, we aimed to explore the possible relationship between salivary metabolic changes and oral flora. Methods: In total, 79 individuals were recruited into the experiment for periodontal analysis. Especially, 30 saliva samples from the AD group and 30 from healthy controls (HCs) with matched periodontal conditions were selected for metabolomic analysis. The random-forest algorithm was used to detect candidate biomarkers. Among these, 19 AD saliva and 19 HC samples were selected to investigate the microbiological factors influencing the alterations in saliva metabolism in patients with AD. Results: The plaque index and bleeding on probing were considerably higher in the AD group. Further, Cis-3-(1-carboxy-ethyl)-3,5-cyclohexadiene-1,2-diol, dodecanoic acid, genipic acid, and N, N-dimethylthanolamine N-oxide were determined as candidate biomarkers, based on the area under the curve (AUC) value (AUC = 0.95). The results of oral-flora sequencing showed that dysbacteriosis may be a reason for the differences in AD saliva metabolism. Conclusion: Dysregulation of the proportion of specific bacterial flora in saliva plays a vital role in metabolic changes in AD. These results will contribute to further improving the AD saliva biomarker system.