Our goal was to develop and externally validate oral health self-report measures for predicting periodontitis in a representative U.S. adult population (30-79 years old) and to evaluate a predictive scoring tool for periodontitis constructed from the best performing model parameter estimates.

The predictive models for periodontitis using demographic characteristics and self-reported oral health measures were developed and tested with the National Health and Nutrition Examination Survey (NHANES) 2009-2012 data (development 2009-2010, validation 2011-2012). The best performing model was externally validated against clinical periodontitis cases defined by measurements from a full-mouth periodontal examination at six sites around all teeth excluding third molars. A predictive scoring tool derived from the transformed sum of the model coefficient estimates was also externally validated. Model performances were evaluated by their sensitivity, specificity, predictive accuracy, and area under the receiver-operating characteristic curve (AUROC).

Our best model used self-reported oral health, smoking, and demographics. Predictive Risk Scores (PRS) of ≥65 captured about 98% of the true periodontitis cases. Three forms of the model (1-individual risk factor variables, 2-continuous PRS, and 3-PRS categories) were applied to the development and validation data sets. Overall, all three forms had high sensitivity (>84%) in both the development and validation data sets and had similar AUROC (around 80%). Specificity was low to moderate. When externally validated, the model incorporating PRS as a continuous measure had high sensitivity (84.0%) and low specificity (57.5%), with AUROC of 79.5% and predictive accuracy of 71.6%. Similarly, when PRS as a categorical variable was externally validated, the model had a high sensitivity (82.8%) and low specificity (59.9%), with an AUROC of 79.3% and predictive accuracy of 72.0%.

Overall, modeling of four self-report oral health measures, combined with smoking and demographic characteristics, performs well in predicting clinical periodontitis in a nationally representative sample of the adult dentate US adult population. Compared with clinical periodontal examination, this approach is promising as a viable, non-clinical, and much less resource-intensive alternative method for estimating the burden of periodontitis.

Periodontitis has emerged as one of the most critical oral diseases, and research on this condition holds great importance for the advancement of stomatology. As the most authoritative national scientific research funding institution in China, the National Natural Science Foundation of China (NSFC) has played a pivotal role in driving the progress of periodontal science by supporting research on periodontitis. This article provides a comprehensive review of the research and development progress related to periodontitis in China from 2014 to 2023, highlighting the significant contributions of the NSFC to this field. We have summarized the detailed funding information from the NSFC, including the number of applicant codes, funded programs and the distribution of funded scholars. These data illustrate the efforts of the NSFC in cultivating young scientists and building research groups to address key challenges in national scientific research. This study offers an overview of the current hot topics, recent breakthroughs and future research prospects related to periodontitis in China.

Radiotherapy (RT) is a key component in the multimodal treatment approach for head and neck cancer (HNC). Post-therapeutic surgical and/or dental interventions on the jawbone carry a risk of developing osteoradionecrosis (ORN). To mitigate this risk, dental examinations and, if necessary, treatment should be conducted prior to RT. However, the consistent implementation of these recommendations in routine dental practice remains uncertain. This study aimed to evaluate whether insured persons of AOK Saxony-Anhalt (AOK ST) utilise dental services in accordance with current treatment recommendations and whether this behaviour influences the need for post-therapeutic tooth removal and the occurrence of ORN.

Anonymised health claims data were analysed from individuals newly diagnosed with HNC between 2017 and 2021, who received RT and were continuously insured by AOK ST from 1 year before the start of RT to 2022. Three dependent variables were evaluated: dental treatment prior to RT, tooth extraction after RT, and ORN occurrence. Independent variables included sex, age, tooth extraction before RT, need for care, exemption from copayment, bisphosphonate prescription, diabetes, chronic obstructive pulmonary disease, alcohol abuse, chemotherapy, and guideline adherence.

Data from 1,086 patients with HNC diagnoses (75.9% male) were analysed. The median follow-up time from the first RT was 796 days (first quartile: 316 days; third quartile: 1,210 days). Twenty-one patients (1.9%) developed ORN after RT. More than 50% of the study population received dental care in accordance with guideline recommendations prior to RT. Need for care had the most significant negative effect on the utilisation of dental treatment prior to RT.

This study did not find evidence of consistent implementation of the recommended guidelines for dental assessment/therapy prior to RT. Patients in need for care and those with chronic comorbidities were less likely to receive and/or require dental care. Although no significant influence on ORN development was observed, the reliability of this finding is limited by the small cohort size and low ORN incidence. Further studies with larger cohorts are needed to validate these findings.

This study aimed to evaluate the effects of periodontal basic therapy combined with various adjunctive treatments on periodontal inflammation and glycemic control in patients with periodontitis and type 2 diabetes mellitus (T2DM) using network meta-analysis.

Randomized controlled trials (RCTs) involving patients with periodontitis and T2DM were retrieved from PubMed, Embase, Cochrane Library, and Web of Science up to February 29, 2024. The Cochrane quality scoring system was applied to assess study quality, and data were analyzed using R and Stata. The study was registered in PROSPERO (Registration No.: CRD42024501722).

Thirty-seven RCTs involving 1,989 patients were included. Among the adjunctive therapies, scaling and root planing (SRP) with local satranidazole gel (SZ) achieved the best improvement in probing depth (PD) and clinical attachment level (CAL); SRP with systemic amoxicillin (AMX) significantly improved bleeding on probing (BOP); SRP with systemic doxycycline (Doxy) or antimicrobial photodynamic therapy (aPDT) was most effective for reducing glycated hemoglobin (HbA1c%); and SRP with diode laser (DL) improved fasting blood sugar (FBS) most effectively.

SRP combined with local SZ may improve PD and CAL in patients with periodontitis and T2DM. Systemic AMX may enhance BOP outcomes, while DOXY or aPDT may help reduce HbA1c. DL may contribute to better FBS improvement.

Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to develop a machine learning model that can accurately predict diabetic macroangiopathy in Chinese patients. A retrospective cross-sectional analytical study was conducted on 1566 hospitalized patients with T2DM. Feature selection was performed using recursive feature elimination (RFE) within the mlr3 framework. Model performance was benchmarked using 29 machine learning (ML) models, with the ranger model selected for its superior performance. Hyperparameters were optimized through grid search and 5-fold cross-validation. Model interpretability was enhanced using SHAP values and PDPs. An external validation set of 106 patients was used to test the model. Key predictive variables identified included the duration of T2DM, age, fibrinogen, and serum urea nitrogen. The predictive model for macroangiopathy was established and showed good discrimination performance with an accuracy of 0.716 and an AUC of 0.777 in the training set. Validation on the external dataset confirmed its robustness with an AUC of 0.745. This study establish an approach based on machine learning algorithm in features selection and the development of prediction tools for diabetic macroangiopathy.

Inflammation plays a fundamental role in the development and bidirectional association of di-verse diseases, such as periodontitis and type 2 diabetes mellitus (T2DM), which generates important clinical complications, where chronic exposure to high levels of blood glucose affects the repair process of periodontal tissues. Likewise, it has been observed that comorbidity, between these two diseases, influences the development of the COVID-19 disease towards a more severe course. However, there is currently very little scientific evidence on the relationship between periodontitis, T2DM and COVID-19 disease. This narrative review aims to provide an understanding of the current and most relevant aspects of the relationship between periodontitis, T2DM and COVID-19 disease. A narrative review was performed through a systematic search of published studies, without date restrictions, indexed in the electronic databases of PubMed, for the inclusion of articles in English, and LILACS for the inclusion of articles in Spanish. This review included different articles, which addressed the most important aspects to present a current perspective on the relationship and influence between periodontitis, T2DM and COVID-19 disease. Comorbidity between periodontitis and T2DM represents a greater risk of developing a more severe course of COVID-19 disease, because these three diseases share three important axes: a clinicopathological axis; an axis associated with glycemia, and an immunological axis associated with inflammation.

Bidirectional positive relationship between periodontitis and type 2 diabetes mellitus (T2DM) has been recognized, interleukin 17 (IL-17) and developmental endothelial locus-1 (Del-1) are proposed to play roles in periodontitis and T2DM. This study aims to investigate the association of IL-17 and Del-1 in patients with periodontitis with and without T2DM by measuring their salivary levels.

A total of 80 participants were enrolled in a cross-sectional study and divided into healthy (H, n = 27), periodontitis (P, n = 29) and periodontitis with diabetes (PDM, n = 24) groups based on their periodontal and diabetic examination results. Periodontal parameters (plaque index [PI], bleeding on probing [BOP], probing depth [PD], and clinical attachment level [CAL]) as well as diabetic parameters (fasting plasma glucose [FG] and glycated hemoglobin [HbA1c]) were documented and unstimulated saliva was collected. Salivary IL-1β, active-matrix metalloproteinase-8 (aMMP-8), tumor necrosis factor-α (TNF-α), IL-6, IL-8, IL-17, and Del-1 were determined through enzyme-linked immunosorbent assay (ELISA) and their relationships with periodontal and diabetic parameters were examined.

The periodontitis and periodontitis with diabetes groups showed significantly higher levels of IL-17 and lower levels of Del-1 compared with healthy group. The periodontitis with diabetes group exhibited higher levels of IL-17 and lower levels of Del-1 compared with the periodontitis group. After correlation analysis, there were significant correlations between salivary IL-17 and Del-1 and clinical parameters, IL-17 and Del-1 were correlated with PD (r = 0.36, -0.39, p < 0.01), CAL (r = 0.40, -0.42, p < 0.01) and BOP (r = 0.35, -0.37, p < 0.01), they were correlated with FG (r = 0.26, -0.25, p < 0.05) and HbA1c (r = 0.28, -0.40, p < 0.05). Positive relationships were observed between IL-17 and IL-1β and between IL-17 and aMMP-8 (r = 0.80, 0.77, p < 0.01), while Del-1 exhibited negative correlations with IL-1β and aMMP-8 (r = 0.59, 0.69 p < 0.01). Comparison between IL-17 and Del-1 confirmed an inverse relationship (r = -0.71, p < 0.01). Salivary Del-1 levels in the older group were lower compared with young group across the H, P and PDM groups, although these differences were not statistically significant (p > 0.05).

Salivary IL-17 and Del-1 levels in the periodontitis with diabetes group showed significant changes compared with the periodontitis group, they exhibited an inverse relationship and were both correlated with periodontal parameters (PD, CAL, and BOP) and diabetic parameters (FG and HbA1c).

Periodontitis and type 2 diabetes mellitus (T2DM) are two common diseases all over the world, some inflammatory mediators (interleukin 17 [IL-17] and developmental endothelial locus-1 [Del-1]) regulate neutrophil production, recruitment and clearance when the body becomes infected and believed to be involved in the progress of diseases of periodontitis and diabetes. In this study, we enrolled healthy subjects, patients with periodontitis, patients with periodontitis and diabetes. We performed dental examinations and evaluated their blood glucose levels, collected their saliva, and detected IL-17 and Del-1 levels in their saliva. We found both patients with periodontitis and patients with periodontitis and diabetes showed higher IL-17 levels and lower Del-1 levels compared with healthy subjects. Patients with periodontitis and diabetes showed higher IL-17 levels and lower Del-1 levels compared with patients with periodontitis. Salivary IL-17 and Del-1 levels were both correlated with dental examination results and blood glucose levels, and salivary IL-17 and Del-1 displayed an inverse relationship.

This study aims to report on the development and validation of the Attitude of Nursing staff towards Oral healthcare for Care-dependent Older adults (ANOCO) questionnaire.

The development of the ANOCO questionnaire was performed in three stages between 2008 and 2019. In a first stage, domains related to oral healthcare attitudes were identified. Next, relevant statements per domain were formulated by a Delphi panel in two rounds, resulting in a questionnaire with 32 statements. In a final phase, this questionnaire was subjected to psychometric analysis, including an evaluation of the construct validity, an internal consistency analysis (Cronbachs alpha) and a principal component analysis.

The questionnaire could significantly distinguish between known groups (dentists, nurses' aides, nursing students and nurses). Regarding internal consistency, Cronbach's alpha was 0.863 in the first sample (n = 361) and 0.843 in the second sample (n = 1051). Based on principal component analysis, 22 statements were retained. Four components with an eigenvalue of more than 1 explained 45% of the total variance.

The ANOCO-22 questionnaire consists of 22 statements and is a valid tool to assess the changes or differences in the attitude of nursing staff towards oral healthcare for care-dependent older adults.

This study implemented a workplace dental-health program to encourage those at risk of diabetes to visit a dentist, and examined factors associated with changes in glycemic control.

The participants included 342 people aged 40-64 years old with an A1c value of 5.6% or higher, and those with diabetes, prediabetes, or needing to exercise caution with regard to diabetes. Participants underwent a dental checkup at a dental clinic in 2018, after which their diabetes status was followed for 3 years. Multivariate multinomial logistic regression analysis was performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the effect of each independent variable on the 3-year change in the A1c value (decrease, stable, or increase).

Having a greater number of teeth was associated with a significantly lower OR for an increased A1c value (decrease ≥ 0.3%) (OR, 0.88; 95% CI, 0.79-0.97). Visiting a dentist regularly was associated with a significantly higher OR for a decreased A1c value (increase ≥ 0.3%) (OR, 4.20; 95% CI, 1.45-12.2).

Among working adults, those who visited a dentist regularly had better A1c values, and those with a greater number of teeth were less likely to experience worsening of A1c values.

Xerostomia is a common complication associated with diabetes mellitus. However, the prevalence of xerostomia in patients with type 2 diabetes mellitus (T2DM) remains unclear. Therefore, the present study aimed to synthesize results from existing research to investigate the prevalence of xerostomia in T2DM patients.

A comprehensive search was conducted in November 2024 across four databases (PubMed, Scopus, Embase, and Web of Science). The search included English literature pertaining to the prevalence of xerostomia in adult patients with T2DM. Conference proceedings, reviews, and literature lacking complete data or containing other diseases affecting xerostomia prevalence were excluded. Two researchers independently assessed the quality of the included studies by using the Joanna Briggs Institute Standardized Critical Appraisal Checklist. Data analyses were performed using Stata version 18.0 software. A proportions approach was used for meta-analysis. If I2 > 50%, a random-effects model was utilized; otherwise, a fixed-effects model was employed. The pooled estimates of prevalence were calculated through double arcsine transformation. Subgroup analyses were conducted based on study design, continent, evaluation tool, disease duration, and HbA1c.

A total of 1355 studies were identified, of which 23 studies encompassing 2486 patients with T2DM met the inclusion criteria. The majority of these studies were small-sample analytical cross-sectional studies using questions about the subjective feeling of oral dryness to assess xerostomia. Risk assessment revealed 2 studies with high risk, 5 with medium risk, and 16 with low risk. The overall prevalence of xerostomia in T2DM patients was 42.49%(95%CI = 36.14-48.46). Subgroup analyses indicated no statistically significant differences based on study design, continent, evaluation tool, disease duration, and HbA1c level.

The lack of high-quality prevalence studies may result in inaccurate estimation of xerostomia prevalence among patients with T2DM. Future research should prioritize large-scale prevalence studies by utilizing more accurate assessment tools.

PROSPERO [CRD42022315150].

Periodontitis is a prevalent inflammatory disease that leads to significant periodontal tissue destruction and compromised dental health, with its severity exacerbated in individuals with Diabetes Mellitus (DM). This review explores the complex relationship between mitochondrial dysfunction and periodontitis in diabetic patients. Recent studies indicate that the excessive production of reactive oxygen species (ROS), primarily generated by dysfunctional mitochondrial electron transport chain (ETC) complexes, contributes to oxidative stress (OS) and subsequent periodontal tissue damage. The interplay between impaired mitochondrial biogenesis, apoptosis of periodontal cells, and ROS accumulation highlights a critical area of concern in understanding the pathophysiology of diabetic periodontitis. Furthermore, altered glycemic control due to inflammatory processes associated with periodontitis may perpetuate a cyclical detriment to oral and systemic health. This review aims to highlight the mechanistic roles of mitochondrial dysfunction in the aggravation of periodontitis among diabetic patients, emphasizing further research to identify potential therapeutic targets and improve treatment efficacy for this dual pathology.

An increase in the aging population underscores the need for oral healthcare practice guidelines. Comprehensive geriatric assessment (CGA) includes multidimensional evaluation and integrates oral health into overall healthcare. However, a framework for CGA in dental setting has not been clearly structured. This study aimed to identify the components of CGA essential for proper oral care in older adults based on the perspective of multidisciplinary experts.

A scoping review was conducted to provide insights into CGAs that are mentioned in treatment plan models for oral healthcare (Protocol registration number 10.17605/OSF.IO/EZRDV). The findings were used as basic information for focus group discussion among the multiple healthcare professions. The first focus group included 6 medical experts of 6 disciplines, and the second focus group included 6 dental experts. Focus group discussion aimed to provide a rationale for selecting CGA components and assessment tools that were essential. Thematic analysis was used to synthesize expert perspectives and build an agreement on the application of CGAs in dental practice.

The scoping review revealed four dental treatment planning models, including the OSCAR model, rational treatment model, the Seattle Care Pathway, and the risk of oral health deterioration (ROHD). These models suggested the key CGA components, including systemic conditions for any risks of comorbidities, oral health conditions, socioeconomic status, dependency, cognitive and mental health, communication, and life expectancy. Data from both focus groups consistently agreed that dentists should evaluate complex oral problems of older adults in multiple dimensions. In addition, they also emphasized the importance of swallowing problems, nutrition, and fall risk. Nonetheless, the selection of assessment tools such as The Barthel Index for Activities of Daily Living, water swallow screening test, Mini Nutritional Assessment, Mini-Cog, Patient Health Questionnaire, and three key questions for fall risk assessment should depend on the purposes and team expertise. The development of dental treatment plans must be individualized based on evaluation results of CGA. The rationale for different treatment levels, including comprehensive, limited, urgency care and no treatment, was discussed. The focus groups emphasized that dependency level, social support and systemic factors were important for selecting a level of care.

CGA provides rationale for oral health problem analysis, treatment planning, and oral healthcare. The expert opinions underscore the importance of comprehensive and individualized care plans suggested in the oral treatment plan model. The multiple dimensions of CGAs include systemic and oral health, socioeconomic factors, dependency, cognitive and mental health, swallowing problem, nutrition, and fall risk. The selection of assessment tools should be optimized based on the purposes and team expertise. The multidisciplinary team has a crucial contribution in comprehensive evaluation of patient problems when formulating treatment plans for special-needed patients.

Diabetes Mellitus type 2 (DM2) is thought to have a bidirectional relationship with Periodontitis (PD). However, the complex molecular interactions between DM2 and PD remain unclear. This study aimed to explore the shared genes and common signatures of DM2 and PD via bioinformatic analysis.

Firstly, using bioinformatic methods to investigate common genes. The series matrix files of GSE6751 for DM and GSE15932 for PD were downloaded from the Gene Expression Omnibus (GEO) database. The data was normalized using the R package, and the limma package was utilized to identify the Differentially Expressed Genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of DEGs were performed using the "clusterProfiler" package in the R software. The protein-protein network was constructed to analyze the potential relationship among the proteins. CytoHubba, a plugin for the Cytoscape software, was used to identify the hub genes. The validation datasets selected for DM2 and PD were GSE10334 and GSE7014, respectively. Receiver Operating Characteristic (ROC) curve analysis was performed to obtain the area under the ROC curve. Lipopolysaccharide (LPS) +  high glucose-induced DM-related PD was simulated to verify the three hub genes through quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and Western blot (WB).

In total, 44 common DEGs were identified. ITGAM, H2BC21, S100A9 was identified as he hub genes of DM2 and PD, with all of them were up-regulated. In addition, the area under the curve of all three hub genes was more than 0.65. In-vitro experiments revealed that the relative expression of S100A9 was increased after the treatment with LPS +  high glucose. Besides, TLR4 and p-NF-κB levels were also improved in model group.

S100A9 was identified as the hub gene of DM2 and PD. S100A9 could trigger TLR4 signaling way to promote disease development, which can be the potential targets for diagnosis and treatment.

Epidemiologic research has linked periodontitis to several types of cancer, particularly breast cancer. Although clinical evidence indicates a higher risk of breast cancer in women with periodontitis than in those without, few studies have explored whether the risk of periodontitis is higher in women with breast cancer than in those without. In this study, we examined the incidence of periodontitis in patients with breast cancer and identified potential interventions for its prevention.

This retrospective cohort study included data from the National Health Insurance Research Database of Taiwan. We identified women who received a diagnosis of breast cancer between 2010 and 2019 and included a 1:1 matched control cohort with no breast cancer. Subsequently, we analyzed the risk of periodontitis by using Cox proportional-hazards models while adjusting for sociodemographic factors, comorbidities, and treatment regimens.

In 82,146 matched pairs, the breast cancer cohort was at a 51 % higher risk of periodontitis compared with the control cohort (adjusted hazard ratio = 1.51, 95 % confidence interval = 1.43-1.60). The stratified analysis revealed the same results. The risk of breast cancer was higher in younger patients than in older patients, whereas the risk of periodontitis was significantly lower in patients who underwent surgery, radiotherapy, chemotherapy, or hormone therapy compared with those who did not.

Breast cancer increases the risk of periodontitis, particularly in younger patients. These patients should receive regular dental care to prevent and manage periodontitis. Anticancer treatments may mitigate the risk of periodontitis in patients with breast cancer.

Diabetes and periodontitis exhibit a bidirectional relationship, posing significant challenges for the treatment of periodontitis in patients with diabetes. Our previous studies showed that the hypoglycemic agent liraglutide (LIRA), together with glycemic control, had favorable therapeutic effects on diabetic periodontitis (DP), achieving a "two birds with one stone" effect. Therefore, exploration of the topical application of LIRA for treating DP is warranted. In this study, nanoparticles were loaded with LIRA using poly (lactic-co-glycolic acid) (PLGA), and their morphology, particle size, encapsulation efficiency, drug loading, and drug release profiles were characterized. These nanoparticles were further encapsulated with hyaluronic acid (HA) to form a LIRA@PLGA/HA sustained-release system. The cytotoxicity of LIRA@PLGA/HA was analyzed using CCK-8 assays, and its anti-inflammatory and osteogenic effects on periodontitis in diabetic rats were evaluated by histology, ELISA, and micro-CT analysis, while its influence on necroptosis-related factors was assessed using qRT-PCR and Western blotting. The results indicated that LIRA@PLGA (30000 Da) exhibited an encapsulation efficiency of 86.2 %, a drug loading capacity of 4.3 %, and a cumulative release of LIRA reaching approximately 60 % after 8 days, thereby meting the requirement for sustained release. Following 24 h of stimulation with various concentrations (0-20 mg/ml) of LIRA@PLGA/HA, the viability of human periodontal ligament cells (HPDLCs) remained above 85 %. Topical application for four weeks significantly inhibited the expression of the inflammatory factors TNF-α and IL-1β in gingival crevicular fluid and serum, reduced inflammatory cell infiltration in periodontal tissues, and attenuated alveolar bone resorption while improving alveolar bone microstructure, showing therapeutic effects similar to the commercial drug PERIOCLINE® (PERIO). Furthermore, LIRA@PLGA/HA reduced the expression of necroptosis-related factors RIPK1, RIPK3, and MLKL. In conclusion, these results suggest that topical application of LIRA@PLGA/HA is effective for the treatment of DP through inhibition of necroptosis, representing a promising treatment strategy.

Objectives: While studies have begun to suggest a potential link between periodontal disease and cancer, there remains a paucity of comprehensive investigations into its association with specific cancer incidence and mortality. This study aimed to analyze association between three oral diseases and site-specific cancer incidence and mortality. Methods: A retrospective cohort study was conducted on a population of 3,845,280, utilizing data sourced from the Korean National Health Insurance Database from 2006 to 2019, supplemented by National Statistics Data from 2010 to 2019. Cox proportional hazards models were applied to estimate the association between oral disease (dental caries, gingivitis, and tooth loss) and site-specific cancer risk of incidence and mortality. Results: After a median follow up of 10.11 years, we identified 181,754 new cancer cases and 37,135 deaths from cancer. Tooth loss was significantly associated with stomach cancer (adjusted hazard ratio (aHR): 1.08, 95% confidence interval (CI): 1.05-1.11), colorectal cancer (1.13, 1.09-1.16), liver cancer (1.09, 1.04-1.14), and lung cancer (1.04, 1.01-1.08) incidences. Tooth loss was significantly associated with mortality for total cancer (1.12, 1.09-1.14), stomach cancer (1.21, 1.12-1.31), colorectal cancer (1.14, 1.05-1.23), liver cancer (1.16, 1.09-1.23), lung cancer (1.08, 1.03-1.13), and prostate cancer (1.24, 1.04-1.47) mortality. Gingivitis was significantly associated with liver cancer incidence and mortality (1.08, 1.03-1.13; 1.11, 1.05-1.18). Conclusions: The results of this study showed that not only tooth loss but also gingivitis, an early stage of periodontal disease, may increase the risk of cancer incidence and mortality. Improving oral health can be prioritized to enhance overall public health, including reducing the risk of cancer.

Background/Objectives: The oral health disorder periodontal disease is widespread around the world and has a public health dimension. This study aimed to perform a systematic review and an appraised analysis that looks at both the prevalence and diversity of risk factors associated with periodontal disease in Saudi Arabia. It places a particular focus on subgroup analyses and pooled prevalence estimates to identify certain populations that could be described as high risk. Methods: Several databases, including PubMed, Scopus, and Google Scholar, were used to conduct the present systematic review. The search was designed to identify relevant studies published from 1980 to 2023. Both quantitative and qualitative studies were included. Subgroup analyses and meta-analyses were performed using a random-effects model to calculate pooled prevalence rates. The studies were evaluated using three criteria that focused on bias. Finally, the authors created a narrative synthesis of the review findings for ease of understanding. Results: The pooled overall prevalence of periodontal disease was 46.2% (95% CI: 40.5-51.8), with high heterogeneity (I2 = 85%). Subgroup analyses identified obese adults as having the highest prevalence of this condition (71.3%), and individuals diagnosed with diabetes also displayed a significantly high prevalence (52.1%). Adolescents aged 15-19 years had an age-specific prevalence of 8.6%, which was significantly lower than that of the other age groups analyzed. Poor oral hygiene, tobacco use, diabetes, and obesity have been recognized as risk factors for periodontal disease. Conclusions: The substantial burden of periodontal disease in Saudi Arabia, especially among high-risk groups, such as obese and diabetic adults, cannot be overstated. Our public health initiatives need to focus on these high-risk individuals, who are likely to be both periodontally and systemically compromised, to provide lifestyle modification counseling and oral hygiene education for them, as well as to routinize their dental care in a way that minimizes the chances of becoming periodontally compromised.

Periodontitis is a widespread disease, associated with challenges both in its diagnosis and in selecting from various therapeutic approaches, which do not always yield the expected success. This literature review was conducted to explore diverse therapeutic approaches, especially those focused on nanotechnologies, and their potential contribution to the successful modulation of the host's response. The effects of the existing microbial diversity and the imbalance of key microbial species in contributing to the progression and worsening of the host's response in periodontitis are well known. It is essential to understand the role of a well-structured treatment plan for periodontitis, providing opportunities for new research and innovative treatment strategies aimed at reducing the impact of periodontitis on oral and overall systemic health. This will be beneficial for dental professionals, enabling them to effectively prevent and treat periodontitis, ultimately improving the overall health and well-being of patients.

Periodontitis (PD) and type 2 diabetes mellitus (T2DM) represent interlinked global health burdens, commonly causing significant clinical complications when coincident. Therefore, managing both conditions (T2DM with periodontitis, DP) simultaneously poses considerable challenges, necessitating novel therapeutic strategies. KQJF has been clinically proven to treat DP with good efficacy, but its pharmacological substances and targets are not clear and urgently need to be clarified.

To define the potential active components and targets of KQJF for the treatment of DP.

The investigation commenced with the application of UPLC-Q-TOF/MS analysis to delineate the active constituents of KQJF and their associated targets in addressing DP. Additionally, the research incorporated subsequent methodologies such as machine learning, network pharmacology, molecular docking, molecular dynamics simulations, and a DP rat model was established and validated by in vivo experiments using H&E staining, immunohistochemistry, quantitative real-time PCR, and Western blot.

KQJF was found to contain 49 prototype compounds and 121 metabolites with potential activity against PD and T2DM. Network pharmacology revealed 66 overlapping genes between the pharmacological targets of KQJF and known targets of PD and T2DM. Further exploration through PPI network and enrichment analyses illuminated the involvement of multi-target and multi-pathway mechanisms. Molecular docking and dynamics simulations confirmed the robust interactions between key compounds within KQJF and proteins associated with the diseases. In vivo validation demonstrated that KQJF treatment ameliorated DP-associated histopathological changes and modulated the expression of crucial proteins (including ABCG2, CCND1, CDKN1B, HIF1A, and PIK3R1) in a DP rat model.

In summary, KQJF exhibits potential therapeutic benefits for DP through a multi-component and multi-target approach, potentially offering a novel integrative treatment strategy. This study underscores the importance of integrating traditional medicine with modern molecular techniques to explore novel therapeutic avenues for complex comorbid conditions, providing a blueprint for future pharmacological explorations.

Neurodegenerative diseases (NDDs) represent a considerable global health burden with no definitive treatments. Emerging evidence suggests that periodontitis may contribute to NDD through shared inflammatory, microbial, and genetic pathways. A retrospective cohort design was applied to analyze hospital records from 2012-2022 and to determine whether periodontitis independently increases NDD risk when accounting for major cardiovascular, cerebrovascular, metabolic, and inflammatory confounders. Likelihood ratio-based Cox regression tests and Weibull survival models were applied to assess the association between periodontitis and NDD risk. Model selection was guided by Akaike and Bayesian information criteria, while Harrell's C-index and receiver operating characteristic curves evaluated predictive performance. Periodontitis demonstrated an independent association with neurodegenerative disease risk (HR 1.43, 95% CI 1.02-1.99). Cerebral infarction conferred the highest hazard (HR 4.81, 95% CI 2.90-7.96), while pneumonia (HR 1.96, 95% CI 1.05-3.64) and gastroesophageal reflux disease (HR 2.82, 95% CI 1.77-4.51) also showed significant increases in risk. Older individuals with periodontitis are at heightened risk of neurodegenerative disease, an effect further intensified by cerebrovascular, cardiometabolic, and gastroesophageal conditions. Pneumonia also emerged as an independent pathophysiological factor that may accelerate disease onset or progression. Attention to oral and systemic factors through coordinated clinical management may mitigate the onset and severity of neurodegeneration.

Odontogenic ameloblast-associated protein (ODAM) is a small secretory protein produced by the junctional epithelium (JE) and mature ameloblasts. It plays a role in odontogenesis and mediates the adhesion of JE to enamel. We used human gingival epithelial cells to evaluate the mechanism of ODAM gene expression regulation in the JE by interleukin (IL)-6.

Ca9-22, Sa3, and HSY cells were stimulated with IL-6 (10 ng/mL), after which total RNA and proteins were extracted. Real-time polymerase chain reaction and Western blot analyses were performed to assess the expression levels of ODAM mRNA and protein. Luciferase (LUC) assays were employed using LUC constructs with varying lengths of the ODAM gene promoter sequence. Gel mobility shift and chromatin immunoprecipitation (ChIP) analyses were conducted to investigate the binding of transcription factors to response elements within the gene promoter.

Treatment with IL-6 increased the expressions of ODAM mRNA and protein. Additionally, it induced promoter activity of the ODAM gene, while LUC activity was suppressed by inhibitors of protein kinase A, tyrosine kinase, MEK1/2, phosphatidylinositol 3-kinase, nuclear factor-κB, signal transducer and activator of transcription (STAT) 3, and glycoprotein 130. Gel mobility shift and ChIP analyses revealed that IL-6 induced the binding of yin yang 1 (YY1), CCAAT/enhancer-binding protein (C/EBP) β, GATA binding protein (GATA), and phospho-STAT3 to the YY1, C/EBP, GATA, and interferon-γ activated transcriptional element (GATE) 1-3 elements.

These findings indicate that IL-6 upregulates ODAM gene expression by targeting the YY1, C/EBP, GATA, and GATE1-3 elements in the promoter region of the human ODAM gene.

This study aims to summarize recent studies available on untargeted metabolomics employed for periodontitis diagnosis, from saliva and gingival crevicular fluid samples, to identify recurring metabolites with biomarker-value potential. A secondary objective was to analysudurue the protocols of existing studies, to facilitate further research.

Three databases were electronically searched for relevant studies (PubMed, Web of Science, Scopus). Risk of bias assessment was performed using the Newcastle-Ottawa scale (NOS). Data was extracted from studies, regarding general characteristics and conclusions, population characteristics, periodontal protocols, and metabolomics protocols. Metabolic pathway analysis was performed for recurrent metabolites.

After screening 405 studies, 13 studies (10 using saliva samples, 3 using GCF samples) were included. 22 metabolites were identified in more than one study and included into the pathway analysis. Butyrate, lactate, isoleucine, glucose, pyruvate, isovalerate, hypoxanthine/xanthine, proline, valine, phenylalanine, and ethanol were most frequently encountered and were found upregulated in periodontitis patients compared to periodontally healthy patients.

Metabolomics could provide valuable opportunities in validating potential biomarkers or diagnosis panels, contributing to the screening, prognosis, progression and monitoring of periodontitis. Further studies on larger populations and using established protocols are needed. (PROSPERO CRD42023470339).

Periodontitis is a prevalent yet frequently overlooked oral disease that is linked to a range of systemic conditions. Although basic treatment and periodontal surgery can alleviate the symptoms of periodontitis to a certain extent, the treatment of severe tissue defects or refractory cases is not effective. Extracellular vesicles (EVs) are subcellular lipid bilayer particles that come from a variety of sources and are prevalent in the biological fluids of vertebrates. They play a key role in intercellular communication by transporting multiple signaling molecules. Recent research has indicated that EVs derived from periodontal pathogens can trigger periodontitis, exacerbate the periodontal damage, and potentially disseminate to other parts of the body, leading to systemic conditions. Conversely, extracellular vesicles derived from dental stem cells (DSCs) have demonstrated the ability to regulate the local periodontal immune environment and foster the regeneration and repair of periodontal tissues, positioning them as a promising candidate for cell-free therapeutic approaches to periodontitis. This review aims to summarize the latest research on the involvement of EVs from different sources in the pathogenesis and treatment of periodontitis, especially to systematically elucidate the mechanism of EVs secreted by periodontal pathogens in periodontitis-related systemic diseases for the first time. By uncovering these complex regulatory processes, new and more effective therapeutic approaches can be explored in the battle against periodontitis and its associated systemic diseases.

Diabetes exacerbates the occurrence and severity of periodontitis, the pathogenesis of diabetic periodontitis (DPD) is influenced by the delayed resolution of inflammation. Eldecalcitol (ED-71) has shown promise in preventing bone loss in DPD. We herein aimed to investigate the role of ED-71 in the inflammatory regression phase of DPD and elucidate the underlying mechanisms. Type-2 diabetes was induced by streptozotocin injection in Wistar rats, and to explore the in vivo effect of ED-71 on macrophage efferocytosis, periodontitis was induced by ligation combined with lipopolysaccharide. Alveolar bone destruction was assessed using micro-computed tomography, hematoxylin-eosin, immunohistochemistry, and tartrate-resistant acid phosphatase staining. Immunofluorescence staining and flow cytometry detected neutrophils, apoptotic cells, and macrophage polarization in periodontal tissue. Additionally, flow cytometry, real-time polymerase chain reaction, western blotting, and enzyme-linked immunosorbent assay were used to examine macrophage efferocytosis and changes in store-operated calcium entry (SOCE). We found that rats with diabetes exhibited more severe alveolar bone destruction and increased neutrophil aggregates in periodontal tissue. Following the ED-71 administration, alveolar bone loss significantly decreased, and the immune microenvironment of periodontal tissue tended to suppress inflammation. Macrophages stimulated with high glucose experienced disruption of SOCE machinery, leading to the inhibition of efferocytosis in vitro. ED-71 demonstrated the ability to restore macrophage efferocytosis by correcting SOCE, and preventing sustained inflammatory damage to periodontal tissue. In conclusion, diabetes impairs macrophage efferocytosis and M2 polarization in periodontitis rats, resulting in the delayed resolution of inflammation. ED-71 could attenuate alveolar bone loss by mitigating macrophage via SOCE machinery in DPD.

The oral-gut microbiota axis plays a crucial role in cardiometabolic health. This review explores the interactions between these microbiomes through enteric, hematogenous, and immune pathways, resulting in disruptions in microbial balance and metabolic processes. These disruptions contribute to systemic inflammation, metabolic disorders, and endothelial dysfunction, which are closely associated with cardiometabolic diseases. Understanding these interactions provides insights for innovative therapeutic strategies to prevent and manage cardiometabolic diseases.

The aging population is increasingly affected by periodontal disease, a condition often overlooked due to its asymptomatic nature. Despite its silent onset, periodontitis is linked to various systemic conditions, contributing to severe complications and a reduced quality of life. With over a billion people globally affected, periodontal diseases present a significant public health challenge. Current diagnostic methods, including clinical exams and radiographs, have limitations, emphasizing the need for more accurate detection methods. This study aims to develop AI-driven models to enhance diagnostic precision and consistency in detecting periodontal disease.

We analyzed 2,000 panoramic radiographs using image processing techniques. The YOLOv8 model segmented teeth, identified the cemento-enamel junction (CEJ), and quantified alveolar bone loss to assess stages of periodontitis.

The teeth segmentation model achieved an accuracy of 97%, while the CEJ and alveolar bone segmentation models reached 98%. The AI system demonstrated outstanding performance, with 94.4% accuracy and perfect sensitivity (100%), surpassing periodontists who achieved 91.1% accuracy and 90.6% sensitivity. General practitioners (GPs) benefitted from AI assistance, reaching 86.7% accuracy and 85.9% sensitivity, further improving diagnostic outcomes.

This study highlights that AI models can effectively detect periodontal bone loss from panoramic radiographs, outperforming current diagnostic methods. The integration of AI into periodontal care offers faster, more accurate, and comprehensive treatment, ultimately improving patient outcomes and alleviating healthcare burdens.

Periodontitis is a chronic inflammatory disease affecting the gingival tissues and supporting structures of the teeth, often leading to tooth loss. The condition begins with the accumulation of dental plaque, which initiates an immune response. Current radiographic methods for assessing alveolar bone loss are subjective, time-consuming, and labor-intensive. This study aims to develop an AI-driven model using Convolutional Neural Networks (CNNs) to accurately assess alveolar bone loss and provide individualized periodontal prognoses from panoramic radiographs.

A total of 2,000 panoramic radiographs were collected using the same device, based on the periodontal diagnosis codes from the HOSxP Program. Image enhancement techniques were applied, and an AI model based on YOLOv8 was developed to segment teeth, identify the cemento-enamel junction (CEJ), and assess alveolar bone levels. The model quantified bone loss and classified prognoses for each tooth.

The teeth segmentation model achieved 97% accuracy, 90% sensitivity, 96% specificity, and an F1 score of 0.80. The CEJ and bone level segmentation model showed superior results with 98% accuracy, 100% sensitivity, 98% specificity, and an F1 score of 0.90. These findings confirm the models' effectiveness in analyzing panoramic radiographs for periodontal bone loss detection and prognostication.

This AI model offers a state-of-the-art approach for assessing alveolar bone loss and predicting individualized periodontal prognoses. It provides a faster, more accurate, and less labor-intensive alternative to current methods, demonstrating its potential for improving periodontal diagnosis and patient outcomes.

This paper aims to review the immunopathogenesis of Diabetes-associated periodontitis (DPD) and to propose a description of the research progress of drugs with potential clinical value from an immunotherapeutic perspective.

A comprehensive literature search was conducted in PubMed, MEDLINE, Embase, Web of Science, Scopus and the Cochrane Library. Inclusion criteria were studies on the association between diabetes and periodontitis using the Boolean operator "AND" for association between diabetes and periodontitis, with no time or language restrictions. Search terms included diabetes mellitus, periodontitis, immunopathogenesis, specific immunity, non-specific immunity, flora, estrogen, pharmacological treatment, immunotherapy.

Alterations in the subgingival flora environment in a hyperglycemic environment elicit an immune response. Overactivity/suppression of nonspecific immune cells and impaired cellular defenses trigger specific immune responses. Epigenetics as well as female hormones also play a role. There is already a small amount of clinical evidence for the role of metronidazole, subantimicrobial doses of doxycycline, minocycline hydrochloride, and metformin in the treatment of DPD. Some preclinical studies have also accumulated experimental evidence for the improved effects of vitamin D3 and other drugs on DPD.

The development of diabetic periodontitis is immunologically linked to a state of immune imbalance and therefore holds great promise for the use of immunotherapeutic drugs.

Immunotherapy with drugs along with periodontal nonsurgical treatment could provide ideas for DPD treatment based on the immunopathogenesis of DPD.

Background/Objectives: Diabetes mellitus and periodontitis share a significant, bidirectional relationship. Diabetes raises the risk of periodontitis and influences its severity, impacting tissue repair and bone metabolism. Conversely, periodontal inflammation can disrupt glycemic control, further complicating this interlinked relationship. This systematic review aimed to evaluate the efficacy of antimicrobial photodynamic therapy (aPDT) as an adjunct to subgingival instrumentation (SI) in the treatment of periodontal pockets with a probing pocket depth (PPD) ≥ 5 mm in individuals with type 2 diabetes mellitus (DM2) and periodontitis. Methods: Using the PICOS framework, this review addressed the following question: "How does aPDT as an adjunct to SI compare to SI alone in treating periodontal pockets with PPD ≥ 5 mm in individuals with DM2 and periodontitis?" Databases searched included PubMed, Scopus, and Web of Science up to December 2024. Randomized clinical trials evaluating periodontal status and HbA1c levels in patients with DM2 undergoing periodontal therapy and experiencing SI were included. Patients who received adjunctive aPDT were compared to a control group that received SI alone. A meta-analysis was conducted illustrating treatment effects across groups. Results: After screening 117 studies based on titles and abstracts, three and four studies met the eligibility criteria for quantitative and qualitative analyses, respectively. The principal periodontal parameters assessed included PPD, clinical attachment level (CAL), plaque index (PI), and bleeding on probing (BOP). Forest plots for PD, BOP, PI, and CAL at baseline, three months, and six months revealed no statistically significant differences between the SI+aPDT group and the SI-only group. Glycated hemoglobin across treatment groups was not different. Conclusions: The combination of aPDT with SI provides limited clinical benefits in treating periodontal pockets with a PPD ≥ 5 mm in diabetic patients with periodontitis.

Chronic diseases have emerged as a paramount global health burden, accounting for 74% of global mortality and causing substantial economic losses. The oral cavity serves as a critical indicator of overall health and is inextricably linked to chronic disorders. Neglecting oral health can exacerbate localized pathologies and accelerate the progression of chronic conditions, whereas effective management has the potential to reduce their incidence and mortality. Nevertheless, limited resources and lack of awareness often impede timely dental intervention, delaying optimal therapeutic measures. This review provides a comprehensive analysis of the impact of prevalent chronic diseases-such as diabetes mellitus, rheumatoid arthritis, cardiovascular disorders, and chronic respiratory diseases-on oral health, along with an exploration of how changes in oral health affect these chronic conditions through both deterioration and intervention mechanisms. Additionally, novel insights into the underlying pathophysiological mechanisms governing these relationships are presented. By synthesizing these advancements, this review aims to illuminate the complex interrelationship between oral health and chronic diseases while emphasizing the urgent need for greater collaboration between dental practitioners and general healthcare providers to improve overall health outcomes.

Chronic periodontal disease primarily causes tooth loss and oral frailty and is linked to chronic conditions such as diabetes mellitus. However, its progression and broader studies on chronic diseases have not been well explored. This study aimed to investigate this association using claims data.

This retrospective cohort study used linked medical, dental, and pharmacy claims data from a local municipality in Japan. The study included participants aged 40-70 years who had received medical care between April 2017 and March 2018. Exposures included age, sex, and common chronic diseases previously reported to be associated with periodontal diseases (21 diseases). We defined the outcome, "progression of severe periodontitis" as the worsening of periodontal disease to a severe stage requiring surgery or tooth extraction, determined by the presence of a periodontal surgery code or a deeper probing pocket depth (≥6 mm) code along with the tooth extraction procedure code. The participants were followed up until March 2022, and multivariate analysis was conducted using Cox proportional hazard models.

Among 28,846 participants, 1035 (3.6%) progressed to severe periodontal disease. In the multivariate analysis, only diabetes mellitus was significantly associated with severe periodontal disease, with a hazard ratio of 1.26 (95% confidence interval, 1.08-1.53) among all chronic diseases.

Patients with diabetes mellitus had a high risk of severe periodontal disease progression, suggesting that proactive dental visits should be recommended to prevent severe periodontal disease.

Artificial intelligence (AI) acts as the state-of-the-art in periodontitis diagnosis in dentistry. Current diagnostic challenges include errors due to a lack of experienced dentists, limited time for radiograph analysis, and mandatory reporting, impacting care quality, cost, and efficiency.

This review aims to evaluate the current and future trends in AI for diagnosing periodontitis.

A thorough literature review was conducted following PRISMA guidelines. We searched databases including PubMed, Scopus, Wiley Online Library, and ScienceDirect for studies published between January 2018 and December 2023. Keywords used in the search included "artificial intelligence," "panoramic radiograph," "periodontitis," "periodontal disease," and "diagnosis."

The review included 12 studies from an initial 211 records. These studies used advanced models, particularly convolutional neural networks (CNNs), demonstrating accuracy rates for periodontal bone loss detection ranging from 0.76 to 0.98. Methodologies included deep learning hybrid methods, automated identification systems, and machine learning classifiers, enhancing diagnostic precision and efficiency.

Integrating AI innovations in periodontitis diagnosis enhances diagnostic accuracy and efficiency, providing a robust alternative to conventional methods. These technologies offer quicker, less labor-intensive, and more precise alternatives to classical approaches. Future research should focus on improving AI model reliability and generalizability to ensure widespread clinical adoption.

Periodontitis, one of the most common forms of periodontal disease, has been linked to several cardiovascular factors including metabolic syndrome and inflammatory processes. This study aimed to determine the association between type 2 diabetes mellitus (T2DM) and periodontitis in a representative sample of individuals in the north of Peru.

Secondary data analysis using information of a population-based survey, enrolling subjects aged 35 to 69 years. The outcome was periodontitis, evaluated using a self-reported and validated 8-item questionnaire (≥5 points compatible with severe periodontitis compared to those without severe periodontitis), whereas the exposure was the presence of T2DM, evaluated using results of oral glucose tolerance test and categorized into two different forms: (a) normoglycemic, prediabetes, and T2DM, and (b) without T2DM, with T2DM and <5 years of diagnosis, and with T2DM and ≥5 years of diagnosis. Poisson regression models were utilized to report prevalence ratios (PR) and 95% confidence intervals (95% CI).

Data from 1606 individuals were analyzed, with a mean age of 48.2 (SD: 10.6) years, and 50.3% were women. Of these, 272 (16.9%) had prediabetes and 176 (11.0%) had T2DM (71.6% with <5 years of disease). Overall, 97.0% presented at least one symptom compatible with periodontitis, 882 (55.0%) had mild, 643 (40.0%) had moderate, and 5% had severe periodontitis. In multivariable model, those with T2DM had a higher prevalence of severe periodontitis (PR = 1.99; 95% CI: 1.12 - 3.54). Similarly, those with <5 years of disease had a higher prevalence of severe periodontitis (PR = 2.48; 95% CI: 1.38 - 4.46).

Our research confirms the association between T2DM and severe periodontitis, especially among those with recent diagnosis (<5 years). Symptoms of periodontitis are quite common in our study population. Our results suggest a need to periodically assess oral health in patients with T2DM.

There is an ongoing controversy regarding the expression of vitamin D receptor (VDR) and binding protein (VDBP) genes, as well as their polymorphisms, in periodontitis. We examined eight single nucleotide polymorphisms (SNPs) and performed a transcriptome-level bioinformatics analysis to clarify their relationship with periodontitis.

To explore VDR and VDBP polymorphisms, 600 subjects were included, including 307 patients with chronic periodontitis (CP) and 293 healthy controls. Genomic DNA was extracted from peripheral venous blood collected from each subject. A MassARRAY system was used to detect SNPs, including rs1544410G/A (BsmI), rs2228570C/T (FokI), rs7975232G/T (ApaI), rs731236T/C (TaqI), rs739837G/T, rs9729G/T, and rs3847987C/A in the VDR gene, and rs7041A/C in the VDBP gene. Then, we analyzed transcriptome sequencing datas of gingival tissues from two single-cell transcriptome sequencing studies to identify differential expression profiles. The objective was to further explore the potential association between VDR gene and gingival tissues in individuals with CP.

The regression analysis model revealed a significant relationship between rs739837G/T (P = 0.04) and rs7041A/C (P = 0.03) polymorphisms and CP susceptibility. Subjects carrying the TT genotype of rs739837 showed a decreased risk of developing CP compared to those carrying the GG + GT genotype (OR = 0.53, 95% CI = 0.29-0.99). Individuals carrying the AC + CC genotype of rs7041 showed a reduced risk of developing CP compared to those with the AA genotype (OR = 0.70, 95% CI = 0.51-0.97). Furthermore, allele C of rs7041 was found to have a protective effect against periodontitis (P = 0.03, OR = 0.75, CI = 0.58-0.98). However, no association was found between CP susceptibility and six other 6 SNPs (rs1544410, rs2228570, rs7975232, rs9729, rs731236, and rs3847987). Differential levels of VDR transcription were observed in gingival tissues during CP.

VDR genetic variability and transcriptional expression are significant factors affecting susceptibility to CP. These findings suggested that rs739837 TT in VDR and rs7041 A/C in VDBP may be protective against periodontitis.

Diabetic periodontitis (DP) stems from hyperglycemia-driven oxidative stress amplification and chronic inflammation, leading to periodontal tissue breakdown. Misregulated forkhead box protein M1 (FOXM1) play key roles in this process, exacerbating both inflammation and oxidative stress. In light of N-Acetylcysteine (NAC)'s potent anti-oxidative capacity and anti-inflammatory potential, understanding how it modulates these central pathways to alleviate DP holds high scientific and clinical importance. An animal model of diabetic mice periodontitis was established, and the model mice were injected with FOXM 1 adenovirus to enrich FOXM 1, and the periodontal pathological histology of each group was evaluated by HE staining. Western blotting and RT-PCR evaluated the expression levels of factors involved in bone destruction. ELISA evaluated the amount of inflammatory factors in mice serum. FOXM 1 over-expression and NAC were treated in murine macrophages, and the intracellular reactive oxygen species(ROS) levels in macrophages were measured using a DCFH-DA probe. Receptor activator of NF-κB ligand (RANKL) and lipopolysaccharide (LPS) were used to establish the macrophage osteoclast differentiation model and test the expression level of osteoclast differentiation factors after giving NAC. Hydrogen peroxide was used to establish a peroxidation environment, the plasmid silenced C-JUN, and the DNA binding activity of activating protein-1(AP1) was detected by EMSA. The effect of peroxidation on the osteoclast differentiation level was determined by WB. Mice with DP model had epithelial damage and inflammatory infiltration in periodontal tissues, and in the FOXM1 enriched group, the periodontal epithelial damage was repaired and inflammation was alleviated. FOXM1 enrichment resulted in DP model lower expression of RANKL (P < 0.01), macrophage colony-stimulating factor (M-CSF) (P < 0.01) and elevated expression of osteoprotegerin (OPG) (P < 0.001). Serum levels of pro-inflammatory factors interleukin (IL)-1β, tumor necrosis factor (TNF-α), and inducible nitric oxide synthase (iNOS) were elevated in DP mice (P < 0.001), and anti-inflammatory factor IL-10 was reduced(P < 0.001),, and FOXM1 enrichment significantly reversed inflammatory factor levels (P < 0.01). Overexpression of FOXM1 reduced ROS content in macrophages (P < 0.001), and NAC was performed to further reduce ROS content (P < 0.01). Silencing of FOXM1 elevated the expression of osteoclast-specific genes NFATc1, TRAP and OSCAR (P < 0.01), and the addition of NAC on top of silencing of FOXM1 markedly suppressed the expression level of osteoclast-specific genes (P < 0.01). ROS increased the transcriptional activity of AP1 (P < 0.001), which promoted osteoclast-specific gene expression (P < 0.001), and osteoclast-specific gene expression was decreased after silencing C-JUN (P < 0.01). FOXM1 relieve diabetic periodontitis inflammation and promote bone formation, regulates ROS production and ROS increases the transcriptional activity of AP1 and affects the osteoclastic differentiation of macrophages, which plays a positive role in bone protection in diabetic periodontitis.

Diabetes mellitus is a chronic metabolic disease characterized by abnormally elevated blood glucose levels. Type II diabetes accounts for approximately 90% of all cases. Several drugs are available for hyperglycemia treatment. However, the current therapies for managing high blood glucose do not prevent or reverse the disease progression, which may result in complications and adverse effects, including diabetic neuropathy, retinopathy, and nephropathy. Hence, developing safer and more effective methods for lowering blood glucose levels is imperative. Transient receptor potential vanilloid-1 (TRPV1) is a significant member of the transient receptor potential family. It is present in numerous body tissues and organs and performs vital physiological functions.

This review aimed to develop new targeted TRPV1 hypoglycemic drugs by systematically summarizing the mechanism of action of the TRPV1-based signaling pathway in preventing and treating diabetes and its complications.

Literature searches were performed in the PubMed, Web of Science, Google Scholar, Medline, and Scopus databases for 10 years from 2013 to 2023. The search terms included "diabetes," "TRPV1," "diabetic complications," and "capsaicin."

TRPV1 is an essential potential target for treating diabetes mellitus and its complications. It reduces hepatic glucose production and food intake and promotes thermogenesis, metabolism, and insulin secretion. Activation of TRPV1 ameliorates diabetic nephropathy, retinopathy, myocardial infarction, vascular endothelial dysfunction, gastroparesis, and bladder dysfunction. Suppression of TRPV1 improves diabetes-related osteoporosis. However, the therapeutic effects of activating or suppressing TRPV1 may vary when treating diabetic neuropathy and periodontitis.

This review demonstrates that TRPV1 is a potential therapeutic target for diabetes and its complications. Additionally, it provides a theoretical basis for developing new hypoglycemic drugs that target TRPV1.

Numerous systematic reviews and meta-analyses have been published that evaluate the association between periodontal disease and systemic diseases, many of which address similar topics. Moreover, their quality requires assessment. Therefore, we performed a cross-sectional analysis to examine the evidence on the relationship between periodontal disease and systemic diseases.

The PubMed, Embase, Web of Science, and the Cochrane Library databases were systematically searched to identify relevant systematic reviews and meta-analyses. Only studies that considered periodontal disease as the exposure factor and various systemic diseases as the outcome were included. The basic characteristics and pertinent data from the selected studies were extracted. The modified version of A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) was employed for quality assessment, while R software was used for statistical analysis.

Among the 212 relevant systematic reviews and meta-analyses, 57 were finally included in our analysis. These studies involved 75 diseases and 81 disease-related outcomes, with cancer (19/81) being the most frequently addressed topic. Of the 81 outcomes, 67 demonstrated a significant association. Notably, the highest risk estimate was found for head and neck cancer [odds ratio (OR) = 3.17, 95% confidence interval (CI) 1.78 - 5.64], while the lowest was observed for premature rupture of the amniotic sac [relative risk (RR) = 1.10, 95% CI 1.08 - 1.12]. The methodological quality ratings indicated that approximately 71.93% of included studies were classified as "Critically low", with another 17.54% rated as "Low", and only about 10.53% categorized as "Moderate".

Periodontal disease significantly elevates the risks associated with 15 cancer-related, 8 cardiovascular-related, 8 metabolic-related, and 5 neurological-related outcomes. However, the overall methodological quality of existing systematic reviews and meta-analyses is generally suboptimal and requires enhancement to generate higher-quality evidence in the future.

To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clustering patterns of clinical blood biochemical indicators.

Data regarding clinical blood biochemical indicators and periodontitis prevalence among 1804 patients with diabetes were sourced from the National Health and Nutrition Examination Survey (NHANES) database spanning 2009 to 2014. A clinical prediction model for periodontitis risk in patients with diabetes was constructed via the XGBoost machine learning method. Furthermore, the relationships between diabetes patient clusters and periodontitis prevalence were investigated through consistent consensus clustering analysis.

Seventeen clinical blood biochemical indicators emerged as superior predictors of periodontitis in patients with diabetes. Patients with diabetes were subsequently categorized into two subtypes: Cluster A presented a slightly lower periodontitis prevalence (74.80%), whereas Cluster B presented a higher prevalence risk (83.68%). Differences between the two groups were considered statistically significant at a p value of ≤0.05. There was marked variability in the associations of different cluster characteristics with periodontitis prevalence.

Machine learning combined with consensus clustering analysis revealed a greater prevalence of periodontitis among patients with diabetes mellitus in Cluster B. This cluster was characterized by a smoking habit, a lower education level, a higher income-to-poverty ratio, and higher levels of albumin (ALB g/L) and alanine aminotransferase (ALT U/L).

Periodontitis is one of the most common complications of diabetes, which seriously affects patients' life quality. It is important to find the key factors and mechanisms to improve the treatment of periodontitis. In our study, high glucose (HG) and lipopolysaccharide (LPS) treated human periodontal ligament cells (hPDLCs) and LPS treated diabetic mice was used to establish the diabetic periodontitis model in vitro and in vivo. O-linked beta-N-acetylglucosamine glycosylation (O-GlcNAcylation) and O-linked N-acetylglucosamine transferase (OGT) protein levels were detected by western blot assay. Cell counting kit-8, alkaline phosphatase (ALP), and alizarin red staining (ARS) assays were used to observe the O-GlcNAcylation and OGT effects on cell viability and osteoblast differentiation. Co-immunoprecipitation (Co-IP) assay was used to detect the relationship between OGT and ALP. The results showed that the levels of OGT and O-GlcNAcylation were significantly increased in both cell and mouse models. ALP and ARS staining results showed that silencing of OGT or inhibition of O-glycosylation notably improved osteogenic differentiation, increased the osteoprotegerin (OPG) protein levels and decreased the receptor activator for nuclear factor-κB Ligand (RANKL) protein levels of the HG and LPS treated hPDLCs. In diabetic periodontitis mice, knockdown of OGT relieved the injury of gingival tissue, increased the ALP and OPG levels and decreased the RANKL levels. Besides, ALP interacted with OGT protein, and OGT protein was found to act on ALP serine 513 glycosylation. In conclusion, our study demonstrated that excessive O-GlcNAcylation could restrain osteoblast differentiation by O-glycosylation in ALP.

This systematic review investigates the probable effect of proton pump inhibitor (PPI) use on the severity of periodontal disease and peri-implantitis and implant survival. We conducted a literature search in PubMed, Scopus, and Cochrane Central Library up to April 2024. Two review authors independently screened the title and abstracts and then the full texts of retrieved studies. Observational and clinical trial studies that assessed the association between PPI use and periodontal disease severity and peri-implantitis or implant survival were included. Data extraction from the included studies was done by 2 reviewers independently. Of 940 studies initially retrieved from online searching, 7 met the inclusion criteria. Three studies examined periodontitis, whereas 4 focused on peri-implantitis and implant longevity. On the contrary, evidence regarding the impact of PPI use on peri-implantitis and implant survival is conflicting. Therefore, more well-designed randomized controlled trials are warranted to come to a definite conclusion. Because PPIs alter the gut microbiome and affect bone, plus that the pathogenesis and etiology of periodontal disease are affected by bacteria within the periodontal pocket, it is hypothesized that they may affect periodontal pathogenesis.

The burgeoning field of microbiomics has unveiled significant insights into the role of the oral microbiome in the pathophysiology of Type 2 Diabetes Mellitus (T2DM), with this review focusing on recent advancements in diabetic oral microbiology, its clinical applications, and identifying factors that may affect study interpretations. A comprehensive review across various databases, including PubMed and Google Scholar, was conducted to collate original research data published in the past five years, specifically targeting studies exploring the impact of the oral microbiome on T2DM and emphasizing research that employs microbiomic approaches in clinical patient populations. The findings delineate the intricate interplay between T2DM and oral microbiome dysbiosis, highlighting significant microbial shifts following periodontal and antidiabetic treatments, and pointing to the complexity of the relationship between oral health and systemic disease. The observed oral microbial shifts in T2DM underscore the critical need for standardized research methodologies in microbiomic studies, suggesting that by adopting a unified approach, future research can more effectively elucidate the oral microbiome's role in T2DM. This could pave the way for innovative diagnostic and therapeutic strategies in managing T2DM and its oral health complications, thus making a pertinent overview of the work within the field.