scholarly journals GenSeizer: A Multiplex PCR-Based Targeted Gene Sequencing Platform for Rapid and Accurate Identification of Major Mycobacterium Species

2020 ◽  
Author(s):  
Bing Li ◽  
Liyun Xu ◽  
Qi Guo ◽  
Jianhui Chen ◽  
Yanan Zhang ◽  
...  
Keyword(s):  
Multiplex Pcr ◽  
Clinical Symptoms ◽  
Simultaneous Detection ◽  
Gene Sequencing ◽  
Large Data ◽  
Cross Reactivity ◽  
Accurate Identification ◽  
Data Set ◽  
Sequencing Platform ◽  
Targeted Gene Sequencing

Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM) infections often exhibit similar clinical symptoms. Timely and effective treatment relies on the rapid and accurate identification of species and resistance genotypes. In this study, a new platform (GenSeizer), which combines bioinformatics analysis of a large data set and multiplex PCR-based targeted gene sequencing, was developed to identify 10 major Mycobacterium species that cause pulmonary, as well as extrapulmonary, human diseases. Simultaneous detection of certain resistance erm(41) and rrl genotypes in M. abscessus was also feasible. This platform was specific and sensitive, exhibited no cross-reactivity among reference strains and a detection limit of 5 DNA copies or 50 CFU Mycobacterium/ml. In a blinded comparison, GenSeizer and multigene sequencing showed 100% agreement in the ability to identify 88 clinical, Mycobacterium isolates. The resistance genotypes, confirmed by whole genome sequencing of 30 M. abscessus strains, were also correctly identified by GenSeizer 100% of the time. These results indicate that GenSeizer is an efficient, reliable platform for diagnosing major pathogenic Mycobacterium species.

scholarly journals Clinical and genetic spectrum of glycogen storage disease in Iranian population using targeted gene sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zahra Beyzaei ◽  
Fatih Ezgu ◽  
Bita Geramizadeh ◽  
Mohammad Hadi Imanieh ◽  
Mahmood Haghighat ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Molecular Genetic ◽  
Gene Sequencing ◽  
Glycogen Storage ◽  
Loss Of Function ◽  
Retrospective Case ◽  
Complex Disorders ◽  
Glycogen Storage Diseases ◽  
Targeted Gene Sequencing ◽  
Retrospective Case Study

AbstractGlycogen storage diseases (GSDs) are known as complex disorders with overlapping manifestations. These features also preclude a specific clinical diagnosis, requiring more accurate paraclinical tests. To evaluate the patients with particular diagnosis features characterizing GSD, an observational retrospective case study was designed by performing a targeted gene sequencing (TGS) for accurate subtyping. A total of the 15 pediatric patients were admitted to our hospital and referred for molecular genetic testing using TGS. Eight genes namely SLC37A4, AGL, GBE1, PYGL, PHKB, PGAM2, and PRKAG2 were detected to be responsible for the onset of the clinical symptoms. A total number of 15 variants were identified i.e. mostly loss-of-function (LoF) variants, of which 10 variants were novel. Finally, diagnosis of GSD types Ib, III, IV, VI, IXb, IXc, X, and GSD of the heart, lethal congenital was made in 13 out of the 14 patients. Notably, GSD-IX and GSD of the heart-lethal congenital (i.e. PRKAG2 deficiency) patients have been reported in Iran for the first time which shown the development of liver cirrhosis with novel variants. These results showed that TGS, in combination with clinical, biochemical, and pathological hallmarks, could provide accurate and high-throughput results for diagnosing and sub-typing GSD and related diseases.

Development of multiplex PCR for rapid detection of metallo-β-lactamase genes in clinical isolates of Acinetobacter baumannii

2020 ◽  
Author(s):  
Reza Ranjbar ◽  
Shahin Zayeri ◽  
Amir Mirzaie
Keyword(s):  
Acinetobacter Baumannii ◽  
Multiplex Pcr ◽  
Rapid Detection ◽  
Simultaneous Detection ◽  
Cross Reactivity ◽  
Clinical Isolates ◽  
Clinical Samples ◽  
Pcr Assay ◽  
Multiplex Pcr Assay

Background and Objectives: Acinetobacter baumannii has been known as a major pathogen causing nosocomial infec- tions. The aim of this study was to develop multiplex PCR for rapid and simultaneous detection of metallo-β-lactamase (MBL) genes in clinical isolates of A. baumannii. Materials and Methods: In this study, we used three sets of primers to amplify the MBL genes including bla        ,     bla   and bla   OXA-48 . The multiplex PCR assay was optimized for rapid and simultaneous detection of MBL genes in A. bau-   OXA-23   NDM   mannii strains recovered from clinical samples. Results: A. baumannii strains recovered from clinical samples were subjected to the study. The multiplex PCR produced 3   OXA-48   OXA-23   bands of 501 bp for bla        , 744 bp for bla observed in multiplex PCR.   OXA-48   and 623 bp for bla   NDM   genes. In addition to, no any cross-reactivity was   Conclusion: Based on obtained data, the multiplex PCR had a good specificity without any cross reactivity and it appears that the multiplex PCR is reliable assay for simultaneous detection of MBL genes in A. baumannii strains.  

scholarly journals Rapid and Accurate Analysis of an X-Ray Fluorescence Microscopy Data Set through Gaussian Mixture-Based Soft Clustering Methods

2013 ◽  
Vol 19 (5) ◽  
pp. 1281-1289 ◽  
Author(s):  
Jesse Ward ◽  
Rebecca Marvin ◽  
Thomas O'Halloran ◽  
Chris Jacobsen ◽  
Stefan Vogt
Keyword(s):  
Simultaneous Detection ◽  
Large Data ◽  
Gaussian Mixture ◽  
Subcellular Fractionation ◽  
Food Vacuole ◽  
Clustering Methods ◽  
Accurate Analysis ◽  
Data Set ◽  
X Ray ◽  
Soft Clustering

AbstractX-ray fluorescence (XRF) microscopy is an important tool for studying trace metals in biology, enabling simultaneous detection of multiple elements of interest and allowing quantification of metals in organelles without the need for subcellular fractionation. Currently, analysis of XRF images is often done using manually defined regions of interest (ROIs). However, since advances in synchrotron instrumentation have enabled the collection of very large data sets encompassing hundreds of cells, manual approaches are becoming increasingly impractical. We describe here the use of soft clustering to identify cell ROIs based on elemental contents, using data collected over a sample of the malaria parasite Plasmodium falciparum as a test case. Soft clustering was able to successfully classify regions in infected erythrocytes as “parasite,” “food vacuole,” “host,” or “background.” In contrast, hard clustering using the k-means algorithm was found to have difficulty in distinguishing cells from background. While initial tests showed convergence on two or three distinct solutions in 60% of the cells studied, subsequent modifications to the clustering routine improved results to yield 100% consistency in image segmentation. Data extracted using soft cluster ROIs were found to be as accurate as data extracted using manually defined ROIs, and analysis time was considerably improved.

scholarly journals Performance assessment of a multi-epitope chimeric antigen for the serological diagnosis of acute Mayaro fever

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paloma Napoleão-Pêgo ◽  
Flávia R. G. Carneiro ◽  
Andressa M. Durans ◽  
Larissa R. Gomes ◽  
Carlos M. Morel ◽  
...  
Keyword(s):  
High Performance ◽  
Clinical Symptoms ◽  
Chimeric Protein ◽  
Cross Reactivity ◽  
Effective Control ◽  
Antigenic Determinants ◽  
Gene Encoding ◽  
Accurate Identification ◽  
Serological Tests ◽  
Mayaro Virus

AbstractMayaro virus (MAYV), which causes mayaro fever, is endemic to limited regions of South America that may expand due to the possible involvement of Aedes spp. mosquitoes in its transmission. Its effective control will require the accurate identification of infected individuals, which has been restricted to nucleic acid-based tests due to similarities with other emerging members of the Alphavirus genus of the Togaviridae family; both in structure and clinical symptoms. Serological tests have a more significant potential to expand testing at a reasonable cost, and their performance primarily reflects that of the antigen utilized to capture pathogen-specific antibodies. Here, we describe the assembly of a synthetic gene encoding multiple copies of antigenic determinants mapped from the nsP1, nsP2, E1, and E2 proteins of MAYV that readily expressed as a stable chimeric protein in bacteria. Its serological performance as the target in ELISAs revealed a high accuracy for detecting anti-MAYV IgM antibodies. No cross-reactivity was observed with serum from seropositive individuals for dengue, chikungunya, yellow fever, Zika, and other infectious diseases as well as healthy individuals. Our data suggest that this bioengineered antigen could be used to develop high-performance serological tests for MAYV infections.

scholarly journals Cas12a/Guide RNA-Based Platform for Rapid and Accurate Identification of Major Mycobacterium Species

2019 ◽  
Vol 58 (2) ◽  
Author(s):  
Guohui Xiao ◽  
Xing He ◽  
Su Zhang ◽  
Yaya Liu ◽  
Zhihang Liang ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Cost Effective ◽  
Cross Reactivity ◽  
Mycobacterium Abscessus ◽  
Mycobacterium Fortuitum ◽  
Accurate Identification ◽  
Content Type ◽  
Guide Rna ◽  
Promising Tool ◽  
Species Specific

ABSTRACT Mycobacterium tuberculosis infection and nontuberculous mycobacteria (NTM) infections exhibit similar clinical symptoms; however, the therapies for these two types of infections are different. Therefore, the rapid and accurate identification of M. tuberculosis and NTM species is very important for the control of tuberculosis and NTM infections. In the present study, a Cas12a/guide RNA (gRNA)-based platform was developed to identify M. tuberculosis and most NTM species. By designing species-specific gRNA probes targeting the rpoB sequence, a Cas12a/gRNA-based platform successfully identified M. tuberculosis and six major NTM species (Mycobacterium abscessus, Mycobacterium intracellulare, Mycobacterium avium, Mycobacterium kansasii, Mycobacterium gordonae, and Mycobacterium fortuitum) without cross-reactivity. In a blind assessment, a total of 72 out of 73 clinical Mycobacterium isolates were correctly identified, which is consistent with previous rpoB sequencing results. These results suggest that the Cas12a/gRNA-based platform is a promising tool for the rapid, accurate, and cost-effective identification of both M. tuberculosis and NTM species.

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Regression Tree ◽  
Large Data ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Gradient Boosting ◽  
Support Vector ◽  
Data Set ◽  
Descriptor Selection

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

scholarly journals Correlation between the structure and skin permeability of compounds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruolan Zeng ◽  
Jiyong Deng ◽  
Limin Dang ◽  
Xinliang Yu
Keyword(s):  
Large Data ◽  
Qsar Model ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Skin Permeability ◽  
Data Set ◽  
Test Set ◽  
Svm Algorithm ◽  
Svm Model ◽  
Toxicity Relationship

AbstractA three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals The Complete DNA Sequence of the Mitochondrial Genome of a “Living Fossil,” the Coelacanth (Latimeria chalumnae)

Genetics ◽  
1997 ◽  
Vol 146 (3) ◽  
pp. 995-1010 ◽  
Author(s):  
Rafael Zardoya ◽  
Axel Meyer
Keyword(s):  
Mitochondrial Genome ◽  
Tandem Repeats ◽  
Phylogenetic Analyses ◽  
Large Data ◽  
Molecular Data ◽  
Phylogenetic Position ◽  
Data Set ◽  
Living Fossil ◽  
Latimeria Chalumnae ◽  
Relationship Of

The complete nucleotide sequence of the 16,407-bp mitochondrial genome of the coelacanth (Latimeria chalumnae) was determined. The coelacanth mitochondrial genome order is identical to the consensus vertebrate gene order which is also found in all ray-finned fishes, the lungfish, and most tetrapods. Base composition and codon usage also conform to typical vertebrate patterns. The entire mitochondrial genome was PCR-amplified with 24 sets of primers that are expected to amplify homologous regions in other related vertebrate species. Analyses of the control region of the coelacanth mitochondrial genome revealed the existence of four 22-bp tandem repeats close to its 3′ end. The phylogenetic analyses of a large data set combining genes coding for rRNAs, tRNA, and proteins (16,140 characters) confirmed the phylogenetic position of the coelacanth as a lobe-finned fish; it is more closely related to tetrapods than to ray-finned fishes. However, different phylogenetic methods applied to this largest available molecular data set were unable to resolve unambiguously the relationship of the coelacanth to the two other groups of extant lobe-finned fishes, the lungfishes and the tetrapods. Maximum parsimony favored a lungfish/coelacanth or a lungfish/tetrapod sistergroup relationship depending on which transversion:transition weighting is assumed. Neighbor-joining and maximum likelihood supported a lungfish/tetrapod sistergroup relationship.

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