The oral and gut microbiota: beyond a short communication

Introduction. The current treatment and prevention of oral disorders, dental caries, periodontal and gum diseases, follow a very non-specific control of plaque as the main causative factor. The main therapeutically approach is carried out on the sole perspective to keep the levels of oral bacteria in an acceptable range compatible with one-way vision of oral-mouth health, as something completely separated from a systemic microbial homeostasis (dysbiosis) concomitant present in the gut. A sealed compartmental view which sees separate and incommunicable responses to a specific condition without considering the presence of interacting confounding factors can negatively influence the diagnosis a diseases and of course its progression. A general non-specific antimicrobial with more general antiplaque therapy based mainly on oral care products together with surgery interventions represent at the moment the only mechanical responses in treating oral diseases. Material and method. The present paper is a narrative review concening interractions between oral and gut microbiota, with a focus on the interdisciplinary approach in antimicrobial treatment. Pubmed, Cochrane Library database were used for searching engines. Key words used were as follows: "inflammatory bowel syndrome (IBS)", "ulcerative colitis", "oral dysbiosis", "gut dysbiosis", "probiotics", "periodontitis". Results and discussions. Literature research showed that there are few issues to be discussed the ever increasing resistance to antibiotics, the high consumption of industrial food and sugars and their negatively effect on gut and oral microbiota. There is a need to highlight and develop a novel philosophical approach in the treatments for oral diseases that will necessarily involve non-conventional antimicrobial solutions. Such approaches should preferably reduce the consumption of both intestinal and oral microbiota, that are intimately connected and host approximately well over 1000 different species of bacteria at 108–109 bacteria per mL of mucous and saliva. Preventive approaches based upon the restoration of the microbial ecological balance, rather than elimination of the disease associated species, have been proposed. Conclusions. Having both oral-gut microbiota screened is an essential moment that influence the healthy immune modulatory and regenerative capacity of the body and, the new proposed formula integrates a wider screen on the patients where oral condition is strictly evaluated together with gut screen; therefore any proposed treatment will be inevitably sustained by the use of prebiotics and probiotics to promote health-associated bacterial growth. Keywords: inflammatory bowel syndrome (IBS), ulcerative colitis, oral dysbiosis, gut dysbiosis, probiotics, periodontitis

Essential oils utility implications in symptomatic Burning Mouth Syndrome

Introduction. Burning mouth syndrome (BMS) is a clinical condition characterized by the presence of chronic pain in absence of clinically visible lesions of the oral mucosa. The etiology is uncertain and the therapeutic strategies still controversial. The objective of this prospective study is to analyze the efficacy of essential oils-based mouthwashes in the therapy of BMS. Material and method. This study included 16 patients affected by BMS who were treated with essential oils-based mouthwashes and glucose solution on alternated days for 30 days. Symptomatology was evaluated after 15, 30 and 90 days. Results and discussions. A the end of the treatment, most of the patients (67%) referred an improvement of symptoms up to complete remission in 90 days. Conclusions. Based on this study, essential oils-based mouthwashes could represent a valid aid in the treatment of BMS. Further studies are necessary in order to identify effective and standardized therapeutic protocols. Keywords: Burning Mouth Syndrome; oral rinse; essential oils; therapeutic strategies

Biostimulation with low-level laser therapy and its effects on soft and hard tissue regeneration. Literature review

Objective. Low-Level Laser Therapy encourages the healing process, reduces inflammation and pain. The aim of this study is to identify the impact of Low-Level Laser Therapy on tissue regeneration with special attention to hard tissues and to compare the effect of several wave lengths in the proliferation and differentiation of cells. Methods. The keywords used were “bone regeneration”, “laser therapy”, “photobiomodulation” OR “bio-stimulation”, “Low-Level Laser therapy” OR “LLLT”, “osteoblast proliferation” AND “differentiation”. Results. The bio-stimulation with Low-Level Laser Therapy also seems to interfere with the osseous integration of implants, by increasing its adherence on the bone-implant surfaces. Evidence has shown that Low-Level Laser Therapy influences the cellular proliferation and differentiation. Conclusions. Low-Level Laser Therapy is a promising therapy in the field of regeneration, but further studies are needed in order to define the standard protocol

Corrective Evolution of Adaptable Process Models

Modeling business processes is a complex and time-consuming task, which can be simplified by allowing process instances to be structurally adapted at runtime, based on context (e.g., by adding or deleting activities). The process model then no longer needs to include a handling procedure for every exception that can occur. Instead, it only needs to include the assumptions under which a successful execution is guaranteed. If a design-time assumption is violated, the exception handling procedure matching the context is selected at runtime. However, if runtime structural adaptation is allowed, the process model may later need to be updated based on the logs of adapted process instances. Evolving the process model is necessary if adapting at run-time is too costly, or if certain adaptations fail and should be avoided. An issue that is insufficiently addressed in the previous work on process evolution is how to evolve a process model and also ensure that the evolved process model continues to achieve the goal of the original model. We refer to the problem of evolving a process model based on selected instance adaptations, such that the evolved model satisfies the goal of the original model, as corrective evolution. Automated techniques for solving the corrective evolution problem are necessary for two reasons. First, the more complex a process model is, the more difficult it is to be changed manually. Second, there is a need to verify that the evolved model satisfies the original goal. To develop automated techniques, we first formalize the problem of corrective evolution. Since we use a graph-based representation of processes, a key element in our formal model is the notion of trace. When plugging an instance adaptation at a particular point in the process model, there can be multiple paths in the model for reaching this point. Each of these paths is uniquely identified by a trace, i.e., a recording of the activities executed up to that point. Depending on traces, an instance adaptation can be used to correct the process model in three different ways. A correction is strict if the adaptation should be plugged in on a precise trace, relaxed if on all traces, and relaxed with conditions if on a subset of all traces. The choice is driven by competing concerns: the evolved model should not introduce untested behavior, but it should also remain understandable. Using our formal model, we develop automated techniques for solving the corrective evolution problem in two cases. The first case is also the most restrictive, when all corrections are strict. This case does not require verification, since the process model and adaptations are assumed to satisfy the goal, as long as the adaptations are applied on the corresponding traces. The second case is when corrections are either strict or relaxed. This second case requires verification, and for this reason we develop an automated technique based on planning. We implemented the two automated techniques as tools, which are integrated into a common toolkit. We used this toolkit to evaluate the tradeoffs between applying strict and relaxed corrections on a scenario built on a real event log

Towards Scalable Web Service Composition With Partial Matches

We investigate scalable algorithms for automated composition (WSC) of Semantic Web Services. Our notion of WSC is very general: the composition semantics includes background knowledge and we use the most general notion of matching, partial matches, where several web services can cooperate, each covering only a part of a requirement. Unsurprisingly, automatic composition in this setting is very hard. We identify a special case with simpler semantics, which covers many relevant scenarios. We develop a composition tool for this special case. Our goal is to achieve scalability: we overcome large search spaces by guiding the search using heuristic techniques. The computed solutions are optimal up to a constant factor. We test our approach on a simple, yet powerful real world use-case; the initial results attest the potential of the approach.

Scalable Web Service Composition with Partial Matches

Abstract. We will investigate scalable algorithms for automated Semantic Web Service Composition (WSC). Our notion of WSC is very general: it allows the generation of new constants by web service outputs; the composition semantics includes powerful background ontologies; and we use the most general notion of matching, partial matches, where several services can cooperate each covering only a part of a requirement. Herein, we define a first formalism. We show that automatic composition is very hard: even testing solutions is Π 2 p-complete. We identify a special case that covers many relevant WSC scenarios, and where solution testing is only coNP-complete. While coNP is still hard, in the area of planning under uncertainty, scalable tools have been developed that deal with the same complexity. In our next step, we will adapt the techniques underlying one of these tools to develop a scalable tool for WSC. In the long term, we will investigate richer formalisms, and accordingly adapt our algorithms.

Diagnostic Value of microRNA-375 as Future Biomarker for Prostate Cancer Detection: A Meta-Analysis

Background and Objectives: Responding to the need for additional biomarkers for the diagnosis of prostate cancer (PCa), mounting studies show that microRNAs (miRNAs/miRs) possess great potential as future promising diagnostic tools. However, the usefulness of these miRNAs is still highly debated, as the degree of inconsistency between study designs and results is still elevated. Herein, we present a meta-analysis evaluating the diagnostic value and accuracy of circulating miR-375, as it is one of the most studied types of miRs in PCa. Materials and Methods: The diagnostic accuracy of miR-375 was evaluated using the QUADAS-2 tool, analyzing different statistical parameters. The seven studies (from six articles) that matched our selection included 422 PCa patients and 212 controls (70 healthy volunteers + 142 with benign prostate diseases). Results and Conclusion: We obtained a p-value of 0.76 for sensitivity, 0.83 for specificity, 16 for DOR, 4.6 for LR+, 0.29 for LR−, and 0.87 for AUC (95% CI 0.83–0.89). Our results confirm that miRNA-375 has high diagnostic potential for PCa, suggesting its usefulness as a powerful biomarker. More comprehensive studies are warranted to better assess its true value as a diagnostic biomarker for this urologic disease