Off-target activity of the 8 kb Dmp1-Cre results in the deletion of Tsc1 gene in mouse intestinal mesenchyme.

The Dmp1-Cre mouse, expressing Cre from an 8-kb DNA fragment of the mouse Dmp1 gene, is a common tool to study gene functions in osteocytes. Here we report that the deletion of Tsc1 (TSC complex subunit 1) by 8 kb Dmp1-Cre causes rectal prolapse in mice. Histological examination shows the presence of colon polyps in Tsc1-deficient mice in association with significantly larger colon and narrower lumen, which recapitulates the common polyps pathology in Tuberous Sclerosis, an autosomal dominant disorder caused by mutations in either TSC1 or TSC2. The intestine in Tsc1-deficient mice is also enlarged with the presence of taller villi. Using the Ai14 reporter mice that express a red fluorescence protein upon Cre recombination, we show that 8 kb Dmp1-Cre activity is evident in portion of the mesenchyme of the colon and small intestine. Lastly, our data show that Tsc1 deletion by Dmp1-Cre leads to an increased proliferation in the mesenchyme of colon, which at least partly contributes to the polyps pathology seen in this mouse model and is likely a contributing factor of the polyps in Tuberous Sclerosis.

The Role of DNA Methylation and Histone Modification in Periodontal Disease: A Systematic Review.

Despite a number of reports in the literature on the role of epigenetic mechanisms in periodontal disease, a thorough assessment of the published studies is warranted to better comprehend the evidence on the relationship between epigenetic changes and periodontal disease and its treatment. Therefore, the aim of this systematic review is to identify and synthesize the evidence for an association between DNA methylation/histone modification and periodontal disease and its treatment in human adults. A systematic search was independently conducted to identify articles meeting the inclusion criteria. DNA methylation and histone modifications associated with periodontal diseases, gene expression, epigenetic changes after periodontal therapy, and the association between epigenetics and clinical parameters were evaluated. Sixteen studies were identified. All included studies examined DNA modifications in relation to periodontitis, and none of the studies examined histone modifications. Substantial variation regarding the reporting of sample sizes and patient characteristics, statistical analyses, and methodology, was found. There was some evidence, albeit inconsistent, for an association between DNA methylation and periodontal disease. IL6, IL6R, IFNG, PTGS2, SOCS1, and TNF were identified as candidate genes that have been assessed for DNA methylation in periodontitis. While several included studies found associations between methylation levels and periodontal disease risk, there is insufficient evidence to support or refute an association between DNA methylation and periodontal disease/therapy in human adults. Further research must be conducted to identify reproducible epigenetic markers and determine the extent to which DNA methylation can be applied as a clinical biomarker.

Personalized scaffolding technologies for alveolar bone regenerative medicine.

The reconstruction of alveolar bone defects associated with teeth and dental implants remains a clinical challenge in the treatment of patients affected by disease or injury of the alveolus. The aim of this review was to provide an overview on advances made in the use of personalized scaffolding technologies coupled with biologics, cells and gene therapies that offer future clinical applications for the treatment of patients requiring periodontal and alveolar bone regeneration. Over the past decade, advancements in three-dimensional (3D) imaging acquisition technologies such as cone-beam computed tomography (CBCT) and precise scaffold fabrication methods such as 3D bioprinting have resulted in personalized scaffolding constructs based on individual patient-specific anatomical data. Furthermore, 'fiber-guiding' scaffold designs utilize topographical cues to guide ligamentous fibers to form in orientation towards the root surface to improve tooth support. Therefore, a topic-focused literature search was conducted looking into fiber-guiding and image-based scaffolds and their associated clinical applications.

Gingival Health Around Cervical Carious Lesions Restored with Calcium Silicate-based Cement (Biodentine™) Compared with Glass-ionomer Cement: A Randomized Clinical Trial.

AIM: The study aims to assess the gingival health around cervical lesions restored with calcium silicate-based cement (Biodentine™) compared to treatment with glass-ionomer cement (GIC). MATERIALS AND METHODS: A total of 28 healthy subjects with carious lesions on the cervical third of the buccal surfaces of posterior teeth (class V-Black's classification) have participated and were distributed over two equal groups. The participants in each group received one type of the tested cements: Biodentine™ or GIC. The oral hygiene and the gingival health of the restored teeth were evaluated clinically at 1, 3, and 6 month intervals. RESULTS: Comparing clinical parameters of gingival and periodontal tissues adjacent to cervical restorations indicated significant differences. Plaque index (PI) and gingival index (GI) were higher in the Biodentine™ group at 1, 3, and 6 months of evaluation with a significant difference (p < 0.05), a rise in pocket depth has been noticed at 3 and 6 months (p < 005). Gingival recession (GR) did not show any difference between groups (p > 0.05). Moreover, bleeding on probing (BOP) values were higher for Biodentine™ restorations compared with GIC with a significant difference (p < 0.05). CONCLUSION: Cervical restorations of Biodentine™ were associated with more plaque accumulation with a higher degree of gingival inflammation in comparison with GIC.

Human platelet-derived growth factor-BB (rhPDGF-BB) with collagen matrix for sinus elevation without using a bone graft.

BACKGROUND: This case report involves a 38-year-old male who presented to the clinic after experiencing complications from a tooth extraction, including a dislodged root segment in the sinus, a sinus wall fenestration on the palate, a residual bone height (RBH) of 3 mm, and inadequate healing of the soft tissue. He presented for implant placement. METHODS: Recombinant human platelet-derived growth factor-BB (rh-PDGF-BB) was applied to a wound dressing material and placed in the sinus cavity alongside a 4.8 × 10 mm dental implant (Straumann SP, Straumann, Andover, MA, USA.). As documented in the literature, a graftless sinus lift via a lateral window was performed using a split-thickness flap technique to elevate the sinus membrane, re-establish its integrity, and restore its barrier function. RESULTS: An 8-month cone beam computed tomography assessment showed a 6.2 mm vertical bone gain and complete implant coverage. CONCLUSION: This approach provided a successful alternative to shorten treatment duration and achieve favorable radiographic outcomes during early healing. KEY POINTS: The use of rhPDGF-BB and a collagen matrix in a sinus lift procedure emerges as a practical therapeutic option when grafting might lack predictability and notably consume more treatment time, while also achieving the desired bone height when used with a simultaneously placed implant.

Clustering by periodontitis-associated factors: A novel application to NHANES data.

BACKGROUND: Unsupervised clustering is a method used to identify heterogeneity among groups and homogeneity within a group of patients. Without a prespecified outcome entry, the resulting model deciphers patterns that may not be disclosed using traditional methods. This is the first time such clustering analysis is applied in identifying unique subgroups at high risk for periodontitis in National Health and Nutrition Examination Surveys (NHANES 2009 to 2014 data sets using >500 variables. METHODS: Questionnaire, examination, and laboratory data (33 tables) for >1,000 variables were merged from 14,072 respondents who underwent clinical periodontal examination. Participants with ≥6 teeth and available data for all selected categories were included (N = 1,222). Data wrangling produced 519 variables. k-means/modes clustering (k = 2:14) was deployed. The optimal k-value was determined through the elbow method, formula = ∑ (xi2 ) - ((∑ xi )2 /n). The 5-cluster model showing the highest variability (63.08%) was selected. The 2012 Centers for Disease Control and Prevention/American Academy of Periodontology (AAP) and 2018 European Federation of Periodontology/AAP periodontitis case definitions were applied. RESULTS: Cluster 1 (n = 249) showed the highest prevalence of severe periodontitis (43%); 39% self-reported "fair" general health; 55% had household income <$35,000/year; and 48% were current smokers. Cluster 2 (n = 154) had one participant with periodontitis. Cluster 3 (n = 242) represented the greatest prevalence of moderate periodontitis (53%). In Cluster 4 (n = 35) only one participant had no periodontitis. Cluster 5 (n = 542) was the systemically healthiest with 77% having no/mild periodontitis. CONCLUSION: Clustering of NHANES demographic, systemic health, and socioeconomic data effectively identifies characteristics that are statistically significantly related to periodontitis status and hence detects subpopulations at high risk for periodontitis without costly clinical examinations.

Association between periodontitis and systemic medication intake: A case-control study.

BACKGROUND: To investigate the frequency of systemic drugs taken by elderly patients with or without periodontitis and the possible association between medication consumption and the severity of periodontitis. METHODS: A total of 1221 patients, including 608 with generalized moderate to severe periodontitis (periodontitis group) and 613 age- and gender-matched individuals with healthy periodontium (healthy group) were selected. Systemic conditions, medications and periodontal status were recorded. Medication intake frequency (%) was compared using unconditional logistic regression. RESULTS: The top three most common medications were angiotensin-converting enzyme (ACE) inhibitors (17.9%), antidepressants (17.8%), and lipid-lowering medications (16.5%). Both ACE inhibitors and antidepressants showed statistically higher intake frequency in the periodontitis group relative to healthy controls (21.5% versus 14.4%; odds ratio [OR] = 1.64), (21.1% versus 14.5%, OR = 1.57) (P < 0.01). Additionally, intake of oral hypoglycemic agents, calcium channel blockers (CCB), insulin, and diuretics were significantly higher in the periodontitis group with OR = 2.49, 2.32, 2.08 and 1.79, respectively (P < 0.05). Several medications demonstrated a disease severity-dependent association comparing generalized severe periodontitis with moderate periodontitis and healthy group: oral hypoglycemic agents (17.4% versus 16.8% versus 8.0%), CCB (14.8% versus 14.4% versus 8.0%) and anticonvulsants (13.4% versus 7.7% versus 6.4%) with OR of 2.43, 1.99, and 2.28 (severe periodontitis versus healthy group), respectively. CONCLUSION: There was a significantly higher frequency of medication intake related to cardiovascular disease and diabetes in patients with periodontitis. A disease severity-dependence with medication intake frequency was also noted. This study provides indirect evidence for the possible relationship between systemic diseases and periodontitis.

Preventive healthcare policies in the US: solutions for disease management using Big Data Analytics.

Data-driven healthcare policy discussions are gaining traction after the Covid-19 outbreak and ahead of the 2020 US presidential elections. The US has a hybrid healthcare structure; it is a system that does not provide universal coverage, albeit few years ago enacted a mandate (Affordable Care Act-ACA) that provides coverage for the majority of Americans. The US has the highest health expenditure per capita of all western and developed countries; however, most Americans don't tap into the benefits of preventive healthcare. It is estimated that only 8% of Americans undergo routine preventive screenings. On a national level, very few states (15 out of the 50) have above-average preventive healthcare metrics. In literature, many studies focus on the cure of diseases (research areas such as drug discovery and disease prediction); whilst a minority have examined data-driven preventive measures-a matter that Americans and policy makers ought to place at the forefront of national issues. In this work, we present solutions for preventive practices and policies through Machine Learning (ML) methods. ML is morally neutral, it depends on the data that train the models; in this work, we make the case that Big Data is an imperative paradigm for healthcare. We examine disparities in clinical data for US patients by developing correlation and imputation methods for data completeness. Non-conventional patterns are identified. The data lifecycle followed is methodical and deliberate; 1000+ clinical, demographical, and laboratory variables are collected from the Centers for Disease Control and Prevention (CDC). Multiple statistical models are deployed (Pearson correlations, Cramer's V, MICE, and ANOVA). Other unsupervised ML models are also examined (K-modes and K-prototypes for clustering). Through the results presented in the paper, pointers to preventive chronic disease tests are presented, and the models are tested and evaluated.

Use of IL-1 ß, IL-6, TNF-α, and MMP-8 biomarkers to distinguish peri-implant diseases: A systematic review and meta-analysis.

OBJECTIVE: To investigate the use of peri-implant crevicular fluid (PICF) interleukin-1ß (IL-1ß), IL-6, tumor necrosis factor-α (TNF-α), and matrix metalloproteinase-8 (MMP-8) biomarkers in distinguishing between healthy implants (H), peri-implant mucositis (MU), and peri-implantitis (PI). MATERIAL AND METHODS: Electronic using three databases (Pubmed, EMBASE, and Cochrane) and manual searches were conducted for articles published up to March 2018 by two independent calibrated reviewers. Meta-analyses using a random-effects model were conducted for each of the cytokines; IL-1ß, IL-6, and TNF-α, to analyze standardized mean difference (SMD) between H and MU, MU and PI, H and PI with their associated 95% confidence intervals (CI). Qualitative assessment of MMP-8 was provided consequent to the lack of studies that provide valid data for a meta-analysis. RESULTS: Nineteen articles were included in this review. IL-1ß, IL-6, and TNF-α, levels were significantly higher in MU than H groups (SMD: 1.94; 95% CI: 0.87, 3.35; P < .001, SMD: 1.17; 95% CI: 0.16, 3.19; P = .031 and SMD: 3.91; 95% CI: 1.13, 6.70; P = .006, respectively). Similar results were obtained with PI compared to H sites (SMD: 2.21, 95% CI: 1.32, 3.11; P < .001, SMD: 1.72; 95% CI: 0.56, 2.87; P = .004 and SMD: 3.78; 95% CI: 1.67, 5.89; P < .001, respectively). IL-6 was statistically higher in PI than MU sites (SMD = 1.46; 95% CI: 0.36, 2.55; P = .009); while IL-1ß increase was not significant. Despite absence of meta-analysis, MMP-8 show to be a promising biomarker in detection of PI in literature. CONCLUSION: Within the limitations of this study, pro-inflammatory cytokines in PICF, such as IL-1ß and IL-6, can be used as adjunct tools to clinical parameters to differentiate H from MU and PI.