Efficacy of Erb-Laser on Inferior Turbinate Hypertrophy: A Retrospective and Cohort Study.

Objectives: Nasal obstruction (NO) is a very common complaint in the practice of otolaryngology. The cause of NO can be due to inferior turbinate hypertrophy (ITH), which may be a result of allergic rhinitis, hyperreactivity, hormonal causes, rhinitis medicamentosa or idiopathic. The most commonly used treatments today include local nasal or systemic corticosteroids, cauterization or microdebrider, or thermal ablation with radiofrequency, coblation or ablative laser (mainly carbon dioxide or diode lasers), and submucosal reduction. Erbium YAG laser in non-ablative and SMOOTH thermal mode is considered as a non-invasive treatment and could be a novel and safe alternative.The aim of this study was to evaluate the safety and performance of a new Erb-laser treatment protocol on bilateral ITH, during and after 3 sessions of treatment throughout 6 months. Methods: This retrospective study was carried out over 30 patients with complaints of NO, sneezing, itching, discharge, and nasal congestion refractory to medical management from July 2019 to December 2020 in the Department of Otorhinolaryngology of a private hospital in Famagusta, North Cyprus. Symptoms were evaluated subjectively by using NO Score and Visual Analog Scale (VAS). Patients were evaluated at the post-procedural 1st-week, and 1st-, 3rd-, and 6th-month postoperatively. During each follow-up visit, symptoms were reassessed by VAS and NO Score. Results: Differences between pre-operative and post-operative VAS and NO Scores were statistically significant. All patients had significant symptomatic improvements, which started from the post-operative 1stweek and persisted throughout the follow-up period. The active laser treatment showed high improvement during and after the procedure, regarding NO, and decreased the nasal burden on quality of life. Conclusion: Erbium YAG laser treatment is a simple, safe, effective, and non-invasive method effective on ITH, with minimal damage on the nasal mucosa. It can be done as an office procedure, with minimal complications. This method will provide a great advantage in the future treatment of NO.

Comparison of modelling approaches demonstrated for p16-mediated signalling pathway in higher eukaryotes.

Quantitative modelling of biological systems using Petri net technologies has experienced renaissance in the past couple of decades. The overwhelming majority of these models is deterministic though underlying biological systems are usually at the mesoscopic level and small, rather than large, and employ sparse molecular structure. Sparse biological systems are accompanied by randomness due to low molecular density, intrinsic random nature of phenomena and noise in an experiment. On the other hand, biochemical reactions are inherently uncertain due to imprecision and vagueness of kinetic parameters. Stochastic methods are used to cope with randomness while fuzzy methods are developed to deal with uncertainty of biological systems, but there is lack of common voice among researchers regarding the best choice of modelling approach for a particular biological system. The main issues addressed in this paper are the choice between deterministic, stochastic and fuzzy parameters and aspects; that is, which modelling approach to follow to reach the realistic approximation of an underlying biological system, and how to measure parallels and discrepancies between different quantitative paradigms. To this end, we use Petri nets with hybrid, stochastic and fuzzy parameters to create quantitative model of p16-mediated signalling pathway in higher eukaryotes, perform deterministic, pure stochastic and fuzzy stochastic simulations to predict the behaviour of major molecular regulators of p16-mediated pathway. In the meanwhile, we show how uncertain kinetic parameters can be precisely approximated in terms of α cuts. Then we perform statistical analysis of simulation results to measure similarity between the three modelling approaches. The statistical analysis reveals significant deviations between deterministic, pure stochastic and fuzzy stochastic approaches for most of the biological components. Due to rather small size of underlying biological system, it turns out that fuzzy stochastic approach is the most appropriate for modelling of p16-mediated signalling pathway because it successfully deals with both randomness and uncertainty and produces quantitative results with biological relevance.

Validation of signalling pathways: Case study of the p16-mediated pathway.

p16 is recognized as a tumor suppressor gene due to the prevalence of its genetic inactivation in all types of human cancers. Additionally, p16 gene plays a critical role in controlling aging, regulating cellular senescence, detection and maintenance of DNA damage. The molecular mechanism behind these events involves p16-mediated signaling pathway (or p16- Rb pathway), the focus of our study. Understanding functional dependence between dynamic behavior of biological components involved in the p16-mediated pathway and aforesaid molecular-level events might suggest possible implications in the diagnosis, prognosis and treatment of human cancer. In the present work, we employ reverse-engineering approach to construct the most detailed computational model of p16-mediated pathway in higher eukaryotes. We implement experimental data from the literature to validate the model, and under various assumptions predict the dynamic behavior of p16 and other biological components by interpreting the simulation results. The quantitative model of p16-mediated pathway is created in a systematic manner in terms of Petri net technologies.