Sharif Digital Repository

The present study was designed to search for metabolic biomarkers and their correlation with serum zinc in Crohn's disease patients. Crohn's disease (CD) is a form of inflammatory bowel disease that may affect any part of the gastrointestinal tract and can be difficult to diagnose using the clinical tests. Thus, introduction of a novel diagnostic method would be a major step towards CD treatment.Proton nuclear magnetic resonance spectroscopy ( 1H NMR) was employed for metabolic profiling to find out which metabolites in the serum have meaningful significance in the diagnosis of CD. CD and healthy subjects were correctly classified using random forest methodology. The classification model for... 

Aim: The aim of this study was to search for metabolic biomarkers of Crohn's disease (CD). Background: Crohn's disease (CD) is a type of inflammatory bowel disease that causes a wide variety of symptoms. CD can influence any part of the gastrointestinal tract from mouth to anus. CD is not easily diagnosed because monitoring tools are currently insufficient. Thus, the discovery of proper methods is needed for early diagnosis of CD. Patients and methods: We utilized metabolic profiling using proton nuclear magnetic resonance spectroscopy (1HNMR) to find the metabolites in serum. Classification of CD and healthy subject was done using partial least squares discriminant analysis (PLS-DA).... 

Objective: Epileptic seizure detection is a key step for epilepsy assessment. In this work, using the pentylenetetrazole (PTZ) model, seizures were induced in rats, and ECoG signals in interictal, preictal, ictal, and postictal periods were recorded. The recorded ECoG signals were then analyzed to detect epileptic seizures in the epileptic rats. Methods: Two different approaches were considered in this work: thresholding and classification. In the thresholding approach, a feature is calculated in consecutive windows, and the resulted index is tracked over time and compared with a threshold. The moment the index crosses the threshold is considered as the moment of seizure onset. In the... 

Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12). A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale)... 

The electrooxidation of clozapine (CLZ) was studied on the surface of a glassy carbon electrode (GCE) modified with a thin film of multiwalled carbon nanotubes (MWCNTs)/new coccine (NC) doped polypyrrole (PPY) by using linear sweep voltammetry (LSV). The pH of the supporting electrolyte (D), drop size of the cast MWCNTs suspension (E) and accumulation time of CLZ on the surface of modified electrode (F) was considered as effective experimental factors and the oxidation peak current of CLZ was selected as the response. By using factorial-based response-surface methodology, the optimum values of factors were obtained as 5.44, 10 μL and 300 s for D, E and F respectively. Under the optimized... 

Heart is a complex system and we can find its function in electrocardiogram (ECG) signal. The records show high mortality rate of heart diseases. So it is essential to detect and recognize ECG arrhythmias. The problem with ECG analysis is the vast variations among morphologies of ECG signals. Premature Ventricular Contractions (PVC) is a common type of arrhythmia which may lead to critical situations and contains risk. This study, proposes a novel approach for detecting PVC and visualizing data with respect to ECG morphologies by using manifold learning. To this end, the Laplacian Eigenmaps - One of the reduction method and it is in the nonlinear category - is used to extract important... 

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods... 

Objective: Epileptic seizures are defined as manifest of excessive and hyper-synchronous activity of neurons in the cerebral cortex that cause frequent malfunction of the human central nervous system. Therefore, finding precursors and predictors of epileptic seizure is of utmost clinical relevance to reduce the epileptic seizure induced nervous system malfunction consequences. Researchers for this purpose may even guide us to a deep understanding of the seizure generating mechanisms. The goal of this paper is to predict epileptic seizures in epileptic rats. Methods: Seizures were induced in rats using pentylenetetrazole (PTZ) model. EEG signals in interictal, preictal, ictal and postictal... 

Objective: Crohn's disease (CD) is one the important illnesses can affect any part of the gastrointestinal tract. CD is not easily diagnosed using the clinical tests. Thus, the discovery of proper methods would be a major step towards CD diagnosis. The aim of this study was to seek the metabolic biomarkers causes of CD compare to control group. Materials and Methods: In present study, we employed metabolic profiling using proton nuclear magnetic resonance spectroscopy (1HNMR) to find metabolites in serum which are helpful for the diagnosis of CD. Classification of CD and healthy subject was done using classification and regression trees (CART). The metabolites that caused changes in people... 

Sparse representation is a powerful tool for image processing, including noise removal. It is an effective method for Gaussian noise removal by taking advantage of a fixed and learned dictionary. In this study, the variable distribution of Rician noise is reduced in magnetic resonance (MR) images by sparse representation based on reconstruction error sets. Standard deviation of Gaussian noise is used to find these errors locally. The proposed method represents two formulas for local error calculation using standard deviation of noise. The acquired results from the real and simulated images are comparable, and in some cases, better than the best Rician noise removal method due to the... 

A new unbreakable solid phase microextraction (SPME) fiber coating based on aniline-silica nanocomposite was electrodeposited on a stainless steel wire. The electropolymerization process was carried out at a constant deposition potential, applied to the corresponding aqueous electrolyte containing aniline and silica nanoparticles. The scanning electron microscopy (SEM) images showed the non-smooth and the porous surface structure of the prepared nanocomposite. The applicability of the new fiber coating was examined by headspace-solid phase microextraction (HS-SPME) of some environmentally important polycyclic aromatic hydrocarbons (PAHs), as model compounds, from aqueous samples.... 

A sensitive glutamate biosensor is prepared based on glutamate dehydrogenase/vertically aligned carbon nanotubes (GLDH, VACNTs). Vertically aligned carbon nanotubes were grown on a silicon substrate by direct current plasma enhanced chemical vapor deposition (DC-PECVD) method. The electrochemical behavior of the synthesized VACNTs was investigated by cyclic voltammetry and electrochemical impedance spectroscopic methods. Glutamate dehydrogenase covalently attached on tip of VACNTs. The electrochemical performance of the electrode for detection of glutamate was investigated by cyclic and differential pulse voltammetry. Differential pulse voltammetric determinations of glutamate are performed... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,... 

In this work a novel unbreakable sol-gel-based in-tube device for on-line solid phase microextraction (SPME) was developed. The inner surface of a copper tube, intended to be used as a high performance liquid chromatography (HPLC) loop, was electrodeposited by metallic Cu followed by the self assembled monolayers (SAM) of 3-(mercaptopropyl) trimethoxysilane (3MPTMOS). Then, poly (ethyleneglycol) (PEG) was chemically bonded to the -OH sites of the SAM already covering the inner surface of the copper loop using sol-gel technology. The homogeneity and the porous surface structure of the SAM and sol-gel coatings were examined using the scanning electron microscopy (SEM) and adsorption/desorption... 

Every year many people suffer from knee injuries. Previous studies on patients with knee injuries have shown that about 40% of knee injuries are Ligament injuries, and about 50% of the ligament injuries are the Anterior Cruciate Ligament (ACL) injuries. Along with other methods, knee arthrometers are widely used to diagnose ACL injuries. In the current research, a knee arthrometer was designed and developed to provide a reliable and repeatable measurement of knee laxity under anteriorposterior applied loads. Testretest configurations to examine repeatability of the device resulted in less than 1.5-mm difference for more than 97% of tests under applied loads of up to 90 N. These tests... 

Studies show that High frequency oscillations (HFOs) can be used as a reliable biomarker of epileptogenic zone, thus many algorithms have been proposed to detect HFOs. Among the wide variety of HFOs, fast ripples (FRs) are important transient oscillations occurring in the frequency band ranging from 250 Hz to 600 Hz. The automatic detection of FRs can be degenerated by the presence of some 'pulse-like' events (commonly, the component of interictal epileptic spikes) associated with an increase of the signal energy in the high frequency bands, exactly as in the case of real FRs. The goal of this study is to propose a new method for automatic detection of fast ripples by using Hidden Markov... 

Background: Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.Methods: The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from... 

Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

Background: Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure and can be used to evaluate fiber bundles. However, due to practical constraints, DWI data acquired in clinics are low resolution. New method: This paper proposes a method for interpolation of orientation distribution functions (ODFs). To this end, fuzzy clustering is applied to segment ODFs based on the principal diffusion directions (PDDs). Next, a cluster is modeled by a tensor so that an ODF is represented by a mixture of tensors. For interpolation, each tensor is rotated separately. Results: The method is applied on the synthetic and real DWI data of control and... 

Atherosclerosis is a major cause of coronary artery disease leading to morbidity and mortality worldwide. Currently, coronary angiography is considered to be the most accurate technique to diagnose coronary artery disease (CAD). However, this technique is an invasive and expensive procedure with risks of serious complications. Since the symptoms of CAD are not noticed until advanced stages of the disease, early and effective diagnosis of CAD is considered a pertinent measure. In this paper, a non-invasive optical signal, the finger photoplethysmogram (PPG) obtained before and after reactive hyperemia is investigated to discriminate between subjects with different CAD conditions. To this end,...