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Aged bone marrow mesenchymal stem cells (BMSCs) exhibit aberrant self-renewal and lineage specification, which contribute to imbalanced bone-fat and progressive bone loss. In addition to known master regulators of lineage commitment, it is crucial to identify pivotal switches governing the specific differentiation fate of aged BMSCs. Here, we profiled differences in epigenetic regulation between adipogenesis and osteogenesis and identified super-enhancer associated lncRNA nuclear-enriched abundant transcript 1 (NEAT1) as a key bone-fat switch in aged BMSCs. We validated that NEAT1 with high enhancer activity was transcriptionally activated by ATF2 and directed aged BMSCs to a greater propensity to differentiate toward adipocytes than osteoblasts by mediating mitochondrial function. Furthermore, we confirmed NEAT1 as a protein-binding scaffold in which phosphorylation modification of SOX2 Ser249/250 by CDK2 impaired SOX2/OCT4 complex stability and dysregulated downstream transcription networks of pluripotency maintenance. In addition, by sponging miR-27b-3p, NEAT1 upregulated BNIP3L, BMP2K, and PPARG expression to shape mitochondrial function and osteogenic/adipogenic differentiation commitment, respectively. In extracellular communication, NEAT1 promoted CSF1 secretion from aged BMSCs and then strengthened osteoclastic differentiation by extracellular vesicle delivery. Notably, Neat1 small interfering RNA delivery induced increased bone mass in aged mice and decreased fat accumulation in the bone marrow. These findings suggest that NEAT1 regulates the lineage fates of BMSCs by orchestrating mitochondrial function and pluripotency maintenance, and might be a potential therapeutic target for skeletal aging.

Despite decades of research, cancer continues to be a major global health concern. The human mouth appears to be a multiplicity of local environments communicating with other organs and causing diseases via microbes. Nowadays, the role of oral microbes in the development and progression of cancer has received increasing scrutiny. At the same time, bioengineering technology and nanotechnology is growing rapidly, in which the physiological activities of natural bacteria are modified to improve the therapeutic efficiency of cancers. These engineered bacteria were transformed to achieve directed genetic reprogramming, selective functional reorganization and precise control. In contrast to endotoxins produced by typical genetically modified bacteria, oral flora exhibits favorable biosafety characteristics. To outline the current cognitions upon oral microbes, engineered microbes and human cancers, related literatures were searched and reviewed based on the PubMed database. We focused on a number of oral microbes and related mechanisms associated with the tumor microenvironment, which involve in cancer occurrence and development. Whether engineering oral bacteria can be a possible application of cancer therapy is worth consideration. A deeper understanding of the relationship between engineered oral bacteria and cancer therapy may enhance our knowledge of tumor pathogenesis thus providing new insights and strategies for cancer prevention and treatment.

Marginal bone loss (MBL) is one of the leading causes of dental implant failure. This study aimed to investigate the feasibility of machine learning (ML) algorithms based on trabeculae microstructure parameters to predict the occurrence of severe MBL. Eighty-one patients (41 severe MBL cases and 40 normal controls) were involved in the current study. Four ML models, including support vector machine (SVM), artificial neural network (ANN), logistic regression (LR), and random forest (RF), were employed to predict severe MBL. The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, and specificity were used to evaluate the performance of these models. At the early stage of functional loading, severe MBL cases showed a significant increase of structure model index and trabecular pattern factor in peri-implant alveolar bone. The SVM model exhibited the best outcome in predicting MBL (AUC = 0.967, sensitivity = 91.67%, specificity = 100.00%), followed by ANN (AUC = 0.928, sensitivity = 91.67%, specificity = 93.33%), LR (AUC = 0.906, sensitivity = 91.67%, specificity = 93.33%), RF (AUC = 0.842, sensitivity = 75.00%, specificity = 86.67%). Together, ML algorithms based on the morphological variation of trabecular bone can be used to predict severe MBL.

Objective To explore the forewarning immunological indicators during periodontal attachment loss progression in American adults. Methods A total of 5744 participants with periodontal attachment loss were enrolled from the National Health and Nutrition Examination Surveys (NHANES) 2009–2014. In which, dependent variable was the counts of teeth with severe attachment loss (depth of periodontal probing was above 5 mm). Independent variables were circulatory immunological indexes, including counts of white blood cells (WBC), Lymphocytes, Monocytes, Neutrophils, Eosinophils, and Basophils. The association among variables was examined using multivariable linear regression models, fitting with smoothing curves, and generalizing additive models. Results Based on the indicators of 5744 subjects, we found that severe attachment loss tended to occur in the elderly or males and was accompanied by higher WBC, Monocytes, and Neutrophils, as well as lower poverty-income ratio and educational qualification. WBC (above the inflection point: 6200 cells/µL) and Neutrophils (above the inflection point: 3300 cells/µL) counts were positively associated with attachment loss progression in each multivariable linear regression model. On subgroup analyses, stratified by sex and race, the positive correlation of WBC or Neutrophils with severe attachment loss was stable in both men and women, as well as in all races except blacks (WBC β = − 0.0576, 95% CI − 0.1945 to 0.0793, Neutrophils β = − 0.0527, 95% CI − 0.2285 to 0.1231). Conclusion Increasing WBC (above 6200 cells/µL) and Neutrophils (above 3300 cells/µL) counts were risk indicators of severe periodontal attachment loss among all races, except in blacks.

There is a growing body of evidence indicating a close association between inflammatory bowel disease (IBD) and disrupted intestinal homeostasis. Excessive production of reactive oxygen species (ROS) and reactive nitrogen species (RNS), along with an increase in M1 proinflammatory macrophage infiltration during the activation of intestinal inflammation, plays a pivotal role in disrupting intestinal homeostasis in IBD. The overabundance of ROS/RNS can cause intestinal tissue damage and the disruption of crucial gut proteins, which ultimately compromises the integrity of the intestinal barrier. The proliferation of M1 macrophages contributes to an exaggerated immune response, further compromising the intestinal immune barrier. Currently, intestinal nanomaterials have gained widespread attention in the context of IBD due to their notable characteristics, including the ability to specifically target regions of interest, clear excess ROS/RNS, and mimic biological enzymes. In this review, we initially elucidated the gut microenvironment in IBD. Subsequently, we delineate therapeutic strategies involving two distinct types of nanomedicine, namely inorganic nanoparticles and natural product nanomaterials. Finally, we present a comprehensive overview of the promising prospects associated with the application of nanomedicine in future clinical settings for the treatment of IBD (graphic abstract). Graphical Abstract Different classes of nanomedicine are used to treat IBD. This review primarily elucidates the current etiology of inflammatory bowel disease and explores two prominent nanomaterial-based therapeutic approaches. First, it aims to eliminate excessive reactive oxygen species and reactive nitrogen species. Second, they focus on modulating the polarization of inflammatory macrophages and reducing the proportion of pro-inflammatory macrophages. Additionally, this article delves into the treatment of inflammatory bowel disease using inorganic metal nanomaterials and natural product nanomaterials

Background Periodontitis-related attachment loss is accompanied by mucosal bleeding and inflammatory lesions. Dietary vitamin K and fibre intake are known to be correlation factors of haemostasis and anti-inflammation, respectively. Objective To explore the association between severe periodontal attachment loss and vitamin K or fibre intake in American adults. Methods A cross-sectional analysis was conducted including 2747 males and 2218 females in the National Health and Nutrition Examination Surveys (NHANES) from 2009 to 2014. The number of teeth with severe periodontal attachment loss (above 5 mm attachment loss) was used as the dependent variable. The main independent variables included the intake of vitamin K and dietary fibre. The association among variables was examined using multivariable linear regression models, hierarchical regression, fitted smoothing curves, and generalized additive models. Results Based on the indicators of 4965 subjects, we found that severe attachment loss tended to occur in elderly individuals or males and was accompanied by less intake of vitamin K or dietary fibre, as well as lower educational qualification. Vitamin K intake was stably negatively associated with attachment loss progression in each multivariable linear regression model. In subgroup analyses, a negative association between fibre intake and attachment loss progression was identified in all races except blacks (β = 0.0005, 95% CI: -0.0005 to 0.0016). The relationship between fibre intake and attachment loss progression was a broad U-shaped curve (inflection point: 753.4 mg), which especially manifested in males (inflection point: 967.5 mg). Conclusion There was an inverse association between vitamin K intake and the progression of periodontal attachment loss in American adults, while dietary fibre should be moderate in intake (below 753.4 mg), especially in males (below 967.5 mg).

Objective To use deep learning to segment the mandible and identify three-dimensional (3D) anatomical landmarks from cone-beam computed tomography (CBCT) images, the planes constructed from the mandibular midline landmarks were compared and analyzed to find the best mandibular midsagittal plane (MMSP). Methods A total of 400 participants were randomly divided into a training group ( n  = 360) and a validation group ( n  = 40). Normal individuals were used as the test group ( n  = 50). The PointRend deep learning mechanism segmented the mandible from CBCT images and accurately identified 27 anatomic landmarks via PoseNet. 3D coordinates of 5 central landmarks and 2 pairs of side landmarks were obtained for the test group. Every 35 combinations of 3 midline landmarks were screened using the template mapping technique. The asymmetry index (AI) was calculated for each of the 35 mirror planes. The template mapping technique plane was used as the reference plane; the top four planes with the smallest AIs were compared through distance, volume difference, and similarity index to find the plane with the fewest errors. Results The mandible was segmented automatically in 10 ± 1.5 s with a 0.98 Dice similarity coefficient. The mean landmark localization error for the 27 landmarks was 1.04 ± 0.28 mm. MMSP should use the plane made by B (supramentale), Gn (gnathion), and F (mandibular foramen). The average AI grade was 1.6 (min–max: 0.59–3.61). There was no significant difference in distance or volume ( P  > 0.05); however, the similarity index was significantly different ( P  < 0.01). Conclusion Deep learning can automatically segment the mandible, identify anatomic landmarks, and address medicinal demands in people without mandibular deformities. The most accurate MMSP was the B-Gn-F plane.

Engineering bacteria are considered as a potential treatment for cardiovascular diseases and related risk factors. Oral bacteria are closely related to the occurrence and development of cardiovascular diseases, and their engineering has broad prospects and potential in the treatment of cardiovascular diseases. Oral pathogenic bacteria undergo protein and genetic engineering, including the incorporation of exogenous plasmids to yield therapeutic effects; genetically engineered oral probiotics can be harnessed to secrete cytokines and reactive oxygen species, offering novel therapeutic avenues for cardiovascular diseases.

Objectives This study aimed to quantitatively evaluate the therapeutic effect of decompression on mandibular cystic lesions using three-dimensional volumetric analysis and investigate factors influencing volume reduction patterns. Methods A retrospective cohort of 44 patients with mandibular cystic lesions, including 12 unicystic ameloblastomas (UAB), 12 odontogenic keratocysts (OKC), and 20 nonkeratinizing cysts (NKC), was analyzed. Volumetric measurements before and after decompression were obtained using Three- dimensional (3D) Slicer software and CBCT data. Outcome variables included absolute volume reduction (AVR), absolute speed of shrinkage (ASS), relative reduction in volume (RRV), and relative speed of shrinkage (RSS). Predictor variables were patient age, gender, presence of impacted teeth, mandibular ramus involvement, preoperative volume, and decompression duration. Statistical analyses were performed, with significance set at P  ≤ 0.05. Results Significant volume reductions were observed across all groups post-decompression ( P  < 0.01). Preoperative volume correlated positively with AVR and ASS ( P  < 0.05). Decompression duration was inversely related to RSS ( P  < 0.05) and positively related to RRV in OKC and NKC groups ( P  < 0.05). Other variables showed no significant associations ( P  > 0.05). Conclusions Decompression effectively reduces mandibular cystic lesion volume, with preoperative size and duration of decompression being key influencing factors. Three-dimensional volumetric analysis provides detailed, reliable evaluation of treatment efficacy, enhancing clinical monitoring and decision-making.

The causes of visual impairment are complex and may be influenced by exposure to environmental pollutants. Using data from the 2003–2004 National Health and Nutrition Examination Survey (NHANES), we examined the association between exposure to ten polycyclic aromatic hydrocarbons (PAHs) and vision problems in 1149 U.S. adults. We employed various supervised learning methods, including variable selection techniques such as Lasso and elastic net, weighted quantile sum regression (WQS), and Bayesian kernel machine regression (BKMR), to assess the association between PAHs and the occurrence of visual impairments. The mediation effects between urinary 2-fluorene and inflammation were evaluated using mediation analysis. Both the lasso and elastic net models consistently identified two specific PAH congeners, 2-fluorene and 1-phenanthrene, as significant predictors. The WQS regression revealed a positive relationship between the PAH mixture and visual impairment, with notable contributions from urinary 2-fluorene (weight = 0.39) and 9-fluorene (weight = 0.21). BKMR analysis indicated that the likelihood of visual impairment increases with higher PAH exposure, showing a general upward trend. This trend also revealed a positive association between visual impairment and exposure to four specific PAH metabolites, including 2-fluorene. A significant mediation effect was observed for alkaline phosphatase (p = 0.03), with a proportion mediated of 10.48%. Our findings suggest a significant association between PAHs and visual impairment, with multiple statistical models consistently emphasizing the crucial role of 2-fluorene exposure. This study highlights the importance of considering environmental pollutants as significant contributors to visual health outcomes, providing insights for preventing visual impairment.