Retendo (mucopolygen complex) effects on achille tendon healing.

INTRODUCTION: The injuries of achilles tendon which is among the most important tendons in the body include many problems. Limited tendon recovery is provided through the surgical procedures available. Re-rupture occurs during and after recovery and the long time it takes to return to work, impossibility of early movement of the affected ankle and not being able to provide a physiological recovery in tendon constitute a problem. Thus, our objective in this study was to demonstrate the recovery effects of Retendon (mucopolygen complex) on achilles tendon. MATERIAL-METHOD: After taking the consent of the ethics board we applied for animal experiments, the experiment animals in our study were separated into two groups as those which were given Retendo® (Mucopolygen Complex - Mucopolysaccharides, Hydrolyzed Collagen Type I, Vitamin C) and the control group. These two groups were separated into four groups. In a total of eight groups, 40 female Wistar-Albino rats with an average weight of 200-350 gr. were included in the study. RESULTS: The study had biomechanical and histological results. While there was no significant difference in vascularization, inflamation and fibroblastic level among the groups in histological terms, collagen formation was detected to be more regular in the experiment group than the control group. A significant efficiency couldn't be acquired in biomechanical terms. DISCUSSION: Although Retendo® (mucopolygen complex) is commonly used in muscle and tendon diseases, its effect mechanism is not definitely known. But in the light of the findings we acquired in our study, we detected that Retendo® (mucopolygen complex) applied after achilles tendon ruptures positively effected collagen sequencing during recovery in histological terms but didn't have a significant effect on the mean load achilles tendon can tolerate before rupturing.

Advanced computing solutions for analysis of laryngeal disorders.

Clinical diagnosis of voice pathologies is performed by analyzing audio, color, shape, and vibration patterns of the laryngeal recordings which are taken with medical imaging devices such as video-laryngostroboscope, direct laryngoscopy, and high-speed videoendoscopes. This paper examines state-of-the-art methods and reveals open issues and problems of computing solutions for analysis and identification of laryngeal disorders. We propose a categorical representation of the most significant applications published so far in terms of their scopes, used methodologies, and achieved results. Laryngeal image/video analysis is discussed in four main categories: segmentation of vocal folds, classification of vocal fold disorders, vocal fold vibration analysis, and vocal fold image stitching. By this study, we reveal new opportunities and potentials of vision-based computerized solutions for evaluation, early diagnosis, and prevention of laryngeal disorders. Graphical abstract.

An Energy-Efficient Multi-Tier Architecture for Fall Detection Using Smartphones.

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions.

A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection.

Transportation planning and solutions have an enormous impact on city life. To minimize the transport duration, urban planners should understand and elaborate the mobility of a city. Thus, researchers look toward monitoring people's daily activities including transportation types and duration by taking advantage of individual's smartphones. This paper introduces a novel segment-based transport mode detection architecture in order to improve the results of traditional classification algorithms in the literature. The proposed post-processing algorithm, namely the Healing algorithm, aims to correct the misclassification results of machine learning-based solutions. Our real-life test results show that the Healing algorithm could achieve up to 40% improvement of the classification results. As a result, the implemented mobile application could predict eight classes including stationary, walking, car, bus, tram, train, metro and ferry with a success rate of 95% thanks to the proposed multi-tier architecture and Healing algorithm.

Classification of laryngeal disorders based on shape and vascular defects of vocal folds.

Vocal fold disorders such as laryngitis, vocal nodules, and vocal polyps may cause hoarseness, breathing and swallowing difficulties due to vocal fold malfunction. Despite the fact that state of the art medical imaging techniques help physicians to obtain more detailed information, difficulty in differentiating minor anomalies of vocal folds encourages physicians to research new strategies and technologies to aid the diagnostic process. Recent studies on vocal fold disorders note the potential role of the vascular structure of vocal folds in differential diagnosis of anomalies. However, standards of clinical usage of the blood vessels have not been well established yet due to the lack of objective and comprehensive evaluation of the vascular structure. In this paper, we present a novel approach that categorizes vocal folds into healthy, nodule, polyp, sulcus vocalis, and laryngitis classes exploiting visible blood vessels on the superior surface of vocal folds and shapes of vocal fold edges by using image processing techniques and machine learning methods. We first detected the vocal folds on videolaryngostroboscopy images by using Histogram of Oriented Gradients (HOG) descriptors. Then we examined the shape of vocal fold edges in order to provide features such as size and splay portion of mass lesions. We developed a new vessel centerline extraction procedure that is specialized to the vascular structure of vocal folds. Extracted vessel centerlines were evaluated in order to get vascular features of vocal folds, such as the amount of vessels in the longitudinal and transverse form. During the last step, categorization of vocal folds was performed by a novel binary decision tree architecture, which evaluates features of the vocal fold edge shape and vascular structure. The performance of the proposed system was evaluated by using laryngeal images of 70 patients. Sensitivity of 86%, 94%, 80%, 73%, and 76% were obtained for healthy, polyp, nodule, laryngitis, and sulcus vocalis classes, respectively. These results indicate that visible vessels of vocal folds can act as a prognostic marker for vocal fold pathologies, as well as the vocal fold shape features, and may play a critical role in more effective diagnosis.

Assessment of videolaryngostroboscopy images based on visible vessels of vocal folds.

Extraction of vessel structures and the vessel features automatically forms an essential step for computer-aided diagnosis. Visible vessels of vocal folds become a diagnostic aid for vocal fold pathologies by publication of limited number of researches which analyze the effects of vocal fold pathologies on visual characteristics of blood vessels. In this paper we present a novel system that extracts blood vessels centerlines on vocal folds images and detects pathologically altered vocal folds exploiting visual characteristics of vessels.

Dysphonic speech reconstruction: construction of a novel system for effective and efficient communication.

In this article, a MELP-based real-time system that produces synthetic speech for patients with chronic dysphonia while preserving their continual structure of speech, was presented. Dysphonic patients, even though strained, could express themselves within face-to-face communications. However, when speaking in a group or using communication devices such as mobile phones, they face serious difficulties in vocal communication since it becomes harder to understand their speech. This system will make the speech of such a patient much more understandable by reconstructing the patients' dysphonic speech in real time. This system can easily be fitting into an embedded system of the size and shape of a mobile phone, so that it could be carried all the time by the patients.

Ethical and legal aspects of stem cell practices in Turkey: where are we?

Advances in medical technology and information have facilitated clinical practices that favourably affect the success rates of treatment for diseases. Regenerative medicine has been the focus of the recent medical agenda, to the extent of fundamentally changing treatment paradigms. Stem cell practices, their efficacy, and associated ethical concerns have been debated intensively in many countries. Stem cell research is carried out along with the treatment of patients. Thus, various groups affected by the practices inevitably participate in the discussions. In addition to discussions based on avoiding any harm, providing benefits and respecting personal autonomy and justice, problems arise owing to the lack of legal regulations for stem cell research and practice. The dimensions of the problems vary in the developing countries, with widespread use of advanced medical technology but with lack of sources allocated for healthcare, dominance of paternalistic physician-patient relationships and failure to achieve a sufficient level of awareness of patients' rights. This article discusses the current situation of stem cell practices within the context of regenerative medicine in Turkey and ethical concerns about some of the legal regulations, such as the Regulation for Umblical Cord Blood Banking and Guidelines for Non-embryonic Stem Cell Study for Non-clinical Purposes directing the research on this issue.