Brain activity changes following neuroproprioceptive "facilitation, inhibition" physiotherapy in multiple sclerosis: a parallel group randomized comparison of two approaches.

BACKGROUND: Imaging methods bring new possibilities for describing the brain plasticity processes that underly the improvement of clinical function after physiotherapy in people with multiple sclerosis (pwMS). Although these processes have been described mainly in connection with task-oriented physiotherapy and aerobic training, they have not been properly verified in neuroproprioceptive "facilitation, inhibition" (facilitation) approaches. AIM: The study determined whether facilitation physiotherapy could enhance brain plasticity, compared two facilitation methods and looked for any relation to clinical improvement in pwMS. DESIGN: The study was designed as parallel group randomized comparison of two kinds of physiotherapeutic interventions referred to healthy controls. SETTING: Thirty-eight outpatients were involved in the study. POPULATION: The study had 80 participants (38 pwMS and 42 healthy controls). METHODS: PwMS were divided into two groups and underwent a two-month physiotherapy program: Vojta reflex locomotion (VRL) or Motor program activating therapy (MPAT), (1 hour, twice a week). Functional magnetic resonance imaging (fMRI) and clinical examination was performed before and after therapy. Healthy controls underwent one fMRI examination. RESULTS: Physiotherapy in pwMS leads to extension of brain activity in specific brain areas (cerebellum, supplementary motor areas and premotor areas) in connection with the improvement of the clinical status of individual patients after therapy (P=0.05). Greater changes (P=0.001) were registered after MPAT than after VRL. The extension of activation was a shift to the examined activation of healthy controls, whose activation was higher in the cerebellum and secondary visual area (P=0.01). CONCLUSIONS: Neuroproprioceptive "facilitation, inhibition" physiotherapy may enhance brain activity and could involve processes connected with the processing of motion activation. CLINICAL REHABILITATION IMPACT: The study showed that facilitation approach can modulate brain activity. This could be useful for developing of effective physiotherapeutic treatment in MS.

Classification of Thyroid Nodules in Ultrasound Images Using Direction-Independent Features Extracted by Two-Threshold Binary Decomposition.

In recent years, several computer-aided diagnosis systems emerged for the diagnosis of thyroid gland disorders using ultrasound imaging. These systems based on machine learning algorithms may offer a second opinion to radiologists by evaluating a malignancy risk of thyroid tissue, thus increasing the overall diagnostic accuracy of ultrasound imaging. Although current computer-aided diagnosis systems exhibit promising results, their use in clinical practice is limited. One of the main limitations is that the majority of them use direction-dependent features. Our intention has been to design a computer-aided diagnosis system, which will use only direction-independent features, that is, it will not be dependent on the orientation and the inclination angle of the ultrasound probe when acquiring the image. We have, therefore, applied histogram analysis and segmentation-based fractal texture analysis algorithm, which calculates direction-independent features only. In our study, 40 thyroid nodules (20 malignant and 20 benign) were used to extract several features, such as histogram parameters, fractal dimension, and mean brightness value in different grayscale bands (obtained by 2-threshold binary decomposition). The features were then used in support vector machine and random forests classifiers to differentiate nodules into malignant and benign classes. Using leave-one-out cross-validation method, the overall accuracy was 92.42% for random forests and 94.64% for support vector machine. Results show that both methods are useful in practice; however, support vector machine provides better results for this application. Proposed computer-aided diagnosis system can provide support to radiologists in their current diagnosis of thyroid nodules, whereby it can optimize the overall accuracy of ultrasound imaging.

Patch-based classification of thyroid nodules in ultrasound images using direction independent features extracted by two-threshold binary decomposition.

Ultrasound imaging of the thyroid gland is considered to be the best diagnostic choice for evaluating thyroid nodules in early stages, since it has been marked as cost-effective, non-invasive and risk-free. Computer aided diagnosis (CAD) systems can offer a second opinion to radiologists, thereby increasing the overall diagnostic accuracy of ultrasound imaging. Although current CAD systems exhibit promising results, their use in clinical practice is limited. Some of the main limitations are that the majority use direction dependent features so, they are only compatible with static images in just one plane (axial or longitudinal), requiring precise segmentation of a nodule. Our intention has been to design a CAD system which will use only direction independent features i.e., not dependent upon the orientation or inclination angle of the ultrasound probe when acquiring the image. In this study, 60 thyroid nodules (20 malignant, 40 benign) were divided into small patches of 17 × 17 pixels, which were then used to extract several direction independent features by employing Two-Threshold Binary Decomposition, a method that decomposes an image into the set of binary images. The features were then used in Random Forests (RF) and Support Vector Machine (SVM) classifiers to categorize nodules into malignant and benign classes. Classification was evaluated using group 10-fold cross-validation method. Performance on individual patches was then averaged to classify whole nodules with the following results: overall accuracy, sensitivity, specificity and area under receiver operating characteristics (ROC) curve: 95%, 95%, 95%, 0.971 for RF and; 91.6%, 95%, 90%, 0.965 for SVM respectively. The patch-based CAD system we present can provide support to radiologists in their current diagnosis of thyroid nodules, whereby it can increase the overall accuracy of ultrasound imaging.

Adipogenesis, lipogenesis and lipolysis is stimulated by mild but not severe hypoxia in 3T3-L1 cells.

In-vitro investigation of the effects of hypoxia is limited by physical laws of gas diffusion and cellular O2 consumption, making prolonged exposures to stable O2 concentrations impossible. Using a gas-permeable cultureware, chronic effects of mild and severe hypoxia on triglyceride accumulation, lipid droplet size distribution, spontaneous lipolysis and gene expression of adipocyte-specific markers were assessed. 3T3-L1 cells were differentiated under 20%, 4% or 1% O2 using a gas-permeable cultureware. Triglyceride accumulation, expression of genes characteristic for advanced adipocyte differentiation and involvement of key lipogenesis enzymes were assessed after exposures. Lipogenesis increased by 375% under mild hypoxia, but dropped by 43% in severe hypoxia. Mild, but not severe, hypoxia increased formation of large lipid droplets 6.4 fold and strongly induced gene expression of adipocyte-specific markers. Spontaneous lipolysis increased by 488% in mild, but only by 135% in severe hypoxia. Inhibition of ATP-dependent citrate lyase suppressed hypoxia-induced lipogenesis by 81% and 85%. Activation of HIF inhibited lipogenesis by 59%. Mild, but not severe, hypoxia stimulates lipolysis and promotes adipocyte differentiation, probably through excess of acetyl-CoA originating from tricarboxylic acid cycle independently of HIF activation.

Monitoring biventricular pacing parameters depending on the left ventricle lead configuration.

OBJECTIVES: To evaluate whether pacing or sensing configuration has an effect on pacing parameters or their time progression. Three left ventricular (LV) pacing parameters were monitored - the LV pacing threshold, pacing impedance and intrinsic R-wave amplitude. METHODS: DATA WERE COLLECTED AT THREE INTERVALS: during implantation; between the second and fifth month after implantation (first follow-up); and between the eighth and 15th month after implantation (second follow-up). Repeated-measures ANOVA was used for the statistical analysis. RESULTS: The impedance, but not its time progression, was significantly higher for the LV tip to LV ring configuration than for other configurations. R-wave amplitude and impedance increased significantly (without dependance on configurations) between implantation and first follow-up, as expected. The time progression of any parameter was not dependent on configuration of the LV lead. CONCLUSIONS: LV tip to LV ring is the best configuration for maintaining a high impedance level. It is better to maintain an individual approach for pacing threshold and R-wave amplitude, and their settings.