Ultraviolet (UV) photofunctionalization has been suggested as an effective method to enhance the osseointegration of titanium surface. In this study, machined surface treated with UV light (M + UV) was compared to sandblasted, large-grit, acid-etched (SLA) surface through in vitro and in vivo studies. Groups of titanium specimens were defined as machined (M), SLA, and M + UV for the disc type, and M + UV and SLA for the implant. The discs and implants were assessed using scanning electron microscopy, confocal laser scanning microscopy, electron spectroscopy for chemical analysis, and the contact angle. Additionally, we evaluated the cell attachment, proliferation assay, and real-time polymerase chain reaction for the MC3T3-E1 cells. In a rabbit tibia model, the implants were examined to evaluate the bone-to-implant contact ratio and the bone area. In the M + UV group, we observed the lower amount of carbon, a 0°-degree contact angle, and enhanced osteogenic cell activities (p < 0.05). The histomorphometric analysis showed that a higher bone-to-implant contact ratio was found in the M + UV implant at 10 days (p < 0.05). In conclusion, the UV photofunctionalization of a Ti dental implant with M surface attained earlier osseointegration than SLA.

This study aims to investigate and assess salivary biomarkers and microbial profiles as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with Stage I periodontitis, 24 with Stage II, 23 with Stage III, and 22 with Stage IV. Salivary proteins (including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A) and planktonic bacteria (including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus) were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROCs) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models that achieved better diagnostic powers, with an AUC value > 0.750 for the diagnosis of Stages II, III, and IV periodontitis (Model PA-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of Stages III and IV periodontitis (Model PA-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers.

This study aimed to compare bone healing and implant stability for three types of dental implants: a threaded implant, a three-dimensional (3D)-printed implant without spikes, and a 3D-printed implant with spikes. In four beagle dogs, left and right mandibular premolars (2nd, 3rd, and 4th) and 1st molars were removed. Twelve weeks later, three types of titanium implants (threaded implant, 3D-printed implant without spikes, and 3D-printed implant with spikes) were randomly inserted into the edentulous ridges of each dog. Implant stability measurements and radiographic recordings were taken every two weeks following implant placement. Twelve weeks after implant surgery, the dogs were sacrificed and bone-to-implant contact (BIC) and bone area fraction occupied (BAFO) were compared between groups. At implant surgery, the primary stability was lower for the 3D-printed implant with spikes (74.05 ± 5.61) than for the threaded implant (83.71 ± 2.90) (p = 0.005). Afterwards, no significant difference in implants’ stability was observed between groups up to post-surgery week 12. Histomorphometrical analysis did not reveal a significant difference between the three implants for BIC (p = 0.101) or BAFO (p = 0.288). Within the limits of this study, 3D-printed implants without spikes and threaded implants showed comparable implant stability measurements, BIC, and BAFO.

Periodontopathic bacteria are known to have a pivotal role in the pathogenesis of periodontitis. The aim of the study was to quantitatively compare bacterial profile of patients with different severity of periodontal disease using samples from mouthwash and the subgingival area. Further analysis was performed to evaluate the correlation between mouthwash and two subgingival sampling methods: paperpoint and gingival retraction cord; 114 subjects enrolled in the study, and were divided equally into three groups according to disease severity. Mouthwash and subgingival sampling were conducted, and the samples were quantitatively analyzed for 11 target periodontopathic bacteria using multiplex real-time PCR. There were statistically significant differences in bacterial counts and prevalence of several species between the study groups. Mouthwash sampling showed significant correlations with two different subgingival sampling methods in regard to the detection of several bacteria (e.g., ρ = 0.793 for Porphyromonas gingivalis in severe periodontitis), implying that mouthwash sampling can reflect subgingival microbiota. However, the correlation was more prominent as disease severity increased. Although bacteria in mouthwash have potential to become a biomarker, it may be more suitable for the diagnosis of severe periodontitis, rather than early diagnosis. Further research is required for the discovery of biomarkers for early diagnosis of periodontitis.

This study was to investigate and assess salivary biomarkers as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with stage I, 24 with stage II, 23 with stage III, and 22 with stage IV periodontitis. Salivary proteins including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A and planktonic bacteria including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mitis, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROC) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models, which achieved better diagnostic powers with an AUC value > 0.750 for the diagnosis of stage II, III, and IV periodontitis (Model PC-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of stage III and IV periodontitis (Model PC-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers.