Transected Tendon Treated with a New Fibrin Sealant Alone or Associated with Adipose-Derived Stem Cells.

Tissue engineering and cell-based therapy combine techniques that create biocompatible materials for cell survival, which can improve tendon repair. This study seeks to use a new fibrin sealant (FS) derived from the venom of Crotalus durissus terrificus, a biodegradable three-dimensional scaffolding produced from animal components only, associated with adipose-derived stem cells (ASC) for application in tendons injuries, considered a common and serious orthopedic problem. Lewis rats had tendons distributed in five groups: normal (N), transected (T), transected and FS (FS) or ASC (ASC) or with FS and ASC (FS + ASC). The in vivo imaging showed higher quantification of transplanted PKH26-labeled ASC in tendons of FS + ASC compared to ASC on the 14th day after transection. A small number of Iba1 labeled macrophages carrying PKH26 signal, probably due to phagocytosis of dead ASC, were observed in tendons of transected groups. ASC up-regulated the Tenomodulin gene expression in the transection region when compared to N, T and FS groups and the expression of TIMP-2 and Scleraxis genes in relation to the N group. FS group presented a greater organization of collagen fibers, followed by FS + ASC and ASC in comparison to N. Tendons from ASC group presented higher hydroxyproline concentration in relation to N and the transected tendons of T, FS and FS + ASC had a higher amount of collagen I and tenomodulin in comparison to N group. Although no marked differences were observed in the other biomechanical parameters, T group had higher value of maximum load compared to the groups ASC and FS + ASC. In conclusion, the FS kept constant the number of transplanted ASC in the transected region until the 14th day after injury. Our data suggest this FS to be a good scaffold for treatment during tendon repair because it was the most effective one regarding tendon organization recovering, followed by the FS treatment associated with ASC and finally by the transplanted ASC on the 21st day. Further investigations in long-term time points of the tendon repair are needed to analyze if the higher tissue organization found with the FS scaffold will improve the biomechanics of the tendons.

Meta-analysis of magnetic resonance imaging accuracy for diagnosis of oral cancer.

OBJECTIVE: To establish the diagnostic accuracy of magnetic resonance imaging (MRI) as an auxiliary means for the diagnosis of oral cancer through a systematic review and meta-analysis. METHODS: An exhaustive search of publications from 1986 to 2016 was performed of Medline, Embase and Cochrane (and related databases), including grey literature. Primary diagnostic accuracy studies that assessed oral cancer (target condition) using MRI (index test) were included. Diagnostic threshold, sensitivity and meta-regression analyses were performed. A meta-analysis was performed using Meta-DiSc® v. 1.4 software. RESULTS: A total of 24 primary studies were assessed, comprising 1,403 oral cancer lesions. Nine studies used diffusion-weighted MRI, with a diagnostic odds ratio (DOR) of 30.7 (95% confidence interval [CI]: 12.7-74.3) and area under the curve (AUC) of 0.917 (95% CI: 0.915-0.918); seven studies used dynamic contrast-enhanced MRI, with a DOR of 48.1 (95%CI: 22.4-103.2) and AUC of 0.936 (95% CI: 0.934-0.937); and 13 studies used traditional MRI, with a DOR of 23.9 (95%CI: 13.2-43.3) and AUC of 0.894 (95% CI: 0.894-0.895). Meta-regression analysis indicated that the magnetic field strength may have influenced the heterogeneity of the results obtained (p = 0.0233) using traditional MRI. Sensitivity analysis revealed a discrete reduction of inconsistency in some subgroups. CONCLUSION: The three types of MRI assessed exhibited satisfactory accuracy compared to biopsy. Considering the relevance of early treatment and screening and that better health care results in improved survival rates and quality of life for oral cancer patients, we suggest the use of MRI as a part of the pre-treatment and monitoring protocol at public health services.

A Data Mining Approach to Identify Sexuality Patterns in a Brazilian University Population.

This paper presents the profile and experience of sexuality generated from a data mining classification task. We used a database about sexuality and gender violence performed on a university population in southern Brazil. The data mining task identified two relationships between the variables, which enabled the distinction of subgroups that better detail the profile and experience of sexuality. The identification of the relationships between the variables define behavioral models and factors of risk that will help define the algorithms being implemented in the data mining classification task.

A Comparative Study of Bayes Net, Naive Bayes and Averaged One-Dependence Estimators for Osteoporosis Analysis.

This paper presents an evaluation of the accuracy of the Bayesian classifiers: Bayes Net, Naive Bayes and Averaged One-Dependence Estimator, to support diagnoses of osteopenia and osteoporosis. All classifiers showed good results, thus, given data, it is possible to produce a reasonably accurate estimate of the diagnosis.

Distributed Parallel Computing in Data Analysis of Osteoporosis.

This research aimed to compare the performance of two models of load balancing (Proportional and Autotuned algorithms) of the JPPF platform in the processing of data mining from a database with osteoporosis and osteopenia. When performing the analysis of execution times, it was observed that the Proportional algorithm performed better in all cases.