Semi-automatic Extraction Research Articles

Comparison of two nucleic acid extraction and testing systems for HCMV-DNA detection and quantitation on whole blood specimens from transplant patients

Quantitative detection of human cytomegalovirus (HCMV) DNA on whole blood is currently the primary choice for virological monitoring in transplant patients and for determining the appropriate antiviral strategy, however specific issues of variability remain in terms of extraction methods, amplification efficiency, and variability. This study compared the performance characteristics of two nucleic acid extraction and testing systems for HCMV-DNA quantitation, the artus® CMV QS-RGQ kit, associated with a fully automated DNA extraction and assay set up by Qiagen (system 1) and the Q-CMV Real Time Complete kit by Nanogen, associated with a semiautomated nucleic acid extraction system by Biomérieux (system 2) in 189 specimens from transplant patients and 10 from 2012 HCMV Quality Control for Molecular Diagnostics (QCMD). The two systems exhibited a 80.4% concordance. Differences between the two systems were within ±1log10copies/ml of the averaged log10 results for 88.9% of the tested specimens. For all qualitatively discordant specimens, mean viral load was ≤3log10copies/ml. Considering viral load measurement, system 1 gave earlier positives that system 2, with a 14.8% of specimens resulted positive at low viral loads with system 1 and negative with system 2. In QCMD specimens, difference was below 0.7log10copies/ml for both the systems.In conclusion, the two systems provided reliable and comparable results. Some specific performance characteristic and automation could be taken into account in terms of less hands of time, fewer errors and reliability.

Object information based interactive segmentation for fatty tissue extraction

Lymph nodes are very important factors for diagnosing gastric cancer in clinical use, and are usually distributed within the fatty tissue around the stomach. When extracting fatty tissues whose structures and textures are complicated, automatic extraction is still a challenging task, while manual extraction is time-consuming. Consequently, semi-automatic extraction, which allows introducing interactive operations, appears to be more realistic. Currently, most interactive methods need to indicate the position and main features in both the object and background. However, it is easier for radiologists to only mark object information. Due to this issue, a new Object Information based Interactive Segmentation (OIIS) method is proposed in this paper. Different from the most existing methods, OIIS just needs to input the object information, while the background information is not required. Experimental results and comparative studies show that OIIS is effective for fatty tissue extraction.

Semi-Automatic Extraction of Straight Roads from Very High Resolution Remotely Sensed Imagery by a Fusion Method

Semi-automatic road tracking methods are regarded as more practical than automatic methods to obtain and update the vector road data. However, road tracking methods lose efficiency when they are applied to extract the straight roads compared to manual digitalizing. An efficient semi-automatic method is proposed for extraction of the straight roads in this paper. Particularly, spoke wheel algorithm and region growing algorithm are combined and fused together to extract a rectangle corresponding to a short road segment. The above process is performed at each pixel along the line segment between two seed points, which derives some rectangles. Moreover, statistical analysis of histograms of directions and widths of the obtained rectangles is made to determine the optimal rectangle. Then a precise road model is determined by the above optimal rectangle. Experiments show that our fused method is capable of efficiently extracting straight roads with a high spatial accuracy, even various types of noises existing.

Semiautomated solid-phase extraction manifold with a solvent-level sensor

A semiautomated solid-phase extraction manifold for multiple extractions is presented. The manifold utilizes commercial solid-phase syringe cartridges and automatically introduces and elutes all the solvents during the extraction, reducing the typical workload and stress of the analyst. The manifold consists of a peristaltic pump with solenoid valves in a flow circuit that contains transmissive photomicrosensors. The photomicrosensors were used to control the solvent dispenser and the solvent level inside the cartridge. As solvent-level sensors, the photomicrosensors determined the exact time the solvent reached the top frit to avoid sorbent drying and accurately perform the solvent exchange. The repeatability of the manifold to introduce a particular volume of solvent into the cartridges was measured, and the precisions were between 0.05 and 2.89% (RSD). To evaluate the manifold, the amount of two fluoroquinolones in a fortified blank milk sample was determined. The results of the intra- and inter-day precision of multiple extractions from the fortified milk samples resulted in precisions better than 9.0% (RSD) and confirmed that the arrangement of the semiautomated manifold could adequately be used in solid-phase extraction with commercial cartridges.

Semi-automated solid phase extraction method for the mass spectrometric quantification of 12 specific metabolites of organophosphorus pesticides, synthetic pyrethroids, and select herbicides in human urine

Organophosphate and pyrethroid insecticides and phenoxyacetic acid herbicides represent important classes of pesticides applied in commercial and residential settings. Interest in assessing the extent of human exposure to these pesticides exists because of their widespread use and their potential adverse health effects. An analytical method for measuring 12 biomarkers of several of these pesticides in urine has been developed. The target analytes were extracted from one milliliter of urine by a semi-automated solid phase extraction technique, separated from each other and from other urinary biomolecules by reversed-phase high performance liquid chromatography, and detected using tandem mass spectrometry with isotope dilution quantitation. This method can be used to measure all the target analytes in one injection with similar repeatability and detection limits of previous methods which required more than one injection. Each step of the procedure was optimized to produce a robust, reproducible, accurate, precise and efficient method. The required selectivity and sensitivity for trace-level analysis (e.g., limits of detection below 0.5ng/mL) was achieved using a narrow diameter analytical column, higher than unit mass resolution for certain analytes, and stable isotope labeled internal standards. The method was applied to the analysis of 55 samples collected from adult anonymous donors with no known exposure to the target pesticides. This efficient and cost-effective method is adequate to handle the large number of samples required for national biomonitoring surveys.

A tool for semi-automated extraction of waterbody feature in SAR imagery

This letter describes the mechanisms of a semi-automated approach of waterbody (lakes and watercourses) feature extraction in synthetic aperture radar (SAR) imagery. The approach is semi-automatic because it requires an interest region for each waterbody to be extracted. This interest region can be provided by the user (manually drawn in the case of new feature extraction) or imported from an existing spatial database (on the case of maps updating). Once the interest region is determined, the tool produces the waterbody feature then the user rejects, accepts after amending or accepts it directly. To process a waterbody, the procedure occurs in four main steps: (1) interest region delimitation; (2) estimation of statistical characteristics of the two regions: inside waterbody and outside waterbody; (3) classification of each resolution cell as inside waterbody or as outside waterbody and (4) determination of main waterbody and converting its edge to a feature. The later will be indexed in a spatial database. The approach accelerates and ameliorates waterbody feature extraction, and it has been tested with success and then integrated into a topographic map production system, especially for the Canadian northern regions, where there is a high density of waterbodies and where Radarsat-2 satellite (our provider of SAR images) are regularly used.

Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

Accurate 3D road information is important for applications such as road maintenance and virtual 3D modeling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive “scanning lines”, which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and refined so that they are both globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech’s Lynx Mobile Mapper System. The completeness, correctness, and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively, which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds.

Extraction of Electronic Health Record Data in a Hospital Setting: Comparison of Automatic and Semi‐Automatic Methods Using Anti‐TNF Therapy as Model

There is limited experience and methods for extractions of drug therapy data from electronic health records (EHR) in the hospital setting. We have therefore developed and evaluated completeness and consistency of an automatic versus a semi-automatic extraction procedure applied on prescribing and administration of the TNF inhibitor infliximab using a hospital EHR system in Karolinska University Hospital, Sweden. Using two different extraction methods (automatic and semi-automatic), all administered infusions of infliximab between 2007 and 2010 were extracted from a database linked to the EHR system. Extracted data included encrypted personal identity number (PIN), date of birth, sex, time of prescription/administration, healthcare units, prescribed/administered dose and time of admission/discharge. The primary diagnosis (ICD-10) for the treatment with infliximab was extracted by linking infliximab infusions to their corresponding treatment episode. A total of 13,590 infusions of infliximab were administered during the period of 2007 to 2010. Of those were 13,531 (99.6%) possible to link to a corresponding treatment episode, and a primary diagnosis was extracted for 13,530 infusions. Information on encrypted PIN, date of birth, time of prescription/administration, time of admission/discharge and healthcare unit was complete. Information about sex was missing in one patient only. Calculable information about dosage was extracted for 13,300 (98.3%) of all linked infusions. This methodological study showed the potential to extract drug therapy data in a hospital setting. The semi-automatic procedure produced an almost complete pattern of demographics, diagnoses and dosages for the treatment with infliximab.

Scientific Ontology Construction Based on Interval Valued Fuzzy Theory Under Web 2.0

Constructi on of the unified and shared domain ontology is significant for effective knowledge management. For the acquisition and sharing of scientific research knowledge under Web2.0, a novel approach of building Interval Valued Fuzzy Ontology ( IVFO ) in scientific research domain is presented. Through interval valued fuzzy theory, the definition and constructing framework of IVFO is proposed. Then IVFO is applied to semi-automatic extraction of information retrieval research domain. The preliminary constructing of research domain ontology is an essential base for the knowledge management system of scientific research. It can be effective methods for enhancing the efficiency and productivity of researching.

Validation and application of a fast semi-automated whole blood extraction for LC-MS/MS simultaneous quantification of cyclosporine A, tacrolimus, sirolimus and everolimus – application to high throughput routine therapeutic drug monitoring

Numerous laboratories carried out simultaneous whole blood quantitation of everolimus, sirolimus, tacrolimus and cyclosporine-A on a liquid chromatography-tandem mass-spectrometry (LC-MS/MS) system with online solid phase extraction (SPE) after manual deproteinization and centrifugation. This method had a relatively low sample throughput due to labor intensive and time-consuming sample preparation. We develop a fast and robust method of semi-automated whole blood sample pre-treatment able to support over 120 samples daily. Whole blood samples were mixed in a V-bottom plate with 2 volumes of ZnSO4/methanol containing deuterated internal standards. After centrifugation, the supernatant was loaded on an online-SPE before being transferred and monitored on the LC-MS/MS system. Assay performance included inter- and intra-day accuracy and imprecision, relative and absolute matrix effects, extraction recovery and selectivity. Intra- and inter-day imprecision was <15% for all tested concentrations. The lower limit of quantification of cyclosporine-A, everolimus, sirolimus and tacrolimus was respectively 26.6, 1.13, 1.57 and 1.28 ng mL−1, with an accuracy between −0.63% and 11.48% and a precision <12% of the nominal concentration. Standard line slope imprecision did not exceed 20% and ion enhancement or suppression was negligible. The comparison methods were performed by Passing and Bablok regression analysis: a high correlation was found between the two pre-treatment methods for tacrolimus, everolimus and sirolimus and between LC-MS/MS vs. radio-immuno-assay for cyclosporine-A. We developed a fast, sound and less misleading analytical method for high throughput (over 120 samples daily) therapeutic drug monitoring of multiple immunosuppressive drugs in routine practice.

“Big Historical Data” Feature Extraction

In the 1930s, the Home Owners’ Loan Corporation (HOLC), a New Deal federal agency, surveyed hundreds of U.S. cities, producing a national map collection that documented the demographic, economic, infrastructural, and ethnic status of tens of thousands of neighborhoods across the country. The resulting collection of so-called redlining maps is one of the preeminent urban and racial surveys conducted in the history of the United States. We at the Digital Innovation Lab of the University of North Carolina at Chapel Hill are building a national digital collection of these paper maps, currently housed at the National Archives in Washington D.C., and using this collection to explore the use of semiautomated feature extraction techniques on large historical content. Our methodology is based on supervised, classification image processing techniques. We use a commercial tool called ArcScan, an extension to the popular ESRI ArcGIS software, to extract tens of thousands of neighborhood boundaries that can then be saved as vector overlays and used to drive the development of new types of research interfaces. We conclude the paper with examples of these new types of interfaces. Finally, we describe the potential impact of linking vectorized national collections together and the need for further research in this area, including using hybrid approaches that involve large-scale crowdsourcing.

A semi-automatic method for extracting a taxonomy for nuclear knowledge using hierarchical document clustering based on concept sets

In this paper, we present a text mining approach for the semiautomatic extraction of taxonomy of concepts for nuclear knowledge and evaluate the achievable results. Taxonomies are a fundamental part of any knowledge management strategy or framework. We propose a method for hierarchical document clustering based on the notion of frequent concept sets. Most clustering algorithms treat documents as a bag of words and bypass the important relationships between words, such as synonyms. In this method, we consider the semantic relationship between words and use a domain thesaurus (ETDE/INIS) to identify concepts. To validate the method, we conducted a case study in which we implemented a prototype, generating a taxonomy for nuclear knowledge with the goal of conceptually mapping the scientific production of the Brazilian Nuclear Energy Commission (CNEN).

DNA extraction method from teeth using QIAcube

The use of semi-automated extraction from forensic samples is useful both for contamination control and method reproducibility. However, when an accredited ISO17025 forensic laboratory starts to use a new analytical system, an internal validation procedure is needed before processing forensic samples. Here we show validation results obtained by introducing QIAcube automated station (Qiagen) for DNA extraction from teeth that enables seamless integration of automated low-throughput sample preparation into the laboratory workflow. Purification steps, in association with QIAamp DNA Investigator Kit, are thus fully automated, in order to prevent cross contamination.A total of 18 teeth stored for 4–5 years after removal and 8 teeth stored for one-two months at room temperature underwent to DNA extraction by using this system. Teeth were previously decontaminated and a conservative endodontic access to pulp chamber was performed. A blood reference of the teeth donors was also collected. After DNA extraction all samples were quantified by using Quantifiler® Duo DNA Quantification Kit. Total DNA ranging between 0.2 and 23,900ng in 50μl of TE buffer with no inhibitors presence in samples. The obtained results confirm the robustness and reproducibility of the extraction method with QIAcube technology.

ESTRATÉGIA SEMIAUTOMÁTICA DE EXTRAÇÃO DE CRUZAMENTOS DE VIAS EM ÁREAS URBANAS USANDO ORTOIMAGENS DE ALTA RESOLUÇÃO

Neste trabalho é apresentada e avaliada uma estratégia semiautomática para a extração do cruzamento de vias com o uso de ortoimagens de alta resolução espacial em cenas correspondentes a áreas urbanas densas. Na estratégia proposta a extração da malha viária é realizada através da coleta de um conjunto de dados de treinamento de amostras que gera, no software WEKA, a árvore de decisão contendo o conhecimento explícito das classes presentes nas imagens. Sobre a malha viária definida, são aplicados operadores morfológicos e algoritmos que permitem a geração de eixos de vias (esqueletos), detecção de hipóteses de cruzamentos, seleção de pontos de referência e a extração do cruzamento de vias. A estratégia propostas foi testada com dados reais e os resultados obtidos foram analisados, permitindo uma avaliação da estratégia, bem como das situações potencialmente problemáticas. Os resultados apresentados nos experimentos demonstraram a viabilidade da extração de vias em cenas de áreas urbanas densas, formadas por malhas viárias com cruzamentos simples e complexos.

Semi-automated extraction of Deviation Indexes (DI) from satellite Persistent Scatterers time series: tests on sedimentary volcanism and tectonically-induced motions

Abstract. We develop a methodology based on satellite Persistent Scatterers (PS) time series and aimed to calculate two indexes which are capable to depict the deviation from a deformation model defined a priori. Through a simple mathematical approach, these indexes reproduce the visual process of identification of trend deviations that is usually performed manually by the radar-interpreter, and guide the prioritization of further interpretation for those areas recording significant variations within their motion history. First tests on semi-automated extraction of the Deviation Indexes (DI) from RADARSAT-1 PS data available over Southern Italy allowed the quantification of tectonically-induced land motions which occurred in February 2005 within the town of Naro, and also the clear recognition of the precursors to mud volcano eruptions which occurred in August 2008 in the village of St. Barbara. For these areas, the information level brought by the DI increases and adds onto that of other PS parameters, such as yearly velocity, standard deviation and coherence. Factors exerting influence on the DI are critically tackled within the discussions, together with the analysis of the potentials of these indexes for monitoring and warning activities of geohazards.

The ontogene system: an advanced information extraction application for biological literature

The ontogene system: an advanced information extraction application for biological literature

Cognitive Sociolinguistics meets loanword research: Measuring variation in the success of anglicisms in Dutch

AbstractThis paper introduces a new, concept-based method for measuring variation in the use and success of loanwords by presenting the results of a case-study on 149 English person reference nouns (i.e. common nouns used to designate people, such as manager) in Dutch. With this paper, we introduce four methodological improvements to current quantitative corpus-based anglicism research, based on the general tenets of Cognitive Sociolinguistics (Geeraerts 2005; Kristiansen and Geeraerts 2007; Geeraerts 2010; Geeraerts et al. 2010): (1) replacing raw frequency as a success measure by a concept-based onomasiological approach; (2) relying on larger datasets and semi-automatic extraction techniques; (3) adding a multivariate perspective to the predominantly structuralist orientation of current accounts; (4) using inferential statistical techniques to help explain variation. We illustrate our method by presenting a case-study on variation in the success of English person reference nouns in Dutch. Generally, this article aims to show how a Cognitive Sociolinguistic perspective on loanword research is beneficial for both paradigms. On the one hand, the concept-based approach provides new insights in the spread of loanwords. On the other hand, attention to contact linguistic phenomena offers a new expansion to the domain of cognitive linguistic studies taking a variationist approach.

A Semi-Automatic Algorithm on Extracting Road Networks from Airborne LiDAR Data

Airborne LiDAR (Light Detection and Ranging) is a powerful remote sensing measure to derive 3D coordinates from terrain surface. Automated or semi-automated road networks extraction from laser point clouds has been a challenging work during last few decades. In this paper, combining intensity with height information of point clouds, initial road point class is discerned using few seed points and subsequently smoothed throughout filling holes technology and morphological open operations. The skeleton of road networks is acquired by virtue of image thinning method and further eliminating short road burrs with length criteria. These center points of road are tracked and connected into vector line segments. By simplifying line nodes, road network can be formed in accuracy of which completeness is 79.8% and correctness is 79%. The virtues of this algorithm enables efficiently reduce errors brought by parking lots.

The integration of the terrestrial and airborne laser scanning technologies in the semi-automated process of retrieving selected trees and forest stand parameters / Integração das tecnologias terrestre e aerotransportada de scanner laser no processo semi-automático de recuperação de árvores selecionadas e de parâmetros de povoamentos florestais

The traditional forest inventory based usually on thousands of the circle plots (radius = 12.62m; area 500 sq m) set in regular network. On every inventory plot, the basic tree and forest stand parameters have to be collected using calliper and hypsometer or even human eye (i.e. crown closure) as well. The modern multifunctional forestry models requires more and more: dens and accurate data to deliver as fast as possible the precise information on the amount of wood stock or other selected forest stand and tree parameters. One of the promising remote sensing technologies is LiDAR collecting the 3D point cloud data. The TLS technology is very precise and fast but is limited to relatively small areas like forest inventory plot. The ALS is more focused on wide-area data collection. Both technologies are complementary, therefore it is a need for the fusion of those two sources of information to enhance the accuracy of tree parameters and enlarge the results for the wide forest areas with statistical models. Paper presents a method of the TLS and ALS point cloud registration and transformation to one coordinate system. The goal of the data fusion was the semi-automatic extraction of the trees selected parameter (height, DBH, basal area, crown closure, base of crown, 2D and 3D tree crown surface) of the TR2 transect in Niepolomice Forest (Krakow, Poland). The results showed that the big potential of the enhancement of height and crown closure or base of the crown exists. Resumo O inventário florestal tradicional baseia-se normalmente em milhares de parcelas circulares (raio = 12,62 m, área 500 m²) dispostas em uma malha regular. Em cada parcela do inventário, os parâmetros básicos da árvore e do povoamento devem sercoletados usando suta e hipsômetro ou até mesmo o olho humano (densidade de copa). Os modernos modelos florestais multifuncionais requerem cada vez mais: dados densos e acurados para gerar o mais rápido possível a informação precisa da quantidade de estoque de madeira ou outro parâmetro selecionado do povoamento e da árvore. Uma das tecnologias promissoras de sensoriamento remoto é o LiDAR coletando os dados da nuvem de pontos 3D. A tecnologia TLS é muito precisa e rápida mas limitada a áreas relativamente pequenas como as parcelas de inventários florestais. A ALS é mais focada na coleta de dados em grandes áreas. Ambas as tecnologias são complementares portanto, é necessário para a fusão das duas fontes de informação aumentar a acurácia dos parâmetros de árvore e ampliar os resultados para grandes áreas florestais com modelos estatísticos. O artigo apresenta um método de registro e transformação do TLS e nuvem de pontos do ALS para um sistema de coordenadas. O objetivo da fusão dos dados foi a extração semi automática de parâmetros selecionados de árvores (altura, DAP, área basal, densidade de copa, base da copa, área 2D e 3D da copa da árvore) do transecto TR2 da Floresta Niepolomice (Krakow, Polônia). Os resultados mostraram que o grande potencial do aprimoramento da altura e do densidade de copa ou da base da copa existe.

Semi-automated quantification of methylmalonic acid in human serum by LC-MS/MS

Background. Methylmalonic acid (MMA), a sensitive biomarker of functional vitamin B12 deficiency, is commonly determined by gas chromatography-mass spectrometry (GC-MS) or liquid chromatography–tandem mass spectrometry (LC-MS/MS) methods using manual extraction and derivatization of MMA to reduce polarity prior to separation. Methods. In the present study we introduce a semi-automated extraction on a strong anion exchanger, HPLC separation on a BEH-amide column to separate serum MMA from its abundant isoform, succinic acid, followed by MS/MS detection and quantification. Results. The extraction of MMA plus internal standard provides full recovery and the method is linear between 0.03 μmol/L and 20.0 μmol/L (r2 = 1.0) with intra-and inter-assay imprecision of 2.2%. Agreement with other laboratories has been demonstrated in external proficiency testing. Compared to both conventional GC-MS and LC-MS/MS methods, the correlation is r2 > 0.99. Conclusions. The use of robotic pipetting, elimination of derivatization and improved separation by the BEH-amide column combined with HILIC chromatographic conditions significantly improve sample throughput compared to conventional methods. Using a single pipetting robot and LC-MS/MS instrument, this method is currently performing 180 analyses per day from10 regional hospitals and several additional distant sites.