Sharif Digital Repository

LncRNAs are involved in the modulation of several signaling pathways which have a crucial effect in the differentiation of periodontal ligament cells and the induction of cementum regeneration. Autophagy and Wnt signaling are two important pathways with a wide range of interrelationships associated with periodontitis. We chose four lncRNAs based on their potential interaction with these two pathways. We examined the expression of FOXD2-AS1, NNT-AS1, GAS8-AS1, and CCAT1 lncRNAs in tissues and blood specimens of patients with periodontitis and unaffected controls using qRT-PCR. Expression amounts of FOXD2-AS1 were lower in blood of cases compared with controls (relative expression (RE) = 0.08,... 

In the present contribution, visible-near infrared hyperspectral imaging (Vis-NIR-HSI) combined with a novel chemometric approach based on mean-filed independent component analysis (MF-ICA) followed by multivariate classification techniques is proposed for saffron authentication and adulteration detection. First, MF-ICA was used to exploit pure spatial and spectral profiles of the components. Then, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to find patterns of authentic samples based on their distribution maps. Then, detection of five common plant-derived adulterants of saffron including safflower, saffron style, calendula, rubia and turmeric were... 

Objectives: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection. Data: We selected diagnostic accuracy studies that used deep learning models on dental imagery (including radiographs, photographs, optical coherence tomography images, near-infrared light transillumination images). The latest version of the quality assessment tool for diagnostic accuracy studies (QUADAS-2) tool was used for risk of bias assessment. Meta-analysis was not performed due to heterogeneity in the studies methods and their performance measurements.... 

Periodontitis is a common oral disorder leading to tooth loss in both developed and developing regions of the world. This multifactorial condition is related to the abnormal activity of several molecular pathways, among them are oxytocin-related pathways. In this study, we enrolled 26 patients and 28 controls and assessed the expression of four oxytocin-related genes, namely, FOS, ITPR, RCAN1, and RGS2, in circulation and affected tissues of enrolled individuals using real-time PCR. Expression of FOS was downregulated in total periodontitis tissues compared with total control tissues [ratio of mean expression (RME) = 0.23, P-value = 0.03]. Expression of FOS was also lower in total blood... 

Prostate cancer (PCa), the second most malignant neoplasm in men, is also the fifth leading cause of cancer-related deaths in men globally. Unfortunately, this malignancy remains largely asymptomatic until late-stage emergence when treatment is limited due to the lack of effective metastatic PCa therapeutics. Due to these limitations, early PCa detection through prostate-specific antigen (PSA) screening has become increasingly important, resulting in a more than 50% decrease in mortality. Conventional assays for PSA detection, such as enzyme-linked immunosorbent assay (ELISA), are labor intensive, relatively expensive, operator-dependent and do not provide adequate sensitivity.... 

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C-ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are... 

Protein inhibitors of activated STAT (PIAS) are involved in the regulation of the JAK/STAT signaling pathway and have interactions with NF-κB, p73 and p53. These proteins regulate immune responses; therefore dysregulation in their expression leads to several immune-mediated disorders. In the present study, we examined expression of PIAS1-4 in peripheral blood of patients with acute/chronic inflammatory demyelinating polyradiculoneuropathy (AIDP/CIDP) compared with healthy subjects. We demonstrated down-regulation of all PIAS genes in both AIDP and CIDP cases compared with controls. Similarly, comparisons in gender-based groups revealed down-regulation of these gene0s in patients of each... 

Signal Transducer and Activator of Transcription (STAT) pathway is functionally located downstream of Janus kinases proteins and can integrate signals from diverse pathways, thus regulating several aspects of immune responses. Although contribution of STAT proteins in the pathogenesis of several inflammatory conditions has been confirmed, their role in the development of periodontitis has been less appraised. Thus, we assessed levels of STAT transcripts in the periodontal tissues and circulation of affected individuals compared with the corresponding controls. Expression of STAT1 was remarkably lower in tissues samples of patients compared with control tissues (Ratio of mean expression (RME)... 

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... 

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... 

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... 

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... 

The novel coronavirus pandemic has rapidly spread around the world since December 2019. Various techniques have been applied in identification of SARS-CoV-2 or COVID-19 infection including computed tomography imaging, whole genome sequencing, and molecular methods such as reverse transcription polymerase chain reaction (RT-PCR). This review article discusses the diagnostic methods currently being deployed for the SARS-CoV-2 identification including optical biosensors and point-of-care diagnostics that are on the horizon. These innovative technologies may provide a more accurate, sensitive and rapid diagnosis of SARS-CoV-2 to manage the present novel coronavirus outbreak, and could be... 

The novel coronavirus pandemic has rapidly spread around the world since December 2019. Various techniques have been applied in identification of SARS-CoV-2 or COVID-19 infection including computed tomography imaging, whole genome sequencing, and molecular methods such as reverse transcription polymerase chain reaction (RT-PCR). This review article discusses the diagnostic methods currently being deployed for the SARS-CoV-2 identification including optical biosensors and point-of-care diagnostics that are on the horizon. These innovative technologies may provide a more accurate, sensitive and rapid diagnosis of SARS-CoV-2 to manage the present novel coronavirus outbreak, and could be... 

In this work, the potential of near-infrared (NIR) and mid-infrared (MIR) spectroscopy along with chemometrics was investigated for authentication and adulteration detection of Iranian saffron samples. First, authentication of one-hundred saffron samples was examined by principal component analysis (PCA). The results showed the NIR spectroscopy can better predict the origin of samples than the MIR. Next, partial least squares-discriminant analysis (PLS-DA) was developed to detect four common plant-derived adulterants (i.e., saffron style, calendula, safflower, and rubia). In all cases, PLS-DA classification figures of merit in terms of sensitivity, specificity, error rate and accuracy were... 

In the present work, a new approach based on external parameter orthogonalization combined with support vector machine (EPO-SVM) is proposed for processing of attenuated total reflectance-Fourier transform mid-infrared (ATR-FT-MIR) spectra with the goal of solving authentication problem in saffron, the most expensive spice in the world. First, one-hundred authentic saffron samples are clustered by principal component analysis (PCA) with EPO as the best preprocessing strategy. Then, EPO-SVM is used for the detection of four commonly used plant-derived adulterants (i.e. safflower, calendula, rubia, and style) in binary mixtures (saffron and each of plant adulterants) and its performance is... 

The NF-κB family includes some transcription factors which have important functions in the regulation of immune responses, therefore participating in the pathophysiology of inflammatory conditions such as peripheral neuropathies. We have quantified expression of a number of NF-κB-related transcripts in patients with Guillain-Barré syndrome (GBS) or chronic inflammatory demyelinating polyneuropathy (CIDP) versus healthy subjects. These transcripts have been previously shown to be functionally related with this family of transcription factors. Expressions of ATG5, DICER-AS1, PACER, DILC, NKILA and ADINR have been increased in both CIDP and GBS patients compared with controls. However,... 

In this work, high-performance thin-layer chromatography (HPTLC) coupled with multivariate image analysis (MIA) is proposed as a fast and reliable tool for authentication and adulteration detection of Iranian saffron samples based on their HPTLC fingerprints. At first, the secondary metabolites of saffron were extracted using ultrasonic-assisted solvent extraction (UASE) which was optimized using central composite design (CCD). Next, the RGB coordinates of HPTLC images were used for estimation of saffron origin based on principal component analysis (PCA). The PCA scores plot showed that saffron samples were clustered into two clear-cut groups which was 92% matched with the geographical... 

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)... 

Background: Convolutional neural networks (CNN) have enabled significant progress in speech recognition, image classification, automotive software engineering, and neuroscience. This impressive progress is largely due to a combination of algorithmic breakthroughs, computation resource improvements, and access to a large amount of data. Method: In this paper, we focus on the automated detection of autism spectrum disorder (ASD) using CNN with a brain imaging dataset. We detected ASD patients using most common resting-state functional magnetic resonance imaging (fMRI) data from a multi-site dataset named the Autism Brain Imaging Exchange (ABIDE). The proposed approach was able to classify ASD...