Sharif Digital Repository

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... 

Purpose Whole genome sequencing of SARS-CoV2 is important to find useful information about the viral lineages, variants of interests and variants of concern. As there are not enough data about the circulating SARS-CoV2 variants in Iran, we sequenced 54 SARS-CoV2 genomes during the 5 waves of pandemic in Iran. Methods After viral RNA extraction from clinical samples collected during the COVID-19 pandemic, next generation sequencing was performed using the Nextseq platform. The sequencing data were analyzed and compared with reference sequences. Results During the 1st wave, V and L clades were detected. The second wave was recognized by G, GH and GR clades. Circulating clades during the 3rd... 

Background: Colorectal cancer (CRC) is one of the most common malignancies in the world and has a high mortality rate. It is believed that dysfunction in the expression of mucins and aberrant expression of some lncRNAs are associated with the occurrence and development of CRC. Therefore, the aim of the present study was to investigate the expression of MUC15, MUC16, MUC20, PCAT1, CCAT1 and HOTAIR genes in colorectal cancer and its relationship with clinicopathological variables. Materials and methods: This research was prospective case-control study. Tumors from CRC patients were collected from the Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. RNA... 

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly... 

According to the WHO, two individuals die every hour from skin cancer and about 9500 people get skin cancer every day just in the United States. Various computer vision algorithms have been introduced for skin lesion detection, classification, and segmentation. This paper proposes a new segmentation-based algorithm in order to select target components using the persistence diagram of the input images. The results, in comparison with the existing seven different both clustering-and histogram-based segmentation methods using three metrics, show improved performance. Medical image segmentation is an essential task in computer-aided diagnosis. The main improvement of our method is to detect one... 

In recent years, extensive research in the field of Deep Learning (DL) has led to the development of a wide array of machine learning algorithms dedicated to solving complex tasks such as image classification or speech recognition. Due to their unprecedented ability to explore large volumes of data and extract meaningful hidden structures, DL models have naturally drawn attention from various fields in science. Analytical chemistry, in particular, has successfully benefited from the application of DL tools for extracting qualitative and quantitative information from high-dimensional and complex chemical measurements. This report provides introductory reading for understanding DL machinery... 

Mechanical ventilation (MV) can result in long-term brain impairments that are resistant to treatment. The mechanisms underlying MV-induced brain function impairment remain unclear. Since nasal airflow modulates brain activity, here we evaluated whether reinstating airflow during MV could influence the memory performance of rats after recovery. Rats were allocated into two study groups: one group received rhythmic air-puff into the nasal cavity during MV and a control group that underwent ventilation without air-puff. During MV, air-puffs induced time-locked event potentials in OB, mPFC and vHPC and significantly increased the oscillatory activity at the air-puff frequency. Furthermore, in... 

Biomass, originates from plant- or animal-based materials with a huge potential to be reused. Here we report a simple, rapid and inexpensive method for preparation of modified biochars derived from the banana peel followed by their applications in pipette-tip micro solid-phase extraction (PT-µSPE). Due to the contribution of various effective parameters on modification of banana peel biochars (BPBs), Taguchi design was used to optimize activation temperature, activation repetition, treatment material and impregnation ratio. Efficiency of the prepared BPBs were studied by extraction of twelve various pesticides, as model analytes with an extended range of log P values (1.4–5.7), followed by... 

Purpose: This study aimed to investigate the biomechanical impact of laminectomy on cervical intersegmental motion and load sharing using a parametric patient-specific finite element (FE) model towards providing clinicians with a viable quantitative tool for informed decision-making and improved surgical planning. Methods: Ten subject-specific nonlinear osteo-ligamentous cervical spine (C3–C7) FE models were developed using X-ray image-based algorithms. The models were used to evaluate the effect of laminectomy on lower cervical spine biomechanics for two-level (C3–C4) and three-level (C3–C5) laminectomy procedures. Results: The average cervical spine ranges of motion (ROM) for the pre-op... 

Investigating human brain activity during expressing emotional states provides deep insight into complex cognitive functions and neurological correlations inside the brain. To be able to resemble the brain function in the best manner, a complex and natural stimulus should be applied as well, the method used for data analysis should have fewer assumptions, simplifications, and parameter adjustment. In this study, we examined a functional magnetic resonance imaging dataset obtained during an emotional audio-movie stimulus associated with human life. We used Jackknife Correlation (JC) method to derive a representation of time-varying functional connectivity. We applied different binary measures... 

Objective(s): Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Materials and Methods: Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Results: Obtained results showed that changes in LFP power... 

Single-cell resolution technologies warrant computational methods that capture cell heterogeneity while allowing efficient comparisons of populations. Here, we summarize cell populations by adding features’ dispersion and covariances to population averages, in the context of image-based profiling. We find that data fusion is critical for these metrics to improve results over the prior alternatives, providing at least ~20% better performance in predicting a compound’s mechanism of action (MoA) and a gene’s pathway. © 2019, The Author(s)  

Gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) are powerful techniques for measurement of all metabolites in complex metabolic samples. However, analyzing GC-MS and especially GC×GC-MS metabolomic data is a major challenge to the researchers in the field of metabolomics mainly due to the complexity and large data size. In this regard, an automated R based software entitled RMet has been developed to overcome the challenges in the metabolomic analysis workflow of GC-MS and GC×GC-MS data sets. Additionally, it is able to facilitate the complex process of extracting reliable and useful biological information from... 

S. lanata has been traditionally used as a medicinal plant due to its various biological activities such as antioxidant activity. Therefore, identification and quality control studies of this plant are of great importance. To this end, gas chromatography (GC) combined with chemometrics was proposed for fingerprint analysis of S. lanata samples. This study sought to classify GC fingerprints of twenty-eight S. lanata samples from eight different regions of Iran and more importantly, to correlate fingerprints to the antioxidant activity to select S. lanata volatile antioxidant markers. S. lanata samples were classified into five and three classes using partial least squares-discriminant... 

Discussing the particularly long gravitational microlensing event OGLE-2014-BLG-1186 with a time-scale tE ∼ 300 d, we present a methodology for identifying the nature of localised deviations from single-lens point-source light curves, which ensures that (1) the claimed signal is substantially above the noise floor, (2) the inferred properties are robustly determined and their estimation is not subject to confusion with systematic noise in the photometry, (3) alternative viable solutions within the model framework are not missed. Annual parallax and binarity could be separated and robustly measured from the wing and the peak data, respectively. We find matching model light curves that involve... 

The joint analysis of multiple data sets to extract their interdependency information has wide applications in biomedical and health informatics. In this paper, we propose an algorithm to extract joint and individual sources of multisubject data sets by using a deflation-based procedure, which is referred to as joint/individual thin independent component analysis (JI-ThICA). The proposed algorithm is based on two cost functions utilizing higher order cumulants to extract joint and individual sources. Joint sources are discriminated by fusing signals of all subjects, whereas individual sources are extracted separately for each subject. Furthermore, JI-ThICA algorithm estimates the number of... 

The joint analysis of multiple datasets to extract their interdependency information has wide applications in biomedical and health informatics. In this paper, we propose an algorithm to extract joint and individual sources of multi-subject datasets by using a deflation based procedure, which is referred to as joint/individual thin independent component analysis (JI-ThICA). The proposed algorithm is based on two cost functions utilizing higher order cumulants to extract joint and individual sources. Joint sources are discriminated by fusing signals of all subjects, whereas individual sources are extracted separately for each subject. Furthermore, JI-ThICA algorithm estimates the number of... 

Chromatographic fingerprinting is an effective methodology for authentication and quality control of herbal products. In the presented study, a chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and multivariate pattern recognition methods was used to establish a gas chromatography-mass spectrometry (GC-MS) fingerprint of saffron. For this purpose, the volatile metabolites of 17 Iranian saffron samples, collected from different geographical regions, were determined using the combined method of ultrasound-assisted solvent extraction (UASE) and dispersive liquid-liquid microextraction (DLLME), coupled with GC-MS. The resolved elution profiles and... 

An important issue for efficient execution of MapReduce jobs on a cloud platform is selecting the best fitting virtual machine (VM) configuration(s) among the miscellany of choices that cloud providers offer. Wise selection of VM configurations can lead to better performance, cost and energy consumption. Therefore, it is crucial to explore the available configurations and choose the best one for each given MapReduce application. Executing the given application on all the configurations for comparison is a costly, time and energy consuming process. An alternative is to run the application on a subset of configurations (sample configurations) and estimate its performance on other...