This study assessed the periodontal conditions of type 2 diabetes (T2DM) patients attending an Outpatient Center in North Italy and explored the associations between metabolic control and periodontitis. Periodontal health of 104 T2DM patients (61 men and 43 women, mean age of 65.3 ± 10.1 years) was assessed according to CDC/AAP periodontitis case definitions and Periodontal Inflamed Surface Area (PISA) Index. Data on sociodemographic factors, lifestyle behaviors, laboratory tests, and glycated hemoglobin (HbA1c) levels were collected by interview and medical records. Poor glycemic control (HbA1c ≥ 7%), family history of T2DM, and C-reactive protein levels were predictors of severe periodontitis. An increase in HbA1c of 1% was associated with a rise in PISA of 89.6 mm². On the other hand, predictors of poor glycemic control were severe periodontitis, waist circumference, unbalanced diet, and sedentary lifestyle. A rise in PISA of 10 mm² increased the odds of having HbA1c ≥ 7% by 2%. There is a strong bidirectional connection between periodontitis and poor glycemic control. The inflammatory burden posed by periodontitis represents the strongest predictor of poor glycemic control.

Pattern analysis of the salivary metabolic profile has been proven accurate in discriminating between generalized periodontitis (GP) patients and healthy individuals (HI), as this disease modifies the salivary concentrations of specific metabolites. Due to the scarcity of data from previous studies, this study aimed to evaluate if non-surgical periodontal therapy (NST) could affect the metabolomic profile in GP patients’ saliva and if it compares to that of HI. Unstimulated salivary samples were collected from 11 HI and 12 GP patients before and 3 months after NST. Nuclear Magnetic Resonance (NMR) spectroscopy, followed by a supervised multivariate statistical approach on entire saliva spectra and partial least square (PLS) discriminant analysis, were performed to obtain metabolic profiles. In the GP group, periodontal treatment improved all clinical parameters, but not all the diseased sites were eradicated. PLS revealed an accuracy of 100% in distinguishing between metabolic profiles of GP patients before and after NST. Orthogonal projection to latent structure was able to discriminate between the three groups of subjects with an accuracy of 85.6%. However, the post-NST metabolic profile of GP patients could not be completely assimilated to that of HI. Although NST may produce significant changes in the metabolic profile, GP patients maintained a distinctive fingerprint compared to HI.

The ultimate goal of periodontal regeneration is to restore the damaged alveolar bone proper, root cementum, and periodontal ligament with collagen fibers inserted into the root surface. The search for new regenerative strategies is a challenging field of periodontal research, and tissue engineering, using stem cells, has recently been shown as a promising approach. This paper aims at reviewing the current available literature on the use of stem cells for the treatment of periodontitis. Up to now, different mesenchymal stem cells (MSCs) have shown potential for periodontal regeneration in animal studies. The most investigated MSCs for periodontal regeneration are bone marrow MSCs (BMMSCs), periodontal ligament stem cells (PDLSCs), and dental pulp stem cells (DPSCs), which have shown very promising results in animal models. Few studies on humans are available but BMMSCs, PDLSCs, and DPSCs have been proven safe and effective. Clinical trials are sparse, but tend to support the efficacy of MSCs for periodontal regeneration. In the future, more human studies will be required to support the use of MSCs in daily clinical practice, especially in order to identify the best protocol to harvest, process, and graft MSCs. Future perspectives include trans-differentiation of somatic cells to generate induced pluripotent stem cells, homing procedures, the use of exogenous stem cells, and 3D-printed scaffolds.

Objectives: The aim of this in vitro study was to compare the efficacy of chemical and mechanical methods for decontamination of titanium dental implant surfaces previously infected with polymicrobial biofilms in a model simulating a peri-implant defect. Furthermore, the effect of each decontamination protocol on MG-63 osteoblast-like cells morphology and adhesion to the treated implants was assessed.Background: Peri-implantitis is a growing issue in dentistry, and evidence about implant surface decontamination procedures is lacking and inconclusive.Methods: A total of 40 previously biofilm-contaminated implants were placed into a custom-made model simulating a peri-implant defect and randomly assigned to five treatment groups: (C) control (no treatment); (AW) air abrasion without any powder; (ESC) air abrasion with powder of erythritol, amorphous silica, and 0.3% chlorhexidine; (HBX) decontamination with a sulfonic/sulfuric acid solution in gel; and (HBX + ESC) a combination of HBX and ESC. Microbiological analysis was performed on five implants per treatment group, and the residual viable bacterial load measured in log 10 CFU/mL was counted for each bacterial strain and for the total number of colonies. The remaining three implants per group and three noncontaminated (NC) implants were used to assess surface biocompatibility using a scanning electron microscope and a backscattered electron microscope after seeding with MG-63 cells.Results: A significant decontaminant effect was achieved using HBX or HBX + ESC, while no differences were observed among other groups. The percentage of implant surface covered by adherent MG-63 cells was influenced by the treatment method. Progressive increases in covered surfaces were observed in groups C, AW, ESC, HBX, HBX + ESC, and NC.Conclusions: A combination of mechanical and chemical decontamination may provide more predictable results than mechanical cleaning alone.