Sharif Digital Repository

Content-based image retrieval (CBIR) has turned into an important and active potential research field with the advance of multimedia and imaging technology. It makes use of image features, such as color, texture and shape, to index images with minimal human intervention. A CBIR system can be used to locate medical images in large databases. In this paper we propose a CBIR system which describes the methodology for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the Adaptive neuro-fuzzy inference system (ANFIS) learning to retrieve similar images from database in two categories: normal and tumoral. A fuzzy classifier has been used, because of the... 

Background: Balance training improves postural control in Parkinson's disease (PD). However, a systematic approach for the development of individualized, optimal training programs is still lacking, as the learning dynamics of the postural control in PD, over a training program, are poorly understood. Objectives: We investigated the learning dynamics of the postural control in PD, during a balance-training program, in terms of the clinical, posturographic, and novel model-based measures. Methods: Twenty patients with PD participated in a balance-training program, 3 days a week, for 6 weeks. Clinical tests assessed functional balance and mobility pre-training, mid-training, and post-training.... 

Purpose: Treatment of metastatic breast cancer patients is challenging and remains a major underlying cause of female mortality. Understanding molecular alterations in tumor development is critical to identify novel biomarkers and targets for cancer diagnosis and therapy. One of the aberrant cancer expressions gaining recent research interest is glypican-1. Several studies reported strong glypican-1 expression in various types of human cancers. However, none of these investigated glypican-1 expression in a large cohort of breast cancer histopathological subtypes. Patients and Methods: Immunohistochemistry was used to assess glypican-1 expression in 220 breast cancer patients and its relation... 

Aim of study: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most patients in the first year due to ineffective treatment. Different clinical, biomedical, and image data features are needed to analyze GBM, increasing complexities. Besides, they lead to weak performances for machine learning models due to ignoring physicians' knowledge. Therefore, this paper proposes a hierarchical model based on Fuzzy C-mean (FCM) clustering, Wrapper feature selection, and twelve classifiers to analyze treatment plans. Methodology/Approach: The proposed method finds the effectiveness of previous and current treatment plans, hierarchically determining the best decision for... 

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a... 

Retinoblastoma is the most frequent primary intraocular tumour in childhood. Early detection of retinoblastoma is the key to successful management with a higher chance of survival. This study aims to assess the knowledge of the general population and healthcare providers about retinoblastoma in term of presentation, risk factors, timing for diagnosis, and complications. A cross-sectional study using an online survey was conducted in three Arab countries (Jordan, Saudi Arabia, and Iraq) between 28 August and 16 September 2020. The questionnaire tool was constructed based on an extensive literature review to explore the study's aim and objectives. Logistic regression was used to identify... 

Objective(s): Multiple sclerosis (MS) is considered as a chronic type of an inflammatory disease characterized by loss of myelin of CNS. Recent evidence indicates that Interleukin 17 (IL-17)-producing T helper cells (Th17 cells) population are increased and regulatory T cells (Treg cells) are decreased in MS. Despite extensive research in understanding the mechanism of Th17 and Treg differentiation, the role of microRNAs in MS is not completely understood. Thereby, as a step closer, we analyzed the expression profile of miR-9-5p and miR-106a-5p, and protein level of retinoic acid receptor (RAR)-related orphan receptor C (RORC; Th17 master transcription factor) as direct target of miR-106a-5p... 

Background. Temporary artery clipping facilitates safe cerebral aneurysm management, besides a risk for cerebral ischemia. We developed an artificial neural network (ANN) to predict the safe clipping time of temporary artery occlusion (TAO) during intracranial aneurysm surgery. Method. We devised a three-layer model to predict the safe clipping time for TAO. We considered age, the diameter of the right and left middle cerebral arteries (MCAs), the diameter of the right and left A1 segment of anterior cerebral arteries (ACAs), the diameter of the anterior communicating artery, mean velocity of flow at the right and left MCAs, and the mean velocity of flow at the right and left ACAs, as well... 

Background: One of the most widely used evaluation methods in miRNA experiments is qRT-PCR. However, selecting suitable internal controls (IC) is crucial for qRT-PCR experiments. Currently, there is no consensus on the ICs for miRNA qRT-PCR experiments in breast cancer. To this end, we tried to identify the most stable (the least expression alteration) and promising miRNAs in normal and tumor breast tissues by employing TCGA miRNA-Seq data and then experimentally validated them on fresh clinical samples. Methods: A multi-component scoring system was used which takes into account multiple expression stability criteria as well as correlation with clinical characteristics. Furthermore, we... 

Irregular hemodynamics affects the progression of various vascular diseases, such atherosclerosis or aneurysms. Despite the extensive hemodynamics studies on animal models, the inter-species differences between humans and animals hamper the translation of such findings. Recent advances in vascular tissue engineering and the suitability ofin vitromodels for interim analysis have increased the use ofin vitrohuman vascular tissue models. Although the effect of flow on endothelial cell (EC) pathophysiology and EC-flow interactions have been vastly studied in two-dimensional systems, they cannot be used to understand the effect of other micro- and macro-environmental parameters associated with... 

Background: The development of colon cancer has been described as a multistep process of carcinogenesis. Understanding molecular and cellular changes underlying this process is required to determine potential biomarkers and therapeutic targets in colon cancers. Several molecular entities, including glypicans, are implicated in cancer development. Among these is glypican-6, which is overexpressed in a limited number of cancers. This study aims to characterise the glypican-6 expression in different types of colon cancer. Methods: Immunohistochemistry was used to characterise glypican-6 expression in a panel of archived formalin-fixed, paraffin-embedded colon tissue types. These types included...