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sensitivity-and-specificity
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ZnO nanoparticle/nanorod-based label-free electrochemical immunoassay for rapid detection of MMP-9 biomarker
, Article Biochemical Engineering Journal ; Volume 164 , 2020 ; Abdekhodaie, M. J ; Mousavi, S. A ; Taghipour, F ; Sharif University of Technology
Elsevier B.V
2020
Abstract
A label-free electrochemical biosensor was developed for the rapid detection of the matrix metalloproteinase 9 (MMP-9) biomarker on the basis of antibody immobilizing on the zinc oxide (ZnO) nanoparticle and ZnO nanorod electrodes. The charge transfer resistance (Rct) of the electrodes was used as the indicator for MMP-9 concentration, which was obtained through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The ZnO nanorod-based biosensor exhibited linear behavior in the MMP-9 concentration range of 1–1000 ng/ml, which is a wider range than the available concentration ranges for most of the conventional methods. The biosensor sensitivity was 32.5 μA/(decade × cm2)...
Visual acuity classification using single trial visual evoked potentials
, Article Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 ; 2009 , Pages 982-985 ; 1557170X (ISSN) ; Shamsollahi, M. B ; Abootalebi, V ; Sharif University of Technology
Abstract
Several researches have been done to identify visual system characteristics. Some of them are based on the processing of the brain signal recordings. Visual evoked potentials (VEPs) are electrical signals which are produced in response to the visual stimuli and recorded by means of electrodes placed on the head. These signals are usually characterized by the amplitude and latency of their peaks. Different types of visual stimuli and visual system characteristics can affect the shape and hence the characteristics of VEPs. In this paper, proper visual stimuli were used and VEPs were recorded in order to classify visual acuity. To achieve this goal, visual evoked potentials were recorded and...
Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks
, Article Computational and Mathematical Methods in Medicine ; Volume 2013 , 2013 ; 1748670X (ISSN) ; Roohafza, H ; Sadeghi, M ; Andalib, E ; Shavandi, H ; Sarrafzadegan, N ; Sharif University of Technology
2013
Abstract
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)...
Using distance on the Riemannian manifold to compare representations in brain and in models
, Article NeuroImage ; Volume 239 , 2021 ; 10538119 (ISSN) ; Shirali, A ; Aghajan, H ; Nili, H ; Sharif University of Technology
Academic Press Inc
2021
Abstract
Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner product and correlation matrix. These representational matrices reside on the manifold of positive semidefinite matrices, called the Riemannian manifold. We hypothesize that representational similarities would be more accurately quantified by considering the underlying manifold of the representational matrices. Thus, we introduce the distance on the Riemannian manifold as a metric for comparing representations. Analyzing simulated and real fMRI...
Switching kalman filter based methods for apnea bradycardia detection from ECG signals
, Article Physiological Measurement ; Volume 36, Issue 9 , 2015 , Pages 1763-1783 ; 09673334 (ISSN) ; Shamsollahi, M. B ; Ge, D ; Hernandez, A. I ; Sharif University of Technology
Abstract
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...
Sol-gel-based solid-phase microextraction and gas chromatography-mass spectrometry determination of dextromethorphan and dextrorphan in human plasma
, Article Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences ; Volume 818, Issue 2 , 2005 , Pages 147-157 ; 15700232 (ISSN) ; Eshaghi, A ; Rouini, M. R ; Sharif University of Technology
2005
Abstract
A novel solid-phase microextraction (SPME) method was developed for isolation of dextromethorphan (DM) and its main metabolite dextrorphan (DP) from human plasma followed by GC-MS determination. Three different polymers, poly(dimethylsiloxane) (PDMS), poly(ethylenepropyleneglycol) monobutyl ether (Ucon) and polyethylene glycol (PEG) were synthesized as coated fibers using sol-gel methodologies. DP was converted to its acetyl-derivative prior to extraction and subsequent determination. The porosity of coated fibers was examined by SEM technique. Effects of different parameters such as fiber coating type, extraction mode, agitation method, sample volume, extraction time, and desorption...
Simultaneous determination of epinephrine and acetaminophen concentrations using a novel carbon paste electrode prepared with 2,2′-[1,2 butanediylbis(nitriloethylidyne)]-bis-hydroquinone and TiO2 nanoparticles
, Article Colloids and Surfaces B: Biointerfaces ; Volume 76, Issue 1 , 2010 , Pages 82-87 ; 09277765 (ISSN) ; Beitollahi, H ; Sheikh Mohseni, M. A ; Benvidi, A ; Naeimi, H ; Nejati Barzoki, M ; Taghavinia, N ; Sharif University of Technology
2010
Abstract
A carbon paste electrode (CPE) modified with 2,2′-[1,2 butanediylbis(nitriloethylidyne)]-bis-hydroquinone (BBNBH) and TiO2 nanoparticles was used for the sensitive voltammetric determination of epinephrine (EP). The electrochemical response characteristics of the modified electrode toward EP and acetaminophen (AC) were investigated by cyclic and differential pulse voltammetry (CV and DPV). The results showed an efficient catalytic activity of the electrode for the electrooxidation of EP, which leads to a reduction in its overpotential by more than 270 mV. The effects of pH and potential sweep rate on the mechanism of the electrode process were investigated. The modified electrode exhibits an...
Sensitivity analysis of the OWA operator
, Article IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics ; Volume 38, Issue 2 , 2008 , Pages 547-552 ; 10834419 (ISSN) ; Szidarovszky, F ; Ardakanian, R ; Sharif University of Technology
2008
Abstract
The successful design and application of the ordered weighted averaging (OWA) method as a decision-making tool depend on the efficient computation of its order weights. The most popular methods for determining the order weights are the fuzzy linguistic quantifiers approach and the minimal variability method, which give different behavior patterns for the OWA. These two methods will be first analyzed in detail by using sensitivity analysis on the outputs of the OWA with respect to the optimism degree of the decision maker, and then the two methods will be compared. The fuzzy linguistic quantifiers approach gives more information about the behavior of the OWA outputs in comparison to the...
Quantitative in vivo microsampling for pharmacokinetic studies based on an integrated solid-phase microextraction system
, Article Analytical Chemistry ; Volume 79, Issue 12 , 2007 , Pages 4507-4513 ; 00032700 (ISSN) ; Eshaghi, A ; Musteata, F. M ; Ouyang, G ; Pawliszyn, J ; Sharif University of Technology
2007
Abstract
An integrated microsampling approach based on solid-phase microextraction (SPME) was developed to provide a complete solution to highly efficient and accurate pharmacokinetic studies. The microsampling system included SPME probes that are made of poly(ethylene glycol) (PEG) and C18-bonded silica, a fast and efficient sampling strategy with accurate kinetic calibration, and a high-throughput desorption device based on a modified 96-well plate. The sampling system greatly improved the quantitative capability of SPME in two ways. First, the use of the C18-bonded silica/PEG fibers minimized the competition effect from analogues of the target analytes in a complicated sample matrix such as blood...
QSAR study of heparanase inhibitors activity using artificial neural networks and Levenberg-Marquardt algorithm
, Article European Journal of Medicinal Chemistry ; Volume 43, Issue 3 , 2008 , Pages 548-556 ; 02235234 (ISSN) ; Asadollahi Baboli, M ; Shahbazikhah, P ; Sharif University of Technology
2008
Abstract
A linear and non-linear quantitative structure-activity relationship (QSAR) study is presented for modeling and predicting heparanase inhibitors' activity. A data set that consisted of 92 derivatives of 2,3-dihydro-1,3-dioxo-1H-isoindole-5-carboxylic acid, furanyl-1,3-thiazol-2-yl and benzoxazol-5-yl acetic acids is used in this study. Among a large number of descriptors, four parameters classified as physico-chemical, topological and electronic indices are chosen using stepwise multiple regression technique. The artificial neural networks (ANNs) model shows superiority over the multiple linear regressions (MLR) by accounting 87.9% of the variances of antiviral potency of the heparanase...
Over-Expression of immune-related lncrnas in inflammatory demyelinating polyradiculoneuropathies
, Article Journal of Molecular Neuroscience ; Volume 71, Issue 5 , 2021 , Pages 991-998 ; 08958696 (ISSN) ; Ghafouri-Fard, S ; Mazdeh, M ; Nicknafs, F ; Nazer, N ; Sayad, A ; Taheri, M ; Sharif University of Technology
Humana Press Inc
2021
Abstract
Long non-coding RNAs (lncRNAs) have crucial roles in the pathogenesis of immune-related disorders. However, their role in the pathobiology of inflammatory demyelinating polyradiculoneuropathies remains unclear. In the current study, we measured peripheral expression of four lncRNAs, namely TUG1, FAS-AS1, NEAT1, and GAS5, in patients with acute/chronic inflammatory demyelinating polyradiculoneuropathies (AIDP/CIDP) compared with healthy subjects. Notably, all lncRNAs were over-expressed in patients compared with controls (P < 0.0001 for all lncRNAs). When assessing their expressions in AIDP and CIDP groups separately, TUG1 and NEAT1 were up-regulated in both patient groups compared with...
Optimization of dispersive liquid-liquid microextraction and improvement of detection limit of methyl tert-butyl ether in water with the aid of chemometrics
, Article Journal of Chromatography A ; Volume 1217, Issue 45 , November , 2010 , Pages 7017-7023 ; 00219673 (ISSN) ; Sereshti, H ; Samadi, S ; Parastar, H ; Sharif University of Technology
2010
Abstract
Dispersive liquid-liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry-selective ion monitoring (GC-MS-SIM) was applied to the determination of methyl tert-butyl ether (MTBE) in water samples. The effect of main parameters affecting the extraction efficiency was studied simultaneously. From selected parameters, volume of extraction solvent, volume of dispersive solvent, and salt concentration were optimized by means of experimental design. The statistical parameters of the derived model were R 2=0.9987 and F=17.83. The optimal conditions were 42.0μL for extraction solvent, 0.30mL for disperser solvent and 5% (w/v) for sodium chloride. The calibration linear range...
Optical radiomic signatures derived from optical coherence tomography images improve identification of melanoma
, Article Cancer Research ; Volume 79, Issue 8 , 2019 , Pages 2021-2030 ; 00085472 (ISSN) ; Fatemizadeh, E ; Blumetti, T ; Daveluy, S ; Moraes, A. F ; Chen, W ; Mehregan, D ; Andersen, P. E ; Nasiriavanaki, M ; Sharif University of Technology
American Association for Cancer Research Inc
2019
Abstract
The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15–30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, "optical properties extraction (OPE)," which improves the...
Opposite trends of GAS6 and GAS6-AS expressions in breast cancer tissues
, Article Experimental and Molecular Pathology ; Volume 118 , 2021 ; 00144800 (ISSN) ; Hussen, B. M ; Taheri, F ; Sattari, A ; Yousefi, H ; Omrani, M. D ; Nazer, N ; Ghafouri Fard, S ; Taheri, M ; Sharif University of Technology
Academic Press Inc
2021
Abstract
Growth arrest-specific gene 6 (GAS6) is a growth factor-like cytokine whose function is related with vitamin K. This protein interacts with receptor tyrosine kinase proteins such as Tyro3, Axl, and TAM Receptor family, therefore affecting the tumorigenic processes via different mechanisms. GAS6-antisense 1 (GAS6-AS1) is a long non-coding RNAs (lncRNAs) that is transcribed from a genomic regions nearby GAS6. This lncRNA is also implicated in the pathobiology of cancer. We intended to judge the role of GAS6 and GAS6-AS1 in the pathogenesis of breast cancer through appraisal of their expression levels in breast cancer tissues and their paired neighboring non-cancerous samples. Expression of...
Noninvasive estimation of tissue temperature via high-resolution spectral analysis techniques
, Article IEEE Transactions on Biomedical Engineering ; Volume 52, Issue 2 , 2005 , Pages 221-228 ; 00189294 (ISSN) ; Ebbini, E. S ; Georgiou, T. T ; Sharif University of Technology
2005
Abstract
We address the noninvasive temperature estimation from pulse-echo radio frequency signals from standard diagnostic ultrasound imaging equipment. In particular, we investigate the use of a high-resolution spectral estimation method for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach, employing generalized second-order statistics, is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods Seip and Ebbini (1995). Furthermore, temperature estimates from the new algorithm are compared with results from the more commonly used echo shift method described in Simon...
Noninvasive detection of coronary artery disease by arterio-oscillo-graphy
, Article IEEE Transactions on Biomedical Engineering ; Volume 52, Issue 4 , 2005 , Pages 743-747 ; 00189294 (ISSN) ; Hashemi Golpayegani, M. R ; Abbaspour Tehrani Fard, A ; Bubvay Nejad, M ; Sharif University of Technology
2005
Abstract
Coronary artery disease (CAD) causes oscillations in peripheral arteries. Oscillations of the walls of the brachial arteries of 51 patients were recorded [together with the electrocardiogram (ECG)] by an accelerometer at different cuff pressures. By analyzing the energy of the oscillations in the 30-250 Hz band, 16 of 22 patients with CAD and 26 of 29 non-CAD subjects were classified correctly, independent of the ECG, and with no effect of heart murmurs
Multi-class segmentation of skin lesions via joint dictionary learning
, Article Biomedical Signal Processing and Control ; Volume 68 , 2021 ; 17468094 (ISSN) ; Mahdavi Amiri, N ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
Melanoma is the deadliest type of human skin cancer. However, it is curable if diagnosed in an early stage. Recently, computer aided diagnosis (CAD) systems have drawn much interests. Segmentation is a crucial step of a CAD system. There are different types of skin lesions having high similarities in terms of color, shape, size and appearance. Most available works focus on a binary segmentation. Due to the huge variety of skin lesions and high similarities between different types of lesions, multi-class segmentation is still a challenging task. Here, we propose a method based on joint dictionary learning for multi-class segmentation of dermoscopic images. The key idea is based on combining...
Model-based fiducial points extraction for baseline wandered electrocardiograms
, Article IEEE Transactions on Biomedical Engineering ; Volume 55, Issue 1 , 2008 , Pages 347-351 ; 00189294 (ISSN) ; Shamsollahi, M. B ; Sharif University of Technology
2008
Abstract
A fast algorithm based on the nonlinear dynamical model for the electrocardiogram (ECG) is presented for the precise extraction of the characteristic points of these signals with baseline drift. Using the adaptive bionic wavelet transform, the baseline wander is removed efficiently. In fact by the means of the bionic wavelet transform, the resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential, which results in a better baseline wander cancellation. At the next step the parameters of the model are chosen to have the least square error with the original ECG. Determining...
Model-based Bayesian filtering of cardiac contaminants from biomedical recordings
, Article Physiological Measurement ; Volume 29, Issue 5 , 2008 , Pages 595-613 ; 09673334 (ISSN) ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
2008
Abstract
Electrocardiogram (ECG) and magnetocardiogram (MCG) signals are among the most considerable sources of noise for other biomedical signals. In some recent works, a Bayesian filtering framework has been proposed for denoising the ECG signals. In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG and ballistocardiographic artifacts from different biomedical recordings such as the electroencephalogram, electromyogram and also for canceling maternal cardiac signals from fetal ECG/MCG. The proposed method is evaluated on simulated and real signals. © 2008 Institute of Physics and Engineering in Medicine
Metabonomics based NMR in Crohn's disease applying PLS-DA
, Article Gastroenterology and Hepatology from Bed to Bench ; Volume 6, Issue SUPPL , 2013 , Pages S82-S86 ; 20082258 (ISSN) ; Oskouie, A. A ; Tafazzoli, M ; Naderi, N ; Sohrabzedeh, K ; Fathi, S ; Norouzinia, M ; Nejad, M. R ; Sharif University of Technology
2013
Abstract
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)....