Quantitative Analysis of Heavy Metals in Children's Toys and Jewelry: A Multi-Instrument, Multitechnique Exercise in Analytical Chemistry and Public Health

ERIC Educational Resources Information Center

Finch, Lauren E.; Hillyer, Margot M.; Leopold, Michael C.

2015-01-01

For most chemistry curricula, laboratory-based activities in quantitative and instrumental analysis continue to be an important aspect of student development/training, one that can be more effective if conceptual understanding is delivered through an inquiry-based process relating the material to relevant issues of public interest and student…

Rapid Determination of Lymphogranuloma Venereum Serovars of Chlamydia trachomatis by Quantitative High-Resolution Melt Analysis (HRMA)

PubMed Central

Stevens, Matthew P.; Garland, Suzanne M.; Zaia, Angelo M.; Tabrizi, Sepehr N.

2012-01-01

A quantitative high-resolution melt analysis assay was developed to differentiate lymphogranuloma venereum-causing serovars of Chlamydia trachomatis (L1 to L3) from other C. trachomatis serovars (D to K). The detection limit of this assay is approximately 10 copies per reaction, comparable to the limits of other quantitative-PCR-based methods. PMID:22933594

Prognostic Value of Quantitative Stress Perfusion Cardiac Magnetic Resonance.

PubMed

Sammut, Eva C; Villa, Adriana D M; Di Giovine, Gabriella; Dancy, Luke; Bosio, Filippo; Gibbs, Thomas; Jeyabraba, Swarna; Schwenke, Susanne; Williams, Steven E; Marber, Michael; Alfakih, Khaled; Ismail, Tevfik F; Razavi, Reza; Chiribiri, Amedeo

2018-05-01

This study sought to evaluate the prognostic usefulness of visual and quantitative perfusion cardiac magnetic resonance (CMR) ischemic burden in an unselected group of patients and to assess the validity of consensus-based ischemic burden thresholds extrapolated from nuclear studies. There are limited data on the prognostic value of assessing myocardial ischemic burden by CMR, and there are none using quantitative perfusion analysis. Patients with suspected coronary artery disease referred for adenosine-stress perfusion CMR were included (n = 395; 70% male; age 58 ± 13 years). The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction, aborted sudden death, and revascularization after 90 days. Perfusion scans were assessed visually and with quantitative analysis. Cross-validated Cox regression analysis and net reclassification improvement were used to assess the incremental prognostic value of visual or quantitative perfusion analysis over a baseline clinical model, initially as continuous covariates, then using accepted thresholds of ≥2 segments or ≥10% myocardium. After a median 460 days (interquartile range: 190 to 869 days) follow-up, 52 patients reached the primary endpoint. At 2 years, the addition of ischemic burden was found to increase prognostic value over a baseline model of age, sex, and late gadolinium enhancement (baseline model area under the curve [AUC]: 0.75; visual AUC: 0.84; quantitative AUC: 0.85). Dichotomized quantitative ischemic burden performed better than visual assessment (net reclassification improvement 0.043 vs. 0.003 against baseline model). This study was the first to address the prognostic benefit of quantitative analysis of perfusion CMR and to support the use of consensus-based ischemic burden thresholds by perfusion CMR for prognostic evaluation of patients with suspected coronary artery disease. Quantitative analysis provided incremental prognostic value to visual assessment and established risk factors, potentially representing an important step forward in the translation of quantitative CMR perfusion analysis to the clinical setting. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

MilQuant: a free, generic software tool for isobaric tagging-based quantitation.

PubMed

Zou, Xiao; Zhao, Minzhi; Shen, Hongyan; Zhao, Xuyang; Tong, Yuanpeng; Wang, Qingsong; Wei, Shicheng; Ji, Jianguo

2012-09-18

Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation. Copyright © 2012 Elsevier B.V. All rights reserved.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

PubMed

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Improved quantitative analysis of spectra using a new method of obtaining derivative spectra based on a singular perturbation technique.

PubMed

Li, Zhigang; Wang, Qiaoyun; Lv, Jiangtao; Ma, Zhenhe; Yang, Linjuan

2015-06-01

Spectroscopy is often applied when a rapid quantitative analysis is required, but one challenge is the translation of raw spectra into a final analysis. Derivative spectra are often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to non-ideal instrument and sample properties. In this study, to improve quantitative analysis of near-infrared spectra, derivatives of noisy raw spectral data need to be estimated with high accuracy. A new spectral estimator based on singular perturbation technique, called the singular perturbation spectra estimator (SPSE), is presented, and the stability analysis of the estimator is given. Theoretical analysis and simulation experimental results confirm that the derivatives can be estimated with high accuracy using this estimator. Furthermore, the effectiveness of the estimator for processing noisy infrared spectra is evaluated using the analysis of beer spectra. The derivative spectra of the beer and the marzipan are used to build the calibration model using partial least squares (PLS) modeling. The results show that the PLS based on the new estimator can achieve better performance compared with the Savitzky-Golay algorithm and can serve as an alternative choice for quantitative analytical applications.

Quantitative analysis of drug distribution by ambient mass spectrometry imaging method with signal extinction normalization strategy and inkjet-printing technology.

PubMed

Luo, Zhigang; He, Jingjing; He, Jiuming; Huang, Lan; Song, Xiaowei; Li, Xin; Abliz, Zeper

2018-03-01

Quantitative mass spectrometry imaging (MSI) is a robust approach that provides both quantitative and spatial information for drug candidates' research. However, because of complicated signal suppression and interference, acquiring accurate quantitative information from MSI data remains a challenge, especially for whole-body tissue sample. Ambient MSI techniques using spray-based ionization appear to be ideal for pharmaceutical quantitative MSI analysis. However, it is more challenging, as it involves almost no sample preparation and is more susceptible to ion suppression/enhancement. Herein, based on our developed air flow-assisted desorption electrospray ionization (AFADESI)-MSI technology, an ambient quantitative MSI method was introduced by integrating inkjet-printing technology with normalization of the signal extinction coefficient (SEC) using the target compound itself. The method utilized a single calibration curve to quantify multiple tissue types. Basic blue 7 and an antitumor drug candidate (S-(+)-deoxytylophorinidine, CAT) were chosen to initially validate the feasibility and reliability of the quantitative MSI method. Rat tissue sections (heart, kidney, and brain) administered with CAT was then analyzed. The quantitative MSI analysis results were cross-validated by LC-MS/MS analysis data of the same tissues. The consistency suggests that the approach is able to fast obtain the quantitative MSI data without introducing interference into the in-situ environment of the tissue sample, and is potential to provide a high-throughput, economical and reliable approach for drug discovery and development. Copyright © 2017 Elsevier B.V. All rights reserved.

Linear Quantitative Profiling Method Fast Monitors Alkaloids of Sophora Flavescens That Was Verified by Tri-Marker Analyses

PubMed Central

Hou, Zhifei; Sun, Guoxiang; Guo, Yong

2016-01-01

The present study demonstrated the use of the Linear Quantitative Profiling Method (LQPM) to evaluate the quality of Alkaloids of Sophora flavescens (ASF) based on chromatographic fingerprints in an accurate, economical and fast way. Both linear qualitative and quantitative similarities were calculated in order to monitor the consistency of the samples. The results indicate that the linear qualitative similarity (LQLS) is not sufficiently discriminating due to the predominant presence of three alkaloid compounds (matrine, sophoridine and oxymatrine) in the test samples; however, the linear quantitative similarity (LQTS) was shown to be able to obviously identify the samples based on the difference in the quantitative content of all the chemical components. In addition, the fingerprint analysis was also supported by the quantitative analysis of three marker compounds. The LQTS was found to be highly correlated to the contents of the marker compounds, indicating that quantitative analysis of the marker compounds may be substituted with the LQPM based on the chromatographic fingerprints for the purpose of quantifying all chemicals of a complex sample system. Furthermore, once reference fingerprint (RFP) developed from a standard preparation in an immediate detection way and the composition similarities calculated out, LQPM could employ the classical mathematical model to effectively quantify the multiple components of ASF samples without any chemical standard. PMID:27529425

A Critical Appraisal of Techniques, Software Packages, and Standards for Quantitative Proteomic Analysis

PubMed Central

Lawless, Craig; Hubbard, Simon J.; Fan, Jun; Bessant, Conrad; Hermjakob, Henning; Jones, Andrew R.

2012-01-01

Abstract New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool (http://www.proteosuite.org/?q=other_resources) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology. PMID:22804616

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

NASA Technical Reports Server (NTRS)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Diagnostic performance of semi-quantitative and quantitative stress CMR perfusion analysis: a meta-analysis.

PubMed

van Dijk, R; van Assen, M; Vliegenthart, R; de Bock, G H; van der Harst, P; Oudkerk, M

2017-11-27

Stress cardiovascular magnetic resonance (CMR) perfusion imaging is a promising modality for the evaluation of coronary artery disease (CAD) due to high spatial resolution and absence of radiation. Semi-quantitative and quantitative analysis of CMR perfusion are based on signal-intensity curves produced during the first-pass of gadolinium contrast. Multiple semi-quantitative and quantitative parameters have been introduced. Diagnostic performance of these parameters varies extensively among studies and standardized protocols are lacking. This study aims to determine the diagnostic accuracy of semi- quantitative and quantitative CMR perfusion parameters, compared to multiple reference standards. Pubmed, WebOfScience, and Embase were systematically searched using predefined criteria (3272 articles). A check for duplicates was performed (1967 articles). Eligibility and relevance of the articles was determined by two reviewers using pre-defined criteria. The primary data extraction was performed independently by two researchers with the use of a predefined template. Differences in extracted data were resolved by discussion between the two researchers. The quality of the included studies was assessed using the 'Quality Assessment of Diagnostic Accuracy Studies Tool' (QUADAS-2). True positives, false positives, true negatives, and false negatives were subtracted/calculated from the articles. The principal summary measures used to assess diagnostic accuracy were sensitivity, specificity, andarea under the receiver operating curve (AUC). Data was pooled according to analysis territory, reference standard and perfusion parameter. Twenty-two articles were eligible based on the predefined study eligibility criteria. The pooled diagnostic accuracy for segment-, territory- and patient-based analyses showed good diagnostic performance with sensitivity of 0.88, 0.82, and 0.83, specificity of 0.72, 0.83, and 0.76 and AUC of 0.90, 0.84, and 0.87, respectively. In per territory analysis our results show similar diagnostic accuracy comparing anatomical (AUC 0.86(0.83-0.89)) and functional reference standards (AUC 0.88(0.84-0.90)). Only the per territory analysis sensitivity did not show significant heterogeneity. None of the groups showed signs of publication bias. The clinical value of semi-quantitative and quantitative CMR perfusion analysis remains uncertain due to extensive inter-study heterogeneity and large differences in CMR perfusion acquisition protocols, reference standards, and methods of assessment of myocardial perfusion parameters. For wide spread implementation, standardization of CMR perfusion techniques is essential. CRD42016040176 .

Quantification of Microbial Phenotypes

PubMed Central

Martínez, Verónica S.; Krömer, Jens O.

2016-01-01

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis. PMID:27941694

Evaluating Inquiry-Based Learning as a Means to Advance Individual Student Achievement

ERIC Educational Resources Information Center

Ziemer, Cherilyn G.

2013-01-01

Although inquiry-based learning has been debated throughout the greater educational community and demonstrated with some effect in modern classrooms, little quantitative analysis has been performed to empirically validate sustained benefits. This quantitative study focused on whether inquiry-based pedagogy actually brought about sustained and…

A Quantitative Analysis of the Extrinsic and Intrinsic Turnover Factors of Relational Database Support Professionals

ERIC Educational Resources Information Center

Takusi, Gabriel Samuto

2010-01-01

This quantitative analysis explored the intrinsic and extrinsic turnover factors of relational database support specialists. Two hundred and nine relational database support specialists were surveyed for this research. The research was conducted based on Hackman and Oldham's (1980) Job Diagnostic Survey. Regression analysis and a univariate ANOVA…

Analysis of airborne MAIS imaging spectrometric data for mineral exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Jinnian; Zheng Lanfen; Tong Qingxi

1996-11-01

The high spectral resolution imaging spectrometric system made quantitative analysis and mapping of surface composition possible. The key issue will be the quantitative approach for analysis of surface parameters for imaging spectrometer data. This paper describes the methods and the stages of quantitative analysis. (1) Extracting surface reflectance from imaging spectrometer image. Lab. and inflight field measurements are conducted for calibration of imaging spectrometer data, and the atmospheric correction has also been used to obtain ground reflectance by using empirical line method and radiation transfer modeling. (2) Determining quantitative relationship between absorption band parameters from the imaging spectrometer data andmore » chemical composition of minerals. (3) Spectral comparison between the spectra of spectral library and the spectra derived from the imagery. The wavelet analysis-based spectrum-matching techniques for quantitative analysis of imaging spectrometer data has beer, developed. Airborne MAIS imaging spectrometer data were used for analysis and the analysis results have been applied to the mineral and petroleum exploration in Tarim Basin area china. 8 refs., 8 figs.« less

Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.

Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

PubMed

Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

2008-09-01

Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

Retinal status analysis method based on feature extraction and quantitative grading in OCT images.

PubMed

Fu, Dongmei; Tong, Hejun; Zheng, Shuang; Luo, Ling; Gao, Fulin; Minar, Jiri

2016-07-22

Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis.

Misconceived Relationships between Logical Positivism and Quantitative Research: An Analysis in the Framework of Ian Hacking.

ERIC Educational Resources Information Center

Yu, Chong Ho

Although quantitative research methodology is widely applied by psychological researchers, there is a common misconception that quantitative research is based on logical positivism. This paper examines the relationship between quantitative research and eight major notions of logical positivism: (1) verification; (2) pro-observation; (3)…

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Quantitative probe of the transition metal redox in battery electrodes through soft x-ray absorption spectroscopy

NASA Astrophysics Data System (ADS)

Li, Qinghao; Qiao, Ruimin; Wray, L. Andrew; Chen, Jun; Zhuo, Zengqing; Chen, Yanxue; Yan, Shishen; Pan, Feng; Hussain, Zahid; Yang, Wanli

2016-10-01

Most battery positive electrodes operate with a 3d transition-metal (TM) reaction centre. A direct and quantitative probe of the TM states upon electrochemical cycling is valuable for understanding the detailed cycling mechanism and charge diffusion in the electrodes, which is related with many practical parameters of a battery. This review includes a comprehensive summary of our recent demonstrations of five different types of quantitative analysis of the TM states in battery electrodes based on soft x-ray absorption spectroscopy and multiplet calculations. In LiFePO4, a system of a well-known two-phase transformation type, the TM redox could be strictly determined through a simple linear combination of the two end-members. In Mn-based compounds, the Mn states could also be quantitatively evaluated, but a set of reference spectra with all the three possible Mn valences needs to be deliberately selected and considered in the fitting. Although the fluorescence signals suffer the self-absorption distortion, the multiplet calculations could consider the distortion effect, which allows a quantitative determination of the overall Ni oxidation state in the bulk. With the aid of multiplet calculations, one could also achieve a quasi-quantitative analysis of the Co redox evolution in LiCoO2 based on the energy position of the spectroscopic peak. The benefit of multiplet calculations is more important for studying electrode materials with TMs of mixed spin states, as exemplified by the quantitative analysis of the mixed spin Na2-x Fe2(CN)6 system. At the end, we showcase that such quantitative analysis could provide valuable information for optimizing the electrochemical performance of Na0.44MnO2 electrodes for Na-ion batteries. The methodology summarized in this review could be extended to other energy application systems with TM redox centre for detailed analysis, for example, fuel cell and catalytic materials.

Statistical design of quantitative mass spectrometry-based proteomic experiments.

PubMed

Oberg, Ann L; Vitek, Olga

2009-05-01

We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis.

PubMed

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L; Hwang, Jae Youn

2016-12-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis.

[Quality evaluation of rhubarb dispensing granules based on multi-component simultaneous quantitative analysis and bioassay].

PubMed

Tan, Peng; Zhang, Hai-Zhu; Zhang, Ding-Kun; Wu, Shan-Na; Niu, Ming; Wang, Jia-Bo; Xiao, Xiao-He

2017-07-01

This study attempts to evaluate the quality of Chinese formula granules by combined use of multi-component simultaneous quantitative analysis and bioassay. The rhubarb dispensing granules were used as the model drug for demonstrative study. The ultra-high performance liquid chromatography (UPLC) method was adopted for simultaneously quantitative determination of the 10 anthraquinone derivatives (such as aloe emodin-8-O-β-D-glucoside) in rhubarb dispensing granules; purgative biopotency of different batches of rhubarb dispensing granules was determined based on compound diphenoxylate tablets-induced mouse constipation model; blood activating biopotency of different batches of rhubarb dispensing granules was determined based on in vitro rat antiplatelet aggregation model; SPSS 22.0 statistical software was used for correlation analysis between 10 anthraquinone derivatives and purgative biopotency, blood activating biopotency. The results of multi-components simultaneous quantitative analysisshowed that there was a great difference in chemical characterizationand certain differences inpurgative biopotency and blood activating biopotency among 10 batches of rhubarb dispensing granules. The correlation analysis showed that the intensity of purgative biopotency was significantly correlated with the content of conjugated anthraquinone glycosides (P<0.01), and the intensity of blood activating biopotency was significantly correlated with the content of free anthraquinone (P<0.01). In summary, the combined use of multi-component simultaneous quantitative analysis and bioassay can achieve objective quantification and more comprehensive reflection on overall quality difference among different batches of rhubarb dispensing granules. Copyright© by the Chinese Pharmaceutical Association.

Multi-frequency local wavenumber analysis and ply correlation of delamination damage.

PubMed

Juarez, Peter D; Leckey, Cara A C

2015-09-01

Wavenumber domain analysis through use of scanning laser Doppler vibrometry has been shown to be effective for non-contact inspection of damage in composites. Qualitative and semi-quantitative local wavenumber analysis of realistic delamination damage and quantitative analysis of idealized damage scenarios (Teflon inserts) have been performed previously in the literature. This paper presents a new methodology based on multi-frequency local wavenumber analysis for quantitative assessment of multi-ply delamination damage in carbon fiber reinforced polymer (CFRP) composite specimens. The methodology is presented and applied to a real world damage scenario (impact damage in an aerospace CFRP composite). The methodology yields delamination size and also correlates local wavenumber results from multiple excitation frequencies to theoretical dispersion curves in order to robustly determine the delamination ply depth. Results from the wavenumber based technique are validated against a traditional nondestructive evaluation method. Published by Elsevier B.V.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Quantitative analysis of crystalline pharmaceuticals in powders and tablets by a pattern-fitting procedure using X-ray powder diffraction data.

PubMed

Yamamura, S; Momose, Y

2001-01-16

A pattern-fitting procedure for quantitative analysis of crystalline pharmaceuticals in solid dosage forms using X-ray powder diffraction data is described. This method is based on a procedure for pattern-fitting in crystal structure refinement, and observed X-ray scattering intensities were fitted to analytical expressions including some fitting parameters, i.e. scale factor, peak positions, peak widths and degree of preferred orientation of the crystallites. All fitting parameters were optimized by the non-linear least-squares procedure. Then the weight fraction of each component was determined from the optimized scale factors. In the present study, well-crystallized binary systems, zinc oxide-zinc sulfide (ZnO-ZnS) and salicylic acid-benzoic acid (SA-BA), were used as the samples. In analysis of the ZnO-ZnS system, the weight fraction of ZnO or ZnS could be determined quantitatively in the range of 5-95% in the case of both powders and tablets. In analysis of the SA-BA systems, the weight fraction of SA or BA could be determined quantitatively in the range of 20-80% in the case of both powders and tablets. Quantitative analysis applying this pattern-fitting procedure showed better reproducibility than other X-ray methods based on the linear or integral intensities of particular diffraction peaks. Analysis using this pattern-fitting procedure also has the advantage that the preferred orientation of the crystallites in solid dosage forms can be also determined in the course of quantitative analysis.

Optimized protocol for quantitative multiple reaction monitoring-based proteomic analysis of formalin-fixed, paraffin embedded tissues

PubMed Central

Kennedy, Jacob J.; Whiteaker, Jeffrey R.; Schoenherr, Regine M.; Yan, Ping; Allison, Kimberly; Shipley, Melissa; Lerch, Melissa; Hoofnagle, Andrew N.; Baird, Geoffrey Stuart; Paulovich, Amanda G.

2016-01-01

Despite a clinical, economic, and regulatory imperative to develop companion diagnostics, precious few new biomarkers have been successfully translated into clinical use, due in part to inadequate protein assay technologies to support large-scale testing of hundreds of candidate biomarkers in formalin-fixed paraffin embedded (FFPE) tissues. While the feasibility of using targeted, multiple reaction monitoring-mass spectrometry (MRM-MS) for quantitative analyses of FFPE tissues has been demonstrated, protocols have not been systematically optimized for robust quantification across a large number of analytes, nor has the performance of peptide immuno-MRM been evaluated. To address this gap, we used a test battery approach coupled to MRM-MS with the addition of stable isotope labeled standard peptides (targeting 512 analytes) to quantitatively evaluate the performance of three extraction protocols in combination with three trypsin digestion protocols (i.e. 9 processes). A process based on RapiGest buffer extraction and urea-based digestion was identified to enable similar quantitation results from FFPE and frozen tissues. Using the optimized protocols for MRM-based analysis of FFPE tissues, median precision was 11.4% (across 249 analytes). There was excellent correlation between measurements made on matched FFPE and frozen tissues, both for direct MRM analysis (R2 = 0.94) and immuno-MRM (R2 = 0.89). The optimized process enables highly reproducible, multiplex, standardizable, quantitative MRM in archival tissue specimens. PMID:27462933

Coupling Reagent for UV/vis Absorbing Azobenzene-Based Quantitative Analysis of the Extent of Functional Group Immobilization on Silica.

PubMed

Choi, Ra-Young; Lee, Chang-Hee; Jun, Chul-Ho

2018-05-18

A methallylsilane coupling reagent, containing both a N-hydroxysuccinimidyl(NHS)-ester group and a UV/vis absorbing azobenzene linker undergoes acid-catalyzed immobilization on silica. Analysis of the UV/vis absorption band associated with the azobenzene group in the adduct enables facile quantitative determination of the extent of loading of the NHS groups. Reaction of NHS-groups on the silica surface with amine groups of GOx and rhodamine can be employed to generate enzyme or dye-immobilized silica for quantitative analysis.

The Adoption Process of Ricefield-Based Fish Seed Production in Northwest Bangladesh: An Understanding through Quantitative and Qualitative Investigation

ERIC Educational Resources Information Center

Haque, Mohammad Mahfujul; Little, David C.; Barman, Benoy K.; Wahab, Md. Abdul

2010-01-01

Purpose: The purpose of the study was to understand the adoption process of ricefield based fish seed production (RBFSP) that has been developed, promoted and established in Northwest Bangladesh. Design/Methodology/Approach: Quantitative investigation based on regression analysis and qualitative investigation using semi-structured interview were…

Project-Based Learning in Undergraduate Environmental Chemistry Laboratory: Using EPA Methods to Guide Student Method Development for Pesticide Quantitation

ERIC Educational Resources Information Center

Davis, Eric J.; Pauls, Steve; Dick, Jonathan

2017-01-01

Presented is a project-based learning (PBL) laboratory approach for an upper-division environmental chemistry or quantitative analysis course. In this work, a combined laboratory class of 11 environmental chemistry students developed a method based on published EPA methods for the extraction of dichlorodiphenyltrichloroethane (DDT) and its…

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

Undergraduate Students' Quantitative Reasoning in Economic Contexts

ERIC Educational Resources Information Center

Mkhatshwa, Thembinkosi Peter; Doerr, Helen M.

2018-01-01

Contributing to a growing body of research on undergraduate students' quantitative reasoning, the study reported in this article used task-based interviews to investigate business calculus students' quantitative reasoning when solving two optimization tasks situated in the context of revenue and profit maximization. Analysis of verbal responses…

A quantitative analysis of the F18 flight control system

NASA Technical Reports Server (NTRS)

Doyle, Stacy A.; Dugan, Joanne B.; Patterson-Hine, Ann

1993-01-01

This paper presents an informal quantitative analysis of the F18 flight control system (FCS). The analysis technique combines a coverage model with a fault tree model. To demonstrate the method's extensive capabilities, we replace the fault tree with a digraph model of the F18 FCS, the only model available to us. The substitution shows that while digraphs have primarily been used for qualitative analysis, they can also be used for quantitative analysis. Based on our assumptions and the particular failure rates assigned to the F18 FCS components, we show that coverage does have a significant effect on the system's reliability and thus it is important to include coverage in the reliability analysis.

Toward best practices in data processing and analysis for intact biotherapeutics by MS in quantitative bioanalysis.

PubMed

Kellie, John F; Kehler, Jonathan R; Karlinsey, Molly Z; Summerfield, Scott G

2017-12-01

Typically, quantitation of biotherapeutics from biological matrices by LC-MS is based on a surrogate peptide approach to determine molecule concentration. Recent efforts have focused on quantitation of the intact protein molecules or larger mass subunits of monoclonal antibodies. To date, there has been limited guidance for large or intact protein mass quantitation for quantitative bioanalysis. Intact- and subunit-level analyses of biotherapeutics from biological matrices are performed at 12-25 kDa mass range with quantitation data presented. Linearity, bias and other metrics are presented along with recommendations made on the viability of existing quantitation approaches. This communication is intended to start a discussion around intact protein data analysis and processing, recognizing that other published contributions will be required.

Distance-based microfluidic quantitative detection methods for point-of-care testing.

PubMed

Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

2016-04-07

Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

Distinguishing nanomaterial particles from background airborne particulate matter for quantitative exposure assessment

NASA Astrophysics Data System (ADS)

Ono-Ogasawara, Mariko; Serita, Fumio; Takaya, Mitsutoshi

2009-10-01

As the production of engineered nanomaterials quantitatively expands, the chance that workers involved in the manufacturing process will be exposed to nanoparticles also increases. A risk management system is needed for workplaces in the nanomaterial industry based on the precautionary principle. One of the problems in the risk management system is difficulty of exposure assessment. In this article, examples of exposure assessment in nanomaterial industries are reviewed with a focus on distinguishing engineered nanomaterial particles from background nanoparticles in workplace atmosphere. An approach by JNIOSH (Japan National Institute of Occupational Safety and Health) to quantitatively measure exposure to carbonaceous nanomaterials is also introduced. In addition to real-time measurements and qualitative analysis by electron microscopy, quantitative chemical analysis is necessary for quantitatively assessing exposure to nanomaterials. Chemical analysis is suitable for quantitative exposure measurement especially at facilities with high levels of background NPs.

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

PubMed Central

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L.; Hwang, Jae Youn

2016-01-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. PMID:28018743

Examining a Paradigm Shift in Organic Depot-Level Software Maintenance for Army Communications and Electronics Equipment

DTIC Science & Technology

2015-05-30

study used quantitative and qualitative analytical methods in the examination of software versus hardware maintenance trends and forecasts, human and...financial resources at TYAD and SEC, and overall compliance with Title 10 mandates (e.g., 10 USC 2466). Quantitative methods were executed by...Systems (PEO EIS). These methods will provide quantitative-based analysis on which to base and justify trends and gaps, as well as qualitative methods

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

PubMed

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Quantitative 13C NMR characterization of fast pyrolysis oils

DOE PAGES

Happs, Renee M.; Lisa, Kristina; Ferrell, III, Jack R.

2016-10-20

Quantitative 13C NMR analysis of model catalytic fast pyrolysis (CFP) oils following literature procedures showed poor agreement for aromatic hydrocarbons between NMR measured concentrations and actual composition. Furthermore, modifying integration regions based on DEPT analysis for aromatic carbons resulted in better agreement. Solvent effects were also investigated for hydrotreated CFP oil.

Quantitative 13C NMR characterization of fast pyrolysis oils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Happs, Renee M.; Lisa, Kristina; Ferrell, III, Jack R.

Quantitative 13C NMR analysis of model catalytic fast pyrolysis (CFP) oils following literature procedures showed poor agreement for aromatic hydrocarbons between NMR measured concentrations and actual composition. Furthermore, modifying integration regions based on DEPT analysis for aromatic carbons resulted in better agreement. Solvent effects were also investigated for hydrotreated CFP oil.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

Three-dimensional modeling and quantitative analysis of gap junction distributions in cardiac tissue.

PubMed

Lackey, Daniel P; Carruth, Eric D; Lasher, Richard A; Boenisch, Jan; Sachse, Frank B; Hitchcock, Robert W

2011-11-01

Gap junctions play a fundamental role in intercellular communication in cardiac tissue. Various types of heart disease including hypertrophy and ischemia are associated with alterations of the spatial arrangement of gap junctions. Previous studies applied two-dimensional optical and electron-microscopy to visualize gap junction arrangements. In normal cardiomyocytes, gap junctions were primarily found at cell ends, but can be found also in more central regions. In this study, we extended these approaches toward three-dimensional reconstruction of gap junction distributions based on high-resolution scanning confocal microscopy and image processing. We developed methods for quantitative characterization of gap junction distributions based on analysis of intensity profiles along the principal axes of myocytes. The analyses characterized gap junction polarization at cell ends and higher-order statistical image moments of intensity profiles. The methodology was tested in rat ventricular myocardium. Our analysis yielded novel quantitative data on gap junction distributions. In particular, the analysis demonstrated that the distributions exhibit significant variability with respect to polarization, skewness, and kurtosis. We suggest that this methodology provides a quantitative alternative to current approaches based on visual inspection, with applications in particular in characterization of engineered and diseased myocardium. Furthermore, we propose that these data provide improved input for computational modeling of cardiac conduction.

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Quantitative measurements of nanoscale permittivity and conductivity using tuning-fork-based microwave impedance microscopy

NASA Astrophysics Data System (ADS)

Wu, Xiaoyu; Hao, Zhenqi; Wu, Di; Zheng, Lu; Jiang, Zhanzhi; Ganesan, Vishal; Wang, Yayu; Lai, Keji

2018-04-01

We report quantitative measurements of nanoscale permittivity and conductivity using tuning-fork (TF) based microwave impedance microscopy (MIM). The system is operated under the driving amplitude modulation mode, which ensures satisfactory feedback stability on samples with rough surfaces. The demodulated MIM signals on a series of bulk dielectrics are in good agreement with results simulated by finite-element analysis. Using the TF-MIM, we have visualized the evolution of nanoscale conductance on back-gated MoS2 field effect transistors, and the results are consistent with the transport data. Our work suggests that quantitative analysis of mesoscopic electrical properties can be achieved by near-field microwave imaging with small distance modulation.

Quantitative analysis of single-molecule superresolution images

PubMed Central

Coltharp, Carla; Yang, Xinxing; Xiao, Jie

2014-01-01

This review highlights the quantitative capabilities of single-molecule localization-based superresolution imaging methods. In addition to revealing fine structural details, the molecule coordinate lists generated by these methods provide the critical ability to quantify the number, clustering, and colocalization of molecules with 10 – 50 nm resolution. Here we describe typical workflows and precautions for quantitative analysis of single-molecule superresolution images. These guidelines include potential pitfalls and essential control experiments, allowing critical assessment and interpretation of superresolution images. PMID:25179006

Spectrochemical analysis of powdered biological samples using transversely excited atmospheric carbon dioxide laser plasma excitation

NASA Astrophysics Data System (ADS)

Zivkovic, Sanja; Momcilovic, Milos; Staicu, Angela; Mutic, Jelena; Trtica, Milan; Savovic, Jelena

2017-02-01

The aim of this study was to develop a simple laser induced breakdown spectroscopy (LIBS) method for quantitative elemental analysis of powdered biological materials based on laboratory prepared calibration samples. The analysis was done using ungated single pulse LIBS in ambient air at atmospheric pressure. Transversely-Excited Atmospheric pressure (TEA) CO2 laser was used as an energy source for plasma generation on samples. The material used for the analysis was a blue-green alga Spirulina, widely used in food and pharmaceutical industries and also in a few biotechnological applications. To demonstrate the analytical potential of this particular LIBS system the obtained spectra were compared to the spectra obtained using a commercial LIBS system based on pulsed Nd:YAG laser. A single sample of known concentration was used to estimate detection limits for Ba, Ca, Fe, Mg, Mn, Si and Sr and compare detection power of these two LIBS systems. TEA CO2 laser based LIBS was also applied for quantitative analysis of the elements in powder Spirulina samples. Analytical curves for Ba, Fe, Mg, Mn and Sr were constructed using laboratory produced matrix-matched calibration samples. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was used as the reference technique for elemental quantification, and reasonably well agreement between ICP and LIBS data was obtained. Results confirm that, in respect to its sensitivity and precision, TEA CO2 laser based LIBS can be successfully applied for quantitative analysis of macro and micro-elements in algal samples. The fact that nearly all classes of materials can be prepared as powders implies that the proposed method could be easily extended to a quantitative analysis of different kinds of materials, organic, biological or inorganic.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

78 FR 65407 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change To List...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... selling investments for the Portfolio. Investments are selected based on fundamental and quantitative... Equity Portfolio. Investments are selected based on fundamental and quantitative analysis. MFS uses... trust and is registered with the Commission as an open-end management investment company.\\5\\ SSgA Funds...

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

The Quantitative Evaluation of the Clinical and Translational Science Awards (CTSA) Program Based on Science Mapping and Scientometric Analysis

PubMed Central

Zhang, Yin; Wang, Lei

2013-01-01

Abstract The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. PMID:24330689

The quantitative evaluation of the Clinical and Translational Science Awards (CTSA) program based on science mapping and scientometric analysis.

PubMed

Zhang, Yin; Wang, Lei; Diao, Tianxi

2013-12-01

The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. © 2013 Wiley Periodicals, Inc.

Quantitative Analysis of Tissue Samples by Combining iTRAQ Isobaric Labeling with Selected/Multiple Reaction Monitoring (SRM/MRM).

PubMed

Narumi, Ryohei; Tomonaga, Takeshi

2016-01-01

Mass spectrometry-based phosphoproteomics is an indispensible technique used in the discovery and quantification of phosphorylation events on proteins in biological samples. The application of this technique to tissue samples is especially useful for the discovery of biomarkers as well as biological studies. We herein describe the application of a large-scale phosphoproteome analysis and SRM/MRM-based quantitation to develop a strategy for the systematic discovery and validation of biomarkers using tissue samples.

Longitudinal studies of the 18F-FDG kinetics after ipilimumab treatment in metastatic melanoma patients based on dynamic FDG PET/CT.

PubMed

Sachpekidis, Christos; Anwar, Hoda; Winkler, Julia K; Kopp-Schneider, Annette; Larribere, Lionel; Haberkorn, Uwe; Hassel, Jessica C; Dimitrakopoulou-Strauss, Antonia

2018-06-05

Immunotherapy has raised the issue of appropriate treatment response evaluation, due to the unique mechanism of action of the immunotherapeutic agents. Aim of this analysis is to evaluate the potential role of quantitative analysis of 2-deoxy-2-( 18 F)fluoro-D-glucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) data in monitoring of patients with metastatic melanoma undergoing ipilimumab therapy. 25 patients with unresectable metastatic melanoma underwent dynamic PET/CT (dPET/CT) of the thorax and upper abdomen as well as static, whole body PET/CT with 18 F-FDG before the start of ipilimumab treatment (baseline PET/CT), after two cycles of treatment (interim PET/CT) and at the end of treatment after four cycles (late PET/CT). The evaluation of dPET/CT studies was based on semi-quantitative (standardized uptake value, SUV) calculation as well as quantitative analysis, based on two-tissue compartment modeling and a fractal approach. Patients' best clinical response, assessed at a mean of 59 weeks, was used as reference. According to their best clinical response, patients were dichotomized in those demonstrating clinical benefit (CB, n = 16 patients) and those demonstrating no clinical benefit (no-CB, n = 9 patients). No statistically significant differences were observed between CB and no-CB regarding either semi-quantitative or quantitative parameters in all scans. On contrary, the application of the recently introduced PET response evaluation criteria for immunotherapy (PERCIMT) led to a correct classification rate of 84% (21/25 patients). Quantitative analysis of 18 F-FDG PET data does not provide additional information in treatment response evaluation of metastatic melanoma patients receiving ipilimumab. PERCIMT criteria correlated better with clinical response.

The Moment of Learning: Quantitative Analysis of Exemplar Gameplay Supports CyGaMEs Approach to Embedded Assessment

ERIC Educational Resources Information Center

Reese, Debbie Denise; Tabachnick, Barbara G.

2010-01-01

In this paper, the authors summarize a quantitative analysis demonstrating that the CyGaMEs toolset for embedded assessment of learning within instructional games measures growth in conceptual knowledge by quantifying player behavior. CyGaMEs stands for Cyberlearning through GaME-based, Metaphor Enhanced Learning Objects. Some scientists of…

COMPARISON OF ENTEROCOCCUS MEASUREMENTS IN FRESHWATER AT TWO RECREATIONAL BEACHES BY QUANTITATIVE POLYMERASE CHAIN REACTION AND MEMBRANE FILER CULTURE ANALYSIS

EPA Science Inventory

Cell densities of the fecal pollution indicator genus, Enterococcus, were determined by a rapid (2-3 hr) quantitative PCR (QPCR) analysis based method in 100 ml water samples collected from recreational beaches on Lake Michigan and Lake Erie during the summer of 2003. Enumeration...

Simultaneous fingerprint, quantitative analysis and anti-oxidative based screening of components in Rhizoma Smilacis Glabrae using liquid chromatography coupled with Charged Aerosol and Coulometric array Detection.

PubMed

Yang, Guang; Zhao, Xin; Wen, Jun; Zhou, Tingting; Fan, Guorong

2017-04-01

An analytical approach including fingerprint, quantitative analysis and rapid screening of anti-oxidative components was established and successfully applied for the comprehensive quality control of Rhizoma Smilacis Glabrae (RSG), a well-known Traditional Chinese Medicine with the homology of medicine and food. Thirteen components were tentatively identified based on their retention behavior, UV absorption and MS fragmentation patterns. Chemometric analysis based on coulmetric array data was performed to evaluate the similarity and variation between fifteen batches. Eight discriminating components were quantified using single-compound calibration. The unit responses of those components in coulmetric array detection were calculated and compared with those of several compounds reported to possess antioxidant activity, and four of them were tentatively identified as main contributors to the total anti-oxidative activity. The main advantage of the proposed approach was that it realized simultaneous fingerprint, quantitative analysis and screening of anti-oxidative components, providing comprehensive information for quality assessment of RSG. Copyright © 2017 Elsevier B.V. All rights reserved.

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Potential of Multivariate Analysis in Assessing Students' Attitude to Curriculum Subjects

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…

Comprehensive Quantitative Analysis on Privacy Leak Behavior

PubMed Central

Fan, Lejun; Wang, Yuanzhuo; Jin, Xiaolong; Li, Jingyuan; Cheng, Xueqi; Jin, Shuyuan

2013-01-01

Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security. However, existing approaches can only qualitatively analyze privacy leak behavior of software applications. No quantitative approach, to the best of our knowledge, has been developed in the open literature. To fill this gap, in this paper we propose for the first time four quantitative metrics, namely, possibility, severity, crypticity, and manipulability, for privacy leak behavior analysis based on Privacy Petri Net (PPN). In order to compare the privacy leak behavior among different software, we further propose a comprehensive metric, namely, overall leak degree, based on these four metrics. Finally, we validate the effectiveness of the proposed approach using real-world software applications. The experimental results demonstrate that our approach can quantitatively analyze the privacy leak behaviors of various software types and reveal their characteristics from different aspects. PMID:24066046

Comprehensive quantitative analysis on privacy leak behavior.

PubMed

Fan, Lejun; Wang, Yuanzhuo; Jin, Xiaolong; Li, Jingyuan; Cheng, Xueqi; Jin, Shuyuan

2013-01-01

Privacy information is prone to be leaked by illegal software providers with various motivations. Privacy leak behavior has thus become an important research issue of cyber security. However, existing approaches can only qualitatively analyze privacy leak behavior of software applications. No quantitative approach, to the best of our knowledge, has been developed in the open literature. To fill this gap, in this paper we propose for the first time four quantitative metrics, namely, possibility, severity, crypticity, and manipulability, for privacy leak behavior analysis based on Privacy Petri Net (PPN). In order to compare the privacy leak behavior among different software, we further propose a comprehensive metric, namely, overall leak degree, based on these four metrics. Finally, we validate the effectiveness of the proposed approach using real-world software applications. The experimental results demonstrate that our approach can quantitatively analyze the privacy leak behaviors of various software types and reveal their characteristics from different aspects.

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics

PubMed Central

Lavallée-Adam, Mathieu

2017-01-01

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. PMID:27010334

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Comparing Online with Brick and Mortar Course Learning Outcomes: An Analysis of Quantitative Methods Curriculum in Public Administration

ERIC Educational Resources Information Center

Harris, Ronald A.; Nikitenko, Gleb O.

2014-01-01

Teaching graduate students in an intensive adult-learning format presents a special challenge for quantitative analytical competencies. Students often lack necessary background, skills and motivation to deal with quantitative-skill-based course work. This study compares learning outcomes for graduate students enrolled in three course sections…

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi-ingredients quantitative analysis.

PubMed

Xu, Ning; Zhou, Guofu; Li, Xiaojuan; Lu, Heng; Meng, Fanyun; Zhai, Huaqiang

2017-05-01

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi-ingredient quantitative analysis. Nineteen batches of Epimedium, collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality. Copyright © 2016 John Wiley & Sons, Ltd.

[Reconstituting evaluation methods based on both qualitative and quantitative paradigms].

PubMed

Miyata, Hiroaki; Okubo, Suguru; Yoshie, Satoru; Kai, Ichiro

2011-01-01

Debate about the relationship between quantitative and qualitative paradigms is often muddled and confusing and the clutter of terms and arguments has resulted in the concepts becoming obscure and unrecognizable. In this study we conducted content analysis regarding evaluation methods of qualitative healthcare research. We extracted descriptions on four types of evaluation paradigm (validity/credibility, reliability/credibility, objectivity/confirmability, and generalizability/transferability), and classified them into subcategories. In quantitative research, there has been many evaluation methods based on qualitative paradigms, and vice versa. Thus, it might not be useful to consider evaluation methods of qualitative paradigm are isolated from those of quantitative methods. Choosing practical evaluation methods based on the situation and prior conditions of each study is an important approach for researchers.

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

Quantitative measurements of nanoscale permittivity and conductivity using tuning-fork-based microwave impedance microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Xiaoyu; Hao, Zhenqi; Wu, Di

Here, we report quantitative measurements of nanoscale permittivity and conductivity using tuning-fork (TF) based microwave impedance microscopy (MIM). The system is operated under the driving amplitude modulation mode, which ensures satisfactory feedback stability on samples with rough surfaces. The demodulated MIM signals on a series of bulk dielectrics are in good agreement with results simulated by finite-element analysis. Using the TF-MIM, we have visualized the evolution of nanoscale conductance on back-gated MoS 2 field effect transistors, and the results are consistent with the transport data. Our work suggests that quantitative analysis of mesoscopic electrical properties can be achieved by near-fieldmore » microwave imaging with small distance modulation.« less

Quantitative measurements of nanoscale permittivity and conductivity using tuning-fork-based microwave impedance microscopy

DOE PAGES

Wu, Xiaoyu; Hao, Zhenqi; Wu, Di; ...

2018-04-01

Here, we report quantitative measurements of nanoscale permittivity and conductivity using tuning-fork (TF) based microwave impedance microscopy (MIM). The system is operated under the driving amplitude modulation mode, which ensures satisfactory feedback stability on samples with rough surfaces. The demodulated MIM signals on a series of bulk dielectrics are in good agreement with results simulated by finite-element analysis. Using the TF-MIM, we have visualized the evolution of nanoscale conductance on back-gated MoS 2 field effect transistors, and the results are consistent with the transport data. Our work suggests that quantitative analysis of mesoscopic electrical properties can be achieved by near-fieldmore » microwave imaging with small distance modulation.« less

Looking at the Brains behind Figurative Language--A Quantitative Meta-Analysis of Neuroimaging Studies on Metaphor, Idiom, and Irony Processing

ERIC Educational Resources Information Center

Bohrn, Isabel C.; Altmann, Ulrike; Jacobs, Arthur M.

2012-01-01

A quantitative, coordinate-based meta-analysis combined data from 354 participants across 22 fMRI studies and one positron emission tomography (PET) study to identify the differences in neural correlates of figurative and literal language processing, and to investigate the role of the right hemisphere (RH) in figurative language processing.…

Clinical applications of a quantitative analysis of regional lift ventricular wall motion

NASA Technical Reports Server (NTRS)

Leighton, R. F.; Rich, J. M.; Pollack, M. E.; Altieri, P. I.

1975-01-01

Observations were summarized which may have clinical application. These were obtained from a quantitative analysis of wall motion that was used to detect both hypokinesis and tardokinesis in left ventricular cineangiograms. The method was based on statistical comparisons with normal values for regional wall motion derived from the cineangiograms of patients who were found not to have heart disease.

Multiplex, quantitative cellular analysis in large tissue volumes with clearing-enhanced 3D microscopy (Ce3D)

PubMed Central

Li, Weizhe; Germain, Ronald N.

2017-01-01

Organ homeostasis, cellular differentiation, signal relay, and in situ function all depend on the spatial organization of cells in complex tissues. For this reason, comprehensive, high-resolution mapping of cell positioning, phenotypic identity, and functional state in the context of macroscale tissue structure is critical to a deeper understanding of diverse biological processes. Here we report an easy to use method, clearing-enhanced 3D (Ce3D), which generates excellent tissue transparency for most organs, preserves cellular morphology and protein fluorescence, and is robustly compatible with antibody-based immunolabeling. This enhanced signal quality and capacity for extensive probe multiplexing permits quantitative analysis of distinct, highly intermixed cell populations in intact Ce3D-treated tissues via 3D histo-cytometry. We use this technology to demonstrate large-volume, high-resolution microscopy of diverse cell types in lymphoid and nonlymphoid organs, as well as to perform quantitative analysis of the composition and tissue distribution of multiple cell populations in lymphoid tissues. Combined with histo-cytometry, Ce3D provides a comprehensive strategy for volumetric quantitative imaging and analysis that bridges the gap between conventional section imaging and disassociation-based techniques. PMID:28808033

An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

NASA Astrophysics Data System (ADS)

Kim, Yongmin; Alexander, Thomas

1986-06-01

In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

A Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS) Quantitative Analysis Method Based on the Auto-Selection of an Internal Reference Line and Optimized Estimation of Plasma Temperature.

PubMed

Yang, Jianhong; Li, Xiaomeng; Xu, Jinwu; Ma, Xianghong

2018-01-01

The quantitative analysis accuracy of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is severely affected by the self-absorption effect and estimation of plasma temperature. Herein, a CF-LIBS quantitative analysis method based on the auto-selection of internal reference line and the optimized estimation of plasma temperature is proposed. The internal reference line of each species is automatically selected from analytical lines by a programmable procedure through easily accessible parameters. Furthermore, the self-absorption effect of the internal reference line is considered during the correction procedure. To improve the analysis accuracy of CF-LIBS, the particle swarm optimization (PSO) algorithm is introduced to estimate the plasma temperature based on the calculation results from the Boltzmann plot. Thereafter, the species concentrations of a sample can be calculated according to the classical CF-LIBS method. A total of 15 certified alloy steel standard samples of known compositions and elemental weight percentages were used in the experiment. Using the proposed method, the average relative errors of Cr, Ni, and Fe calculated concentrations were 4.40%, 6.81%, and 2.29%, respectively. The quantitative results demonstrated an improvement compared with the classical CF-LIBS method and the promising potential of in situ and real-time application.

Quantification of the methylation status of the PWS/AS imprinted region: comparison of two approaches based on bisulfite sequencing and methylation-sensitive MLPA.

PubMed

Dikow, Nicola; Nygren, Anders Oh; Schouten, Jan P; Hartmann, Carolin; Krämer, Nikola; Janssen, Bart; Zschocke, Johannes

2007-06-01

Standard methods used for genomic methylation analysis allow the detection of complete absence of either methylated or non-methylated alleles but are usually unable to detect changes in the proportion of methylated and unmethylated alleles. We compare two methods for quantitative methylation analysis, using the chromosome 15q11-q13 imprinted region as model. Absence of the non-methylated paternal allele in this region leads to Prader-Willi syndrome (PWS) whilst absence of the methylated maternal allele results in Angelman syndrome (AS). A proportion of AS is caused by mosaic imprinting defects which may be missed with standard methods and require quantitative analysis for their detection. Sequence-based quantitative methylation analysis (SeQMA) involves quantitative comparison of peaks generated through sequencing reactions after bisulfite treatment. It is simple, cost-effective and can be easily established for a large number of genes. However, our results support previous suggestions that methods based on bisulfite treatment may be problematic for exact quantification of methylation status. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) avoids bisulfite treatment. It detects changes in both CpG methylation as well as copy number of up to 40 chromosomal sequences in one simple reaction. Once established in a laboratory setting, the method is more accurate, reliable and less time consuming.

Preliminary research on eddy current bobbin quantitative test for heat exchange tube in nuclear power plant

NASA Astrophysics Data System (ADS)

Qi, Pan; Shao, Wenbin; Liao, Shusheng

2016-02-01

For quantitative defects detection research on heat transfer tube in nuclear power plants (NPP), two parts of work are carried out based on the crack as the main research objects. (1) Production optimization of calibration tube. Firstly, ASME, RSEM and homemade crack calibration tubes are applied to quantitatively analyze the defects depth on other designed crack test tubes, and then the judgment with quantitative results under crack calibration tube with more accuracy is given. Base on that, weight analysis of influence factors for crack depth quantitative test such as crack orientation, length, volume and so on can be undertaken, which will optimize manufacture technology of calibration tubes. (2) Quantitative optimization of crack depth. Neural network model with multi-calibration curve adopted to optimize natural crack test depth generated in in-service tubes shows preliminary ability to improve quantitative accuracy.

Acoustics based assessment of respiratory diseases using GMM classification.

PubMed

Mayorga, P; Druzgalski, C; Morelos, R L; Gonzalez, O H; Vidales, J

2010-01-01

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595

Using enterprise architecture to analyse how organisational structure impact motivation and learning

NASA Astrophysics Data System (ADS)

Närman, Pia; Johnson, Pontus; Gingnell, Liv

2016-06-01

When technology, environment, or strategies change, organisations need to adjust their structures accordingly. These structural changes do not always enhance the organisational performance as intended partly because organisational developers do not understand the consequences of structural changes in performance. This article presents a model-based analysis framework for quantitative analysis of the effect of organisational structure on organisation performance in terms of employee motivation and learning. The model is based on Mintzberg's work on organisational structure. The quantitative analysis is formalised using the Object Constraint Language (OCL) and the Unified Modelling Language (UML) and implemented in an enterprise architecture tool.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

PubMed

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

Extraction efficiency and implications for absolute quantitation of propranolol in mouse brain, liver and kidney thin tissue sections using droplet-based liquid microjunction surface sampling-HPLC ESI-MS/MS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kertesz, Vilmos; Weiskittel, Taylor M.; Vavek, Marissa

Currently, absolute quantitation aspects of droplet-based surface sampling for thin tissue analysis using a fully automated autosampler/HPLC-ESI-MS/MS system are not fully evaluated. Knowledge of extraction efficiency and its reproducibility is required to judge the potential of the method for absolute quantitation of analytes from thin tissue sections. Methods: Adjacent thin tissue sections of propranolol dosed mouse brain (10- μm-thick), kidney (10- μm-thick) and liver (8-, 10-, 16- and 24- μm-thick) were obtained. Absolute concentration of propranolol was determined in tissue punches from serial sections using standard bulk tissue extraction protocols and subsequent HPLC separations and tandem mass spectrometric analysis. Thesemore » values were used to determine propranolol extraction efficiency from the tissues with the droplet-based surface sampling approach. Results: Extraction efficiency of propranolol using 10- μm-thick brain, kidney and liver thin tissues using droplet-based surface sampling varied between ~45-63%. Extraction efficiency decreased from ~65% to ~36% with liver thickness increasing from 8 μm to 24 μm. Randomly selecting half of the samples as standards, precision and accuracy of propranolol concentrations obtained for the other half of samples as quality control metrics were determined. Resulting precision ( ±15%) and accuracy ( ±3%) values, respectively, were within acceptable limits. In conclusion, comparative quantitation of adjacent mouse thin tissue sections of different organs and of various thicknesses by droplet-based surface sampling and by bulk extraction of tissue punches showed that extraction efficiency was incomplete using the former method, and that it depended on the organ and tissue thickness. However, once extraction efficiency was determined and applied, the droplet-based approach provided the required quantitation accuracy and precision for assay validations. Furthermore, this means that once the extraction efficiency was calibrated for a given tissue type and drug, the droplet-based approach provides a non-labor intensive and high-throughput means to acquire spatially resolved quantitative analysis of multiple samples of the same type.« less

Extraction efficiency and implications for absolute quantitation of propranolol in mouse brain, liver and kidney thin tissue sections using droplet-based liquid microjunction surface sampling-HPLC ESI-MS/MS

DOE PAGES

Kertesz, Vilmos; Weiskittel, Taylor M.; Vavek, Marissa; ...

2016-06-22

Currently, absolute quantitation aspects of droplet-based surface sampling for thin tissue analysis using a fully automated autosampler/HPLC-ESI-MS/MS system are not fully evaluated. Knowledge of extraction efficiency and its reproducibility is required to judge the potential of the method for absolute quantitation of analytes from thin tissue sections. Methods: Adjacent thin tissue sections of propranolol dosed mouse brain (10- μm-thick), kidney (10- μm-thick) and liver (8-, 10-, 16- and 24- μm-thick) were obtained. Absolute concentration of propranolol was determined in tissue punches from serial sections using standard bulk tissue extraction protocols and subsequent HPLC separations and tandem mass spectrometric analysis. Thesemore » values were used to determine propranolol extraction efficiency from the tissues with the droplet-based surface sampling approach. Results: Extraction efficiency of propranolol using 10- μm-thick brain, kidney and liver thin tissues using droplet-based surface sampling varied between ~45-63%. Extraction efficiency decreased from ~65% to ~36% with liver thickness increasing from 8 μm to 24 μm. Randomly selecting half of the samples as standards, precision and accuracy of propranolol concentrations obtained for the other half of samples as quality control metrics were determined. Resulting precision ( ±15%) and accuracy ( ±3%) values, respectively, were within acceptable limits. In conclusion, comparative quantitation of adjacent mouse thin tissue sections of different organs and of various thicknesses by droplet-based surface sampling and by bulk extraction of tissue punches showed that extraction efficiency was incomplete using the former method, and that it depended on the organ and tissue thickness. However, once extraction efficiency was determined and applied, the droplet-based approach provided the required quantitation accuracy and precision for assay validations. Furthermore, this means that once the extraction efficiency was calibrated for a given tissue type and drug, the droplet-based approach provides a non-labor intensive and high-throughput means to acquire spatially resolved quantitative analysis of multiple samples of the same type.« less

Development of duplex SYBR Green I-based real-time quantitative reverse-transcription PCR for detection and discrimination of grapevine viruses

USDA-ARS?s Scientific Manuscript database

A SYBR® Green-based real-time quantitative reverse transcription PCR (qRT-PCR) assay in combination with melt curve analysis (MCA) was developed for the detection of nine grapevine viruses. The detection limits for singleplex qRT-PCR for all nine grapevine viruses were determined to be in the range ...

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Quantitative mass spectrometry: an overview

NASA Astrophysics Data System (ADS)

Urban, Pawel L.

2016-10-01

Mass spectrometry (MS) is a mainstream chemical analysis technique in the twenty-first century. It has contributed to numerous discoveries in chemistry, physics and biochemistry. Hundreds of research laboratories scattered all over the world use MS every day to investigate fundamental phenomena on the molecular level. MS is also widely used by industry-especially in drug discovery, quality control and food safety protocols. In some cases, mass spectrometers are indispensable and irreplaceable by any other metrological tools. The uniqueness of MS is due to the fact that it enables direct identification of molecules based on the mass-to-charge ratios as well as fragmentation patterns. Thus, for several decades now, MS has been used in qualitative chemical analysis. To address the pressing need for quantitative molecular measurements, a number of laboratories focused on technological and methodological improvements that could render MS a fully quantitative metrological platform. In this theme issue, the experts working for some of those laboratories share their knowledge and enthusiasm about quantitative MS. I hope this theme issue will benefit readers, and foster fundamental and applied research based on quantitative MS measurements. This article is part of the themed issue 'Quantitative mass spectrometry'.

Global scaling for semi-quantitative analysis in FP-CIT SPECT.

PubMed

Kupitz, D; Apostolova, I; Lange, C; Ulrich, G; Amthauer, H; Brenner, W; Buchert, R

2014-01-01

Semi-quantitative characterization of dopamine transporter availability from single photon emission computed tomography (SPECT) with 123I-ioflupane (FP-CIT) is based on uptake ratios relative to a reference region. The aim of this study was to evaluate the whole brain as reference region for semi-quantitative analysis of FP-CIT SPECT. The rationale was that this might reduce statistical noise associated with the estimation of non-displaceable FP-CIT uptake. 150 FP-CIT SPECTs were categorized as neurodegenerative or non-neurodegenerative by an expert. Semi-quantitative analysis of specific binding ratios (SBR) was performed with a custom-made tool based on the Statistical Parametric Mapping software package using predefined regions of interest (ROIs) in the anatomical space of the Montreal Neurological Institute. The following reference regions were compared: predefined ROIs for frontal and occipital lobe and whole brain (without striata, thalamus and brainstem). Tracer uptake in the reference region was characterized by the mean, median or 75th percentile of its voxel intensities. The area (AUC) under the receiver operating characteristic curve was used as performance measure. The highest AUC of 0.973 was achieved by the SBR of the putamen with the 75th percentile in the whole brain as reference. The lowest AUC for the putamen SBR of 0.937 was obtained with the mean in the frontal lobe as reference. We recommend the 75th percentile in the whole brain as reference for semi-quantitative analysis in FP-CIT SPECT. This combination provided the best agreement of the semi-quantitative analysis with visual evaluation of the SPECT images by an expert and, therefore, is appropriate to support less experienced physicians.

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software.

PubMed

Moon, Andres; Smith, Geoffrey H; Kong, Jun; Rogers, Thomas E; Ellis, Carla L; Farris, Alton B Brad

2018-02-01

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm 2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling "maxima" criteria for CD3 expression (custom CD3+ cells/mm 2 ). Based on visual inspections of "markup" images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide "flow cytometry" that can facilitate additional diagnostic accuracy in tissue-based assessments.

Inter-rater reliability of motor unit number estimates and quantitative motor unit analysis in the tibialis anterior muscle.

PubMed

Boe, S G; Dalton, B H; Harwood, B; Doherty, T J; Rice, C L

2009-05-01

To establish the inter-rater reliability of decomposition-based quantitative electromyography (DQEMG) derived motor unit number estimates (MUNEs) and quantitative motor unit (MU) analysis. Using DQEMG, two examiners independently obtained a sample of needle and surface-detected motor unit potentials (MUPs) from the tibialis anterior muscle from 10 subjects. Coupled with a maximal M wave, surface-detected MUPs were used to derive a MUNE for each subject and each examiner. Additionally, size-related parameters of the individual MUs were obtained following quantitative MUP analysis. Test-retest MUNE values were similar with high reliability observed between examiners (ICC=0.87). Additionally, MUNE variability from test-retest as quantified by a 95% confidence interval was relatively low (+/-28 MUs). Lastly, quantitative data pertaining to MU size, complexity and firing rate were similar between examiners. MUNEs and quantitative MU data can be obtained with high reliability by two independent examiners using DQEMG. Establishing the inter-rater reliability of MUNEs and quantitative MU analysis using DQEMG is central to the clinical applicability of the technique. In addition to assessing response to treatments over time, multiple clinicians may be involved in the longitudinal assessment of the MU pool of individuals with disorders of the central or peripheral nervous system.

Quantification and Comparison of Anti-Fibrotic Therapies by Polarized SRM and SHG-Based Morphometry in Rat UUO Model

PubMed Central

Weldon, Steve M.; Matera, Damian; Lee, ChungWein; Yang, Haichun; Fryer, Ryan M.; Fogo, Agnes B.; Reinhart, Glenn A.

2016-01-01

Renal interstitial fibrosis (IF) is an important pathologic manifestation of disease progression in a variety of chronic kidney diseases (CKD). However, the quantitative and reproducible analysis of IF remains a challenge, especially in experimental animal models of progressive IF. In this study, we compare traditional polarized Sirius Red morphometry (SRM) to novel Second Harmonic Generation (SHG)-based morphometry of unstained tissues for quantitative analysis of IF in the rat 5 day unilateral ureteral obstruction (UUO) model. To validate the specificity of SHG for detecting fibrillar collagen components in IF, co-localization studies for collagens type I, III, and IV were performed using IHC. In addition, we examined the correlation, dynamic range, sensitivity, and ability of polarized SRM and SHG-based morphometry to detect an anti-fibrotic effect of three different treatment regimens. Comparisons were made across three separate studies in which animals were treated with three mechanistically distinct pharmacologic agents: enalapril (ENA, 15, 30, 60 mg/kg), mycophenolate mofetil (MMF, 2, 20 mg/kg) or the connective tissue growth factor (CTGF) neutralizing antibody, EX75606 (1, 3, 10 mg/kg). Our results demonstrate a strong co-localization of the SHG signal with fibrillar collagens I and III but not non-fibrillar collagen IV. Quantitative IF, calculated as percent cortical area of fibrosis, demonstrated similar response profile for both polarized SRM and SHG-based morphometry. The two methodologies exhibited a strong correlation across all three pharmacology studies (r2 = 0.89–0.96). However, compared with polarized SRM, SHG-based morphometry delivered a greater dynamic range and absolute magnitude of reduction of IF after treatment. In summary, we demonstrate that SHG-based morphometry in unstained kidney tissues is comparable to polarized SRM for quantitation of fibrillar collagens, but with an enhanced sensitivity to detect treatment-induced reductions in IF. Thus, performing SHG-based morphometry on unstained kidney tissue is a reliable alternative to traditional polarized SRM for quantitative analysis of IF. PMID:27257917

Data from quantitative label free proteomics analysis of rat spleen.

PubMed

Dudekula, Khadar; Le Bihan, Thierry

2016-09-01

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography.

PubMed

Shi, Zhanqun; Xu, Xiaoyu; Ma, Jiaojiao; Zhen, Dong; Zhang, Hao

2018-04-02

Small cracks are common defects in steel and often lead to catastrophic accidents in industrial applications. Various nondestructive testing methods have been investigated for crack detection; however, most current methods focus on qualitative crack identification and image processing. In this study, eddy current pulsed thermography (ECPT) was applied for quantitative crack detection based on derivative analysis of temperature variation. The effects of the incentive parameters on the temperature variation were analyzed in the simulation study. The crack profile and position are identified in the thermal image based on the Canny edge detection algorithm. Then, one or more trajectories are determined through the crack profile in order to determine the crack boundary through its temperature distribution. The slope curve along the trajectory is obtained. Finally, quantitative analysis of the crack sizes was performed by analyzing the features of the slope curves. The experimental verification showed that the crack sizes could be quantitatively detected with errors of less than 1%. Therefore, the proposed ECPT method was demonstrated to be a feasible and effective nondestructive approach for quantitative crack detection.

Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2010-03-01

Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

PubMed

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

RNA-based determination of ESR1 and HER2 expression and response to neoadjuvant chemotherapy.

PubMed

Denkert, C; Loibl, S; Kronenwett, R; Budczies, J; von Törne, C; Nekljudova, V; Darb-Esfahani, S; Solbach, C; Sinn, B V; Petry, C; Müller, B M; Hilfrich, J; Altmann, G; Staebler, A; Roth, C; Ataseven, B; Kirchner, T; Dietel, M; Untch, M; von Minckwitz, G

2013-03-01

Hormone and human epidermal growth factor receptor 2 (HER2) receptors are the most important breast cancer biomarkers, and additional objective and quantitative test methods such as messenger RNA (mRNA)-based quantitative analysis are urgently needed. In this study, we investigated the clinical validity of RT-PCR-based evaluation of estrogen receptor (ESR1) and HER2 mRNA expression. A total of 1050 core biopsies from two retrospective (GeparTrio, GeparQuattro) and one prospective (PREDICT) neoadjuvant studies were evaluated by quantitative RT-PCR for ESR1 and HER2. ESR1 mRNA was significantly predictive for reduced response to neoadjuvant chemotherapy in univariate and multivariate analysis in all three cohorts. The complete pathologically documented response (pathological complete response, pCR) rate for ESR1+/HER2- tumors was 7.3%, 8.0% and 8.6%; for ESR1-/HER2- tumors it was 34.4%, 33.7% and 37.3% in GeparTrio, GeparQuattro and PREDICT, respectively (P < 0.001 in each cohort). In the Kaplan-Meier analysis in GeparTrio patients with ESR1+/HER2- tumors had the best prognosis, compared with ESR1-/HER2- and ESR1-/HER2+ tumors [disease-free survival (DFS): P < 0.0005, overall survival (OS): P < 0.0005]. Our results suggest that mRNA levels of ESR1 and HER2 predict response to neoadjuvant chemotherapy and are significantly associated with long-term outcome. As an additional option to standard immunohistochemistry and gene-array-based analysis, quantitative RT-PCR analysis might be useful for determination of the receptor status in breast cancer.

Automated Quantitative Rare Earth Elements Mineralogy by Scanning Electron Microscopy

NASA Astrophysics Data System (ADS)

Sindern, Sven; Meyer, F. Michael

2016-09-01

Increasing industrial demand of rare earth elements (REEs) stems from the central role they play for advanced technologies and the accelerating move away from carbon-based fuels. However, REE production is often hampered by the chemical, mineralogical as well as textural complexity of the ores with a need for better understanding of their salient properties. This is not only essential for in-depth genetic interpretations but also for a robust assessment of ore quality and economic viability. The design of energy and cost-efficient processing of REE ores depends heavily on information about REE element deportment that can be made available employing automated quantitative process mineralogy. Quantitative mineralogy assigns numeric values to compositional and textural properties of mineral matter. Scanning electron microscopy (SEM) combined with a suitable software package for acquisition of backscatter electron and X-ray signals, phase assignment and image analysis is one of the most efficient tools for quantitative mineralogy. The four different SEM-based automated quantitative mineralogy systems, i.e. FEI QEMSCAN and MLA, Tescan TIMA and Zeiss Mineralogic Mining, which are commercially available, are briefly characterized. Using examples of quantitative REE mineralogy, this chapter illustrates capabilities and limitations of automated SEM-based systems. Chemical variability of REE minerals and analytical uncertainty can reduce performance of phase assignment. This is shown for the REE phases parisite and synchysite. In another example from a monazite REE deposit, the quantitative mineralogical parameters surface roughness and mineral association derived from image analysis are applied for automated discrimination of apatite formed in a breakdown reaction of monazite and apatite formed by metamorphism prior to monazite breakdown. SEM-based automated mineralogy fulfils all requirements for characterization of complex unconventional REE ores that will become increasingly important for supply of REEs in the future.

Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

NASA Astrophysics Data System (ADS)

Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

2017-03-01

A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

Quantitative allochem compositional analysis of Lochkovian-Pragian boundary sections in the Prague Basin (Czech Republic)

NASA Astrophysics Data System (ADS)

Weinerová, Hedvika; Hron, Karel; Bábek, Ondřej; Šimíček, Daniel; Hladil, Jindřich

2017-06-01

Quantitative allochem compositional trends across the Lochkovian-Pragian boundary Event were examined at three sections recording the proximal to more distal carbonate ramp environment of the Prague Basin. Multivariate statistical methods (principal component analysis, correspondence analysis, cluster analysis) of point-counted thin section data were used to reconstruct facies stacking patterns and sea-level history. Both the closed-nature allochem percentages and their centred log-ratio (clr) coordinates were used. Both these approaches allow for distinguishing of lowstand, transgressive and highstand system tracts within the Praha Formation, which show gradual transition from crinoid-dominated facies deposited above the storm wave base to dacryoconarid-dominated facies of deep-water environment below the storm wave base. Quantitative compositional data also indicate progradative-retrogradative trends in the macrolithologically monotonous shallow-water succession and enable its stratigraphic correlation with successions from deeper-water environments. Generally, the stratigraphic trends of the clr data are more sensitive to subtle changes in allochem composition in comparison to the results based on raw data. A heterozoan-dominated allochem association in shallow-water environments of the Praha Formation supports the carbonate ramp environment assumed by previous authors.

Broadband external cavity quantum cascade laser based sensor for gasoline detection

NASA Astrophysics Data System (ADS)

Ding, Junya; He, Tianbo; Zhou, Sheng; Li, Jinsong

2018-02-01

A new type of tunable diode spectroscopy sensor based on an external cavity quantum cascade laser (ECQCL) and a quartz crystal tuning fork (QCTF) were used for quantitative analysis of volatile organic compounds. In this work, the sensor system had been tested on different gasoline sample analysis. For signal processing, the self-established interpolation algorithm and multiple linear regression algorithm model were used for quantitative analysis of major volatile organic compounds in gasoline samples. The results were very consistent with that of the standard spectra taken from the Pacific Northwest National Laboratory (PNNL) database. In future, The ECQCL sensor will be used for trace explosive, chemical warfare agent, and toxic industrial chemical detection and spectroscopic analysis, etc.

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait.

PubMed

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-12-31

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits.

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait

PubMed Central

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-01-01

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits. PMID:14975142

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Sieve-based device for MALDI sample preparation. III. Its power for quantitative measurements.

PubMed

Molin, Laura; Cristoni, Simone; Seraglia, Roberta; Traldi, Pietro

2011-02-01

The solid sample inhomogeneity is a weak point of traditional MALDI deposition techniques that reflects negatively on quantitative analysis. The recently developed sieve-based device (SBD) sample deposition method, based on the electrospraying of matrix/analyte solutions through a grounded sieve, allows the homogeneous deposition of microcrystals with dimensions smaller than that of the laser spot. In each microcrystal the matrix/analyte molar ratio can be considered constant. Then, by irradiating different portions of the microcrystal distribution an identical response is obtained. This result suggests the employment of SBD in the development of quantitative procedures. For this aim, mixtures of different proteins of known molarity were analyzed, showing a good relationship between molarity and intensity ratios. This behaviour was also observed in the case of proteins with quite different ionic yields. The power of the developed method for quantitative evaluation was also tested by the measurement of the abundance of IGPP[Oxi]GPP[Oxi]GLMGPP (m/z 1219) present in the collagen-α-5(IV) chain precursor, differently expressed in urines from healthy subjects and diabetic-nephropathic patients, confirming its overexpression in the presence of nephropathy. The data obtained indicate that SBD is a particularly effective method for quantitative analysis also in biological fluids of interest. Copyright © 2011 John Wiley & Sons, Ltd.

ANTONIA perfusion and stroke. A software tool for the multi-purpose analysis of MR perfusion-weighted datasets and quantitative ischemic stroke assessment.

PubMed

Forkert, N D; Cheng, B; Kemmling, A; Thomalla, G; Fiehler, J

2014-01-01

The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation. Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses. For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used. Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.

Quantitative Analysis of Color Differences within High Contrast, Low Power Reversible Electrophoretic Displays

DOE PAGES

Giera, Brian; Bukosky, Scott; Lee, Elaine; ...

2018-01-23

Here, quantitative color analysis is performed on videos of high contrast, low power reversible electrophoretic deposition (EPD)-based displays operated under different applied voltages. This analysis is coded in an open-source software, relies on a color differentiation metric, ΔE * 00, derived from digital video, and provides an intuitive relationship between the operating conditions of the devices and their performance. Time-dependent ΔE * 00 color analysis reveals color relaxation behavior, recoverability for different voltage sequences, and operating conditions that can lead to optimal performance.

Quantitative Analysis of Color Differences within High Contrast, Low Power Reversible Electrophoretic Displays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giera, Brian; Bukosky, Scott; Lee, Elaine

Here, quantitative color analysis is performed on videos of high contrast, low power reversible electrophoretic deposition (EPD)-based displays operated under different applied voltages. This analysis is coded in an open-source software, relies on a color differentiation metric, ΔE * 00, derived from digital video, and provides an intuitive relationship between the operating conditions of the devices and their performance. Time-dependent ΔE * 00 color analysis reveals color relaxation behavior, recoverability for different voltage sequences, and operating conditions that can lead to optimal performance.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data

NASA Astrophysics Data System (ADS)

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-01

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

PubMed

Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-05-07

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Information Technology Tools Analysis in Quantitative Courses of IT-Management (Case Study: M.Sc.-Tehran University)

ERIC Educational Resources Information Center

Eshlaghy, Abbas Toloie; Kaveh, Haydeh

2009-01-01

The purpose of this study was to determine the most suitable ICT-based education and define the most suitable e-content creation tools for quantitative courses in the IT-management Masters program. ICT-based tools and technologies are divided in to three categories: the creation of e-content, the offering of e-content, and access to e-content. In…

Quantitative analysis of regional myocardial performance in coronary artery disease

NASA Technical Reports Server (NTRS)

Stewart, D. K.; Dodge, H. T.; Frimer, M.

1975-01-01

Findings from a group of subjects with significant coronary artery stenosis are given. A group of controls determined by use of a quantitative method for the study of regional myocardial performance based on the frame-by-frame analysis of biplane left ventricular angiograms are presented. Particular emphasis was placed upon the analysis of wall motion in terms of normalized segment dimensions, timing and velocity of contraction. The results were compared with the method of subjective assessment used clinically.

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

PubMed

Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian

2012-10-24

Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.

Data from SILAC-based quantitative analysis of lysates from mouse microglial cells treated with Withaferin A (WA).

PubMed

Narayan, Malathi; Seeley, Kent W; Jinwal, Umesh K

2016-06-01

Mass spectrometry data collected in a study analyzing the effect of withaferin A (WA) on a mouse microglial (N9) cell line is presented in this article. Data was collected from SILAC-based quantitative analysis of lysates from mouse microglial cells treated with either WA or DMSO vehicle control. This article reports all the proteins that were identified in this analysis. The data presented here is related to the published research article on the effect of WA on the differential regulation of proteins in mouse microglial cells [1]. Mass spectrometry data has also been deposited in the ProteomeXchange with the identifier PXD003032.

Digital Imaging

NASA Technical Reports Server (NTRS)

1986-01-01

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

Quantitative analysis of voids in percolating structures in two-dimensional N-body simulations

NASA Technical Reports Server (NTRS)

Harrington, Patrick M.; Melott, Adrian L.; Shandarin, Sergei F.

1993-01-01

We present in this paper a quantitative method for defining void size in large-scale structure based on percolation threshold density. Beginning with two-dimensional gravitational clustering simulations smoothed to the threshold of nonlinearity, we perform percolation analysis to determine the large scale structure. The resulting objective definition of voids has a natural scaling property, is topologically interesting, and can be applied immediately to redshift surveys.

Content Analysis of a Computer-Based Faculty Activity Repository

ERIC Educational Resources Information Center

Baker-Eveleth, Lori; Stone, Robert W.

2013-01-01

The research presents an analysis of faculty opinions regarding the introduction of a new computer-based faculty activity repository (FAR) in a university setting. The qualitative study employs content analysis to better understand the phenomenon underlying these faculty opinions and to augment the findings from a quantitative study. A web-based…

[The development of a computer model in the quantitative assessment of thallium-201 myocardial scintigraphy].

PubMed

Raineri, M; Traina, M; Rotolo, A; Candela, B; Lombardo, R M; Raineri, A A

1993-05-01

Thallium-201 scintigraphy is a widely used noninvasive procedure for the detection and prognostic assessment of patients with suspected or proven coronary artery disease. Thallium uptake can be evaluated by a visual analysis or by a quantitative interpretation. Quantitative scintigraphy enhances disease detection in individual coronary arteries, provides a more precise estimate of the amount of ischemic myocardium, distinguishing scar from hypoperfused tissue. Due to the great deal of data, analysis, interpretation and comparison of thallium uptake can be very complex. We designed a computer-based system for the interpretation of quantitative thallium-201 scintigraphy data uptake. We used a database (DataEase 4.2-DataEase Italia). Our software has the following functions: data storage; calculation; conversion of numerical data into different definitions classifying myocardial perfusion; uptake data comparison; automatic conclusion; comparison of different scintigrams for the same patient. Our software is made up by 4 sections: numeric analysis, descriptive analysis, automatic conclusion, clinical remarks. We introduced in the computer system appropriate information, "logical paths", that use the "IF ... THEN" rules. The software executes these rules in order to analyze the myocardial regions in the 3 phases of scintigraphic analysis (stress, redistribution, re-injection), in the 3 projections (LAO 45 degrees, LAT,ANT), considering our uptake cutoff, obtaining, finally, the automatic conclusions. For these reasons, our computer-based system could be considered a real "expert system".

Stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization.

PubMed

Veeraraghavan, Rengasayee; Gourdie, Robert G

2016-11-07

The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. © 2016 Veeraraghavan and Gourdie. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Widely-targeted quantitative lipidomics methodology by supercritical fluid chromatography coupled with fast-scanning triple quadrupole mass spectrometry.

PubMed

Takeda, Hiroaki; Izumi, Yoshihiro; Takahashi, Masatomo; Paxton, Thanai; Tamura, Shohei; Koike, Tomonari; Yu, Ying; Kato, Noriko; Nagase, Katsutoshi; Shiomi, Masashi; Bamba, Takeshi

2018-05-03

Lipidomics, the mass spectrometry-based comprehensive analysis of lipids, has attracted attention as an analytical approach to provide novel insight into lipid metabolism and to search for biomarkers. However, an ideal method for both comprehensive and quantitative analysis of lipids has not been fully developed. Herein, we have proposed a practical methodology for widely-targeted quantitative lipidome analysis using supercritical fluid chromatography fast-scanning triple-quadrupole mass spectrometry (SFC/QqQMS) and theoretically calculated a comprehensive lipid multiple reaction monitoring (MRM) library. Lipid classes can be separated by SFC with a normal phase diethylamine-bonded silica column with high-resolution, high-throughput, and good repeatability. Structural isomers of phospholipids can be monitored by mass spectrometric separation with fatty acyl-based MRM transitions. SFC/QqQMS analysis with an internal standard-dilution method offers quantitative information for both lipid class and individual lipid molecular species in the same lipid class. Additionally, data acquired using this method has advantages including reduction of misidentification and acceleration of data analysis. Using the SFC/QqQMS system, alteration of plasma lipid levels in myocardial infarction-prone rabbits to the supplementation of eicosapentaenoic acid was first observed. Our developed SFC/QqQMS method represents a potentially useful tool for in-depth studies focused on complex lipid metabolism and biomarker discovery. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

A Radioactivity Based Quantitative Analysis of the Amount of Thorium Present in Ores and Metallurgical Products; ANALYSE QUANTITATIVE DU THORIUM DANS LES MINERAIS ET LES PRODUITS THORIFERES PAR UNE METHODE BASEE SUR LA RADIOACTIVITE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collee, R.; Govaerts, J.; Winand, L.

1959-10-31

A brief resume of the classical methods of quantitative determination of thorium in ores and thoriferous products is given to show that a rapid, accurate, and precise physical method based on the radioactivity of thorium would be of great utility. A method based on the utilization of the characteristic spectrum of the thorium gamma radiation is presented. The preparation of the samples and the instruments needed for the measurements is discussed. The experimental results show that the reproducibility is very satisfactory and that it is possible to detect Th contents of 1% or smaller. (J.S.R.)

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

PubMed

Gunawardena, Harsha P; O'Brien, Jonathon; Wrobel, John A; Xie, Ling; Davies, Sherri R; Li, Shunqiang; Ellis, Matthew J; Qaqish, Bahjat F; Chen, Xian

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Relating interesting quantitative time series patterns with text events and text features

NASA Astrophysics Data System (ADS)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other application domains such as data analysis of smart grids, cyber physical systems or the security of critical infrastructure, where the data consists of a combination of quantitative and textual time series data.

An approach to standardization of urine sediment analysis via suggestion of a common manual protocol.

PubMed

Ko, Dae-Hyun; Ji, Misuk; Kim, Sollip; Cho, Eun-Jung; Lee, Woochang; Yun, Yeo-Min; Chun, Sail; Min, Won-Ki

2016-01-01

The results of urine sediment analysis have been reported semiquantitatively. However, as recent guidelines recommend quantitative reporting of urine sediment, and with the development of automated urine sediment analyzers, there is an increasing need for quantitative analysis of urine sediment. Here, we developed a protocol for urine sediment analysis and quantified the results. Based on questionnaires, various reports, guidelines, and experimental results, we developed a protocol for urine sediment analysis. The results of this new protocol were compared with those obtained with a standardized chamber and an automated sediment analyzer. Reference intervals were also estimated using new protocol. We developed a protocol with centrifugation at 400 g for 5 min, with the average concentration factor of 30. The correlation between quantitative results of urine sediment analysis, the standardized chamber, and the automated sediment analyzer were generally good. The conversion factor derived from the new protocol showed a better fit with the results of manual count than the default conversion factor in the automated sediment analyzer. We developed a protocol for manual urine sediment analysis to quantitatively report the results. This protocol may provide a mean for standardization of urine sediment analysis.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

Assessing the risk posed by natural hazards to infrastructures

NASA Astrophysics Data System (ADS)

Eidsvig, Unni; Kristensen, Krister; Vidar Vangelsten, Bjørn

2015-04-01

The modern society is increasingly dependent on infrastructures to maintain its function, and disruption in one of the infrastructure systems may have severe consequences. The Norwegian municipalities have, according to legislation, a duty to carry out a risk and vulnerability analysis and plan and prepare for emergencies in a short- and long term perspective. Vulnerability analysis of the infrastructures and their interdependencies is an important part of this analysis. This paper proposes a model for assessing the risk posed by natural hazards to infrastructures. The model prescribes a three level analysis with increasing level of detail, moving from qualitative to quantitative analysis. This paper focuses on the second level, which consists of a semi-quantitative analysis. The purpose of this analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures identified in the level 1 analysis and investigate the need for further analyses, i.e. level 3 quantitative analyses. The proposed level 2 analysis considers the frequency of the natural hazard, different aspects of vulnerability including the physical vulnerability of the infrastructure itself and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale. The proposed indicators characterize the robustness of the infrastructure, the importance of the infrastructure as well as interdependencies between society and infrastructure affecting the potential for cascading effects. Each indicator is ranked on a 1-5 scale based on pre-defined ranking criteria. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard and the number of users of the infrastructure. Case studies for two Norwegian municipalities are presented, where risk to primary road, water supply and power network threatened by storm and landslide is assessed. The application examples show that the proposed model provides a useful tool for screening of undesirable events, with the ultimate goal to reduce the societal vulnerability.

Histopathological image analysis of chemical-induced hepatocellular hypertrophy in mice.

PubMed

Asaoka, Yoshiji; Togashi, Yuko; Mutsuga, Mayu; Imura, Naoko; Miyoshi, Tomoya; Miyamoto, Yohei

2016-04-01

Chemical-induced hepatocellular hypertrophy is frequently observed in rodents, and is mostly caused by the induction of phase I and phase II drug metabolic enzymes and peroxisomal lipid metabolic enzymes. Liver weight is a sensitive and commonly used marker for detecting hepatocellular hypertrophy, but is also increased by a number of other factors. Histopathological observations subjectively detect changes such as hepatocellular hypertrophy based on the size of a hepatocyte. Therefore, quantitative microscopic observations are required to evaluate histopathological alterations objectively. In the present study, we developed a novel quantitative method for an image analysis of hepatocellular hypertrophy using liver sections stained with hematoxylin and eosin, and demonstrated its usefulness for evaluating hepatocellular hypertrophy induced by phenobarbital (a phase I and phase II enzyme inducer) and clofibrate (a peroxisomal enzyme inducer) in mice. The algorithm of this imaging analysis was designed to recognize an individual hepatocyte through a combination of pixel-based and object-based analyses. Hepatocellular nuclei and the surrounding non-hepatocellular cells were recognized by the pixel-based analysis, while the areas of the recognized hepatocellular nuclei were then expanded until they ran against their expanding neighboring hepatocytes and surrounding non-hepatocellular cells by the object-based analysis. The expanded area of each hepatocellular nucleus was regarded as the size of an individual hepatocyte. The results of this imaging analysis showed that changes in the sizes of hepatocytes corresponded with histopathological observations in phenobarbital and clofibrate-treated mice, and revealed a correlation between hepatocyte size and liver weight. In conclusion, our novel image analysis method is very useful for quantitative evaluations of chemical-induced hepatocellular hypertrophy. Copyright © 2015 Elsevier GmbH. All rights reserved.

A novel multi-walled carbon nanotube-based antibody conjugate for quantitative and semi-quantitative lateral flow assays.

PubMed

Sun, Wenjuan; Hu, Xiaolong; Liu, Jia; Zhang, Yurong; Lu, Jianzhong; Zeng, Libo

2017-10-01

In this study, the multi-walled carbon nanotubes (MWCNTs) were applied in lateral flow strips (LFS) for semi-quantitative and quantitative assays. Firstly, the solubility of MWCNTs was improved using various surfactants to enhance their biocompatibility for practical application. The dispersed MWCNTs were conjugated with the methamphetamine (MET) antibody in a non-covalent manner and then manufactured into the LFS for the quantitative detection of MET. The MWCNTs-based lateral flow assay (MWCNTs-LFA) exhibited an excellent linear relationship between the values of test line and MET when its concentration ranges from 62.5 to 1500 ng/mL. The sensitivity of the LFS was evaluated by conjugating MWCNTs with HCG antibody and the MWCNTs conjugated method is 10 times more sensitive than the one conjugated with classical colloidal gold nanoparticles. Taken together, our data demonstrate that MWCNTs-LFA is a more sensitive and reliable assay for semi-quantitative and quantitative detection which can be used in forensic analysis.

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

2009-01-01

Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644970

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics.

PubMed

Lavallée-Adam, Mathieu; Yates, John R

2016-03-24

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the Web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Gold Nanoparticle Labeling Based ICP-MS Detection/Measurement of Bacteria, and Their Quantitative Photothermal Destruction

PubMed Central

Lin, Yunfeng

2015-01-01

Bacteria such as Salmonella and E. coli present a great challenge in public health care in today’s society. Protection of public safety against bacterial contamination and rapid diagnosis of infection require simple and fast assays for the detection and elimination of bacterial pathogens. After utilizing Salmonella DT104 as an example bacterial strain for our investigation, we report a rapid and sensitive assay for the qualitative and quantitative detection of bacteria by using antibody affinity binding, popcorn shaped gold nanoparticle (GNPOPs) labeling, surfance enchanced Raman spectroscopy (SERS), and inductively coupled plasma mass spectrometry (ICP-MS) detection. For qualitative analysis, our assay can detect Salmonella within 10 min by Raman spectroscopy; for quantitative analysis, our assay has the ability to measure as few as 100 Salmonella DT104 in a 1 mL sample (100 CFU/mL) within 40 min. Based on the quantitative detection, we investigated the quantitative destruction of Salmonella DT104, and the assay’s photothermal efficiency in order to reduce the amount of GNPOPs in the assay to ultimately to eliminate any potential side effects/toxicity to the surrounding cells in vivo. Results suggest that our assay may serve as a promising candidate for qualitative and quantitative detection and elimination of a variety of bacterial pathogens. PMID:26417447

Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program.

PubMed

Fu, Rongwei; Gartlehner, Gerald; Grant, Mark; Shamliyan, Tatyana; Sedrakyan, Art; Wilt, Timothy J; Griffith, Lauren; Oremus, Mark; Raina, Parminder; Ismaila, Afisi; Santaguida, Pasqualina; Lau, Joseph; Trikalinos, Thomas A

2011-11-01

This article is to establish recommendations for conducting quantitative synthesis, or meta-analysis, using study-level data in comparative effectiveness reviews (CERs) for the Evidence-based Practice Center (EPC) program of the Agency for Healthcare Research and Quality. We focused on recurrent issues in the EPC program and the recommendations were developed using group discussion and consensus based on current knowledge in the literature. We first discussed considerations for deciding whether to combine studies, followed by discussions on indirect comparison and incorporation of indirect evidence. Then, we described our recommendations on choosing effect measures and statistical models, giving special attention to combining studies with rare events; and on testing and exploring heterogeneity. Finally, we briefly presented recommendations on combining studies of mixed design and on sensitivity analysis. Quantitative synthesis should be conducted in a transparent and consistent way. Inclusion of multiple alternative interventions in CERs increases the complexity of quantitative synthesis, whereas the basic issues in quantitative synthesis remain crucial considerations in quantitative synthesis for a CER. We will cover more issues in future versions and update and improve recommendations with the accumulation of new research to advance the goal for transparency and consistency. Copyright © 2011 Elsevier Inc. All rights reserved.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

QUANTITATIVE MASS SPECTROMETRIC ANALYSIS OF GLYCOPROTEINS COMBINED WITH ENRICHMENT METHODS

PubMed Central

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc. Rapid Commun. Mass Spec Rev 34:148–165, 2015. PMID:24889823

Quantitative analysis of glycated albumin in serum based on ATR-FTIR spectrum combined with SiPLS and SVM.

PubMed

Li, Yuanpeng; Li, Fucui; Yang, Xinhao; Guo, Liu; Huang, Furong; Chen, Zhenqiang; Chen, Xingdan; Zheng, Shifu

2018-08-05

A rapid quantitative analysis model for determining the glycated albumin (GA) content based on Attenuated total reflectance (ATR)-Fourier transform infrared spectroscopy (FTIR) combining with linear SiPLS and nonlinear SVM has been developed. Firstly, the real GA content in human serum was determined by GA enzymatic method, meanwhile, the ATR-FTIR spectra of serum samples from the population of health examination were obtained. The spectral data of the whole spectra mid-infrared region (4000-600 cm -1 ) and GA's characteristic region (1800-800 cm -1 ) were used as the research object of quantitative analysis. Secondly, several preprocessing steps including first derivative, second derivative, variable standardization and spectral normalization, were performed. Lastly, quantitative analysis regression models were established by using SiPLS and SVM respectively. The SiPLS modeling results are as follows: root mean square error of cross validation (RMSECV T ) = 0.523 g/L, calibration coefficient (R C ) = 0.937, Root Mean Square Error of Prediction (RMSEP T ) = 0.787 g/L, and prediction coefficient (R P ) = 0.938. The SVM modeling results are as follows: RMSECV T  = 0.0048 g/L, R C  = 0.998, RMSEP T  = 0.442 g/L, and R p  = 0.916. The results indicated that the model performance was improved significantly after preprocessing and optimization of characteristic regions. While modeling performance of nonlinear SVM was considerably better than that of linear SiPLS. Hence, the quantitative analysis model for GA in human serum based on ATR-FTIR combined with SiPLS and SVM is effective. And it does not need sample preprocessing while being characterized by simple operations and high time efficiency, providing a rapid and accurate method for GA content determination. Copyright © 2018 Elsevier B.V. All rights reserved.

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

PubMed

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

PubMed

Tu, Chengjian; Li, Jun; Sheng, Quanhu; Zhang, Ming; Qu, Jun

2014-04-04

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R(2) > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Systematic Assessment of Survey Scan and MS2-Based Abundance Strategies for Label-Free Quantitative Proteomics Using High-Resolution MS Data

PubMed Central

2015-01-01

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R2 > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery. PMID:24635752

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

New approaches for the analysis of confluent cell layers with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Pohl, L.; Kaiser, M.; Ketelhut, S.; Pereira, S.; Goycoolea, F.; Kemper, Björn

2016-03-01

Digital holographic microscopy (DHM) enables high resolution non-destructive inspection of technical surfaces and minimally-invasive label-free live cell imaging. However, the analysis of confluent cell layers represents a challenge as quantitative DHM phase images in this case do not provide sufficient information for image segmentation, determination of the cellular dry mass or calculation of the cell thickness. We present novel strategies for the analysis of confluent cell layers with quantitative DHM phase contrast utilizing a histogram based-evaluation procedure. The applicability of our approach is illustrated by quantification of drug induced cell morphology changes and it is shown that the method is capable to quantify reliable global morphology changes of confluent cell layers.

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data.

PubMed

Vu, Trung N; Valkenborg, Dirk; Smets, Koen; Verwaest, Kim A; Dommisse, Roger; Lemière, Filip; Verschoren, Alain; Goethals, Bart; Laukens, Kris

2011-10-20

Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline. We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data. The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from http://code.google.com/p/speaq/.

A versatile quantitation platform based on platinum nanoparticles incorporated volumetric bar-chart chip for highly sensitive assays.

PubMed

Wang, Yuzhen; Zhu, Guixian; Qi, Wenjin; Li, Ying; Song, Yujun

2016-11-15

Platinum nanoparticles incorporated volumetric bar-chart chip (PtNPs-V-Chip) is able to be used for point-of-care tests by providing quantitative and visualized readout without any assistance from instruments, data processing, or graphic plotting. To improve the sensitivity of PtNPs-V-Chip, hybridization chain reaction was employed in this quantitation platform for highly sensitive assays that can detect as low as 16 pM Ebola Virus DNA, 0.01ng/mL carcinoembryonic antigen (CEA), and the 10 HER2-expressing cancer cells. Based on this amplified strategy, a 100-fold decrease of detection limit was achieved for DNA by improving the number of platinum nanoparticle catalyst for the captured analyte. This quantitation platform can also distinguish single base mismatch of DNA hybridization and observe the concentration threshold of CEA. The new strategy lays the foundation for this quantitation platform to be applied in forensic analysis, biothreat detection, clinical diagnostics and drug screening. Copyright © 2016 Elsevier B.V. All rights reserved.

Improving Student Understanding of Qualitative and Quantitative Analysis via GC/MS Using a Rapid SPME-Based Method for Determination of Trihalomethanes in Drinking Water

ERIC Educational Resources Information Center

Huang, Shu Rong; Palmer, Peter T.

2017-01-01

This paper describes a method for determination of trihalomethanes (THMs) in drinking water via solid-phase microextraction (SPME) GC/MS as a means to develop and improve student understanding of the use of GC/MS for qualitative and quantitative analysis. In the classroom, students are introduced to SPME, GC/MS instrumentation, and the use of MS…

Cardiac imaging: working towards fully-automated machine analysis & interpretation

PubMed Central

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-01-01

Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804

Identification and Quantitative Analysis of Acetaminophen, Acetylsalicylic Acid, and Caffeine in Commercial Analgesic Tablets by LC-MS

ERIC Educational Resources Information Center

Fenk, Christopher J.; Hickman, Nicole M.; Fincke, Melissa A.; Motry, Douglas H.; Lavine, Barry

2010-01-01

An undergraduate LC-MS experiment is described for the identification and quantitative determination of acetaminophen, acetylsalicylic acid, and caffeine in commercial analgesic tablets. This inquiry-based experimental procedure requires minimal sample preparation and provides good analytical results. Students are provided sufficient background…

NEW TARGET AND CONTROL ASSAYS FOR QUANTITATIVE POLYMERASE CHAIN REACTION (QPCR) ANALYSIS OF ENTEROCOCCI IN WATER

EPA Science Inventory

Enterococci are frequently monitored in water samples as indicators of fecal pollution. Attention is now shifting from culture based methods for enumerating these organisms to more rapid molecular methods such as QPCR. Accurate quantitative analyses by this method requires highly...

Behavioral Changes Based on a Course in Agroecology: A Mixed Methods Study

ERIC Educational Resources Information Center

Harms, Kristyn; King, James; Francis, Charles

2009-01-01

This study evaluated and described student perceptions of a course in agroecology to determine if participants experienced changed perceptions and behaviors resulting from the Agroecosystems Analysis course. A triangulation validating quantitative data mixed methods approach included a written survey comprised of both quantitative and open-ended…

Quantitative Analysis of Qualitative Information from Interviews: A Systematic Literature Review

ERIC Educational Resources Information Center

Fakis, Apostolos; Hilliam, Rachel; Stoneley, Helen; Townend, Michael

2014-01-01

Background: A systematic literature review was conducted on mixed methods area. Objectives: The overall aim was to explore how qualitative information from interviews has been analyzed using quantitative methods. Methods: A contemporary review was undertaken and based on a predefined protocol. The references were identified using inclusion and…

Assessment and monitoring of forest ecosystem structure

Treesearch

Oscar A. Aguirre Calderón; Javier Jiménez Pérez; Horst Kramer

2006-01-01

Characterization of forest ecosystems structure must be based on quantitative indices that allow objective analysis of human influences or natural succession processes. The objective of this paper is the compilation of diverse quantitative variables to describe structural attributes from the arboreal stratum of the ecosystem, as well as different methods of forest...

Orthogonal analytical methods for botanical standardization: Determination of green tea catechins by qNMR and LC-MS/MS

PubMed Central

Napolitano, José G.; Gödecke, Tanja; Lankin, David C.; Jaki, Birgit U.; McAlpine, James B.; Chen, Shao-Nong; Pauli, Guido F.

2013-01-01

The development of analytical methods for parallel characterization of multiple phytoconstituents is essential to advance the quality control of herbal products. While chemical standardization is commonly carried out by targeted analysis using gas or liquid chromatography-based methods, more universal approaches based on quantitative 1H NMR (qHNMR) measurements are being used increasingly in the multi-targeted assessment of these complex mixtures. The present study describes the development of a 1D qHNMR-based method for simultaneous identification and quantification of green tea constituents. This approach utilizes computer-assisted 1H iterative Full Spin Analysis (HiFSA) and enables rapid profiling of seven catechins in commercial green tea extracts. The qHNMR results were cross-validated against quantitative profiles obtained with an orthogonal LC-MS/MS method. The relative strengths and weaknesses of both approaches are discussed, with special emphasis on the role of identical reference standards in qualitative and quantitative analyses. PMID:23870106

Quantitative comparison of cognitive behavioral therapy and music therapy research: a methodological best-practices analysis to guide future investigation for adult psychiatric patients.

PubMed

Silverman, Michael J

2008-01-01

While the music therapy profession is relatively young and small in size, it can treat a variety of clinical populations and has established a diverse research base. However, although the profession originated working with persons diagnosed with mental illnesses, there is a considerable lack of quantitative research concerning the effects of music therapy with this population. Music therapy clinicians and researchers have reported on this lack of evidence and the difficulty in conducting psychosocial research on their interventions (Choi, 1997; Silverman, 2003a). While published studies have provided suggestions for future research, no studies have provided detailed propositions for the methodology and design of meticulous high quality randomized controlled psychiatric music therapy research. How do other psychotherapies accomplish their databases and could the music therapy field borrow from their rigorous "methodological best practices" to strengthen its own literature base? Therefore, as the National Institutes of Mental Health state the treatment of choice for evidence-based psychotherapy is cognitive behavioral therapy (CBT), aspects of this psychotherapy's literature base were analyzed. The purpose of this literature analysis was to (a) analyze and identify components of high-quality quantitative CBT research for adult psychiatric consumers, (b) analyze and identify the variables and other elements of existing quantitative psychiatric music therapy research for adult consumers, and (c) compare the two data sets to identify the best methodological designs and variables for future quantitative music therapy research with the mental health population. A table analyzing randomized and thoroughly controlled studies involving the use of CBT for persons with severe mental illnesses is included to determine chief components of high-quality experimental research designs and implementation of quantitative clinical research. The table also shows the same analyzed components for existing quantitative psychiatric music therapy research with adult consumers, thus highlighting potential areas and elements for future investigations. A second table depicts a number of potential dependent measures and their sources to be evaluated in future music therapy studies. A third table providing suggestions for future research is derived from a synthesis of the tables and is included to guide researchers and encourage the advancement and expansion of the current literature base. The body of the paper is a discussion of the results of the literature analysis derived from the tables, meta-analyses, and reviews of literature. It is hoped that this report will lead to the addition of future high-quality quantitative research to the psychiatric music therapy literature base and thus provide evidence-based services to as many persons with mental illnesses as possible.

Improvements to direct quantitative analysis of multiple microRNAs facilitating faster analysis.

PubMed

Ghasemi, Farhad; Wegman, David W; Kanoatov, Mirzo; Yang, Burton B; Liu, Stanley K; Yousef, George M; Krylov, Sergey N

2013-11-05

Studies suggest that patterns of deregulation in sets of microRNA (miRNA) can be used as cancer diagnostic and prognostic biomarkers. Establishing a "miRNA fingerprint"-based diagnostic technique requires a suitable miRNA quantitation method. The appropriate method must be direct, sensitive, capable of simultaneous analysis of multiple miRNAs, rapid, and robust. Direct quantitative analysis of multiple microRNAs (DQAMmiR) is a recently introduced capillary electrophoresis-based hybridization assay that satisfies most of these criteria. Previous implementations of the method suffered, however, from slow analysis time and required lengthy and stringent purification of hybridization probes. Here, we introduce a set of critical improvements to DQAMmiR that address these technical limitations. First, we have devised an efficient purification procedure that achieves the required purity of the hybridization probe in a fast and simple fashion. Second, we have optimized the concentrations of the DNA probe to decrease the hybridization time to 10 min. Lastly, we have demonstrated that the increased probe concentrations and decreased incubation time removed the need for masking DNA, further simplifying the method and increasing its robustness. The presented improvements bring DQAMmiR closer to use in a clinical setting.

Quantitative model analysis with diverse biological data: applications in developmental pattern formation.

PubMed

Pargett, Michael; Umulis, David M

2013-07-15

Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works, and to infer regulatory interactions that produce a model consistent with the observed data. Both of these approaches to modeling are informed by experimental data, however, much of the data available or even acquirable are not quantitative. Data that is not strictly quantitative cannot be used by classical, quantitative, model-based analyses that measure a difference between the measured observation and the model prediction for that observation. To bridge the model-to-data gap, a variety of techniques have been developed to measure model "fitness" and provide numerical values that can subsequently be used in model optimization or model inference studies. Here, we discuss a selection of traditional and novel techniques to transform data of varied quality and enable quantitative comparison with mathematical models. This review is intended to both inform the use of these model analysis methods, focused on parameter estimation, and to help guide the choice of method to use for a given study based on the type of data available. Applying techniques such as normalization or optimal scaling may significantly improve the utility of current biological data in model-based study and allow greater integration between disparate types of data. Copyright © 2013 Elsevier Inc. All rights reserved.

Development of quantitative exposure data for a pooled exposure-response analysis of 10 silica cohorts.

PubMed

Mannetje, Andrea 't; Steenland, Kyle; Checkoway, Harvey; Koskela, Riitta-Sisko; Koponen, Matti; Attfield, Michael; Chen, Jingqiong; Hnizdo, Eva; DeKlerk, Nicholas; Dosemeci, Mustafa

2002-08-01

Comprehensive quantitative silica exposure estimates over time, measured in the same units across a number of cohorts, would make possible a pooled exposure-response analysis for lung cancer. Such an analysis would help clarify the continuing controversy regarding whether silica causes lung cancer. Existing quantitative exposure data for 10 silica-exposed cohorts were retrieved from the original investigators. Occupation- and time-specific exposure estimates were either adopted/adapted or developed for each cohort, and converted to milligram per cubic meter (mg/m(3)) respirable crystalline silica. Quantitative exposure assignments were typically based on a large number (thousands) of raw measurements, or otherwise consisted of exposure estimates by experts (for two cohorts). Median exposure level of the cohorts ranged between 0.04 and 0.59 mg/m(3) respirable crystalline silica. Exposure estimates were partially validated via their successful prediction of silicosis in these cohorts. Existing data were successfully adopted or modified to create comparable quantitative exposure estimates over time for 10 silica-exposed cohorts, permitting a pooled exposure-response analysis. The difficulties encountered in deriving common exposure estimates across cohorts are discussed. Copyright 2002 Wiley-Liss, Inc.

Sub-band denoising and spline curve fitting method for hemodynamic measurement in perfusion MRI

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Huang, Hsiao-Ling; Hsu, Yuan-Yu; Chen, Chi-Chen; Chen, Ing-Yi; Wu, Liang-Chi; Liu, Ren-Shyan; Lin, Kang-Ping

2003-05-01

In clinical research, non-invasive MR perfusion imaging is capable of investigating brain perfusion phenomenon via various hemodynamic measurements, such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean trasnit time (MTT). These hemodynamic parameters are useful in diagnosing brain disorders such as stroke, infarction and periinfarct ischemia by further semi-quantitative analysis. However, the accuracy of quantitative analysis is usually affected by poor signal-to-noise ratio image quality. In this paper, we propose a hemodynamic measurement method based upon sub-band denoising and spline curve fitting processes to improve image quality for better hemodynamic quantitative analysis results. Ten sets of perfusion MRI data and corresponding PET images were used to validate the performance. For quantitative comparison, we evaluate gray/white matter CBF ratio. As a result, the hemodynamic semi-quantitative analysis result of mean gray to white matter CBF ratio is 2.10 +/- 0.34. The evaluated ratio of brain tissues in perfusion MRI is comparable to PET technique is less than 1-% difference in average. Furthermore, the method features excellent noise reduction and boundary preserving in image processing, and short hemodynamic measurement time.

Assessment of acute myocarditis by cardiac magnetic resonance imaging: Comparison of qualitative and quantitative analysis methods.

PubMed

Imbriaco, Massimo; Nappi, Carmela; Puglia, Marta; De Giorgi, Marco; Dell'Aversana, Serena; Cuocolo, Renato; Ponsiglione, Andrea; De Giorgi, Igino; Polito, Maria Vincenza; Klain, Michele; Piscione, Federico; Pace, Leonardo; Cuocolo, Alberto

2017-10-26

To compare cardiac magnetic resonance (CMR) qualitative and quantitative analysis methods for the noninvasive assessment of myocardial inflammation in patients with suspected acute myocarditis (AM). A total of 61 patients with suspected AM underwent coronary angiography and CMR. Qualitative analysis was performed applying Lake-Louise Criteria (LLC), followed by quantitative analysis based on the evaluation of edema ratio (ER) and global relative enhancement (RE). Diagnostic performance was assessed for each method by measuring the area under the curves (AUC) of the receiver operating characteristic analyses. The final diagnosis of AM was based on symptoms and signs suggestive of cardiac disease, evidence of myocardial injury as defined by electrocardiogram changes, elevated troponin I, exclusion of coronary artery disease by coronary angiography, and clinical and echocardiographic follow-up at 3 months after admission to the chest pain unit. In all patients, coronary angiography did not show significant coronary artery stenosis. Troponin I levels and creatine kinase were higher in patients with AM compared to those without (both P < .001). There were no significant differences among LLC, T2-weighted short inversion time inversion recovery (STIR) sequences, early (EGE), and late (LGE) gadolinium-enhancement sequences for diagnosis of AM. The AUC for qualitative (T2-weighted STIR 0.92, EGE 0.87 and LGE 0.88) and quantitative (ER 0.89 and global RE 0.80) analyses were also similar. Qualitative and quantitative CMR analysis methods show similar diagnostic accuracy for the diagnosis of AM. These findings suggest that a simplified approach using a shortened CMR protocol including only T2-weighted STIR sequences might be useful to rule out AM in patients with acute coronary syndrome and normal coronary angiography.

Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results

NASA Astrophysics Data System (ADS)

Tanaka, R.; Sanada, S.; Oda, M.; Mitsutaka, M.; Suzuki, K.; Sakuta, K.; Kawashima, H.

2014-03-01

Rib movement during respiration is one of the diagnostic criteria in pulmonary impairments. In general, the rib movement is assessed in fluoroscopy. However, the shadows of lung vessels and bronchi overlapping ribs prevent accurate quantitative analysis of rib movement. Recently, an image-processing technique for separating bones from soft tissue in static chest radiographs, called "bone suppression technique", has been developed. Our purpose in this study was to evaluate the usefulness of dynamic bone images created by the bone suppression technique in quantitative analysis of rib movement. Dynamic chest radiographs of 10 patients were obtained using a dynamic flat-panel detector (FPD). Bone suppression technique based on a massive-training artificial neural network (MTANN) was applied to the dynamic chest images to create bone images. Velocity vectors were measured in local areas on the dynamic bone images, which formed a map. The velocity maps obtained with bone and original images for scoliosis and normal cases were compared to assess the advantages of bone images. With dynamic bone images, we were able to quantify and distinguish movements of ribs from those of other lung structures accurately. Limited rib movements of scoliosis patients appeared as reduced rib velocity vectors. Vector maps in all normal cases exhibited left-right symmetric distributions, whereas those in abnormal cases showed nonuniform distributions. In conclusion, dynamic bone images were useful for accurate quantitative analysis of rib movements: Limited rib movements were indicated as a reduction of rib movement and left-right asymmetric distribution on vector maps. Thus, dynamic bone images can be a new diagnostic tool for quantitative analysis of rib movements without additional radiation dose.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Supramolecular assembly affording a ratiometric two-photon fluorescent nanoprobe for quantitative detection and bioimaging.

PubMed

Wang, Peng; Zhang, Cheng; Liu, Hong-Wen; Xiong, Mengyi; Yin, Sheng-Yan; Yang, Yue; Hu, Xiao-Xiao; Yin, Xia; Zhang, Xiao-Bing; Tan, Weihong

2017-12-01

Fluorescence quantitative analyses for vital biomolecules are in great demand in biomedical science owing to their unique detection advantages with rapid, sensitive, non-damaging and specific identification. However, available fluorescence strategies for quantitative detection are usually hard to design and achieve. Inspired by supramolecular chemistry, a two-photon-excited fluorescent supramolecular nanoplatform ( TPSNP ) was designed for quantitative analysis with three parts: host molecules (β-CD polymers), a guest fluorophore of sensing probes (Np-Ad) and a guest internal reference (NpRh-Ad). In this strategy, the TPSNP possesses the merits of (i) improved water-solubility and biocompatibility; (ii) increased tissue penetration depth for bioimaging by two-photon excitation; (iii) quantitative and tunable assembly of functional guest molecules to obtain optimized detection conditions; (iv) a common approach to avoid the limitation of complicated design by adjustment of sensing probes; and (v) accurate quantitative analysis by virtue of reference molecules. As a proof-of-concept, we utilized the two-photon fluorescent probe NHS-Ad-based TPSNP-1 to realize accurate quantitative analysis of hydrogen sulfide (H 2 S), with high sensitivity and good selectivity in live cells, deep tissues and ex vivo -dissected organs, suggesting that the TPSNP is an ideal quantitative indicator for clinical samples. What's more, TPSNP will pave the way for designing and preparing advanced supramolecular sensors for biosensing and biomedicine.

QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

PubMed

Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

2015-11-03

We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

The Brain Network for Deductive Reasoning: A Quantitative Meta-analysis of 28 Neuroimaging Studies

PubMed Central

Prado, Jérôme; Chadha, Angad; Booth, James R.

2011-01-01

Over the course of the past decade, contradictory claims have been made regarding the neural bases of deductive reasoning. Researchers have been puzzled by apparent inconsistencies in the literature. Some have even questioned the effectiveness of the methodology used to study the neural bases of deductive reasoning. However, the idea that neuroimaging findings are inconsistent is not based on any quantitative evidence. Here, we report the results of a quantitative meta-analysis of 28 neuroimaging studies of deductive reasoning published between 1997 and 2010, combining 382 participants. Consistent areas of activations across studies were identified using the multilevel kernel density analysis method. We found that results from neuroimaging studies are more consistent than what has been previously assumed. Overall, studies consistently report activations in specific regions of a left fronto-parietal system, as well as in the left Basal Ganglia. This brain system can be decomposed into three subsystems that are specific to particular types of deductive arguments: relational, categorical, and propositional. These dissociations explain inconstancies in the literature. However, they are incompatible with the notion that deductive reasoning is supported by a single cognitive system relying either on visuospatial or rule-based mechanisms. Our findings provide critical insight into the cognitive organization of deductive reasoning and need to be accounted for by cognitive theories. PMID:21568632

[A new method of processing quantitative PCR data].

PubMed

Ke, Bing-Shen; Li, Guang-Yun; Chen, Shi-Min; Huang, Xiang-Yan; Chen, Ying-Jian; Xu, Jun

2003-05-01

Today standard PCR can't satisfy the need of biotechnique development and clinical research any more. After numerous dynamic research, PE company found there is a linear relation between initial template number and cycling time when the accumulating fluorescent product is detectable.Therefore,they developed a quantitative PCR technique to be used in PE7700 and PE5700. But the error of this technique is too great to satisfy the need of biotechnique development and clinical research. A better quantitative PCR technique is needed. The mathematical model submitted here is combined with the achievement of relative science,and based on the PCR principle and careful analysis of molecular relationship of main members in PCR reaction system. This model describes the function relation between product quantity or fluorescence intensity and initial template number and other reaction conditions, and can reflect the accumulating rule of PCR product molecule accurately. Accurate quantitative PCR analysis can be made use this function relation. Accumulated PCR product quantity can be obtained from initial template number. Using this model to do quantitative PCR analysis,result error is only related to the accuracy of fluorescence intensity or the instrument used. For an example, when the fluorescence intensity is accurate to 6 digits and the template size is between 100 to 1,000,000, the quantitative result accuracy will be more than 99%. The difference of result error is distinct using same condition,same instrument but different analysis method. Moreover,if the PCR quantitative analysis system is used to process data, it will get result 80 times of accuracy than using CT method.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

New insight in quantitative analysis of vascular permeability during immune reaction (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kalchenko, Vyacheslav; Molodij, Guillaume; Kuznetsov, Yuri; Smolyakov, Yuri; Israeli, David; Meglinski, Igor; Harmelin, Alon

2016-03-01

The use of fluorescence imaging of vascular permeability becomes a golden standard for assessing the inflammation process during experimental immune response in vivo. The use of the optical fluorescence imaging provides a very useful and simple tool to reach this purpose. The motivation comes from the necessity of a robust and simple quantification and data presentation of inflammation based on a vascular permeability. Changes of the fluorescent intensity, as a function of time is a widely accepted method to assess the vascular permeability during inflammation related to the immune response. In the present study we propose to bring a new dimension by applying a more sophisticated approach to the analysis of vascular reaction by using a quantitative analysis based on methods derived from astronomical observations, in particular by using a space-time Fourier filtering analysis followed by a polynomial orthogonal modes decomposition. We demonstrate that temporal evolution of the fluorescent intensity observed at certain pixels correlates quantitatively to the blood flow circulation at normal conditions. The approach allows to determine the regions of permeability and monitor both the fast kinetics related to the contrast material distribution in the circulatory system and slow kinetics associated with extravasation of the contrast material. Thus, we introduce a simple and convenient method for fast quantitative visualization of the leakage related to the inflammatory (immune) reaction in vivo.

Quality evaluation of LC-MS/MS-based E. coli H antigen typing (MS-H) through label-free quantitative data analysis in a clinical sample setup.

PubMed

Cheng, Keding; Sloan, Angela; McCorrister, Stuart; Peterson, Lorea; Chui, Huixia; Drebot, Mike; Nadon, Celine; Knox, J David; Wang, Gehua

2014-12-01

The need for rapid and accurate H typing is evident during Escherichia coli outbreak situations. This study explores the transition of MS-H, a method originally developed for rapid H antigen typing of E. coli using LC-MS/MS of flagella digest of reference strains and some clinical strains, to E. coli isolates in clinical scenario through quantitative analysis and method validation. Motile and nonmotile strains were examined in batches to simulate clinical sample scenario. Various LC-MS/MS batch run procedures and MS-H typing rules were compared and summarized through quantitative analysis of MS-H data output for a standard method development. Label-free quantitative data analysis of MS-H typing was proven very useful for examining the quality of MS-H result and the effects of some sample carryovers from motile E. coli isolates. Based on this, a refined procedure and protein identification rule specific for clinical MS-H typing was established and validated. With LC-MS/MS batch run procedure and database search parameter unique for E. coli MS-H typing, the standard procedure maintained high accuracy and specificity in clinical situations, and its potential to be used in a clinical setting was clearly established. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

USGS Publications Warehouse

Anderson, Ryan; Clegg, Samuel M.; Frydenvang, Jens; Wiens, Roger C.; McLennan, Scott M.; Morris, Richard V.; Ehlmann, Bethany L.; Dyar, M. Darby

2017-01-01

Accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response of an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “sub-model” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. The sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.

Analysis of swimming performance: perceptions and practices of US-based swimming coaches.

PubMed

Mooney, Robert; Corley, Gavin; Godfrey, Alan; Osborough, Conor; Newell, John; Quinlan, Leo Richard; ÓLaighin, Gearóid

2016-01-01

In elite swimming, a broad range of methods are used to assess performance, inform coaching practices and monitor athletic progression. The aim of this paper was to examine the performance analysis practices of swimming coaches and to explore the reasons behind the decisions that coaches take when analysing performance. Survey data were analysed from 298 Level 3 competitive swimming coaches (245 male, 53 female) based in the United States. Results were compiled to provide a generalised picture of practices and perceptions and to examine key emerging themes. It was found that a disparity exists between the importance swim coaches place on biomechanical analysis of swimming performance and the types of analyses that are actually conducted. Video-based methods are most frequently employed, with over 70% of coaches using these methods at least monthly, with analyses being mainly qualitative in nature rather than quantitative. Barriers to the more widespread use of quantitative biomechanical analysis in elite swimming environments were explored. Constraints include time, cost and availability of resources, but other factors such as sources of information on swimming performance and analysis and control over service provision are also discussed, with particular emphasis on video-based methods and emerging sensor-based technologies.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

PubMed

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

NASA Astrophysics Data System (ADS)

Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

2017-10-01

The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

Microstructural study of the nickel-base alloy WAZ-20 using qualitative and quantitative electron optical techniques

NASA Technical Reports Server (NTRS)

Young, S. G.

1973-01-01

The NASA nickel-base alloy WAZ-20 was analyzed by advanced metallographic techniques to qualitatively and quantitatively characterize its phases and stability. The as-cast alloy contained primary gamma-prime, a coarse gamma-gamma prime eutectic, a gamma-fine gamma prime matrix, and MC carbides. A specimen aged at 870 C for 1000 hours contained these same constituents and a few widely scattered high W particles. No detrimental phases (such as sigma or mu) were observed. Scanning electron microscope, light metallography, and replica electron microscope methods are compared. The value of quantitative electron microprobe techniques such as spot and area analysis is demonstrated.

Automated detection of arterial input function in DSC perfusion MRI in a stroke rat model

NASA Astrophysics Data System (ADS)

Yeh, M.-Y.; Lee, T.-H.; Yang, S.-T.; Kuo, H.-H.; Chyi, T.-K.; Liu, H.-L.

2009-05-01

Quantitative cerebral blood flow (CBF) estimation requires deconvolution of the tissue concentration time curves with an arterial input function (AIF). However, image-based determination of AIF in rodent is challenged due to limited spatial resolution. We evaluated the feasibility of quantitative analysis using automated AIF detection and compared the results with commonly applied semi-quantitative analysis. Permanent occlusion of bilateral or unilateral common carotid artery was used to induce cerebral ischemia in rats. The image using dynamic susceptibility contrast method was performed on a 3-T magnetic resonance scanner with a spin-echo echo-planar-image sequence (TR/TE = 700/80 ms, FOV = 41 mm, matrix = 64, 3 slices, SW = 2 mm), starting from 7 s prior to contrast injection (1.2 ml/kg) at four different time points. For quantitative analysis, CBF was calculated by the AIF which was obtained from 10 voxels with greatest contrast enhancement after deconvolution. For semi-quantitative analysis, relative CBF was estimated by the integral divided by the first moment of the relaxivity time curves. We observed if the AIFs obtained in the three different ROIs (whole brain, hemisphere without lesion and hemisphere with lesion) were similar, the CBF ratios (lesion/normal) between quantitative and semi-quantitative analyses might have a similar trend at different operative time points. If the AIFs were different, the CBF ratios might be different. We concluded that using local maximum one can define proper AIF without knowing the anatomical location of arteries in a stroke rat model.

42 CFR 82.17 - What types of information could be used to supplement or substitute for individual monitoring data?

Code of Federal Regulations, 2014 CFR

2014-10-01

... SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED... environment; or, (b) A quantitative characterization of the radiation environment in which the covered... quantitative characterization of the radiation environment in which the employee worked, based on analysis of...

Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales

Treesearch

Lisa A. Schulte; David J. Mladenoff; Erik V. Nordheim

2002-01-01

We developed a quantitative and replicable classification system to improve understanding of historical composition and structure within northern Wisconsin's forests. The classification system was based on statistical cluster analysis and two forest metrics, relative dominance (% basal area) and relative importance (mean of relative dominance and relative density...

42 CFR 82.17 - What types of information could be used to supplement or substitute for individual monitoring data?

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED... environment; or, (b) A quantitative characterization of the radiation environment in which the covered... quantitative characterization of the radiation environment in which the employee worked, based on analysis of...

42 CFR 82.17 - What types of information could be used to supplement or substitute for individual monitoring data?

Code of Federal Regulations, 2012 CFR

2012-10-01

... SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED... environment; or, (b) A quantitative characterization of the radiation environment in which the covered... quantitative characterization of the radiation environment in which the employee worked, based on analysis of...

42 CFR 82.17 - What types of information could be used to supplement or substitute for individual monitoring data?

Code of Federal Regulations, 2013 CFR

2013-10-01

... SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED... environment; or, (b) A quantitative characterization of the radiation environment in which the covered... quantitative characterization of the radiation environment in which the employee worked, based on analysis of...

42 CFR 82.17 - What types of information could be used to supplement or substitute for individual monitoring data?

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED... environment; or, (b) A quantitative characterization of the radiation environment in which the covered... quantitative characterization of the radiation environment in which the employee worked, based on analysis of...

Quantitative refractive index distribution of single cell by combining phase-shifting interferometry and AFM imaging.

PubMed

Zhang, Qinnan; Zhong, Liyun; Tang, Ping; Yuan, Yingjie; Liu, Shengde; Tian, Jindong; Lu, Xiaoxu

2017-05-31

Cell refractive index, an intrinsic optical parameter, is closely correlated with the intracellular mass and concentration. By combining optical phase-shifting interferometry (PSI) and atomic force microscope (AFM) imaging, we constructed a label free, non-invasive and quantitative refractive index of single cell measurement system, in which the accurate phase map of single cell was retrieved with PSI technique and the cell morphology with nanoscale resolution was achieved with AFM imaging. Based on the proposed AFM/PSI system, we achieved quantitative refractive index distributions of single red blood cell and Jurkat cell, respectively. Further, the quantitative change of refractive index distribution during Daunorubicin (DNR)-induced Jurkat cell apoptosis was presented, and then the content changes of intracellular biochemical components were achieved. Importantly, these results were consistent with Raman spectral analysis, indicating that the proposed PSI/AFM based refractive index system is likely to become a useful tool for intracellular biochemical components analysis measurement, and this will facilitate its application for revealing cell structure and pathological state from a new perspective.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Risk analysis for veterinary biologicals released into the environment.

PubMed

Silva, S V; Samagh, B S; Morley, R S

1995-12-01

All veterinary biologicals licensed in Canada must be shown to be pure, potent, safe and effective. A risk-based approach is used to evaluate the safety of all biologicals, whether produced by conventional methods or by molecular biological techniques. Traditionally, qualitative risk assessment methods have been used for this purpose. More recently, quantitative risk assessment has become available for complex issues. The quantitative risk assessment method uses "scenario tree analysis' to predict the likelihood of various outcomes and their respective impacts. The authors describe the quantitative risk assessment approach which is used within the broader context of risk analysis (i.e. risk assessment, risk management and risk communication) to develop recommendations for the field release of veterinary biologicals. The general regulatory framework for the licensing of veterinary biologicals in Canada is also presented.

Management Approaches to Stomal and Peristomal Complications: A Narrative Descriptive Study.

PubMed

Beitz, Janice M; Colwell, Janice C

2016-01-01

The purpose of this study was to identify optimal interventions for selected complications based on WOC nurse experts' judgment/expertise. A cross-sectional quantitative descriptive design with qualitative, narrative-type components was used for this study. Following validation rating of appropriateness of interventions and quantitative rankings of first-, second-, and third-line approaches, participants provided substantive handwritten narrative comments about listed interventions. Comments were organized and prioritized using frequency count. Narrative comments reflected the quantitative rankings of efficacy of approaches. Clinicians offered further specific suggestions regarding product use and progression of care for selected complications. Narrative analysis using descriptive quantitative frequency count supported the rankings of most preferred treatments of selected stomal and peristomal complications. Findings add to the previous research on prioritized approaches and evidence-based practice in ostomy care.

Improved cardiac motion detection from ultrasound images using TDIOF: a combined B-mode/ tissue Doppler approach

NASA Astrophysics Data System (ADS)

Tavakoli, Vahid; Stoddard, Marcus F.; Amini, Amir A.

2013-03-01

Quantitative motion analysis of echocardiographic images helps clinicians with the diagnosis and therapy of patients suffering from cardiac disease. Quantitative analysis is usually based on TDI (Tissue Doppler Imaging) or speckle tracking. These methods are based on two independent techniques - the Doppler Effect and image registration, respectively. In order to increase the accuracy of the speckle tracking technique and cope with the angle dependency of TDI, herein, a combined approach dubbed TDIOF (Tissue Doppler Imaging Optical Flow) is proposed. TDIOF is formulated based on the combination of B-mode and Doppler energy terms in an optical flow framework and minimized using algebraic equations. In this paper, we report on validations with simulated, physical cardiac phantom, and in-vivo patient data. It is shown that the additional Doppler term is able to increase the accuracy of speckle tracking, the basis for several commercially available echocardiography analysis techniques.

Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven

2006-01-01

A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

The Analysis of Seawater: A Laboratory-Centered Learning Project in General Chemistry.

ERIC Educational Resources Information Center

Selco, Jodye I.; Roberts, Julian L., Jr.; Wacks, Daniel B.

2003-01-01

Describes a sea-water analysis project that introduces qualitative and quantitative analysis methods and laboratory methods such as gravimetric analysis, potentiometric titration, ion-selective electrodes, and the use of calibration curves. Uses a problem-based cooperative teaching approach. (Contains 24 references.) (YDS)

Quantitative prediction of phase transformations in silicon during nanoindentation

NASA Astrophysics Data System (ADS)

Zhang, Liangchi; Basak, Animesh

2013-08-01

This paper establishes the first quantitative relationship between the phases transformed in silicon and the shape characteristics of nanoindentation curves. Based on an integrated analysis using TEM and unit cell properties of phases, the volumes of the phases emerged in a nanoindentation are formulated as a function of pop-out size and depth of nanoindentation impression. This simple formula enables a fast, accurate and quantitative prediction of the phases in a nanoindentation cycle, which has been impossible before.

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

PubMed

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method frequently correspond to subregions of visible spots that may represent post-translational modifications or co-migrating proteins that cannot be visually resolved from adjacent, more abundant proteins on the gel image. Thus, it is possible that this image-based approach may actually improve the realized resolution of the gel, revealing differentially expressed proteins that would not have even been detected as spots by modern spot-based analyses.

A new strategy for statistical analysis-based fingerprint establishment: Application to quality assessment of Semen sojae praeparatum.

PubMed

Guo, Hui; Zhang, Zhen; Yao, Yuan; Liu, Jialin; Chang, Ruirui; Liu, Zhao; Hao, Hongyuan; Huang, Taohong; Wen, Jun; Zhou, Tingting

2018-08-30

Semen sojae praeparatum with homology of medicine and food is a famous traditional Chinese medicine. A simple and effective quality fingerprint analysis, coupled with chemometrics methods, was developed for quality assessment of Semen sojae praeparatum. First, similarity analysis (SA) and hierarchical clusting analysis (HCA) were applied to select the qualitative markers, which obviously influence the quality of Semen sojae praeparatum. 21 chemicals were selected and characterized by high resolution ion trap/time-of-flight mass spectrometry (LC-IT-TOF-MS). Subsequently, principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to select the quantitative markers of Semen sojae praeparatum samples from different origins. Moreover, 11 compounds with statistical significance were determined quantitatively, which provided an accurate and informative data for quality evaluation. This study proposes a new strategy for "statistic analysis-based fingerprint establishment", which would be a valuable reference for further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

ICP-MS as a novel detection system for quantitative element-tagged immunoassay of hidden peanut allergens in foods.

PubMed

Careri, Maria; Elviri, Lisa; Mangia, Alessandro; Mucchino, Claudio

2007-03-01

A novel ICP-MS-based ELISA immunoassay via element-tagged determination was devised for quantitative analysis of hidden allergens in food. The method was able to detect low amounts of peanuts (down to approximately 2 mg peanuts kg(-1) cereal-based matrix) by using a europium-tagged antibody. Selectivity was proved by the lack of detectable cross-reaction with a number of protein-rich raw materials.

Size-adjusted Quantitative Gleason Score as a Predictor of Biochemical Recurrence after Radical Prostatectomy.

PubMed

Deng, Fang-Ming; Donin, Nicholas M; Pe Benito, Ruth; Melamed, Jonathan; Le Nobin, Julien; Zhou, Ming; Ma, Sisi; Wang, Jinhua; Lepor, Herbert

2016-08-01

The risk of biochemical recurrence (BCR) following radical prostatectomy for pathologic Gleason 7 prostate cancer varies according to the proportion of Gleason 4 component. We sought to explore the value of several novel quantitative metrics of Gleason 4 disease for the prediction of BCR in men with Gleason 7 disease. We analyzed a cohort of 2630 radical prostatectomy cases from 1990-2007. All pathologic Gleason 7 cases were identified and assessed for quantity of Gleason pattern 4. Three methods were used to quantify the extent of Gleason 4: a quantitative Gleason score (qGS) based on the proportion of tumor composed of Gleason pattern 4, a size-weighted score (swGS) incorporating the overall quantity of Gleason 4, and a size index (siGS) incorporating the quantity of Gleason 4 based on the index lesion. Associations between the above metrics and BCR were evaluated using Cox proportional hazards regression analysis. qGS, swGS, and siGS were significantly associated with BCR on multivariate analysis when adjusted for traditional Gleason score, age, prostate specific antigen, surgical margin, and stage. Using Harrell's c-index to compare the scoring systems, qGS (0.83), swGS (0.84), and siGS (0.84) all performed better than the traditional Gleason score (0.82). Quantitative measures of Gleason pattern 4 predict BCR better than the traditional Gleason score. In men with Gleason 7 prostate cancer, quantitative analysis of the proportion of Gleason pattern 4 (quantitative Gleason score), as well as size-weighted measurement of Gleason 4 (size-weighted Gleason score), and a size-weighted measurement of Gleason 4 based on the largest tumor nodule significantly improve the predicted risk of biochemical recurrence compared with the traditional Gleason score. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Classification-based quantitative analysis of stable isotope labeling by amino acids in cell culture (SILAC) data.

PubMed

Kim, Seongho; Carruthers, Nicholas; Lee, Joohyoung; Chinni, Sreenivasa; Stemmer, Paul

2016-12-01

Stable isotope labeling by amino acids in cell culture (SILAC) is a practical and powerful approach for quantitative proteomic analysis. A key advantage of SILAC is the ability to simultaneously detect the isotopically labeled peptides in a single instrument run and so guarantee relative quantitation for a large number of peptides without introducing any variation caused by separate experiment. However, there are a few approaches available to assessing protein ratios and none of the existing algorithms pays considerable attention to the proteins having only one peptide hit. We introduce new quantitative approaches to dealing with SILAC protein-level summary using classification-based methodologies, such as Gaussian mixture models with EM algorithms and its Bayesian approach as well as K-means clustering. In addition, a new approach is developed using Gaussian mixture model and a stochastic, metaheuristic global optimization algorithm, particle swarm optimization (PSO), to avoid either a premature convergence or being stuck in a local optimum. Our simulation studies show that the newly developed PSO-based method performs the best among others in terms of F1 score and the proposed methods further demonstrate the ability of detecting potential markers through real SILAC experimental data. No matter how many peptide hits the protein has, the developed approach can be applicable, rescuing many proteins doomed to removal. Furthermore, no additional correction for multiple comparisons is necessary for the developed methods, enabling direct interpretation of the analysis outcomes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multidimensional electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) for quantitative analysis of the proteome and phosphoproteome in clinical and biomedical research.

PubMed

Loroch, Stefan; Schommartz, Tim; Brune, Wolfram; Zahedi, René Peiman; Sickmann, Albert

2015-05-01

Quantitative proteomics and phosphoproteomics have become key disciplines in understanding cellular processes. Fundamental research can be done using cell culture providing researchers with virtually infinite sample amounts. In contrast, clinical, pre-clinical and biomedical research is often restricted to minute sample amounts and requires an efficient analysis with only micrograms of protein. To address this issue, we generated a highly sensitive workflow for combined LC-MS-based quantitative proteomics and phosphoproteomics by refining an ERLIC-based 2D phosphoproteomics workflow into an ERLIC-based 3D workflow covering the global proteome as well. The resulting 3D strategy was successfully used for an in-depth quantitative analysis of both, the proteome and the phosphoproteome of murine cytomegalovirus-infected mouse fibroblasts, a model system for host cell manipulation by a virus. In a 2-plex SILAC experiment with 150 μg of a tryptic digest per condition, the 3D strategy enabled the quantification of ~75% more proteins and even ~134% more peptides compared to the 2D strategy. Additionally, we could quantify ~50% more phosphoproteins by non-phosphorylated peptides, concurrently yielding insights into changes on the levels of protein expression and phosphorylation. Beside its sensitivity, our novel three-dimensional ERLIC-strategy has the potential for semi-automated sample processing rendering it a suitable future perspective for clinical, pre-clinical and biomedical research. Copyright © 2015. Published by Elsevier B.V.

A review of state-of-the-art stereology for better quantitative 3D morphology in cardiac research.

PubMed

Mühlfeld, Christian; Nyengaard, Jens Randel; Mayhew, Terry M

2010-01-01

The aim of stereological methods in biomedical research is to obtain quantitative information about three-dimensional (3D) features of tissues, cells, or organelles from two-dimensional physical or optical sections. With immunogold labeling, stereology can even be used for the quantitative analysis of the distribution of molecules within tissues and cells. Nowadays, a large number of design-based stereological methods offer an efficient quantitative approach to intriguing questions in cardiac research, such as "Is there a significant loss of cardiomyocytes during progression from ventricular hypertrophy to heart failure?" or "Does a specific treatment reduce the degree of fibrosis in the heart?" Nevertheless, the use of stereological methods in cardiac research is rare. The present review article demonstrates how some of the potential pitfalls in quantitative microscopy may be avoided. To this end, we outline the concepts of design-based stereology and illustrate their practical applications to a wide range of biological questions in cardiac research. We hope that the present article will stimulate researchers in cardiac research to incorporate design-based stereology into their study designs, thus promoting an unbiased quantitative 3D microscopy.

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide-based quantitative proteomics.

PubMed

Liu, Kehui; Zhang, Jiyang; Fu, Bin; Xie, Hongwei; Wang, Yingchun; Qian, Xiaohong

2014-07-01

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative twoplex glycan analysis using 12C6 and 13C6 stable isotope 2-aminobenzoic acid labelling and capillary electrophoresis mass spectrometry.

PubMed

Váradi, Csaba; Mittermayr, Stefan; Millán-Martín, Silvia; Bones, Jonathan

2016-12-01

Capillary electrophoresis (CE) offers excellent efficiency and orthogonality to liquid chromatographic (LC) separations for oligosaccharide structural analysis. Combination of CE with high resolution mass spectrometry (MS) for glycan analysis remains a challenging task due to the MS incompatibility of background electrolyte buffers and additives commonly used in offline CE separations. Here, a novel method is presented for the analysis of 2-aminobenzoic acid (2-AA) labelled glycans by capillary electrophoresis coupled to mass spectrometry (CE-MS). To ensure maximum resolution and excellent precision without the requirement for excessive analysis times, CE separation conditions including the concentration and pH of the background electrolyte, the effect of applied pressure on the capillary inlet and the capillary length were evaluated. Using readily available 12/13 C 6 stable isotopologues of 2-AA, the developed method can be applied for quantitative glycan profiling in a twoplex manner based on the generation of extracted ion electropherograms (EIE) for 12 C 6 'light' and 13 C 6 'heavy' 2-AA labelled glycan isotope clusters. The twoplex quantitative CE-MS glycan analysis platform is ideally suited for comparability assessment of biopharmaceuticals, such as monoclonal antibodies, for differential glycomic analysis of clinical material for potential biomarker discovery or for quantitative microheterogeneity analysis of different glycosylation sites within a glycoprotein. Additionally, due to the low injection volume requirements of CE, subsequent LC-MS analysis of the same sample can be performed facilitating the use of orthogonal separation techniques for structural elucidation or verification of quantitative performance.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

NASA Astrophysics Data System (ADS)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Quantitative Appearance Inspection for Film Coated Tablets.

PubMed

Yoshino, Hiroyuki; Yamashita, Kazunari; Iwao, Yasunori; Noguchi, Shuji; Itai, Shigeru

2016-01-01

The decision criteria for the physical appearance of pharmaceutical products are subjective and qualitative means of evaluation that are based entirely on human interpretation. In this study, we have developed a comprehensive method for the quantitative analysis of the physical appearance of film coated tablets. Three different kinds of film coated tablets with considerable differences in their physical appearances were manufactured as models, and their surface roughness, contact angle, color measurements and physicochemical properties were investigated as potential characteristics for the quantitative analysis of their physical appearance. All of these characteristics were useful for the quantitative evaluation of the physical appearances of the tablets, and could potentially be used to establish decision criteria to assess the quality of tablets. In particular, the analysis of the surface roughness and film coating properties of the tablets by terahertz spectroscopy allowed for an effective evaluation of the tablets' properties. These results indicated the possibility of inspecting the appearance of tablets during the film coating process.

Analysis of Ergot Alkaloids

PubMed Central

Crews, Colin

2015-01-01

The principles and application of established and newer methods for the quantitative and semi-quantitative determination of ergot alkaloids in food, feed, plant materials and animal tissues are reviewed. The techniques of sampling, extraction, clean-up, detection, quantification and validation are described. The major procedures for ergot alkaloid analysis comprise liquid chromatography with tandem mass spectrometry (LC-MS/MS) and liquid chromatography with fluorescence detection (LC-FLD). Other methods based on immunoassays are under development and variations of these and minor techniques are available for specific purposes. PMID:26046699

A computer system to be used with laser-based endoscopy for quantitative diagnosis of early gastric cancer.

PubMed

Miyaki, Rie; Yoshida, Shigeto; Tanaka, Shinji; Kominami, Yoko; Sanomura, Yoji; Matsuo, Taiji; Oka, Shiro; Raytchev, Bisser; Tamaki, Toru; Koide, Tetsushi; Kaneda, Kazufumi; Yoshihara, Masaharu; Chayama, Kazuaki

2015-02-01

To evaluate the usefulness of a newly devised computer system for use with laser-based endoscopy in differentiating between early gastric cancer, reddened lesions, and surrounding tissue. Narrow-band imaging based on laser light illumination has come into recent use. We devised a support vector machine (SVM)-based analysis system to be used with the newly devised endoscopy system to quantitatively identify gastric cancer on images obtained by magnifying endoscopy with blue-laser imaging (BLI). We evaluated the usefulness of the computer system in combination with the new endoscopy system. We evaluated the system as applied to 100 consecutive early gastric cancers in 95 patients examined by BLI magnification at Hiroshima University Hospital. We produced a set of images from the 100 early gastric cancers; 40 flat or slightly depressed, small, reddened lesions; and surrounding tissues, and we attempted to identify gastric cancer, reddened lesions, and surrounding tissue quantitatively. The average SVM output value was 0.846 ± 0.220 for cancerous lesions, 0.381 ± 0.349 for reddened lesions, and 0.219 ± 0.277 for surrounding tissue, with the SVM output value for cancerous lesions being significantly greater than that for reddened lesions or surrounding tissue. The average SVM output value for differentiated-type cancer was 0.840 ± 0.207 and for undifferentiated-type cancer was 0.865 ± 0.259. Although further development is needed, we conclude that our computer-based analysis system used with BLI will identify gastric cancers quantitatively.

Development of scan analysis techniques employing a small computer. Final report, February 1, 1963--July 31, 1976

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1976-08-05

During the thirteen year duration of this contract the goal has been to develop and apply computer based analysis of radionuclide scan data so as to make available improved diagnostic information based on a knowledge of localized quantitative estimates of radionuclide concentration. Results are summarized. (CH)

Quantitative methods for compensation of matrix effects and self-absorption in Laser Induced Breakdown Spectroscopy signals of solids

NASA Astrophysics Data System (ADS)

Takahashi, Tomoko; Thornton, Blair

2017-12-01

This paper reviews methods to compensate for matrix effects and self-absorption during quantitative analysis of compositions of solids measured using Laser Induced Breakdown Spectroscopy (LIBS) and their applications to in-situ analysis. Methods to reduce matrix and self-absorption effects on calibration curves are first introduced. The conditions where calibration curves are applicable to quantification of compositions of solid samples and their limitations are discussed. While calibration-free LIBS (CF-LIBS), which corrects matrix effects theoretically based on the Boltzmann distribution law and Saha equation, has been applied in a number of studies, requirements need to be satisfied for the calculation of chemical compositions to be valid. Also, peaks of all elements contained in the target need to be detected, which is a bottleneck for in-situ analysis of unknown materials. Multivariate analysis techniques are gaining momentum in LIBS analysis. Among the available techniques, principal component regression (PCR) analysis and partial least squares (PLS) regression analysis, which can extract related information to compositions from all spectral data, are widely established methods and have been applied to various fields including in-situ applications in air and for planetary explorations. Artificial neural networks (ANNs), where non-linear effects can be modelled, have also been investigated as a quantitative method and their applications are introduced. The ability to make quantitative estimates based on LIBS signals is seen as a key element for the technique to gain wider acceptance as an analytical method, especially in in-situ applications. In order to accelerate this process, it is recommended that the accuracy should be described using common figures of merit which express the overall normalised accuracy, such as the normalised root mean square errors (NRMSEs), when comparing the accuracy obtained from different setups and analytical methods.

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

The other half of the story: effect size analysis in quantitative research.

PubMed

Maher, Jessica Middlemis; Markey, Jonathan C; Ebert-May, Diane

2013-01-01

Statistical significance testing is the cornerstone of quantitative research, but studies that fail to report measures of effect size are potentially missing a robust part of the analysis. We provide a rationale for why effect size measures should be included in quantitative discipline-based education research. Examples from both biological and educational research demonstrate the utility of effect size for evaluating practical significance. We also provide details about some effect size indices that are paired with common statistical significance tests used in educational research and offer general suggestions for interpreting effect size measures. Finally, we discuss some inherent limitations of effect size measures and provide further recommendations about reporting confidence intervals.

Quantitative capillary electrophoresis and its application in analysis of alkaloids in tea, coffee, coca cola, and theophylline tablets.

PubMed

Li, Mengjia; Zhou, Junyi; Gu, Xue; Wang, Yan; Huang, Xiaojing; Yan, Chao

2009-01-01

A quantitative CE (qCE) system with high precision has been developed, in which a 4-port nano-valve was isolated from the electric field and served as sample injector. The accurate amount of sample was introduced into the CE system with high reproducibility. Based on this system, consecutive injections and separations were performed without voltage interruption. Reproducibilities in terms of RSD lower than 0.8% for retention time and 1.7% for peak area were achieved. The effectiveness of the system was demonstrated by the quantitative analysis of caffeine, theobromine, and theophylline in real samples, such as tea leaf, roasted coffee, coca cola, and theophylline tablets.

To label or not to label: applications of quantitative proteomics in neuroscience research.

PubMed

Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

2012-02-01

Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Photometric Determination of Ammonium and Phosphate in Seawater Medium Using a Microplate Reader.

PubMed

Ruppersberg, Hanna S; Goebel, Maren R; Kleinert, Svea I; Wünsch, Daniel; Trautwein, Kathleen; Rabus, Ralf

2017-01-01

To more efficiently process the large sample numbers for quantitative determination of ammonium (NH4+) and phosphate (orthophosphate, PO43-) generated during comprehensive growth experiments with the marine Roseobacter group member Phaeobacter inhibens DSM 17395, specific colorimetric assays employing a microplate reader (MPR) were established. The NH4+ assay is based on the reaction of NH4+ with hypochlorite and salicylate, yielding a limit of detection of 14 µM, a limit of quantitation of 36 µM, and a linear range for quantitative determination up to 200 µM. The PO43-assay is based on the complex formation of PO43- with ammonium molybdate in the presence of ascorbate and zinc acetate, yielding a limit of detection of 13 µM, a limit of quantitation of 50 µM, and a linear range for quantitative determination up to 1 mM. Both MPR-based assays allowed for fast (significantly lower than 1 h) analysis of 21 samples plus standards for calibration (all measured in triplicates) and showed only low variation across a large collection of biological samples. © 2017 S. Karger AG, Basel.

Quantitative and qualitative measure of intralaboratory two-dimensional protein gel reproducibility and the effects of sample preparation, sample load, and image analysis.

PubMed

Choe, Leila H; Lee, Kelvin H

2003-10-01

We investigate one approach to assess the quantitative variability in two-dimensional gel electrophoresis (2-DE) separations based on gel-to-gel variability, sample preparation variability, sample load differences, and the effect of automation on image analysis. We observe that 95% of spots present in three out of four replicate gels exhibit less than a 0.52 coefficient of variation (CV) in fluorescent stain intensity (% volume) for a single sample run on multiple gels. When four parallel sample preparations are performed, this value increases to 0.57. We do not observe any significant change in quantitative value for an increase or decrease in sample load of 30% when using appropriate image analysis variables. Increasing use of automation, while necessary in modern 2-DE experiments, does change the observed level of quantitative and qualitative variability among replicate gels. The number of spots that change qualitatively for a single sample run in parallel varies from a CV = 0.03 for fully manual analysis to CV = 0.20 for a fully automated analysis. We present a systematic method by which a single laboratory can measure gel-to-gel variability using only three gel runs.

Risk Factors for Chronic Subdural Hematoma Recurrence Identified Using Quantitative Computed Tomography Analysis of Hematoma Volume and Density.

PubMed

Stavrinou, Pantelis; Katsigiannis, Sotirios; Lee, Jong Hun; Hamisch, Christina; Krischek, Boris; Mpotsaris, Anastasios; Timmer, Marco; Goldbrunner, Roland

2017-03-01

Chronic subdural hematoma (CSDH), a common condition in elderly patients, presents a therapeutic challenge with recurrence rates of 33%. We aimed to identify specific prognostic factors for recurrence using quantitative analysis of hematoma volume and density. We retrospectively reviewed radiographic and clinical data of 227 CSDHs in 195 consecutive patients who underwent evacuation of the hematoma through a single burr hole, 2 burr holes, or a mini-craniotomy. To examine the relationship between hematoma recurrence and various clinical, radiologic, and surgical factors, we used quantitative image-based analysis to measure the hematoma and trapped air volumes and the hematoma densities. Recurrence of CSDH occurred in 35 patients (17.9%). Multivariate logistic regression analysis revealed that the percentage of hematoma drained and postoperative CSDH density were independent risk factors for recurrence. All 3 evacuation methods were equally effective in draining the hematoma (71.7% vs. 73.7% vs. 71.9%) without observable differences in postoperative air volume captured in the subdural space. Quantitative image analysis provided evidence that percentage of hematoma drained and postoperative CSDH density are independent prognostic factors for subdural hematoma recurrence. Copyright © 2016 Elsevier Inc. All rights reserved.

SMART: A Propositional Logic-Based Trade Analysis and Risk Assessment Tool for a Complex Mission

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Nicholas, Austin; Alibay, Farah; Parrish, Joseph

2015-01-01

This paper introduces a new trade analysis software called the Space Mission Architecture and Risk Analysis Tool (SMART). This tool supports a high-level system trade study on a complex mission, such as a potential Mars Sample Return (MSR) mission, in an intuitive and quantitative manner. In a complex mission, a common approach to increase the probability of success is to have redundancy and prepare backups. Quantitatively evaluating the utility of adding redundancy to a system is important but not straightforward, particularly when the failure of parallel subsystems are correlated.

Visualisation and quantitative analysis of the rodent malaria liver stage by real time imaging.

PubMed

Ploemen, Ivo H J; Prudêncio, Miguel; Douradinha, Bruno G; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J F; Hermsen, Cornelus C; Sauerwein, Robert W; Baptista, Fernanda G; Mota, Maria M; Waters, Andrew P; Que, Ivo; Lowik, Clemens W G M; Khan, Shahid M; Janse, Chris J; Franke-Fayard, Blandine M D

2009-11-18

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luc(con), expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1-5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium.

Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

PubMed Central

Douradinha, Bruno G.; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J. F.; Hermsen, Cornelus C.; Sauerwein, Robert W.; Baptista, Fernanda G.; Mota, Maria M.; Waters, Andrew P.; Que, Ivo; Lowik, Clemens W. G. M.; Khan, Shahid M.; Janse, Chris J.; Franke-Fayard, Blandine M. D.

2009-01-01

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium. PMID:19924309

Design and analysis of quantitative differential proteomics investigations using LC-MS technology.

PubMed

Bukhman, Yury V; Dharsee, Moyez; Ewing, Rob; Chu, Peter; Topaloglou, Thodoros; Le Bihan, Thierry; Goh, Theo; Duewel, Henry; Stewart, Ian I; Wisniewski, Jacek R; Ng, Nancy F

2008-02-01

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is becoming an increasingly important tool in characterizing the abundance of proteins in biological samples of various types and across conditions. Effects of disease or drug treatments on protein abundance are of particular interest for the characterization of biological processes and the identification of biomarkers. Although state-of-the-art instrumentation is available to make high-quality measurements and commercially available software is available to process the data, the complexity of the technology and data presents challenges for bioinformaticians and statisticians. Here, we describe a pipeline for the analysis of quantitative LC-MS data. Key components of this pipeline include experimental design (sample pooling, blocking, and randomization) as well as deconvolution and alignment of mass chromatograms to generate a matrix of molecular abundance profiles. An important challenge in LC-MS-based quantitation is to be able to accurately identify and assign abundance measurements to members of protein families. To address this issue, we implement a novel statistical method for inferring the relative abundance of related members of protein families from tryptic peptide intensities. This pipeline has been used to analyze quantitative LC-MS data from multiple biomarker discovery projects. We illustrate our pipeline here with examples from two of these studies, and show that the pipeline constitutes a complete workable framework for LC-MS-based differential quantitation. Supplementary material is available at http://iec01.mie.utoronto.ca/~thodoros/Bukhman/.

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

Analytical approaches to determination of total choline in foods and dietary supplements.

PubMed

Phillips, Melissa M

2012-06-01

Choline is a quaternary amine that is synthesized in the body or consumed through the diet. Choline is critical for cell membrane structure and function and in synthesis of the neurotransmitter acetylcholine. Although the human body produces this micronutrient, dietary supplementation of choline is necessary for good health. The major challenge in the analysis of choline in foods and dietary supplements is in the extraction and/or hydrolysis approach. In many products, choline is present as choline esters, which can be quantitated individually or treated with acid, base, or enzymes in order to release choline ions for analysis. A critical review of approaches based on extraction and quantitation of each choline ester as well as hydrolysis-based methods for determination of total choline in foods and dietary supplements is presented.

Quantitative molecular analysis in mantle cell lymphoma.

PubMed

Brízová, H; Hilská, I; Mrhalová, M; Kodet, R

2011-07-01

A molecular analysis has three major roles in modern oncopathology--as an aid in the differential diagnosis, in molecular monitoring of diseases, and in estimation of the potential prognosis. In this report we review the application of the molecular analysis in a group of patients with mantle cell lymphoma (MCL). We demonstrate that detection of the cyclin D1 mRNA level is a molecular marker in 98% of patients with MCL. Cyclin D1 quantitative monitoring is specific and sensitive for the differential diagnosis and for the molecular monitoring of the disease in the bone marrow. Moreover, the dynamics of cyclin D1 in bone marrow reflects the disease development and it predicts the clinical course. We employed the molecular analysis for a precise quantitative detection of proliferation markers, Ki-67, topoisomerase IIalpha, and TPX2, that are described as effective prognostic factors. Using the molecular approach it is possible to measure the proliferation rate in a reproducible, standard way which is an essential prerequisite for using the proliferation activity as a routine clinical tool. Comparing with immunophenotyping we may conclude that the quantitative PCR-based analysis is a useful, reliable, rapid, reproducible, sensitive and specific method broadening our diagnostic tools in hematopathology. In comparison to interphase FISH in paraffin sections quantitative PCR is less technically demanding and less time-consuming and furthermore it is more sensitive in detecting small changes in the mRNA level. Moreover, quantitative PCR is the only technology which provides precise and reproducible quantitative information about the expression level. Therefore it may be used to demonstrate the decrease or increase of a tumor-specific marker in bone marrow in comparison with a previously aspirated specimen. Thus, it has a powerful potential to monitor the course of the disease in correlation with clinical data.

Constellation Ground Systems Launch Availability Analysis: Enhancing Highly Reliable Launch Systems Design

NASA Technical Reports Server (NTRS)

Gernand, Jeffrey L.; Gillespie, Amanda M.; Monaghan, Mark W.; Cummings, Nicholas H.

2010-01-01

Success of the Constellation Program's lunar architecture requires successfully launching two vehicles, Ares I/Orion and Ares V/Altair, in a very limited time period. The reliability and maintainability of flight vehicles and ground systems must deliver a high probability of successfully launching the second vehicle in order to avoid wasting the on-orbit asset launched by the first vehicle. The Ground Operations Project determined which ground subsystems had the potential to affect the probability of the second launch and allocated quantitative availability requirements to these subsystems. The Ground Operations Project also developed a methodology to estimate subsystem reliability, availability and maintainability to ensure that ground subsystems complied with allocated launch availability and maintainability requirements. The verification analysis developed quantitative estimates of subsystem availability based on design documentation; testing results, and other information. Where appropriate, actual performance history was used for legacy subsystems or comparative components that will support Constellation. The results of the verification analysis will be used to verify compliance with requirements and to highlight design or performance shortcomings for further decision-making. This case study will discuss the subsystem requirements allocation process, describe the ground systems methodology for completing quantitative reliability, availability and maintainability analysis, and present findings and observation based on analysis leading to the Ground Systems Preliminary Design Review milestone.

Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

PubMed Central

Bergman, Juraj; Mitrikeski, Petar T.

2015-01-01

Summary Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait. PMID:27904371

Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism.

PubMed

Guo, Longhua; Qiu, Bin; Chi, Yuwu; Chen, Guonan

2008-09-01

In this paper, an ultrasensitive CE-CL detection system coupled with a novel double-on-column coaxial flow detection interface was developed for the detection of PCR products. A reliable procedure based on this system had been demonstrated for qualitative and quantitative analysis of genetically modified organism-the detection of Roundup Ready Soy (RRS) samples was presented as an example. The promoter, terminator, function and two reference genes of RRS were amplified with multiplex PCR simultaneously. After that, the multiplex PCR products were labeled with acridinium ester at the 5'-terminal through an amino modification and then analyzed by the proposed CE-CL system. Reproducibility of analysis times and peak heights for the CE-CL analysis were determined to be better than 0.91 and 3.07% (RSD, n=15), respectively, for three consecutive days. It was shown that this method could accurately and qualitatively detect RRS standards and the simulative samples. The evaluation in terms of quantitative analysis of RRS provided by this new method was confirmed by comparing our assay results with those of the standard real-time quantitative PCR (RT-QPCR) using SYBR Green I dyes. The results showed a good coherence between the two methods. This approach demonstrated the possibility for accurate qualitative and quantitative detection of GM plants in a single run.

Institutional Gender Equity Salary Analysis and Recursive Impact of Career and Life Choices

ERIC Educational Resources Information Center

Peterson, Teri S.

2013-01-01

This study employed mixed methods, engaging both quantitative and qualitative inquiries. In terms of the quantitative inquiry, the purpose of this study was to explore and assess gender-based salary inequities at a Carnegie Classified Research High university in the Intermountain West. Qualitative inquiry was used to follow up and contextually…

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1993-01-01

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

The APOSTEL recommendations for reporting quantitative optical coherence tomography studies.

PubMed

Cruz-Herranz, Andrés; Balk, Lisanne J; Oberwahrenbrock, Timm; Saidha, Shiv; Martinez-Lapiscina, Elena H; Lagreze, Wolf A; Schuman, Joel S; Villoslada, Pablo; Calabresi, Peter; Balcer, Laura; Petzold, Axel; Green, Ari J; Paul, Friedemann; Brandt, Alexander U; Albrecht, Philipp

2016-06-14

To develop consensus recommendations for reporting of quantitative optical coherence tomography (OCT) study results. A panel of experienced OCT researchers (including 11 neurologists, 2 ophthalmologists, and 2 neuroscientists) discussed requirements for performing and reporting quantitative analyses of retinal morphology and developed a list of initial recommendations based on experience and previous studies. The list of recommendations was subsequently revised during several meetings of the coordinating group. We provide a 9-point checklist encompassing aspects deemed relevant when reporting quantitative OCT studies. The areas covered are study protocol, acquisition device, acquisition settings, scanning protocol, funduscopic imaging, postacquisition data selection, postacquisition data analysis, recommended nomenclature, and statistical analysis. The Advised Protocol for OCT Study Terminology and Elements recommendations include core items to standardize and improve quality of reporting in quantitative OCT studies. The recommendations will make reporting of quantitative OCT studies more consistent and in line with existing standards for reporting research in other biomedical areas. The recommendations originated from expert consensus and thus represent Class IV evidence. They will need to be regularly adjusted according to new insights and practices. © 2016 American Academy of Neurology.

Accuracy and Precision of Silicon Based Impression Media for Quantitative Areal Texture Analysis

PubMed Central

Goodall, Robert H.; Darras, Laurent P.; Purnell, Mark A.

2015-01-01

Areal surface texture analysis is becoming widespread across a diverse range of applications, from engineering to ecology. In many studies silicon based impression media are used to replicate surfaces, and the fidelity of replication defines the quality of data collected. However, while different investigators have used different impression media, the fidelity of surface replication has not been subjected to quantitative analysis based on areal texture data. Here we present the results of an analysis of the accuracy and precision with which different silicon based impression media of varying composition and viscosity replicate rough and smooth surfaces. Both accuracy and precision vary greatly between different media. High viscosity media tested show very low accuracy and precision, and most other compounds showed either the same pattern, or low accuracy and high precision, or low precision and high accuracy. Of the media tested, mid viscosity President Jet Regular Body and low viscosity President Jet Light Body (Coltène Whaledent) are the only compounds to show high levels of accuracy and precision on both surface types. Our results show that data acquired from different impression media are not comparable, supporting calls for greater standardisation of methods in areal texture analysis. PMID:25991505

Quantitative comparison of high-resolution MRI and myelin-stained histology of the human cerebral cortex.

PubMed

Osechinskiy, Sergey; Kruggel, Frithjof

2009-01-01

The architectonic analysis of the human cerebral cortex is presently based on the examination of stained tissue sections. Recent progress in high-resolution magnetic resonance imaging (MRI) promotes the feasibility of an in vivo architectonic analysis. Since the exact relationship between the laminar fine-structure of a cortical MRI signal and histological cyto-and myeloarchitectonic staining patterns is not known, a quantitative study comparing high-resolution MRI to histological ground truth images is necessary for validating a future MRI based architectonic analysis. This communication describes an ongoing study comparing post mortem MR images to a myelin-stained histology of the brain cortex. After establishing a close spatial correspondence between histological sections and MRI using a slice-to-volume nonrigid registration algorithm, transcortical intensity profiles, extracted from both imaging modalities along curved trajectories of a Laplacian vector field, are compared via a cross-correlational analysis.

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2018-02-01

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

The behavior of SiC and Si3N4 ceramics in mixed oxidation/chlorination environments

NASA Technical Reports Server (NTRS)

Marra, John E.; Kreidler, Eric R.; Jacobson, Nathan S.; Fox, Dennis S.

1989-01-01

The behavior of silicon-based ceramics in mixed oxidation/chlorination environments was studied. High pressure mass spectrometry was used to quantitatively identify the reaction products. The quantitative identification of the corrosion products was coupled with thermogravimetric analysis and thermodynamic equilibrium calculations run under similar conditions in order to deduce the mechanism of corrosion. Variations in the behavior of the different silicon-based materials are discussed. Direct evidence of the existence of silicon oxychloride compounds is presented.

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. PMID:25864377

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Ryan B.; Clegg, Samuel M.; Frydenvang, Jens

We report that accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response ofmore » an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “submodel” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. Lastly, the sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.« less

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

DOE PAGES

Anderson, Ryan B.; Clegg, Samuel M.; Frydenvang, Jens; ...

2016-12-15

We report that accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response ofmore » an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “submodel” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. Lastly, the sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.« less

Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

PubMed

Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

2015-08-01

We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

Variants in TTC25 affect autistic trait in patients with autism spectrum disorder and general population.

PubMed

Vojinovic, Dina; Brison, Nathalie; Ahmad, Shahzad; Noens, Ilse; Pappa, Irene; Karssen, Lennart C; Tiemeier, Henning; van Duijn, Cornelia M; Peeters, Hilde; Amin, Najaf

2017-08-01

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder with a complex genetic architecture. To identify genetic variants underlying ASD, we performed single-variant and gene-based genome-wide association studies using a dense genotyping array containing over 2.3 million single-nucleotide variants in a discovery sample of 160 families with at least one child affected with non-syndromic ASD using a binary (ASD yes/no) phenotype and a quantitative autistic trait. Replication of the top findings was performed in Psychiatric Genomics Consortium and Erasmus Rucphen Family (ERF) cohort study. Significant association of quantitative autistic trait was observed with the TTC25 gene at 17q21.2 (effect size=10.2, P-value=3.4 × 10 -7 ) in the gene-based analysis. The gene also showed nominally significant association in the cohort-based ERF study (effect=1.75, P-value=0.05). Meta-analysis of discovery and replication improved the association signal (P-value meta =1.5 × 10 -8 ). No genome-wide significant signal was observed in the single-variant analysis of either the binary ASD phenotype or the quantitative autistic trait. Our study has identified a novel gene TTC25 to be associated with quantitative autistic trait in patients with ASD. The replication of association in a cohort-based study and the effect estimate suggest that variants in TTC25 may also be relevant for broader ASD phenotype in the general population. TTC25 is overexpressed in frontal cortex and testis and is known to be involved in cilium movement and thus an interesting candidate gene for autistic trait.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Quantitative analysis of low-density SNP data for parentage assignment and estimation of family contributions to pooled samples.

PubMed

Henshall, John M; Dierens, Leanne; Sellars, Melony J

2014-09-02

While much attention has focused on the development of high-density single nucleotide polymorphism (SNP) assays, the costs of developing and running low-density assays have fallen dramatically. This makes it feasible to develop and apply SNP assays for agricultural species beyond the major livestock species. Although low-cost low-density assays may not have the accuracy of the high-density assays widely used in human and livestock species, we show that when combined with statistical analysis approaches that use quantitative instead of discrete genotypes, their utility may be improved. The data used in this study are from a 63-SNP marker Sequenom® iPLEX Platinum panel for the Black Tiger shrimp, for which high-density SNP assays are not currently available. For quantitative genotypes that could be estimated, in 5% of cases the most likely genotype for an individual at a SNP had a probability of less than 0.99. Matrix formulations of maximum likelihood equations for parentage assignment were developed for the quantitative genotypes and also for discrete genotypes perturbed by an assumed error term. Assignment rates that were based on maximum likelihood with quantitative genotypes were similar to those based on maximum likelihood with perturbed genotypes but, for more than 50% of cases, the two methods resulted in individuals being assigned to different families. Treating genotypes as quantitative values allows the same analysis framework to be used for pooled samples of DNA from multiple individuals. Resulting correlations between allele frequency estimates from pooled DNA and individual samples were consistently greater than 0.90, and as high as 0.97 for some pools. Estimates of family contributions to the pools based on quantitative genotypes in pooled DNA had a correlation of 0.85 with estimates of contributions from DNA-derived pedigree. Even with low numbers of SNPs of variable quality, parentage testing and family assignment from pooled samples are sufficiently accurate to provide useful information for a breeding program. Treating genotypes as quantitative values is an alternative to perturbing genotypes using an assumed error distribution, but can produce very different results. An understanding of the distribution of the error is required for SNP genotyping platforms.

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

PubMed

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

PubMed Central

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

Web-Based Essay Critiquing System and EFL Students' Writing: A Quantitative and Qualitative Investigation

ERIC Educational Resources Information Center

Lee, Cynthia; Wong, Kelvin C. K.; Cheung, William K.; Lee, Fion S. L.

2009-01-01

The paper first describes a web-based essay critiquing system developed by the authors using latent semantic analysis (LSA), an automatic text analysis technique, to provide students with immediate feedback on content and organisation for revision whenever there is an internet connection. It reports on its effectiveness in enhancing adult EFL…

A Comparative Analysis of New Governance Instruments in the Transnational Educational Space: A Shift to Knowledge-Based Instruments?

ERIC Educational Resources Information Center

Ioannidou, Alexandra

2007-01-01

In recent years, the ongoing development towards a knowledge-based society--associated with globalization, an aging population, new technologies and organizational changes--has led to a more intensive analysis of education and learning throughout life with regard to quantitative, qualitative and financial aspects. In this framework, education…

Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

ERIC Educational Resources Information Center

Muslihah, Oleh Eneng

2015-01-01

The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

Quantitative learning strategies based on word networks

NASA Astrophysics Data System (ADS)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

Quantitative Assessment of Parkinsonian Tremor Based on an Inertial Measurement Unit

PubMed Central

Dai, Houde; Zhang, Pengyue; Lueth, Tim C.

2015-01-01

Quantitative assessment of parkinsonian tremor based on inertial sensors can provide reliable feedback on the effect of medication. In this regard, the features of parkinsonian tremor and its unique properties such as motor fluctuations and dyskinesia are taken into account. Least-square-estimation models are used to assess the severities of rest, postural, and action tremors. In addition, a time-frequency signal analysis algorithm for tremor state detection was also included in the tremor assessment method. This inertial sensor-based method was verified through comparison with an electromagnetic motion tracking system. Seven Parkinson’s disease (PD) patients were tested using this tremor assessment system. The measured tremor amplitudes correlated well with the judgments of a neurologist (r = 0.98). The systematic analysis of sensor-based tremor quantification and the corresponding experiments could be of great help in monitoring the severity of parkinsonian tremor. PMID:26426020

Determinations of Carbon Dioxide by Titration: New Experiments for General, Physical, and Quantitative Analysis Courses.

ERIC Educational Resources Information Center

Crossno, S. K.; And Others

1996-01-01

Presents experiments involving the analysis of commercial products such as carbonated beverages and antacids that illustrate the principles of acid-base reactions and present interesting problems in stoichiometry for students. (JRH)

A Quantitative Analysis of Evidence-Based Testing Practices in Nursing Education

ERIC Educational Resources Information Center

Moore, Wendy

2017-01-01

The focus of this dissertation is evidence-based testing practices in nursing education. Specifically, this research study explored the implementation of evidence-based testing practices between nursing faculty of various experience levels. While the significance of evidence-based testing in nursing education is well documented, little is known…

The Intellectual Structure of Metacognitive Scaffolding in Science Education: A Co-Citation Network Analysis

ERIC Educational Resources Information Center

Tang, Kai-Yu; Wang, Chia-Yu; Chang, Hsin-Yi; Chen, Sufen; Lo, Hao-Chang; Tsai, Chin-Chung

2016-01-01

The issues of metacognitive scaffolding in science education (MSiSE) have become increasingly popular and important. Differing from previous content reviews, this study proposes a series of quantitative computer-based analyses by integrating document co-citation analysis, social network analysis, and exploratory factor analysis to explore the…

Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

PubMed

Knowles, David W; Biggin, Mark D

2013-01-01

Animals comprise dynamic three-dimensional arrays of cells that express gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution. Here we summarize light microscopy-based approaches to establish permanent, quantitative datasets-atlases-that record this information. We focus on experiments that capture data for whole embryos or large areas of tissue in three dimensions, often at multiple time points. We compare and contrast the advantages and limitations of different methods and highlight some of the discoveries made. We emphasize the need for interdisciplinary collaborations and integrated experimental pipelines that link sample preparation, image acquisition, image analysis, database design, visualization, and quantitative analysis. Copyright © 2013 Wiley Periodicals, Inc.

The absolute counting of red cell-derived microparticles with red cell bead by flow rate based assay.

PubMed

Nantakomol, Duangdao; Imwong, Malika; Soontarawirat, Ingfar; Kotjanya, Duangporn; Khakhai, Chulalak; Ohashi, Jun; Nuchnoi, Pornlada

2009-05-01

Activation of red blood cell is associated with the formation of red cell-derived microparticles (RMPs). Analysis of circulating RMPs is becoming more refined and clinically useful. A quantitative Trucount tube method is the conventional method uses for quantitating RMPs. In this study, we validated a quantitative method called "flow rate based assay using red cell bead (FCB)" to measure circulating RMPs in the peripheral blood of healthy subjects. Citrated blood samples collected from 30 cases of healthy subjects were determined the RMPs count by using double labeling of annexin V-FITC and anti-glycophorin A-PE. The absolute RMPs numbers were measured by FCB, and the results were compared with the Trucount or with flow rate based calibration (FR). Statistical correlation and agreement were analyzed using linear regression and Bland-Altman analysis. There was no significant difference in the absolute number of RMPs quantitated by FCB when compared with those two reference methods including the Trucount tube and FR method. The absolute RMPs count obtained from FCB method was highly correlated with those obtained from Trucount tube (r(2) = 0.98, mean bias 4 cell/microl, limit of agreement [LOA] -20.3 to 28.3 cell/microl), and FR method (r(2) = 1, mean bias 10.3 cell/microl, and LOA -5.5 to 26.2 cell/microl). This study demonstrates that FCB is suitable and more affordable for RMPs quantitation in the clinical samples. This method is a low cost and interchangeable to latex bead-based method for generating the absolute counts in the resource-limited areas. (c) 2008 Clinical Cytometry Society.

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study.

PubMed

Ha, Richard; Mema, Eralda; Guo, Xiaotao; Mango, Victoria; Desperito, Elise; Ha, Jason; Wynn, Ralph; Zhao, Binsheng

2016-04-01

The amount of fibroglandular tissue (FGT) has been linked to breast cancer risk based on mammographic density studies. Currently, the qualitative assessment of FGT on mammogram (MG) and magnetic resonance imaging (MRI) is prone to intra and inter-observer variability. The purpose of this study is to develop an objective quantitative FGT measurement tool for breast MRI that could provide significant clinical value. An IRB approved study was performed. Sixty breast MRI cases with qualitative assessment of mammographic breast density and MRI FGT were randomly selected for quantitative analysis from routine breast MRIs performed at our institution from 1/2013 to 12/2014. Blinded to the qualitative data, whole breast and FGT contours were delineated on T1-weighted pre contrast sagittal images using an in-house, proprietary segmentation algorithm which combines the region-based active contours and a level set approach. FGT (%) was calculated by: [segmented volume of FGT (mm(3))/(segmented volume of whole breast (mm(3))] ×100. Statistical correlation analysis was performed between quantified FGT (%) on MRI and qualitative assessments of mammographic breast density and MRI FGT. There was a significant positive correlation between quantitative MRI FGT assessment and qualitative MRI FGT (r=0.809, n=60, P<0.001) and mammographic density assessment (r=0.805, n=60, P<0.001). There was a significant correlation between qualitative MRI FGT assessment and mammographic density assessment (r=0.725, n=60, P<0.001). The four qualitative assessment categories of FGT correlated with the calculated mean quantitative FGT (%) of 4.61% (95% CI, 0-12.3%), 8.74% (7.3-10.2%), 18.1% (15.1-21.1%), 37.4% (29.5-45.3%). Quantitative measures of FGT (%) were computed with data derived from breast MRI and correlated significantly with conventional qualitative assessments. This quantitative technique may prove to be a valuable tool in clinical use by providing computer generated standardized measurements with limited intra or inter-observer variability.

Intramolecular carbon and nitrogen isotope analysis by quantitative dry fragmentation of the phenylurea herbicide isoproturon in a combined injector/capillary reactor prior to GC separation.

PubMed

Penning, Holger; Elsner, Martin

2007-11-01

Potentially, compound-specific isotope analysis may provide unique information on source and fate of pesticides in natural systems. Yet for isotope analysis, LC-based methods that are based on the use of organic solvents often cannot be used and GC-based analysis is frequently not possible due to thermolability of the analyte. A typical example of a compound with such properties is isoproturon (3-(4-isopropylphenyl)-1,1-dimethylurea), belonging to the worldwide extensively used phenylurea herbicides. To make isoproturon accessible to carbon and nitrogen isotope analysis, we developed a GC-based method during which isoproturon was quantitatively fragmented to dimethylamine and 4-isopropylphenylisocyanate. Fragmentation occurred only partially in the injector but was mainly achieved on a heated capillary column. The fragments were then chromatographically separated and individually measured by isotope ratio mass spectrometry. The reliability of the method was tested in hydrolysis experiments with three isotopically different batches of isoproturon. For all three products, the same isotope fractionation factors were observed during conversion and the difference in isotope composition between the batches was preserved. This study demonstrates that fragmentation of phenylurea herbicides does not only make them accessible to isotope analysis but even enables determination of intramolecular isotope fractionation.

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity

PubMed Central

Zhu, Jin; Heinecke, Dominic; Mulla, Wahid A.; Bradford, William D.; Rubinstein, Boris; Box, Andrew; Haug, Jeffrey S.; Li, Rong

2015-01-01

Errors in mitosis are a primary cause of chromosome instability (CIN), generating aneuploid progeny cells. Whereas a variety of factors can influence CIN, under most conditions mitotic errors are rare events that have been difficult to measure accurately. Here we report a green fluorescent protein−based quantitative chromosome transmission fidelity (qCTF) assay in budding yeast that allows sensitive and quantitative detection of CIN and can be easily adapted to high-throughput analysis. Using the qCTF assay, we performed genome-wide quantitative profiling of genes that affect CIN in a dosage-dependent manner and identified genes that elevate CIN when either increased (icCIN) or decreased in copy number (dcCIN). Unexpectedly, qCTF screening also revealed genes whose change in copy number quantitatively suppress CIN, suggesting that the basal error rate of the wild-type genome is not minimized, but rather, may have evolved toward an optimal level that balances both stability and low-level karyotype variation for evolutionary adaptation. PMID:25823586

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity.

PubMed

Zhu, Jin; Heinecke, Dominic; Mulla, Wahid A; Bradford, William D; Rubinstein, Boris; Box, Andrew; Haug, Jeffrey S; Li, Rong

2015-03-30

Errors in mitosis are a primary cause of chromosome instability (CIN), generating aneuploid progeny cells. Whereas a variety of factors can influence CIN, under most conditions mitotic errors are rare events that have been difficult to measure accurately. Here we report a green fluorescent protein-based quantitative chromosome transmission fidelity (qCTF) assay in budding yeast that allows sensitive and quantitative detection of CIN and can be easily adapted to high-throughput analysis. Using the qCTF assay, we performed genome-wide quantitative profiling of genes that affect CIN in a dosage-dependent manner and identified genes that elevate CIN when either increased (icCIN) or decreased in copy number (dcCIN). Unexpectedly, qCTF screening also revealed genes whose change in copy number quantitatively suppress CIN, suggesting that the basal error rate of the wild-type genome is not minimized, but rather, may have evolved toward an optimal level that balances both stability and low-level karyotype variation for evolutionary adaptation. Copyright © 2015 Zhu et al.

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative evaluation of translational medicine based on scientometric analysis and information extraction.

PubMed

Zhang, Yin; Diao, Tianxi; Wang, Lei

2014-12-01

Designed to advance the two-way translational process between basic research and clinical practice, translational medicine has become one of the most important areas in biomedicine. The quantitative evaluation of translational medicine is valuable for the decision making of global translational medical research and funding. Using the scientometric analysis and information extraction techniques, this study quantitatively analyzed the scientific articles on translational medicine. The results showed that translational medicine had significant scientific output and impact, specific core field and institute, and outstanding academic status and benefit. While it is not considered in this study, the patent data are another important indicators that should be integrated in the relevant research in the future. © 2014 Wiley Periodicals, Inc.

Development of iPad application "Postima" for quantitative analysis of the effects of manual therapy

NASA Astrophysics Data System (ADS)

Sugiyama, Naruhisa; Shirakawa, Tomohiro

2017-07-01

The technical difficulty of diagnosing joint misalignment and/or dysfunction by quantitative evaluation is commonly acknowledged among manual therapists. Usually, manual therapists make a diagnosis based on a combination of observing patient symptoms and performing physical examinations, both of which rely on subjective criteria and thus contain some uncertainty. We thus sought to investigate the correlations among posture, skeletal misalignment, and pain severity over the course of manual therapy treatment, and to explore the possibility of establishing objective criteria for diagnosis. For this purpose, we developed an iPad application that realizes the measurement of patients' postures and analyzes them quantitatively. We also discuss the results and effectiveness of the measurement and analysis.

Topology Design for Directional Range Extension Networks with Antenna Blockage

DTIC Science & Technology

2017-03-19

introduced by pod-based antenna blockages. Using certain modeling approximations, the paper presents a quantitative analysis showing design trade-offs...parameters. Sec- tion IV develops quantitative relationships among key design elements and performance metrics. Section V considers some implications of the...Topology Design for Directional Range Extension Networks with Antenna Blockage Thomas Shake MIT Lincoln Laboratory shake@ll.mit.edu Abstract

Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR.

PubMed

Kodama, Takashi; Kurosawa, Yasunori; Kitta, Kazumi; Naito, Shigehiro

2010-01-01

The Horwitz curve estimates interlaboratory precision as a function only of concentration, and is frequently used as a method performance criterion in food analysis with chemical methods. The quantitative biochemical methods based on real-time PCR require an analogous criterion to progressively promote method validation. We analyzed the tendency of precision using a simplex real-time PCR technique in 53 collaborative studies of seven genetically modified (GM) crops. Reproducibility standard deviation (SR) and repeatability standard deviation (Sr) of the genetically modified organism (GMO) amount (%) was more or less independent of GM crops (i.e., maize, soybean, cotton, oilseed rape, potato, sugar beet, and rice) and evaluation procedure steps. Some studies evaluated whole steps consisting of DNA extraction and PCR quantitation, whereas others focused only on the PCR quantitation step by using DNA extraction solutions. Therefore, SR and Sr for GMO amount (%) are functions only of concentration similar to the Horwitz curve. We proposed S(R) = 0.1971C 0.8685 and S(r) = 0.1478C 0.8424, where C is the GMO amount (%). We also proposed a method performance index in GMO quantitative methods that is analogous to the Horwitz Ratio.

The Functional Resonance Analysis Method for a systemic risk based environmental auditing in a sinter plant: A semi-quantitative approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patriarca, Riccardo, E-mail: riccardo.patriarca@uniroma1.it; Di Gravio, Giulio; Costantino, Francesco

Environmental auditing is a main issue for any production plant and assessing environmental performance is crucial to identify risks factors. The complexity of current plants arises from interactions among technological, human and organizational system components, which are often transient and not easily detectable. The auditing thus requires a systemic perspective, rather than focusing on individual behaviors, as emerged in recent research in the safety domain for socio-technical systems. We explore the significance of modeling the interactions of system components in everyday work, by the application of a recent systemic method, i.e. the Functional Resonance Analysis Method (FRAM), in order tomore » define dynamically the system structure. We present also an innovative evolution of traditional FRAM following a semi-quantitative approach based on Monte Carlo simulation. This paper represents the first contribution related to the application of FRAM in the environmental context, moreover considering a consistent evolution based on Monte Carlo simulation. The case study of an environmental risk auditing in a sinter plant validates the research, showing the benefits in terms of identifying potential critical activities, related mitigating actions and comprehensive environmental monitoring indicators. - Highlights: • We discuss the relevance of a systemic risk based environmental audit. • We present FRAM to represent functional interactions of the system. • We develop a semi-quantitative FRAM framework to assess environmental risks. • We apply the semi-quantitative FRAM framework to build a model for a sinter plant.« less

Ratio of sequential chromatograms for quantitative analysis and peak deconvolution: Application to standard addition method and process monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Synovec, R.E.; Johnson, E.L.; Bahowick, T.J.

1990-08-01

This paper describes a new technique for data analysis in chromatography, based on taking the point-by-point ratio of sequential chromatograms that have been base line corrected. This ratio chromatogram provides a robust means for the identification and the quantitation of analytes. In addition, the appearance of an interferent is made highly visible, even when it coelutes with desired analytes. For quantitative analysis, the region of the ratio chromatogram corresponding to the pure elution of an analyte is identified and is used to calculate a ratio value equal to the ratio of concentrations of the analyte in sequential injections. For themore » ratio value calculation, a variance-weighted average is used, which compensates for the varying signal-to-noise ratio. This ratio value, or equivalently the percent change in concentration, is the basis of a chromatographic standard addition method and an algorithm to monitor analyte concentration in a process stream. In the case of overlapped peaks, a spiking procedure is used to calculate both the original concentration of an analyte and its signal contribution to the original chromatogram. Thus, quantitation and curve resolution may be performed simultaneously, without peak modeling or curve fitting. These concepts are demonstrated by using data from ion chromatography, but the technique should be applicable to all chromatographic techniques.« less

Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

PubMed

Percy, Andrew J; Yang, Juncong; Chambers, Andrew G; Mohammed, Yassene; Miliotis, Tasso; Borchers, Christoph H

2016-01-01

Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

Comparing the MRI-based Goutallier Classification to an experimental quantitative MR spectroscopic fat measurement of the supraspinatus muscle.

PubMed

Gilbert, Fabian; Böhm, Dirk; Eden, Lars; Schmalzl, Jonas; Meffert, Rainer H; Köstler, Herbert; Weng, Andreas M; Ziegler, Dirk

2016-08-22

The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy. MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman's rank correlation. Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01). The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.

Quantitative analysis of multiple sclerosis: a feasibility study

NASA Astrophysics Data System (ADS)

Li, Lihong; Li, Xiang; Wei, Xinzhou; Sturm, Deborah; Lu, Hongbing; Liang, Zhengrong

2006-03-01

Multiple Sclerosis (MS) is an inflammatory and demyelinating disorder of the central nervous system with a presumed immune-mediated etiology. For treatment of MS, the measurements of white matter (WM), gray matter (GM), and cerebral spinal fluid (CSF) are often used in conjunction with clinical evaluation to provide a more objective measure of MS burden. In this paper, we apply a new unifying automatic mixture-based algorithm for segmentation of brain tissues to quantitatively analyze MS. The method takes into account the following effects that commonly appear in MR imaging: 1) The MR data is modeled as a stochastic process with an inherent inhomogeneity effect of smoothly varying intensity; 2) A new partial volume (PV) model is built in establishing the maximum a posterior (MAP) segmentation scheme; 3) Noise artifacts are minimized by a priori Markov random field (MRF) penalty indicating neighborhood correlation from tissue mixture. The volumes of brain tissues (WM, GM) and CSF are extracted from the mixture-based segmentation. Experimental results of feasibility studies on quantitative analysis of MS are presented.

Quantitative Analysis of Global Proteome and Lysine Acetylome Reveal the Differential Impacts of VPA and SAHA on HL60 Cells.

PubMed

Zhu, Xiaoyu; Liu, Xin; Cheng, Zhongyi; Zhu, Jun; Xu, Lei; Wang, Fengsong; Qi, Wulin; Yan, Jiawei; Liu, Ning; Sun, Zimin; Liu, Huilan; Peng, Xiaojun; Hao, Yingchan; Zheng, Nan; Wu, Quan

2016-01-29

Valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA) are both HDAC inhibitors (HDACi). Previous studies indicated that both inhibitors show therapeutic effects on acute myeloid leukaemia (AML), while the differential impacts of the two different HDACi on AML treatment still remains elusive. In this study, using 3-plex SILAC based quantitative proteomics technique, anti-acetyllysine antibody based affinity enrichment, high resolution LC-MS/MS and intensive bioinformatic analysis, the quantitative proteome and acetylome in SAHA and VPA treated AML HL60 cells were extensively studied. In total, 5,775 proteins and 1,124 lysine acetylation sites were successfully obtained in response to VAP and SAHA treatment. It is found that VPA and SAHA treatment differently induced proteome and acetylome profiling in AML HL60 cells. This study revealed the differential impacts of VPA and SAHA on proteome/acetylome in AML cells, deepening our understanding of HDAC inhibitor mediated AML therapeutics.

Characterization of nano-sized oxides in Fe-12Cr oxide-dispersion-strengthened ferritic steel using small-angle neutron scattering

NASA Astrophysics Data System (ADS)

Han, Young-Soo; Mao, Xiaodong; Jang, Jinsung; Kim, Tae-Kyu

2015-04-01

The ferritic ODS steel was manufactured by hot isostatic pressing and heat treatment. The nano-sized microstructures such as yttrium oxides and Cr oxides were quantitatively analyzed by small-angle neutron scattering (SANS). The effects of the fabrication conditions on the nano-sized microstructure were investigated in relation to the quantitative analysis results obtained by SANS. The ratio between magnetic and nuclear scattering components was calculated, and the characteristics of the nano-sized yttrium oxides are discussed based on the SANS analysis results.

Restriction Site Tiling Analysis: accurate discovery and quantitative genotyping of genome-wide polymorphisms using nucleotide arrays

PubMed Central

2010-01-01

High-throughput genotype data can be used to identify genes important for local adaptation in wild populations, phenotypes in lab stocks, or disease-related traits in human medicine. Here we advance microarray-based genotyping for population genomics with Restriction Site Tiling Analysis. The approach simultaneously discovers polymorphisms and provides quantitative genotype data at 10,000s of loci. It is highly accurate and free from ascertainment bias. We apply the approach to uncover genomic differentiation in the purple sea urchin. PMID:20403197

Optical contrast and refractive index of natural van der Waals heterostructure nanosheets of franckeite

PubMed Central

Gant, Patricia; Ghasemi, Foad; Maeso, David; Munuera, Carmen; López-Elvira, Elena; Frisenda, Riccardo; De Lara, David Pérez; Rubio-Bollinger, Gabino; Garcia-Hernandez, Mar

2017-01-01

We study mechanically exfoliated nanosheets of franckeite by quantitative optical microscopy. The analysis of transmission-mode and epi-illumination-mode optical microscopy images provides a rapid method to estimate the thickness of the exfoliated flakes at first glance. A quantitative analysis of the optical contrast spectra by means of micro-reflectance allows one to determine the refractive index of franckeite over a broad range of the visible spectrum through a fit of the acquired spectra to a model based on the Fresnel law. PMID:29181292

Corneal topography with high-speed swept source OCT in clinical examination

PubMed Central

Karnowski, Karol; Kaluzny, Bartlomiej J.; Szkulmowski, Maciej; Gora, Michalina; Wojtkowski, Maciej

2011-01-01

We present the applicability of high-speed swept source (SS) optical coherence tomography (OCT) for quantitative evaluation of the corneal topography. A high-speed OCT device of 108,000 lines/s permits dense 3D imaging of the anterior segment within a time period of less than one fourth of second, minimizing the influence of motion artifacts on final images and topographic analysis. The swept laser performance was specially adapted to meet imaging depth requirements. For the first time to our knowledge the results of a quantitative corneal analysis based on SS OCT for clinical pathologies such as keratoconus, a cornea with superficial postinfectious scar, and a cornea 5 months after penetrating keratoplasty are presented. Additionally, a comparison with widely used commercial systems, a Placido-based topographer and a Scheimpflug imaging-based topographer, is demonstrated. PMID:21991558

The Social Action Perspective: Attachments to Work and Productivity in the Research Function.

ERIC Educational Resources Information Center

Rebne, Douglas

1989-01-01

Examines faculty motivation and quantitative performance in research. Factor analysis discloses three bases of employment motivation: moral, calculative, and alienative. Regression analysis indicates that moral and alienative attachments contribute to explaining research productivity. (Author/TE)

A Fan-tastic Quantitative Exploration of Ohm's Law

NASA Astrophysics Data System (ADS)

Mitchell, Brandon; Ekey, Robert; McCullough, Roy; Reitz, William

2018-02-01

Teaching simple circuits and Ohm's law to students in the introductory classroom has been extensively investigated through the common practice of using incandescent light bulbs to help students develop a conceptual foundation before moving on to quantitative analysis. However, the bulb filaments' resistance has a large temperature dependence, which makes them less suitable as a tool for quantitative analysis. Some instructors show that light bulbs do not obey Ohm's law either outright or through inquiry-based laboratory experiments. Others avoid the subject altogether by using bulbs strictly for qualitative purposes and then later switching to resistors for a numerical analysis, or by changing the operating conditions of the bulb so that it is "barely" glowing. It seems incongruous to develop a conceptual basis for the behavior of simple circuits using bulbs only to later reveal that they do not follow Ohm's law. Recently, small computer fans were proposed as a suitable replacement of bulbs for qualitative analysis of simple circuits where the current is related to the rotational speed of the fans. In this contribution, we demonstrate that fans can also be used for quantitative measurements and provide suggestions for successful classroom implementation.

USING MICROSOFT OFFICE EXCEL® 2007 TO CONDUCT GENERALIZED MATCHING ANALYSES

PubMed Central

Reed, Derek D

2009-01-01

The generalized matching equation is a robust and empirically supported means of analyzing relations between reinforcement and behavior. Unfortunately, no simple task analysis is available to behavior analysts interested in using the matching equation to evaluate data in clinical or applied settings. This technical article presents a task analysis for the use of Microsoft Excel to analyze and plot the generalized matching equation. Using a data-based case example and a step-by-step guide for completing the analysis, these instructions are intended to promote the use of quantitative analyses by researchers with little to no experience in quantitative analyses or the matching law. PMID:20514196

Using Microsoft Office Excel 2007 to conduct generalized matching analyses.

PubMed

Reed, Derek D

2009-01-01

The generalized matching equation is a robust and empirically supported means of analyzing relations between reinforcement and behavior. Unfortunately, no simple task analysis is available to behavior analysts interested in using the matching equation to evaluate data in clinical or applied settings. This technical article presents a task analysis for the use of Microsoft Excel to analyze and plot the generalized matching equation. Using a data-based case example and a step-by-step guide for completing the analysis, these instructions are intended to promote the use of quantitative analyses by researchers with little to no experience in quantitative analyses or the matching law.

A quantitative analysis of municipal solid waste disposal charges in China.

PubMed

Wu, Jian; Zhang, Weiqian; Xu, Jiaxuan; Che, Yue

2015-03-01

Rapid industrialization and economic development have caused a tremendous increase in municipal solid waste (MSW) generation in China. China began implementing a policy of MSW disposal fees for household waste management at the end of last century. Three charging methods were implemented throughout the country: a fixed disposal fee, a potable water-based disposal fee, and a plastic bag-based disposal fee. To date, there has been little qualitative or quantitative analysis on the effectiveness of this relatively new policy. This paper provides a general overview of MSW fee policy in China, attempts to verify whether the policy is successful in reducing general waste collected, and proposes an improved charging system to address current problems. The paper presents an empirical statistical analysis of policy effectiveness derived from an environmental Kuznets curve (EKC) test on panel data of China. EKC tests on different kinds of MSW charge systems were then examined for individual provinces or cities. A comparison of existing charging systems was conducted using environmental and economic criteria. The results indicate the following: (1) the MSW policies implemented over the study period were effective in the reduction of waste generation, (2) the household waste discharge fee policy did not act as a strong driver in terms of waste prevention and reduction, and (3) the plastic bag-based disposal fee appeared to be performing well according to qualitative and quantitative analysis. Based on current situation of waste discharging management in China, a three-stage transitional charging scheme is proposed and both advantages and drawbacks discussed. Evidence suggests that a transition from a fixed disposal fee to a plastic bag-based disposal fee involving various stakeholders should be the next objective of waste reduction efforts.

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast.

PubMed

Pang, Wei; Coghill, George M

2015-05-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A Quantitative Approach to Scar Analysis

PubMed Central

Khorasani, Hooman; Zheng, Zhong; Nguyen, Calvin; Zara, Janette; Zhang, Xinli; Wang, Joyce; Ting, Kang; Soo, Chia

2011-01-01

Analysis of collagen architecture is essential to wound healing research. However, to date no consistent methodologies exist for quantitatively assessing dermal collagen architecture in scars. In this study, we developed a standardized approach for quantitative analysis of scar collagen morphology by confocal microscopy using fractal dimension and lacunarity analysis. Full-thickness wounds were created on adult mice, closed by primary intention, and harvested at 14 days after wounding for morphometrics and standard Fourier transform-based scar analysis as well as fractal dimension and lacunarity analysis. In addition, transmission electron microscopy was used to evaluate collagen ultrastructure. We demonstrated that fractal dimension and lacunarity analysis were superior to Fourier transform analysis in discriminating scar versus unwounded tissue in a wild-type mouse model. To fully test the robustness of this scar analysis approach, a fibromodulin-null mouse model that heals with increased scar was also used. Fractal dimension and lacunarity analysis effectively discriminated unwounded fibromodulin-null versus wild-type skin as well as healing fibromodulin-null versus wild-type wounds, whereas Fourier transform analysis failed to do so. Furthermore, fractal dimension and lacunarity data also correlated well with transmission electron microscopy collagen ultrastructure analysis, adding to their validity. These results demonstrate that fractal dimension and lacunarity are more sensitive than Fourier transform analysis for quantification of scar morphology. PMID:21281794

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development☆

PubMed Central

Mahan, Ellen D.; Morrow, Kathleen M.; Hayes, John E.

2015-01-01

Background Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Study Design Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey’s honestly significant difference test. Results Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Conclusions Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. PMID:21757061

Quantitative perceptual differences among over-the-counter vaginal products using a standardized methodology: implications for microbicide development.

PubMed

Mahan, Ellen D; Morrow, Kathleen M; Hayes, John E

2011-08-01

Increasing prevalence of HIV infection among women worldwide has motivated the development of female-initiated prevention methods, including gel-based microbicides. User acceptability is vital for microbicide success; however, varying cultural vaginal practices indicate multiple formulations must be developed to appeal to different populations. Perceptual attributes of microbicides have been identified as primary drivers of acceptability; however, previous studies do not allow for direct comparison of these qualities between multiple formulations. Six vaginal products were analyzed ex vivo using descriptive analysis. Perceptual attributes of samples were identified by trained participants (n=10) and rated quantitatively using scales based on a panel-developed lexicon. Data were analyzed using two-way ANOVAs for each attribute; product differences were assessed via Tukey's honestly significant difference test. Significant differences were found between products for multiple attributes. Patterns were also seen for attributes across intended product usage (i.e., contraceptive, moisturizer or lubricant). For example, Options© Gynol II® (Caldwell Consumer Health, LLC) was significantly stickier and grainier than other products. Descriptive analysis, a quantitative approach that is based on consensus lexicon usage among participants, successfully quantified perceptual differences among vaginal products. Since perceptual attributes of products can be directly compared quantitatively, this study represents a novel approach that could be used to inform rational design of microbicides. Copyright © 2011 Elsevier Inc. All rights reserved.

Quantitative Förster resonance energy transfer analysis for kinetic determinations of SUMO-specific protease.

PubMed

Liu, Yan; Song, Yang; Madahar, Vipul; Liao, Jiayu

2012-03-01

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research, and it is a very powerful tool for elucidating protein interactions in either dynamic or steady state. SUMOylation (the process of SUMO [small ubiquitin-like modifier] conjugation to substrates) is an important posttranslational protein modification with critical roles in multiple biological processes. Conjugating SUMO to substrates requires an enzymatic cascade. Sentrin/SUMO-specific proteases (SENPs) act as an endopeptidase to process the pre-SUMO or as an isopeptidase to deconjugate SUMO from its substrate. To fully understand the roles of SENPs in the SUMOylation cycle, it is critical to understand their kinetics. Here, we report a novel development of a quantitative FRET-based protease assay for SENP1 kinetic parameter determination. The assay is based on the quantitative analysis of the FRET signal from the total fluorescent signal at acceptor emission wavelength, which consists of three components: donor (CyPet-SUMO1) emission, acceptor (YPet) emission, and FRET signal during the digestion process. Subsequently, we developed novel theoretical and experimental procedures to determine the kinetic parameters, k(cat), K(M), and catalytic efficiency (k(cat)/K(M)) of catalytic domain SENP1 toward pre-SUMO1. Importantly, the general principles of this quantitative FRET-based protease kinetic determination can be applied to other proteases. Copyright © 2011 Elsevier Inc. All rights reserved.

[Clinical research XXIII. From clinical judgment to meta-analyses].

PubMed

Rivas-Ruiz, Rodolfo; Castelán-Martínez, Osvaldo D; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Noyola-Castillo, Maura E; Talavera, Juan O

2014-01-01

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

Single and two-shot quantitative phase imaging using Hilbert-Huang Transform based fringe pattern analysis

NASA Astrophysics Data System (ADS)

Trusiak, Maciej; Micó, Vicente; Patorski, Krzysztof; García-Monreal, Javier; Sluzewski, Lukasz; Ferreira, Carlos

2016-08-01

In this contribution we propose two Hilbert-Huang Transform based algorithms for fast and accurate single-shot and two-shot quantitative phase imaging applicable in both on-axis and off-axis configurations. In the first scheme a single fringe pattern containing information about biological phase-sample under study is adaptively pre-filtered using empirical mode decomposition based approach. Further it is phase demodulated by the Hilbert Spiral Transform aided by the Principal Component Analysis for the local fringe orientation estimation. Orientation calculation enables closed fringes efficient analysis and can be avoided using arbitrary phase-shifted two-shot Gram-Schmidt Orthonormalization scheme aided by Hilbert-Huang Transform pre-filtering. This two-shot approach is a trade-off between single-frame and temporal phase shifting demodulation. Robustness of the proposed techniques is corroborated using experimental digital holographic microscopy studies of polystyrene micro-beads and red blood cells. Both algorithms compare favorably with the temporal phase shifting scheme which is used as a reference method.

Nondestructive evaluation of degradation in papaya fruit using intensity based algorithms

NASA Astrophysics Data System (ADS)

Kumari, Shubhashri; Nirala, Anil Kumar

2018-05-01

In the proposed work degradation in Papaya fruit has been evaluated nondestructively using laser biospeckle technique. The biospeckle activity inside the fruit has been evaluated qualitatively and quantitatively during its maturity to degradation stage using intensity based algorithms. Co-occurrence matrix (COM) has been used for qualitative analysis whereas Inertia Moment (IM), Absolute value Difference (AVD) and Autocovariance methods have been used for quantitative analysis. The biospeckle activity has been found to first increase and then decrease during study period of five days. In addition Granulometric size distribution (GSD) has also been used for the first time for the evaluation of degradation of the papaya. It is concluded that the degradation process of papaya fruit can be evaluated nondestructively using all the mentioned algorithms.

Changes in monosaccharides, organic acids and amino acids during Cabernet Sauvignon wine ageing based on a simultaneous analysis using gas chromatography-mass spectrometry.

PubMed

Zhang, Xin-Ke; Lan, Yi-Bin; Zhu, Bao-Qing; Xiang, Xiao-Feng; Duan, Chang-Qing; Shi, Ying

2018-01-01

Monosaccharides, organic acids and amino acids are the important flavour-related components in wines. The aim of this article is to develop and validate a method that could simultaneously analyse these compounds in wine based on silylation derivatisation and gas chromatography-mass spectrometry (GC-MS), and apply this method to the investigation of the changes of these compounds and speculate upon their related influences on Cabernet Sauvignon wine flavour during wine ageing. This work presented a new approach for wine analysis and provided more information concerning red wine ageing. This method could simultaneously quantitatively analyse 2 monosaccharides, 8 organic acids and 13 amino acids in wine. A validation experiment showed good linearity, sensitivity, reproducibility and recovery. Multiple derivatives of five amino acids have been found but their effects on quantitative analysis were negligible, except for methionine. The evolution pattern of each category was different, and we speculated that the corresponding mechanisms involving microorganism activities, physical interactions and chemical reactions had a great correlation with red wine flavours during ageing. Simultaneously quantitative analysis of monosaccharides, organic acids and amino acids in wine was feasible and reliable and this method has extensive application prospects. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning.

PubMed

Mirsky, Simcha K; Barnea, Itay; Levi, Mattan; Greenspan, Hayit; Shaked, Natan T

2017-09-01

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries.

PubMed

Hamers, F P; Lankhorst, A J; van Laar, T J; Veldhuis, W B; Gispen, W H

2001-02-01

Analysis of locomotion is an important tool in the study of peripheral and central nervous system damage. Most locomotor scoring systems in rodents are based either upon open field locomotion assessment, for example, the BBB score or upon foot print analysis. The former yields a semiquantitative description of locomotion as a whole, whereas the latter generates quantitative data on several selected gait parameters. In this paper, we describe the use of a newly developed gait analysis method that allows easy quantitation of a large number of locomotion parameters during walkway crossing. We were able to extract data on interlimb coordination, swing duration, paw print areas (total over stance, and at 20-msec time resolution), stride length, and base of support: Similar data can not be gathered by any single previously described method. We compare changes in gait parameters induced by two different models of spinal cord injury in rats, transection of the dorsal half of the spinal cord and spinal cord contusion injury induced by the NYU or MASCIS device. Although we applied this method to rats with spinal cord injury, the usefulness of this method is not limited to rats or to the investigation of spinal cord injuries alone.

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Automated classification of cell morphology by coherence-controlled holographic microscopy

NASA Astrophysics Data System (ADS)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.

PubMed

Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina

2008-10-01

We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.

Automated classification of cell morphology by coherence-controlled holographic microscopy.

PubMed

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs

PubMed Central

Morisset, Dany; Dobnik, David; Hamels, Sandrine; Žel, Jana; Gruden, Kristina

2008-01-01

We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880

Quantitative Analysis of the Efficiency of OLEDs.

PubMed

Sim, Bomi; Moon, Chang-Ki; Kim, Kwon-Hyeon; Kim, Jang-Joo

2016-12-07

We present a comprehensive model for the quantitative analysis of factors influencing the efficiency of organic light-emitting diodes (OLEDs) as a function of the current density. The model takes into account the contribution made by the charge carrier imbalance, quenching processes, and optical design loss of the device arising from various optical effects including the cavity structure, location and profile of the excitons, effective radiative quantum efficiency, and out-coupling efficiency. Quantitative analysis of the efficiency can be performed with an optical simulation using material parameters and experimental measurements of the exciton profile in the emission layer and the lifetime of the exciton as a function of the current density. This method was applied to three phosphorescent OLEDs based on a single host, mixed host, and exciplex-forming cohost. The three factors (charge carrier imbalance, quenching processes, and optical design loss) were influential in different ways, depending on the device. The proposed model can potentially be used to optimize OLED configurations on the basis of an analysis of the underlying physical processes.

Quantitative analysis of Ni2+/Ni3+ in Li[NixMnyCoz]O2 cathode materials: Non-linear least-squares fitting of XPS spectra

NASA Astrophysics Data System (ADS)

Fu, Zewei; Hu, Juntao; Hu, Wenlong; Yang, Shiyu; Luo, Yunfeng

2018-05-01

Quantitative analysis of Ni2+/Ni3+ using X-ray photoelectron spectroscopy (XPS) is important for evaluating the crystal structure and electrochemical performance of Lithium-nickel-cobalt-manganese oxide (Li[NixMnyCoz]O2, NMC). However, quantitative analysis based on Gaussian/Lorentzian (G/L) peak fitting suffers from the challenges of reproducibility and effectiveness. In this study, the Ni2+ and Ni3+ standard samples and a series of NMC samples with different Ni doping levels were synthesized. The Ni2+/Ni3+ ratios in NMC were quantitatively analyzed by non-linear least-squares fitting (NLLSF). Two Ni 2p overall spectra of synthesized Li [Ni0.33Mn0.33Co0.33]O2(NMC111) and bulk LiNiO2 were used as the Ni2+ and Ni3+ reference standards. Compared to G/L peak fitting, the fitting parameters required no adjustment, meaning that the spectral fitting process was free from operator dependence and the reproducibility was improved. Comparison of residual standard deviation (STD) showed that the fitting quality of NLLSF was superior to that of G/L peaks fitting. Overall, these findings confirmed the reproducibility and effectiveness of the NLLSF method in XPS quantitative analysis of Ni2+/Ni3+ ratio in Li[NixMnyCoz]O2 cathode materials.

Quantitative Analysis of Science and Chemistry Textbooks for Indicators of Reform: A complementary perspective

NASA Astrophysics Data System (ADS)

Kahveci, Ajda

2010-07-01

In this study, multiple thematically based and quantitative analysis procedures were utilized to explore the effectiveness of Turkish chemistry and science textbooks in terms of their reflection of reform. The themes gender equity, questioning level, science vocabulary load, and readability level provided the conceptual framework for the analyses. An unobtrusive research method, content analysis, was used by coding the manifest content and counting the frequency of words, photographs, drawings, and questions by cognitive level. The context was an undergraduate chemistry teacher preparation program at a large public university in a metropolitan area in northwestern Turkey. Forty preservice chemistry teachers were guided to analyze 10 middle school science and 10 high school chemistry textbooks. Overall, the textbooks included unfair gender representations, a considerably higher number of input and processing than output level questions, and high load of science terminology. The textbooks failed to provide sufficient empirical evidence to be considered as gender equitable and inquiry-based. The quantitative approach employed for evaluation contrasts with a more interpretive approach, and has the potential in depicting textbook profiles in a more reliable way, complementing the commonly employed qualitative procedures. Implications suggest that further work in this line is needed on calibrating the analysis procedures with science textbooks used in different international settings. The procedures could be modified and improved to meet specific evaluation needs. In the Turkish context, next step research may concern the analysis of science textbooks being rewritten for the reform-based curricula to make cross-comparisons and evaluate a possible progression.

Constellation Ground Systems Launch Availability Analysis: Enhancing Highly Reliable Launch Systems Design

NASA Technical Reports Server (NTRS)

Gernand, Jeffrey L.; Gillespie, Amanda M.; Monaghan, Mark W.; Cummings, Nicholas H.

2010-01-01

Success of the Constellation Program's lunar architecture requires successfully launching two vehicles, Ares I/Orion and Ares V/Altair, within a very limited time period. The reliability and maintainability of flight vehicles and ground systems must deliver a high probability of successfully launching the second vehicle in order to avoid wasting the on-orbit asset launched by the first vehicle. The Ground Operations Project determined which ground subsystems had the potential to affect the probability of the second launch and allocated quantitative availability requirements to these subsystems. The Ground Operations Project also developed a methodology to estimate subsystem reliability, availability, and maintainability to ensure that ground subsystems complied with allocated launch availability and maintainability requirements. The verification analysis developed quantitative estimates of subsystem availability based on design documentation, testing results, and other information. Where appropriate, actual performance history was used to calculate failure rates for legacy subsystems or comparative components that will support Constellation. The results of the verification analysis will be used to assess compliance with requirements and to highlight design or performance shortcomings for further decision making. This case study will discuss the subsystem requirements allocation process, describe the ground systems methodology for completing quantitative reliability, availability, and maintainability analysis, and present findings and observation based on analysis leading to the Ground Operations Project Preliminary Design Review milestone.

Comparison of three‐dimensional analysis and stereological techniques for quantifying lithium‐ion battery electrode microstructures

PubMed Central

TAIWO, OLUWADAMILOLA O.; FINEGAN, DONAL P.; EASTWOOD, DAVID S.; FIFE, JULIE L.; BROWN, LEON D.; DARR, JAWWAD A.; LEE, PETER D.; BRETT, DANIEL J.L.

2016-01-01

Summary Lithium‐ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium‐ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3‐D imaging techniques, quantitative assessment of 3‐D microstructures from 2‐D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two‐dimensional (2‐D) data sets. In this study, stereological prediction and three‐dimensional (3‐D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium‐ion battery electrodes were imaged using synchrotron‐based X‐ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2‐D image sections generated from tomographic imaging, whereas direct 3‐D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2‐D image sections is bound to be associated with ambiguity and that volume‐based 3‐D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially‐dependent parameters, such as tortuosity and pore‐phase connectivity. PMID:26999804

Comparison of three-dimensional analysis and stereological techniques for quantifying lithium-ion battery electrode microstructures.

PubMed

Taiwo, Oluwadamilola O; Finegan, Donal P; Eastwood, David S; Fife, Julie L; Brown, Leon D; Darr, Jawwad A; Lee, Peter D; Brett, Daniel J L; Shearing, Paul R

2016-09-01

Lithium-ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium-ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3-D imaging techniques, quantitative assessment of 3-D microstructures from 2-D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two-dimensional (2-D) data sets. In this study, stereological prediction and three-dimensional (3-D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium-ion battery electrodes were imaged using synchrotron-based X-ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2-D image sections generated from tomographic imaging, whereas direct 3-D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2-D image sections is bound to be associated with ambiguity and that volume-based 3-D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially-dependent parameters, such as tortuosity and pore-phase connectivity. © 2016 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Current trends in mass spectrometry of peptides and proteins: Application to veterinary and sports-doping control.

PubMed

van den Broek, Irene; Blokland, Marco; Nessen, Merel A; Sterk, Saskia

2015-01-01

Detection of misuse of peptides and proteins as growth promoters is a major issue for sport and food regulatory agencies. The limitations of current analytical detection strategies for this class of compounds, in combination with their efficacy in growth-promoting effects, make peptide and protein drugs highly susceptible to abuse by either athletes or farmers who seek for products to illicitly enhance muscle growth. Mass spectrometry (MS) for qualitative analysis of peptides and proteins is well-established, particularly due to tremendous efforts in the proteomics community. Similarly, due to advancements in targeted proteomic strategies and the rapid growth of protein-based biopharmaceuticals, MS for quantitative analysis of peptides and proteins is becoming more widely accepted. These continuous advances in MS instrumentation and MS-based methodologies offer enormous opportunities for detection and confirmation of peptides and proteins. Therefore, MS seems to be the method of choice to improve the qualitative and quantitative analysis of peptide and proteins with growth-promoting properties. This review aims to address the opportunities of MS for peptide and protein analysis in veterinary control and sports-doping control with a particular focus on detection of illicit growth promotion. An overview of potential peptide and protein targets, including their amino acid sequence characteristics and current MS-based detection strategies is, therefore, provided. Furthermore, improvements of current and new detection strategies with state-of-the-art MS instrumentation are discussed for qualitative and quantitative approaches. © 2013 Wiley Periodicals, Inc.

Qualitative and Quantitative Analysis for Facial Complexion in Traditional Chinese Medicine

PubMed Central

Zhao, Changbo; Li, Guo-zheng; Li, Fufeng; Wang, Zhi; Liu, Chang

2014-01-01

Facial diagnosis is an important and very intuitive diagnostic method in Traditional Chinese Medicine (TCM). However, due to its qualitative and experience-based subjective property, traditional facial diagnosis has a certain limitation in clinical medicine. The computerized inspection method provides classification models to recognize facial complexion (including color and gloss). However, the previous works only study the classification problems of facial complexion, which is considered as qualitative analysis in our perspective. For quantitative analysis expectation, the severity or degree of facial complexion has not been reported yet. This paper aims to make both qualitative and quantitative analysis for facial complexion. We propose a novel feature representation of facial complexion from the whole face of patients. The features are established with four chromaticity bases splitting up by luminance distribution on CIELAB color space. Chromaticity bases are constructed from facial dominant color using two-level clustering; the optimal luminance distribution is simply implemented with experimental comparisons. The features are proved to be more distinctive than the previous facial complexion feature representation. Complexion recognition proceeds by training an SVM classifier with the optimal model parameters. In addition, further improved features are more developed by the weighted fusion of five local regions. Extensive experimental results show that the proposed features achieve highest facial color recognition performance with a total accuracy of 86.89%. And, furthermore, the proposed recognition framework could analyze both color and gloss degrees of facial complexion by learning a ranking function. PMID:24967342

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Quantitative 3D analysis of bone in hip osteoarthritis using clinical computed tomography.

PubMed

Turmezei, Tom D; Treece, Graham M; Gee, Andrew H; Fotiadou, Anastasia F; Poole, Kenneth E S

2016-07-01

To assess the relationship between proximal femoral cortical bone thickness and radiological hip osteoarthritis using quantitative 3D analysis of clinical computed tomography (CT) data. Image analysis was performed on clinical CT imaging data from 203 female volunteers with a technique called cortical bone mapping (CBM). Colour thickness maps were created for each proximal femur. Statistical parametric mapping was performed to identify statistically significant differences in cortical bone thickness that corresponded with the severity of radiological hip osteoarthritis. Kellgren and Lawrence (K&L) grade, minimum joint space width (JSW) and a novel CT-based osteophyte score were also blindly assessed from the CT data. For each increase in K&L grade, cortical thickness increased by up to 25 % in distinct areas of the superolateral femoral head-neck junction and superior subchondral bone plate. For increasing severity of CT osteophytes, the increase in cortical thickness was more circumferential, involving a wider portion of the head-neck junction, with up to a 7 % increase in cortical thickness per increment in score. Results were not significant for minimum JSW. These findings indicate that quantitative 3D analysis of the proximal femur can identify changes in cortical bone thickness relevant to structural hip osteoarthritis. • CT is being increasingly used to assess bony involvement in osteoarthritis • CBM provides accurate and reliable quantitative analysis of cortical bone thickness • Cortical bone is thicker at the superior femoral head-neck with worse osteoarthritis • Regions of increased thickness co-locate with impingement and osteophyte formation • Quantitative 3D bone analysis could enable clinical disease prediction and therapy development.

SaaS Platform for Time Series Data Handling

NASA Astrophysics Data System (ADS)

Oplachko, Ekaterina; Rykunov, Stanislav; Ustinin, Mikhail

2018-02-01

The paper is devoted to the description of MathBrain, a cloud-based resource, which works as a "Software as a Service" model. It is designed to maximize the efficiency of the current technology and to provide a tool for time series data handling. The resource provides access to the following analysis methods: direct and inverse Fourier transforms, Principal component analysis and Independent component analysis decompositions, quantitative analysis, magnetoencephalography inverse problem solution in a single dipole model based on multichannel spectral data.

Use-related risk analysis for medical devices based on improved FMEA.

PubMed

Liu, Long; Shuai, Ma; Wang, Zhu; Li, Ping

2012-01-01

In order to effectively analyze and control use-related risk of medical devices, quantitative methodologies must be applied. Failure Mode and Effects Analysis (FMEA) is a proactive technique for error detection and risk reduction. In this article, an improved FMEA based on Fuzzy Mathematics and Grey Relational Theory is developed to better carry out user-related risk analysis for medical devices. As an example, the analysis process using this improved FMEA method for a certain medical device (C-arm X-ray machine) is described.

[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

Patient-specific coronary blood supply territories for quantitative perfusion analysis

PubMed Central

Zakkaroff, Constantine; Biglands, John D.; Greenwood, John P.; Plein, Sven; Boyle, Roger D.; Radjenovic, Aleksandra; Magee, Derek R.

2018-01-01

Abstract Myocardial perfusion imaging, coupled with quantitative perfusion analysis, provides an important diagnostic tool for the identification of ischaemic heart disease caused by coronary stenoses. The accurate mapping between coronary anatomy and under-perfused areas of the myocardium is important for diagnosis and treatment. However, in the absence of the actual coronary anatomy during the reporting of perfusion images, areas of ischaemia are allocated to a coronary territory based on a population-derived 17-segment (American Heart Association) AHA model of coronary blood supply. This work presents a solution for the fusion of 2D Magnetic Resonance (MR) myocardial perfusion images and 3D MR angiography data with the aim to improve the detection of ischaemic heart disease. The key contribution of this work is a novel method for the mediated spatiotemporal registration of perfusion and angiography data and a novel method for the calculation of patient-specific coronary supply territories. The registration method uses 4D cardiac MR cine series spanning the complete cardiac cycle in order to overcome the under-constrained nature of non-rigid slice-to-volume perfusion-to-angiography registration. This is achieved by separating out the deformable registration problem and solving it through phase-to-phase registration of the cine series. The use of patient-specific blood supply territories in quantitative perfusion analysis (instead of the population-based model of coronary blood supply) has the potential of increasing the accuracy of perfusion analysis. Quantitative perfusion analysis diagnostic accuracy evaluation with patient-specific territories against the AHA model demonstrates the value of the mediated spatiotemporal registration in the context of ischaemic heart disease diagnosis. PMID:29392098

Analyzing the texture changes in the quantitative phase maps of adipocytes

NASA Astrophysics Data System (ADS)

Roitshtain, Darina; Sharabani-Yosef, Orna; Gefen, Amit; Shaked, Natan T.

2016-03-01

We present a new analysis tool for studying texture changes in the quantitative phase maps of live cells acquired by wide-field interferometry. The sensitivity of wide-field interferometry systems to small changes in refractive index enables visualizing cells and inner cell organelles without the using fluorescent dyes or other cell-invasive approaches, which may affect the measurement and require external labeling. Our label-free texture-analysis tool is based directly on the optical path delay profile of the sample and does not necessitate decoupling refractive index and thickness in the cell quantitative phase profile; thus, relevant parameters can be calculated using a single-frame acquisition. Our experimental system includes low-coherence wide-field interferometer, combined with simultaneous florescence microscopy system for validation. We used this system and analysis tool for studying lipid droplets formation in adipocytes. The latter demonstration is relevant for various cellular functions such as lipid metabolism, protein storage and degradation to viral replication. These processes are functionally linked to several physiological and pathological conditions, including obesity and metabolic diseases. Quantification of these biological phenomena based on the texture changes in the cell phase map has a potential as a new cellular diagnosis tool.

Quantitative analyses of tartaric acid based on terahertz time domain spectroscopy

NASA Astrophysics Data System (ADS)

Cao, Binghua; Fan, Mengbao

2010-10-01

Terahertz wave is the electromagnetic spectrum situated between microwave and infrared wave. Quantitative analysis based on terahertz spectroscopy is very important for the application of terahertz techniques. But how to realize it is still under study. L-tartaric acid is widely used as acidulant in beverage, and other food, such as soft drinks, wine, candy, bread and some colloidal sweetmeats. In this paper, terahertz time-domain spectroscopy is applied to quantify the tartaric acid. Two methods are employed to process the terahertz spectra of different samples with different content of tartaric acid. The first one is linear regression combining correlation analysis. The second is partial least square (PLS), in which the absorption spectra in the 0.8-1.4THz region are used to quantify the tartaric acid. To compare the performance of these two principles, the relative error of the two methods is analyzed. For this experiment, the first method does better than the second one. But the first method is suitable for the quantitative analysis of materials which has obvious terahertz absorption peaks, while for material which has no obvious terahertz absorption peaks, the second one is more appropriate.

Analysis of Gold Ores by Fire Assay

ERIC Educational Resources Information Center

Blyth, Kristy M.; Phillips, David N.; van Bronswijk, Wilhelm

2004-01-01

Students of an Applied Chemistry degree course carried out a fire-assay exercise. The analysis showed that the technique was a worthwhile quantitative analytical technique and covered interesting theory including acid-base and redox chemistry and other concepts such as inquarting and cupelling.

PHYSIOLOCIGALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT

EPA Science Inventory

PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT. Barton HA. Experimental Toxicology Division, National Health and Environmental Effects Laboratory, ORD, U.S. EPA
Dose-response analysis requires quantitatively linking infor...

Limited diagnostic value of Dual-Time-Point (18)F-FDG PET/CT imaging for classifying solitary pulmonary nodules in granuloma-endemic regions both at visual and quantitative analyses.

PubMed

Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming

2016-10-01

This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The quantitative surface analysis of an antioxidant additive in a lubricant oil matrix by desorption electrospray ionization mass spectrometry

PubMed Central

Da Costa, Caitlyn; Reynolds, James C; Whitmarsh, Samuel; Lynch, Tom; Creaser, Colin S

2013-01-01

RATIONALE Chemical additives are incorporated into commercial lubricant oils to modify the physical and chemical properties of the lubricant. The quantitative analysis of additives in oil-based lubricants deposited on a surface without extraction of the sample from the surface presents a challenge. The potential of desorption electrospray ionization mass spectrometry (DESI-MS) for the quantitative surface analysis of an oil additive in a complex oil lubricant matrix without sample extraction has been evaluated. METHODS The quantitative surface analysis of the antioxidant additive octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix was carried out by DESI-MS in the presence of 2-(pentyloxy)ethyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl)propionate as an internal standard. A quadrupole/time-of-flight mass spectrometer fitted with an in-house modified ion source enabling non-proximal DESI-MS was used for the analyses. RESULTS An eight-point calibration curve ranging from 1 to 80 µg/spot of octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix and in the presence of the internal standard was used to determine the quantitative response of the DESI-MS method. The sensitivity and repeatability of the technique were assessed by conducting replicate analyses at each concentration. The limit of detection was determined to be 11 ng/mm2 additive on spot with relative standard deviations in the range 3–14%. CONCLUSIONS The application of DESI-MS to the direct, quantitative surface analysis of a commercial lubricant additive in a native oil lubricant matrix is demonstrated. © 2013 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons, Ltd. PMID:24097398

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

Quantitative analysis of fracture surface by roughness and fractal method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, X.W.; Tian, J.F.; Kang, Y.

1995-09-01

In recent years there has been extensive research and great development in Quantitative Fractography, which acts as an integral part of fractographic analysis. A prominent technique for studying the fracture surface is based on fracture profile generation and the major means for characterizing the profile quantitatively are roughness and fractal methods. By this way, some quantitative indexes such as the roughness parameters R{sub L} for profile and R{sub S} for surface, fractal dimensions D{sub L} for profile and D{sub S} for surface can be measured. Given the relationships between the indexes and the mechanical properties of materials, it is possiblemore » to achieve the goal of protecting materials from fracture. But, as the case stands, the theory and experimental technology of quantitative fractography are still imperfect and remain to be studied further. Recently, Gokhale and Underwood et al have proposed an assumption-free method for estimating the surface roughness by vertically sectioning the fracture surface with sections at an angle of 120 deg with each other, which could be expressed as follows: R{sub S} = {ovr R{sub L}{center_dot}{Psi}} where {Psi} is the profile structure factor. This method is based on the classical sterological principles and verified with the aid of computer simulations for some ruled surfaces. The results are considered to be applicable to fracture surfaces with any arbitrary complexity and anisotropy. In order to extend the detail applications to this method in quantitative fractography, the authors made a study on roughness and fractal methods dependent on this method by performing quantitative measurements on some typical low-temperature impact fractures.« less

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Simultaneous qualitative and quantitative analysis of flavonoids and alkaloids from the leaves of Nelumbo nucifera Gaertn. using high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

PubMed

Guo, Yujie; Chen, Xi; Qi, Jin; Yu, Boyang

2016-07-01

A reliable method, combining qualitative analysis by high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and quantitative assessment by high-performance liquid chromatography with photodiode array detection, has been developed to simultaneously analyze flavonoids and alkaloids in lotus leaf extracts. In the qualitative analysis, a total of 30 compounds, including 12 flavonoids, 16 alkaloids, and two proanthocyanidins, were identified. The fragmentation behaviors of four types of flavone glycoside and three types of alkaloid are summarized. The mass spectra of four representative components, quercetin 3-O-glucuronide, norcoclaurine, nuciferine, and neferine, are shown to illustrate their fragmentation pathways. Five pairs of isomers were detected and three of them were distinguished by comparing the elution order with reference substances and the mass spectrometry data with reported data. In the quantitative analysis, 30 lotus leaf samples from different regions were analyzed to investigate the proportion of eight representative compounds. Quercetin 3-O-glucuronide was found to be the predominant constituent of lotus leaf extracts. For further discrimination among the samples, hierarchical cluster analysis, and principal component analysis, based on the areas of the eight quantitative peaks, were carried out. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using computer-based video analysis in the study of fidgety movements.

PubMed

Adde, Lars; Helbostad, Jorunn L; Jensenius, Alexander Refsum; Taraldsen, Gunnar; Støen, Ragnhild

2009-09-01

Absence of fidgety movements (FM) in high-risk infants is a strong marker for later cerebral palsy (CP). FMs can be classified by the General Movement Assessment (GMA), based on Gestalt perception of the infant's movement pattern. More objective movement analysis may be provided by computer-based technology. The aim of this study was to explore the feasibility of a computer-based video analysis of infants' spontaneous movements in classifying non-fidgety versus fidgety movements. GMA was performed from video material of the fidgety period in 82 term and preterm infants at low and high risks of developing CP. The same videos were analysed using the developed software called General Movement Toolbox (GMT) with visualisation of the infant's movements for qualitative analyses. Variables derived from the calculation of displacement of pixels from one video frame to the next were used for quantitative analyses. Visual representations from GMT showed easily recognisable patterns of FMs. Of the eight quantitative variables derived, the variability in displacement of a spatial centre of active pixels in the image had the highest sensitivity (81.5) and specificity (70.0) in classifying FMs. By setting triage thresholds at 90% sensitivity and specificity for FM, the need for further referral was reduced by 70%. Video recordings can be used for qualitative and quantitative analyses of FMs provided by GMT. GMT is easy to implement in clinical practice, and may provide assistance in detecting infants without FMs.

Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR.

PubMed

Sauer, Eva; Reinke, Ann-Kathrin; Courts, Cornelius

2016-05-01

Applying molecular genetic approaches for the identification of forensically relevant body fluids, which often yield crucial information for the reconstruction of a potential crime, is a current topic of forensic research. Due to their body fluid specific expression patterns and stability against degradation, microRNAs (miRNA) emerged as a promising molecular species, with a range of candidate markers published. The analysis of miRNA via quantitative Real-Time PCR, however, should be based on a relevant strategy of normalization of non-biological variances to deliver reliable and biologically meaningful results. The herein presented work is the as yet most comprehensive study of forensic body fluid identification via miRNA expression analysis based on a thoroughly validated qPCR procedure and unbiased statistical decision making to identify single source samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of tissue mesodissection to molecular cancer diagnostics.

PubMed

Krizman, David; Adey, Nils; Parry, Robert

2015-02-01

To demonstrate clinical application of a mesodissection platform that was developed to combine advantages of laser-based instrumentation with the speed/ease of manual dissection for automated dissection of tissue off standard glass slides. Genomic analysis for KRAS gene mutation was performed on formalin fixed paraffin embedded (FFPE) cancer patient tissue that was dissected using the mesodissection platform. Selected reaction monitoring proteomic analysis for quantitative Her2 protein expression was performed on FFPE patient tumour tissue dissected by a laser-based instrument and the MilliSect instrument. Genomic analysis demonstrates highly confident detection of KRAS mutation specifically in lung cancer cells and not the surrounding benign, non-tumour tissue. Proteomic analysis demonstrates Her2 quantitative protein expression in breast cancer cells dissected manually, by laser-based instrumentation and by MilliSect instrumentation (mesodissection). Slide-mounted tissue dissection is commonly performed using laser-based instruments or manually scraping tissue by scalpel. Here we demonstrate that the mesodissection platform as performed by the MilliSect instrument for tissue dissection is cost-effective; it functions comparably to laser-based dissection and which can be adopted into a clinical diagnostic workflow. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Use of near infrared correlation spectroscopy for quantitation of surface iron, absorbed water and stored electronic energy in a suite of Mars soil analog materials

NASA Technical Reports Server (NTRS)

Coyne, Lelia M.; Banin, Amos; Carle, Glenn; Orenberg, James; Scattergood, Thomas

1989-01-01

A number of questions concerning the surface mineralogy and the history of water on Mars remain unresolved using the Viking analyses and Earth-based telescopic data. Identification and quantitation of iron-bearing clays on Mars would elucidate these outstanding issues. Near infrared correlation analysis, a method typically applied to qualitative and quantitative analysis of individual constituents of multicomponent mixtures, is adapted here to selection of distinctive features of a small, highly homologous series of Fe/Ca-exchanged montmorillonites and several kalinites. Independently determined measures of surface iron, relative humidity and stored electronic energy were used as constituent data for linear regression of the constituent vs. reflectance data throughout the spectral region 0.68 to 2.5 micrometers. High correlations were found in appropriate regions for all three constituents, though that with stored energy is still considered tenuous. Quantitation was improved using 1st and 2nd derivative spectra. High resolution data over a broad spectral range would be required to quantitatively identify iron-bearing clays by remotely sensed reflectance.

[Development and application of morphological analysis method in Aspergillus niger fermentation].

PubMed

Tang, Wenjun; Xia, Jianye; Chu, Ju; Zhuang, Yingping; Zhang, Siliang

2015-02-01

Filamentous fungi are widely used in industrial fermentation. Particular fungal morphology acts as a critical index for a successful fermentation. To break the bottleneck of morphological analysis, we have developed a reliable method for fungal morphological analysis. By this method, we can prepare hundreds of pellet samples simultaneously and obtain quantitative morphological information at large scale quickly. This method can largely increase the accuracy and reliability of morphological analysis result. Based on that, the studies of Aspergillus niger morphology under different oxygen supply conditions and shear rate conditions were carried out. As a result, the morphological responding patterns of A. niger morphology to these conditions were quantitatively demonstrated, which laid a solid foundation for the further scale-up.

Quantitative analysis of amygdalin and prunasin in Prunus serotina Ehrh. using (1) H-NMR spectroscopy.

PubMed

Santos Pimenta, Lúcia P; Schilthuizen, Menno; Verpoorte, Robert; Choi, Young Hae

2014-01-01

Prunus serotina is native to North America but has been invasively introduced in Europe since the seventeenth century. This plant contains cyanogenic glycosides that are believed to be related to its success as an invasive plant. For these compounds, chromatographic- or spectrometric-based (targeting on HCN hydrolysis) methods of analysis have been employed so far. However, the conventional methods require tedious preparation steps and a long measuring time. To develop a fast and simple method to quantify the cyanogenic glycosides, amygdalin and prunasin in dried Prunus serotina leaves without any pre-purification steps using (1) H-NMR spectroscopy. Extracts of Prunus serotina leaves using CH3 OH-d4 and KH2 PO4 buffer in D2 O (1:1) were quantitatively analysed for amygdalin and prunasin using (1) H-NMR spectroscopy. Different internal standards were evaluated for accuracy and stability. The purity of quantitated (1) H-NMR signals was evaluated using several two-dimensional NMR experiments. Trimethylsilylpropionic acid sodium salt-d4 proved most suitable as the internal standard for quantitative (1) H-NMR analysis. Two-dimensional J-resolved NMR was shown to be a useful tool to confirm the structures and to check for possible signal overlapping with the target signals for the quantitation. Twenty-two samples of P. serotina were subsequently quantitatively analysed for the cyanogenic glycosides prunasin and amygdalin. The NMR method offers a fast, high-throughput analysis of cyanogenic glycosides in dried leaves permitting simultaneous quantification and identification of prunasin and amygdalin in Prunus serotina. Copyright © 2013 John Wiley & Sons, Ltd.

A comparative study of qualitative and quantitative methods for the assessment of adhesive remnant after bracket debonding.

PubMed

Cehreli, S Burcak; Polat-Ozsoy, Omur; Sar, Cagla; Cubukcu, H Evren; Cehreli, Zafer C

2012-04-01

The amount of the residual adhesive after bracket debonding is frequently assessed in a qualitative manner, utilizing the adhesive remnant index (ARI). This study aimed to investigate whether quantitative assessment of the adhesive remnant yields more precise results compared to qualitative methods utilizing the 4- and 5-point ARI scales. Twenty debonded brackets were selected. Evaluation and scoring of the adhesive remnant on bracket bases were made consecutively using: 1. qualitative assessment (visual scoring) and 2. quantitative measurement (image analysis) on digital photographs. Image analysis was made on scanning electron micrographs (SEM) and high-precision elemental maps of the adhesive remnant as determined by energy dispersed X-ray spectrometry. Evaluations were made in accordance with the original 4-point and the modified 5-point ARI scales. Intra-class correlation coefficients (ICCs) were calculated, and the data were evaluated using Friedman test followed by Wilcoxon signed ranks test with Bonferroni correction. ICC statistics indicated high levels of agreement for qualitative visual scoring among examiners. The 4-point ARI scale was compliant with the SEM assessments but indicated significantly less adhesive remnant compared to the results of quantitative elemental mapping. When the 5-point scale was used, both quantitative techniques yielded similar results with those obtained qualitatively. These results indicate that qualitative visual scoring using the ARI is capable of generating similar results with those assessed by quantitative image analysis techniques. In particular, visual scoring with the 5-point ARI scale can yield similar results with both the SEM analysis and elemental mapping.

Accuracy Enhancement of Raman Spectroscopy Using Complementary Laser-Induced Breakdown Spectroscopy (LIBS) with Geologically Mixed Samples.

PubMed

Choi, Soojin; Kim, Dongyoung; Yang, Junho; Yoh, Jack J

2017-04-01

Quantitative Raman analysis was carried out with geologically mixed samples that have various matrices. In order to compensate the matrix effect in Raman shift, laser-induced breakdown spectroscopy (LIBS) analysis was performed. Raman spectroscopy revealed the geological materials contained in the mixed samples. However, the analysis of a mixture containing different matrices was inaccurate due to the weak signal of the Raman shift, interference, and the strong matrix effect. On the other hand, the LIBS quantitative analysis of atomic carbon and calcium in mixed samples showed high accuracy. In the case of the calcite and gypsum mixture, the coefficient of determination of atomic carbon using LIBS was 0.99, while the signal using Raman was less than 0.9. Therefore, the geological composition of the mixed samples is first obtained using Raman and the LIBS-based quantitative analysis is then applied to the Raman outcome in order to construct highly accurate univariate calibration curves. The study also focuses on a method to overcome matrix effects through the two complementary spectroscopic techniques of Raman spectroscopy and LIBS.

Fluorescence-labeled methylation-sensitive amplified fragment length polymorphism (FL-MS-AFLP) analysis for quantitative determination of DNA methylation and demethylation status.

PubMed

Kageyama, Shinji; Shinmura, Kazuya; Yamamoto, Hiroko; Goto, Masanori; Suzuki, Koichi; Tanioka, Fumihiko; Tsuneyoshi, Toshihiro; Sugimura, Haruhiko

2008-04-01

The PCR-based DNA fingerprinting method called the methylation-sensitive amplified fragment length polymorphism (MS-AFLP) analysis is used for genome-wide scanning of methylation status. In this study, we developed a method of fluorescence-labeled MS-AFLP (FL-MS-AFLP) analysis by applying a fluorescence-labeled primer and fluorescence-detecting electrophoresis apparatus to the existing method of MS-AFLP analysis. The FL-MS-AFLP analysis enables quantitative evaluation of more than 350 random CpG loci per run. It was shown to allow evaluation of the differences in methylation level of blood DNA of gastric cancer patients and evaluation of hypermethylation and hypomethylation in DNA from gastric cancer tissue in comparison with adjacent non-cancerous tissue.

Physiologically based pharmacokinetic (PBPK) modeling considering methylated trivalent arsenicals

EPA Science Inventory

PBPK modeling provides a quantitative biologically-based framework to integrate diverse types of information for application to risk analysis. For example, genetic polymorphisms in arsenic metabolizing enzymes (AS3MT) can lead to differences in target tissue dosimetry for key tri...

Power Grid Construction Project Portfolio Optimization Based on Bi-level programming model

NASA Astrophysics Data System (ADS)

Zhao, Erdong; Li, Shangqi

2017-08-01

As the main body of power grid operation, county-level power supply enterprises undertake an important emission to guarantee the security of power grid operation and safeguard social power using order. The optimization of grid construction projects has been a key issue of power supply capacity and service level of grid enterprises. According to the actual situation of power grid construction project optimization of county-level power enterprises, on the basis of qualitative analysis of the projects, this paper builds a Bi-level programming model based on quantitative analysis. The upper layer of the model is the target restriction of the optimal portfolio; the lower layer of the model is enterprises’ financial restrictions on the size of the enterprise project portfolio. Finally, using a real example to illustrate operation proceeding and the optimization result of the model. Through qualitative analysis and quantitative analysis, the bi-level programming model improves the accuracy and normative standardization of power grid enterprises projects.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Influence analysis in quantitative trait loci detection.

PubMed

Dou, Xiaoling; Kuriki, Satoshi; Maeno, Akiteru; Takada, Toyoyuki; Shiroishi, Toshihiko

2014-07-01

This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87.

PubMed

Pahn, Gregor; Skornitzke, Stephan; Schlemmer, Hans-Peter; Kauczor, Hans-Ulrich; Stiller, Wolfram

2016-01-01

Based on the guidelines from "Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography" of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated. The extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers. Spatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment. The presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Measurement Models for Reasoned Action Theory.

PubMed

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin

2012-03-01

Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach.

Quantitative Analysis of the Interdisciplinarity of Applied Mathematics.

PubMed

Xie, Zheng; Duan, Xiaojun; Ouyang, Zhenzheng; Zhang, Pengyuan

2015-01-01

The increasing use of mathematical techniques in scientific research leads to the interdisciplinarity of applied mathematics. This viewpoint is validated quantitatively here by statistical and network analysis on the corpus PNAS 1999-2013. A network describing the interdisciplinary relationships between disciplines in a panoramic view is built based on the corpus. Specific network indicators show the hub role of applied mathematics in interdisciplinary research. The statistical analysis on the corpus content finds that algorithms, a primary topic of applied mathematics, positively correlates, increasingly co-occurs, and has an equilibrium relationship in the long-run with certain typical research paradigms and methodologies. The finding can be understood as an intrinsic cause of the interdisciplinarity of applied mathematics.

Quantitative mutant analysis of viral quasispecies by chip-based matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry

PubMed Central

Amexis, Georgios; Oeth, Paul; Abel, Kenneth; Ivshina, Anna; Pelloquin, Francois; Cantor, Charles R.; Braun, Andreas; Chumakov, Konstantin

2001-01-01

RNA viruses exist as quasispecies, heterogeneous and dynamic mixtures of mutants having one or more consensus sequences. An adequate description of the genomic structure of such viral populations must include the consensus sequence(s) plus a quantitative assessment of sequence heterogeneities. For example, in quality control of live attenuated viral vaccines, the presence of even small quantities of mutants or revertants may indicate incomplete or unstable attenuation that may influence vaccine safety. Previously, we demonstrated the monitoring of oral poliovirus vaccine with the use of mutant analysis by PCR and restriction enzyme cleavage (MAPREC). In this report, we investigate genetic variation in live attenuated mumps virus vaccine by using both MAPREC and a platform (DNA MassArray) based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Mumps vaccines prepared from the Jeryl Lynn strain typically contain at least two distinct viral substrains, JL1 and JL2, which have been characterized by full length sequencing. We report the development of assays for characterizing sequence variants in these substrains and demonstrate their use in quantitative analysis of substrains and sequence variations in mixed virus cultures and mumps vaccines. The results obtained from both the MAPREC and MALDI-TOF methods showed excellent correlation. This suggests the potential utility of MALDI-TOF for routine quality control of live viral vaccines and for assessment of genetic stability and quantitative monitoring of genetic changes in other RNA viruses of clinical interest. PMID:11593021

Extracting microtubule networks from superresolution single-molecule localization microscopy data

PubMed Central

Zhang, Zhen; Nishimura, Yukako; Kanchanawong, Pakorn

2017-01-01

Microtubule filaments form ubiquitous networks that specify spatial organization in cells. However, quantitative analysis of microtubule networks is hampered by their complex architecture, limiting insights into the interplay between their organization and cellular functions. Although superresolution microscopy has greatly facilitated high-resolution imaging of microtubule filaments, extraction of complete filament networks from such data sets is challenging. Here we describe a computational tool for automated retrieval of microtubule filaments from single-molecule-localization–based superresolution microscopy images. We present a user-friendly, graphically interfaced implementation and a quantitative analysis of microtubule network architecture phenotypes in fibroblasts. PMID:27852898

Highly sensitive transient absorption imaging of graphene and graphene oxide in living cells and circulating blood.

PubMed

Li, Junjie; Zhang, Weixia; Chung, Ting-Fung; Slipchenko, Mikhail N; Chen, Yong P; Cheng, Ji-Xin; Yang, Chen

2015-07-23

We report a transient absorption (TA) imaging method for fast visualization and quantitative layer analysis of graphene and GO. Forward and backward imaging of graphene on various substrates under ambient condition was imaged with a speed of 2 μs per pixel. The TA intensity linearly increased with the layer number of graphene. Real-time TA imaging of GO in vitro with capability of quantitative analysis of intracellular concentration and ex vivo in circulating blood were demonstrated. These results suggest that TA microscopy is a valid tool for the study of graphene based materials.

Simultaneous extraction and quantitation of several bioactive amines in cheese and chocolate.

PubMed

Baker, G B; Wong, J T; Coutts, R T; Pasutto, F M

1987-04-17

A method is described for simultaneous extraction and quantitation of the amines 2-phenylethylamine, tele-methylhistamine, histamine, tryptamine, m- and p-tyramine, 3-methoxytyramine, 5-hydroxytryptamine, cadaverine, putrescine, spermidine and spermine. This method is based on extractive derivatization of the amines with a perfluoroacylating agent, pentafluorobenzoyl chloride, under basic aqueous conditions. Analysis was done on a gas chromatograph equipped with an electron-capture detector and a capillary column system. The procedure is relatively rapid and provides derivatives with good chromatographic properties. Its application to analysis of the above amines in cheese and chocolate products is described.

LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

PubMed Central

Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

2014-01-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

PubMed

Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

2012-03-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

PubMed

Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Van Dorssaeler, Alain; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

2016-01-30

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Portable paper-based device for quantitative colorimetric assays relying on light reflectance principle.

PubMed

Li, Bowei; Fu, Longwen; Zhang, Wei; Feng, Weiwei; Chen, Lingxin

2014-04-01

This paper presents a novel paper-based analytical device based on the colorimetric paper assays through its light reflectance. The device is portable, low cost (<20 dollars), and lightweight (only 176 g) that is available to assess the cost-effectiveness and appropriateness of the original health care or on-site detection information. Based on the light reflectance principle, the signal can be obtained directly, stably and user-friendly in our device. We demonstrated the utility and broad applicability of this technique with measurements of different biological and pollution target samples (BSA, glucose, Fe, and nitrite). Moreover, the real samples of Fe (II) and nitrite in the local tap water were successfully analyzed, and compared with the standard UV absorption method, the quantitative results showed good performance, reproducibility, and reliability. This device could provide quantitative information very conveniently and show great potential to broad fields of resource-limited analysis, medical diagnostics, and on-site environmental detection. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advanced body composition assessment: from body mass index to body composition profiling.

PubMed

Borga, Magnus; West, Janne; Bell, Jimmy D; Harvey, Nicholas C; Romu, Thobias; Heymsfield, Steven B; Dahlqvist Leinhard, Olof

2018-06-01

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment. © American Federation for Medical Research (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Detection of propofol concentrations in blood by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Wróbel, M. S.; Gnyba, M.; UrniaŻ, R.; Myllylä, T. S.; Jedrzejewska-Szczerska, M.

2015-07-01

In this paper we present a proof-of-concept of a Raman spectroscopy-based approach for measuring the content of propofol, a common anesthesia drug, in whole human blood, and plasma, which is intended for use during clinical procedures. This method utilizes the Raman spectroscopy as a chemically-sensitive method for qualitative detection of the presence of a drug and a quantitative determination of its concentration. A number of samples from different patients with added various concentrations of propofol IV solution were measured. This is most equivalent to a real in-vivo situation. Subsequent analysis of a set of spectra was carried out to extract qualitative and quantitative information. We conclude, that the changes in the spectra of blood with propofol, overlap with the most prominent lines of the propofol solution, especially at spectral regions: 1450 cm-1, 1250- 1260 cm-1, 1050 cm-1, 875-910 cm-1, 640 cm-1. Later, we have introduced a quantitative analysis program based on correlation matrix closest fit, and a LOO cross-validation. We have achieved 36.67% and 60% model precision when considering full spectra, or specified bands, respectively. These results prove the possibility of using Raman spectroscopy for quantitative detection of propofol concentrations in whole human blood.

[Quantitative surface analysis of Pt-Co, Cu-Au and Cu-Ag alloy films by XPS and AES].

PubMed

Li, Lian-Zhong; Zhuo, Shang-Jun; Shen, Ru-Xiang; Qian, Rong; Gao, Jie

2013-11-01

In order to improve the quantitative analysis accuracy of AES, We associated XPS with AES and studied the method to reduce the error of AES quantitative analysis, selected Pt-Co, Cu-Au and Cu-Ag binary alloy thin-films as the samples, used XPS to correct AES quantitative analysis results by changing the auger sensitivity factors to make their quantitative analysis results more similar. Then we verified the accuracy of the quantitative analysis of AES when using the revised sensitivity factors by other samples with different composition ratio, and the results showed that the corrected relative sensitivity factors can reduce the error in quantitative analysis of AES to less than 10%. Peak defining is difficult in the form of the integral spectrum of AES analysis since choosing the starting point and ending point when determining the characteristic auger peak intensity area with great uncertainty, and to make analysis easier, we also processed data in the form of the differential spectrum, made quantitative analysis on the basis of peak to peak height instead of peak area, corrected the relative sensitivity factors, and verified the accuracy of quantitative analysis by the other samples with different composition ratio. The result showed that the analytical error in quantitative analysis of AES reduced to less than 9%. It showed that the accuracy of AES quantitative analysis can be highly improved by the way of associating XPS with AES to correct the auger sensitivity factors since the matrix effects are taken into account. Good consistency was presented, proving the feasibility of this method.

Recent advances in mass spectrometry-based proteomics of gastric cancer.

PubMed

Kang, Changwon; Lee, Yejin; Lee, J Eugene

2016-10-07

The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

Quantitative analysis of RNA-protein interactions on a massively parallel array for mapping biophysical and evolutionary landscapes

PubMed Central

Buenrostro, Jason D.; Chircus, Lauren M.; Araya, Carlos L.; Layton, Curtis J.; Chang, Howard Y.; Snyder, Michael P.; Greenleaf, William J.

2015-01-01

RNA-protein interactions drive fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. Here we repurpose a high-throughput sequencing instrument to quantitatively measure binding and dissociation of MS2 coat protein to >107 RNA targets generated on a flow-cell surface by in situ transcription and inter-molecular tethering of RNA to DNA. We decompose the binding energy contributions from primary and secondary RNA structure, finding that differences in affinity are often driven by sequence-specific changes in association rates. By analyzing the biophysical constraints and modeling mutational paths describing the molecular evolution of MS2 from low- to high-affinity hairpins, we quantify widespread molecular epistasis, and a long-hypothesized structure-dependent preference for G:U base pairs over C:A intermediates in evolutionary trajectories. Our results suggest that quantitative analysis of RNA on a massively parallel array (RNAMaP) relationships across molecular variants. PMID:24727714

Quantitative x-ray phase-contrast imaging using a single grating of comparable pitch to sample feature size.

PubMed

Morgan, Kaye S; Paganin, David M; Siu, Karen K W

2011-01-01

The ability to quantitatively retrieve transverse phase maps during imaging by using coherent x rays often requires a precise grating or analyzer-crystal-based setup. Imaging of live animals presents further challenges when these methods require multiple exposures for image reconstruction. We present a simple method of single-exposure, single-grating quantitative phase contrast for a regime in which the grating period is much greater than the effective pixel size. A grating is used to create a high-visibility reference pattern incident on the sample, which is distorted according to the complex refractive index and thickness of the sample. The resolution, along a line parallel to the grating, is not restricted by the grating spacing, and the detector resolution becomes the primary determinant of the spatial resolution. We present a method of analysis that maps the displacement of interrogation windows in order to retrieve a quantitative phase map. Application of this analysis to the imaging of known phantoms shows excellent correspondence.

Improving membrane based multiplex immunoassays for semi-quantitative detection of multiple cytokines in a single sample

PubMed Central

2014-01-01

Background Inflammatory mediators can serve as biomarkers for the monitoring of the disease progression or prognosis in many conditions. In the present study we introduce an adaptation of a membrane-based technique in which the level of up to 40 cytokines and chemokines can be determined in both human and rodent blood in a semi-quantitative way. The planar assay was modified using the LI-COR (R) detection system (fluorescence based) rather than chemiluminescence and semi-quantitative outcomes were achieved by normalizing the outcomes using the automated exposure settings of the Odyssey readout device. The results were compared to the gold standard assay, namely ELISA. Results The improved planar assay allowed the detection of a considerably higher number of analytes (n = 30 and n = 5 for fluorescent and chemiluminescent detection, respectively). The improved planar method showed high sensitivity up to 17 pg/ml and a linear correlation of the normalized fluorescence intensity with the results from the ELISA (r = 0.91). Conclusions The results show that the membrane-based technique is a semi-quantitative assay that correlates satisfactorily to the gold standard when enhanced by the use of fluorescence and subsequent semi-quantitative analysis. This promising technique can be used to investigate inflammatory profiles in multiple conditions, particularly in studies with constraints in sample sizes and/or budget. PMID:25022797

Higher Education Students' Attitudes towards Experiential Learning in International Business

ERIC Educational Resources Information Center

Chavan, Meena

2011-01-01

Using qualitative and quantitative analysis this paper presents a teaching model based on experiential learning in a large "International Business" unit. Preliminary analysis of 92 student evaluations determined the effectiveness of experiential learning to allow students to explore the association between theory and practice. The…

The Role of Recurrence Plots in Characterizing the Output-Unemployment Relationship: An Analysis

PubMed Central

Caraiani, Petre; Haven, Emmanuel

2013-01-01

We analyse the output-unemployment relationship using an approach based on cross-recurrence plots and quantitative recurrence analysis. We use post-war period quarterly U.S. data. The results obtained show the emergence of a complex and interesting relationship. PMID:23460814

Multiplexed and Microparticle-based Analyses: Quantitative Tools for the Large-Scale Analysis of Biological Systems

PubMed Central

Nolan, John P.; Mandy, Francis

2008-01-01

While the term flow cytometry refers to the measurement of cells, the approach of making sensitive multiparameter optical measurements in a flowing sample stream is a very general analytical approach. The past few years have seen an explosion in the application of flow cytometry technology for molecular analysis and measurements using micro-particles as solid supports. While microsphere-based molecular analyses using flow cytometry date back three decades, the need for highly parallel quantitative molecular measurements that has arisen from various genomic and proteomic advances has driven the development in particle encoding technology to enable highly multiplexed assays. Multiplexed particle-based immunoassays are now common place, and new assays to study genes, protein function, and molecular assembly. Numerous efforts are underway to extend the multiplexing capabilities of microparticle-based assays through new approaches to particle encoding and analyte reporting. The impact of these developments will be seen in the basic research and clinical laboratories, as well as in drug development. PMID:16604537

Medium-based noninvasive preimplantation genetic diagnosis for human α-thalassemias-SEA.

PubMed

Wu, Haitao; Ding, Chenhui; Shen, Xiaoting; Wang, Jing; Li, Rong; Cai, Bing; Xu, Yanwen; Zhong, Yiping; Zhou, Canquan

2015-03-01

To develop a noninvasive medium-based preimplantation genetic diagnosis (PGD) test for α-thalassemias-SEA. The embryos of α-thalassemia-SEA carriers undergoing in vitro fertilization (IVF) were cultured. Single cells were biopsied from blastomeres and subjected to fluorescent gap polymerase chain reaction (PCR) analysis; the spent culture media that contained embryo genomic DNA and corresponding blastocysts as verification were subjected to quantitative-PCR (Q-PCR) detection of α-thalassemia-SEA. The diagnosis efficiency and allele dropout (ADO) ratio were calculated, and the cell-free DNA concentration was quantitatively assessed in the culture medium. The diagnosis efficiency of medium-based α-thalassemias-SEA detection significantly increased compared with that of biopsy-based fluorescent gap PCR analysis (88.6% vs 82.1%, P < 0.05). There is no significant difference regarding ADO ratio between them. The optimal time for medium-based α-thalassemias-SEA detection is Day 5 (D5) following IVF. Medium-based α-thalassemias-SEA detection could represent a novel, quick, and noninvasive approach for carriers to undergo IVF and PGD.

Quantitative Clinical Diagnostic Analysis of Acetone in Human Blood by HPLC: A Metabolomic Search for Acetone as Indicator

PubMed Central

Akgul Kalkan, Esin; Sahiner, Mehtap; Ulker Cakir, Dilek; Alpaslan, Duygu; Yilmaz, Selehattin

2016-01-01

Using high-performance liquid chromatography (HPLC) and 2,4-dinitrophenylhydrazine (2,4-DNPH) as a derivatizing reagent, an analytical method was developed for the quantitative determination of acetone in human blood. The determination was carried out at 365 nm using an ultraviolet-visible (UV-Vis) diode array detector (DAD). For acetone as its 2,4-dinitrophenylhydrazone derivative, a good separation was achieved with a ThermoAcclaim C18 column (15 cm × 4.6 mm × 3 μm) at retention time (t R) 12.10 min and flowrate of 1 mL min−1 using a (methanol/acetonitrile) water elution gradient. The methodology is simple, rapid, sensitive, and of low cost, exhibits good reproducibility, and allows the analysis of acetone in biological fluids. A calibration curve was obtained for acetone using its standard solutions in acetonitrile. Quantitative analysis of acetone in human blood was successfully carried out using this calibration graph. The applied method was validated in parameters of linearity, limit of detection and quantification, accuracy, and precision. We also present acetone as a useful tool for the HPLC-based metabolomic investigation of endogenous metabolism and quantitative clinical diagnostic analysis. PMID:27298750

Direct comparison of low- and mid-frequency Raman spectroscopy for quantitative solid-state pharmaceutical analysis.

PubMed

Lipiäinen, Tiina; Fraser-Miller, Sara J; Gordon, Keith C; Strachan, Clare J

2018-02-05

This study considers the potential of low-frequency (terahertz) Raman spectroscopy in the quantitative analysis of ternary mixtures of solid-state forms. Direct comparison between low-frequency and mid-frequency spectral regions for quantitative analysis of crystal form mixtures, without confounding sampling and instrumental variations, is reported for the first time. Piroxicam was used as a model drug, and the low-frequency spectra of piroxicam forms β, α2 and monohydrate are presented for the first time. These forms show clear spectral differences in both the low- and mid-frequency regions. Both spectral regions provided quantitative models suitable for predicting the mixture compositions using partial least squares regression (PLSR), but the low-frequency data gave better models, based on lower errors of prediction (2.7, 3.1 and 3.2% root-mean-square errors of prediction [RMSEP] values for the β, α2 and monohydrate forms, respectively) than the mid-frequency data (6.3, 5.4 and 4.8%, for the β, α2 and monohydrate forms, respectively). The better performance of low-frequency Raman analysis was attributed to larger spectral differences between the solid-state forms, combined with a higher signal-to-noise ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

Bayes` theorem and quantitative risk assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaplan, S.

1994-12-31

This paper argues that for a quantitative risk analysis (QRA) to be useful for public and private decision making, and for rallying the support necessary to implement those decisions, it is necessary that the QRA results be ``trustable.`` Trustable means that the results are based solidly and logically on all the relevant evidence available. This, in turn, means that the quantitative results must be derived from the evidence using Bayes` theorem. Thus, it argues that one should strive to make their QRAs more clearly and explicitly Bayesian, and in this way make them more ``evidence dependent`` than ``personality dependent.``

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

A Tutorial on Multiblock Discriminant Correspondence Analysis (MUDICA): A New Method for Analyzing Discourse Data from Clinical Populations

ERIC Educational Resources Information Center

Williams, Lynne J.; Abdi, Herve; French, Rebecca; Orange, Joseph B.

2010-01-01

Purpose: In communication disorders research, clinical groups are frequently described based on patterns of performance, but researchers often study only a few participants described by many quantitative and qualitative variables. These data are difficult to handle with standard inferential tools (e.g., analysis of variance or factor analysis)…

Visual and Quantitative Analysis Methods of Respiratory Patterns for Respiratory Gated PET/CT.

PubMed

Son, Hye Joo; Jeong, Young Jin; Yoon, Hyun Jin; Park, Jong-Hwan; Kang, Do-Young

2016-01-01

We integrated visual and quantitative methods for analyzing the stability of respiration using four methods: phase space diagrams, Fourier spectra, Poincaré maps, and Lyapunov exponents. Respiratory patterns of 139 patients were grouped based on the combination of the regularity of amplitude, period, and baseline positions. Visual grading was done by inspecting the shape of diagram and classified into two states: regular and irregular. Quantitation was done by measuring standard deviation of x and v coordinates of Poincaré map (SD x , SD v ) or the height of the fundamental peak ( A 1 ) in Fourier spectrum or calculating the difference between maximal upward and downward drift. Each group showed characteristic pattern on visual analysis. There was difference of quantitative parameters (SD x , SD v , A 1 , and MUD-MDD) among four groups (one way ANOVA, p = 0.0001 for MUD-MDD, SD x , and SD v , p = 0.0002 for A 1 ). In ROC analysis, the cutoff values were 0.11 for SD x (AUC: 0.982, p < 0.0001), 0.062 for SD v (AUC: 0.847, p < 0.0001), 0.117 for A 1 (AUC: 0.876, p < 0.0001), and 0.349 for MUD-MDD (AUC: 0.948, p < 0.0001). This is the first study to analyze multiple aspects of respiration using various mathematical constructs and provides quantitative indices of respiratory stability and determining quantitative cutoff value for differentiating regular and irregular respiration.

A clustering approach to segmenting users of internet-based risk calculators.

PubMed

Harle, C A; Downs, J S; Padman, R

2011-01-01

Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

Effectiveness of Myocardial Contrast Echocardiography Quantitative Analysis during Adenosine Stress versus Visual Analysis before Percutaneous Therapy in Acute Coronary Pain: A Coronary Artery TIMI Grading Comparing Study

PubMed Central

Yang, Lixia; Mu, Yuming; Quaglia, Luiz Augusto; Tang, Qi; Guan, Lina; Wang, Chunmei; Shih, Ming Chi

2012-01-01

The study aim was to compare two different stress echocardiography interpretation techniques based on the correlation with thrombosis in myocardial infarction (TIMI ) flow grading from acute coronary syndrome (ACS) patients. Forty-one patients with suspected ACS were studied before diagnostic coronary angiography with myocardial contrast echocardiography (MCE) at rest and at stress. The correlation of visual interpretation of MCE and TIMI flow grade was significant. The quantitative analysis (myocardial perfusion parameters: A, β, and A × β) and TIMI flow grade were significant. MCE visual interpretation and TIMI flow grade had a high degree of agreement, on diagnosing myocardial perfusion abnormality. If one considers TIMI flow grade <3 as abnormal, MCE visual interpretation at rest had 73.1% accuracy with 58.2% sensitivity and 84.2% specificity and at stress had 80.4% accuracy with 76.6% sensitivity and 83.3% specificity. The MCE quantitative analysis has better accuracy with 100% of agreement with different level of TIMI flow grading. MCE quantitative analysis at stress has showed a direct correlation with TIMI flow grade, more significant than the visual interpretation technique. Further studies could measure the clinical relevance of this more objective approach to managing acute coronary syndrome patient before percutaneous coronary intervention (PCI). PMID:22778555

Remote quantitative analysis of minerals based on multispectral line-calibrated laser-induced breakdown spectroscopy (LIBS).

PubMed

Wan, Xiong; Wang, Peng

2014-01-01

Laser-induced breakdown spectroscopy (LIBS) is a feasible remote sensing technique used for mineral analysis in some unapproachable places where in situ probing is needed, such as analysis of radioactive elements in a nuclear leak or the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Here a compact custom 15 m focus optical component, combining a six times beam expander with a telescope, has been built, with which the laser beam of a 1064 nm Nd ; YAG laser is focused on remote minerals. The excited LIBS signals that reveal the elemental compositions of minerals are collected by another compact single lens-based signal acquisition system. In our remote LIBS investigations, the LIBS spectra of an unknown ore have been detected, from which the metal compositions are obtained. In addition, a multi-spectral line calibration (MSLC) method is proposed for the quantitative analysis of elements. The feasibility of the MSLC and its superiority over a single-wavelength determination have been confirmed by comparison with traditional chemical analysis of the copper content in the ore.

Distance-Based Tear Lactoferrin Assay on Microfluidic Paper Device Using Interfacial Interactions on Surface-Modified Cellulose.

PubMed

Yamada, Kentaro; Henares, Terence G; Suzuki, Koji; Citterio, Daniel

2015-11-11

"Distance-based" detection motifs on microfluidic paper-based analytical devices (μPADs) allow quantitative analysis without using signal readout instruments in a similar manner to classical analogue thermometers. To realize a cost-effective and calibration-free distance-based assay of lactoferrin in human tear fluid on a μPAD not relying on antibodies or enzymes, we investigated the fluidic mobilities of the target protein and Tb(3+) cations used as the fluorescent detection reagent on surface-modified cellulosic filter papers. Chromatographic elution experiments in a tear-like sample matrix containing electrolytes and proteins revealed a collapse of attractive electrostatic interactions between lactoferrin or Tb(3+) and the cellulosic substrate, which was overcome by the modification of the paper surface with the sulfated polysaccharide ι-carrageenan. The resulting μPAD based on the fluorescence emission distance successfully analyzed 0-4 mg mL(-1) of lactoferrin in complex human tear matrix with a lower limit of detection of 0.1 mg mL(-1) by simple visual inspection. Assay results of 18 human tear samples including ocular disease patients and healthy volunteers showed good correlation to the reference ELISA method with a slope of 0.997 and a regression coefficient of 0.948. The distance-based quantitative signal and the good batch-to-batch fabrication reproducibility relying on printing methods enable quantitative analysis by simply reading out "concentration scale marks" printed on the μPAD without performing any calibration and using any signal readout instrument.

Toward quantitative estimation of material properties with dynamic mode atomic force microscopy: a comparative study.

PubMed

Ghosal, Sayan; Gannepalli, Anil; Salapaka, Murti

2017-08-11

In this article, we explore methods that enable estimation of material properties with the dynamic mode atomic force microscopy suitable for soft matter investigation. The article presents the viewpoint of casting the system, comprising of a flexure probe interacting with the sample, as an equivalent cantilever system and compares a steady-state analysis based method with a recursive estimation technique for determining the parameters of the equivalent cantilever system in real time. The steady-state analysis of the equivalent cantilever model, which has been implicitly assumed in studies on material property determination, is validated analytically and experimentally. We show that the steady-state based technique yields results that quantitatively agree with the recursive method in the domain of its validity. The steady-state technique is considerably simpler to implement, however, slower compared to the recursive technique. The parameters of the equivalent system are utilized to interpret storage and dissipative properties of the sample. Finally, the article identifies key pitfalls that need to be avoided toward the quantitative estimation of material properties.

A novel image-based quantitative method for the characterization of NETosis

PubMed Central

Zhao, Wenpu; Fogg, Darin K.; Kaplan, Mariana J.

2015-01-01

NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional ‘suicidal’ NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of ‘vital’ NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess ‘suicidal’ or ‘vital’ NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both ‘suicidal’ and ‘vital’ NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. Use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies. PMID:26003624

Precise Quantitation of MicroRNA in a Single Cell with Droplet Digital PCR Based on Ligation Reaction.

PubMed

Tian, Hui; Sun, Yuanyuan; Liu, Chenghui; Duan, Xinrui; Tang, Wei; Li, Zhengping

2016-12-06

MicroRNA (miRNA) analysis in a single cell is extremely important because it allows deep understanding of the exact correlation between the miRNAs and cell functions. Herein, we wish to report a highly sensitive and precisely quantitative assay for miRNA detection based on ligation-based droplet digital polymerase chain reaction (ddPCR), which permits the quantitation of miRNA in a single cell. In this ligation-based ddPCR assay, two target-specific oligonucleotide probes can be simply designed to be complementary to the half-sequence of the target miRNA, respectively, which avoids the sophisticated design of reverse transcription and provides high specificity to discriminate a single-base difference among miRNAs with simple operations. After the miRNA-templated ligation, the ddPCR partitions individual ligated products into a water-in-oil droplet and digitally counts the fluorescence-positive and negative droplets after PCR amplification for quantification of the target molecules, which possesses the power of precise quantitation and robustness to variation in PCR efficiency. By integrating the advantages of the precise quantification of ddPCR and the simplicity of the ligation-based PCR, the proposed method can sensitively measure let-7a miRNA with a detection limit of 20 aM (12 copies per microliter), and even a single-base difference can be discriminated in let-7 family members. More importantly, due to its high selectivity and sensitivity, the proposed method can achieve precise quantitation of miRNAs in single-cell lysate. Therefore, the ligation-based ddPCR assay may serve as a useful tool to exactly reveal the miRNAs' actions in a single cell, which is of great importance for the study of miRNAs' biofunction as well as for the related biomedical studies.

Using a SWOT analysis to inform healthy eating and physical activity strategies for a remote First Nations community in Canada.

PubMed

Skinner, Kelly; Hanning, Rhona M; Sutherland, Celine; Edwards-Wheesk, Ruby; Tsuji, Leonard J S

2012-01-01

To plan community-driven health promotion strategies based on a strengths, weaknesses, opportunities, and threats (SWOT) analysis of the healthy eating and physical activity patterns of First Nation (FN) youth. Cross-sectional qualitative and quantitative data used to develop SWOT themes and strategies. Remote, subarctic FN community of Fort Albany, Ontario, Canada. Adult (n  =  25) and youth (n  =  66, grades 6-11) community members. Qualitative data were collected using five focus groups with adults (two focus groups) and youth (three focus groups), seven individual interviews with adults, and an environmental scan of 13 direct observations of events/locations (e.g., the grocery store). Quantitative data on food/physical activity behaviors were collected using a validated Web-based survey with youth. Themes were identified from qualitative and quantitative data and were analyzed and interpreted within a SWOT matrix. Thirty-two SWOT themes were identified (e.g., accessibility of existing facilities, such as the gymnasium). The SWOT analysis showed how these themes could be combined and transformed into 12 strategies (e.g., expanding and enhancing the school snack/breakfast program) while integrating suggestions from the community. SWOT analysis was a beneficial tool that facilitated the combination of local data and community ideas in the development of targeted health promotion strategies for the FN community of Fort Albany.

Label free quantitative proteomics analysis on the cisplatin resistance in ovarian cancer cells.

PubMed

Wang, F; Zhu, Y; Fang, S; Li, S; Liu, S

2017-05-20

Quantitative proteomics has been made great progress in recent years. Label free quantitative proteomics analysis based on the mass spectrometry is widely used. Using this technique, we determined the differentially expressed proteins in the cisplatin-sensitive ovarian cancer cells COC1 and cisplatin-resistant cells COC1/DDP before and after the application of cisplatin. Using the GO analysis, we classified those proteins into different subgroups bases on their cellular component, biological process, and molecular function. We also used KEGG pathway analysis to determine the key signal pathways that those proteins were involved in. There are 710 differential proteins between COC1 and COC1/DDP cells, 783 between COC1 and COC1/DDP cells treated with cisplatin, 917 between the COC1/DDP cells and COC1/DDP cells treated with LaCl3, 775 between COC1/DDP cells treated with cisplatin and COC1/DDP cells treated with cisplatin and LaCl3. Among the same 411 differentially expressed proteins in cisplatin-sensitive COC1 cells and cisplain-resistant COC1/DDP cells before and after cisplatin treatment, 14% of them were localized on the cell membrane. According to the KEGG results, differentially expressed proteins were classified into 21 groups. The most abundant proteins were involved in spliceosome. This study lays a foundation for deciphering the mechanism for drug resistance in ovarian tumor.

Methylation analysis of plasma cell-free DNA for breast cancer early detection using bisulfite next-generation sequencing.

PubMed

Li, Zibo; Guo, Xinwu; Tang, Lili; Peng, Limin; Chen, Ming; Luo, Xipeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Xia, Kun; Wang, Jun

2016-10-01

Circulating cell-free DNA (cfDNA) has been considered as a potential biomarker for non-invasive cancer detection. To evaluate the methylation levels of six candidate genes (EGFR, GREM1, PDGFRB, PPM1E, SOX17, and WRN) in plasma cfDNA as biomarkers for breast cancer early detection, quantitative analysis of the promoter methylation of these genes from 86 breast cancer patients and 67 healthy controls was performed by using microfluidic-PCR-based target enrichment and next-generation bisulfite sequencing technology. The predictive performance of different logistic models based on methylation status of candidate genes was investigated by means of the area under the ROC curve (AUC) and odds ratio (OR) analysis. Results revealed that EGFR, PPM1E, and 8 gene-specific CpG sites showed significantly hypermethylation in cancer patients' plasma and significantly associated with breast cancer (OR ranging from 2.51 to 9.88). The AUC values for these biomarkers were ranging from 0.66 to 0.75. Combinations of multiple hypermethylated genes or CpG sites substantially improved the predictive performance for breast cancer detection. Our study demonstrated the feasibility of quantitative measurement of candidate gene methylation in cfDNA by using microfluidic-PCR-based target enrichment and bisulfite next-generation sequencing, which is worthy of further validation and potentially benefits a broad range of applications in clinical oncology practice. Quantitative analysis of methylation pattern of plasma cfDNA by next-generation sequencing might be a valuable non-invasive tool for early detection of breast cancer.

Quantitative Analysis of Tetramethylenedisulfotetramine ("Tetramine") Spiked into Beverages by Liquid Chromatography Tandem Mass Spectrometry with Validation by Gas Chromatography Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owens, J; Hok, S; Alcaraz, A

Tetramethylenedisulfotetramine, commonly known as tetramine, is a highly neurotoxic rodenticide (human oral LD{sub 50} = 0.1 mg/kg) used in hundreds of deliberate food poisoning events in China. Here we describe a method for quantitation of tetramine spiked into beverages, including milk, juice, tea, cola, and water and cleaned up by C8 solid phase extraction and liquid-liquid extraction. Quantitation by high performance liquid chromatography tandem mass spectrometry (LC/MS/MS) was based upon fragmentation of m/z 347 to m/z 268. The method was validated by gas chromatography mass spectrometry (GC/MS) operated in SIM mode for ions m/z 212, 240, and 360. The limitmore » of quantitation was 0.10 {micro}g/mL by LC/MS/MS versus 0.15 {micro}g/mL for GC/MS. Fortifications of the beverages at 2.5 {micro}g/mL and 0.25 {micro}g/mL were recovered ranging from 73-128% by liquid-liquid extraction for GC/MS analysis, 13-96% by SPE and 10-101% by liquid-liquid extraction for LC/MS/MS analysis.« less

Meeting Report: Tissue-based Image Analysis.

PubMed

Saravanan, Chandra; Schumacher, Vanessa; Brown, Danielle; Dunstan, Robert; Galarneau, Jean-Rene; Odin, Marielle; Mishra, Sasmita

2017-10-01

Quantitative image analysis (IA) is a rapidly evolving area of digital pathology. Although not a new concept, the quantification of histological features on photomicrographs used to be cumbersome, resource-intensive, and limited to specialists and specialized laboratories. Recent technological advances like highly efficient automated whole slide digitizer (scanner) systems, innovative IA platforms, and the emergence of pathologist-friendly image annotation and analysis systems mean that quantification of features on histological digital images will become increasingly prominent in pathologists' daily professional lives. The added value of quantitative IA in pathology includes confirmation of equivocal findings noted by a pathologist, increasing the sensitivity of feature detection, quantification of signal intensity, and improving efficiency. There is no denying that quantitative IA is part of the future of pathology; however, there are also several potential pitfalls when trying to estimate volumetric features from limited 2-dimensional sections. This continuing education session on quantitative IA offered a broad overview of the field; a hands-on toxicologic pathologist experience with IA principles, tools, and workflows; a discussion on how to apply basic stereology principles in order to minimize bias in IA; and finally, a reflection on the future of IA in the toxicologic pathology field.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes.

PubMed

Yu, Clinton; Huszagh, Alexander; Viner, Rosa; Novitsky, Eric J; Rychnovsky, Scott D; Huang, Lan

2016-10-18

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

PubMed

Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

2015-12-01

An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

Evaluating Computer-Related Incidents on Campus

ERIC Educational Resources Information Center

Rothschild, Daniel; Rezmierski, Virginia

2004-01-01

The Computer Incident Factor Analysis and Categorization (CIFAC) Project at the University of Michigan began in September 2003 with grants from EDUCAUSE and the National Science Foundation (NSF). The project's primary goal is to create a best-practices security framework for colleges and universities based on rigorous quantitative analysis of…

Image analysis and modeling in medical image computing. Recent developments and advances.

PubMed

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body. Hence, model-based image computing methods are important tools to improve medical diagnostics and patient treatment in future.

Thinking big

NASA Astrophysics Data System (ADS)

Collins, Harry

2008-02-01

Physicists are often quick to discount social research based on qualitative techniques such as ethnography and "deep case studies" - where a researcher draws conclusions about a community based on immersion in the field - thinking that only quantitative research backed up by statistical analysis is sound. The balance is not so clear, however.

DNA BASED METHOD OF MOLD AND APPLYING THE ENVIRONMENTAL RELATIVE MOLDINESS INDEX (ERMI)

EPA Science Inventory

NASA facilities can potentially have mold contamination problems. The EPA has created an Environmental Relative Moldiness Index based on the analysis of dust by Mold Specific Quantitative PCR (MSQPCR). In this presentation, the scientific background for the ERMI will be present...

Dependency, democracy, and infant mortality: a quantitative, cross-national analysis of less developed countries.

PubMed

Shandra, John M; Nobles, Jenna; London, Bruce; Williamson, John B

2004-07-01

This study presents quantitative, sociological models designed to account for cross-national variation in infant mortality rates. We consider variables linked to four different theoretical perspectives: the economic modernization, social modernization, political modernization, and dependency perspectives. The study is based on a panel regression analysis of a sample of 59 developing countries. Our preliminary analysis based on additive models replicates prior studies to the extent that we find that indicators linked to economic and social modernization have beneficial effects on infant mortality. We also find support for hypotheses derived from the dependency perspective suggesting that multinational corporate penetration fosters higher levels of infant mortality. Subsequent analysis incorporating interaction effects suggest that the level of political democracy conditions the effects of dependency relationships based upon exports, investments from multinational corporations, and international lending institutions. Transnational economic linkages associated with exports, multinational corporations, and international lending institutions adversely affect infant mortality more strongly at lower levels of democracy than at higher levels of democracy: intranational, political factors interact with the international, economic forces to affect infant mortality. We conclude with some brief policy recommendations and suggestions for the direction of future research.

EBprot: Statistical analysis of labeling-based quantitative proteomics data.

PubMed

Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon

2015-08-01

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

TREX13 Data Analysis/Modeling

DTIC Science & Technology

2015-09-30

TREX13 data analysis /modeling Dajun (DJ) Tang Applied Physics Laboratory, University of Washington 1013 NE 40th Street, Seattle, WA 98105...accuracy in those predictions. With extensive TREX13 data in hand, the objective now shifts to realizing the long-term goals using data analysis and...be quantitatively addressed. The approach to analysis can be summarized into the following steps: 1. Based on measurements, assess to what degree

Chemical purity using quantitative 1H-nuclear magnetic resonance: a hierarchical Bayesian approach for traceable calibrations

NASA Astrophysics Data System (ADS)

Toman, Blaza; Nelson, Michael A.; Lippa, Katrice A.

2016-10-01

Chemical purity assessment using quantitative 1H-nuclear magnetic resonance spectroscopy is a method based on ratio references of mass and signal intensity of the analyte species to that of chemical standards of known purity. As such, it is an example of a calculation using a known measurement equation with multiple inputs. Though multiple samples are often analyzed during purity evaluations in order to assess measurement repeatability, the uncertainty evaluation must also account for contributions from inputs to the measurement equation. Furthermore, there may be other uncertainty components inherent in the experimental design, such as independent implementation of multiple calibration standards. As such, the uncertainty evaluation is not purely bottom up (based on the measurement equation) or top down (based on the experimental design), but inherently contains elements of both. This hybrid form of uncertainty analysis is readily implemented with Bayesian statistical analysis. In this article we describe this type of analysis in detail and illustrate it using data from an evaluation of chemical purity and its uncertainty for a folic acid material.

Blackboard architecture for medical image interpretation

NASA Astrophysics Data System (ADS)

Davis, Darryl N.; Taylor, Christopher J.

1991-06-01

There is a growing interest in using sophisticated knowledge-based systems for biomedical image interpretation. We present a principled attempt to use artificial intelligence methodologies in interpreting lateral skull x-ray images. Such radiographs are routinely used in cephalometric analysis to provide quantitative measurements useful to clinical orthodontists. Manual and interactive methods of analysis are known to be error prone and previous attempts to automate this analysis typically fail to capture the expertise and adaptability required to cope with the variability in biological structure and image quality. An integrated model-based system has been developed which makes use of a blackboard architecture and multiple knowledge sources. A model definition interface allows quantitative models, of feature appearance and location, to be built from examples as well as more qualitative modelling constructs. Visual task definition and blackboard control modules allow task-specific knowledge sources to act on information available to the blackboard in a hypothesise and test reasoning cycle. Further knowledge-based modules include object selection, location hypothesis, intelligent segmentation, and constraint propagation systems. Alternative solutions to given tasks are permitted.

An analytical approach based on ESI-MS, LC-MS and PCA for the quali-quantitative analysis of cycloartane derivatives in Astragalus spp.

PubMed

Napolitano, Assunta; Akay, Seref; Mari, Angela; Bedir, Erdal; Pizza, Cosimo; Piacente, Sonia

2013-11-01

Astragalus species are widely used as health foods and dietary supplements, as well as drugs in traditional medicine. To rapidly evaluate metabolite similarities and differences among the EtOH extracts of the roots of eight commercial Astragalus spp., an approach based on direct analyses by ESI-MS followed by PCA of ESI-MS data, was carried out. Successively, quali-quantitative analyses of cycloartane derivatives in the eight Astragalus spp. by LC-ESI-MS(n) and PCA of LC-ESI-MS data were performed. This approach allowed to promptly highlighting metabolite similarities and differences among the various Astragalus spp. PCA results from LC-ESI-MS data of Astragalus samples were in reasonable agreement with both PCA results of ESI-MS data and quantitative results. This study affords an analytical method for the quali-quantitative determination of cycloartane derivatives in herbal preparations used as health and food supplements. Copyright © 2013 Elsevier B.V. All rights reserved.

Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method

PubMed Central

Nuzzo, Genoveffa; Gallo, Carmela; d’Ippolito, Giuliana; Cutignano, Adele; Sardo, Angela; Fontana, Angelo

2013-01-01

Accurate characterization of biomass constituents is a crucial aspect of research in the biotechnological application of natural products. Here we report an efficient, fast and reproducible method for the identification and quantitation of fatty acids and complex lipids (triacylglycerols, glycolipids, phospholipids) in microalgae under investigation for the development of functional health products (probiotics, food ingredients, drugs, etc.) or third generation biofuels. The procedure consists of extraction of the biological matrix by modified Folch method and direct analysis of the resulting material by proton nuclear magnetic resonance (1H NMR). The protocol uses a reference electronic signal as external standard (ERETIC method) and allows assessment of total lipid content, saturation degree and class distribution in both high throughput screening of algal collection and metabolic analysis during genetic or culturing studies. As proof of concept, the methodology was applied to the analysis of three microalgal species (Thalassiosira weissflogii, Cyclotella cryptica and Nannochloropsis salina) which drastically differ for the qualitative and quantitative composition of their fatty acid-based lipids. PMID:24084790

Differences in standing and sitting postures of youth with idiopathic scoliosis from quantitative analysis of digital photographs.

PubMed

Fortin, Carole; Ehrmann Feldman, Debbie; Cheriet, Farida; Labelle, Hubert

2013-08-01

The objective of this study was to explore whether differences in standing and sitting postures of youth with idiopathic scoliosis could be detected from quantitative analysis of digital photographs. Standing and sitting postures of 50 participants aged 10-20-years-old with idiopathic scoliosis (Cobb angle: 15° to 60°) were assessed from digital photographs using a posture evaluation software program. Based on the XY coordinates of markers, 13 angular and linear posture indices were calculated in both positions. Paired t-tests were used to compare values of standing and sitting posture indices. Significant differences between standing and sitting positions (p < 0.05) were found for head protraction, shoulder elevation, scapula asymmetry, trunk list, scoliosis angle, waist angles, and frontal and sagittal plane pelvic tilt. Quantitative analysis of digital photographs is a clinically feasible method to measure standing and sitting postures among youth with scoliosis and to assist in decisions on therapeutic interventions.

Quantitative Doppler Analysis Using Conventional Color Flow Imaging Acquisitions.

PubMed

Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Lovstakken, Lasse

2018-05-01

Interleaved acquisitions used in conventional triplex mode result in a tradeoff between the frame rate and the quality of velocity estimates. On the other hand, workflow becomes inefficient when the user has to switch between different modes, and measurement variability is increased. This paper investigates the use of power spectral Capon estimator in quantitative Doppler analysis using data acquired with conventional color flow imaging (CFI) schemes. To preserve the number of samples used for velocity estimation, only spatial averaging was utilized, and clutter rejection was performed after spectral estimation. The resulting velocity spectra were evaluated in terms of spectral width using a recently proposed spectral envelope estimator. The spectral envelopes were also used for Doppler index calculations using in vivo and string phantom acquisitions. In vivo results demonstrated that the Capon estimator can provide spectral estimates with sufficient quality for quantitative analysis using packet-based CFI acquisitions. The calculated Doppler indices were similar to the values calculated using spectrograms estimated on a commercial ultrasound scanner.

Accounting for Limited Detection Efficiency and Localization Precision in Cluster Analysis in Single Molecule Localization Microscopy

PubMed Central

Shivanandan, Arun; Unnikrishnan, Jayakrishnan; Radenovic, Aleksandra

2015-01-01

Single Molecule Localization Microscopy techniques like PhotoActivated Localization Microscopy, with their sub-diffraction limit spatial resolution, have been popularly used to characterize the spatial organization of membrane proteins, by means of quantitative cluster analysis. However, such quantitative studies remain challenged by the techniques’ inherent sources of errors such as a limited detection efficiency of less than 60%, due to incomplete photo-conversion, and a limited localization precision in the range of 10 – 30nm, varying across the detected molecules, mainly depending on the number of photons collected from each. We provide analytical methods to estimate the effect of these errors in cluster analysis and to correct for them. These methods, based on the Ripley’s L(r) – r or Pair Correlation Function popularly used by the community, can facilitate potentially breakthrough results in quantitative biology by providing a more accurate and precise quantification of protein spatial organization. PMID:25794150

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Quantitative analysis of multi-component gas mixture based on AOTF-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Huimin; Zhang, Yong; Liu, Junhua

2007-12-01

Near Infrared (NIR) spectroscopy analysis technology has attracted many eyes and has wide application in many domains in recent years because of its remarkable advantages. But the NIR spectrometer can only be used for liquid and solid analysis by now. In this paper, a new quantitative analysis method of gas mixture by using new generation NIR spectrometer is explored. To collect the NIR spectra of gas mixtures, a vacuumable gas cell was designed and assembled to Luminar 5030-731 Acousto-Optic Tunable Filter (AOTF)-NIR spectrometer. Standard gas samples of methane (CH 4), ethane (C IIH 6) and propane (C 3H 8) are diluted with super pure nitrogen via precision volumetric gas flow controllers to obtain gas mixture samples of different concentrations dynamically. The gas mixtures were injected into the gas cell and the spectra of wavelength between 1100nm-2300nm were collected. The feature components extracted from gas mixture spectra by using Partial Least Squares (PLS) were used as the inputs of the Support Vector Regress Machine (SVR) to establish the quantitative analysis model. The effectiveness of the model is tested by the samples of predicting set. The prediction Root Mean Square Error (RMSE) of CH 4, C IIH 6 and C 3H 8 is respectively 1.27%, 0.89%, and 1.20% when the concentrations of component gas are over 0.5%. It shows that the AOTF-NIR spectrometer with gas cell can be used for gas mixture analysis. PLS combining with SVR has a good performance in NIR spectroscopy analysis. This paper provides the bases for extending the application of NIR spectroscopy analysis to gas detection.

Multivariate analysis, mass balance techniques, and statistical tests as tools in igneous petrology: application to the Sierra de las Cruces volcanic range (Mexican Volcanic Belt).

PubMed

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures).

Problem-based learning on quantitative analytical chemistry course

NASA Astrophysics Data System (ADS)

Fitri, Noor

2017-12-01

This research applies problem-based learning method on chemical quantitative analytical chemistry, so called as "Analytical Chemistry II" course, especially related to essential oil analysis. The learning outcomes of this course include aspects of understanding of lectures, the skills of applying course materials, and the ability to identify, formulate and solve chemical analysis problems. The role of study groups is quite important in improving students' learning ability and in completing independent tasks and group tasks. Thus, students are not only aware of the basic concepts of Analytical Chemistry II, but also able to understand and apply analytical concepts that have been studied to solve given analytical chemistry problems, and have the attitude and ability to work together to solve the problems. Based on the learning outcome, it can be concluded that the problem-based learning method in Analytical Chemistry II course has been proven to improve students' knowledge, skill, ability and attitude. Students are not only skilled at solving problems in analytical chemistry especially in essential oil analysis in accordance with local genius of Chemistry Department, Universitas Islam Indonesia, but also have skilled work with computer program and able to understand material and problem in English.

Multi-wavelength spectrophotometric determination of acidity constant of some newly synthesized Schiff bases and their QSPR study

NASA Astrophysics Data System (ADS)

Hemmateenejad, Bahram; Emami, Leila; Sharghi, Hashem

2010-01-01

The acidity constants of some newly synthesized Schiff base derivatives were determined by hard-model based multivariate data analysis of the spectrophotometric data in the course of pH-metric titration in 50% (v/v) methanol-water binary solvent. The employed data analysis method was also able to extract the pure spectra and pH-dependent concentration profiles of the acid-base species. The molecules that possess different substituents (both electron donating and withdrawing) on the ortho-, meta- and para-positions of one of the phenyl ring showed variable acidity constants ranging from 8.77 to 11.07 whereas the parent molecule had an acidity constant of 10.25. To investigate the quantitative effects of changing of substitution pattern on the acidity constant, a quantitative structure-property relation analysis was conducted using substituent constants and molecular descriptor. Some models with high statistical quality (measured by cross-validation Q2) were obtained. It was found that the acidity constant of the studied molecules in the methanol-water mixed solvent not only is affected by electronic features of the solutes but also by the lipophilic interaction between methanol part of solvent and the deprotonated solutes.

Quantitative Infrared Spectroscopy in Challenging Environments: Applications to Passive Remote Sensing and Process Monitoring

DTIC Science & Technology

2012-12-01

IR remote sensing o ers a measurement method to detect gaseous species in the outdoor environment. Two major obstacles limit the application of this... method in quantitative analysis : (1) the e ect of both temperature and concentration on the measured spectral intensities and (2) the di culty and...crucial. In this research, particle swarm optimization, a population- based optimization method was applied. Digital ltering and wavelet processing methods

Semi-quantitative methods yield greater inter- and intraobserver agreement than subjective methods for interpreting 99m technetium-hydroxymethylene-diphosphonate uptake in equine thoracic processi spinosi.

PubMed

van Zadelhoff, Claudia; Ehrle, Anna; Merle, Roswitha; Jahn, Werner; Lischer, Christoph

2018-05-09

Scintigraphy is a standard diagnostic method for evaluating horses with back pain due to suspected thoracic processus spinosus pathology. Lesion detection is based on subjective or semi-quantitative assessments of increased uptake. This retrospective, analytical study is aimed to compare semi-quantitative and subjective methods in the evaluation of scintigraphic images of the processi spinosi in the equine thoracic spine. Scintigraphic images of 20 Warmblood horses, presented for assessment of orthopedic conditions between 2014 and 2016, were included in the study. Randomized, blinded image evaluation was performed by 11 veterinarians using subjective and semi-quantitative methods. Subjective grading was performed for the analysis of red-green-blue and grayscale scintigraphic images, which were presented in full-size or as masked images. For the semi-quantitative assessment, observers placed regions of interest over each processus spinosus. The uptake ratio of each processus spinosus in comparison to a reference region of interest was determined. Subsequently, a modified semi-quantitative calculation was developed whereby only the highest counts-per-pixel for a specified number of pixels was processed. Inter- and intraobserver agreement was calculated using intraclass correlation coefficients. Inter- and intraobserver intraclass correlation coefficients were 41.65% and 71.39%, respectively, for the subjective image assessment. Additionally, a correlation between intraobserver agreement, experience, and grayscale images was identified. The inter- and intraobserver agreement was significantly increased when using semi-quantitative analysis (97.35% and 98.36%, respectively) or the modified semi-quantitative calculation (98.61% and 98.82%, respectively). The proposed modified semi-quantitative technique showed a higher inter- and intraobserver agreement when compared to other methods, which makes it a useful tool for the analysis of scintigraphic images. The association of the findings from this study with clinical and radiological examinations requires further investigation. © 2018 American College of Veterinary Radiology.

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

PubMed

Larue, Ruben T H M; Defraene, Gilles; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-02-01

Quantitative analysis of tumour characteristics based on medical imaging is an emerging field of research. In recent years, quantitative imaging features derived from CT, positron emission tomography and MR scans were shown to be of added value in the prediction of outcome parameters in oncology, in what is called the radiomics field. However, results might be difficult to compare owing to a lack of standardized methodologies to conduct quantitative image analyses. In this review, we aim to present an overview of the current challenges, technical routines and protocols that are involved in quantitative imaging studies. The first issue that should be overcome is the dependency of several features on the scan acquisition and image reconstruction parameters. Adopting consistent methods in the subsequent target segmentation step is evenly crucial. To further establish robust quantitative image analyses, standardization or at least calibration of imaging features based on different feature extraction settings is required, especially for texture- and filter-based features. Several open-source and commercial software packages to perform feature extraction are currently available, all with slightly different functionalities, which makes benchmarking quite challenging. The number of imaging features calculated is typically larger than the number of patients studied, which emphasizes the importance of proper feature selection and prediction model-building routines to prevent overfitting. Even though many of these challenges still need to be addressed before quantitative imaging can be brought into daily clinical practice, radiomics is expected to be a critical component for the integration of image-derived information to personalize treatment in the future.

Quantitative transmission Raman spectroscopy of pharmaceutical tablets and capsules.

PubMed

Johansson, Jonas; Sparén, Anders; Svensson, Olof; Folestad, Staffan; Claybourn, Mike

2007-11-01

Quantitative analysis of pharmaceutical formulations using the new approach of transmission Raman spectroscopy has been investigated. For comparison, measurements were also made in conventional backscatter mode. The experimental setup consisted of a Raman probe-based spectrometer with 785 nm excitation for measurements in backscatter mode. In transmission mode the same system was used to detect the Raman scattered light, while an external diode laser of the same type was used as excitation source. Quantitative partial least squares models were developed for both measurement modes. The results for tablets show that the prediction error for an independent test set was lower for the transmission measurements with a relative root mean square error of about 2.2% as compared with 2.9% for the backscatter mode. Furthermore, the models were simpler in the transmission case, for which only a single partial least squares (PLS) component was required to explain the variation. The main reason for the improvement using the transmission mode is a more representative sampling of the tablets compared with the backscatter mode. Capsules containing mixtures of pharmaceutical powders were also assessed by transmission only. The quantitative results for the capsules' contents were good, with a prediction error of 3.6% w/w for an independent test set. The advantage of transmission Raman over backscatter Raman spectroscopy has been demonstrated for quantitative analysis of pharmaceutical formulations, and the prospects for reliable, lean calibrations for pharmaceutical analysis is discussed.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

PubMed Central

Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

Diagnostic accuracy of semi-automatic quantitative metrics as an alternative to expert reading of CT myocardial perfusion in the CORE320 study.

PubMed

Ostovaneh, Mohammad R; Vavere, Andrea L; Mehra, Vishal C; Kofoed, Klaus F; Matheson, Matthew B; Arbab-Zadeh, Armin; Fujisawa, Yasuko; Schuijf, Joanne D; Rochitte, Carlos E; Scholte, Arthur J; Kitagawa, Kakuya; Dewey, Marc; Cox, Christopher; DiCarli, Marcelo F; George, Richard T; Lima, Joao A C

To determine the diagnostic accuracy of semi-automatic quantitative metrics compared to expert reading for interpretation of computed tomography perfusion (CTP) imaging. The CORE320 multicenter diagnostic accuracy clinical study enrolled patients between 45 and 85 years of age who were clinically referred for invasive coronary angiography (ICA). Computed tomography angiography (CTA), CTP, single photon emission computed tomography (SPECT), and ICA images were interpreted manually in blinded core laboratories by two experienced readers. Additionally, eight quantitative CTP metrics as continuous values were computed semi-automatically from myocardial and blood attenuation and were combined using logistic regression to derive a final quantitative CTP metric score. For the reference standard, hemodynamically significant coronary artery disease (CAD) was defined as a quantitative ICA stenosis of 50% or greater and a corresponding perfusion defect by SPECT. Diagnostic accuracy was determined by area under the receiver operating characteristic curve (AUC). Of the total 377 included patients, 66% were male, median age was 62 (IQR: 56, 68) years, and 27% had prior myocardial infarction. In patient based analysis, the AUC (95% CI) for combined CTA-CTP expert reading and combined CTA-CTP semi-automatic quantitative metrics was 0.87(0.84-0.91) and 0.86 (0.83-0.9), respectively. In vessel based analyses the AUC's were 0.85 (0.82-0.88) and 0.84 (0.81-0.87), respectively. No significant difference in AUC was found between combined CTA-CTP expert reading and CTA-CTP semi-automatic quantitative metrics in patient based or vessel based analyses(p > 0.05 for all). Combined CTA-CTP semi-automatic quantitative metrics is as accurate as CTA-CTP expert reading to detect hemodynamically significant CAD. Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Pedagogical Beliefs in Work-Based Learning: An Analysis and Implications of Teachers' Belief Orientations

ERIC Educational Resources Information Center

Abukari, Abdulai

2014-01-01

This paper presents findings of a research project that aimed to critically examine the pedagogical beliefs of work-based learning teachers, and their potential implication on practice and expectations of learners and employers. Based on an online tool, qualitative and quantitative (descriptive) data were generated from a purposive sample of some…

Development and Evaluation of a Multimedia e-Learning Resource for Electrolyte and Acid-Base Disorders

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Chikte, Usuf M. E.; Halperin, Mitchell L.

2011-01-01

This article reports on the development and evaluation of a Web-based application that provides instruction and hands-on practice in managing electrolyte and acid-base disorders. Our teaching approach, which focuses on concepts rather than details, encourages quantitative analysis and a logical problem-solving approach. Identifying any dangers to…

Gender-Based Barriers Experienced by Male Students in an Online RN-to-BSN Nursing Program

ERIC Educational Resources Information Center

Kirk, John R.

2012-01-01

This quantitative survey-based research study examined the experiences of 49 men through a comparative analysis of their traditional classroom-based Diploma or Associate Degree in Nursing program and their subsequent experiences in the University of Phoenix online Registered Nurse to Bachelor of Science in Nursing (RN-to-BSN) degree completion…

[Reliability theory based on quality risk network analysis for Chinese medicine injection].

PubMed

Li, Zheng; Kang, Li-Yuan; Fan, Xiao-Hui

2014-08-01

A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.

Measurement Models for Reasoned Action Theory

PubMed Central

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin

2012-01-01

Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach. PMID:23243315

The application of high-speed cinematography for the quantitative analysis of equine locomotion.

PubMed

Fredricson, I; Drevemo, S; Dalin, G; Hjertën, G; Björne, K

1980-04-01

Locomotive disorders constitute a serious problem in horse racing which will only be rectified by a better understanding of the causative factors associated with disturbances of gait. This study describes a system for the quantitative analysis of the locomotion of horses at speed. The method is based on high-speed cinematography with a semi-automatic system of analysis of the films. The recordings are made with a 16 mm high-speed camera run at 500 frames per second (fps) and the films are analysed by special film-reading equipment and a mini-computer. The time and linear gait variables are presented in tabular form and the angles and trajectories of the joints and body segments are presented graphically.

Safe Passage Data Analysis: Interim Report

DOT National Transportation Integrated Search

1993-04-01

The purpose of this report is to describe quantitatively the costs and benefits of screener : proficiency evaluation and reporting systems (SPEARS) equipment, particularly computer-based : instruction (CBI) systems, compared to current methods of tra...

Professional Learning: A Fuzzy Logic-Based Modelling Approach

ERIC Educational Resources Information Center

Gravani, M. N.; Hadjileontiadou, S. J.; Nikolaidou, G. N.; Hadjileontiadis, L. J.

2007-01-01

Studies have suggested that professional learning is influenced by two key parameters, i.e., climate and planning, and their associated variables (mutual respect, collaboration, mutual trust, supportiveness, openness). In this paper, we applied analysis of the relationships between the proposed quantitative, fuzzy logic-based model and a series of…

Developing and Assessing E-Learning Techniques for Teaching Forecasting

ERIC Educational Resources Information Center

Gel, Yulia R.; O'Hara Hines, R. Jeanette; Chen, He; Noguchi, Kimihiro; Schoner, Vivian

2014-01-01

In the modern business environment, managers are increasingly required to perform decision making and evaluate related risks based on quantitative information in the face of uncertainty, which in turn increases demand for business professionals with sound skills and hands-on experience with statistical data analysis. Computer-based training…

Do Functional Behavioral Assessments Improve Intervention Effectiveness for Students with ADHD? A Single-Subject Meta-Analysis

ERIC Educational Resources Information Center

Miller, Faith G.

2011-01-01

The primary purpose of this quantitative synthesis of single-subject research was to investigate the relative effectiveness of function-based and non-function-based behavioral interventions for students diagnosed with attention-deficit/hyperactivity disorder. In addition, associations between various participant, assessment, and intervention…

Automated quantitative cytological analysis using portable microfluidic microscopy.

PubMed

Jagannadh, Veerendra Kalyan; Murthy, Rashmi Sreeramachandra; Srinivasan, Rajesh; Gorthi, Sai Siva

2016-06-01

In this article, a portable microfluidic microscopy based approach for automated cytological investigations is presented. Inexpensive optical and electronic components have been used to construct a simple microfluidic microscopy system. In contrast to the conventional slide-based methods, the presented method employs microfluidics to enable automated sample handling and image acquisition. The approach involves the use of simple in-suspension staining and automated image acquisition to enable quantitative cytological analysis of samples. The applicability of the presented approach to research in cellular biology is shown by performing an automated cell viability assessment on a given population of yeast cells. Further, the relevance of the presented approach to clinical diagnosis and prognosis has been demonstrated by performing detection and differential assessment of malaria infection in a given sample. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of DNA interactions using single-molecule force spectroscopy.

PubMed

Ritzefeld, Markus; Walhorn, Volker; Anselmetti, Dario; Sewald, Norbert

2013-06-01

Protein-DNA interactions are involved in many biochemical pathways and determine the fate of the corresponding cell. Qualitative and quantitative investigations on these recognition and binding processes are of key importance for an improved understanding of biochemical processes and also for systems biology. This review article focusses on atomic force microscopy (AFM)-based single-molecule force spectroscopy and its application to the quantification of forces and binding mechanisms that lead to the formation of protein-DNA complexes. AFM and dynamic force spectroscopy are exciting tools that allow for quantitative analysis of biomolecular interactions. Besides an overview on the method and the most important immobilization approaches, the physical basics of the data evaluation is described. Recent applications of AFM-based force spectroscopy to investigate DNA intercalation, complexes involving DNA aptamers and peptide- and protein-DNA interactions are given.

Comparing quantitative analysis on revealed comparative advantages of aquatic products trade of china and ASEAN based on 21st century maritime silk road

NASA Astrophysics Data System (ADS)

Luo, X. F.; Han, Y. H.; Li, Z. W.

2017-11-01

As the world’s leading aquaculture, aquatic production and trading country, China’s development of aquatic products trade with ASEAN is facing a historic opportunity in the favourable circumstances of construction of the 21st century Maritime Silk Road. In order to make guidance of the product selection and transformation for corresponding export enterprises, this article makes a quantitative analysis the Revealed Comparative Advantage of aquatic products trade from China and ASEAN respectively based on the HS classification and thoroughly compares the RCA indices. The comparison results show that the international competitiveness of aquatic products structures of China and ASEAN are quite different with few overlaps of strong competitive products, and there is a great gap between the two areas in many kinds of products.

In situ flash x-ray high-speed computed tomography for the quantitative analysis of highly dynamic processes

NASA Astrophysics Data System (ADS)

Moser, Stefan; Nau, Siegfried; Salk, Manfred; Thoma, Klaus

2014-02-01

The in situ investigation of dynamic events, ranging from car crash to ballistics, often is key to the understanding of dynamic material behavior. In many cases the important processes and interactions happen on the scale of milli- to microseconds at speeds of 1000 m s-1 or more. Often, 3D information is necessary to fully capture and analyze all relevant effects. High-speed 3D-visualization techniques are thus required for the in situ analysis. 3D-capable optical high-speed methods often are impaired by luminous effects and dust, while flash x-ray based methods usually deliver only 2D data. In this paper, a novel 3D-capable flash x-ray based method, in situ flash x-ray high-speed computed tomography is presented. The method is capable of producing 3D reconstructions of high-speed processes based on an undersampled dataset consisting of only a few (typically 3 to 6) x-ray projections. The major challenges are identified, discussed and the chosen solution outlined. The application is illustrated with an exemplary application of a 1000 m s-1 high-speed impact event on the scale of microseconds. A quantitative analysis of the in situ measurement of the material fragments with a 3D reconstruction with 1 mm voxel size is presented and the results are discussed. The results show that the HSCT method allows gaining valuable visual and quantitative mechanical information for the understanding and interpretation of high-speed events.

In-depth Qualitative and Quantitative Profiling of Tyrosine Phosphorylation Using a Combination of Phosphopeptide Immunoaffinity Purification and Stable Isotope Dimethyl Labeling*

PubMed Central

Boersema, Paul J.; Foong, Leong Yan; Ding, Vanessa M. Y.; Lemeer, Simone; van Breukelen, Bas; Philp, Robin; Boekhorst, Jos; Snel, Berend; den Hertog, Jeroen; Choo, Andre B. H.; Heck, Albert J. R.

2010-01-01

Several mass spectrometry-based assays have emerged for the quantitative profiling of cellular tyrosine phosphorylation. Ideally, these methods should reveal the exact sites of tyrosine phosphorylation, be quantitative, and not be cost-prohibitive. The latter is often an issue as typically several milligrams of (stable isotope-labeled) starting protein material are required to enable the detection of low abundance phosphotyrosine peptides. Here, we adopted and refined a peptidecentric immunoaffinity purification approach for the quantitative analysis of tyrosine phosphorylation by combining it with a cost-effective stable isotope dimethyl labeling method. We were able to identify by mass spectrometry, using just two LC-MS/MS runs, more than 1100 unique non-redundant phosphopeptides in HeLa cells from about 4 mg of starting material without requiring any further affinity enrichment as close to 80% of the identified peptides were tyrosine phosphorylated peptides. Stable isotope dimethyl labeling could be incorporated prior to the immunoaffinity purification, even for the large quantities (mg) of peptide material used, enabling the quantification of differences in tyrosine phosphorylation upon pervanadate treatment or epidermal growth factor stimulation. Analysis of the epidermal growth factor-stimulated HeLa cells, a frequently used model system for tyrosine phosphorylation, resulted in the quantification of 73 regulated unique phosphotyrosine peptides. The quantitative data were found to be exceptionally consistent with the literature, evidencing that such a targeted quantitative phosphoproteomics approach can provide reproducible results. In general, the combination of immunoaffinity purification of tyrosine phosphorylated peptides with large scale stable isotope dimethyl labeling provides a cost-effective approach that can alleviate variation in sample preparation and analysis as samples can be combined early on. Using this approach, a rather complete qualitative and quantitative picture of tyrosine phosphorylation signaling events can be generated. PMID:19770167

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

PubMed

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

Swelling-induced optical anisotropy of thermoresponsive hydrogels based on poly(2-(2-methoxyethoxy)ethyl methacrylate): deswelling kinetics probed by quantitative Mueller matrix polarimetry.

PubMed

Patil, Nagaraj; Soni, Jalpa; Ghosh, Nirmalya; De, Priyadarsi

2012-11-29

Thermodynamically favored polymer-water interactions below the lower critical solution temperature (LCST) caused swelling-induced optical anisotropy (linear retardance) of thermoresponsive hydrogels based on poly(2-(2-methoxyethoxy)ethyl methacrylate). This was exploited to study the macroscopic deswelling kinetics quantitatively by a generalized polarimetry analysis method, based on measurement of the Mueller matrix and its subsequent inverse analysis via the polar decomposition approach. The derived medium polarization parameters, namely, linear retardance (δ), diattenuation (d), and depolarization coefficient (Δ), of the hydrogels showed interesting differences between the gels prepared by conventional free radical polymerization (FRP) and reversible addition-fragmentation chain transfer polymerization (RAFT) and also between dry and swollen state. The effect of temperature, cross-linking density, and polymerization technique employed to synthesize hydrogel on deswelling kinetics was systematically studied via conventional gravimetry and corroborated further with the corresponding Mueller matrix derived quantitative polarimetry characteristics (δ, d, and Δ). The RAFT gels exhibited higher swelling ratio and swelling-induced optical anisotropy compared to FRP gels and also deswelled faster at 30 °C. On the contrary, at 45 °C, deswelling was significantly retarded for the RAFT gels due to formation of a skin layer, which was confirmed and quantified via the enhanced diattenuation and depolarization parameters.

Smartphone based visual and quantitative assays on upconversional paper sensor.

PubMed

Mei, Qingsong; Jing, Huarong; Li, You; Yisibashaer, Wuerzha; Chen, Jian; Nan Li, Bing; Zhang, Yong

2016-01-15

The integration of smartphone with paper sensors recently has been gain increasing attentions because of the achievement of quantitative and rapid analysis. However, smartphone based upconversional paper sensors have been restricted by the lack of effective methods to acquire luminescence signals on test paper. Herein, by the virtue of 3D printing technology, we exploited an auxiliary reusable device, which orderly assembled a 980nm mini-laser, optical filter and mini-cavity together, for digitally imaging the luminescence variations on test paper and quantitative analyzing pesticide thiram by smartphone. In detail, copper ions decorated NaYF4:Yb/Tm upconversion nanoparticles were fixed onto filter paper to form test paper, and the blue luminescence on it would be quenched after additions of thiram through luminescence resonance energy transfer mechanism. These variations could be monitored by the smartphone camera, and then the blue channel intensities of obtained colored images were calculated to quantify amounts of thiram through a self-written Android program installed on the smartphone, offering a reliable and accurate detection limit of 0.1μM for the system. This work provides an initial demonstration of integrating upconversion nanosensors with smartphone digital imaging for point-of-care analysis on a paper-based platform. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative Protein Topography Analysis and High-Resolution Structure Prediction Using Hydroxyl Radical Labeling and Tandem-Ion Mass Spectrometry (MS)*

PubMed Central

Kaur, Parminder; Kiselar, Janna; Yang, Sichun; Chance, Mark R.

2015-01-01

Hydroxyl radical footprinting based MS for protein structure assessment has the goal of understanding ligand induced conformational changes and macromolecular interactions, for example, protein tertiary and quaternary structure, but the structural resolution provided by typical peptide-level quantification is limiting. In this work, we present experimental strategies using tandem-MS fragmentation to increase the spatial resolution of the technique to the single residue level to provide a high precision tool for molecular biophysics research. Overall, in this study we demonstrated an eightfold increase in structural resolution compared with peptide level assessments. In addition, to provide a quantitative analysis of residue based solvent accessibility and protein topography as a basis for high-resolution structure prediction; we illustrate strategies of data transformation using the relative reactivity of side chains as a normalization strategy and predict side-chain surface area from the footprinting data. We tested the methods by examination of Ca+2-calmodulin showing highly significant correlations between surface area and side-chain contact predictions for individual side chains and the crystal structure. Tandem ion based hydroxyl radical footprinting-MS provides quantitative high-resolution protein topology information in solution that can fill existing gaps in structure determination for large proteins and macromolecular complexes. PMID:25687570

Nanoparticle surface characterization and clustering through concentration-dependent surface adsorption modeling.

PubMed

Chen, Ran; Zhang, Yuntao; Sahneh, Faryad Darabi; Scoglio, Caterina M; Wohlleben, Wendel; Haase, Andrea; Monteiro-Riviere, Nancy A; Riviere, Jim E

2014-09-23

Quantitative characterization of nanoparticle interactions with their surrounding environment is vital for safe nanotechnological development and standardization. A recent quantitative measure, the biological surface adsorption index (BSAI), has demonstrated promising applications in nanomaterial surface characterization and biological/environmental prediction. This paper further advances the approach beyond the application of five descriptors in the original BSAI to address the concentration dependence of the descriptors, enabling better prediction of the adsorption profile and more accurate categorization of nanomaterials based on their surface properties. Statistical analysis on the obtained adsorption data was performed based on three different models: the original BSAI, a concentration-dependent polynomial model, and an infinite dilution model. These advancements in BSAI modeling showed a promising development in the application of quantitative predictive modeling in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

Ranking Quantitative Resistance to Septoria tritici Blotch in Elite Wheat Cultivars Using Automated Image Analysis.

PubMed

Karisto, Petteri; Hund, Andreas; Yu, Kang; Anderegg, Jonas; Walter, Achim; Mascher, Fabio; McDonald, Bruce A; Mikaberidze, Alexey

2018-05-01

Quantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis of 21,420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

Hydrophobic ionic liquids for quantitative bacterial cell lysis with subsequent DNA quantification.

PubMed

Fuchs-Telka, Sabine; Fister, Susanne; Mester, Patrick-Julian; Wagner, Martin; Rossmanith, Peter

2017-02-01

DNA is one of the most frequently analyzed molecules in the life sciences. In this article we describe a simple and fast protocol for quantitative DNA isolation from bacteria based on hydrophobic ionic liquid supported cell lysis at elevated temperatures (120-150 °C) for subsequent PCR-based analysis. From a set of five hydrophobic ionic liquids, 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide was identified as the most suitable for quantitative cell lysis and DNA extraction because of limited quantitative PCR inhibition by the aqueous eluate as well as no detectable DNA uptake. The newly developed method was able to efficiently lyse Gram-negative bacterial cells, whereas Gram-positive cells were protected by their thick cell wall. The performance of the final protocol resulted in quantitative DNA extraction efficiencies for Gram-negative bacteria similar to those obtained with a commercial kit, whereas the number of handling steps, and especially the time required, was dramatically reduced. Graphical Abstract After careful evaluation of five hydrophobic ionic liquids, 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([BMPyr + ][Ntf 2 - ]) was identified as the most suitable ionic liquid for quantitative cell lysis and DNA extraction. When used for Gram-negative bacteria, the protocol presented is simple and very fast and achieves DNA extraction efficiencies similar to those obtained with a commercial kit. ddH 2 O double-distilled water, qPCR quantitative PCR.

Quantitative analysis of 18F-NaF dynamic PET/CT cannot differentiate malignant from benign lesions in multiple myeloma

PubMed Central

Sachpekidis, Christos; Hillengass, Jens; Goldschmidt, Hartmut; Anwar, Hoda; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-01-01

A renewed interest has been recently developed for the highly sensitive bone-seeking radiopharmaceutical 18F-NaF. Aim of the present study is to evaluate the potential utility of quantitative analysis of 18F-NaF dynamic PET/CT data in differentiating malignant from benign degenerative lesions in multiple myeloma (MM). 80 MM patients underwent whole-body PET/CT and dynamic PET/CT scanning of the pelvis with 18F-NaF. PET/CT data evaluation was based on visual (qualitative) assessment, semi-quantitative (SUV) calculations, and absolute quantitative estimations after application of a 2-tissue compartment model and a non-compartmental approach leading to the extraction of fractal dimension (FD). In total 263 MM lesions were demonstrated on 18F-NaF PET/CT. Semi-quantitative and quantitative evaluations were performed for 25 MM lesions as well as for 25 benign, degenerative and traumatic lesions. Mean SUVaverage for MM lesions was 11.9 and mean SUVmax was 23.2. Respectively, SUVaverage and SUVmax for degenerative lesions were 13.5 and 20.2. Kinetic analysis of 18F-NaF revealed the following mean values for MM lesions: K1 = 0.248 (1/min), k3 = 0.359 (1/min), influx (Ki) = 0.107 (1/min), FD = 1.382, while the respective values for degenerative lesions were: K1 = 0.169 (1/min), k3 = 0.422 (1/min), influx (Ki) = 0.095 (1/min), FD = 1. 411. No statistically significant differences between MM and benign degenerative disease regarding SUVaverage, SUVmax, K1, k3 and influx (Ki) were demonstrated. FD was significantly higher in degenerative than in malignant lesions. The present findings show that quantitative analysis of 18F-NaF PET data cannot differentiate malignant from benign degenerative lesions in MM patients, supporting previously published results, which reflect the limited role of 18F-NaF PET/CT in the diagnostic workup of MM. PMID:28913153

Navigational Traffic Conflict Technique: A Proactive Approach to Quantitative Measurement of Collision Risks in Port Waters

NASA Astrophysics Data System (ADS)

Debnath, Ashim Kumar; Chin, Hoong Chor

Navigational safety analysis relying on collision statistics is often hampered because of the low number of observations. A promising alternative approach that overcomes this problem is proposed in this paper. By analyzing critical vessel interactions this approach proactively measures collision risk in port waters. The proposed method is illustrated for quantitative measurement of collision risks in Singapore port fairways, and validated by examining correlations between the measured risks with those perceived by pilots. This method is an ethically appealing alternative to the collision-based analysis for fast, reliable and effective safety assessment, thus possessing great potential for managing collision risks in port waters.

The life sciences mass spectrometry research unit.

PubMed

Hopfgartner, Gérard; Varesio, Emmanuel

2012-01-01

The Life Sciences Mass Spectrometry (LSMS) research unit focuses on the development of novel analytical workflows based on innovative mass spectrometric and software tools for the analysis of low molecular weight compounds, peptides and proteins in complex biological matrices. The present article summarizes some of the recent work of the unit: i) the application of matrix-assisted laser desorption/ionization (MALDI) for mass spectrometry imaging (MSI) of drug of abuse in hair, ii) the use of high resolution mass spectrometry for simultaneous qualitative/quantitative analysis in drug metabolism and metabolomics, and iii) the absolute quantitation of proteins by mass spectrometry using the selected reaction monitoring mode.

Growth and maturity: A quantitative systematic review and network analysis in anthropometric history.

PubMed

Galofré-Vilà, Gregori

2018-02-01

This paper reviews the current wealth of anthropometric history since the early efforts of Robert Fogel in the 1970s. The survey is based on a quantitative systematic review of the literature and counts a total of 447 peer-reviewed articles being published in the main leading journals in economic history, economics and biology. Data are analysed using network analysis by journal and author and the main contributions of anthropometric history are highlighted, pointing to future areas of inquiry. The contributions of books and book chapters are also quantified and analysed. Copyright © 2017 Elsevier B.V. All rights reserved.

Highly sensitive transient absorption imaging of graphene and graphene oxide in living cells and circulating blood

PubMed Central

Li, Junjie; Zhang, Weixia; Chung, Ting-Fung; Slipchenko, Mikhail N.; Chen, Yong P.; Cheng, Ji-Xin; Yang, Chen

2015-01-01

We report a transient absorption (TA) imaging method for fast visualization and quantitative layer analysis of graphene and GO. Forward and backward imaging of graphene on various substrates under ambient condition was imaged with a speed of 2 μs per pixel. The TA intensity linearly increased with the layer number of graphene. Real-time TA imaging of GO in vitro with capability of quantitative analysis of intracellular concentration and ex vivo in circulating blood were demonstrated. These results suggest that TA microscopy is a valid tool for the study of graphene based materials. PMID:26202216

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

[Medical habilitation in German-speaking countries : Quantitative assessment of content and elaboration of habilitation guidelines].

PubMed

Weineck, S B; Koelblinger, D; Kiesslich, T

2015-04-01

Habilitation defines the qualification to conduct self-contained university teaching and is the key for access to a professorship at German, Austrian and Swiss universities. Despite all changes implemented in the European higher education systems during the Bologna process, it is the highest qualification level issued through the process of an university examination and remains the core concept of scientific careers in these countries. In the field of medicine, this applies not only to scientific staff at the universities but also to those medical doctors aiming at a clinical career track. To provide a quantitative analysis of the scientific, didactic, and procedural criteria for medical habilitation in German-speaking countries. Based on the guidelines of all 43 medical academic institutions, the criteria which candidates are required to fulfil prior to habilitation as well as formal requirements related to the habilitation procedure itself have been acquired and quantitatively analyzed. Having evaluated all habilitation guidelines by means of 87 items, the quantitative analysis revealed significant differences in terms of number, kind and scale of criteria stated therein. Most habilitation guidelines scarcely define the capabilities applicants have to prove: concerning the scientific qualifications on types of publications for instance, no item was mentioned in more than half of all habilitation guidelines. Based on this data analysis, the authors discuss the related literature and describe five main distinguishing areas of habilitation guidelines in terms of the set of the formal and procedural framework as well as the prequalification and postqualification criteria imposed on habilitation candidates. There are therefore substantial differences in the organization of the habilitation for medicine.

The Use of Multi-Criteria Evaluation and Network Analysis in the Area Development Planning Process

DTIC Science & Technology

2013-03-01

layouts. The alternative layout scoring process, base in multi-criteria evaluation, returns a quantitative score for each alternative layout and a...The purpose of this research was to develop improvements to the area development planning process. These plans are used to improve operations within...an installation sub-section by altering the physical layout of facilities. One methodology was developed based on apply network analysis concepts to

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

PubMed

Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

Evaluation of electrochemical, UV/VIS and Raman spectroelectrochemical detection of Naratriptan with screen-printed electrodes.

PubMed

Hernández, Carla Navarro; Martín-Yerga, Daniel; González-García, María Begoña; Hernández-Santos, David; Fanjul-Bolado, Pablo

2018-02-01

Naratriptan, active pharmaceutical ingredient with antimigraine activity was electrochemically detected in untreated screen-printed carbon electrodes (SPCEs). Cyclic voltammetry and differential pulse voltammetry were used to carry out quantitative analysis of this molecule (in a Britton-Robinson buffer solution at pH 3.0) through its irreversible oxidation (diffusion controlled) at a potential of +0.75V (vs. Ag pseudoreference electrode). Naratriptan oxidation product is an indole based dimer with a yellowish colour (maximum absorption at 320nm) so UV-VIS spectroelectrochemistry technique was used for the very first time as an in situ characterization and quantification technique for this molecule. A reflection configuration approach allowed its measurement over the untreated carbon based electrode. Finally, time resolved Raman Spectroelectrochemistry is used as a powerful technique to carry out qualitative and quantitative analysis of Naratriptan. Electrochemically treated silver screen-printed electrodes are shown as easy to use and cost-effective SERS substrates for the analysis of Naratriptan. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative analysis of fungicide azoxystrobin in agricultural samples with rapid, simple and reliable monoclonal immunoassay.

PubMed

Watanabe, Eiki; Miyake, Shiro

2013-01-15

This work presents analytical performance of a kit-based direct competitive enzyme-linked immunosorbent assay (dc-ELISA) for azoxystrobin detection in agricultural products. The dc-ELISA was sufficiently sensitive for analysis of residue levels close to the maximum residue limits. The dc-ELISA did not show cross-reactivity to other strobilurin analogues. Absorbance decreased with the increase of methanol concentration in sample solution from 2% to 40%, while the standard curve became most linear when the sample solution contained 10% methanol. Agricultural samples were extracted with methanol, and the extracts were diluted with water to 10% methanol adequate. No significant matrix interference was observed. Satisfying recovery was found for all of spiked samples and the results were well agreed with the analysis with liquid chromatography. These results clearly indicate that the kit-based dc-ELISA is suitable for the rapid, simple, quantitative and reliable determination of the fungicide. Copyright © 2012 Elsevier Ltd. All rights reserved.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

PubMed

Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

2015-01-01

Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.

Linking agent-based models and stochastic models of financial markets

PubMed Central

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

2012-01-01

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

Linking agent-based models and stochastic models of financial markets.

PubMed

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Quantitative estimation of minimum offset for multichannel surface-wave survey with actively exciting source

USGS Publications Warehouse

Xu, Y.; Xia, J.; Miller, R.D.

2006-01-01

Multichannel analysis of surface waves is a developing method widely used in shallow subsurface investigations. The field procedures and related parameters are very important for successful applications. Among these parameters, the source-receiver offset range is seldom discussed in theory and normally determined by empirical or semi-quantitative methods in current practice. This paper discusses the problem from a theoretical perspective. A formula for quantitatively evaluating a layered homogenous elastic model was developed. The analytical results based on simple models and experimental data demonstrate that the formula is correct for surface wave surveys for near-surface applications. ?? 2005 Elsevier B.V. All rights reserved.

Ascertaining Validity in the Abstract Realm of PMESII Simulation Models: An Analysis of the Peace Support Operations Model (PSOM)

DTIC Science & Technology

2009-06-01

simulation is the campaign-level Peace Support Operations Model (PSOM). This thesis provides a quantitative analysis of PSOM. The results are based ...multiple potential outcomes , further development and analysis is required before the model is used for large scale analysis . 15. NUMBER OF PAGES 159...multiple potential outcomes , further development and analysis is required before the model is used for large scale analysis . vi THIS PAGE

Developing Interactional Competence through Video-Based Computer-Mediated Conversations: Beginning Learners of Spanish

ERIC Educational Resources Information Center

Tecedor Cabrero, Marta

2013-01-01

This dissertation examines the discourse produced by beginning learners of Spanish using social media. Specifically, it looks at the use and development of interactional resources during two video-mediated conversations. Through a combination of Conversation Analysis tools and quantitative data analysis, the use of turn-taking strategies, repair…

Protein Analysis Using Real-Time PCR Instrumentation: Incorporation in an Integrated, Inquiry-Based Project

ERIC Educational Resources Information Center

Southard, Jonathan N.

2014-01-01

Instrumentation for real-time PCR is used primarily for amplification and quantitation of nucleic acids. The capability to measure fluorescence while controlling temperature in multiple samples can also be applied to the analysis of proteins. Conformational stability and changes in stability due to ligand binding are easily assessed. Protein…

Two Decades of Literature on Self-Directed Learning: A Content Analysis.

ERIC Educational Resources Information Center

Brockett, Ralph G.; Stockdale, Susan L.; Fogerson, Dewey L.; Cox, Barry F.; Canipe, James B.; Chuprina, Larissa A.; Donaghy, Robert C.; Chadwell, Nancy E.

Using a quantitative content analysis approach, a study examined the literature on self direction, or self-directed learning (SDL), that appeared in 14 mainstream adult education journals between 1980-98. The procedure involved classifying, entering, and tallying information on each article through use of an Internet-based program. Results…

A Re-Examination of the Education Production Function Using Individual Participant Data

ERIC Educational Resources Information Center

Pigott, Therese D.; Williams, Ryan T.; Polanin, Joshua R.

2011-01-01

The focus and purpose of this research is to examine the benefits, limitations, and implications of Individual Participant Data (IPD) meta-analysis in education. Comprehensive research reviews in education have been limited to the use of aggregated data (AD) meta- analysis, techniques based on quantitatively combining information from studies on…

Field and In-Lab Determination of Ca[superscript 2+] in Seawater

ERIC Educational Resources Information Center

Stoodley, Robin; Nun~ez, Jose R. Rodriguez; Bartz, Tessa

2014-01-01

Portions of classic undergraduate quantitative analysis experiments in complexiometric titration and potentiometry are combined with a field-sampling experience to create a two period (2 × 3 h) comparison-based experiment for second-year students. A multifunctional chemical analysis device is used with calcium ion-selective electrode for field…

An emerging strategy for evaluating the grades of Keemun black tea by combinatory liquid chromatography-Orbitrap mass spectrometry-based untargeted metabolomics and inhibition effects on α-glucosidase and α-amylase.

PubMed

Guo, Xuemei; Long, Piaopiao; Meng, Qilu; Ho, Chi-Tang; Zhang, Liang

2018-04-25

Quantitative analysis and untargeted liquid chromatography mass spectrum (LC-MS) based metabolomics of different grades of Keemun black tea (KBT) were conducted. Quantitative analysis did not show tight correlation between tea grades and contents of polyphenols, but untargeted metabolomics analysis revealed that high-grades KBT were distinguished from the low-grades. S-plot and Variable Importance (VIP) analysis gave 28 marker compounds responsible for the discrimination of different grades of KBT. The inhibitory effects of KBT on α-amylase and α-glucosidase were positively correlated to tea grades, and the correlation coefficient between each marker compound and inhibitory rate were calculated. Thirteen compounds were positively related to the anti-glycemic activity, and theasinensin A, afzelechin gallate and kaempferol-glucoside were confirmed as grade-related bioactive marker compounds by chemical and bioassay in effective fractions. This study suggested that combinatory metabolomics and bioactivities assay provided a new strategy for the classification of tea grades. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Quantitative and Qualitative Differences in Morphological Traits Revealed between Diploid Fragaria Species

PubMed Central

SARGENT, DANIEL J.; GEIBEL, M.; HAWKINS, J. A.; WILKINSON, M. J.; BATTEY, N. H.; SIMPSON, D. W.

2004-01-01

• Background and Aims The aims of this investigation were to highlight the qualitative and quantitative diversity apparent between nine diploid Fragaria species and produce interspecific populations segregating for a large number of morphological characters suitable for quantitative trait loci analysis. • Methods A qualitative comparison of eight described diploid Fragaria species was performed and measurements were taken of 23 morphological traits from 19 accessions including eight described species and one previously undescribed species. A principal components analysis was performed on 14 mathematically unrelated traits from these accessions, which partitioned the species accessions into distinct morphological groups. Interspecific crosses were performed with accessions of species that displayed significant quantitative divergence and, from these, populations that should segregate for a range of quantitative traits were raised. • Key Results Significant differences between species were observed for all 23 morphological traits quantified and three distinct groups of species accessions were observed after the principal components analysis. Interspecific crosses were performed between these groups, and F2 and backcross populations were raised that should segregate for a range of morphological characters. In addition, the study highlighted a number of distinctive morphological characters in many of the species studied. • Conclusions Diploid Fragaria species are morphologically diverse, yet remain highly interfertile, making the group an ideal model for the study of the genetic basis of phenotypic differences between species through map-based investigation using quantitative trait loci. The segregating interspecific populations raised will be ideal for such investigations and could also provide insights into the nature and extent of genome evolution within this group. PMID:15469944

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Practical considerations of image analysis and quantification of signal transduction IHC staining.

PubMed

Grunkin, Michael; Raundahl, Jakob; Foged, Niels T

2011-01-01

The dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations. However, immunohistochemistry is a multistep procedure including a lot of technical pitfalls leading to intra- and interlaboratory variability of its outcome. The resulting variations in staining intensity and disruption of original morphology are an extra challenge for the image analysis software, which therefore preferably should be dedicated to the detection and quantification of histomorphometrical end points.

Simultaneous quantitation of 14 active components in Yinchenhao decoction with an ultrahigh performance liquid chromatography-diode array detector: Method development and ingredient analysis of different commonly prepared samples.

PubMed

Yi, YaXiong; Zhang, Yong; Ding, Yue; Lu, Lu; Zhang, Tong; Zhao, Yuan; Xu, XiaoJun; Zhang, YuXin

2016-11-01

J. Sep. Sci. 2016, 39, 4147-4157 DOI: 10.1002/jssc.201600284 Yinchenhao decoction (YCHD) is a famous Chinese herbal formula recorded in the Shang Han Lun which was prescribed by Zhongjing Zhang during 150-219 AD. A novel quantitative analysis method was developed, based on ultrahigh performance liquid chromatography coupled with a diode array detector for the simultaneous determination of 14 main active components in Yinchenhao decoction. Furthermore, the method has been applied for compositional difference analysis of the 14 components in eight normal extraction samples of Yinchenhao decoction, with the aid of hierarchical clustering analysis and similarity analysis. The present research could help hospital, factory and lab choose the best way to make Yinchenhao decoction with better efficacy. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel approach for evaluating the performance of real time quantitative loop-mediated isothermal amplification-based methods.

PubMed

Nixon, Gavin J; Svenstrup, Helle F; Donald, Carol E; Carder, Caroline; Stephenson, Judith M; Morris-Jones, Stephen; Huggett, Jim F; Foy, Carole A

2014-12-01

Molecular diagnostic measurements are currently underpinned by the polymerase chain reaction (PCR). There are also a number of alternative nucleic acid amplification technologies, which unlike PCR, work at a single temperature. These 'isothermal' methods, reportedly offer potential advantages over PCR such as simplicity, speed and resistance to inhibitors and could also be used for quantitative molecular analysis. However there are currently limited mechanisms to evaluate their quantitative performance, which would assist assay development and study comparisons. This study uses a sexually transmitted infection diagnostic model in combination with an adapted metric termed isothermal doubling time (IDT), akin to PCR efficiency, to compare quantitative PCR and quantitative loop-mediated isothermal amplification (qLAMP) assays, and to quantify the impact of matrix interference. The performance metric described here facilitates the comparison of qLAMP assays that could assist assay development and validation activities.

Quantitative profiling of immune repertoires for minor lymphocyte counts using unique molecular identifiers.

PubMed

Egorov, Evgeny S; Merzlyak, Ekaterina M; Shelenkov, Andrew A; Britanova, Olga V; Sharonov, George V; Staroverov, Dmitriy B; Bolotin, Dmitriy A; Davydov, Alexey N; Barsova, Ekaterina; Lebedev, Yuriy B; Shugay, Mikhail; Chudakov, Dmitriy M

2015-06-15

Emerging high-throughput sequencing methods for the analyses of complex structure of TCR and BCR repertoires give a powerful impulse to adaptive immunity studies. However, there are still essential technical obstacles for performing a truly quantitative analysis. Specifically, it remains challenging to obtain comprehensive information on the clonal composition of small lymphocyte populations, such as Ag-specific, functional, or tissue-resident cell subsets isolated by sorting, microdissection, or fine needle aspirates. In this study, we report a robust approach based on unique molecular identifiers that allows profiling Ag receptors for several hundred to thousand lymphocytes while preserving qualitative and quantitative information on clonal composition of the sample. We also describe several general features regarding the data analysis with unique molecular identifiers that are critical for accurate counting of starting molecules in high-throughput sequencing applications. Copyright © 2015 by The American Association of Immunologists, Inc.

Quantitative imaging of aggregated emulsions.

PubMed

Penfold, Robert; Watson, Andrew D; Mackie, Alan R; Hibberd, David J

2006-02-28

Noise reduction, restoration, and segmentation methods are developed for the quantitative structural analysis in three dimensions of aggregated oil-in-water emulsion systems imaged by fluorescence confocal laser scanning microscopy. Mindful of typical industrial formulations, the methods are demonstrated for concentrated (30% volume fraction) and polydisperse emulsions. Following a regularized deconvolution step using an analytic optical transfer function and appropriate binary thresholding, novel application of the Euclidean distance map provides effective discrimination of closely clustered emulsion droplets with size variation over at least 1 order of magnitude. The a priori assumption of spherical nonintersecting objects provides crucial information to combat the ill-posed inverse problem presented by locating individual particles. Position coordinates and size estimates are recovered with sufficient precision to permit quantitative study of static geometrical features. In particular, aggregate morphology is characterized by a novel void distribution measure based on the generalized Apollonius problem. This is also compared with conventional Voronoi/Delauney analysis.

Quantitative analysis of transmittance and photoluminescence using a low cost apparatus

NASA Astrophysics Data System (ADS)

Onorato, P.; Malgieri, M.; De Ambrosis, A.

2016-01-01

We show how a low cost spectrometer, based on the use of inexpensive diffraction transmission gratings coupled with a commercial digital photo camera or a cellphone, can be assembled and employed to obtain quantitative spectra of different sources. In particular, we discuss its use in studying the spectra of fluorescent colored ink, used in highlighting pens, for which the transmission band and the emission peaks are measured and related to the ink color.

Acoustic Facies Analysis of Side-Scan Sonar Data

NASA Astrophysics Data System (ADS)

Dwan, Fa Shu

Acoustic facies analysis methods have allowed the generation of system-independent values for the quantitative seafloor acoustic parameter, backscattering strength, from GLORIA and (TAMU) ^2 side-scan sonar data. The resulting acoustic facies parameters enable quantitative comparisons of data collected by different sonar systems, data from different environments, and measurements made with survey geometries. Backscattering strength values were extracted from the sonar amplitude data by inversion based on the sonar equation. Image processing products reveal seafloor features and patterns of relative intensity. To quantitatively compare data collected at different times or by different systems, and to ground truth-measurements and geoacoustic models, quantitative corrections must be made on any given data set for system source level, beam pattern, time-varying gain, processing gain, transmission loss, absorption, insonified area contribution, and grazing angle effects. In the sonar equation, backscattering strength is the sonar parameter which is directly related to seafloor properties. The GLORIA data used in this study are from the edge of a distal lobe of the Monterey Fan. An interfingered region of strong and weak seafloor signal returns from a flat seafloor region provides an ideal data set for this study. Inversion of imagery data from the region allows the quantitative definition of different acoustic facies. The (TAMU) ^2 data used are from a calibration site near the Green Canyon area of the Gulf of Mexico. Acoustic facies analysis techniques were implemented to generate statistical information for acoustic facies based on the estimates of backscattering strength. The backscattering strength values have been compared with Lambert's Law and other functions to parameterize the description of the acoustic facies. The resulting Lambertian constant values range from -26 dB to -36 dB. A modified Lambert relationship, which consists of both intercept and slope terms, appears to represent the BSS versus grazing angle profiles better based on chi^2 testing and error ellipse generation. Different regression functions, composed of trigonometric functions, were analyzed for different segments of the BSS profiles. A cotangent or sine/cosine function shows promising results for representing the entire grazing angle span of the BSS profiles.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

PubMed

Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

2016-10-28

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Surface plasmon resonance microscopy: achieving a quantitative optical response

PubMed Central

Peterson, Alexander W.; Halter, Michael; Plant, Anne L.; Elliott, John T.

2016-01-01

Surface plasmon resonance (SPR) imaging allows real-time label-free imaging based on index of refraction, and changes in index of refraction at an interface. Optical parameter analysis is achieved by application of the Fresnel model to SPR data typically taken by an instrument in a prism based configuration. We carry out SPR imaging on a microscope by launching light into a sample, and collecting reflected light through a high numerical aperture microscope objective. The SPR microscope enables spatial resolution that approaches the diffraction limit, and has a dynamic range that allows detection of subnanometer to submicrometer changes in thickness of biological material at a surface. However, unambiguous quantitative interpretation of SPR changes using the microscope system could not be achieved using the Fresnel model because of polarization dependent attenuation and optical aberration that occurs in the high numerical aperture objective. To overcome this problem, we demonstrate a model to correct for polarization diattenuation and optical aberrations in the SPR data, and develop a procedure to calibrate reflectivity to index of refraction values. The calibration and correction strategy for quantitative analysis was validated by comparing the known indices of refraction of bulk materials with corrected SPR data interpreted with the Fresnel model. Subsequently, we applied our SPR microscopy method to evaluate the index of refraction for a series of polymer microspheres in aqueous media and validated the quality of the measurement with quantitative phase microscopy. PMID:27782542

Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases

PubMed Central

Zhang, Hongpo

2018-01-01

Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN) is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart) and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively. PMID:29854369

Risk manager formula for success: Influencing decision making.

PubMed

Midgley, Mike

2017-10-01

Providing the ultimate decision makers with a quantitative risk analysis based on thoughtful assessment by the organization's experts enables an efficient decision. © 2017 American Society for Healthcare Risk Management of the American Hospital Association.

The use of immunohistochemistry for biomarker assessment--can it compete with other technologies?

PubMed

Dunstan, Robert W; Wharton, Keith A; Quigley, Catherine; Lowe, Amanda

2011-10-01

A morphology-based assay such as immunohistochemistry (IHC) should be a highly effective means to define the expression of a target molecule of interest, especially if the target is a protein. However, over the past decade, IHC as a platform for biomarkers has been challenged by more quantitative molecular assays with reference standards but that lack morphologic context. For IHC to be considered a "top-tier" biomarker assay, it must provide truly quantitative data on par with non-morphologic assays, which means it needs to be run with reference standards. However, creating such standards for IHC will require optimizing all aspects of tissue collection, fixation, section thickness, morphologic criteria for assessment, staining processes, digitization of images, and image analysis. This will also require anatomic pathology to evolve from a discipline that is descriptive to one that is quantitative. A major step in this transformation will be replacing traditional ocular microscopes with computer monitors and whole slide images, for without digitization, there can be no accurate quantitation; without quantitation, there can be no standardization; and without standardization, the value of morphology-based IHC assays will not be realized.

Quantitative analysis of glycerophospholipids by LC-MS: acquisition, data handling, and interpretation

PubMed Central

Myers, David S.; Ivanova, Pavlina T.; Milne, Stephen B.; Brown, H. Alex

2012-01-01

As technology expands what it is possible to accurately measure, so too the challenges faced by modern mass spectrometry applications expand. A high level of accuracy in lipid quantitation across thousands of chemical species simultaneously is demanded. While relative changes in lipid amounts with varying conditions may provide initial insights or point to novel targets, there are many questions that require determination of lipid analyte absolute quantitation. Glycerophospholipids present a significant challenge in this regard, given the headgroup diversity, large number of possible acyl chain combinations, and vast range of ionization efficiency of species. Lipidomic output is being used more often not just for profiling of the masses of species, but also for highly-targeted flux-based measurements which put additional burdens on the quantitation pipeline. These first two challenges bring into sharp focus the need for a robust lipidomics workflow including deisotoping, differentiation from background noise, use of multiple internal standards per lipid class, and the use of a scriptable environment in order to create maximum user flexibility and maintain metadata on the parameters of the data analysis as it occurs. As lipidomics technology develops and delivers more output on a larger number of analytes, so must the sophistication of statistical post-processing also continue to advance. High-dimensional data analysis methods involving clustering, lipid pathway analysis, and false discovery rate limitation are becoming standard practices in a maturing field. PMID:21683157

Analysis of Biomass Sugars Using a Novel HPLC Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agblevor, F. A.; Hames, B. R.; Schell, D.

The precise quantitative analysis of biomass sugars is a very important step in the conversion of biomass feedstocks to fuels and chemicals. However, the most accurate method of biomass sugar analysis is based on the gas chromatography analysis of derivatized sugars either as alditol acetates or trimethylsilanes. The derivatization method is time consuming but the alternative high-performance liquid chromatography (HPLC) method cannot resolve most sugars found in biomass hydrolysates. We have demonstrated for the first time that by careful manipulation of the HPLC mobile phase, biomass monomeric sugars (arabinose, xylose, fructose, glucose, mannose, and galactose) can be analyzed quantitatively andmore » there is excellent baseline resolution of all the sugars. This method was demonstrated for standard sugars, pretreated corn stover liquid and solid fractions. Our method can also be used to analyze dimeric sugars (cellobiose and sucrose).« less

Microbial-based evaluation of foaming events in full-scale wastewater treatment plants by microscopy survey and quantitative image analysis.

PubMed

Leal, Cristiano; Amaral, António Luís; Costa, Maria de Lourdes

2016-08-01

Activated sludge systems are prone to be affected by foaming occurrences causing the sludge to rise in the reactor and affecting the wastewater treatment plant (WWTP) performance. Nonetheless, there is currently a knowledge gap hindering the development of foaming events prediction tools that may be fulfilled by the quantitative monitoring of AS systems biota and sludge characteristics. As such, the present study focuses on the assessment of foaming events in full-scale WWTPs, by quantitative protozoa, metazoa, filamentous bacteria, and sludge characteristics analysis, further used to enlighten the inner relationships between these parameters. In the current study, a conventional activated sludge system (CAS) and an oxidation ditch (OD) were surveyed throughout a period of 2 and 3 months, respectively, regarding their biota and sludge characteristics. The biota community was monitored by microscopic observation, and a new filamentous bacteria index was developed to quantify their occurrence. Sludge characteristics (aggregated and filamentous biomass contents and aggregate size) were determined by quantitative image analysis (QIA). The obtained data was then processed by principal components analysis (PCA), cross-correlation analysis, and decision trees to assess the foaming occurrences, and enlighten the inner relationships. It was found that such events were best assessed by the combined use of the relative abundance of testate amoeba and nocardioform filamentous index, presenting a 92.9 % success rate for overall foaming events, and 87.5 and 100 %, respectively, for persistent and mild events.

Quantitative analysis of crystalline pharmaceuticals in tablets by pattern-fitting procedure using X-ray diffraction pattern.

PubMed

Takehira, Rieko; Momose, Yasunori; Yamamura, Shigeo

2010-10-15

A pattern-fitting procedure using an X-ray diffraction pattern was applied to the quantitative analysis of binary system of crystalline pharmaceuticals in tablets. Orthorhombic crystals of isoniazid (INH) and mannitol (MAN) were used for the analysis. Tablets were prepared under various compression pressures using a direct compression method with various compositions of INH and MAN. Assuming that X-ray diffraction pattern of INH-MAN system consists of diffraction intensities from respective crystals, observed diffraction intensities were fitted to analytic expression based on X-ray diffraction theory and separated into two intensities from INH and MAN crystals by a nonlinear least-squares procedure. After separation, the contents of INH were determined by using the optimized normalization constants for INH and MAN. The correction parameter including all the factors that are beyond experimental control was required for quantitative analysis without calibration curve. The pattern-fitting procedure made it possible to determine crystalline phases in the range of 10-90% (w/w) of the INH contents. Further, certain characteristics of the crystals in the tablets, such as the preferred orientation, size of crystallite, and lattice disorder were determined simultaneously. This method can be adopted to analyze compounds whose crystal structures are known. It is a potentially powerful tool for the quantitative phase analysis and characterization of crystals in tablets and powders using X-ray diffraction patterns. Copyright 2010 Elsevier B.V. All rights reserved.

Analysis of Mammalian Sphingolipids by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) and Tissue Imaging Mass Spectrometry (TIMS)

PubMed Central

Sullards, M. Cameron; Liu, Ying; Chen, Yanfeng; Merrill, Alfred H.

2011-01-01

Sphingolipids are a highly diverse category of molecules that serve not only as components of biological structures but also as regulators of numerous cell functions. Because so many of the structural features of sphingolipids give rise to their biological activity, there is a need for comprehensive or “sphingolipidomic” methods for identification and quantitation of as many individual subspecies as possible. This review defines sphingolipids as a class, briefly discusses classical methods for their analysis, and focuses primarily on liquid chromatography tandem mass spectrometry (LC-MS/MS) and tissue imaging mass spectrometry (TIMS). Recently, a set of evolving and expanding methods have been developed and rigorously validated for the extraction, identification, separation, and quantitation of sphingolipids by LC-MS/MS. Quantitation of these biomolecules is made possible via the use of an internal standard cocktail. The compounds that can be readily analyzed are free long-chain (sphingoid) bases, sphingoid base 1-phosphates, and more complex species such as ceramides, ceramide 1-phosphates, sphingomyelins, mono- and di-hexosylceramides sulfatides, and novel compounds such as the 1-deoxy- and 1-(deoxymethyl)-sphingoid bases and their N-acyl-derivatives. These methods can be altered slightly to separate and quantitate isomeric species such as glucosyl/galactosylceramide. Because these techniques require the extraction of sphingolipids from their native environment, any information regarding their localization in histological slices is lost. Therefore, this review also describes methods for TIMS. This technique has been shown to be a powerful tool to determine the localization of individual molecular species of sphingolipids directly from tissue slices. PMID:21749933

Fuzzy method of recognition of high molecular substances in evidence-based biology

NASA Astrophysics Data System (ADS)

Olevskyi, V. I.; Smetanin, V. T.; Olevska, Yu. B.

2017-10-01

Nowadays modern requirements to achieving reliable results along with high quality of researches put mathematical analysis methods of results at the forefront. Because of this, evidence-based methods of processing experimental data have become increasingly popular in the biological sciences and medicine. Their basis is meta-analysis, a method of quantitative generalization of a large number of randomized trails contributing to a same special problem, which are often contradictory and performed by different authors. It allows identifying the most important trends and quantitative indicators of the data, verification of advanced hypotheses and discovering new effects in the population genotype. The existing methods of recognizing high molecular substances by gel electrophoresis of proteins under denaturing conditions are based on approximate methods for comparing the contrast of electrophoregrams with a standard solution of known substances. We propose a fuzzy method for modeling experimental data to increase the accuracy and validity of the findings of the detection of new proteins.

Study of distributed learning as a solution to category proliferation in Fuzzy ARTMAP based neural systems.

PubMed

Parrado-Hernández, Emilio; Gómez-Sánchez, Eduardo; Dimitriadis, Yannis A

2003-09-01

An evaluation of distributed learning as a means to attenuate the category proliferation problem in Fuzzy ARTMAP based neural systems is carried out, from both qualitative and quantitative points of view. The study involves two original winner-take-all (WTA) architectures, Fuzzy ARTMAP and FasArt, and their distributed versions, dARTMAP and dFasArt. A qualitative analysis of the distributed learning properties of dARTMAP is made, focusing on the new elements introduced to endow Fuzzy ARTMAP with distributed learning. In addition, a quantitative study on a selected set of classification problems points out that problems have to present certain features in their output classes in order to noticeably reduce the number of recruited categories and achieve an acceptable classification accuracy. As part of this analysis, distributed learning was successfully adapted to a member of the Fuzzy ARTMAP family, FasArt, and similar procedures can be used to extend distributed learning capabilities to other Fuzzy ARTMAP based systems.

Wavelet-based multiscale analysis of bioimpedance data measured by electric cell-substrate impedance sensing for classification of cancerous and normal cells.

PubMed

Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen

2015-12-01

The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients.

PubMed

Ma, Kevin C; Fernandez, James R; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S; Liu, Brent J

2015-12-01

MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients

PubMed Central

Ma, Kevin C.; Fernandez, James R.; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S.; Liu, Brent J.

2016-01-01

Purpose MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. Method An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. Summary The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. PMID:26564667

Interpreting comprehensive two-dimensional gas chromatography using peak topography maps with application to petroleum forensics.

PubMed

Ghasemi Damavandi, Hamidreza; Sen Gupta, Ananya; Nelson, Robert K; Reddy, Christopher M

2016-01-01

Comprehensive two-dimensional gas chromatography [Formula: see text] provides high-resolution separations across hundreds of compounds in a complex mixture, thus unlocking unprecedented information for intricate quantitative interpretation. We exploit this compound diversity across the [Formula: see text] topography to provide quantitative compound-cognizant interpretation beyond target compound analysis with petroleum forensics as a practical application. We focus on the [Formula: see text] topography of biomarker hydrocarbons, hopanes and steranes, as they are generally recalcitrant to weathering. We introduce peak topography maps (PTM) and topography partitioning techniques that consider a notably broader and more diverse range of target and non-target biomarker compounds compared to traditional approaches that consider approximately 20 biomarker ratios. Specifically, we consider a range of 33-154 target and non-target biomarkers with highest-to-lowest peak ratio within an injection ranging from 4.86 to 19.6 (precise numbers depend on biomarker diversity of individual injections). We also provide a robust quantitative measure for directly determining "match" between samples, without necessitating training data sets. We validate our methods across 34 [Formula: see text] injections from a diverse portfolio of petroleum sources, and provide quantitative comparison of performance against established statistical methods such as principal components analysis (PCA). Our data set includes a wide range of samples collected following the 2010 Deepwater Horizon disaster that released approximately 160 million gallons of crude oil from the Macondo well (MW). Samples that were clearly collected following this disaster exhibit statistically significant match [Formula: see text] using PTM-based interpretation against other closely related sources. PTM-based interpretation also provides higher differentiation between closely correlated but distinct sources than obtained using PCA-based statistical comparisons. In addition to results based on this experimental field data, we also provide extentive perturbation analysis of the PTM method over numerical simulations that introduce random variability of peak locations over the [Formula: see text] biomarker ROI image of the MW pre-spill sample (sample [Formula: see text] in Additional file 4: Table S1). We compare the robustness of the cross-PTM score against peak location variability in both dimensions and compare the results against PCA analysis over the same set of simulated images. Detailed description of the simulation experiment and discussion of results are provided in Additional file 1: Section S8. We provide a peak-cognizant informational framework for quantitative interpretation of [Formula: see text] topography. Proposed topographic analysis enables [Formula: see text] forensic interpretation across target petroleum biomarkers, while including the nuances of lesser-known non-target biomarkers clustered around the target peaks. This allows potential discovery of hitherto unknown connections between target and non-target biomarkers.

Race and Older Mothers’ Differentiation: A Sequential Quantitative and Qualitative Analysis

PubMed Central

Sechrist, Jori; Suitor, J. Jill; Riffin, Catherine; Taylor-Watson, Kadari; Pillemer, Karl

2011-01-01

The goal of this paper is to demonstrate a process by which qualitative and quantitative approaches are combined to reveal patterns in the data that are unlikely to be detected and confirmed by either method alone. Specifically, we take a sequential approach to combining qualitative and quantitative data to explore race differences in how mothers differentiate among their adult children. We began with a standard multivariate analysis examining race differences in mothers’ differentiation among their adult children regarding emotional closeness and confiding. Finding no race differences in this analysis, we conducted an in-depth comparison of the Black and White mothers’ narratives to determine whether there were underlying patterns that we had been unable to detect in our first analysis. Using this method, we found that Black mothers were substantially more likely than White mothers to emphasize interpersonal relationships within the family when describing differences among their children. In our final step, we developed a measure of familism based on the qualitative data and conducted a multivariate analysis to confirm the patterns revealed by the in-depth comparison of the mother’s narratives. We conclude that using such a sequential mixed methods approach to data analysis has the potential to shed new light on complex family relations. PMID:21967639

Chemical Fingerprint Analysis and Quantitative Analysis of Rosa rugosa by UPLC-DAD.

PubMed

Mansur, Sanawar; Abdulla, Rahima; Ayupbec, Amatjan; Aisa, Haji Akbar

2016-12-21

A method based on ultra performance liquid chromatography with a diode array detector (UPLC-DAD) was developed for quantitative analysis of five active compounds and chemical fingerprint analysis of Rosa rugosa . Ten batches of R. rugosa collected from different plantations in the Xinjiang region of China were used to establish the fingerprint. The feasibility and advantages of the used UPLC fingerprint were verified for its similarity evaluation by systematically comparing chromatograms with professional analytical software recommended by State Food and Drug Administration (SFDA) of China. In quantitative analysis, the five compounds showed good regression (R² = 0.9995) within the test ranges, and the recovery of the method was in the range of 94.2%-103.8%. The similarities of liquid chromatography fingerprints of 10 batches of R. rugosa were more than 0.981. The developed UPLC fingerprint method is simple, reliable, and validated for the quality control and identification of R. rugosa . Additionally, simultaneous quantification of five major bioactive ingredients in the R. rugosa samples was conducted to interpret the consistency of the quality test. The results indicated that the UPLC fingerprint, as a characteristic distinguishing method combining similarity evaluation and quantification analysis, can be successfully used to assess the quality and to identify the authenticity of R. rugosa .

Application of a SERS-based lateral flow immunoassay strip for the rapid and sensitive detection of staphylococcal enterotoxin B

NASA Astrophysics Data System (ADS)

Hwang, Joonki; Lee, Sangyeop; Choo, Jaebum

2016-06-01

A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner.A novel surface-enhanced Raman scattering (SERS)-based lateral flow immunoassay (LFA) biosensor was developed to resolve problems associated with conventional LFA strips (e.g., limits in quantitative analysis and low sensitivity). In our SERS-based biosensor, Raman reporter-labeled hollow gold nanospheres (HGNs) were used as SERS detection probes instead of gold nanoparticles. With the proposed SERS-based LFA strip, the presence of a target antigen can be identified through a colour change in the test zone. Furthermore, highly sensitive quantitative evaluation is possible by measuring SERS signals from the test zone. To verify the feasibility of the SERS-based LFA strip platform, an immunoassay of staphylococcal enterotoxin B (SEB) was performed as a model reaction. The limit of detection (LOD) for SEB, as determined with the SERS-based LFA strip, was estimated to be 0.001 ng mL-1. This value is approximately three orders of magnitude more sensitive than that achieved with the corresponding ELISA-based method. The proposed SERS-based LFA strip sensor shows significant potential for the rapid and sensitive detection of target markers in a simplified manner. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07243c

A Study of Cognitive Load for Enhancing Student’s Quantitative Literacy in Inquiry Lab Learning

NASA Astrophysics Data System (ADS)

Nuraeni, E.; Rahman, T.; Alifiani, D. P.; Khoerunnisa, R. S.

2017-09-01

Students often find it difficult to appreciate the relevance of the role of quantitative analysis and concept attainment in the science class. This study measured student cognitive load during the inquiry lab of the respiratory system to improve quantitative literacy. Participants in this study were 40 11th graders from senior high school in Indonesia. After students learned, their feelings about the degree of mental effort that it took to complete the learning tasks were measured by 28 self-report on a 4-point Likert scale. The Task Complexity Worksheet were used to asses processing quantitative information and paper based test were applied to assess participants’ concept achievements. The results showed that inquiry instructional induced a relatively low mental effort, high processing information and high concept achievments.

An open-source computational and data resource to analyze digital maps of immunopeptidomes

DOE PAGES

Caron, Etienne; Espona, Lucia; Kowalewski, Daniel J.; ...

2015-07-08

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

Printing 2-dimentional droplet array for single-cell reverse transcription quantitative PCR assay with a microfluidic robot.

PubMed

Zhu, Ying; Zhang, Yun-Xia; Liu, Wen-Wen; Ma, Yan; Fang, Qun; Yao, Bo

2015-04-01

This paper describes a nanoliter droplet array-based single-cell reverse transcription quantitative PCR (RT-qPCR) assay method for quantifying gene expression in individual cells. By sequentially printing nanoliter-scale droplets on microchip using a microfluidic robot, all liquid-handling operations including cell encapsulation, lysis, reverse transcription, and quantitative PCR with real-time fluorescence detection, can be automatically achieved. The inhibition effect of cell suspension buffer on RT-PCR assay was comprehensively studied to achieve high-sensitivity gene quantification. The present system was applied in the quantitative measurement of expression level of mir-122 in single Huh-7 cells. A wide distribution of mir-122 expression in single cells from 3061 copies/cell to 79998 copies/cell was observed, showing a high level of cell heterogeneity. With the advantages of full-automation in liquid-handling, simple system structure, and flexibility in achieving multi-step operations, the present method provides a novel liquid-handling mode for single cell gene expression analysis, and has significant potentials in transcriptional identification and rare cell analysis.