Computer‐assisted implant surgery (CAIS), either static or dynamic, is well documented to significantly improve the accuracy of implant placement. Whether the increased accuracy leads to a corresponding improvement in clinical outcomes has not yet been systematically investigated. The aim of this critical review was to investigate whether the use of CAIS can lead to reduction of complications as well as improved clinical and patient‐reported outcomes (PROs) when compared with conventional freehand implant surgery. A comprehensive online search was conducted to identify studies where implants were installed with static computer‐assisted implant surgery (s‐CAIS)or dynamic computer‐assisted implant surgery(d‐CAIS) or combinations of the two, either compared with conventional free‐hand implant placement or not. Seventy‐seven studies were finally included in qualitative analysis, while data from three studies assessing postsurgical pain were suitable for a meta‐analysis. Only a small number of the available studies were comparative. The current evidence does not suggest any difference with regard to intraoperative complications, immediate postsurgical healing, osseointegration success, and survival of implants placed with CAIS or freehand protocols. Intraoperative and early healing events as reported by patients in randomized clinical trials (RCTs) did not differ significantly between CAIS used with flap elevation and conventional implant placement. There is limited evidence that increased accuracy of placement with CAIS is correlated with superior esthetic outcomes. Use of CAIS does not significantly reduce the length of surgeries in cases of single implants and partially edentulous patients, although there appears to be a more favorable impact in fully edentulous patients. Although CAIS alone does not seem to improve healing and the clinical and PRO, to the extent that it can increase the utilization of flapless surgery and predictability of immediacy protocols, its use may indirectly lead to substantial improvements in all of the above parameters.

The presence of inflammatory infiltrates with B cells, specifically plasma cells, is the hallmark of periodontitis lesions. The composition of these infiltrates in various stages of homeostasis and disease development is not well documented. Human tissue biopsies from sites with gingival health (n = 29), gingivitis (n = 8), and periodontitis (n = 21) as well as gingival tissue after treated periodontitis (n = 6) were obtained and analyzed for their composition of B cell subsets. Ag specificity, Ig secretion, and expression of receptor activator of NF-κB ligand and granzyme B were performed. Although most of the B cell subsets in healthy gingiva and gingivitis tissues were CD19⁺CD27⁺CD38⁻ memory B cells, the major B cell component in periodontitis was CD19⁺CD27⁺CD38⁺CD138⁺HLA-DR^low plasma cells, not plasmablasts. Plasma cell aggregates were observed at the base of the periodontal pocket and scattered throughout the gingiva, especially apically toward the advancing front of the lesion. High expression of CXCL12, a proliferation-inducing ligand, B cell–activating factor, IL-10, IL-6, and IL-21 molecules involved in local B cell responses was detected in both gingivitis and periodontitis tissues. Periodontitis tissue plasma cells mainly secreted IgG specific to periodontal pathogens and also expressed receptor activator of NF-κB ligand, a bone resorption cytokine. Memory B cells resided in the connective tissue subjacent to the junctional epithelium in healthy gingiva. This suggested a role of memory B cells in maintaining periodontal homeostasis.

This study evaluated methylation patterns of long interspersed nuclear element-1 (LINE-1) sequences from 17 loci in several cell types, including squamous cell cancer cell lines, normal oral epithelium (NOE), white blood cells and head and neck squamous cell cancers (HNSCC). Although sequences of each LINE-1 are homologous, LINE-1 methylation levels at each locus are different. Moreover, some loci demonstrate the different methylation levels between normal tissue types. Interestingly, in some chromosomal regions, wider ranges of LINE-1 methylation levels were observed. In cancerous cells, the methylation levels of most LINE-1 loci demonstrated a positive correlation with each other and with the genome-wide levels. Therefore, the loss of genome-wide methylation in cancerous cells occurs as a generalized process. However, different LINE-1 loci showed different incidences of HNSCC hypomethylation, which is a lower methylation level than NOE. Additionally, we report a closer direct association between two LINE-1s in different EPHA3 introns. Finally, hypermethylation of some LINE-1s can be found sporadically in cancer. In conclusion, even though the global hypomethylation process that occurs in cancerous cells can generally deplete LINE-1 methylation levels, LINE-1 methylation can be influenced differentially depending on where the particular sequences are located in the genome.