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Accurate diagnosis of Parkinson's Disease (PD) at its early stages remains a challenge for modern clinicians. In this study, we utilize a convolutional neural network (CNN) approach to address this problem. In particular, we develop a CNN-based network model highly capable of discriminating PD patients based on Single Photon Emission Computed Tomography (SPECT) images from healthy controls. A total of 2723 SPECT images are analyzed in this study, of which 1364 images from the healthy control group, and the other 1359 images are in the PD group. Image normalization process is carried out to enhance the regions of interests (ROIs) necessary for our network to learn distinguishing features from them. A 10-fold cross-validation is implemented to evaluate the performance of the network model. Our approach demonstrates outstanding performance with an accuracy of 99.34 %, sensitivity of 99.04 % and specificity of 99.63 %, outperforming all previously published results. Given the high performance and easy-to-use features of our network, it can be deduced that our approach has the potential to revolutionize the diagnosis of PD and its management.

Background: Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long- term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Type 2 diabetes (T2D) is characterized by a condition of systemic low-grade inflammation. IL-8 is an important member of the chemokine family of proinflammatory chemotactic cytokines. IL-8 was initially characterized as a potent chemoattractant of neutrophils and was later shown to also activate neutrophils. IL-8 is also known to be a potent promoter of angiogenesis. Objective: It was the Assessment of Interleukin (8) in Type 2 Diabetes Mellitus. Patients and Methods: Serum IL 8 level in Type 2 Diabetes Mellitus. 30 patients compared to 30 normal individuals were included in this study. Results: There was a highly statistical significant difference between all patients and control groups as regard serum IL 8 level (mean of serum IL 8 in patients and control groups were 69.9 ± 20.5 and 5.4 ± 3.3 respectively, p= < 0.001). Conclusion: Type 2 diabetes mellitus patients showed marked elevation of circulating IL-8 levels which identify subjects with worse inflammatory state and metabolic control and therefore it may be used as a marker for the rate of development of diabeteic complications.

Services of Family planning have an essential role for improving the quality of family's lives and also their economic welfare. Family planning methods may lead to menstrual changes such as menorrhagia, oligomenorrhea or inter-menstrual spotting. Aim of the study: to assess the effect of contraceptive use on menstrual cycle patterns among clients attending family planning clinics in Assiut City and to assess the effect of menstrual cycle side effects on contraceptive discontinuation among these clients. Subject and Methods: This prospective study was conducted on1570 clients in F.P. clinics serve the west sector of Assiut city by using a structured interviewing and follow up questionnaires. Results: There are statistical significant differences between case &control group as regards Monthly Injectable, the combined pills and Progestin-Only Injectable used and menstrual disorders respectively. There is statistical significant difference between different method of family planning methods and discontinuation rate (P.V=0.008) and between contraceptive methods and its side effects at the first and second follow up (P.V=

Parkinson’s disease (PD) is a neurodegenerative disorder and a global health problem that has no curative therapies. Surgery is a well-established therapy for controlling symptoms of advanced PD patients. This paper proposes a streamlined model to classify PD and to identify appropriate patients for surgical therapy. The data was gathered from the Parkinson’s Progressive Markers Initiative consisting of 1080 subjects. Multilayer Perceptron (MLP), Decision trees, Support Vector Machine and Na¨ıve Bayes are used as classifiers. MLP achieves the highest accuracy as compared to other three classifiers. The dataset used in our experiments is from the Parkinson Progressive Markers Initiative. With feature selection, it is observed that the same classification accuracy is achieved with 60% of the attributes as that using all attributes. It is demonstrated that our classification model for PD patients produces the most accurate results and achieves the highest accuracy of 98.13%

Low serum albumin was found as a predictor of long-term mortality in colorectal cancer (CRC) patients. Our aim was to evaluate the value of the pretreatment albumin/globulin ratio (AGR) to predict the long-term mortality in CRC patients.Patients were included if they had comprehensive metabolic panel (CMP) before treatment (surgery or chemotherapy). The albumin/globulin ratio, routinely reported in CMP, is calculated [AGR = Albumin/(Total protein - Albumin)]. Patients were divided into three equal tertiles according to their pretreatment AGR. The primary outcome was cancer-related mortality, which was obtained from our cancer registry database.A total of 534 consecutive CRC patients had pretreatment CMP. The 1st AGR tertile had a significant higher 4-year mortality compared to the second and third AGR tertiles (42 vs. 19 and 7 %, p 0.0001 according to Fisher's exact two-tailed test). In the multivariate model, AGR remained an independent predictor of survival with 75 % decrease in mortality among the highest AGR tertile in comparison to the lowest AGR tertile, p 0.0001. In the subset of 234 patients with normal serum albumin (albumin of3.5 g/dl), serum AGR continues to be an independent predictor of cancer-related mortality with an adjusted hazard ratio of the third tertile compared to the first tertile equal to 0.05 (95 % confidence interval 0.01-0.33, p = 0.002).Low AGR was a strong independent predictor of long-term cancer-specific survival among colorectal cancer patients. Additionally, among the patients with normal albumin (3.5 g/dl), patients with lower globulins but higher albumin and AGR levels had better survival.