Morphological changes of Bunni (Barbus sharpeyi) larvae in laboratory conditions

In this study, the early development of Bunni (Barbus sharpeyi) larvae was surveyed through morphological changes and measuring total length, standard length, head length, thickness of larvae, eye diameter and snout length. The initial period of the larval life can be divided into 2 phases: endogenous and exogenous food sources. During the first three days of the larvae development, there was a gradual yolk sac reduction until its complete absorption at the end of third day, indicating the necessity of exogenous feeding. From the fourth to eleventh day, the final development of the heart, gill, air bladder, fins and intestine were observed. Total length of newly hatched larvae was 6.26mm and total length of fifteen days larvae was 8.35mm. The larval development of Barbus sharpeyi was similar to other Barbus species

A Generalized Neural Network Approach to Mobile Robot Navigation and Obstacle Avoidance

In this thesis, we tackle the problem of extending neural network navigation algorithms for various types of mobile robots and 2-dimensional range sensors. We propose a general method to interpret the data from various types of 2-dimensional range sensors and a neural network algorithm to perform the navigation task. Our approach can yield a global navigation algorithm which can be applied to various types of range sensors and mobile robot platforms. Moreover, this method allows the neural networks to be trained using only one type of 2-dimensional range sensor, which contributes positively to reducing the time required for training the networks. Experimental results carried out in simulation environments demonstrate the effectiveness of our approach in mobile robot navigation for different kinds of robots and sensors. Therefore, the successful implementation of our method provides a solution to apply mobile robot navigation algorithms to various robot platforms

The effects of a strengthening exercise program with EMG biofeedback to correct patellar alignment and reduce knee pain in women with patellofemoral pain syndrome

Background and aims: EMG biofeedback as a relatively new tool in helping to relieve muscle dysfunction has been proposed. The aim of this study was to investigate the effects of a strengthening exercise program with electromyographical biofeedback on the alignment corrections of the patella and the knee pain in patients with patella-femoral pain syndrome. Methods: This research was a clinical trials study. 22 participants with patella-femoral pain syndrome were randomly divided into two equal groups (n=11). The first group underwent a strengthening exercise program with biofeedback electromyography. The second group also recieved a strengthening exercise program without biofeedback electromyography. Using VAS questionnaire, the knee pain was assessed. Radiography technique was also applied to evaluate the knee alignments including Sulcus, congruence and tilt angles and Q angle assessed by clinical tests. Pair t-test and Independent t-test with SPSS were used for statistical analysis. Results: The results showed that the knee pain, congruence and Q angle had significant decrease after the therapy in both groups (P<0.05). However, the patellar tilt displayed a significant decrease only in the strengthening exercise program in the biofeedback electromyography group (P<0.05). In between group comparisons, pain and Q angle reduction after strengthening exercise program with biofeedback electromyography group was significantly more than strengthening exercise program without biofeedback electromyography group (P<0.05). Conclusion: Muscular strengthening exercise with electromyographical biofeedback displayed a better treatment outcome for pain reduction and correction of knee alignment. It seems that the provision of electromyographic biofeedback be preferred in comparison with the muscular strength training method without electromyographic biofeedback by creating more motivation for performing the exercises precisely and it can be used as a supportive tool in rehabilitation

Izražajnost kalretinina kao biomarkera rizika za metastatski karcinom mliječne žlijezde u pasa

Malignant breast tumors are the most common tumors in humans and are associated with a poor prognosis. An accurate animal model of human mammary gland tumorigenesis is needed to test novel diagnosis and treatment strategies. Dogs represent a promising model since they develop such tumors spontaneously. In the present study, three immunomarkers, including calretinin, c-Kit (CD117) and placental alkaline phosphatase (Plap), were used and compared with each other, in relation to estrogen and progesterone receptors and HER2 (triple markers), with the intention of malignancy grading. Enhanced expression of calretinin and placental alkaline phosphatase, without immunoreaction to c-Kit in neoplastic cells, is related to high-grade malignancy. Out of 50 tumors, 31 were metastasized, 29 of which (93.5%) were moderately to strongly calretinin positive (P<0.05). However, the results for c-Kit - and Plap+ in metastatic tumors were not reproducible. It may be concluded that calretinin could be introduced as a determinant biomarker in the diagnosis of breast cancer metastasis.Maligni tumori dojke najčešći su tumori u ljudi i povezani su s lošom prognozom. Da bi se testirali novi dijagnostički postupci i terapijske procedure u ljudi, potreban je prikladan životinjski model tumorogeneze mliječne žlijezde. Psi su potencijalno dobar model zbog spontanog razvoja ovakvih tumora. U ovom su istraživanju, s ciljem stupnjevanja malignosti, međusobno uspoređena tri imunomarkera, kalretinin, c-Kit (CD117) i placentalna alkalna fosfataza (Plap), a zatim su isti uspoređeni i s estrogenskim, progesteronskim te HER2 (trostrukim) markerima. Povećanje izražajnosti kalretinina i placentalne alkalne fosfataze, bez imunoreakcije na c-Kit u neoplastičnim stanicama povezano je s visokim stupnjem malignosti. Od 50 tumora, 31 je metastazirao, od kojih je 29 (93,5 %) bilo umjereno do izrazito pozitivno na kalretinin (P < 0,05). Doduše, rezultati za c-Ki ti Plap+ nisu bili ponovljivi. Zaključujemo da bi kalretinin mogao poslužiti kao biomarker u dijagnostici metatstatskog raka dojke

Density-Based Histogram Partitioning and Local Equalization for Contrast Enhancement of Images

Histogram Equalization technique is one of the basic methods in image contrast enhancement. Using this method, in the case of images with uniform gray levels (with narrow histogram), causes loss of image detail and the natural look of the image. To overcome this problem and to have a better image contrast enhancement, a new two-step method was proposed. In the first step, the image histogram is partitioned into some sub-histograms according to mean value and standard deviation, which will be controlled with PSNR measure. In the second step, each sub-histogram will be improved separately and locally with traditional histogram equalization. Finally, all sub-histograms will be combined to obtain the enhanced image. Experimental results shows that this method would not only keep the visual details of the histogram, but also enhance image contrast

The relationship between the number of extrema of compound sinusoidal signals and its high-frequency component

As the main findings of our research work, we present a novel theorem on the relationship between the number of extrema of compound sinusoidal signals and its high-frequency component. In the case of signals consisting of the sum of two sine signals, if the high-frequency component has a higher product of the frequency and the amplitude, then we prove that the frequency of the high-frequency component is proportional to the number of extrema in a time interval. This theorem justifies some of the experimental results of other researchers on the relevance of extrema to frequency and amplitude. To confirm the theorem, extrema counting was performed on speech signals and compared with Fourier transform. The experimental results show that the average number of extrema of the compound sinusoidal signal or its derivatives over a time interval can be used to estimate the frequency at its highest frequency band. An important application of this research work is the fast calculation of high frequencies of a signal. This theorem also shows that the number of extrema points can be used as a new effective feature for signal processing, especially speech signals

T cell lymphoma in the atrium of a young bull

In this report, T-cell lymphoma in the atrium of a 1.5-year-old Holstein bull is described. Macro-scopically, a large white to a yellow tumour mass with a size of 4.5×3.5×2 cm was observed in the left atrium. Histopathological examination revealed extensive infiltration of medium- to large-sized lymphocytic cells with round to oval nuclei and stippled chromatin, surrounded by a narrow rim of pale eosinophilic cytoplasm. Immunohistochemically, the tumour cells indicated positivity with CD3 and Ki-67, but negativity with CD79α, CD20 and S100. On the basis of the histologic and immuno-histochemical findings, this tumour was diagnosed as a T-cell lymphoma

Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.Comment: The Lancet Digital Health, 202