Effect of Implant Surface Roughness and Macro- and Micro-Structural Composition on Wear and Metal Particles Released

Background: Considerations about implant surface wear and metal particles released during implant placement have been reported. However, little is known about implant surface macro- and microstructural components, which can influence these events. The aim of this research was to investigate accurately the surface morphology and chemical composition of commercially available dental implants, by means of multivariate and multidimensional statistical analysis, in order to predict their effect on wear onset and particle release during implant placement. Methods: The implant surface characterization (roughness, texture) was carried out through Confocal Microscopy and SEM-EDS analysis; the quantitative surface quality variables (amplitude and hybrid roughness parameters) were statistically analyzed through post hoc Bonferroni's test for pair comparisons. Results: The parameters used by discriminant analysis evidenced several differences in terms of implant surface roughness between the examined fixtures. In relation to the observed surface quality, some of the investigated implants showed the presence of residuals due to the industrial surface treatments. Conclusions: Many structural components of the dental implant surface can influence the wear onset and particles released during the implant placement

Otolarylogical features in a cohort of patients affected with 22q11.2 deletion syndrome: a monocentric survey

Otorhinolaryngologic manifestations are common in 22q11.2 deletion syndrome (22q11.2DS), but poorly described. This study aimed to better define the ear-nose-throat (ENT) phenotype of 22q11.2DS patients, in the attempt to best detect subjects requiring subspecialist intervention. We enrolled 25 patients affected with 22q11.2DS. Anatomic and functional ENT findings were investigated using clinical, laboratory and instrumental data. Immunophenotype and frequency of infections were evaluated. Univariate and multivariate analyses were performed. ENT anomalies were found in 88% of patients, and in 20% congenital palate defects required surgery. Adenoids hypertrophy or palatine tonsils hypertrophy were noted in 80 and 48%. Fourty-eight percent of subjects had rhinolalia/phonia, severe in half of these. We also found nasal regurgitation or laryngeal penetration/aspiration in 20 and 16%, respectively. Instrumental exams revealed a mild conductive hypoacusia in 32% (bilateral in most cases), tympanometric anomalies in 28%, and swallowing abnormalities in 16%. Statistical univariate analysis showed a direct association between rhinolalia/phonia and episodes of laryngeal aspiration (P=0.016) and between tympanometric anomalies and increased adenoid volume (P=0.044). No association between episodes of food aspiration and palatal anomalies was found. Moreover, no statistically significant association was observed between the number of airway infections and the ENT findings. This study contributes to better define the ENT phenotype in patients with 22q11.2DS, helpful to prevent potential complications. Furthermore, the identification of a subcategory of patients may allow the early adoption of specific speech therapy programs to improve the clinical outcome of 22q11.2DS patients

Prognostic value of p27(Kip1 )expression in Basaloid Squamous Cell Carcinoma of the larynx

BACKGROUND: Very few reports have investigated the role of cell cycle regulators as biomarkers in Basaloid Squamous Cell Carcinoma (BSCC) of the larynx, a definite morphologic, uncommon, very aggressive variant of squamous cell carcinoma. Lower expression of Ki67/Mib-1, a proliferation marker highly expressed in the majority of tumours, and p53, a tumour suppressor protein that can induce an arrest of the G1-S transition, was related to a better prognosis in laryngeal BSCC. In the head and neck, p27(kip1), a member of the Cip1/Kip1 family of cyclin-dependent kinase inhibitors, has emerged as an independent prognostic factor, able to identify low-expressing tumours with unfavourable course. Up to date the role of this protein was never studied in BSCC. Aim of our study was to investigate the potential prognostic value of p27(kip1 )levels and their correlation with Ki67/Mib-1 and p53 expression in BSCC of the larynx. METHODS: The retrospective study group consisted of 15 male and 1 female patients, affected by laryngeal BSCC, ranging in age from 44 to 69 years (mean 58). The tumour originated from the supraglottis in thirtheen cases and from the glottis in the remaining three. Ten patients had metastatic cervical lymph nodes at presentation and were classified as N+. Post surgical stage was IV in four patients, III in nine, II in two cases and I in the remaining one. Follow-up ranged from a minimum of 5 months up to 9 years. Paraffin-embedded tissue sections of each laryngeal tumour were analyzed for p27(kip), Ki67/Mib-1 and p53 expression by immunohistochemistry. RESULTS: The immunohistochemical study showed p27(kip1 )expression in 40% of the patients with no evidence of disease (NED) and in none (0%) of the patients dead of disease (DOD), whilst p53 was expressed in 60% of patients in NED status and in 90% of patients in DOD status. Ki67/Mib-1 was positive in 80% of NED patients and in 100% of DOD patients. At multivariate analysis, performed by means of Discriminant analysis, low levels of p27(kip1 )expression significantly correlated with poor prognosis (P < 0.05). CONCLUSION: p27(kip1 )protein has been shown to be a significant independent prognostic factor in laryngeal SCC. In our series of laryngeal BSCC the resulting data seem to confirm the clinical prognostic relevance of p27(kip1 )low expression, which directly correlated with biological aggressiveness and consequent shortened survival

Diagnostica avanzata in sistemi meccanici complessi

L’analisi vibrazionale di fenomeni transienti a durata molto breve viene oggi effettuata attraverso tecniche classiche basate sullo studio degli spettri e più in generale a mezzo varianti della Fast Fourier Transform (FFT). Il limite di queste tecniche è che sono applicabili a fenomeni vibrazionali periodici. La maggior parte dei fenomeni vibrazionali di origine meccanica oggetto della presente ricerca, che interessa vari campi, non sono periodici. Per poter analizzare tali tipologie vibrazionali si ricorre, quindi, ad un artificio numerico che presuppone che tali fenomeni siano lentamente variabili nel tempo oppure quasi-stazionari. Per fenomeni, però, di durata molto brevi, non è possibile applicare questa ipotesi di lavoro. L’obiettivo di questa ricerca è, quindi, lo studio, la messa a punto e la verifica di metodi e tecniche alternative di analisi che possano essere adoperate nelle condizioni appena descritte

A New Approach of Detecting Chaos in Deterministic Dynamical System

In this study we focus on a new approach to determine whether a deterministic dynamic system is chaotic or periodic. To validate the reliability and sensitivity of the method, it is applied to a C30 Capstone turbine by setting several rotational speeds of the turbine and using mixed fuels

Evaluation of image denoising using fuzziness measures

Concept of fuzzy sets has been incorporated at various stages (e.g., input, output, learning and neuronal level) of network and multi-layered perceptron to handle imprecise, incomplete input data and intractable pattern classes for recognition. Its extension to expert system for rule generation and inferencing has been made along with applications to real life data. This shows how pattern description in terms of properties and membership values can be processed by a neural net for fuzzy and crisp classification. A generalized framework for integration of multilayer perceptron and fuzziness measures has been developed to design an unsupervised system for image denoising. Implementation of fuzzy set theoretic operators using neural networks and the utility of these networks in pattern classification and rule generation have been demonstrated. Various ways of integrating fuzzy set theory and connectionist systems for feature evaluation under both supervised and unsupervised modes have been formulated together with the theoretical analysis

Applications of advanced signal processing analysis

Nowadays, in the industrial field, the predictive maintenance is an important methodology employed for reducing risks of machine stops. Machines are continuously monitored in order to maximize the performance, both in terms of quality and productivity. In this paper it is pointed out an advanced methodology of signal processing which allows to evaluate in advance which kind of fault can happen on a machinery. Several applications are presented in order to show the main features of the method

An introduction to the determination of the level of audibility performed with DWT

Normally, the level of audibility is investigated by means of the Evoked Potentials. In this work we illustrate the use of the Discrete Wavelet Transform for the exploration of observed signals. The results point to validate the decomposition of Evoked Potentials by wavelet analysis in order to allow to us a good identification of the level in auditory sensitivity of chinchillas. The aim of the work is to objective the determination of threshold of audibility of auditory Evoked Potentials response and their classification in terms of reliability based on the multiresolution analysis performed by wavelets. Usually, the Evoked Potentials are examined by two independent observers in order to define their features. In particular, the threshold value is obtained by calculating, for each ear, the average of the lowest intensity at which the response was revealed and the highest intensity at which the response disappeared. The use of wavelets for statistical purposes is still in its infancy, and it will be some years before their genuine practical advantages and disadvantages are understood properly. In particular the statistical ideas presented in this paper are clearly in need of further development but the results so far are extremely promising