Early, high-throughput, and accurate recognition of osteogenic differentiation of stem cells is urgently required in stem cell therapy, tissue engineering, and regenerative medicine. In this study, we established an automatic deep learning algorithm, i.e., osteogenic convolutional neural network (OCNN), to quantitatively measure the osteogenic differentiation of rat bone marrow mesenchymal stem cells (rBMSCs). rBMSCs stained with F-actin and DAPI during early differentiation (day 0, 1, 4, and 7) were captured using laser confocal scanning microscopy to train OCNN. As a result, OCNN successfully distinguished differentiated cells at a very early stage (24 h) with a high area under the curve (AUC) (0.94 ± 0.04) and correlated with conventional biochemical markers. Meanwhile, OCNN exhibited better prediction performance compared with the single morphological parameters and support vector machine. Furthermore, OCNN successfully predicted the dose-dependent effects of small-molecule osteogenic drugs and a cytokine. OCNN-based online learning models can further recognize the osteogenic differentiation of rBMSCs cultured on several material surfaces. Hence, this study initially demonstrated the foreground of OCNN in osteogenic drug and biomaterial screening for next-generation tissue engineering and stem cell research.
Aim Electroacupuncture (EA) regulates distant body physiology through somatic sensory autonomic reflexes, balances the microbiome, and can promote the release of immune cells into bloodstream, thereby inhibiting severe systemic inflammation. This makes it possible to use EA as an integrated treatment for periodontitis. Materials and Methods In this study, EA was applied to the ST36 acupoints in a ligature‐induced periodontitis (LIP) mouse model. Then the effects of EA on periodontal myeloid cells, cytokines, and the microbiome were comprehensively analysed using flow cytometry, quantitative Polymerase Chain Reaction (PCR), and 16 S sequencing. Results Results demonstrated that EA could significantly relieve periodontal bone resorption. EA also suppressed the infiltration of macrophages and neutrophils, reduced gene expression of the pro‐inflammatory cytokines IL‐1β, IL‐6, IL‐17 and TNF‐α, and increased expression of the anti‐inflammatory factors IL‐4 and IL‐10 in periodontal tissues. Moreover, composition of the periodontal microbiome was regulated by EA, finding that complex of microbiota, including supragingival Veillonella, subgingival Streptococcus, and subgingival Erysipelatoclostridium, were significantly reduced. Meanwhile, nitrate and nitrate‐related activities of subgingival microbiota were reversed. Network analysis revealed close relationships among Veillonella, Streptococcus, and Bacteroides. Conclusions Our study indicates that EA can effectively alleviate inflammation and bone resorption in LIP mice, potentially via the regulation of myeloid cells, cytokines, and periodontal microbiome.
Background and ObjectivesCigarette smoking has been reported as an independent risk factor for periodontitis. Tobacco toxins affect periodontal tissue not only locally but also systemically, leading to the deterioration and recurrence of periodontitis. However, the mechanism of cigarette smoke‐related periodontitis (CSRP) is unclear and thus lacks targeted treatment strategies. Quercetin, a plant‐derived polyphenolic flavonoid, has been reported to have therapeutic effects on periodontitis due to its documented antioxidant activity. This study aimed to evaluate the effects of quercetin on CSRP and elucidated the underlying mechanism.MethodsThe cigarette smoke‐related ligature‐induced periodontitis mouse model was established by intraperitoneal injection of cigarette smoke extract (CSE) and silk ligation of bilateral maxillary second molars. Quercetin was adopted by gavage as a therapeutic strategy. Micro‐computed tomography was used to evaluate the alveolar bone resorption. Immunohistochemistry detected the oxidative stress and autophagy markers in vivo. Cell viability was determined by Cell Counting Kit‐8, and oxidative stress levels were tested by 2,7‐dichlorodihydrofluorescein diacetate probe and lipid peroxidation malondialdehyde assay kit. Alkaline phosphatase and alizarin red staining were used to determine osteogenic differentiation. Network pharmacology analysis, molecular docking, and western blot were utilized to elucidate the underlying molecular mechanism.ResultsAlveolar bone resorption was exacerbated and oxidative stress products were accumulated during CSE exposure in vivo. Oxidative stress damage induced by CSE caused inhibition of osteogenic differentiation in vitro. Quercetin effectively protected the osteogenic differentiation of human periodontal ligament cells (hPDLCs) and periodontal tissue by upregulating the expression of Beclin‐1 thus to promote autophagy and reduce oxidative stress damage.ConclusionOur results established a role of oxidative stress damage and autophagy dysfunction in the mechanism of CSE‐induced destruction of periodontal tissue and hPDLCs, and provided a potential application value of quercetin to ameliorate CSRP.
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