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Micropropagation of Aloe vera L. Grown in South Iran
R. Hosseini,M. Parsa
Pakistan Journal of Biological Sciences , 2007,
Abstract: Abstarct: Aloe vera L. is a medicinal plant grown in different parts of the world. Several papers have reported the micropropagation of this plant and its response to different combinations of hormones. In this research, we used A. vera plants grown in south Iran. MS culture medium with twenty three combinations of hormones were used, including some of those employed previously by other researchers. Ten media showed positive results and the best result was obtained using Kin (1 mg L-1)+IAA (0.1 mg L-1) which has not been reported before. Produced plantlets rooted in free hormone MS medium and transferred into soil. The survival rate was 83%.
Computer- Aided diagnosis system for the evaluation of chronic obstructive pulmonary disease on CT Images
Parsa Hosseini M,Soltanian-Zadeh H,Akhlaghpoor Sh
Tehran University Medical Journal , 2011,
Abstract: "n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Chronic Obstructive Pulmonary Disease (COPD) is one of the most prevalent pulmonary diseases. Use of an automatic system for the detection and diagnosis of the disease will be beneficial to the patients' treatment decision-making process. In this paper, we propose a new approach for the Computer Aided Diagnosis (CAD) of the disease and determination of its severity axial CT scan images."n"nMethods: In this study, 24 lung CT scans in full inspiratory and expiratory states were performed. Variations in the normalized pattern of the lungs' external parenchyma were exploited as a feature for COPD diagnosis. Subsequently, a Bayesian classifier was used to classify variations into two normal and abnormal patterns for the discrimination of patients and healthy individuals. Finally, the accuracy of the classification was assessed statistically. "n"nResults: With the proposed method, the lungs parenchymal elasticity and air-trapping were determined quantitatively. The more this feature tended to zero, the more severe air-trapping and obstructive pulmonary disease is. By analyzing CT images in the healthy and patient groups, we calculated the hard threshold for the diagnosis of the disease. Clinical results tested by the mentioned method, suggested the effectiveness of this approach."n"nConclusion: In regard to the challenges of COPD diagnosis, we propose a new computer-aided design which may be helpful to physicians for a more accurate diagnosis of the disease. Moreover, this severity scoring algorithm may be useful for targeted disease management and risk-adjustment.
Designing A New CAD System for Pulmonary Nodule Detection in High Resolution Computed Tomography (HRCT) Images
M Parsa Hosseini,H Soltanian-Zadeh,SH Akhlaghpoor,A Jalali
Tehran University Medical Journal , 2012,
Abstract: Background: Lung diseases and lung cancer are among the most dangerous diseases with high mortality in both men and women. Lung nodules are abnormal pulmonary masses and are among major lung symptoms. A Computer Aided Diagnosis (CAD) system may play an important role in accurate and early detection of lung nodules. This article presents a new CAD system for lung nodule detection from chest computed tomography (CT) images.Methods: Twenty-five adult patients with lung nodules in their CT scan images presented to the National Research Institute of Tuberculosis and Lung Disease, Masih Daneshvari Hospital, Tehran, Iran in 2011-2012 were enrolled in the study. The patients were randomly assigned into two experimental (9 female, 6 male, mean age 43±5.63 yrs) and control (6 female, 4 male, mean age 39±4.91 yrs) groups. A fully-automatic method was developed for detecting lung nodules by employing medical image processing and analysis and statistical pattern recognition algorithms.esults: Using segmentation methods, the lung parenchyma was extracted from 2-D CT images. Then, candidate regions were labeled in pseudo-color images. In the next step, some features of lung nodules were extracted. Finally, an artificial feed forward neural network was used for classification of nodules.Conclusion: Considering the complexity and different shapes of lung nodules and large number of CT images to evaluate, finding lung nodules are difficult and time consuming for physicians and include human error. Experimental results showed the accuracy of the proposed method to be appropriate (P<0.05) for lung nodule detection.
An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets
Parsa Hosseini, Arianne Tremblay, Benjamin F Matthews, Nadim W Alkharouf
BMC Research Notes , 2010, DOI: 10.1186/1756-0500-3-183
Abstract: We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations.TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data in a CASAVA-build into functional annotations while producing corresponding gene expression measurements. Achieving such analysis is executed in an ultrafast and highly efficient manner, whether the analysis be a single-read or paired-end sequencing experiment. TASE is a user-friendly and freely available application, allowing rapid analysis and annotation of any given Illumina Solexa sequencing dataset with ease.In one run, the Illumina Solexa Genome Analyzer II sequencer produces over 50 billion nucleotides of DNA sequence data [1]. The Illumina Solexa sequencer can be used to sequence genomes as well as sequence DNA reverse transcribed from RNA to provide gene expression information. As the read length of Illumina Solexa sequ
Detection and Severity Scoring of Chronic Obstructive Pulmonary Disease Using Volumetric Analysis of Lung CT Images
Mohammad Parsa Hosseini,Hamid Soltanian-Zadeh,Shahram Akhlaghpoor
Iranian Journal of Radiology , 2012,
Abstract: Background: Chronic obstructive pulmonary disease (COPD) is a devastating disease. While there is no cure for COPD and the lung damage associated with this disease cannot be reversed, it is still very important to diagnose it as early as possible.Objectives: In this paper, we propose a novel method based on the measurement of air trapping in the lungs from CT images to detect COPD and to evaluate its severity.Patients and Methods: Twenty-five patients and twelve normal adults were included in this study. The proposed method found volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration were compared and changes in the areas and volumes of the lungs between inspiration and expiration were used to define quantitative measures (features). Using these features, the subjects were classified into two groups of normal and COPD patients using a Bayesian classifier. In addition, t-tests were applied to evaluate discrimination powers of the features for this classification.Results: For the cases studied, the proposed method estimated air trapping in the lungs from CT images without human intervention. Based on the results, a mathematical model was developed to relate variations of lung volumes to the severity of the disease.Conclusions: As a computer aided diagnosis (CAD) system, the proposed method may assist radiologists in the detection of COPD. It quantifies air trapping in the lungs and thus may assist them with the scoring of the disease by quantifying the severity of the disease.
MAPT and PAICE: Tools for time series and single time point transcriptionist visualization and knowledge discovery
Parsa Hosseini,Arianne Tremblay,Benjamin F Matthews,Nadim W Alkharouf
Bioinformation , 2012,
Abstract: With the advent of next-generation sequencing, -omics fields such as transcriptomics have experienced increases in data throughput on the order of magnitudes. In terms of analyzing and visually representing these huge datasets, an intuitive and computationally tractable approach is to map quantified transcript expression onto biochemical pathways while employing data-mining and visualization principles to accelerate knowledge discovery. We present two cross-platform tools: MAPT (Mapping and Analysis of Pathways through Time) and PAICE (Pathway Analysis and Integrated Coloring of Experiments), an easy to use analysis suite to facilitate time series and single time point transcriptomics analysis. In unison, MAPT and PAICE serve as a visual workbench for transcriptomics knowledge discovery, data-mining and functional annotation. Both PAICE and MAPT are two distinct but yet inextricably linked tools. The former is specifically designed to map EC accessions onto KEGG pathways while handling multiple gene copies, detection-call analysis, as well as UN/annotated EC accessions lacking quantifiable expression. The latter tool integrates PAICE datasets to drive visualization, annotation, and data-mining.
Changes of Left Ventricular Mass Index Among End-Stage Renal Disease Patients After Renal Transplantation
Mohammad Hassan Namazi,Saeed Alipour Parsa,Banafshe Hosseini,Habibollah Saadat
Urology Journal , 2010,
Abstract: Purpose: The aim of this study was to determine left ventricular (LV) mass index via echocardiography in end-stage renal disease patients (ESRD) before and after renal transplantation, and its association with one-year survival. Materials and Methods: Forty-seven patients with ESRD who were candidate for renal transplantation were evaluated with echocardiography before and 4 months after the operation. Left ventricular ejection fraction (EF), LV mass, and LV mass index were determined. All of the patients were followed up for 1 year.Results: Mean LVEF was 51.6% which increased to 53.7% after renal transplantation (P = .001). Mean LV mass was 209 gr before the operation which decreased to 189 gr after the operation (P = .001). Mean LV mass index before the operation was 120 gr/m2 which decreased to 110 gr/m2 following the operation (P = .002). All of the patients survived during 1-year follow-up, and no death was reported.Conclusion: Renal transplantation had beneficial effects in terms of LV function in young patients with ESRD.
Topological quantum buses: coherent quantum information transfer between topological and conventional qubits
Parsa Bonderson,Roman M. Lutchyn
Physics , 2010, DOI: 10.1103/PhysRevLett.106.130505
Abstract: We propose computing bus devices that enable quantum information to be coherently transferred between topological and conventional qubits. We describe a concrete realization of such a topological quantum bus acting between a topological qubit in a Majorana wire network and a conventional semiconductor double quantum dot qubit. Specifically, this device measures the joint (fermion) parity of these two different qubits by using the Aharonov-Casher effect in conjunction with an ancilliary superconducting flux qubit that facilitates the measurement. Such a parity measurement, together with the ability to apply Hadamard gates to the two qubits, allows one to produce states in which the topological and conventional qubits are maximally entangled and to teleport quantum states between the topological and conventional quantum systems.
Regular sequences and local cohomology modules with respect to a pair of ideals
Sh. Payrovi,M. Lotfi Parsa
Mathematics , 2013,
Abstract: Let $R$ be a Noetherian ring, $I$ and $J$ two ideals of $R$ and $t$ an integer. Let $S$ be the class of Artinian $R$-modules, or the class of all $R$-modules $N$ with $\dim_RN\leq k$, where $k$ is an integer. It is proved that $\inf\{i: H^{i}_{I,J}(M)\notin S\}=\inf\{S-\depth_\frak{a}(M): \frak{a}\in \tilde{\rm W}(I,J)\}$, where $M$ is a finitely generated $R$-module, or is a $ZD$-module such that $M/\frak{a}M\notin S$ for all $\frak{a}\in \tilde{\rm W}(I,J)$. Let $\Supp_R H^{i}_{I,J}(M)$ be a finite subset of $\Max(R)$ for all $i
Regular sequences and ZD-modules
Sh. Payrovi,M. Lotfi Parsa
Mathematics , 2013,
Abstract: Let R be a Noetherian ring, I an ideal of R and M a ZD-module. Let S be a Melkersson subcategory with respect to I such that M/IM doesn't belong to S. We show that all maximal S-sequences on M in I, have equal length. If this common length is denoted by S-depth_I(M), then S-depth_I(M) = inf{i : H^i_I(M) doesn't belong to S}.
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