No abstract

A novel, direct and independent association between sleep duration and the prevalence of periodontitis was found. However, it needs to be investigated how the factors influencing the sleep duration affect this association.

The human body is naturally colonized by a huge number of different commensal microbial species, in a relatively stable equilibrium. When this microbial community undergoes dysbiosis at any part of the body, it interacts with the innate immune system and results in a poor health status, locally or systemically. Research studies show that bacteria are capable of significantly influencing specific cells of the immune system, resulting in many diseases, including a neoplastic response. Amongst the multiple different types of diseases, pancreatic cancer and liver cirrhosis were significantly considered in this paper, as they are major fatal diseases. Recently, these two diseases were shown to be associated with increased or decreased numbers of certain oral bacterial species. These findings open the way for a broader perception and more specific investigative studies, to better understand the possible future treatment and prevention. This review aims to describe the correlation between oral dysbiosis and both pancreatic cancer and liver cirrhotic diseases, as well as demonstrating the possible diagnostic and treatment modalities, relying on the oral microbiota, itself, as prospective, simple, applicable non-invasive approaches to patients, by focusing on the state of the art. PubMed was electronically searched, using the following key words: “oral microbiota” and “pancreatic cancer” (PC), “liver cirrhosis”, “systemic involvement”, and “inflammatory mediators”. Oral dysbiosis is a common problem related to poor oral or systemic health conditions. Oral pathogens can disseminate to distant body organs via the local, oral blood circulation, or pass through the gastrointestinal tract and enter into the systemic circulation. Once oral pathogens reach an organ, they modify the immune response and stimulate the release of the inflammatory mediators, this results in a disease. Recent studies have reported a correlation between oral dysbiosis and the increased risk of pancreatic and liver diseases and provided evidence of the presence of oral pathogens in diseased organs. The profound impact that microbial communities have on human health, provides a wide domain towards precisely investigating and clearly understanding the mechanism of many diseases, including cancer. Oral microbiota is an essential contributor to health status and imbalance in this community was correlated to oral and systemic diseases. The presence of elevated numbers of certain oral bacteria, particularly P. gingivalis, as well as elevated levels of blood serum antibodies, against this bacterial species, was associated with a higher risk of pancreatic cancer and liver cirrhosis incidence. Attempts are increasingly directed towards investigating the composition of oral microbiome as a simple diagnostic approach in multiple diseases, including pancreatic and liver pathosis. Moreover, treatment efforts are concerned in the recruitment of microbiota, for remedial purposes of the aforementioned and other different diseases. Further investigation is required to confirm and clarify the role of oral microbiota in enhancing pancreatic and liver diseases. Improving the treatment modalities requires an exertion of more effort, especially, concerning the microbiome engineering and oral microbiota transplantation.

Structured Abstract Objectives To introduce a new, fast, reliable, and free from software‐related bias method to predict three‐dimensionally the root position and angulation during and after orthodontic treatment. The final goal is to keep to a minimum the use of ionizing radiation by eliminating the necessity of multiple radiation exposure for checking root alignment. Setting and Sample Population Pre‐ and post‐treatment digital models and cone‐beam computed tomographic (CBCT) scans from a patient were retrieved. Material and Methods The post‐treatment digital model (post‐model) was set as the reference; pre‐ and post‐treatment CBCT scans were pre‐aligned to the post‐model with a point set registration; iterative closest point algorithm was then employed for final adjustments. The accuracy of the proposed method was assessed by comparing the average distance between the expected root position setup with the true position of the roots, as from the post‐treatment CBCT. Results After crown superimposition, 3D colour maps showed that the accuracy of the root prediction was below 0.1 mm. Conclusion The proposed digital workflow allows to predict in an accurate and truly three‐dimensional way the final position of roots, when an initial CBCT is available, without the need of an extra X‐ray examination for the patient at the end of treatment. The limitation of the exposure to mid‐ and post‐treatment X‐rays is in accordance with the ALARA (As Low As Reasonably Achievable) principle and it is even more relevant in growing patients.