Restoring periodontal tissue homoeostasis prevents cognitive decline by reducing the number of Serpina3nhigh astrocytes in the hippocampus.

Cognitive decline has been linked to periodontitis through an undetermined pathophysiological mechanism. This study aimed to explore the mechanism underlying periodontitis-related cognitive decline and identify therapeutic strategies for this condition. Using single-nucleus RNA sequencing we found that changes in astrocyte number, gene expression, and cell‒cell communication were associated with cognitive decline in mice with periodontitis. In addition, activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome was observed to decrease the phagocytic capability of macrophages and reprogram macrophages to a more proinflammatory state in the gingiva, thus aggravating periodontitis. To further investigate this finding, lipid-based nanoparticles carrying NLRP3 siRNA (NPsiNLRP3) were used to inhibit overactivation of the NLRP3 inflammasome in gingival macrophages, restoring the oral microbiome and reducing periodontal inflammation. Furthermore, gingival injection of NPsiNLRP3 reduced the number of Serpina3nhigh astrocytes in the hippocampus and prevented cognitive decline. This study provides a functional basis for the mechanism by which the destruction of periodontal tissues can worsen cognitive decline and identifies nanoparticle-mediated restoration of gingival macrophage function as a novel treatment for periodontitis-related cognitive decline.

Blocking CXCR1/2 attenuates experimental periodontitis by suppressing neutrophils recruitment.

Periodontitis (PD) is a common chronic oral inflammatory disease that cause alveolar bone loss. Current strategies for bone regeneration achieve limited results in PD. The aberrant host osteoimmunity to pathogenic bacteria is responsible for the destruction of alveolar bone in PD. We aimed to investigate the distinctive activity of immune cells in PD to create more effective and precise therapeutic approaches for treating PD. In this study, we revealed that neutrophils in the inflamed alveolar bone of PD patients expressed higher levels of CXCR1/2 and had a stronger pro-inflammatory capacity and chemotactic ability than that in healthy individuals. Suppressing the recruitment of neutrophils to inflamed sites with the CXCR1/2 inhibitor reparixin reduced alveolar bone loss in PD mice. In this study, we not only revealed that neutrophils exhibit a heterogeneously stronger pro-inflammatory capacity in the inflamed alveolar bone of PD patients but also provided a precise therapeutic treatment for PD involving the suppression of neutrophil recruitment.

The spatial transcriptomic landscape of human gingiva in health and periodontitis.

The gingiva is a key oral barrier that protects oral tissues from various stimuli. A loss of gingival tissue homeostasis causes periodontitis, one of the most prevalent inflammatory diseases in humans. The human gingiva exists as a complex cell network comprising specialized structures. To understand the tissue-specific pathophysiology of the gingiva, we applied a recently developed spatial enhanced resolution omics-sequencing (Stereo-seq) technique to obtain a spatial transcriptome (ST) atlas of the gingiva in healthy individuals and periodontitis patients. By utilizing Stereo-seq, we identified the major cell types present in the gingiva, which included epithelial cells, fibroblasts, endothelial cells, and immune cells, as well as subgroups of epithelial cells and immune cells. We further observed that inflammation-related signalling pathways, such as the JAK-STAT and NF-κB signalling pathways, were significantly upregulated in the endothelial cells of the gingiva of periodontitis patients compared with those of healthy individuals. Additionally, we characterized the spatial distribution of periodontitis risk genes in the gingiva and found that the expression of IFI16 was significantly increased in endothelial cells of inflamed gingiva. In conclusion, our Stereo-seq findings may facilitate the development of innovative therapeutic strategies for periodontitis by mapping periodontitis-relevant genes and pathways and effector cells.

Order Space-Based Morphology for Color Image Processing.

Mathematical morphology is a fundamental tool based on order statistics for image processing, such as noise reduction, image enhancement and feature extraction, and is well-established for binary and grayscale images, whose pixels can be sorted by their pixel values, i.e., each pixel has a single number. On the other hand, each pixel in a color image has three numbers corresponding to three color channels, e.g., red (R), green (G) and blue (B) channels in an RGB color image. Therefore, it is difficult to sort color pixels uniquely. In this paper, we propose a method for unifying the orders of pixels sorted in each color channel separately, where we consider that a pixel exists in a three-dimensional space called order space, and derive a single order by a monotonically nondecreasing function defined on the order space. We also fuzzify the proposed order space-based morphological operations, and demonstrate the effectiveness of the proposed method by comparing with a state-of-the-art method based on hypergraph theory. The proposed method treats three orders of pixels sorted in respective color channels equally. Therefore, the proposed method is consistent with the conventional morphological operations for binary and grayscale images.