Molecularly tagged genes and quantitative trait loci in cucumber

USDA-ARS?s Scientific Manuscript database

Since the release of the cucumber draft genome, significant progress has been made in molecular mapping, tagging or cloning of horticulturally important genes and quantitative trait loci (QTLs) in cucumber, which provides the foundation for practicing marker-assisted selection in cucumber breeding. ...

Quantitative proteomic analysis of amniocytes reveals potentially dysregulated molecular networks in Down syndrome

PubMed Central

2013-01-01

Background Down syndrome (DS), caused by an extra copy of chromosome 21, affects 1 in 750 live births and is characterized by cognitive impairment and a constellation of congenital defects. Currently, little is known about the molecular pathogenesis and no direct genotype-phenotype relationship has yet been confirmed. Since DS amniocytes are expected to have a distinct biological behaviour compared to normal amniocytes, we hypothesize that relative quantification of proteins produced from trisomy and euploid (chromosomally normal) amniocytes will reveal dysregulated molecular pathways. Results Chromosomally normal- and Trisomy 21-amniocytes were quantitatively analyzed by using Stable Isotope Labeling of Amino acids in Cell culture and tandem mass spectrometry. A total of 4919 unique proteins were identified from the supernatant and cell lysate proteome. More specifically, 4548 unique proteins were identified from the lysate, and 91% of these proteins were quantified based on MS/MS spectra ratios of peptides containing isotope-labeled amino acids. A total of 904 proteins showed significant differential expression and were involved in 25 molecular pathways, each containing a minimum of 16 proteins. Sixty of these proteins consistently showed aberrant expression from trisomy 21 affected amniocytes, indicating their potential role in DS pathogenesis. Nine proteins were analyzed with a multiplex selected reaction monitoring assay in an independent set of Trisomy 21-amniocyte samples and two of them (SOD1 and NES) showed a consistent differential expression. Conclusions The most extensive proteome of amniocytes and amniotic fluid has been generated and differentially expressed proteins from amniocytes with Trisomy 21 revealed molecular pathways that seem to be most significantly affected by the presence of an extra copy of chromosome 21. PMID:23394617

Behavioral and molecular studies of quantitative differences in hygienic behavior in honeybees.

PubMed

Gempe, Tanja; Stach, Silke; Bienefeld, Kaspar; Otte, Marianne; Beye, Martin

2016-10-21

Hygienic behavior (HB) enables honeybees to tolerate parasites, including infection with the parasitic mite Varroa destructor, and it is a well-known example of a quantitative genetic trait. The understanding of the molecular processes underpinning the quantitative differences in this behavior remains limited. We performed gene expression studies in worker bees that displayed quantitative genetic differences in HB. We established a high and low genetic source of HB performance and studied the engagements into HB of single worker bees under the same environmental conditions. We found that the percentage of worker bees that engaged in a hygienic behavioral task tripled in the high versus low HB sources, thus suggesting that genetic differences may mediate differences in stimulated states to perform HB. We found 501 differently expressed genes (DEGs) in the brains of hygienic and non-hygienic performing workers in the high HB source bees, and 342 DEGs in the brains of hygienic performing worker bees, relative to the gene expression in non-hygienic worker bees from the low HB source group. "Cell surface receptor ligand signal transduction" in the high and "negative regulation of cell communication" in the low HB source were overrepresented molecular processes, suggesting that these molecular processes in the brain may play a role in the regulation of quantitative differences in HB. Moreover, only 21 HB-associated DEGs were common between the high and low HB sources. The better HB colony performance is primarily achieved by a high number of bees engaging in the hygienic tasks that associate with distinct molecular processes in the brain. We propose that different gene products and pathways may mediate the quantitative genetic differences of HB.

International Standards and Reference Materials for Quantitative Molecular Infectious Disease Testing

PubMed Central

Madej, Roberta M.; Davis, Jack; Holden, Marcia J.; Kwang, Stan; Labourier, Emmanuel; Schneider, George J.

2010-01-01

The utility of quantitative molecular diagnostics for patient management depends on the ability to relate patient results to prior results or to absolute values in clinical practice guidelines. To do this, those results need to be comparable across time and methods, either by producing the same value across methods and test versions or by using reliable and stable conversions. Universally available standards and reference materials specific to quantitative molecular technologies are critical to this process but are few in number. This review describes recent history in the establishment of international standards for nucleic acid test development, organizations involved in current efforts, and future issues and initiatives. PMID:20075208

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

PubMed

Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

2016-05-05

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Inverse transport problems in quantitative PAT for molecular imaging

NASA Astrophysics Data System (ADS)

Ren, Kui; Zhang, Rongting; Zhong, Yimin

2015-12-01

Fluorescence photoacoustic tomography (fPAT) is a molecular imaging modality that combines photoacoustic tomography with fluorescence imaging to obtain high-resolution imaging of fluorescence distributions inside heterogeneous media. The objective of this work is to study inverse problems in the quantitative step of fPAT where we intend to reconstruct physical coefficients in a coupled system of radiative transport equations using internal data recovered from ultrasound measurements. We derive uniqueness and stability results on the inverse problems and develop some efficient algorithms for image reconstructions. Numerical simulations based on synthetic data are presented to validate the theoretical analysis. The results we present here complement these in Ren K and Zhao H (2013 SIAM J. Imaging Sci. 6 2024-49) on the same problem but in the diffusive regime.

Evaluation of a quantitative H2S MPN test for fecal microbes analysis of water using biochemical and molecular identification.

PubMed

McMahan, Lanakila; Grunden, Amy M; Devine, Anthony A; Sobsey, Mark D

2012-04-15

The sensitivity and specificity of the H(2)S test to detect fecal bacteria in water has been variable and uncertain in previous studies, partly due to its presence-absence results. Furthermore, in groundwater samples false-positive results have been reported, with H(2)S-positive samples containing no fecal coliforms or Escherichia coli. False-negative results also have been reported in other studies, with H(2)S-negative samples found to contain E. coli. Using biochemical and molecular methods and a novel quantitative test format, this research identified the types and numbers of microbial community members present in natural water samples, including fecal indicators and pathogens as well as other bacteria. Representative water sources tested in this study included cistern rainwater, a protected lake, and wells in agricultural and forest settings. Samples from quantitative H(2)S tests of water were further cultured for fecal bacteria by spread plating onto the selective media for detection and isolation of Aeromonas spp., E. coli, Clostridium spp., H(2)S-producers, and species of Salmonella and Shigella. Isolates were then tested for H(2)S production, and identified to the genus and species level using biochemical methods. Terminal Restriction Fragment Length Polymorphisms (TRFLP) was the molecular method employed to quantitatively characterize microbial community diversity. Overall, it was shown that water samples testing positive for H(2)S bacteria also had bacteria of likely fecal origin and waters containing fecal pathogens also were positive for H(2)S bacteria. Of the microorganisms isolated from natural water, greater than 70 percent were identified using TRFLP analysis to reveal a relatively stable group of organisms whose community composition differed with water source and over time. These results further document the validity of the H(2)S test for detecting and quantifying fecal contamination of water. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative Molecular Phenotyping of Gill Remodeling in a Cichlid Fish Responding to Salinity Stress*

PubMed Central

Kültz, Dietmar; Li, Johnathon; Gardell, Alison; Sacchi, Romina

2013-01-01

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into

Differential diagnosis of lung carcinoma with three-dimensional quantitative molecular vibrational imaging

NASA Astrophysics Data System (ADS)

Gao, Liang; Hammoudi, Ahmad A.; Li, Fuhai; Thrall, Michael J.; Cagle, Philip T.; Chen, Yuanxin; Yang, Jian; Xia, Xiaofeng; Fan, Yubo; Massoud, Yehia; Wang, Zhiyong; Wong, Stephen T. C.

2012-06-01

The advent of molecularly targeted therapies requires effective identification of the various cell types of non-small cell lung carcinomas (NSCLC). Currently, cell type diagnosis is performed using small biopsies or cytology specimens that are often insufficient for molecular testing after morphologic analysis. Thus, the ability to rapidly recognize different cancer cell types, with minimal tissue consumption, would accelerate diagnosis and preserve tissue samples for subsequent molecular testing in targeted therapy. We report a label-free molecular vibrational imaging framework enabling three-dimensional (3-D) image acquisition and quantitative analysis of cellular structures for identification of NSCLC cell types. This diagnostic imaging system employs superpixel-based 3-D nuclear segmentation for extracting such disease-related features as nuclear shape, volume, and cell-cell distance. These features are used to characterize cancer cell types using machine learning. Using fresh unstained tissue samples derived from cell lines grown in a mouse model, the platform showed greater than 97% accuracy for diagnosis of NSCLC cell types within a few minutes. As an adjunct to subsequent histology tests, our novel system would allow fast delineation of cancer cell types with minimum tissue consumption, potentially facilitating on-the-spot diagnosis, while preserving specimens for additional tests. Furthermore, 3-D measurements of cellular structure permit evaluation closer to the native state of cells, creating an alternative to traditional 2-D histology specimen evaluation, potentially increasing accuracy in diagnosing cell type of lung carcinomas.

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 analysis of pork and chicken products by droplet digital PCR.

PubMed

Cai, Yicun; Li, Xiang; Lv, Rong; Yang, Jielin; Li, Jian; He, Yuping; Pan, Liangwen

2014-01-01

In this project, a highly precise quantitative method based on the digital polymerase chain reaction (dPCR) technique was developed to determine the weight of pork and chicken in meat products. Real-time quantitative polymerase chain reaction (qPCR) is currently used for quantitative molecular analysis of the presence of species-specific DNAs in meat products. However, it is limited in amplification efficiency and relies on standard curves based Ct values, detecting and quantifying low copy number target DNA, as in some complex mixture meat products. By using the dPCR method, we find the relationships between the raw meat weight and DNA weight and between the DNA weight and DNA copy number were both close to linear. This enabled us to establish formulae to calculate the raw meat weight based on the DNA copy number. The accuracy and applicability of this method were tested and verified using samples of pork and chicken powder mixed in known proportions. Quantitative analysis indicated that dPCR is highly precise in quantifying pork and chicken in meat products and therefore has the potential to be used in routine analysis by government regulators and quality control departments of commercial food and feed enterprises.

SILAC-based quantitative proteomic analysis reveals widespread molecular alterations in human skin keratinocytes upon chronic arsenic exposure.

PubMed

Mir, Sartaj Ahmad; Pinto, Sneha M; Paul, Somnath; Raja, Remya; Nanjappa, Vishalakshi; Syed, Nazia; Advani, Jayshree; Renuse, Santosh; Sahasrabuddhe, Nandini A; Prasad, T S Keshava; Giri, Ashok K; Gowda, Harsha; Chatterjee, Aditi

2017-03-01

Chronic exposure to arsenic is associated with dermatological and nondermatological disorders. Consumption of arsenic-contaminated drinking water results in accumulation of arsenic in liver, spleen, kidneys, lungs, and gastrointestinal tract. Although arsenic is cleared from these sites, a substantial amount of residual arsenic is left in keratin-rich tissues including skin. Epidemiological studies suggest the association of skin cancer upon arsenic exposure, however, the mechanism of arsenic-induced carcinogenesis is not completely understood. We developed a cell line based model to understand the molecular mechanisms involved in arsenic-mediated toxicity and carcinogenicity. Human skin keratinocyte cell line, HaCaT, was chronically exposed to 100 nM sodium arsenite over a period of 6 months. We observed an increase in basal ROS levels in arsenic-exposed cells. SILAC-based quantitative proteomics approach resulted in identification of 2111 proteins of which 42 proteins were found to be overexpressed and 54 downregulated (twofold) upon chronic arsenic exposure. Our analysis revealed arsenic-induced overexpression of aldo-keto reductase family 1 member C2 (AKR1C2), aldo-keto reductase family 1 member C3 (AKR1C3), glutamate-cysteine ligase catalytic subunit (GCLC), and NAD(P)H dehydrogenase [quinone] 1 (NQO1) among others. We observed downregulation of several members of the plakin family including periplakin (PPL), envoplakin (EVPL), and involucrin (IVL) that are essential for terminal differentiation of keratinocytes. MRM and Western blot analysis confirmed differential expression of several candidate proteins. Our study provides insights into molecular alterations upon chronic arsenic exposure on skin. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Formalizing the definition of meta-analysis in Molecular Ecology.

PubMed

ArchMiller, Althea A; Bauer, Eric F; Koch, Rebecca E; Wijayawardena, Bhagya K; Anil, Ammu; Kottwitz, Jack J; Munsterman, Amelia S; Wilson, Alan E

2015-08-01

Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first meta-analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's FST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'meta-analyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted meta-analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta-analysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology. © 2015 John Wiley & Sons Ltd.

Quantitative analysis of intermolecular interactions in orthorhombic rubrene

DOE PAGES

Hathwar, Venkatesha R.; Sist, Mattia; Jørgensen, Mads R. V.; ...

2015-08-14

Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically,more » the presence of C π...C πinteractions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI) analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. Finally, the quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations.« less

Molecular Modeling on Berberine Derivatives toward BuChE: An Integrated Study with Quantitative Structure-Activity Relationships Models, Molecular Docking, and Molecular Dynamics Simulations.

PubMed

Fang, Jiansong; Pang, Xiaocong; Wu, Ping; Yan, Rong; Gao, Li; Li, Chao; Lian, Wenwen; Wang, Qi; Liu, Ai-lin; Du, Guan-hua

2016-05-01

A dataset of 67 berberine derivatives for the inhibition of butyrylcholinesterase (BuChE) was studied based on the combination of quantitative structure-activity relationships models, molecular docking, and molecular dynamics methods. First, a series of berberine derivatives were reported, and their inhibitory activities toward butyrylcholinesterase (BuChE) were evaluated. By 2D- quantitative structure-activity relationships studies, the best model built by partial least-square had a conventional correlation coefficient of the training set (R(2)) of 0.883, a cross-validation correlation coefficient (Qcv2) of 0.777, and a conventional correlation coefficient of the test set (Rpred2) of 0.775. The model was also confirmed by Y-randomization examination. In addition, the molecular docking and molecular dynamics simulation were performed to better elucidate the inhibitory mechanism of three typical berberine derivatives (berberine, C2, and C55) toward BuChE. The predicted binding free energy results were consistent with the experimental data and showed that the van der Waals energy term (ΔEvdw) difference played the most important role in differentiating the activity among the three inhibitors (berberine, C2, and C55). The developed quantitative structure-activity relationships models provide details on the fine relationship linking structure and activity and offer clues for structural modifications, and the molecular simulation helps to understand the inhibitory mechanism of the three typical inhibitors. In conclusion, the results of this study provide useful clues for new drug design and discovery of BuChE inhibitors from berberine derivatives. © 2015 John Wiley & Sons A/S.

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.

The use of digital PCR to improve the application of quantitative molecular diagnostic methods for tuberculosis.

PubMed

Devonshire, Alison S; O'Sullivan, Denise M; Honeyborne, Isobella; Jones, Gerwyn; Karczmarczyk, Maria; Pavšič, Jernej; Gutteridge, Alice; Milavec, Mojca; Mendoza, Pablo; Schimmel, Heinz; Van Heuverswyn, Fran; Gorton, Rebecca; Cirillo, Daniela Maria; Borroni, Emanuele; Harris, Kathryn; Barnard, Marinus; Heydenrych, Anthenette; Ndusilo, Norah; Wallis, Carole L; Pillay, Keshree; Barry, Thomas; Reddington, Kate; Richter, Elvira; Mozioğlu, Erkan; Akyürek, Sema; Yalçınkaya, Burhanettin; Akgoz, Muslum; Žel, Jana; Foy, Carole A; McHugh, Timothy D; Huggett, Jim F

2016-08-03

Real-time PCR (qPCR) based methods, such as the Xpert MTB/RIF, are increasingly being used to diagnose tuberculosis (TB). While qualitative methods are adequate for diagnosis, the therapeutic monitoring of TB patients requires quantitative methods currently performed using smear microscopy. The potential use of quantitative molecular measurements for therapeutic monitoring has been investigated but findings have been variable and inconclusive. The lack of an adequate reference method and reference materials is a barrier to understanding the source of such disagreement. Digital PCR (dPCR) offers the potential for an accurate method for quantification of specific DNA sequences in reference materials which can be used to evaluate quantitative molecular methods for TB treatment monitoring. To assess a novel approach for the development of quality assurance materials we used dPCR to quantify specific DNA sequences in a range of prototype reference materials and evaluated accuracy between different laboratories and instruments. The materials were then also used to evaluate the quantitative performance of qPCR and Xpert MTB/RIF in eight clinical testing laboratories. dPCR was found to provide results in good agreement with the other methods tested and to be highly reproducible between laboratories without calibration even when using different instruments. When the reference materials were analysed with qPCR and Xpert MTB/RIF by clinical laboratories, all laboratories were able to correctly rank the reference materials according to concentration, however there was a marked difference in the measured magnitude. TB is a disease where the quantification of the pathogen could lead to better patient management and qPCR methods offer the potential to rapidly perform such analysis. However, our findings suggest that when precisely characterised materials are used to evaluate qPCR methods, the measurement result variation is too high to determine whether molecular quantification

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

Qualitative and quantitative analysis of heparin and low molecular weight heparins using size exclusion chromatography with multiple angle laser scattering/refractive index and inductively coupled plasma/mass spectrometry detectors.

PubMed

Ouyang, Yilan; Zeng, Yangyang; Yi, Lin; Tang, Hong; Li, Duxin; Linhardt, Robert J; Zhang, Zhenqing

2017-11-03

Heparin, a highly sulfated glycosaminoglycan, has been used as a clinical anticoagulant over 80 years. Low molecular weight heparins (LMWHs), heparins partially depolymerized using different processes, are widely used as clinical anticoagulants. Qualitative molecular weight (MW) and quantitative mass content analysis are two important factors that contribute to LMWH quality control. Size exclusion chromatography (SEC), relying on multiple angle laser scattering (MALS)/refractive index (RI) detectors, has been developed for accurate analysis of heparin MW in the absence of standards. However, the cations, which ion-pair with the anionic polysaccharide chains of heparin and LMWHs, had not been considered in previous reports. In this study, SEC with MALS/RI and inductively coupled plasma/mass spectrometry detectors were used in a comprehensive analytical approach taking both anionic polysaccharide and ion-paired cations heparin products. This approach was also applied to quantitative analysis of heparin and LMWHs. Full profiles of MWs and mass recoveries for three commercial heparin/LMWH products, heparin sodium, enoxaparin sodium and nadroparin calcium, were obtained and all showed higher MWs than previously reported. This important improvement more precisely characterized the MW properties of heparin/LMWHs and potentially many other anionic polysaccharides. Copyright © 2017 Elsevier B.V. All rights reserved.

[Methods of quantitative proteomics].

PubMed

Kopylov, A T; Zgoda, V G

2007-01-01

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.

Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics.

PubMed

Bahrami, Naeim; Hartman, Stephen J; Chang, Yu-Hsuan; Delfanti, Rachel; White, Nathan S; Karunamuni, Roshan; Seibert, Tyler M; Dale, Anders M; Hattangadi-Gluth, Jona A; Piccioni, David; Farid, Nikdokht; McDonald, Carrie R

2018-06-02

Molecular markers of WHO grade II/III glioma are known to have important prognostic and predictive implications and may be associated with unique imaging phenotypes. The purpose of this study is to determine whether three clinically relevant molecular markers identified in gliomas-IDH, 1p/19q, and MGMT status-show distinct quantitative MRI characteristics on FLAIR imaging. Sixty-one patients with grade II/III gliomas who had molecular data and MRI available prior to radiation were included. Quantitative MRI features were extracted that measured tissue heterogeneity (homogeneity and pixel correlation) and FLAIR border distinctiveness (edge contrast; EC). T-tests were conducted to determine whether patients with different genotypes differ across the features. Logistic regression with LASSO regularization was used to determine the optimal combination of MRI and clinical features for predicting molecular subtypes. Patients with IDH wildtype tumors showed greater signal heterogeneity (p = 0.001) and lower EC (p = 0.008) within the FLAIR region compared to IDH mutant tumors. Among patients with IDH mutant tumors, 1p/19q co-deleted tumors had greater signal heterogeneity (p = 0.002) and lower EC (p = 0.005) compared to 1p/19q intact tumors. MGMT methylated tumors showed lower EC (p = 0.03) compared to the unmethylated group. The combination of FLAIR border distinctness, heterogeneity, and pixel correlation optimally classified tumors by IDH status. Quantitative imaging characteristics of FLAIR heterogeneity and border pattern in grade II/III gliomas may provide unique information for determining molecular status at time of initial diagnostic imaging, which may then guide subsequent surgical and medical management.

Analysis of low molecular weight compounds by MALDI-FTICR-MS.

PubMed

Wang, Hao-Yang; Chu, Xu; Zhao, Zhi-Xiong; He, Xiao-Shuang; Guo, Yin-Long

2011-05-15

This review focuses on recent applications of matrix-assisted laser desorption ionization-Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS) in qualitative and quantitative analysis of low molecular weight compounds. The scope of the work includes amino acids, small peptides, mono and oligosaccharides, lipids, metabolic compounds, small molecule phytochemicals from medicinal herbs and even the volatile organic compounds from tobacco. We discuss both direct analysis and analysis following derivatization. In addition we review sample preparation strategies to reduce interferences in the low m/z range and to improve sensitivities by derivatization with charge tags. We also present coupling of head space techniques with MALDI-FTICR-MS. Furthermore, omics analyses based on MALDI-FTICR-MS were also discussed, including proteomics, metabolomics and lipidomics, as well as the relative MS imaging for bio-active low molecular weight compounds. Finally, we discussed the investigations on dissociation/rearrangement processes of low molecular weight compounds by MALDI-FTICR-MS. Copyright © 2011 Elsevier B.V. All rights reserved.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

PubMed

Wilson, Jennifer L; Altman, Russ B

2018-02-01

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

L-Phenylalanine catabolism and 2-phenylethanol synthesis in Yarrowia lipolytica--mapping molecular identities through whole-proteome quantitative mass spectrometry analysis.

PubMed

Celińska, Ewelina; Olkowicz, Mariola; Grajek, Włodzimierz

2015-08-01

A world-wide effort is now being pursued towards the development of flavors and fragrances (F&F) production independently from traditional sources, as well as autonomously from depleting fossil fuel supplies. Biotechnological production of F&F by microbes has emerged as a vivid solution to the current market limitations. Amongst a wide variety of fragrant chemicals, 2-PE is of significant interest to both scientific and industrial community. Although the general overview of the 2-PE synthesis pathway is commonly known, involvement of particular molecular identities in this pathway has not been elucidated in Yarrowia lipolytica to date. The aim of this study was mapping molecular identities involved in 2-PE synthesis in Y. lipolytica. To acquire a comprehensive landscape of the proteins that are directly and indirectly involved in L-Phe degradation and 2-PE synthesis, we took advantage of comprehensibility and sensitivity of high-throughput LC-MS/MS-quantitative analysis. Amongst a number of proteins involved in amino acid turnover and the central carbon metabolism, enzymes involved in L-Phe conversion to 2-PE have been identified. Results on yeast-to-hyphae transition in relation to the character of the provided nitrogen source have been presented. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

A CZT-based blood counter for quantitative molecular imaging.

PubMed

Espagnet, Romain; Frezza, Andrea; Martin, Jean-Pierre; Hamel, Louis-André; Lechippey, Laëtitia; Beauregard, Jean-Mathieu; Després, Philippe

2017-12-01

Robust quantitative analysis in positron emission tomography (PET) and in single-photon emission computed tomography (SPECT) typically requires the time-activity curve as an input function for the pharmacokinetic modeling of tracer uptake. For this purpose, a new automated tool for the determination of blood activity as a function of time is presented. The device, compact enough to be used on the patient bed, relies on a peristaltic pump for continuous blood withdrawal at user-defined rates. Gamma detection is based on a 20 × 20 × 15 mm 3 cadmium zinc telluride (CZT) detector, read by custom-made electronics and a field-programmable gate array-based signal processing unit. A graphical user interface (GUI) allows users to select parameters and easily perform acquisitions. This paper presents the overall design of the device as well as the results related to the detector performance in terms of stability, sensitivity and energy resolution. Results from a patient study are also reported. The device achieved a sensitivity of 7.1 cps/(kBq/mL) and a minimum detectable activity of 2.5 kBq/ml for 18 F. The gamma counter also demonstrated an excellent stability with a deviation in count rates inferior to 0.05% over 6 h. An energy resolution of 8% was achieved at 662 keV. The patient study was conclusive and demonstrated that the compact gamma blood counter developed has the sensitivity and the stability required to conduct quantitative molecular imaging studies in PET and SPECT.

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

PubMed Central

Xue, Yong; Chen, Shihui; Liu, Yong

2017-01-01

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

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.

Genetics and child psychiatry: I Advances in quantitative and molecular genetics.

PubMed

Rutter, M; Silberg, J; O'Connor, T; Simonoff, E

1999-01-01

Advances in quantitative psychiatric genetics as a whole are reviewed with respect to conceptual and methodological issues in relation to statistical model fitting, new genetic designs, twin and adoptee studies, definition of the phenotype, pervasiveness of genetic influences, pervasiveness of environmental influences, shared and nonshared environmental effects, and nature-nurture interplay. Advances in molecular genetics are discussed in relation to the shifts in research strategies to investigate multifactorial disorders (affected relative linkage designs, association strategies, and quantitative trait loci studies); new techniques and identified genetic mechanisms (expansion of trinucleotide repeats, genomic imprinting, mitochondrial DNA, fluorescent in-situ hybridisation, behavioural phenotypes, and animal models); and the successful localisation of genes.

Quantitative analysis of microtubule orientation in interdigitated leaf pavement cells

PubMed Central

Akita, Kae; Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2015-01-01

Leaf pavement cells are shaped like a jigsaw puzzle in most dicotyledon species. Molecular genetic studies have identified several genes required for pavement cells morphogenesis and proposed that microtubules play crucial roles in the interdigitation of pavement cells. In this study, we performed quantitative analysis of cortical microtubule orientation in leaf pavement cells in Arabidopsis thaliana. We captured confocal images of cortical microtubules in cotyledon leaf epidermis expressing GFP-tubulinβ and quantitatively evaluated the microtubule orientations relative to the pavement cell growth axis using original image processing techniques. Our results showed that microtubules kept parallel orientations to the growth axis during pavement cell growth. In addition, we showed that immersion treatment of seed cotyledons in solutions containing tubulin polymerization and depolymerization inhibitors decreased pavement cell complexity. Treatment with oryzalin and colchicine inhibited the symmetric division of guard mother cells. PMID:26039484

Quantitative analysis of microtubule orientation in interdigitated leaf pavement cells.

PubMed

Akita, Kae; Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2015-01-01

Leaf pavement cells are shaped like a jigsaw puzzle in most dicotyledon species. Molecular genetic studies have identified several genes required for pavement cells morphogenesis and proposed that microtubules play crucial roles in the interdigitation of pavement cells. In this study, we performed quantitative analysis of cortical microtubule orientation in leaf pavement cells in Arabidopsis thaliana. We captured confocal images of cortical microtubules in cotyledon leaf epidermis expressing GFP-tubulinβ and quantitatively evaluated the microtubule orientations relative to the pavement cell growth axis using original image processing techniques. Our results showed that microtubules kept parallel orientations to the growth axis during pavement cell growth. In addition, we showed that immersion treatment of seed cotyledons in solutions containing tubulin polymerization and depolymerization inhibitors decreased pavement cell complexity. Treatment with oryzalin and colchicine inhibited the symmetric division of guard mother cells.

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'.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Quantitative ultrasound molecular imaging by modeling the binding kinetics of targeted contrast agent

NASA Astrophysics Data System (ADS)

Turco, Simona; Tardy, Isabelle; Frinking, Peter; Wijkstra, Hessel; Mischi, Massimo

2017-03-01

Ultrasound molecular imaging (USMI) is an emerging technique to monitor diseases at the molecular level by the use of novel targeted ultrasound contrast agents (tUCA). These consist of microbubbles functionalized with targeting ligands with high-affinity for molecular markers of specific disease processes, such as cancer-related angiogenesis. Among the molecular markers of angiogenesis, the vascular endothelial growth factor receptor 2 (VEGFR2) is recognized to play a major role. In response, the clinical-grade tUCA BR55 was recently developed, consisting of VEGFR2-targeting microbubbles which can flow through the entire circulation and accumulate where VEGFR2 is over-expressed, thus causing selective enhancement in areas of active angiogenesis. Discrimination between bound and free microbubbles is crucial to assess cancer angiogenesis. Currently, this is done non-quantitatively by looking at the late enhancement, about 10 min after injection, or by calculation of the differential targeted enhancement, requiring the application of a high-pressure ultrasound (US) burst to destroy all the microbubbles in the acoustic field and isolate the signal coming only from bound microbubbles. In this work, we propose a novel method based on mathematical modeling of the binding kinetics during the tUCA first pass, thus reducing the acquisition time and with no need for a destructive US burst. Fitting time-intensity curves measured with USMI by the proposed model enables the assessment of cancer angiogenesis at both the vascular and molecular levels. This is achieved by estimation of quantitative parameters related to the microvascular architecture and microbubble binding. The proposed method was tested in 11 prostate-tumor bearing rats by performing USMI after injection of BR55, and showed good agreement with current USMI methods. The novel information provided by the proposed method, possibly combined with the current non-quantitative methods, may bring deeper insight into

Quantitative Hydrocarbon Surface Analysis

NASA Technical Reports Server (NTRS)

Douglas, Vonnie M.

2000-01-01

The elimination of ozone depleting substances, such as carbon tetrachloride, has resulted in the use of new analytical techniques for cleanliness verification and contamination sampling. The last remaining application at Rocketdyne which required a replacement technique was the quantitative analysis of hydrocarbons by infrared spectrometry. This application, which previously utilized carbon tetrachloride, was successfully modified using the SOC-400, a compact portable FTIR manufactured by Surface Optics Corporation. This instrument can quantitatively measure and identify hydrocarbons from solvent flush of hardware as well as directly analyze the surface of metallic components without the use of ozone depleting chemicals. Several sampling accessories are utilized to perform analysis for various applications.

Multivariate Quantitative Chemical Analysis

NASA Technical Reports Server (NTRS)

Kinchen, David G.; Capezza, Mary

1995-01-01

Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Global quantitative analysis of phosphorylation underlying phencyclidine signaling and sensorimotor gating in the prefrontal cortex.

PubMed

McClatchy, D B; Savas, J N; Martínez-Bartolomé, S; Park, S K; Maher, P; Powell, S B; Yates, J R

2016-02-01

Prepulse inhibition (PPI) is an example of sensorimotor gating and deficits in PPI have been demonstrated in schizophrenia patients. Phencyclidine (PCP) suppression of PPI in animals has been studied to elucidate the pathological elements of schizophrenia. However, the molecular mechanisms underlying PCP treatment or PPI in the brain are still poorly understood. In this study, quantitative phosphoproteomic analysis was performed on the prefrontal cortex from rats that were subjected to PPI after being systemically injected with PCP or saline. PCP downregulated phosphorylation events were significantly enriched in proteins associated with long-term potentiation (LTP). Importantly, this data set identifies functionally novel phosphorylation sites on known LTP-associated signaling molecules. In addition, mutagenesis of a significantly altered phosphorylation site on xCT (SLC7A11), the light chain of system xc-, the cystine/glutamate antiporter, suggests that PCP also regulates the activity of this protein. Finally, new insights were also derived on PPI signaling independent of PCP treatment. This is the first quantitative phosphorylation proteomic analysis providing new molecular insights into sensorimotor gating.

Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study.

PubMed

Hruska, Carrie B; Geske, Jennifer R; Swanson, Tiffinee N; Mammel, Alyssa N; Lake, David S; Manduca, Armando; Conners, Amy Lynn; Whaley, Dana H; Scott, Christopher G; Carter, Rickey E; Rhodes, Deborah J; O'Connor, Michael K; Vachon, Celine M

2018-06-05

Background parenchymal uptake (BPU), which refers to the level of Tc-99m sestamibi uptake within normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor, independent of mammographic density. Prior analyses have used subjective categories to describe BPU. We evaluate a new quantitative method for assessing BPU by testing its reproducibility, comparing quantitative results with previously established subjective BPU categories, and determining the association of quantitative BPU with breast cancer risk. Two nonradiologist operators independently performed region-of-interest analysis on MBI images viewed in conjunction with corresponding digital mammograms. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat. Operator agreement and the correlation of quantitative BPU measures with subjective BPU categories assessed by expert radiologists were determined. Percent density on mammograms was estimated using Cumulus. The association of quantitative BPU with breast cancer (per one unit BPU) was examined within an established case-control study of 62 incident breast cancer cases and 177 matched controls. Quantitative BPU ranged from 0.4 to 3.2 across all subjects and was on average higher in cases compared to controls (1.4 versus 1.2, p < 0.007 for both operators). Quantitative BPU was strongly correlated with subjective BPU categories (Spearman's r = 0.59 to 0.69, p < 0.0001, for each paired combination of two operators and two radiologists). Interoperator and intraoperator agreement in the quantitative BPU measure, assessed by intraclass correlation, was 0.92 and 0.98, respectively. Quantitative BPU measures showed either no correlation or weak negative correlation with mammographic percent density. In a model adjusted for body mass index and percent density, higher quantitative BPU was

iTRAQ-Based Quantitative Proteomic Analysis of the Initiation of Head Regeneration in Planarians.

PubMed

Geng, Xiaofang; Wang, Gaiping; Qin, Yanli; Zang, Xiayan; Li, Pengfei; Geng, Zhi; Xue, Deming; Dong, Zimei; Ma, Kexue; Chen, Guangwen; Xu, Cunshuan

2015-01-01

The planarian Dugesia japonica has amazing ability to regenerate a head from the anterior ends of the amputated stump with maintenance of the original anterior-posterior polarity. Although planarians present an attractive system for molecular investigation of regeneration and research has focused on clarifying the molecular mechanism of regeneration initiation in planarians at transcriptional level, but the initiation mechanism of planarian head regeneration (PHR) remains unclear at the protein level. Here, a global analysis of proteome dynamics during the early stage of PHR was performed using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy, and our data are available via ProteomeXchange with identifier PXD002100. The results showed that 162 proteins were differentially expressed at 2 h and 6 h following amputation. Furthermore, the analysis of expression patterns and functional enrichment of the differentially expressed proteins showed that proteins involved in muscle contraction, oxidation reduction and protein synthesis were up-regulated in the initiation of PHR. Moreover, ingenuity pathway analysis showed that predominant signaling pathways such as ILK, calcium, EIF2 and mTOR signaling which were associated with cell migration, cell proliferation and protein synthesis were likely to be involved in the initiation of PHR. The results for the first time demonstrated that muscle contraction and ILK signaling might played important roles in the initiation of PHR at the global protein level. The findings of this research provide a molecular basis for further unraveling the mechanism of head regeneration initiation in planarians.

Quantitative Structure-Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I-Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis.

PubMed

Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou

2018-03-28

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

PubMed Central

Blackiston, Douglas; Shomrat, Tal; Nicolas, Cindy L.; Granata, Christopher; Levin, Michael

2010-01-01

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science. PMID:21179424

Congruent climate-related genecological responses from molecular markers and quantitative traits for western white pine (Pinus monticola)

Treesearch

Bryce A. Richardson; Gerald E. Rehfeldt; Mee-Sook Kim

2009-01-01

Analyses of molecular and quantitative genetic data demonstrate the existence of congruent climate-related patterns in western white pine (Pinus monticola). Two independent studies allowed comparisons of amplified fragment length polymorphism (AFLP) markers with quantitative variation in adaptive traits. Principal component analyses...

Chiral Analysis of Isopulegol by Fourier Transform Molecular Rotational Spectroscopy

NASA Astrophysics Data System (ADS)

Evangelisti, Luca; Seifert, Nathan A.; Spada, Lorenzo; Pate, Brooks

2016-06-01

Chiral analysis on molecules with multiple chiral centers can be performed using pulsed-jet Fourier transform rotational spectroscopy. This analysis includes quantitative measurement of diastereomer products and, with the three wave mixing methods developed by Patterson, Schnell, and Doyle (Nature 497, 475-477 (2013)), quantitative determination of the enantiomeric excess of each diastereomer. The high resolution features enable to perform the analysis directly on complex samples without the need for chromatographic separation. Isopulegol has been chosen to show the capabilities of Fourier transform rotational spectroscopy for chiral analysis. Broadband rotational spectroscopy produces spectra with signal-to-noise ratio exceeding 1000:1. The ability to identify low-abundance (0.1-1%) diastereomers in the sample will be described. Methods to rapidly identify rotational spectra from isotopologues at natural abundance will be shown and the molecular structures obtained from this analysis will be compared to theory. The role that quantum chemistry calculations play in identifying structural minima and estimating their spectroscopic properties to aid spectral analysis will be described. Finally, the implementation of three wave mixing techniques to measure the enantiomeric excess of each diastereomer and determine the absolute configuration of the enantiomer in excess will be described.

Quantitative Analysis of Food and Feed Samples with Droplet Digital PCR

PubMed Central

Morisset, Dany; Štebih, Dejan; Milavec, Mojca; Gruden, Kristina; Žel, Jana

2013-01-01

In this study, the applicability of droplet digital PCR (ddPCR) for routine analysis in food and feed samples was demonstrated with the quantification of genetically modified organisms (GMOs). Real-time quantitative polymerase chain reaction (qPCR) is currently used for quantitative molecular analysis of the presence of GMOs in products. However, its use is limited for detecting and quantifying very small numbers of DNA targets, as in some complex food and feed matrices. Using ddPCR duplex assay, we have measured the absolute numbers of MON810 transgene and hmg maize reference gene copies in DNA samples. Key performance parameters of the assay were determined. The ddPCR system is shown to offer precise absolute and relative quantification of targets, without the need for calibration curves. The sensitivity (five target DNA copies) of the ddPCR assay compares well with those of individual qPCR assays and of the chamber digital PCR (cdPCR) approach. It offers a dynamic range over four orders of magnitude, greater than that of cdPCR. Moreover, when compared to qPCR, the ddPCR assay showed better repeatability at low target concentrations and a greater tolerance to inhibitors. Finally, ddPCR throughput and cost are advantageous relative to those of qPCR for routine GMO quantification. It is thus concluded that ddPCR technology can be applied for routine quantification of GMOs, or any other domain where quantitative analysis of food and feed samples is needed. PMID:23658750

Real-Time Quantitative Analysis of Valproic Acid in Exhaled Breath by Low Temperature Plasma Ionization Mass Spectrometry

NASA Astrophysics Data System (ADS)

Gong, Xiaoxia; Shi, Songyue; Gamez, Gerardo

2017-04-01

Real-time analysis of exhaled human breath is a rapidly growing field in analytical science and has great potential for rapid and noninvasive clinical diagnosis and drug monitoring. In the present study, an LTP-MS method was developed for real-time, in-vivo and quantitative analysis of γ-valprolactone, a metabolite of valproic acid (VPA), in exhaled breath without any sample pretreatment. In particular, the effect of working conditions and geometry of the LTP source on the ions of interest, protonated molecular ion at m/z 143 and ammonium adduct ion at m/z 160, were systematically characterized. Tandem mass spectrometry (MS/MS) with collision-induced dissociation (CID) was carried out in order to identify γ-valprolactone molecular ions ( m/z 143), and the key fragment ion ( m/z 97) was used for quantitation. In addition, the fragmentation of ammonium adduct ions to protonated molecular ions was performed in-source to improve the signal-to-noise ratio. At optimum conditions, signal reproducibility with an RSD of 8% was achieved. The concentration of γ-valprolactone in exhaled breath was determined for the first time to be 4.83 (±0.32) ng/L by using standard addition method. Also, a calibration curve was obtained with a linear range from 0.7 to 22.5 ng/L, and the limit of detection was 0.18 ng/L for γ-valprolactone in standard gas samples. Our results show that LTP-MS is a powerful analytical platform with high sensitivity for quantitative analysis of volatile organic compounds in human breath, and can have potential applications in pharmacokinetics or for patient monitoring and treatment.

Are three generations of quantitative molecular methods sufficient in medical virology? Brief review.

PubMed

Clementi, Massimo; Bagnarelli, Patrizia

2015-10-01

In the last two decades, development of quantitative molecular methods has characterized the evolution of clinical virology more than any other methodological advancement. Using these methods, a great deal of studies has addressed efficiently in vivo the role of viral load, viral replication activity, and viral transcriptional profiles as correlates of disease outcome and progression, and has highlighted the physio-pathology of important virus diseases of humans. Furthermore, these studies have contributed to a better understanding of virus-host interactions and have sharply revolutionized the research strategies in basic and medical virology. In addition and importantly from a medical point of view, quantitative methods have provided a rationale for the therapeutic intervention and therapy monitoring in medically important viral diseases. Despite the advances in technology and the development of three generations of molecular methods within the last two decades (competitive PCR, real-time PCR, and digital PCR), great challenges still remain for viral testing related not only to standardization, accuracy, and precision, but also to selection of the best molecular targets for clinical use and to the identification of thresholds for risk stratification and therapeutic decisions. Future research directions, novel methods and technical improvements could be important to address these challenges.

Analysis of glycerophosphocholine molecular species as derivatives of 7-[(chlorocarbonyl)-methoxy]-4-methylcoumarin.

PubMed

Wheelan, P; Zirrolli, J A; Clay, K L

1992-01-01

A method has been developed for the analysis of derivatized diradylglycerols obtained from glycerophosphocholine (GPC) of transformed murine bone marrow-derived mast cells that provided high performance liquid chromatography (HPLC) separation of GPC subclasses and molecular species separation with on-line quantitation using UV detection. In addition, the derivatized diradylglycerol species were unequivocably identified by continuous flow fast-atom bombardment mass spectrometry. GPC was initially isolated by thin-layer chromatography (TLC), the phosphocholine group was hydrolyzed, and the resultant diradylglycerol was derivatized with 7-[(chlorocarbonyl)-methoxy]-4-methylcoumarin (CMMC). After separation of the derivatized subclasses by normal phase HPLC, the individual molecular species of the alkylacyl and diacyl subclasses were quantitated and collected during a subsequent reverse phase HPLC step. With an extinction coefficient of 14,700 l mol-1 cm-1 at a wavelength detection of 320 nm, the CMMC derivatives afforded sensitive UV detection (100 pmol) and quantitation of the molecular species. Continuous flow fast-atom bombardment mass spectrometry of the alkylacyl CMMC derivatives yielded abundant [MH]+ ions and a single fragment ion formed by loss of alkylketene from the sn-2 acyl group, [MH-(R = C = O)]+. No fragmentation of the sn-1 alkyl chain was observed. Diacyl derivatives also produced abundant [MH]+ ions plus two fragment ions arising from loss of RCOOH from each of the acyl substituents and two fragment ions from the loss of alkyketene from each acyl group. Individual molecular species substituents were assigned from these ions.

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

Quantitative analysis of pyroglutamic acid in peptides.

PubMed

Suzuki, Y; Motoi, H; Sato, K

1999-08-01

A simplified and rapid procedure for the determination of pyroglutamic acid in peptides was developed. The method involves the enzymatic cleavage of an N-terminal pyroglutamate residue using a thermostable pyroglutamate aminopeptidase and isocratic HPLC separation of the resulting enzymatic hydrolysate using a column switching technique. Pyroglutamate aminopeptidase from a thermophilic archaebacteria, Pyrococcus furiosus, cleaves N-terminal pyroglutamic acid residue independent of the molecular weight of the substrate. It cleaves more than 85% of pyroglutamate from peptides whose molecular weight ranges from 362.4 to 4599.4 Da. Thus, a new method is presented that quantitatively estimates N-terminal pyroglutamic acid residue in peptides.

A new molecular diagnostic tool for quantitatively detecting and genotyping “Candidatus Liberibacter species”

USDA-ARS?s Scientific Manuscript database

A new molecular diagnostic method was developed for quantitative detection of “Candidatus Liberibacter” species associated with citrus Huanglongbing (“Ca. Liberibacter asiaticus”, “Ca. Liberibacter africanus” and “Ca. Liberibacter americanus”) and potato zebra chip disorder (“Ca. Liberibacter solana...

A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure

PubMed Central

Liu, Fengping; Cao, Chenzhong; Cheng, Bin

2011-01-01

A quantitative structure–property relationship (QSPR) analysis of aliphatic alcohols is presented. Four physicochemical properties were studied: boiling point (BP), n-octanol–water partition coefficient (lg POW), water solubility (lg W) and the chromatographic retention indices (RI) on different polar stationary phases. In order to investigate the quantitative structure–property relationship of aliphatic alcohols, the molecular structure ROH is divided into two parts, R and OH to generate structural parameter. It was proposed that the property is affected by three main factors for aliphatic alcohols, alkyl group R, substituted group OH, and interaction between R and OH. On the basis of the polarizability effect index (PEI), previously developed by Cao, the novel molecular polarizability effect index (MPEI) combined with odd-even index (OEI), the sum eigenvalues of bond-connecting matrix (SX1CH) previously developed in our team, were used to predict the property of aliphatic alcohols. The sets of molecular descriptors were derived directly from the structure of the compounds based on graph theory. QSPR models were generated using only calculated descriptors and multiple linear regression techniques. These QSPR models showed high values of multiple correlation coefficient (R > 0.99) and Fisher-ratio statistics. The leave-one-out cross-validation demonstrated the final models to be statistically significant and reliable. PMID:21731451

Molecular basis of quantitative structure-properties relationships (QSPR): a quantum similarity approach.

PubMed

Ponec, R; Amat, L; Carbó-Dorca, R

1999-05-01

Since the dawn of quantitative structure-properties relationships (QSPR), empirical parameters related to structural, electronic and hydrophobic molecular properties have been used as molecular descriptors to determine such relationships. Among all these parameters, Hammett sigma constants and the logarithm of the octanol-water partition coefficient, log P, have been massively employed in QSPR studies. In the present paper, a new molecular descriptor, based on quantum similarity measures (QSM), is proposed as a general substitute of these empirical parameters. This work continues previous analyses related to the use of QSM to QSPR, introducing molecular quantum self-similarity measures (MQS-SM) as a single working parameter in some cases. The use of MQS-SM as a molecular descriptor is first confirmed from the correlation with the aforementioned empirical parameters. The Hammett equation has been examined using MQS-SM for a series of substituted carboxylic acids. Then, for a series of aliphatic alcohols and acetic acid esters, log P values have been correlated with the self-similarity measure between density functions in water and octanol of a given molecule. And finally, some examples and applications of MQS-SM to determine QSAR are presented. In all studied cases MQS-SM appeared to be excellent molecular descriptors usable in general QSPR applications of chemical interest.

Molecular basis of quantitative structure-properties relationships (QSPR): A quantum similarity approach

NASA Astrophysics Data System (ADS)

Ponec, Robert; Amat, Lluís; Carbó-dorca, Ramon

1999-05-01

Since the dawn of quantitative structure-properties relationships (QSPR), empirical parameters related to structural, electronic and hydrophobic molecular properties have been used as molecular descriptors to determine such relationships. Among all these parameters, Hammett σ constants and the logarithm of the octanol- water partition coefficient, log P, have been massively employed in QSPR studies. In the present paper, a new molecular descriptor, based on quantum similarity measures (QSM), is proposed as a general substitute of these empirical parameters. This work continues previous analyses related to the use of QSM to QSPR, introducing molecular quantum self-similarity measures (MQS-SM) as a single working parameter in some cases. The use of MQS-SM as a molecular descriptor is first confirmed from the correlation with the aforementioned empirical parameters. The Hammett equation has been examined using MQS-SM for a series of substituted carboxylic acids. Then, for a series of aliphatic alcohols and acetic acid esters, log P values have been correlated with the self-similarity measure between density functions in water and octanol of a given molecule. And finally, some examples and applications of MQS-SM to determine QSAR are presented. In all studied cases MQS-SM appeared to be excellent molecular descriptors usable in general QSPR applications of chemical interest.

Energy Dispersive Spectrometry and Quantitative Analysis Short Course. Introduction to X-ray Energy Dispersive Spectrometry and Quantitative Analysis

NASA Technical Reports Server (NTRS)

Carpenter, Paul; Curreri, Peter A. (Technical Monitor)

2002-01-01

This course will cover practical applications of the energy-dispersive spectrometer (EDS) to x-ray microanalysis. Topics covered will include detector technology, advances in pulse processing, resolution and performance monitoring, detector modeling, peak deconvolution and fitting, qualitative and quantitative analysis, compositional mapping, and standards. An emphasis will be placed on use of the EDS for quantitative analysis, with discussion of typical problems encountered in the analysis of a wide range of materials and sample geometries.

Quantitative interaction analysis permits molecular insights into functional NOX4 NADPH oxidase heterodimer assembly.

PubMed

O'Neill, Sharon; Mathis, Magalie; Kovačič, Lidija; Zhang, Suisheng; Reinhardt, Jürgen; Scholz, Dimitri; Schopfer, Ulrich; Bouhelal, Rochdi; Knaus, Ulla G

2018-06-08

Protein-protein interactions critically regulate many biological systems, but quantifying functional assembly of multipass membrane complexes in their native context is still challenging. Here, we combined modeling-assisted protein modification and information from human disease variants with a minimal-size fusion tag, split-luciferase-based approach to probe assembly of the NADPH oxidase 4 (NOX4)-p22 phox enzyme, an integral membrane complex with unresolved structure, which is required for electron transfer and generation of reactive oxygen species (ROS). Integrated analyses of heterodimerization, trafficking, and catalytic activity identified determinants for the NOX4-p22 phox interaction, such as heme incorporation into NOX4 and hot spot residues in transmembrane domains 1 and 4 in p22 phox Moreover, their effect on NOX4 maturation and ROS generation was analyzed. We propose that this reversible and quantitative protein-protein interaction technique with its small split-fragment approach will provide a protein engineering and discovery tool not only for NOX research, but also for other intricate membrane protein complexes, and may thereby facilitate new drug discovery strategies for managing NOX-associated diseases. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Carbohydrates and phenols as quantitative molecular vegetation proxies in peats

NASA Astrophysics Data System (ADS)

Kaiser, K.; Benner, R. H.

2012-12-01

Vegetation in peatlands is intricately linked to local environmental conditions and climate. Here we use chemical analyses of carbohydrates and phenols to reconstruct paleovegetation in peat cores collected from 56.8°N (SIB04), 58.4°N (SIB06), 63.8°N (G137) and 66.5°N (E113) in the Western Siberian Lowland. Lignin phenols (vanillyl and syringyl phenols) were sensitive biomarkers for vascular plant contributions and provided additional information on the relative contributions of angiosperm and gymnosperm plants. Specific neutral sugar compositions allowed identification of sphagnum mosses, sedges (Cyperaceae) and lichens. Hydroxyphenols released by CuO oxidation were useful tracers of sphagnum moss contributions. The three independent molecular proxies were calibrated with a diverse group of peat-forming plants to yield quantitative estimates (%C) of vascular plant, sphagnum moss and lichen contributions in peat core samples. Correlation analysis indicated the three molecular proxies produced fairly similar results for paleovegetation compositions, generally within the error interval of each approach (≤26%). The lignin-based method generally lead to higher estimates of vascular plant vegetation. Several significant deviations were also observed due to different reactivities of carbohydrate and phenolic polymers during peat decomposition. Rapid vegetation changes on timescales of 50-200 years were observed in the southern cores SIB04 and SIB06 over the last 2000 years. Vanillyl and syringyl phenol ratios indicated these vegetation changes were largely due to varying inputs of angiosperm and gymnosperm plants. The northern permafrost cores G137 and E113 showed a more stable development. Lichens briefly replaced sphagnum mosses and vascular plants in both of these cores. Shifts in vegetation did not correlate well with Northern hemisphere climate variability over the last 2000 years. This suggested that direct climate forcing of peatland dynamics was overridden

Using Qualitative Hazard Analysis to Guide Quantitative Safety Analysis

NASA Technical Reports Server (NTRS)

Shortle, J. F.; Allocco, M.

2005-01-01

Quantitative methods can be beneficial in many types of safety investigations. However, there are many difficulties in using quantitative m ethods. Far example, there may be little relevant data available. This paper proposes a framework for using quantitative hazard analysis to prioritize hazard scenarios most suitable for quantitative mziysis. The framework first categorizes hazard scenarios by severity and likelihood. We then propose another metric "modeling difficulty" that desc ribes the complexity in modeling a given hazard scenario quantitatively. The combined metrics of severity, likelihood, and modeling difficu lty help to prioritize hazard scenarios for which quantitative analys is should be applied. We have applied this methodology to proposed concepts of operations for reduced wake separation for airplane operatio ns at closely spaced parallel runways.

Molecular Analysis of Sarcoidosis Granulomas Reveals Antimicrobial Targets

PubMed Central

Celada, Lindsay J.; Polosukhin, Vasiliy V.; Atkinson, James B.; Drake, Wonder P.

2016-01-01

Sarcoidosis is a granulomatous disease of unknown cause. Prior molecular and immunologic studies have confirmed the presence of mycobacterial virulence factors, such as catalase peroxidase and superoxide dismutase A, within sarcoidosis granulomas. Molecular analysis of granulomas can identify targets of known antibiotics classes. Currently, major antibiotics are directed against DNA synthesis, protein synthesis, and cell wall formation. We conducted molecular analysis of 40 sarcoidosis diagnostic specimens and compared them with 33 disease control specimens for the presence of mycobacterial genes that encode antibiotic targets. We assessed for genes involved in DNA synthesis (DNA gyrase A [gyrA] and DNA gyrase B), protein synthesis (RNA polymerase subunit β), cell wall synthesis (embCAB operon and enoyl reductase), and catalase peroxidase. Immunohistochemical analysis was conducted to investigate the locale of mycobacterial genes such as gyrA within 12 sarcoidosis specimens and 12 disease controls. Mycobacterial DNA was detected in 33 of 39 sarcoidosis specimens by quantitative real-time polymerase chain reaction compared with 2 of 30 disease control specimens (P < 0.001, two-tailed Fisher’s test). Twenty of 39 were positive for three or more mycobacterial genes, compared with 1 of 30 control specimens (P < 0.001, two-tailed Fisher’s test). Immunohistochemistry analysis localized mycobacterial gyrA nucleic acids to sites of granuloma formation in 9 of 12 sarcoidosis specimens compared with 1 of 12 disease controls (P < 0.01). Microbial genes encoding enzymes that can be targeted by currently available antimycobacterial antibiotics are present in sarcoidosis specimens and localize to sites of granulomatous inflammation. Use of antimicrobials directed against target enzymes may be an innovative treatment alternative. PMID:26807608

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer.

PubMed

Shah, Anup D; Inder, Kerry L; Shah, Alok K; Cristino, Alexandre S; McKie, Arthur B; Gabra, Hani; Davis, Melissa J; Hill, Michelle M

2016-10-07

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

Quantitative Data Analysis--In the Graduate Curriculum

ERIC Educational Resources Information Center

Albers, Michael J.

2017-01-01

A quantitative research study collects numerical data that must be analyzed to help draw the study's conclusions. Teaching quantitative data analysis is not teaching number crunching, but teaching a way of critical thinking for how to analyze the data. The goal of data analysis is to reveal the underlying patterns, trends, and relationships of a…

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

PubMed Central

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Quantitative Impact of Plasma Clearance and Down-regulation on GLP-1 Receptor Molecular Imaging.

PubMed

Zhang, Liang; Thurber, Greg M

2016-02-01

Quantitative molecular imaging of beta cell mass (BCM) would enable early detection and treatment monitoring of type 1 diabetes. The glucagon-like peptide-1 (GLP-1) receptor is an attractive target due to its beta cell specificity and cell surface location. We quantitatively investigated the impact of plasma clearance and receptor internalization on targeting efficiency in healthy B6 mice. Four exenatide-based probes were synthesized that varied in molecular weight, binding affinity, and plasma clearance. The GLP-1 receptor internalization rate and in vivo receptor expression were quantified. Receptor internalization (54,000 receptors/cell in vivo) decreased significantly within minutes, reducing the benefit of a slower-clearing agent. The multimers and albumin binding probes had higher kidney and liver uptake, respectively. Slow plasma clearance is beneficial for GLP-1 receptor peptide therapeutics. However, for exendin-based imaging of islets, down-regulation of the GLP-1 receptor and non-specific background uptake result in a higher target-to-background ratio for fast-clearing agents.

Quantitative Impact of Plasma Clearance and Down-regulation on GLP-1 Receptor Molecular Imaging

PubMed Central

Zhang, Liang; Thurber, Greg M.

2016-01-01

Purpose Quantitative molecular imaging of beta cell mass (BCM) would enable early detection and treatment monitoring of type-1 diabetes. The glucagon like peptide-1 (GLP-1) receptor is an attractive target due to its beta cell specificity and cell surface location. We quantitatively investigated the impact of plasma clearance and receptor internalization on targeting efficiency in healthy B6 mice. Procedures Four exenatide-based probes were synthesized that varied in molecular weight, binding affinity, and plasma clearance. The GLP-1 receptor internalization rate and in vivo receptor expression were quantified. Results Receptor internalization (54,000 receptors/cell in vivo) decreased significantly within minutes, reducing the benefit of a slower clearing agent. The multimers and albumin binding probes had higher kidney and liver uptake, respectively. Conclusions Slow plasma clearance is beneficial for GLP-1 receptor peptide therapeutics. However, for exendin-based imaging of islets, downregulation of the GLP-1 receptor and non-specific background uptake result in a higher TBR for fast-clearing agents. PMID:26194012

Respiromics - An integrative analysis linking mitochondrial bioenergetics to molecular signatures.

PubMed

Walheim, Ellen; Wiśniewski, Jacek R; Jastroch, Martin

2018-03-01

Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Here, we combine quantitative mitochondrial respirometry (Seahorse technology) and proteomics (LC-MS/MS-based total protein approach) to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO) in the liver. The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Our integrative analysis, that we dubbed "respiromics", represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

iTRAQ-based quantitative proteomics analysis of molecular mechanisms associated with Bombyx mori (Lepidoptera) larval midgut response to BmNPV in susceptible and near-isogenic strains.

PubMed

Yu, Haizhong; Wang, Xueyang; Xu, Jiaping; Ma, Yan; Zhang, Shangzhi; Yu, Dong; Fei, Dongqiong; Muhammad, Azharuddin

2017-08-08

Bombyx mori nucleopolyhedrovirus (BmNPV) has been identified as a major pathogen responsible for severe economic loss. Most silkworm strains are susceptible to BmNPV, with only a few highly resistant strains thus far identified. Here we investigated the molecular basis of silkworm resistance to BmNPV using susceptible (the recurrent parent P50) and resistant (near-isogenic line BC9) strains and a combination of iTRAQ-based quantitative proteomics, reverse-transcription quantitative PCR and Western blotting. By comparing the proteomes of infected and non-infected P50 and BC9 silkworms, we identified 793 differentially expressed proteins (DEPs). By gene ontology and KEGG enrichment analyses, we found that these DEPs are preferentially involved in metabolism, catalytic activity, amino sugar and nucleotide sugar metabolism and carbon metabolism. 114 (14.38%) DEPs were associated with the cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. After removing the genetic background and individual immune stress response proteins, we identified 84 DEPs were found that are potentially involved in resistance to BmNPV. Further studies showed that a serine protease was down-regulated in P50 and up-regulated in BC9 after BmNPV infection. Taken together, these results provide insights into the molecular mechanism of silkworm response to BmNPV. Bombyx mori nucleopolyhedrovirus (BmNPV) is highly pathogenic, causing serious losses in sericulture every year. However, the molecular mechanisms of BmNPV infection and host defence remain unclear. Here we combined quantitative proteomic, bioinformatics, RT-qPCR and Western blotting analyses and found that BmNPV invasion causes complex protein alterations in the larval midgut, and that these changes are related to cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. Five important differentially

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

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

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Hologram quantitative structure-activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors.

PubMed

Magalhães, Uiaran de Oliveira; Souza, Alessandra Mendonça Teles de; Albuquerque, Magaly Girão; Brito, Monique Araújo de; Bello, Murilo Lamim; Cabral, Lucio Mendes; Rodrigues, Carlos Rangel

2013-01-01

Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure-activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q (2) = 0.802, r (2) = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2-5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q (2) = 0.748, r (2) = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives.

Hologram quantitative structure–activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors

PubMed Central

de Oliveira Magalhães, Uiaran; de Souza, Alessandra Mendonça Teles; Albuquerque, Magaly Girão; de Brito, Monique Araújo; Bello, Murilo Lamim; Cabral, Lucio Mendes; Rodrigues, Carlos Rangel

2013-01-01

Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure–activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure–activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q2 = 0.802, r2 = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2–5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q2 = 0.748, r2 = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives. PMID:24039405

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Molecular galactose-galectin association in neuroblastoma cells: An unconventional tool for qualitative/quantitative screening.

PubMed

Pastorino, Fabio; Ponzoni, Mirco; Simone, Giuseppina

2017-05-01

Galectin decorates the cell membrane and forms an extracellular molecular association with galactoside units. Here, galactoside probes have been used to study galectin expression in neuroblastoma cells. The hypothesis behind this investigation has been that the molecular mechanisms by which glycans modulate neural metastatic cells involve a protein-carbohydrate association, galectin-galactose. Preliminary screening to validate the hypothesis has been performed with galactose moieties anchored to beads. The molecular association has been studied by FACS. In vitro experiments reveal the molecular binding preferences of the metastatic neuroblastoma cells. Ex vivo, the galactose probes discriminate healthy tissues. The unconventional assay in microfluidics used in this study displayed results analogous to the above (GI-LI-N cell capture efficiency overcomes IMR-32). At the point of equilibrium of shear and binding forces, the capture yield inside the chamber was measured to 60 ± 4.4% in GI-LI-N versus 40 ± 2.1% in IMR-32. Staining of the fished cells and subsequent conjugation with red beads bearing the galactose also have evidenced that microfluidics can be used to study and quantify the molecular association of galectin-galactose. Most importantly, a crucial insight for obtaining single-cell qualitative/quantitative glycome analysis has been achieved. Finally, the specificity of the assay performed in microfluidics is demonstrated by comparing GI-LI-N fishing efficiency in galactose and fucose environments. The residual adhesion to fucose confirmed the existence of receptors for this glycan and that its eventual unspecific binding (i.e. due to electrostatic interactions) is insignificant compared with the molecular binding. Identification and understanding of this mechanism of discrimination can be relevant for diagnostic monitoring and for producing probes tailored to interfere with galectin activities associated with the malignant phenotype. Besides, the given

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

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features

PubMed Central

Gangeh, Mehrdad; Tadayyon, Hadi; Sadeghi-Naini, Ali; Gandhi, Sonal; Wright, Frances C.; Slodkowska, Elzbieta; Curpen, Belinda; Tran, William; Czarnota, Gregory J.

2018-01-01

Background Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer. Methods The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times. Results Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone

Drift mobility of photo-electrons in organic molecular crystals: Quantitative comparison between theory and experiment

NASA Astrophysics Data System (ADS)

Reineker, P.; Kenkre, V. M.; Kühne, R.

1981-08-01

A quantitative comparison of a simple theoretical prediction for the drift mobility of photo-electrons in organic molecular crystals, calculated within the model of the coupled band-like and hopping motion, with experiments in napthalene of Schein et al. and Karl et al. is given.

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

Three molecular forms of atrial natriuretic peptides: quantitative analysis and biological characterization.

PubMed

Nagai-Okatani, Chiaki; Kangawa, Kenji; Minamino, Naoto

2017-07-01

Atrial natriuretic peptide (ANP) is primarily produced in the heart tissue and plays a pivotal role in maintaining cardiovascular homeostasis in endocrine and autocrine/paracrine systems and has clinical applications as a biomarker and a therapeutic agent for cardiac diseases. ANP is synthesized by atrial cardiomyocytes as a preprohormone that is processed by a signal peptidase and stored in secretory granules as a prohormone. Subsequent proteolytic processing of ANP by corin during the secretion process results in a bioactive form consisting of 28 amino acid residues. Mechanical stretch of the atrial wall and multiple humoral factors directly stimulates the transcription and secretion of ANP. Secreted ANP elicits natriuretic and diuretic effects via cyclic guanosine monophosphate produced through binding to the guanylyl cyclase-A/natriuretic peptide receptor-A. Circulating ANP is subjected to rapid clearance by a natriuretic peptide receptor-C-mediated mechanism and proteolytic degradation by neutral endopeptidase. In humans, ANP is present as three endogenous molecular forms: bioactive α-ANP, a homodimer of α-ANP designated as β-ANP, and an ANP precursor designated as proANP (also referred to as γ-ANP). The proANP and especially β-ANP, as minor forms in circulation, are notably increased in patients with cardiac diseases, suggesting the utility of monitoring the pathophysiological conditions that result in abnormal proANP processing that cannot be monitored by inactive N-terminal proANP-related fragments. Emerging plate-based sandwich immunoassays for individual quantitation of the three ANP forms enables evaluation of diagnostic implications and net ANP bioactivity. This new tool may provide further understanding in the pathophysiology of cardiac diseases. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.

Quantitative structure-activity relationship of organosulphur compounds as soybean 15-lipoxygenase inhibitors using CoMFA and CoMSIA.

PubMed

Caballero, Julio; Fernández, Michael; Coll, Deysma

2010-12-01

Three-dimensional quantitative structure-activity relationship studies were carried out on a series of 28 organosulphur compounds as 15-lipoxygenase inhibitors using comparative molecular field analysis and comparative molecular similarity indices analysis. Quantitative information on structure-activity relationships is provided for further rational development and direction of selective synthesis. All models were carried out over a training set including 22 compounds. The best comparative molecular field analysis model only included steric field and had a good Q² = 0.789. Comparative molecular similarity indices analysis overcame the comparative molecular field analysis results: the best comparative molecular similarity indices analysis model also only included steric field and had a Q² = 0.894. In addition, this model predicted adequately the compounds contained in the test set. Furthermore, plots of steric comparative molecular similarity indices analysis field allowed conclusions to be drawn for the choice of suitable inhibitors. In this sense, our model should prove useful in future 15-lipoxygenase inhibitor design studies. © 2010 John Wiley & Sons A/S.

Mapping, fine mapping, and molecular dissection of quantitative trait Loci in domestic animals.

PubMed

Georges, Michel

2007-01-01

Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

Quantitative Genetics in the Era of Molecular Genetics: Learning Abilities and Disabilities as an Example

ERIC Educational Resources Information Center

Haworth, Claire M. A.; Plomin, Robert

2010-01-01

Objective: To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples. Method: Recent twin research in the area of learning…

Quantitative Assessment of Molecular Dynamics Sampling for Flexible Systems.

PubMed

Nemec, Mike; Hoffmann, Daniel

2017-02-14

Molecular dynamics (MD) simulation is a natural method for the study of flexible molecules but at the same time is limited by the large size of the conformational space of these molecules. We ask by how much the MD sampling quality for flexible molecules can be improved by two means: the use of diverse sets of trajectories starting from different initial conformations to detect deviations between samples and sampling with enhanced methods such as accelerated MD (aMD) or scaled MD (sMD) that distort the energy landscape in controlled ways. To this end, we test the effects of these approaches on MD simulations of two flexible biomolecules in aqueous solution, Met-Enkephalin (5 amino acids) and HIV-1 gp120 V3 (a cycle of 35 amino acids). We assess the convergence of the sampling quantitatively with known, extensive measures of cluster number N c and cluster distribution entropy S c and with two new quantities, conformational overlap O conf and density overlap O dens , both conveniently ranging from 0 to 1. These new overlap measures quantify self-consistency of sampling in multitrajectory MD experiments, a necessary condition for converged sampling. A comprehensive assessment of sampling quality of MD experiments identifies the combination of diverse trajectory sets and aMD as the most efficient approach among those tested. However, analysis of O dens between conventional and aMD trajectories also reveals that we have not completely corrected aMD sampling for the distorted energy landscape. Moreover, for V3, the courses of N c and O dens indicate that much higher resources than those generally invested today will probably be needed to achieve convergence. The comparative analysis also shows that conventional MD simulations with insufficient sampling can be easily misinterpreted as being converged.

A Direct, Quantitative Connection between Molecular Dynamics Simulations and Vibrational Probe Line Shapes.

PubMed

Xu, Rosalind J; Blasiak, Bartosz; Cho, Minhaeng; Layfield, Joshua P; Londergan, Casey H

2018-05-17

A quantitative connection between molecular dynamics simulations and vibrational spectroscopy of probe-labeled systems would enable direct translation of experimental data into structural and dynamical information. To constitute this connection, all-atom molecular dynamics (MD) simulations were performed for two SCN probe sites (solvent-exposed and buried) in a calmodulin-target peptide complex. Two frequency calculation approaches with substantial nonelectrostatic components, a quantum mechanics/molecular mechanics (QM/MM)-based technique and a solvatochromic fragment potential (SolEFP) approach, were used to simulate the infrared probe line shapes. While QM/MM results disagreed with experiment, SolEFP results matched experimental frequencies and line shapes and revealed the physical and dynamic bases for the observed spectroscopic behavior. The main determinant of the CN probe frequency is the exchange repulsion between the probe and its local structural neighbors, and there is a clear dynamic explanation for the relatively broad probe line shape observed at the "buried" probe site. This methodology should be widely applicable to vibrational probes in many environments.

Quantitative analysis of comparative genomic hybridization

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

Manoir, S. du; Bentz, M.; Joos, S.

1995-01-01

Comparative genomic hybridization (CGH) is a new molecular cytogenetic method for the detection of chromosomal imbalances. Following cohybridization of DNA prepared from a sample to be studied and control DNA to normal metaphase spreads, probes are detected via different fluorochromes. The ratio of the test and control fluorescence intensities along a chromosome reflects the relative copy number of segments of a chromosome in the test genome. Quantitative evaluation of CGH experiments is required for the determination of low copy changes, e.g., monosomy or trisomy, and for the definition of the breakpoints involved in unbalanced rearrangements. In this study, a programmore » for quantitation of CGH preparations is presented. This program is based on the extraction of the fluorescence ratio profile along each chromosome, followed by averaging of individual profiles from several metaphase spreads. Objective parameters critical for quantitative evaluations were tested, and the criteria for selection of suitable CGH preparations are described. The granularity of the chromosome painting and the regional inhomogeneity of fluorescence intensities in metaphase spreads proved to be crucial parameters. The coefficient of variation of the ratio value for chromosomes in balanced state (CVBS) provides a general quality criterion for CGH experiments. Different cutoff levels (thresholds) of average fluorescence ratio values were compared for their specificity and sensitivity with regard to the detection of chromosomal imbalances. 27 refs., 15 figs., 1 tab.« less

A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

PubMed

Sahoo, Sagarika; Adhikari, Chandana; Kuanar, Minati; Mishra, Bijay K

2016-01-01

Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD). This review is a survey on the generation of the molecular descriptors and its probable applications in QSP/AR. Literatures have been collected from a wide class of research journals, citable web reports, seminar proceedings and books. The MDs were classified according to their generation. The applications of the MDs on the QSP/AR have also been reported in this review. The MDs can be classified into experimental and theoretical types, having a sub classification of the later into structural and quantum chemical descriptors. The structural parameters are derived from molecular graphs or topology of the molecules. Even the pixel of the molecular image can be used as molecular descriptor. In QSPR studies the physicochemical properties include boiling point, heat capacity, density, refractive index, molar volume, surface tension, heat of formation, octanol-water partition coefficient, solubility, chromatographic retention indices etc. Among biological activities toxicity, antimalarial activity, sensory irritant, potencies of local anesthetic, tadpole narcosis, antifungal activity, enzyme inhibiting activity are some important parameters in the QSAR studies. The classification of the MDs is mostly generic in nature. The application of the MDs in QSP/AR also has a generic link. Experimental MDs are more suitable in correlation analysis than the theoretical ones but are more expensive for generation. In advent of sophisticated computational tools and experimental design proliferation of MDs is inevitable, but for a highly optimized MD, studies on generation of MD is an unending

Dual color fluorescence quantitative detection of specific single-stranded DNA with molecular beacons and nucleic acid dye SYBR Green I.

PubMed

Xiang, Dong-Shan; Zhou, Guo-Hua; Luo, Ming; Ji, Xing-Hu; He, Zhi-Ke

2012-08-21

We have developed a dual color fluorescence quantitative detection method for specific single-stranded DNA with molecular beacons (MBs) and nucleic acid dye SYBR Green I by synchronous scanning fluorescence spectrometry. It is demonstrated by a reverse-transcription oligonucleotide sequence (target DNA, 33 bases) of RNA fragment of human immunodeficiency virus (HIV) as a model system. In the absence of target DNA, the MBs are in the stem-closed state, the fluorescence of 5-carboxy-X-rhodamine (ROX) is quenched by black hole quencher-2 (BHQ-2), and the interaction between SYBR Green I and the MBs is very weak. At this time the fluorescence signals of ROX and SYBR Green I are all very weak. In the presence of target DNA, MBs hybridize with target DNA and form a double-strand structure, the fluorophore ROX is separated from the quencher BHQ-2, and the fluorescence of ROX recovers. At the same time, SYBR Green I binds to hybridized dsDNA, whose fluorescence intensity is significantly enhanced. Thus, dual color fluorescence quantitative detection for the target DNA can be realized by synchronous scanning fluorescence spectrometry. In this strategy, the fluorescence signal of SYBR Green I is far larger than that of ROX, so the quantitative analysis of target DNA with the fluorescence intensity of SYBR Green I can significantly improve the detection sensitivity. In addition, the false-positive signals of MBs do not affect the fluorescence signals of nucleic acid dye SYBR Green I. Thereby, in the analysis of complex samples, quantitative analysis of target DNA with SYBR Green I can avoid the false-positive signals of MBs and improve the detection accuracy.

Tracking and Motion Analysis of Crack Propagations in Crystals for Molecular Dynamics

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

Tsap, L V; Duchaineau, M; Goldgof, D B

2001-05-14

This paper presents a quantitative analysis for a discovery in molecular dynamics. Recent simulations have shown that velocities of crack propagations in crystals under certain conditions can become supersonic, which is contrary to classical physics. In this research, they present a framework for tracking and motion analysis of crack propagations in crystals. It includes line segment extraction based on Canny edge maps, feature selection based on physical properties, and subsequent tracking of primary and secondary wavefronts. This tracking is completely automated; it runs in real time on three 834-image sequences using forty 250 MHZ processors. Results supporting physical observations aremore » presented in terms of both feature tracking and velocity analysis.« less

[Quantitative data analysis for live imaging of bone.

PubMed

Seno, Shigeto

Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

Non-Invasive Early Detection and Molecular Analysis of Low X-ray Dose Effects in the Lens

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

Goldstein, Lee

This is the Final Progress Report for DOE-funded research project DE-PS02-08ER08-01 titled “Non-Invasive Early Detection and Molecular Analysis of Low X-ray Dose Effects in the Lens”. The project focuses on the effects of low-linear energy transfer (LET) radiation on the ocular lens. The lens is an exquisitely radiosensitive tissue with a highly-ordered molecular structure that is amenable to non-invasive optical study from the periphery. These merits point to the lens as an ideal target for laser-based molecular biodosimetry (MBD). Following exposure to different types of ionizing radiations, the lens demonstrates molecular changes (e.g., oxidation, racemization, crosslinkage, truncation, aggregation, etc.) thatmore » impact the structure and function of the long-lived proteins in the cytosol of lens fiber cells. The vast majority of proteins in the lens comprise the highly-ordered crystallins. These highly conserved lens proteins are amongst the most concentrated and stable in the body. Once synthesized, the crystallins are retained in the fiber cell cytoplasm for life. Taken together, these properties point to the lens as an ideal system for quantitative in vivo MBD assessment using quasi-elastic light scattering (QLS) analysis. In this project, we deploy a purpose-designed non-invasive infrared laser QLS instrument as a quantitative tool for longitudinal assessment of pre-cataractous molecular changes in the lenses of living mice exposed to low-dose low-LET radiation compared to non-irradiated sham controls. We hypothesize that radiation exposure will induce dose-dependent changes in the molecular structure of matrix proteins in the lens. Mechanistic assays to ascertain radiation-induced molecular changes in the lens focus on protein aggregation and gene/protein expression patterns. We anticipate that this study will contribute to our understanding of early molecular changes associated with radiation-induced tissue pathology. This study also affords

Quantitative implementation of the endogenous molecular-cellular network hypothesis in hepatocellular carcinoma.

PubMed

Wang, Gaowei; Zhu, Xiaomei; Gu, Jianren; Ao, Ping

2014-06-06

A quantitative hypothesis for cancer genesis and progression-the endogenous molecular-cellular network hypothesis, intended to include both genetic and epigenetic causes of cancer-has been proposed recently. Using this hypothesis, here we address the molecular basis for maintaining normal liver and hepatocellular carcinoma (HCC), and the potential strategy to cure or relieve HCC. First, we elaborate the basic assumptions of the hypothesis and establish a core working network of HCC according to the hypothesis. Second, we quantify the working network by a nonlinear dynamical system. We show that the working network reproduces the main known features of normal liver and HCC at both the modular and molecular levels. Lastly, the validated working network reveals that (i) specific positive feedback loops are responsible for the maintenance of normal liver and HCC; (ii) inhibiting proliferation and inflammation-related positive feedback loops and simultaneously inducing a liver-specific positive feedback loop is predicated as a potential strategy to cure or relieve HCC; and (iii) the genesis and regression of HCC are asymmetric. In light of the characteristic properties of the nonlinear dynamical system, we demonstrate that positive feedback loops must exist as a simple and general molecular basis for the maintenance of heritable phenotypes, such as normal liver and HCC, and regulating the positive feedback loops directly or indirectly provides potential strategies to cure or relieve HCC.

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

Quantitative proteomic analysis of human testis reveals system-wide molecular and cellular pathways associated with non-obstructive azoospermia.

PubMed

Alikhani, Mehdi; Mirzaei, Mehdi; Sabbaghian, Marjan; Parsamatin, Pouria; Karamzadeh, Razieh; Adib, Samane; Sodeifi, Niloofar; Gilani, Mohammad Ali Sadighi; Zabet-Moghaddam, Masoud; Parker, Lindsay; Wu, Yunqi; Gupta, Vivek; Haynes, Paul A; Gourabi, Hamid; Baharvand, Hossein; Salekdeh, Ghasem Hosseini

2017-06-06

Male infertility accounts for half of the infertility problems experienced by couples. Azoospermia, having no measurable level of sperm in seminal fluid, is one of the known conditions resulting in male infertility. In order to elucidate the complex molecular mechanisms causing male azoospermia, label-free quantitative shotgun proteomics was carried out on testicular tissue specimens from patients with obstructive azoospermia and non-obstructive azoospermia, including maturation arrest (MA) and Sertoli cell only syndrome (SCOS). The abundance of 520 proteins was significantly changed across three groups of samples. We were able to identify several functional biological pathways enriched in azoospermia samples and confirm selected differentially abundant proteins, using multiple histological methods. The results revealed that cell cycle and proteolysis, and RNA splicing were the most significant biological processes impaired by the substantial suppression of proteins related to the aforementioned categories in SCOS tissues. In the MA patient testes, generation of precursor metabolites and energy as well as oxidation-reduction were the most significantly altered processes. Novel candidate proteins identified in this study include key transcription factors, many of which have not previously been shown to be associated with azoospermia. Our findings can provide substantial insights into the molecular regulation of spermatogenesis and human reproduction. The obtained data showed a drastic suppression of proteins involved in spliceosome, cell cycle and proteasome proteins, as well as energy and metabolic production in Sertoli cell only syndrome testis tissue, and to a lesser extent in maturation arrest samples. Moreover, we identified new transcription factors that are highly down-regulated in SCOS and MA patients, thus helping to understand the molecular complexity of spermatogenesis in male infertility. Our findings provide novel candidate protein targets associated

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

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.

Quantitative molecular characterization of bovine vitreous and lens with non-invasive dynamic light scattering

NASA Technical Reports Server (NTRS)

Ansari, R. R.; Suh, K. I.; Dunker, S.; Kitaya, N.; Sebag, J.

2001-01-01

The non-invasive technique of dynamic light scattering (DLS) was used to quantitatively characterize vitreous and lens structure on a molecular level by measuring the sizes of the predominant particles and mapping the three-dimensional topographic distribution of these structural macromolecules in three spatial dimensions. The results of DLS measurements in five fresh adult bovine eyes were compared to DLS measurements in model solutions of hyaluronan (HA) and collagen (Coll). In the bovine eyes DLS measurements were obtained from excised samples of gel and liquid vitreous and compared to the model solutions. Measurements in whole vitreous were obtained at multiple points posterior to the lens to generate a three-dimensional 'map' of molecular structure. The macromolecule distribution in bovine lens was similarly characterized.In each bovine vitreous (Bo Vit) specimen, DLS predominantly detected two distinct particles, which differed in diffusion properties and hence size. Comparisons with model vitreous solutions demonstrated that these most likely corresponded to the Coll and HA components of vitreous. Three-dimensional mapping of Bo Vit found heterogeneity throughout the vitreous body, with different particle size distributions for Coll and HA at different loci. In contrast, the three-dimensional distribution of lens macromolecules was more homogeneous. Thus, the non-invasive DLS technique can quantitate the average sizes of vitreous and lens macromolecules and map their three-dimensional distribution. This method to assess quantitatively the macromolecular structure of vitreous and lens should be useful for clinical as well as experimental applications in health and disease. Copyright 2001 Academic Press.

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/.

Quantitative performance characterization of three-dimensional noncontact fluorescence molecular tomography

NASA Astrophysics Data System (ADS)

Favicchio, Rosy; Psycharakis, Stylianos; Schönig, Kai; Bartsch, Dusan; Mamalaki, Clio; Papamatheakis, Joseph; Ripoll, Jorge; Zacharakis, Giannis

2016-02-01

Fluorescent proteins and dyes are routine tools for biological research to describe the behavior of genes, proteins, and cells, as well as more complex physiological dynamics such as vessel permeability and pharmacokinetics. The use of these probes in whole body in vivo imaging would allow extending the range and scope of current biomedical applications and would be of great interest. In order to comply with a wide variety of application demands, in vivo imaging platform requirements span from wide spectral coverage to precise quantification capabilities. Fluorescence molecular tomography (FMT) detects and reconstructs in three dimensions the distribution of a fluorophore in vivo. Noncontact FMT allows fast scanning of an excitation source and noninvasive measurement of emitted fluorescent light using a virtual array detector operating in free space. Here, a rigorous process is defined that fully characterizes the performance of a custom-built horizontal noncontact FMT setup. Dynamic range, sensitivity, and quantitative accuracy across the visible spectrum were evaluated using fluorophores with emissions between 520 and 660 nm. These results demonstrate that high-performance quantitative three-dimensional visible light FMT allowed the detection of challenging mesenteric lymph nodes in vivo and the comparison of spectrally distinct fluorescent reporters in cell culture.

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

PubMed Central

de la Fuente, Ildefonso Martínez

2010-01-01

One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

Structures of glycans bound to receptors from saturation transfer difference (STD) NMR spectroscopy: quantitative analysis by using CORCEMA-ST.

PubMed

Enríquez-Navas, Pedro M; Guzzi, Cinzia; Muñoz-García, Juan C; Nieto, Pedro M; Angulo, Jesús

2015-01-01

Glycan-receptor interactions are of fundamental relevance for a large number of biological processes, and their kinetics properties (medium/weak binding affinities) make them appropriated to be studied by ligand observed NMR techniques, among which saturation transfer difference (STD) NMR spectroscopy has been shown to be a very robust and powerful approach. The quantitative analysis of the results from a STD NMR study of a glycan-receptor interaction is essential to be able to translate the resulting spectral intensities into a 3D molecular model of the complex. This chapter describes how to carry out such a quantitative analysis by means of the Complete Relaxation and Conformational Exchange Matrix Approach for STD NMR (CORCEMA-ST), in general terms, and an example of a previous work on an antibody-glycan interaction is also shown.

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.

An Quantitative Analysis Method Of Trabecular Pattern In A Bone

NASA Astrophysics Data System (ADS)

Idesawa, Masanor; Yatagai, Toyohiko

1982-11-01

Orientation and density of trabecular pattern observed in a bone is closely related to its mechanical properties and deseases of a bone are appeared as changes of orientation and/or density distrbution of its trabecular patterns. They have been treated from a qualitative point of view so far because quantitative analysis method has not be established. In this paper, the authors proposed and investigated some quantitative analysis methods of density and orientation of trabecular patterns observed in a bone. These methods can give an index for evaluating orientation of trabecular pattern quantitatively and have been applied to analyze trabecular pattern observed in a head of femur and their availabilities are confirmed. Key Words: Index of pattern orientation, Trabecular pattern, Pattern density, Quantitative analysis

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.

Molecular Imaging and Quantitation of EphA2 Expression in Xenograft Models with 89Zr-DS-8895a.

PubMed

Burvenich, Ingrid J G; Parakh, Sagun; Gan, Hui K; Lee, Fook-Thean; Guo, Nancy; Rigopoulos, Angela; Lee, Sze-Ting; Gong, Sylvia; O'Keefe, Graeme J; Tochon-Danguy, Henri; Kotsuma, Masakatsu; Hasegawa, Jun; Senaldi, Giorgio; Scott, Andrew M

2016-06-01

Subtype A2 of the erythropoietin-producing hepatocellular tyrosine kinase (EphA2) cell surface receptor is expressed in a range of epithelial cancers. This study evaluated the molecular imaging of EphA2 expression in vivo in mouse tumor models using SPECT/MR and PET/MR and a humanized anti-EphA2 antibody, DS-8895a. DS-8895a was labeled with (111)In, (125)I, and (89)Zr and assessed for radiochemical purity, immunoreactivity (Lindmo analysis), antigen-binding affinity (Scatchard analysis), and serum stability in vitro. In vivo biodistribution, imaging, and pharmacokinetic studies were performed with SPECT/MR and PET/MR. A dose-escalation study was also performed to determine EphA2 receptor saturability through tissue and imaging quantitative analysis. All conjugates demonstrated good serum stability and specific binding to EphA2-expressing cells in vitro. In vivo biodistribution studies showed high uptake of (111)In-CHX-A″-DTPA-DS-8895a and (89)Zr-Df-Bz-NCS-DS-8895a in EphA2-expressing xenograft models, with no specific uptake in normal tissues. In comparison, retention of (125)I-DS-8895a in tumors was lower because of internalization of the radioconjugate and dehalogenation. These results were confirmed by SPECT/MR and PET/MR. EphA2 receptor saturation was observed at the 30 mg/kg dose. Molecular imaging of tumor uptake of DS-8895a allows noninvasive measurement of EphA2 expression in tumors in vivo and determination of receptor saturation. (89)Zr-Df-Bz-NCS-DS-8895a is suited for human bioimaging trials on the basis of superior imaging characteristics and will inform DS-8895a dose assessment and patient response evaluation in clinical trials. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

PubMed

Potemkin, Andrey V; Grishina, Maria A; Potemkin, Vladimir A

2017-01-01

In 1979, R.D.Cramer and M.Milne made a first realization of 3D comparison of molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (Dynamic Lattice- Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities. Then, in 1988, the method which was called CoMFA (Comparative Molecular Field Analysis) was introduced and the appropriate software became commercially available. Since 1988, a lot of 3D QSAR methods, algorithms and their modifications are introduced for solving of virtual drug discovery problems (e.g., CoMSIA, CoMMA, HINT, HASL, GOLPE, GRID, PARM, Raptor, BiS, CiS, ConGO,). All the methods can be divided into two groups (classes):1. Methods studying the exterior of molecules; 2) Methods studying the interior of molecules. A series of grid-based computational technologies for Continual Molecular Interior analysis (CoMIn) are invented in the current paper. The grid-based analysis is fulfilled by means of a lattice construction analogously to many other grid-based methods. The further continual elucidation of molecular structure is performed in various ways. (i) In terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum

Molecular Rotors for Universal Quantitation of Nanoscale Hydrophobic Interfaces in Microplate Format.

PubMed

Bisso, Paul W; Tai, Michelle; Katepalli, Hari; Bertrand, Nicolas; Blankschtein, Daniel; Langer, Robert

2018-01-10

Hydrophobic self-assembly pairs diverse chemical precursors and simple formulation processes to access a vast array of functional colloids. Exploration of this design space, however, is stymied by lack of broadly general, high-throughput colloid characterization tools. Here, we show that a narrow structural subset of fluorescent, zwitterionic molecular rotors, dialkylaminostilbazolium sulfonates [DASS] with intermediate-length alkyl tails, fills this major analytical void by quantitatively sensing hydrophobic interfaces in microplate format. DASS dyes supersede existing interfacial probes by avoiding off-target fluorogenic interactions and dye aggregation while preserving hydrophobic partitioning strength. To illustrate the generality of this approach, we demonstrate (i) a microplate-based technique for measuring mass concentration of small (20-200 nm), dilute (submicrogram sensitivity) drug delivery nanoparticles; (ii) elimination of particle size, surfactant chemistry, and throughput constraints on quantifying the complex surfactant/metal oxide adsorption isotherms critical for environmental remediation and enhanced oil recovery; and (iii) more reliable self-assembly onset quantitation for chemically and structurally distinct amphiphiles. These methods could streamline the development of nanotechnologies for a broad range of applications.

Incorporation of unique molecular identifiers in TruSeq adapters improves the accuracy of quantitative sequencing.

PubMed

Hong, Jungeui; Gresham, David

2017-11-01

Quantitative analysis of next-generation sequencing (NGS) data requires discriminating duplicate reads generated by PCR from identical molecules that are of unique origin. Typically, PCR duplicates are identified as sequence reads that align to the same genomic coordinates using reference-based alignment. However, identical molecules can be independently generated during library preparation. Misidentification of these molecules as PCR duplicates can introduce unforeseen biases during analyses. Here, we developed a cost-effective sequencing adapter design by modifying Illumina TruSeq adapters to incorporate a unique molecular identifier (UMI) while maintaining the capacity to undertake multiplexed, single-index sequencing. Incorporation of UMIs into TruSeq adapters (TrUMIseq adapters) enables identification of bona fide PCR duplicates as identically mapped reads with identical UMIs. Using TrUMIseq adapters, we show that accurate removal of PCR duplicates results in improved accuracy of both allele frequency (AF) estimation in heterogeneous populations using DNA sequencing and gene expression quantification using RNA-Seq.

Consistency and reproducibility of next-generation sequencing and other multigene mutational assays: A worldwide ring trial study on quantitative cytological molecular reference specimens.

PubMed

Malapelle, Umberto; Mayo-de-Las-Casas, Clara; Molina-Vila, Miguel A; Rosell, Rafael; Savic, Spasenija; Bihl, Michel; Bubendorf, Lukas; Salto-Tellez, Manuel; de Biase, Dario; Tallini, Giovanni; Hwang, David H; Sholl, Lynette M; Luthra, Rajyalakshmi; Weynand, Birgit; Vander Borght, Sara; Missiaglia, Edoardo; Bongiovanni, Massimo; Stieber, Daniel; Vielh, Philippe; Schmitt, Fernando; Rappa, Alessandra; Barberis, Massimo; Pepe, Francesco; Pisapia, Pasquale; Serra, Nicola; Vigliar, Elena; Bellevicine, Claudio; Fassan, Matteo; Rugge, Massimo; de Andrea, Carlos E; Lozano, Maria D; Basolo, Fulvio; Fontanini, Gabriella; Nikiforov, Yuri E; Kamel-Reid, Suzanne; da Cunha Santos, Gilda; Nikiforova, Marina N; Roy-Chowdhuri, Sinchita; Troncone, Giancarlo

2017-08-01

Molecular testing of cytological lung cancer specimens includes, beyond epidermal growth factor receptor (EGFR), emerging predictive/prognostic genomic biomarkers such as Kirsten rat sarcoma viral oncogene homolog (KRAS), neuroblastoma RAS viral [v-ras] oncogene homolog (NRAS), B-Raf proto-oncogene, serine/threonine kinase (BRAF), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA). Next-generation sequencing (NGS) and other multigene mutational assays are suitable for cytological specimens, including smears. However, the current literature reflects single-institution studies rather than multicenter experiences. Quantitative cytological molecular reference slides were produced with cell lines designed to harbor concurrent mutations in the EGFR, KRAS, NRAS, BRAF, and PIK3CA genes at various allelic ratios, including low allele frequencies (AFs; 1%). This interlaboratory ring trial study included 14 institutions across the world that performed multigene mutational assays, from tissue extraction to data analysis, on these reference slides, with each laboratory using its own mutation analysis platform and methodology. All laboratories using NGS (n = 11) successfully detected the study's set of mutations with minimal variations in the means and standard errors of variant fractions at dilution points of 10% (P = .171) and 5% (P = .063) despite the use of different sequencing platforms (Illumina, Ion Torrent/Proton, and Roche). However, when mutations at a low AF of 1% were analyzed, the concordance of the NGS results was low, and this reflected the use of different thresholds for variant calling among the institutions. In contrast, laboratories using matrix-assisted laser desorption/ionization-time of flight (n = 2) showed lower concordance in terms of mutation detection and mutant AF quantification. Quantitative molecular reference slides are a useful tool for monitoring the performance of different multigene mutational

Good practices for quantitative bias analysis.

PubMed

Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

2014-12-01

Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage

Quantitative mass spectrometry methods for pharmaceutical analysis

PubMed Central

Loos, Glenn; Van Schepdael, Ann

2016-01-01

Quantitative pharmaceutical analysis is nowadays frequently executed using mass spectrometry. Electrospray ionization coupled to a (hybrid) triple quadrupole mass spectrometer is generally used in combination with solid-phase extraction and liquid chromatography. Furthermore, isotopically labelled standards are often used to correct for ion suppression. The challenges in producing sensitive but reliable quantitative data depend on the instrumentation, sample preparation and hyphenated techniques. In this contribution, different approaches to enhance the ionization efficiencies using modified source geometries and improved ion guidance are provided. Furthermore, possibilities to minimize, assess and correct for matrix interferences caused by co-eluting substances are described. With the focus on pharmaceuticals in the environment and bioanalysis, different separation techniques, trends in liquid chromatography and sample preparation methods to minimize matrix effects and increase sensitivity are discussed. Although highly sensitive methods are generally aimed for to provide automated multi-residue analysis, (less sensitive) miniaturized set-ups have a great potential due to their ability for in-field usage. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644982

Quantitative proteomics in biological research.

PubMed

Wilm, Matthias

2009-10-01

Proteomics has enabled the direct investigation of biological material, at first through the analysis of individual proteins, then of lysates from cell cultures, and finally of extracts from tissues and biopsies from entire organisms. Its latest manifestation - quantitative proteomics - allows deeper insight into biological systems. This article reviews the different methods used to extract quantitative information from mass spectra. It follows the technical developments aimed toward global proteomics, the attempt to characterize every expressed protein in a cell by at least one peptide. When applications of the technology are discussed, the focus is placed on yeast biology. In particular, differential quantitative proteomics, the comparison between an experiment and its control, is very discriminating for proteins involved in the process being studied. When trying to understand biological processes on a molecular level, differential quantitative proteomics tends to give a clearer picture than global transcription analyses. As a result, MS has become an even more indispensable tool for biochemically motivated biological research.

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

Quantitative Analysis of the Molecular Dynamics of P3HT:PCBM Bulk Heterojunction.

PubMed

Guilbert, Anne A Y; Zbiri, Mohamed; Dunbar, Alan D F; Nelson, Jenny

2017-09-28

The optoelectronic properties of blends of conjugated polymers and small molecules are likely to be affected by the molecular dynamics of the active layer components. We study the dynamics of regioregular poly(3-hexylthiophene) (P3HT):phenyl-C61-butyric acid methyl ester (PCBM) blends using molecular dynamics (MD) simulation on time scales up to 50 ns and in a temperature range of 250-360 K. First, we compare the MD results with quasi-elastic neutron-scattering (QENS) measurements. Experiment and simulation give evidence of the vitrification of P3HT upon blending and the plasticization of PCBM by P3HT. Second, we reconstruct the QENS signal based on the independent simulations of the three phases constituting the complex microstructure of such blends. Finally, we found that P3HT chains tend to wrap around PCBM molecules in the amorphous mixture of P3HT and PCBM; this molecular interaction between P3HT and PCBM is likely to be responsible for the observed frustration of P3HT, the plasticization of PCBM, and the partial miscibility of P3HT and PCBM.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Quantitative PCR and disaccharide profiling to characterize the animal origin of low-molecular-weight heparins.

PubMed

Houiste, Céline; Auguste, Cécile; Macrez, Céline; Dereux, Stéphanie; Derouet, Angélique; Anger, Pascal

2009-02-01

Low-molecular-weight heparins (LMWHs) are widely used in the management of thrombosis and acute coronary syndromes. They are obtained by the enzymatic or chemical depolymerization of porcine intestinal heparin. Enoxaparin sodium, a widely used LMWH, has a unique and reproducible oligosaccharide profile which is determined by the origin of the starting material and a tightly controlled manufacturing process. Although other enoxaparin-like LMWHs do exist, specific release criteria including the origin of the crude heparin utilized for their production, have not been established. A quantitative polymerase chain reaction method has been developed to ensure the purity of the porcine origin of crude heparin, with a DNA detection limit as low as 1 ppm for bovine, or 10 ppm for ovine contaminants. This method is routinely used as the release acceptance criterion during enoxaparin sodium manufacturing. Furthermore, when the process removes DNA, other analytical techniques can be used to assess any contamination. Disaccharide profiling after exhaustive depolymerization can determine the presence of at least 10% bovine or 20% ovine material; multivariate analysis is useful to perform the data analysis. Consistent with the availability of newer technology, these methods should be required as acceptance criteria for crude heparins used in the manufacture of LMWHs to ensure their safety, quality, and immunologic profile.

Mini-Column Ion-Exchange Separation and Atomic Absorption Quantitation of Nickel, Cobalt, and Iron: An Undergraduate Quantitative Analysis Experiment.

ERIC Educational Resources Information Center

Anderson, James L.; And Others

1980-01-01

Presents an undergraduate quantitative analysis experiment, describing an atomic absorption quantitation scheme that is fast, sensitive and comparatively simple relative to other titration experiments. (CS)

Quantitative analysis of arm movement smoothness

NASA Astrophysics Data System (ADS)

Szczesna, Agnieszka; Błaszczyszyn, Monika

2017-07-01

The paper deals with the problem of motion data quantitative smoothness analysis. We investigated values of movement unit, fluidity and jerk for healthy and paralyzed arm of patients with hemiparesis after stroke. Patients were performing drinking task. To validate the approach, movement of 24 patients were captured using optical motion capture system.

UPLC-MS/MS quantitative analysis and structural fragmentation study of five Parmotrema lichens from the Eastern Ghats.

PubMed

Kumar, K; Siva, Bandi; Sarma, V U M; Mohabe, Satish; Reddy, A Madhusudana; Boustie, Joel; Tiwari, Ashok K; Rao, N Rama; Babu, K Suresh

2018-07-15

Comparative phytochemical analysis of five lichen species [Parmotrema tinctorum (Delise ex Nyl.) Hale, P. andinum (Mull. Arg.) Hale, P. praesorediosum (Nyl.) Hale, P. grayanum (Hue) Hale, P. austrosinense (Zahlbr.) Hale] of Parmotrema genus were performed using two complementary UPLC-MS systems. The first system consists of high resolution UPLC-QToF-MS/MS spectrometer and the second system consisted of UPLC-MS/MS in Multiple Reaction Monitoring (MRM) mode for quantitative analysis of major constituents in the selected lichen species. The individual compounds (47 compounds) were identified using Q-ToF-MS/MS, via comparison of the exact molecular masses from their MS/MS spectra, the comparison of literature data and retention times to those of standard compounds which were isolated from crude extract of abundant lichen, P. tinctorum. The analysis also allowed us to identify unknown peaks/compounds, which were further characterized by their mass fragmentation studies. The quantitative MRM analysis was useful to have a better discrimination of species according to their chemical profile. Moreover, the determination of antioxidant activities (ABTS + inhibition) and Advance Glycation Endproducts (AGEs) inhibition carried out for the crude extracts revealed a potential antiglycaemic activity to be confirmed for P. austrosinense. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative analysis of genomic DNA degradation in whole blood under various storage conditions for molecular diagnostic testing.

PubMed

Permenter, Jessalyn; Ishwar, Arjun; Rounsavall, Angie; Smith, Maddie; Faske, Jennifer; Sailey, Charles J; Alfaro, Maria P

2015-12-01

Proper storage of whole blood is crucial for isolating nucleic acids from leukocytes and to ensure adequate performance of downstream assays in the molecular diagnostic laboratory. Short-term and long-term storage recommendations are lacking for successful isolation of genomic DNA (gDNA). Container type (EDTA or heparin), temperature (4 °C and room temperature) and time (1-130 days) were assessed as criterion for sample acceptance policies. The percentage of integrated area (%Ti) between 150 and 10,000 bp from the 2200 TapeStation electropherogram was calculated to measure gDNA degradation. Refrigerated EDTA samples yielded gDNA with low %Ti (high quality). Heparinized samples stored at room temperature yielded gDNA of worst quality. Downstream analysis demonstrated that the quality of the gDNA correlated with the quality of the data; samples with high %Ti generated significantly lower levels of high molecular weight amplicons. Recommendations from these analyses include storing blood samples intended for nucleic acid isolation in EDTA tubes at 4 °C for long term storage (>10 days). gDNA should be extracted within 3 days when blood is stored at room temperature regardless of the container. Finally, refrigerated heparinized samples should not be stored longer than 9 days if expecting high quality gDNA isolates. Laboratories should consider many factors, in addition to the results obtained herein, to update their policies for sample acceptance for gDNA extraction intended for molecular genetic testing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of a calibration protocol for quantitative imaging for molecular radiotherapy dosimetry

NASA Astrophysics Data System (ADS)

Wevrett, J.; Fenwick, A.; Scuffham, J.; Nisbet, A.

2017-11-01

Within the field of molecular radiotherapy, there is a significant need for standardisation in dosimetry, in both quantitative imaging and dosimetry calculations. Currently, there are a wide range of techniques used by different clinical centres and as a result there is no means to compare patient doses between centres. To help address this need, a 3 year project was funded by the European Metrology Research Programme, and a number of clinical centres were involved in the project. One of the required outcomes of the project was to develop a calibration protocol for three dimensional quantitative imaging of volumes of interest. Two radionuclides were selected as being of particular interest: iodine-131 (131I, used to treat thyroid disorders) and lutetium-177 (177Lu, used to treat neuroendocrine tumours). A small volume of activity within a scatter medium (water), representing a lesion within a patient body, was chosen as the calibration method. To ensure ease of use in clinical centres, an "off-the-shelf" solution was proposed - to avoid the need for in-house manufacturing. The BIODEX elliptical Jaszczak phantom and 16 ml fillable sphere were selected. The protocol was developed for use on SPECT/CT gamma cameras only, where the CT dataset would be used to correct the imaging data for attenuation of the emitted photons within the phantom. The protocol corrects for scatter of emitted photons using the triple energy window correction technique utilised by most clinical systems. A number of clinical systems were tested in the development of this protocol, covering the major manufacturers of gamma camera generally used in Europe. Initial imaging was performed with 131I and 177Lu at a number of clinical centres, but due to time constraints in the project, some acquisitions were performed with 177Lu only. The protocol is relatively simplistic, and does not account for the effects of dead-time in high activity patients, the presence of background activity surrounding

Activation of a camptothecin prodrug by specific carboxylesterases as predicted by quantitative structure-activity relationship and molecular docking studies.

PubMed

Yoon, Kyoung Jin P; Krull, Erik J; Morton, Christopher L; Bornmann, William G; Lee, Richard E; Potter, Philip M; Danks, Mary K

2003-11-01

7-Ethyl-10-[4-(1-piperidino)-1-piperidino]carbonyloxycamptothecin (irinotecan, CPT-11) is a camptothecin prodrug that is metabolized by carboxylesterases (CE) to the active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38), a topoisomerase I inhibitor. CPT-11 has shown encouraging antitumor activity against a broad spectrum of tumor types in early clinical trials, but hematopoietic and gastrointestinal toxicity limit its administration. To increase the therapeutic index of CPT-11 and to develop other prodrug analogues for enzyme/prodrug gene therapy applications, our laboratories propose to develop camptothecin prodrugs that will be activated by specific CEs. Specific analogues might then be predicted to be activated, for example, predominantly by human liver CE(hCE1), by human intestinal CE (hiCE), or in gene therapy approaches using a rabbit liver CE (rCE). This study describes a molecular modeling approach to relate the structure of rCE-activated camptothecin prodrugs with their biological activation. Comparative molecular field analysis, comparative molecular similarity index analysis, and docking studies were used to predict the biological activity of a 4-benzylpiperazine derivative of CPT-11 [7-ethyl-10-[4-(1-benzyl)-1-piperazino]carbonyloxycamptothecin (BP-CPT)] in U373MG glioma cell lines transfected with plasmids encoding rCE or hiCE. BP-CPT has been reported to be activated more efficiently than CPT-11 by a rat serum esterase activity; however, three-dimensional quantitative structure-activity relationship studies predicted that rCE would activate BP-CPT less efficiently than CPT-11. This was confirmed by both growth inhibition experiments and kinetic studies. The method is being used to design camptothecin prodrugs predicted to be activated by specific CEs.

iTRAQ-Based Quantitative Proteomic Analysis of the Antimicrobial Mechanism of Peptide F1 against Escherichia coli.

PubMed

Miao, Jianyin; Chen, Feilong; Duan, Shan; Gao, Xiangyang; Liu, Guo; Chen, Yunjiao; Dixon, William; Xiao, Hang; Cao, Yong

2015-08-19

Antimicrobial peptides have received increasing attention in the agricultural and food industries due to their potential to control pathogens. However, to facilitate the development of novel peptide-based antimicrobial agents, details regarding the molecular mechanisms of these peptides need to be elucidated. The aim of this study was to investigate the antimicrobial mechanism of peptide F1, a bacteriocin found in Tibetan kefir, against Escherichia coli at protein levels using iTRAQ-based quantitative proteomic analysis. In response to treatment with peptide F1, 31 of the 280 identified proteins in E. coli showed alterations in their expression, including 10 down-regulated proteins and 21 up-regulated proteins. These 31 proteins all possess different molecular functions and are involved in different molecular pathways, as is evident in referencing the Kyoto Encyclopedia of Genes and Genomes pathways. Specifically, pathways that were significantly altered in E. coli in response to peptide F1 treatment include the tricarboxylic acid cycle, oxidative phosphorylation, glycerophospholipid metabolism, and the cell cycle-caulobacter pathways, which was also associated with inhibition of the cell growth, induction of morphological changes, and cell death. The results provide novel insights into the molecular mechanisms of antimicrobial peptides.

Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem.

PubMed

Xie, Weilong; Yu, Kangfu; Pauls, K Peter; Navabi, Alireza

2012-04-01

The effectiveness of image analysis (IA) compared with an ordinal visual scale, for quantitative measurement of disease severity, its application in quantitative genetic studies, and its effect on the estimates of genetic parameters were investigated. Studies were performed using eight backcross-derived families of common bean (Phaseolus vulgaris) (n = 172) segregating for the molecular marker SU91, known to be associated with a quantitative trait locus (QTL) for resistance to common bacterial blight (CBB), caused by Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans. Even though both IA and visual assessments were highly repeatable, IA was more sensitive in detecting quantitative differences between bean genotypes. The CBB phenotypic difference between the two SU91 genotypic groups was consistently more than fivefold for IA assessments but generally only two- to threefold for visual assessments. Results suggest that the visual assessment results in overestimation of the effect of QTL in genetic studies. This may have been caused by lack of additivity and uneven intervals of the visual scale. Although visual assessment of disease severity is a useful tool for general selection in breeding programs, assessments using IA may be more suitable for phenotypic evaluations in quantitative genetic studies involving CBB resistance as well as other foliar diseases.

Construction of Viable Soil Defined Media Using Quantitative Metabolomics Analysis of Soil Metabolites

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

Jenkins, Stefan; Swenson, Tami L.; Lau, Rebecca

Exometabolomics enables analysis of metabolite utilization of low molecular weight organic substances by soil bacteria. Thus, environmentally-based defined media are needed to examine ecologically relevant patterns of substrate utilization. Here, we describe an approach for the construction of defined media using untargeted characterization of water soluble soil microbial metabolites from a saprolite soil collected from the Oak Ridge Field Research Center (ORFRC). To broadly characterize metabolites, both liquid chromatography mass spectrometry (LC/MS) and gas chromatography mass spectrometry (GC/MS) were used. With this approach, 96 metabolites were identified, including amino acids, amino acid derivatives, sugars, sugar alcohols, mono- and di-carboxylic acids,more » nucleobases, and nucleosides. From this pool of metabolites, 25 were quantified. Molecular weight cut-off filtration determined the fraction of carbon accounted for by the quantified metabolites and revealed that these soil metabolites have an uneven quantitative distribution (e.g., trehalose accounted for 9.9% of the < 1 kDa fraction). This quantitative information was used to formulate two soil defined media (SDM), one containing 23 metabolites (SDM1) and one containing 46 (SDM2). To evaluate the viability of the SDM, we examined the growth of 30 phylogenetically diverse soil bacterial isolates from the ORFRC field site. The simpler SDM1 supported the growth of 13 isolates while the more complex SDM2 supported 15 isolates. To investigate SDM1 substrate preferences, one isolate, Pseudomonas corrugata strain FW300-N2E2 was selected for a time-series exometabolomics analysis. Interestingly, it was found that this organism preferred lower-abundance substrates such as guanine, glycine, proline and arginine and glucose and did not utilize the more abundant substrates maltose, mannitol, trehalose and uridine. These results demonstrate the viability and utility of using exometabolomics to construct a

Construction of Viable Soil Defined Media Using Quantitative Metabolomics Analysis of Soil Metabolites

PubMed Central

Jenkins, Stefan; Swenson, Tami L.; Lau, Rebecca; Rocha, Andrea M.; Aaring, Alex; Hazen, Terry C.; Chakraborty, Romy; Northen, Trent R.

2017-01-01

Exometabolomics enables analysis of metabolite utilization of low molecular weight organic substances by soil bacteria. Environmentally-based defined media are needed to examine ecologically relevant patterns of substrate utilization. Here, we describe an approach for the construction of defined media using untargeted characterization of water soluble soil microbial metabolites from a saprolite soil collected from the Oak Ridge Field Research Center (ORFRC). To broadly characterize metabolites, both liquid chromatography mass spectrometry (LC/MS) and gas chromatography mass spectrometry (GC/MS) were used. With this approach, 96 metabolites were identified, including amino acids, amino acid derivatives, sugars, sugar alcohols, mono- and di-carboxylic acids, nucleobases, and nucleosides. From this pool of metabolites, 25 were quantified. Molecular weight cut-off filtration determined the fraction of carbon accounted for by the quantified metabolites and revealed that these soil metabolites have an uneven quantitative distribution (e.g., trehalose accounted for 9.9% of the <1 kDa fraction). This quantitative information was used to formulate two soil defined media (SDM), one containing 23 metabolites (SDM1) and one containing 46 (SDM2). To evaluate the viability of the SDM, we examined the growth of 30 phylogenetically diverse soil bacterial isolates from the ORFRC field site. The simpler SDM1 supported the growth of 13 isolates while the more complex SDM2 supported 15 isolates. To investigate SDM1 substrate preferences, one isolate, Pseudomonas corrugata strain FW300-N2E2 was selected for a time-series exometabolomics analysis. Interestingly, it was found that this organism preferred lower-abundance substrates such as guanine, glycine, proline and arginine and glucose and did not utilize the more abundant substrates maltose, mannitol, trehalose and uridine. These results demonstrate the viability and utility of using exometabolomics to construct a tractable

Construction of Viable Soil Defined Media Using Quantitative Metabolomics Analysis of Soil Metabolites

DOE PAGES

Jenkins, Stefan; Swenson, Tami L.; Lau, Rebecca; ...

2017-12-22

Exometabolomics enables analysis of metabolite utilization of low molecular weight organic substances by soil bacteria. Thus, environmentally-based defined media are needed to examine ecologically relevant patterns of substrate utilization. Here, we describe an approach for the construction of defined media using untargeted characterization of water soluble soil microbial metabolites from a saprolite soil collected from the Oak Ridge Field Research Center (ORFRC). To broadly characterize metabolites, both liquid chromatography mass spectrometry (LC/MS) and gas chromatography mass spectrometry (GC/MS) were used. With this approach, 96 metabolites were identified, including amino acids, amino acid derivatives, sugars, sugar alcohols, mono- and di-carboxylic acids,more » nucleobases, and nucleosides. From this pool of metabolites, 25 were quantified. Molecular weight cut-off filtration determined the fraction of carbon accounted for by the quantified metabolites and revealed that these soil metabolites have an uneven quantitative distribution (e.g., trehalose accounted for 9.9% of the < 1 kDa fraction). This quantitative information was used to formulate two soil defined media (SDM), one containing 23 metabolites (SDM1) and one containing 46 (SDM2). To evaluate the viability of the SDM, we examined the growth of 30 phylogenetically diverse soil bacterial isolates from the ORFRC field site. The simpler SDM1 supported the growth of 13 isolates while the more complex SDM2 supported 15 isolates. To investigate SDM1 substrate preferences, one isolate, Pseudomonas corrugata strain FW300-N2E2 was selected for a time-series exometabolomics analysis. Interestingly, it was found that this organism preferred lower-abundance substrates such as guanine, glycine, proline and arginine and glucose and did not utilize the more abundant substrates maltose, mannitol, trehalose and uridine. These results demonstrate the viability and utility of using exometabolomics to construct a

Control of separation and quantitative analysis by GC-FTIR

NASA Astrophysics Data System (ADS)

Semmoud, A.; Huvenne, Jean P.; Legrand, P.

1992-03-01

Software for 3-D representations of the 'Absorbance-Wavenumber-Retention time' is used to control the quality of the GC separation. Spectral information given by the FTIR detection allows the user to be sure that a chromatographic peak is 'pure.' The analysis of peppermint essential oil is presented as an example. This assurance is absolutely required for quantitative applications. In these conditions, we have worked out a quantitative analysis of caffeine. Correlation coefficients between integrated absorbance measurements and concentration of caffeine are discussed at two steps of the data treatment.

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 γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method.

PubMed

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-02-01

To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method

PubMed Central

Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-01-01

Objective To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. Methods TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Results Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. Conclusions The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil. PMID:25182282

Applying Qualitative Hazard Analysis to Support Quantitative Safety Analysis for Proposed Reduced Wake Separation Conops

NASA Technical Reports Server (NTRS)

Shortle, John F.; Allocco, Michael

2005-01-01

This paper describes a scenario-driven hazard analysis process to identify, eliminate, and control safety-related risks. Within this process, we develop selective criteria to determine the applicability of applying engineering modeling to hypothesized hazard scenarios. This provides a basis for evaluating and prioritizing the scenarios as candidates for further quantitative analysis. We have applied this methodology to proposed concepts of operations for reduced wake separation for closely spaced parallel runways. For arrivals, the process identified 43 core hazard scenarios. Of these, we classified 12 as appropriate for further quantitative modeling, 24 that should be mitigated through controls, recommendations, and / or procedures (that is, scenarios not appropriate for quantitative modeling), and 7 that have the lowest priority for further analysis.

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.

ITRAQ-based quantitative proteomic analysis of Cynops orientalis limb regeneration.

PubMed

Tang, Jie; Yu, Yuan; Zheng, Hanxue; Yin, Lu; Sun, Mei; Wang, Wenjun; Cui, Jihong; Liu, Wenguang; Xie, Xin; Chen, Fulin

2017-09-22

Salamanders regenerate their limbs after amputation. However, the molecular mechanism of this unique regeneration remains unclear. In this study, isobaric tags for relative and absolute quantification (iTRAQ) coupled with liquid chromatography tandem mass spectrometry (LC-MS/MS) was employed to quantitatively identify differentially expressed proteins in regenerating limbs 3, 7, 14, 30 and 42 days post amputation (dpa). Of 2636 proteins detected in total, 253 proteins were differentially expressed during different regeneration stages. Among these proteins, Asporin, Cadherin-13, Keratin, Collagen alpha-1(XI) and Titin were down-regulated. CAPG, Coronin-1A, AnnexinA1, Cathepsin B were up-regulated compared with the control. The identified proteins were further analyzed to obtain information about their expression patterns and functions in limb regeneration. Functional analysis indicated that the differentially expressed proteins were associated with wound healing, immune response, cellular process, metabolism and binding. This work indicated that significant proteome alternations occurred during salamander limb regeneration. The results may provide fundamental knowledge to understand the mechanism of limb regeneration.

Live-cell confocal microscopy and quantitative 4D image analysis of anchor cell invasion through the basement membrane in C. elegans

PubMed Central

Kelley, Laura C.; Wang, Zheng; Hagedorn, Elliott J.; Wang, Lin; Shen, Wanqing; Lei, Shijun; Johnson, Sam A.; Sherwood, David R.

2018-01-01

Cell invasion through basement membrane (BM) barriers is crucial during development, leukocyte trafficking, and for the spread of cancer. Despite its importance in normal and diseased states, the mechanisms that direct invasion are poorly understood, in large part because of the inability to visualize dynamic cell-basement membrane interactions in vivo. This protocol describes multi-channel time-lapse confocal imaging of anchor cell invasion in live C. elegans. Methods presented include outline slide preparation and worm growth synchronization (15 min), mounting (20 min), image acquisition (20-180 min), image processing (20 min), and quantitative analysis (variable timing). Images acquired enable direct measurement of invasive dynamics including invadopodia formation, cell membrane protrusions, and BM removal. This protocol can be combined with genetic analysis, molecular activity probes, and optogenetic approaches to uncover molecular mechanisms underlying cell invasion. These methods can also be readily adapted for real-time analysis of cell migration, basement membrane turnover, and cell membrane dynamics by any worm laboratory. PMID:28880279

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Accurate calibration of a molecular beam time-of-flight mass spectrometer for on-line analysis of high molecular weight species.

PubMed

Apicella, B; Wang, X; Passaro, M; Ciajolo, A; Russo, C

2016-10-15

Time-of-Flight (TOF) Mass Spectrometry is a powerful analytical technique, provided that an accurate calibration by standard molecules in the same m/z range of the analytes is performed. Calibration in a very large m/z range is a difficult task, particularly in studies focusing on the detection of high molecular weight clusters of different molecules or high molecular weight species. External calibration is the most common procedure used for TOF mass spectrometric analysis in the gas phase and, generally, the only available standards are made up of mixtures of noble gases, covering a small mass range for calibration, up to m/z 136 (higher mass isotope of xenon). In this work, an accurate calibration of a Molecular Beam Time-of Flight Mass Spectrometer (MB-TOFMS) is presented, based on the use of water clusters up to m/z 3000. The advantages of calibrating a MB-TOFMS with water clusters for the detection of analytes with masses above those of the traditional calibrants such as noble gases were quantitatively shown by statistical calculations. A comparison of the water cluster and noble gases calibration procedures in attributing the masses to a test mixture extending up to m/z 800 is also reported. In the case of the analysis of combustion products, another important feature of water cluster calibration was shown, that is the possibility of using them as "internal standard" directly formed from the combustion water, under suitable experimental conditions. The water clusters calibration of a MB-TOFMS gives rise to a ten-fold reduction in error compared to the traditional calibration with noble gases. The consequent improvement in mass accuracy in the calibration of a MB-TOFMS has important implications in various fields where detection of high molecular mass species is required. In combustion products analysis, it is also possible to obtain a new calibration spectrum before the acquisition of each spectrum, only modifying some operative conditions. Copyright © 2016

Quantiprot - a Python package for quantitative analysis of protein sequences.

PubMed

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data.

PubMed

Mitchell, Christopher J; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-08-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, (15)N, (13)C, or (18)O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25-45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. © 2016 by The American Society for Biochemistry and Molecular Biology

Quantitation of low molecular weight sugars by chemical derivatization-liquid chromatography/multiple reaction monitoring/mass spectrometry.

PubMed

Han, Jun; Lin, Karen; Sequria, Carita; Yang, Juncong; Borchers, Christoph H

2016-07-01

A new method for the separation and quantitation of 13 mono- and disaccharides has been developed by chemical derivatization/ultra-HPLC/negative-ion ESI-multiple-reaction monitoring MS. 3-Nitrophenylhydrazine (at 50°C for 60 min) was shown to be able to quantitatively derivatize low-molecular weight (LMW) reducing sugars. The nonreducing sugar, sucrose, was not derivatized. A pentafluorophenyl-bonded phase column was used for the chromatographic separation of the derivatized sugars. This method exhibits femtomole-level sensitivity, high precision (CVs of ≤ 4.6%) and high accuracy for the quantitation of LMW sugars in wine. Excellent linearity (R(2) ≥ 0.9993) and linear ranges of ∼500-fold for disaccharides and ∼1000-4000-fold for monosaccharides were achieved. With internal calibration ((13) C-labeled internal standards), recoveries were between 93.6% ± 1.6% (xylose) and 104.8% ± 5.2% (glucose). With external calibration, recoveries ranged from 82.5% ± 0.8% (ribulose) to 105.2% ± 2.1% (xylulose). Quantitation of sugars in two red wines and two white wines was performed using this method; quantitation of the central carbon metabolism-related carboxylic acids and tartaric acid was carried out using a previously established derivatization procedure with 3-nitrophenylhydrazine as well. The results showed that these two classes of compounds-both of which have important organoleptic properties-had different compositions in red and white wines. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

What Really Happens in Quantitative Group Research? Results of a Content Analysis of Recent Quantitative Research in "JSGW"

ERIC Educational Resources Information Center

Boyle, Lauren H.; Whittaker, Tiffany A.; Eyal, Maytal; McCarthy, Christopher J.

2017-01-01

The authors conducted a content analysis on quantitative studies published in "The Journal for Specialists in Group Work" ("JSGW") between 2012 and 2015. This brief report provides a general overview of the current practices of quantitative group research in counseling. The following study characteristics are reported and…

Method and apparatus for chromatographic quantitative analysis

DOEpatents

Fritz, James S.; Gjerde, Douglas T.; Schmuckler, Gabriella

1981-06-09

An improved apparatus and method for the quantitative analysis of a solution containing a plurality of anion species by ion exchange chromatography which utilizes a single eluent and a single ion exchange bed which does not require periodic regeneration. The solution containing the anions is added to an anion exchange resin bed which is a low capacity macroreticular polystyrene-divinylbenzene resin containing quarternary ammonium functional groups, and is eluted therefrom with a dilute solution of a low electrical conductance organic acid salt. As each anion species is eluted from the bed, it is quantitatively sensed by conventional detection means such as a conductivity cell.

Diagnostic accuracy of semi-quantitative and quantitative culture techniques for the diagnosis of catheter-related infections in newborns and molecular typing of isolated microorganisms.

PubMed

Riboli, Danilo Flávio Moraes; Lyra, João César; Silva, Eliane Pessoa; Valadão, Luisa Leite; Bentlin, Maria Regina; Corrente, José Eduardo; Rugolo, Ligia Maria Suppo de Souza; da Cunha, Maria de Lourdes Ribeiro de Souza

2014-05-22

Catheter-related bloodstream infections (CR-BSIs) have become the most common cause of healthcare-associated bloodstream infections in neonatal intensive care units (ICUs). Microbiological evidence implicating catheters as the source of bloodstream infection is necessary to establish the diagnosis of CR-BSIs. Semi-quantitative culture is used to determine the presence of microorganisms on the external catheter surface, whereas quantitative culture also isolates microorganisms present inside the catheter. The main objective of this study was to determine the sensitivity and specificity of these two techniques for the diagnosis of CR-BSIs in newborns from a neonatal ICU. In addition, PFGE was used for similarity analysis of the microorganisms isolated from catheters and blood cultures. Semi-quantitative and quantitative methods were used for the culture of catheter tips obtained from newborns. Strains isolated from catheter tips and blood cultures which exhibited the same antimicrobial susceptibility profile were included in the study as positive cases of CR-BSI. PFGE of the microorganisms isolated from catheters and blood cultures was performed for similarity analysis and detection of clones in the ICU. A total of 584 catheter tips from 399 patients seen between November 2005 and June 2012 were analyzed. Twenty-nine cases of CR-BSI were confirmed. Coagulase-negative staphylococci (CoNS) were the most frequently isolated microorganisms, including S. epidermidis as the most prevalent species (65.5%), followed by S. haemolyticus (10.3%), yeasts (10.3%), K. pneumoniae (6.9%), S. aureus (3.4%), and E. coli (3.4%). The sensitivity of the semi-quantitative and quantitative techniques was 72.7% and 59.3%, respectively, and specificity was 95.7% and 94.4%. The diagnosis of CR-BSIs based on PFGE analysis of similarity between strains isolated from catheter tips and blood cultures showed 82.6% sensitivity and 100% specificity. The semi-quantitative culture method showed higher

Use of quantitative molecular diagnostic methods to identify causes of diarrhoea in children: a reanalysis of the GEMS case-control study.

PubMed

Liu, Jie; Platts-Mills, James A; Juma, Jane; Kabir, Furqan; Nkeze, Joseph; Okoi, Catherine; Operario, Darwin J; Uddin, Jashim; Ahmed, Shahnawaz; Alonso, Pedro L; Antonio, Martin; Becker, Stephen M; Blackwelder, William C; Breiman, Robert F; Faruque, Abu S G; Fields, Barry; Gratz, Jean; Haque, Rashidul; Hossain, Anowar; Hossain, M Jahangir; Jarju, Sheikh; Qamar, Farah; Iqbal, Najeeha Talat; Kwambana, Brenda; Mandomando, Inacio; McMurry, Timothy L; Ochieng, Caroline; Ochieng, John B; Ochieng, Melvin; Onyango, Clayton; Panchalingam, Sandra; Kalam, Adil; Aziz, Fatima; Qureshi, Shahida; Ramamurthy, Thandavarayan; Roberts, James H; Saha, Debasish; Sow, Samba O; Stroup, Suzanne E; Sur, Dipika; Tamboura, Boubou; Taniuchi, Mami; Tennant, Sharon M; Toema, Deanna; Wu, Yukun; Zaidi, Anita; Nataro, James P; Kotloff, Karen L; Levine, Myron M; Houpt, Eric R

2016-09-24

Diarrhoea is the second leading cause of mortality in children worldwide, but establishing the cause can be complicated by diverse diagnostic approaches and varying test characteristics. We used quantitative molecular diagnostic methods to reassess causes of diarrhoea in the Global Enteric Multicenter Study (GEMS). GEMS was a study of moderate to severe diarrhoea in children younger than 5 years in Africa and Asia. We used quantitative real-time PCR (qPCR) to test for 32 enteropathogens in stool samples from cases and matched asymptomatic controls from GEMS, and compared pathogen-specific attributable incidences with those found with the original GEMS microbiological methods, including culture, EIA, and reverse-transcriptase PCR. We calculated revised pathogen-specific burdens of disease and assessed causes in individual children. We analysed 5304 sample pairs. For most pathogens, incidence was greater with qPCR than with the original methods, particularly for adenovirus 40/41 (around five times), Shigella spp or enteroinvasive Escherichia coli (EIEC) and Campylobactor jejuni o C coli (around two times), and heat-stable enterotoxin-producing E coli ([ST-ETEC] around 1·5 times). The six most attributable pathogens became, in descending order, Shigella spp, rotavirus, adenovirus 40/41, ST-ETEC, Cryptosporidium spp, and Campylobacter spp. Pathogen-attributable diarrhoeal burden was 89·3% (95% CI 83·2-96·0) at the population level, compared with 51·5% (48·0-55·0) in the original GEMS analysis. The top six pathogens accounted for 77·8% (74·6-80·9) of all attributable diarrhoea. With use of model-derived quantitative cutoffs to assess individual diarrhoeal cases, 2254 (42·5%) of 5304 cases had one diarrhoea-associated pathogen detected and 2063 (38·9%) had two or more, with Shigella spp and rotavirus being the pathogens most strongly associated with diarrhoea in children with mixed infections. A quantitative molecular diagnostic approach improved population

Quantitative Analysis of High-Quality Officer Selection by Commandants Career-Level Education Board

DTIC Science & Technology

2017-03-01

due to Marines being evaluated before the end of their initial service commitment. Our research utilizes quantitative variables to analyze the...not provide detailed information why. B. LIMITATIONS The photograph analysis in this research is strictly limited to a quantitative analysis in...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release. Distribution is unlimited. QUANTITATIVE

Molecular modeling of polymers 16. Gaseous diffusion in polymers: a quantitative structure-property relationship (QSPR) analysis.

PubMed

Patel, H C; Tokarski, J S; Hopfinger, A J

1997-10-01

The purpose of this study was to identify the key physicochemical molecular properties of polymeric materials responsible for gaseous diffusion in the polymers. Quantitative structure-property relationships, QSPRs were constructed using a genetic algorithm on a training set of 16 polymers for which CO2, N2, O2 diffusion constants were measured. Nine physicochemical properties of each of the polymers were used in the trial basis set for QSPR model construction. The linear cross-correlation matrices were constructed and investigated for colinearity among the members of the training sets. Common water diffusion measures for a limited training set of six polymers was used to construct a "semi-QSPR" model. The bulk modulus of the polymer was overwhelmingly found to be the dominant physicochemical polymer property that governs CO2, N2 and O2 diffusion. Some secondary physicochemical properties controlling diffusion, including conformational entropy, were also identified as correlation descriptors. Very significant QSPR diffusion models were constructed for all three gases. Cohesive energy was identified as the main correlation physicochemical property with aqueous diffusion measures. The dominant role of polymer bulk modulus on gaseous diffusion makes it difficult to develop criteria for selective transport of gases through polymers. Moreover, high bulk moduli are predicted to be necessary for effective gas barrier materials. This property requirement may limit the processing and packaging features of the material. Aqueous diffusion in polymers may occur by a different mechanism than gaseous diffusion since bulk modulus does not correlate with aqueous diffusion, but rather cohesive energy of the polymer.

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.

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.

Direct mapping of electrical noise sources in molecular wire-based devices

NASA Astrophysics Data System (ADS)

Cho, Duckhyung; Lee, Hyungwoo; Shekhar, Shashank; Yang, Myungjae; Park, Jae Yeol; Hong, Seunghun

2017-02-01

We report a noise mapping strategy for the reliable identification and analysis of noise sources in molecular wire junctions. Here, different molecular wires were patterned on a gold substrate, and the current-noise map on the pattern was measured and analyzed, enabling the quantitative study of noise sources in the patterned molecular wires. The frequency spectra of the noise from the molecular wire junctions exhibited characteristic 1/f2 behavior, which was used to identify the electrical signals from molecular wires. This method was applied to analyze the molecular junctions comprising various thiol molecules on a gold substrate, revealing that the noise in the junctions mainly came from the fluctuation of the thiol bonds. Furthermore, we quantitatively compared the frequencies of such bond fluctuations in different molecular wire junctions and identified molecular wires with lower electrical noise, which can provide critical information for designing low-noise molecular electronic devices. Our method provides valuable insights regarding noise phenomena in molecular wires and can be a powerful tool for the development of molecular electronic devices.

Direct mapping of electrical noise sources in molecular wire-based devices

PubMed Central

Cho, Duckhyung; Lee, Hyungwoo; Shekhar, Shashank; Yang, Myungjae; Park, Jae Yeol; Hong, Seunghun

2017-01-01

We report a noise mapping strategy for the reliable identification and analysis of noise sources in molecular wire junctions. Here, different molecular wires were patterned on a gold substrate, and the current-noise map on the pattern was measured and analyzed, enabling the quantitative study of noise sources in the patterned molecular wires. The frequency spectra of the noise from the molecular wire junctions exhibited characteristic 1/f2 behavior, which was used to identify the electrical signals from molecular wires. This method was applied to analyze the molecular junctions comprising various thiol molecules on a gold substrate, revealing that the noise in the junctions mainly came from the fluctuation of the thiol bonds. Furthermore, we quantitatively compared the frequencies of such bond fluctuations in different molecular wire junctions and identified molecular wires with lower electrical noise, which can provide critical information for designing low-noise molecular electronic devices. Our method provides valuable insights regarding noise phenomena in molecular wires and can be a powerful tool for the development of molecular electronic devices. PMID:28233821

Quantitative Analysis of Human Pluripotency and Neural Specification by In-Depth (Phospho)Proteomic Profiling.

PubMed

Singec, Ilyas; Crain, Andrew M; Hou, Junjie; Tobe, Brian T D; Talantova, Maria; Winquist, Alicia A; Doctor, Kutbuddin S; Choy, Jennifer; Huang, Xiayu; La Monaca, Esther; Horn, David M; Wolf, Dieter A; Lipton, Stuart A; Gutierrez, Gustavo J; Brill, Laurence M; Snyder, Evan Y

2016-09-13

Controlled differentiation of human embryonic stem cells (hESCs) can be utilized for precise analysis of cell type identities during early development. We established a highly efficient neural induction strategy and an improved analytical platform, and determined proteomic and phosphoproteomic profiles of hESCs and their specified multipotent neural stem cell derivatives (hNSCs). This quantitative dataset (nearly 13,000 proteins and 60,000 phosphorylation sites) provides unique molecular insights into pluripotency and neural lineage entry. Systems-level comparative analysis of proteins (e.g., transcription factors, epigenetic regulators, kinase families), phosphorylation sites, and numerous biological pathways allowed the identification of distinct signatures in pluripotent and multipotent cells. Furthermore, as predicted by the dataset, we functionally validated an autocrine/paracrine mechanism by demonstrating that the secreted protein midkine is a regulator of neural specification. This resource is freely available to the scientific community, including a searchable website, PluriProt. Published by Elsevier Inc.

[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.

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.

Quantitative study of mammalian cells by scanning transmission soft X-ray microscopy

NASA Astrophysics Data System (ADS)

Shinohara, K.; Ohigashi, T.; Toné, S.; Kado, M.; Ito, A.

2017-06-01

Molecular distribution in mammalian cells was studied by soft X-ray scanning transmission microscopy with respect to the quantitative aspect of analysis. NEXAFS profiles at the C, N and O K-absorption edges were combined and used for the analysis. For the estimation of quantity for nucleic acids and proteins, NEXAFS profiles of DNA and bovine serum albumin (BSA) at the N K-absorption edge were applied assuming that those were their representatives. The method has a potential to explore the other molecular components than nucleic acids and proteins.

Seniors' Online Communities: A Quantitative Content Analysis

ERIC Educational Resources Information Center

Nimrod, Galit

2010-01-01

Purpose: To examine the contents and characteristics of seniors' online communities and to explore their potential benefits to older adults. Design and Methods: Quantitative content analysis of a full year's data from 14 leading online communities using a novel computerized system. The overall database included 686,283 messages. Results: There was…

Targeted methods for quantitative analysis of protein glycosylation

PubMed Central

Goldman, Radoslav; Sanda, Miloslav

2018-01-01

Quantification of proteins by LC-MS/MS-MRM has become a standard method with broad projected clinical applicability. MRM quantification of protein modifications is, however, far less utilized, especially in the case of glycoproteins. This review summarizes current methods for quantitative analysis of protein glycosylation with a focus on MRM methods. We describe advantages of this quantitative approach, analytical parameters that need to be optimized to achieve reliable measurements, and point out the limitations. Differences between major classes of N- and O-glycopeptides are described and class-specific glycopeptide assays are demonstrated. PMID:25522218

Software for quantitative analysis of radiotherapy: overview, requirement analysis and design solutions.

PubMed

Zhang, Lanlan; Hub, Martina; Mang, Sarah; Thieke, Christian; Nix, Oliver; Karger, Christian P; Floca, Ralf O

2013-06-01

Radiotherapy is a fast-developing discipline which plays a major role in cancer care. Quantitative analysis of radiotherapy data can improve the success of the treatment and support the prediction of outcome. In this paper, we first identify functional, conceptional and general requirements on a software system for quantitative analysis of radiotherapy. Further we present an overview of existing radiotherapy analysis software tools and check them against the stated requirements. As none of them could meet all of the demands presented herein, we analyzed possible conceptional problems and present software design solutions and recommendations to meet the stated requirements (e.g. algorithmic decoupling via dose iterator pattern; analysis database design). As a proof of concept we developed a software library "RTToolbox" following the presented design principles. The RTToolbox is available as open source library and has already been tested in a larger-scale software system for different use cases. These examples demonstrate the benefit of the presented design principles. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Highly sensitive fluorescence quantitative detection of specific DNA sequences with molecular beacons and nucleic acid dye SYBR Green I.

PubMed

Xiang, Dongshan; Zhai, Kun; Xiang, Wenjun; Wang, Lianzhi

2014-11-01

A highly sensitive fluorescence method of quantitative detection for specific DNA sequence is developed based on molecular beacon (MB) and nucleic acid dye SYBR Green I by synchronous fluorescence analysis. It is demonstrated by an oligonucleotide sequence of wild-type HBV (target DNA) as a model system. In this strategy, the fluorophore of MB is designed to be 6-carboxyfluorescein group (FAM), and the maximum excitation wavelength and maximum emission wavelength are both very close to that of SYBR Green I. In the presence of targets DNA, the MBs hybridize with the targets DNA and form double-strand DNA (dsDNA), the fluorophore FAM is separated from the quencher BHQ-1, thus the fluorophore emit fluorescence. At the same time, SYBR Green I binds to dsDNA, the fluorescence intensity of SYBR Green I is significantly enhanced. When targets DNA are detected by synchronous fluorescence analysis, the fluorescence peaks of FAM and SYBR Green I overlap completely, so the fluorescence signal of system will be significantly enhanced. Thus, highly sensitive fluorescence quantitative detection for DNA can be realized. Under the optimum conditions, the total fluorescence intensity of FAM and SYBR Green I exhibits good linear dependence on concentration of targets DNA in the range from 2×10(-11) to 2.5×10(-9)M. The detection limit of target DNA is estimated to be 9×10(-12)M (3σ). Compared with previously reported methods of detection DNA with MB, the proposed method can significantly enhance the detection sensitivity. Copyright © 2014 Elsevier B.V. All rights reserved.

Molecular Descriptors

NASA Astrophysics Data System (ADS)

Consonni, Viviana; Todeschini, Roberto

In the last decades, several scientific researches have been focused on studying how to encompass and convert - by a theoretical pathway - the information encoded in the molecular structure into one or more numbers used to establish quantitative relationships between structures and properties, biological activities, or other experimental properties. Molecular descriptors are formally mathematical representations of a molecule obtained by a well-specified algorithm applied to a defined molecular representation or a well-specified experimental procedure. They play a fundamental role in chemistry, pharmaceutical sciences, environmental protection policy, toxicology, ecotoxicology, health research, and quality control. Evidence of the interest of the scientific community in the molecular descriptors is provided by the huge number of descriptors proposed up today: more than 5000 descriptors derived from different theories and approaches are defined in the literature and most of them can be calculated by means of dedicated software applications. Molecular descriptors are of outstanding importance in the research fields of quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs), where they are the independent chemical information used to predict the properties of interest. Along with the definition of appropriate molecular descriptors, the molecular structure representation and the mathematical tools for deriving and assessing models are other fundamental components of the QSAR/QSPR approach. The remarkable progress during the last few years in chemometrics and chemoinformatics has led to new strategies for finding mathematical meaningful relationships between the molecular structure and biological activities, physico-chemical, toxicological, and environmental properties of chemicals. Different approaches for deriving molecular descriptors here reviewed and some of the most relevant descriptors are presented in

Micro-matrix solid-phase dispersion coupled with MEEKC for quantitative analysis of lignans in Schisandrae Chinensis Fructus using molecular sieve TS-1 as a sorbent.

PubMed

Chu, Chu; Wei, Mengmeng; Wang, Shan; Zheng, Liqiong; He, Zheng; Cao, Jun; Yan, Jizhong

2017-09-15

A simple and effective method was developed for determining lignans in Schisandrae Chinensis Fructus by using a micro-matrix solid phase dispersion (MSPD) technique coupled with microemulsion electrokinetic chromatography (MEEKC). Molecular sieve, TS-1, was applied as a solid supporting material in micro MSPD extraction for the first time. Parameters that affect extraction efficiency, such as type of dispersant, mass ratio of the sample to the dispersant, grinding time, elution solvent and volume were optimized. The optimal extraction conditions involve dispersing 25mg of powdered Schisandrae samples with 50mg of TS-1 by a mortar and pestle. A grinding time of 150s was adopted. The blend was then transferred to a solid-phase extraction cartridge and the target analytes were eluted with 500μL of methanol. Moreover, several parameters affecting MEEKC separation were studied, including the type of oil, SDS concentration, type and concentration of cosurfactant, and concentration of organic modifier. A satisfactory linearity (R>0.9998) was obtained, and the calculated limits of quantitation were less than 2.77μg/mL. Finally, the micro MSPD-MEEKC method was successfully applied to the analysis of lignans in complex Schisandrae fructus samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.

PubMed

Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J

2013-03-01

Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.

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.

Molecular Imaging of Tumors Using a Quantitative T1 Mapping Technique via Magnetic Resonance Imaging

PubMed Central

Herrmann, Kelsey; Johansen, Mette L.; Craig, Sonya E.; Vincent, Jason; Howell, Michael; Gao, Ying; Lu, Lan; Erokwu, Bernadette; Agnes, Richard S.; Lu, Zheng-Rong; Pokorski, Jonathan K.; Basilion, James; Gulani, Vikas; Griswold, Mark; Flask, Chris; Brady-Kalnay, Susann M.

2015-01-01

Magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM) with molecular imaging agents would allow for the specific localization of brain tumors. Prior studies using T1-weighted MR imaging demonstrated that the SBK2-Tris-(Gd-DOTA)3 molecular imaging agent labeled heterotopic xenograft models of brain tumors more intensely than non-specific contrast agents using conventional T1-weighted imaging techniques. In this study, we used a dynamic quantitative T1 mapping strategy to more objectively compare intra-tumoral retention of the SBK2-Tris-(Gd-DOTA)3 agent over time in comparison to non-targeted control agents. Our results demonstrate that the targeted SBK2-Tris-(Gd-DOTA)3 agent, a scrambled-Tris-(Gd-DOTA)3 control agent, and the non-specific clinical contrast agent Optimark™ all enhanced flank tumors of human glioma cells with similar maximal changes on T1 mapping. However, the retention of the agents differs. The non-specific agents show significant recovery within 20 min by an increase in T1 while the specific agent SBK2-Tris-(Gd-DOTA)3 is retained in the tumors and shows little recovery over 60 min. The retention effect is demonstrated by percent change in T1 values and slope calculations as well as by calculations of gadolinium concentration in tumor compared to muscle. Quantitative T1 mapping demonstrates the superior binding and retention in tumors of the SBK2-Tris-(Gd-DOTA)3 agent over time compared to the non-specific contrast agent currently in clinical use. PMID:26435847

ImatraNMR: Novel software for batch integration and analysis of quantitative NMR spectra

NASA Astrophysics Data System (ADS)

Mäkelä, A. V.; Heikkilä, O.; Kilpeläinen, I.; Heikkinen, S.

2011-08-01

Quantitative NMR spectroscopy is a useful and important tool for analysis of various mixtures. Recently, in addition of traditional quantitative 1D 1H and 13C NMR methods, a variety of pulse sequences aimed for quantitative or semiquantitative analysis have been developed. To obtain actual usable results from quantitative spectra, they must be processed and analyzed with suitable software. Currently, there are many processing packages available from spectrometer manufacturers and third party developers, and most of them are capable of analyzing and integration of quantitative spectra. However, they are mainly aimed for processing single or few spectra, and are slow and difficult to use when large numbers of spectra and signals are being analyzed, even when using pre-saved integration areas or custom scripting features. In this article, we present a novel software, ImatraNMR, designed for batch analysis of quantitative spectra. In addition to capability of analyzing large number of spectra, it provides results in text and CSV formats, allowing further data-analysis using spreadsheet programs or general analysis programs, such as Matlab. The software is written with Java, and thus it should run in any platform capable of providing Java Runtime Environment version 1.6 or newer, however, currently it has only been tested with Windows and Linux (Ubuntu 10.04). The software is free for non-commercial use, and is provided with source code upon request.

Quantitative experimental monitoring of molecular diffusion in clay with positron emission tomography

NASA Astrophysics Data System (ADS)

Kulenkampff, Johannes; Zakhnini, Abdelhamid; Gründig, Marion; Lippmann-Pipke, Johanna

2016-08-01

Clay plays a prominent role as barrier material in the geosphere. The small particle sizes cause extremely small pore sizes and induce low permeability and high sorption capacity. Transport of dissolved species by molecular diffusion, driven only by a concentration gradient, is less sensitive to the pore size. Heterogeneous structures on the centimetre scale could cause heterogeneous effects, like preferential transport zones, which are difficult to assess. Laboratory measurements with diffusion cells yield limited information on heterogeneity, and pore space imaging methods have to consider scale effects. We established positron emission tomography (PET), applying a high-resolution PET scanner as a spatially resolved quantitative method for direct laboratory observation of the molecular diffusion process of a PET tracer on the prominent scale of 1-100 mm. Although PET is rather insensitive to bulk effects, quantification required significant improvements of the image reconstruction procedure with respect to Compton scatter and attenuation. The experiments were conducted with 22Na and 124I over periods of 100 and 25 days, respectively. From the images we derived trustable anisotropic diffusion coefficients and, in addition, we identified indications of preferential transport zones. We thus demonstrated the unique potential of the PET imaging modality for geoscientific process monitoring under conditions where other methods fail, taking advantage of the extremely high detection sensitivity that is typical of radiotracer applications.

Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: A quantitative proteomics approach.

PubMed

Lebesgue, Nicolas; da Costa, Gonçalo; Ribeiro, Raquel Mesquita; Ribeiro-Silva, Cristina; Martins, Gabriel G; Matranga, Valeria; Scholten, Arjen; Cordeiro, Carlos; Heck, Albert J R; Santos, Romana

2016-04-14

Marine bioadhesives have unmatched performances in wet environments, being an inspiration for biomedical applications. In sea urchins specialized adhesive organs, tube feet, mediate reversible adhesion, being composed by a disc, producing adhesive and de-adhesive secretions, and a motile stem. After tube foot detachment, the secreted adhesive remains bound to the substratum as a footprint. Sea urchin adhesive is composed by proteins and sugars, but so far only one protein, Nectin, was shown to be over-expressed as a transcript in tube feet discs, suggesting its involvement in sea urchin adhesion. Here we use high-resolution quantitative mass-spectrometry to perform the first study combining the analysis of the differential proteome of an adhesive organ, with the proteome of its secreted adhesive. This strategy allowed us to identify 163 highly over-expressed disc proteins, specifically involved in sea urchin reversible adhesion; to find that 70% of the secreted adhesive components fall within five protein groups, involved in exocytosis and microbial protection; and to provide evidences that Nectin is not only highly expressed in tube feet discs but is an actual component of the adhesive. These results give an unprecedented insight into the molecular mechanisms underlying sea urchin adhesion, and opening new doors to develop wet-reliable, reversible, and ecological biomimetic adhesives. Sea urchins attach strongly but in a reversible manner to substratum, being a valuable source of inspiration for industrial and biomedical applications. Yet, the molecular mechanisms governing reversible adhesion are still poorly studied delaying the engineering of biomimetic adhesives. We used the latest mass spectrometry techniques to analyze the differential proteome of an adhesive organ and the proteome of its secreted adhesive, allowing us to uncover the key players in sea urchin reversible adhesion. We demonstrate, that Nectin, a protein previously pointed out as potentially

Capillary Electrophoresis-Mass Spectrometry for the Analysis of Heparin Oligosaccharides and Low Molecular Weight Heparin.

PubMed

Sun, Xiaojun; Lin, Lei; Liu, Xinyue; Zhang, Fuming; Chi, Lianli; Xia, Qiangwei; Linhardt, Robert J

2016-02-02

Heparins, highly sulfated, linear polysaccharides also known as glycosaminoglycans, are among the most challenging biopolymers to analyze. Hyphenated techniques in conjunction with mass spectrometry (MS) offer rapid analysis of complex glycosaminoglycan mixtures, providing detailed structural and quantitative data. Previous analytical approaches have often relied on liquid chromatography (LC)-MS, and some have limitations including long separation times, low resolution of oligosaccharide mixtures, incompatibility of eluents, and often require oligosaccharide derivatization. This study examines the analysis of glycosaminoglycan oligosaccharides using a novel electrokinetic pump-based capillary electrophoresis (CE)-MS interface. CE separation and electrospray were optimized using a volatile ammonium bicarbonate electrolyte and a methanol-formic acid sheath fluid. The online analyses of highly sulfated heparin oligosaccharides, ranging from disaccharides to low molecular weight heparins, were performed within a 10 min time frame, offering an opportunity for higher-throughput analysis. Disaccharide compositional analysis as well as top-down analysis of low molecular weight heparin was demonstrated. Using normal polarity CE separation and positive-ion electrospray ionization MS, excellent run-to-run reproducibility (relative standard deviation of 3.6-5.1% for peak area and 0.2-0.4% for peak migration time) and sensitivity (limit of quantification of 2.0-5.9 ng/mL and limit of detection of 0.6-1.8 ng/mL) could be achieved.

Analysis of molecular interactions in solid dosage forms; challenge to molecular pharmaceutics.

PubMed

Yamamoto, Keiji; Limwikrant, Waree; Moribe, Kunikazu

2011-01-01

The molecular states of active pharmaceutical ingredients (APIs) in pharmaceutical dosage forms strongly affect the properties and quality of a drug. Various important fundamental physicochemical studies were reviewed from the standpoint of molecular pharmaceutics. Mechanochemical effects were evaluated in mixtures of APIs and pharmaceutical additives. Amorphization, complex formation and nanoparticle formation are observed after grinding process depending on the combination of APIs and pharmaceutical additives. Sealed-heating method and mesoporous materials have been used to investigate drug molecular interactions in dosage forms. Molecular states have been investigated using powder X-ray diffraction, thermal analysis, IR, solid state fluorometry, and NMR. © 2011 Pharmaceutical Society of Japan

Quantitative sampling of conformational heterogeneity of a DNA hairpin using molecular dynamics simulations and ultrafast fluorescence spectroscopy

PubMed Central

Voltz, Karine; Léonard, Jérémie; Touceda, Patricia Tourón; Conyard, Jamie; Chaker, Ziyad; Dejaegere, Annick; Godet, Julien; Mély, Yves; Haacke, Stefan; Stote, Roland H.

2016-01-01

Molecular dynamics (MD) simulations and time resolved fluorescence (TRF) spectroscopy were combined to quantitatively describe the conformational landscape of the DNA primary binding sequence (PBS) of the HIV-1 genome, a short hairpin targeted by retroviral nucleocapsid proteins implicated in the viral reverse transcription. Three 2-aminopurine (2AP) labeled PBS constructs were studied. For each variant, the complete distribution of fluorescence lifetimes covering 5 orders of magnitude in timescale was measured and the populations of conformers experimentally observed to undergo static quenching were quantified. A binary quantification permitted the comparison of populations from experimental lifetime amplitudes to populations of aromatically stacked 2AP conformers obtained from simulation. Both populations agreed well, supporting the general assumption that quenching of 2AP fluorescence results from pi-stacking interactions with neighboring nucleobases and demonstrating the success of the proposed methodology for the combined analysis of TRF and MD data. Cluster analysis of the latter further identified predominant conformations that were consistent with the fluorescence decay times and amplitudes, providing a structure-based rationalization for the wide range of fluorescence lifetimes. Finally, the simulations provided evidence of local structural perturbations induced by 2AP. The approach presented is a general tool to investigate fine structural heterogeneity in nucleic acid and nucleoprotein assemblies. PMID:26896800

Studies on the factors modulating indole-3-acetic acid production in endophytic bacterial isolates from Piper nigrum and molecular analysis of ipdc gene.

PubMed

Jasim, B; Jimtha John, C; Shimil, V; Jyothis, M; Radhakrishnan, E K

2014-09-01

The study mainly aimed quantitative analysis of IAA produced by endophytic bacteria under various conditions including the presence of extract from Piper nigrum. Analysis of genetic basis of IAA production was also conducted by studying the presence and diversity of the ipdc gene among the selected isolates. Five endophytic bacteria isolated previously from P. nigrum were used for the study. The effect of temperature, pH, agitation, tryptophan concentration and plant extract on modulating IAA production of selected isolates was analysed by colorimetric method. Comparative and quantitative analysis of IAA production by colorimetric isolates under optimal culture condition was analysed by HPTLC method. Presence of ipdc gene and thereby biosynthetic basis of IAA production among the selected isolates were studied by PCR-based amplification and subsequent insilico analysis of sequence obtained. Among the selected bacterial isolates from P. nigrum, isolate PnB 8 (Klebsiella pneumoniae) was found to have the maximum yield of IAA under various conditions optimized and was confirmed by colorimetric, HPLC and HPTLC analysis. Very interestingly, the study showed stimulating effect of phytochemicals from P. nigrum on IAA production by endophytic bacteria isolated from same plant. This study is unique because of the selection of endophytes from same source for comparative and quantitative analysis of IAA production under various conditions. Study on stimulatory effect of phytochemicals on bacterial IAA production as explained in the study is a novel approach. Studies on molecular basis of IAA production which was confirmed by sequence analysis of ipdc gene make the study scientifically attractive. Even though microbial production of IAA is well known, current report on detailed optimization, effect of plant extract and molecular confirmation of IAA biosynthesis is comparatively novel in its approach. © 2014 The Society for Applied Microbiology.

Quantitative biology of single neurons

PubMed Central

Eberwine, James; Lovatt, Ditte; Buckley, Peter; Dueck, Hannah; Francis, Chantal; Kim, Tae Kyung; Lee, Jaehee; Lee, Miler; Miyashiro, Kevin; Morris, Jacqueline; Peritz, Tiina; Schochet, Terri; Spaethling, Jennifer; Sul, Jai-Yoon; Kim, Junhyong

2012-01-01

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible. PMID:22915636

Fluorescence, Absorption, and Excitation Spectra of Polycyclic Aromatic Hydrocarbons as a Tool for Quantitative Analysis

ERIC Educational Resources Information Center

Rivera-Figueroa, A. M.; Ramazan, K. A.; Finlayson-Pitts, B. J.

2004-01-01

A quantitative and qualitative study of the interplay between absorption, fluorescence, and excitation spectra of pollutants called polycyclic aromatic hydrocarbons (PAHs) is conducted. The study of five PAH displays the correlation of the above-mentioned properties along with the associated molecular changes.

Electron-density descriptors as predictors in quantitative structure--activity/property relationships and drug design.

PubMed

Matta, Chérif F; Arabi, Alya A

2011-06-01

The use of electron density-based molecular descriptors in drug research, particularly in quantitative structure--activity relationships/quantitative structure--property relationships studies, is reviewed. The exposition starts by a discussion of molecular similarity and transferability in terms of the underlying electron density, which leads to a qualitative introduction to the quantum theory of atoms in molecules (QTAIM). The starting point of QTAIM is the topological analysis of the molecular electron-density distributions to extract atomic and bond properties that characterize every atom and bond in the molecule. These atomic and bond properties have considerable potential as bases for the construction of robust quantitative structure--activity/property relationships models as shown by selected examples in this review. QTAIM is applicable to the electron density calculated from quantum-chemical calculations and/or that obtained from ultra-high resolution x-ray diffraction experiments followed by nonspherical refinement. Atomic and bond properties are introduced followed by examples of application of each of these two families of descriptors. The review ends with a study whereby the molecular electrostatic potential, uniquely determined by the density, is used in conjunction with atomic properties to elucidate the reasons for the biological similarity of bioisosteres.

Measurement of incident molecular temperature in the formation of organic thin films

NASA Astrophysics Data System (ADS)

Abe, Takahiro; Matsubara, Ryosuke; Hayakawa, Munetaka; Shimoyama, Akifumi; Tanaka, Takaaki; Tsuji, Akira; Takahashi, Yoshikazu; Kubono, Atsushi

2018-03-01

To investigate the effects of incident molecular temperature on organic-thin-film growth by vacuum evaporation, quantitative analysis of molecular temperature is required. In this study, we propose a method of determining molecular temperature based on the heat exchange between a platinum filament and molecular vapor. Molecular temperature is estimated from filament temperature, which remains unchanged even under molecular vapor supply. The results indicate that our method has sufficient sensitivity to evaluate the molecular temperature under the typical growth rate used for fabrication of functional organic thin films.

Molecular biology of Homo sapiens: Abstracts of papers presented at the 51st Cold Spring Harbor symposium on quantitative biology

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

Watson, J.D.; Siniscalco, M.

This volume contains abstracts of papers presented at the 51st Cold Springs Harbor Symposium on Quantitative Biology. The topic for this meeting was the ''Molecular Biology of Homo sapiens.'' Sessions were entitled Human Gene Map, Human Cancer Genes, Genetic Diagnosis, Human Evolution, Drugs Made Off Human Genes, Receptors, and Gene Therapy. (DT)

Nucleolar molecular signature of pluripotent stem cells.

PubMed

Pliss, Artem; Kuzmin, Andrey N; Kachynski, Aliaksandr V; Jiang, Houbo; Hu, Zhixing; Ren, Yong; Feng, Jian; Prasad, Paras N

2013-04-02

Induced pluripotent stem cells (iPSC) are generated by reprogramming somatic cells to the pluripotent state. Identification and quantitative characterization of changes in the molecular organization of the cell during the process of cellular reprogramming is valuable for stem cell research and advancement of its therapeutic applications. Here we employ quantitative Raman microspectroscopy and biomolecular component analysis (BCA) for a comparative analysis of the molecular composition of nucleoli in skin fibroblasts and iPSC derived from them. We report that the cultured fibroblasts obtained from different human subjects, share comparable concentrations of proteins, RNA, DNA, and lipids in the molecular composition of nucleoli. The nucleolar molecular environment is drastically changed in the corresponding iPSC. We measured that the transition from skin fibroblasts to iPSC is accompanied by a statistically significant increase in protein concentrations ~1.3-fold, RNA concentrations ~1.3-fold, and DNA concentrations ~1.4-fold, while no statistically significant difference was found for the lipid concentrations. The analysis of molecular vibrations associated with diverse aminoacids and protein conformations indicates that nucleoli of skin fibroblasts contain similar subsets of proteins, with prevalence of tyrosine. In iPSC, we observed a higher signal from tryptophan with an increase in the random coil and α helix protein conformations, indicating changes in the subset of nucleolar proteins during cell reprogramming. At the same time, the concentrations of major types of macromolecules and protein conformations in the nucleoli of iPSC and human embryonic stem cells (hESC) were found to be similar. We discuss these results in the context of nucleolar function and conclude that the nucleolar molecular content is correlated with the cellular differentiation status. The approach described here shows the potential for spectroscopically monitoring changes in

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 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.

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

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

Molecular design of new aggrecanases-2 inhibitors.

PubMed

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

2013-10-01

Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications. Copyright © 2013 Elsevier Ltd. All rights reserved.

ImatraNMR: novel software for batch integration and analysis of quantitative NMR spectra.

PubMed

Mäkelä, A V; Heikkilä, O; Kilpeläinen, I; Heikkinen, S

2011-08-01

Quantitative NMR spectroscopy is a useful and important tool for analysis of various mixtures. Recently, in addition of traditional quantitative 1D (1)H and (13)C NMR methods, a variety of pulse sequences aimed for quantitative or semiquantitative analysis have been developed. To obtain actual usable results from quantitative spectra, they must be processed and analyzed with suitable software. Currently, there are many processing packages available from spectrometer manufacturers and third party developers, and most of them are capable of analyzing and integration of quantitative spectra. However, they are mainly aimed for processing single or few spectra, and are slow and difficult to use when large numbers of spectra and signals are being analyzed, even when using pre-saved integration areas or custom scripting features. In this article, we present a novel software, ImatraNMR, designed for batch analysis of quantitative spectra. In addition to capability of analyzing large number of spectra, it provides results in text and CSV formats, allowing further data-analysis using spreadsheet programs or general analysis programs, such as Matlab. The software is written with Java, and thus it should run in any platform capable of providing Java Runtime Environment version 1.6 or newer, however, currently it has only been tested with Windows and Linux (Ubuntu 10.04). The software is free for non-commercial use, and is provided with source code upon request. Copyright © 2011 Elsevier Inc. All rights reserved.

Stable Isotope Quantitative N-Glycan Analysis by Liquid Separation Techniques and Mass Spectrometry.

PubMed

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

2017-01-01

Liquid phase separation analysis and subsequent quantitation remains a challenging task for protein-derived oligosaccharides due to their inherent structural complexity and diversity. Incomplete resolution or co-detection of multiple glycan species complicates peak area-based quantitation and associated statistical analysis when optical detection methods are used. The approach outlined herein describes the utilization of stable isotope variants of commonly used fluorescent tags that allow for mass-based glycan identification and relative quantitation following separation by liquid chromatography (LC) or capillary electrophoresis (CE). Comparability assessment of glycoprotein-derived oligosaccharides is performed by derivatization with commercially available isotope variants of 2-aminobenzoic acid or aniline and analysis by LC- and CE-mass spectrometry. Quantitative information is attained from the extracted ion chromatogram/electropherogram ratios generated from the light and heavy isotope clusters.

Quantitative analysis of weak interactions by Lattice energy calculation, Hirshfeld surface and DFT studies of sulfamonomethoxine

NASA Astrophysics Data System (ADS)

Patel, Kinjal D.; Patel, Urmila H.

2017-01-01

Sulfamonomethoxine, 4-Amino-N-(6-methoxy-4-pyrimidinyl) benzenesulfonamide (C11H12N4O3S), is investigated by single crystal X-ray diffraction technique. Pair of N-H⋯N and C-H⋯O intermolecular interactions along with π···π interaction are responsible for the stability of the molecular packing of the structure. In order to understand the nature of the interactions and their quantitative contributions towards the crystal packing, the 3D Hirshfeld surface and 2D fingerprint plot analysis are carried out. PIXEL calculations are performed to determine the lattice energies correspond to intermolecular interactions in the crystal structure. Ab initio quantum chemical calculations of sulfamonomethoxine (SMM) have been performed by B3LYP method, using 6-31G** basis set with the help of Schrodinger software. The computed geometrical parameters are in good agreement with the experimental data. The Mulliken charge distribution, calculated using B3LYP method to confirm the presence of electron acceptor and electron donor atoms, responsible for intermolecular hydrogen bond interactions hence the molecular stability.

[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.

Quantitative Analysis of Subcellular Distribution of the SUMO Conjugation System by Confocal Microscopy Imaging.

PubMed

Mas, Abraham; Amenós, Montse; Lois, L Maria

2016-01-01

Different studies point to an enrichment in SUMO conjugation in the cell nucleus, although non-nuclear SUMO targets also exist. In general, the study of subcellular localization of proteins is essential for understanding their function within a cell. Fluorescence microscopy is a powerful tool for studying subcellular protein partitioning in living cells, since fluorescent proteins can be fused to proteins of interest to determine their localization. Subcellular distribution of proteins can be influenced by binding to other biomolecules and by posttranslational modifications. Sometimes these changes affect only a portion of the protein pool or have a partial effect, and a quantitative evaluation of fluorescence images is required to identify protein redistribution among subcellular compartments. In order to obtain accurate data about the relative subcellular distribution of SUMO conjugation machinery members, and to identify the molecular determinants involved in their localization, we have applied quantitative confocal microscopy imaging. In this chapter, we will describe the fluorescent protein fusions used in these experiments, and how to measure, evaluate, and compare average fluorescence intensities in cellular compartments by image-based analysis. We show the distribution of some components of the Arabidopsis SUMOylation machinery in epidermal onion cells and how they change their distribution in the presence of interacting partners or even when its activity is affected.

Inhibition of acetylcholinesterase by two genistein derivatives: kinetic analysis, molecular docking and molecular dynamics simulation.

PubMed

Fang, Jiansong; Wu, Ping; Yang, Ranyao; Gao, Li; Li, Chao; Wang, Dongmei; Wu, Song; Liu, Ai-Lin; Du, Guan-Hua

2014-12-01

In this study two genistein derivatives (G1 and G2) are reported as inhibitors of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), and differences in the inhibition of AChE are described. Although they differ in structure by a single methyl group, the inhibitory effect of G1 (IC50=264 nmol/L) on AChE was 80 times stronger than that of G2 (IC50=21,210 nmol/L). Enzyme-kinetic analysis, molecular docking and molecular dynamics (MD) simulations were conducted to better understand the molecular basis for this difference. The results obtained by kinetic analysis demonstrated that G1 can interact with both the catalytic active site and peripheral anionic site of AChE. The predicted binding free energies of two complexes calculated by the molecular mechanics/generalized born surface area (MM/GBSA) method were consistent with the experimental data. The analysis of the individual energy terms suggested that a difference between the net electrostatic contributions (ΔE ele+ΔG GB) was responsible for the binding affinities of these two inhibitors. Additionally, analysis of the molecular mechanics and MM/GBSA free energy decomposition revealed that the difference between G1 and G2 originated from interactions with Tyr124, Glu292, Val294 and Phe338 of AChE. In conclusion, the results reveal significant differences at the molecular level in the mechanism of inhibition of AChE by these structurally related compounds.

a Study of the Synchrotron Laue Method for Quantitative Crystal Structure Analysis.

NASA Astrophysics Data System (ADS)

Gomez de Anderez, Dora M.

1990-01-01

Available from UMI in association with The British Library. Quantitative crystal structure analyses have been carried out on small molecule crystals using synchrotron radiation and the Laue method. A variety of single crystal structure determinations and associated refinements are used and compared with the monochromatic analyses. The new molecular structure of 7-amino-5-bromo -4-methyl-2-oxo-1,2,3,4-tetrahidro-1, 6 -naphthyridine-8-carbonitrile (C_{10 }H_9ON_4 Br.H_2O) has been determined, first using monochromatic Mo Kalpha radiation and a four-circle diffractometer, then using synchrotron Laue diffraction photography. The structure refinements showed a R-factor of 4.97 and 14.0% for the Mo Kalpha and Laue data respectively. The molecular structure of (S)-2-chloro-2-fluoro-N-((S)-1-phenylethyl) ethanamide, (C_{10}H _{11}ClFNO), has been determined using the same crystal throughout for X-ray monochromatic analyses (Mo Kalpha and Cu K alpha) followed by synchrotron Laue data collection. The Laue and monochromatic data compare favourably. The R -factors (on F) were 6.23, 6.45 and 8.19% for the Mo K alpha, Cu Kalpha and Laue data sets respectively. The molecular structure of 3-(5-hydroxy-3-methyl-1-phenylpyrazol-4-yl)-1,3-diphenyl -prop- 2-en-1-one, (C_{25 }H_{20}N _2O_2) has been determined using the synchrotron Laue method. The results compare very well with Mo Kalpha monochromatic data. The R-factors (on F) were 4.60 and 5.29% for Mo Kalpha and Laue analysis respectively. The Laue method is assessed in locating the 20 hydrogen atoms in this structure. The structure analysis of the benzil compound ((C_6H_5 O.CO_2)) is carried out using the synchrotron Laue method firstly at room temperature and secondly at low temperature -114 ^circC. The structure shows an R-factor (on F) of 13.06% and 6.85% for each data set respectively. The synchrotron Laue method was used to collect data for ergocalciferol (Vitamin D_2). The same crystal was also used to record oscillation

Quantitative collision induced mass spectrometry of substituted piperazines - A correlative analysis between theory and experiment

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka; Spiteller, Michael

2017-12-01

The present paper deals with quantitative kinetics and thermodynamics of collision induced dissociation (CID) reactions of piperazines under different experimental conditions together with a systematic description of effect of counter-ions on common MS fragment reactions of piperazines; and intra-molecular effect of quaternary cyclization of substituted piperazines yielding to quaternary salts. There are discussed quantitative model equations of rate constants as well as free Gibbs energies of series of m-independent CID fragment processes in GP, which have been evidenced experimentally. Both kinetic and thermodynamic parameters are also predicted by computational density functional theory (DFT) and ab initio both static and dynamic methods. The paper examines validity of Maxwell-Boltzmann distribution to non-Boltzmann CID processes in quantitatively as well. The experiments conducted within the latter framework yield to an excellent correspondence with theoretical quantum chemical modeling. The important property of presented model equations of reaction kinetics is the applicability in predicting unknown and assigning of known mass spectrometric (MS) patterns. The nature of "GP" continuum of CID-MS coupled scheme of measurements with electrospray ionization (ESI) source is discussed, performing parallel computations in gas-phase (GP) and polar continuum at different temperatures and ionic strengths. The effect of pressure is presented. The study contributes significantly to methodological and phenomenological developments of CID-MS and its analytical implementations for quantitative and structural analyses. It also demonstrates great prospective of a complementary application of experimental CID-MS and computational quantum chemistry studying chemical reactivity, among others. To a considerable extend this work underlies the place of computational quantum chemistry to the field of experimental analytical chemistry in particular highlighting the structural analysis.

[Research progress of molecular genetic analysis in Schistosoma variation].

PubMed

Zheng, Su-Yue; Li, Fei

2014-02-01

The development of molecular biology techniques makes important contributions to the researches of heritable variation of Schistosoma. In recent years, the molecular genetic analysis in the Schistosoma variation researches mainly includes the restriction fragment length polymorphism (RFLP), random amplified polymorphism technology (RAPD), microsatellite anchored PCR (SSR-PCR), and polymerase reaction single-strand conformation polymorphism (PCR-SSCP). This article reviews the research progress of molecular genetic analysis in Schistosoma variation in recent years.

Stand-off molecular composition analysis

NASA Astrophysics Data System (ADS)

Hughes, Gary B.; Lubin, Philip; Meinhold, Peter; O'Neill, Hugh; Brashears, Travis; Zhang, Qicheng; Griswold, Janelle; Riley, Jordan; Motta, Caio

2015-09-01

Molecular composition of distant stars is explored by observing absorption spectra. The star produces blackbody radiation that passes through the molecular cloud of vaporized material surrounding the star. Characteristic absorption lines are discernible with a spectrometer, and molecular composition is investigated by comparing spectral observations with known material profiles. Most objects in the solar system—asteroids, comets, planets, moons—are too cold to be interrogated in this manner. Molecular clouds around cold objects consist primarily of volatiles, so bulk composition cannot be probed. Additionally, low volatile density does not produce discernible absorption lines in the faint signal generated by low blackbody temperatures. This paper describes a system for probing the molecular composition of cold solar system targets from a distant vantage. The concept utilizes a directed energy beam to melt and vaporize a spot on a distant target, such as from a spacecraft orbiting the object. With sufficient flux (~10 MW/m2), the spot temperature rises rapidly (to ~2 500 K), and evaporation of all materials on the target surface occurs. The melted spot creates a high-temperature blackbody source, and ejected material creates a molecular plume in front of the spot. Bulk composition is investigated by using a spectrometer to view the heated spot through the ejected material. Spatial composition maps could be created by scanning the surface. Applying the beam to a single spot continuously produces a borehole, and shallow sub-surface composition profiling is also possible. Initial simulations of absorption profiles with laser heating show great promise for molecular composition analysis.

Principles of quantitation of viral loads using nucleic acid sequence-based amplification in combination with homogeneous detection using molecular beacons.

PubMed

Weusten, Jos J A M; Carpay, Wim M; Oosterlaken, Tom A M; van Zuijlen, Martien C A; van de Wiel, Paul A

2002-03-15

For quantitative NASBA-based viral load assays using homogeneous detection with molecular beacons, such as the NucliSens EasyQ HIV-1 assay, a quantitation algorithm is required. During the amplification process there is a constant growth in the concentration of amplicons to which the beacon can bind while generating a fluorescence signal. The overall fluorescence curve contains kinetic information on both amplicon formation and beacon binding, but only the former is relevant for quantitation. In the current paper, mathematical modeling of the relevant processes is used to develop an equation describing the fluorescence curve as a function of the amplification time and the relevant kinetic parameters. This equation allows reconstruction of RNA formation, which is characterized by an exponential increase in concentrations as long as the primer concentrations are not rate limiting and by linear growth over time after the primer pool is depleted. During the linear growth phase, the actual quantitation is based on assessing the amplicon formation rate from the viral RNA relative to that from a fixed amount of calibrator RNA. The quantitation procedure has been successfully applied in the NucliSens EasyQ HIV-1 assay.

Improved method and apparatus for chromatographic quantitative analysis

DOEpatents

Fritz, J.S.; Gjerde, D.T.; Schmuckler, G.

An improved apparatus and method are described for the quantitative analysis of a solution containing a plurality of anion species by ion exchange chromatography which utilizes a single element and a single ion exchange bed which does not require periodic regeneration. The solution containing the anions is added to an anion exchange resin bed which is a low capacity macroreticular polystyrene-divinylbenzene resin containing quarternary ammonium functional groups, and is eluted therefrom with a dilute solution of a low electrical conductance organic acid salt. As each anion species is eluted from the bed, it is quantitatively sensed by conventional detection means such as a conductivity cell.

A comparative analysis of the effectiveness of cytogenetic and molecular genetic methods in the detection of Down syndrome.

PubMed

Mačkić-Đurović, Mirela; Projić, Petar; Ibrulj, Slavka; Cakar, Jasmina; Marjanović, Damir

2014-05-01

The goal of this study was to examine the effectiveness of 6 STR markers application (D21S1435, D21S11, D21S1270, D21S1411, D21S226 and IFNAR) in molecular genetic diagnostics of Down syndrome (DS) and to compare it with cytogenetic method. Testing was performed on 73 children, with the previously cytogenetically confirmed Down syndrome. DNA isolated from the buccal swab was used. Previously mentioned loci located on chromosome 21 were simultaneously amplified using quantitative fluorescence PCR (QF PCR). Using this method, 60 previously cytogenetically diagnosed DS with standard type of trisomy 21 were confirmed. Furthermore, six of eight children with mosaic type of DS were detected. Two false negative results for mosaic type of DS were obtained. Finally, five children with the translocation type of Down syndrome were also confirmed with this molecular test. In conclusion, molecular genetic analysis of STR loci is fast, cheap and simple method that could be used in detection of DS. Regarding possible false results detected for certain number of mosaic types, cytogenetic analysis should be used as a confirmatory test.

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.

PubMed

Walker, Martin; Basáñez, María-Gloria; Ouédraogo, André Lin; Hermsen, Cornelus; Bousema, Teun; Churcher, Thomas S

2015-01-16

Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.

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...

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

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.

[Quantitative relationship between gas chromatographic retention time and structural parameters of alkylphenols].

PubMed

Ruan, Xiaofang; Zhang, Ruisheng; Yao, Xiaojun; Liu, Mancang; Fan, Botao

2007-03-01

Alkylphenols are a group of permanent pollutants in the environment and could adversely disturb the human endocrine system. It is therefore important to effectively separate and measure the alkylphenols. To guide the chromatographic analysis of these compounds in practice, the development of quantitative relationship between the molecular structure and the retention time of alkylphenols becomes necessary. In this study, topological, constitutional, geometrical, electrostatic and quantum-chemical descriptors of 44 alkylphenols were calculated using a software, CODESSA, and these descriptors were pre-selected using the heuristic method. As a result, three-descriptor linear model (LM) was developed to describe the relationship between the molecular structure and the retention time of alkylphenols. Meanwhile, the non-linear regression model was also developed based on support vector machine (SVM) using the same three descriptors. The correlation coefficient (R(2)) for the LM and SVM was 0.98 and 0. 92, and the corresponding root-mean-square error was 0. 99 and 2. 77, respectively. By comparing the stability and prediction ability of the two models, it was found that the linear model was a better method for describing the quantitative relationship between the retention time of alkylphenols and the molecular structure. The results obtained suggested that the linear model could be applied for the chromatographic analysis of alkylphenols with known molecular structural parameters.

Understanding molecular structure from molecular mechanics.

PubMed

Allinger, Norman L

2011-04-01

Molecular mechanics gives us a well known model of molecular structure. It is less widely recognized that valence bond theory gives us structures which offer a direct interpretation of molecular mechanics formulations and parameters. The electronic effects well-known in physical organic chemistry can be directly interpreted in terms of valence bond structures, and hence quantitatively calculated and understood. The basic theory is outlined in this paper, and examples of the effects, and their interpretation in illustrative examples is presented.

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.

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.

Quantitative High-Resolution Genomic Analysis of Single Cancer Cells

PubMed Central

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A.; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics. PMID:22140428

Quantitative high-resolution genomic analysis of single cancer cells.

PubMed

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

Quantitative secondary ion mass spectrometric analysis of secondary ion polarity in GaN films implanted with oxygen

NASA Astrophysics Data System (ADS)

Hashiguchi, Minako; Sakaguchi, Isao; Adachi, Yutaka; Ohashi, Naoki

2016-10-01

Quantitative analyses of N and O ions in GaN thin films implanted with oxygen ions (16O+) were conducted by secondary ion mass spectrometry (SIMS). Positive (CsM+) and negative secondary ions extracted by Cs+ primary ion bombardment were analyzed for oxygen quantitative analysis. The oxygen depth profiles were obtained using two types of primary ion beams: a Gaussian-type beam and a broad spot beam. The oxygen peak concentrations in GaN samples were from 3.2 × 1019 to 7.0 × 1021 atoms/cm3. The depth profiles show equivalent depth resolutions in the two analyses. The intensity of negative oxygen ions was approximately two orders of magnitude higher than that of positive ions. In contrast, the O/N intensity ratio measured using CsM+ molecular ions was close to the calculated atomic density ratio, indicating that the SIMS depth profiling using CsM+ ions is much more effective for the measurements of O and N ions in heavy O-implanted GaN than that using negative ions.

Preliminary evidence for associations between molecular markers and quantitative traits in a set of bread wheat (Triticum aestivum L.) cultivars and breeding lines.

PubMed

Abdollahi Mandoulakani, Babak; Nasri, Shilan; Dashchi, Sahar; Arzhang, Sorour; Bernousi, Iraj; Abbasi Holasou, Hossein

The identification of polymorphic markers associated with various quantitative traits allows us to test their performance for the exploitation of the extensive quantitative variation maintained in gene banks. In the current study, a set of 97 wheat germplasm accessions including 48 cultivars and 49 breeding lines were evaluated for 18 agronomic traits. The accessions were also genotyped with 23 ISSR, nine IRAP and 20 REMAP markers, generating a total of 658 clear and scorable bands, 86% of which were polymorphic. Both neighbor-joining dendrogram and Bayesian analysis of clustering of individuals revealed that the accessions could be divided into four genetically distinct groups, indicating the presence of a population structure in current wheat germplasm. Associations between molecular markers and 18 agronomic traits were analyzed using the mixed linear model (MLM) approach. A total of 94 loci were found to be significantly associated with agronomic traits (P≤0.01). The highest number of bands significantly associated with the 18 traits varied from 11 for number of spikelets spike -1 (NSS) to two for grain yield in row (GRY). Loci ISSR16-9 and REMAP13-10 were associated with three different traits. The results of the current study provide useful information about the performance of retrotransposon-based and ISSR molecular markers that could be helpful in selecting potentially elite gene bank samples for wheat-breeding programs. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Molecular and agronomic analysis of intraspecific variability in Capsicum baccatum var. pendulum accessions.

PubMed

Leite, P S S; Rodrigues, R; Silva, R N O; Pimenta, S; Medeiros, A M; Bento, C S; Gonçalves, L S A

2016-10-05

Capsicum baccatum is one of the most important chili peppers in South America, since this region is considered to be the center of origin and diversity of this species. In Brazil, C. baccatum has been widely explored by family farmers and there are different local names for each fruit phenotype, such as cambuci and dedo-de-moça (lady's finger). Although very popular among farmers and consumers, C. baccatum has been less extensively studied than other Capsicum species. This study describes the phenotypic and genotypic variability in C. baccatum var. pendulum accessions. Twenty-nine accessions from the Universidade Estadual do Norte Fluminense Darcy Ribeiro gene bank, and one commercial genotype ('BRS-Mari') were evaluated for 53 morphoagronomic descriptors (31 qualitative and 22 quantitative traits). In addition, accessions were genotyped using 30 microsatellite primers. Three accessions from the C. annuum complex were included in the molecular characterization. Nine of 31 qualitative descriptors were monomorphic, while all quantitative descriptors were highly significant different between accessions (P < 0.01). Using the unweighted pair group method using arithmetic averages, four groups were obtained based on multicategoric variables and five groups were obtained based on quantitative variables. In the genotyping analysis, 12 polymorphic simple sequence repeat primers amplified in C. baccatum with dissimilarity between accessions ranging from 0.13 to 0.91, permitting the formation of two distinct groups for Bayesian analysis. These results indicate wide variability among the accessions comparing phenotypic and genotypic data and revealed distinct patterns of dissimilarity between matrices, indicating that both steps are valuable for the characterization of C. baccatum var. pendulum accessions.

Benefit-risk analysis : a brief review and proposed quantitative approaches.

PubMed

Holden, William L

2003-01-01

Given the current status of benefit-risk analysis as a largely qualitative method, two techniques for a quantitative synthesis of a drug's benefit and risk are proposed to allow a more objective approach. The recommended methods, relative-value adjusted number-needed-to-treat (RV-NNT) and its extension, minimum clinical efficacy (MCE) analysis, rely upon efficacy or effectiveness data, adverse event data and utility data from patients, describing their preferences for an outcome given potential risks. These methods, using hypothetical data for rheumatoid arthritis drugs, demonstrate that quantitative distinctions can be made between drugs which would better inform clinicians, drug regulators and patients about a drug's benefit-risk profile. If the number of patients needed to treat is less than the relative-value adjusted number-needed-to-harm in an RV-NNT analysis, patients are willing to undergo treatment with the experimental drug to derive a certain benefit knowing that they may be at risk for any of a series of potential adverse events. Similarly, the results of an MCE analysis allow for determining the worth of a new treatment relative to an older one, given not only the potential risks of adverse events and benefits that may be gained, but also by taking into account the risk of disease without any treatment. Quantitative methods of benefit-risk analysis have a place in the evaluative armamentarium of pharmacovigilance, especially those that incorporate patients' perspectives.

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.

Quantitative risk analysis of oil storage facilities in seismic areas.

PubMed

Fabbrocino, Giovanni; Iervolino, Iunio; Orlando, Francesca; Salzano, Ernesto

2005-08-31

Quantitative risk analysis (QRA) of industrial facilities has to take into account multiple hazards threatening critical equipment. Nevertheless, engineering procedures able to evaluate quantitatively the effect of seismic action are not well established. Indeed, relevant industrial accidents may be triggered by loss of containment following ground shaking or other relevant natural hazards, either directly or through cascade effects ('domino effects'). The issue of integrating structural seismic risk into quantitative probabilistic seismic risk analysis (QpsRA) is addressed in this paper by a representative study case regarding an oil storage plant with a number of atmospheric steel tanks containing flammable substances. Empirical seismic fragility curves and probit functions, properly defined both for building-like and non building-like industrial components, have been crossed with outcomes of probabilistic seismic hazard analysis (PSHA) for a test site located in south Italy. Once the seismic failure probabilities have been quantified, consequence analysis has been performed for those events which may be triggered by the loss of containment following seismic action. Results are combined by means of a specific developed code in terms of local risk contour plots, i.e. the contour line for the probability of fatal injures at any point (x, y) in the analysed area. Finally, a comparison with QRA obtained by considering only process-related top events is reported for reference.

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

Molecular clustering of patients with diabetes and pulmonary tuberculosis: A systematic review and meta-analysis.

PubMed

Blanco-Guillot, Francles; Delgado-Sánchez, Guadalupe; Mongua-Rodríguez, Norma; Cruz-Hervert, Pablo; Ferreyra-Reyes, Leticia; Ferreira-Guerrero, Elizabeth; Yanes-Lane, Mercedes; Montero-Campos, Rogelio; Bobadilla-Del-Valle, Miriam; Torres-González, Pedro; Ponce-de-León, Alfredo; Sifuentes-Osornio, José; Garcia-Garcia, Lourdes

2017-01-01

Many studies have explored the relationship between diabetes mellitus (DM) and tuberculosis (TB) demonstrating increased risk of TB among patients with DM and poor prognosis of patients suffering from the association of DM/TB. Owing to a paucity of studies addressing this question, it remains unclear whether patients with DM and TB are more likely than TB patients without DM to be grouped into molecular clusters defined according to the genotype of the infecting Mycobacterium tuberculosis bacillus. That is, whether there is convincing molecular epidemiological evidence for TB transmission among DM patients. Objective: We performed a systematic review and meta-analysis to quantitatively evaluate the propensity for patients with DM and pulmonary TB (PTB) to cluster according to the genotype of the infecting M. tuberculosis bacillus. We conducted a systematic search in MEDLINE and LILACS from 1990 to June, 2016 with the following combinations of key words "tuberculosis AND transmission" OR "tuberculosis diabetes mellitus" OR "Mycobacterium tuberculosis molecular epidemiology" OR "RFLP-IS6110" OR "Spoligotyping" OR "MIRU-VNTR". Studies were included if they met the following criteria: (i) studies based on populations from defined geographical areas; (ii) use of genotyping by IS6110- restriction fragment length polymorphism (RFLP) analysis and spoligotyping or mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) or other amplification methods to identify molecular clustering; (iii) genotyping and analysis of 50 or more cases of PTB; (iv) study duration of 11 months or more; (v) identification of quantitative risk factors for molecular clustering including DM; (vi) > 60% coverage of the study population; and (vii) patients with PTB confirmed bacteriologically. The exclusion criteria were: (i) Extrapulmonary TB; (ii) TB caused by nontuberculous mycobacteria; (iii) patients with PTB and HIV; (iv) pediatric PTB patients; (v) TB in closed

Molecular clustering of patients with diabetes and pulmonary tuberculosis: A systematic review and meta-analysis

PubMed Central

Blanco-Guillot, Francles; Delgado-Sánchez, Guadalupe; Mongua-Rodríguez, Norma; Cruz-Hervert, Pablo; Ferreyra-Reyes, Leticia; Ferreira-Guerrero, Elizabeth; Yanes-Lane, Mercedes; Montero-Campos, Rogelio; Bobadilla-del-Valle, Miriam; Torres-González, Pedro; Ponce-de-León, Alfredo; Sifuentes-Osornio, José; Garcia-Garcia, Lourdes

2017-01-01

Introduction Many studies have explored the relationship between diabetes mellitus (DM) and tuberculosis (TB) demonstrating increased risk of TB among patients with DM and poor prognosis of patients suffering from the association of DM/TB. Owing to a paucity of studies addressing this question, it remains unclear whether patients with DM and TB are more likely than TB patients without DM to be grouped into molecular clusters defined according to the genotype of the infecting Mycobacterium tuberculosis bacillus. That is, whether there is convincing molecular epidemiological evidence for TB transmission among DM patients. Objective: We performed a systematic review and meta-analysis to quantitatively evaluate the propensity for patients with DM and pulmonary TB (PTB) to cluster according to the genotype of the infecting M. tuberculosis bacillus. Materials and methods We conducted a systematic search in MEDLINE and LILACS from 1990 to June, 2016 with the following combinations of key words “tuberculosis AND transmission” OR “tuberculosis diabetes mellitus” OR “Mycobacterium tuberculosis molecular epidemiology” OR “RFLP-IS6110” OR “Spoligotyping” OR “MIRU-VNTR”. Studies were included if they met the following criteria: (i) studies based on populations from defined geographical areas; (ii) use of genotyping by IS6110- restriction fragment length polymorphism (RFLP) analysis and spoligotyping or mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) or other amplification methods to identify molecular clustering; (iii) genotyping and analysis of 50 or more cases of PTB; (iv) study duration of 11 months or more; (v) identification of quantitative risk factors for molecular clustering including DM; (vi) > 60% coverage of the study population; and (vii) patients with PTB confirmed bacteriologically. The exclusion criteria were: (i) Extrapulmonary TB; (ii) TB caused by nontuberculous mycobacteria; (iii) patients with

Molecular inversion probe assay for allelic quantitation

PubMed Central

Ji, Hanlee; Welch, Katrina

2010-01-01

Molecular inversion probe (MIP) technology has been demonstrated to be a robust platform for large-scale dual genotyping and copy number analysis. Applications in human genomic and genetic studies include the possibility of running dual germline genotyping and combined copy number variation ascertainment. MIPs analyze large numbers of specific genetic target sequences in parallel, relying on interrogation of a barcode tag, rather than direct hybridization of genomic DNA to an array. The MIP approach does not replace, but is complementary to many of the copy number technologies being performed today. Some specific advantages of MIP technology include: Less DNA required (37 ng vs. 250 ng), DNA quality less important, more dynamic range (amplifications detected up to copy number 60), allele specific information “cleaner” (less SNP crosstalk/contamination), and quality of markers better (fewer individual MIPs versus SNPs needed to identify copy number changes). MIPs can be considered a candidate gene (targeted whole genome) approach and can find specific areas of interest that otherwise may be missed with other methods. PMID:19488872

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 .

Quantitative Resistance: More Than Just Perception of a Pathogen.

PubMed

Corwin, Jason A; Kliebenstein, Daniel J

2017-04-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. © 2017 American Society of Plant Biologists. All rights reserved.

Quantitative Resistance: More Than Just Perception of a Pathogen

PubMed Central

2017-01-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. PMID:28302676

Comparative study of standard space and real space analysis of quantitative MR brain data.

PubMed

Aribisala, Benjamin S; He, Jiabao; Blamire, Andrew M

2011-06-01

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space. Copyright © 2011 Wiley-Liss, Inc.

Quantitation of tumor uptake with molecular breast imaging.

PubMed

Bache, Steven T; Kappadath, S Cheenu

2017-09-01

We developed scatter and attenuation-correction techniques for quantifying images obtained with Molecular Breast Imaging (MBI) systems. To investigate scatter correction, energy spectra of a 99m Tc point source were acquired with 0-7-cm-thick acrylic to simulate scatter between the detector heads. System-specific scatter correction factor, k, was calculated as a function of thickness using a dual energy window technique. To investigate attenuation correction, a 7-cm-thick rectangular phantom containing 99m Tc-water simulating breast tissue and fillable spheres simulating tumors was imaged. Six spheres 10-27 mm in diameter were imaged with sphere-to-background ratios (SBRs) of 3.5, 2.6, and 1.7 and located at depths of 0.5, 1.5, and 2.5 cm from the center of the water bath for 54 unique tumor scenarios (3 SBRs × 6 sphere sizes × 3 depths). Phantom images were also acquired in-air under scatter- and attenuation-free conditions, which provided ground truth counts. To estimate true counts, T, from each tumor, the geometric mean (GM) of the counts within a prescribed region of interest (ROI) from the two projection images was calculated as T=C1C2eμtF, where C are counts within the square ROI circumscribing each sphere on detectors 1 and 2, μ is the linear attenuation coefficient of water, t is detector separation, and the factor F accounts for background activity. Four unique F definitions-standard GM, background-subtraction GM, MIRD Primer 16 GM, and a novel "volumetric GM"-were investigated. Error in T was calculated as the percentage difference with respect to in-air. Quantitative accuracy using the different GM definitions was calculated as a function of SBR, depth, and sphere size. Sensitivity of quantitative accuracy to ROI size was investigated. We developed an MBI simulation to investigate the robustness of our corrections for various ellipsoidal tumor shapes and detector separations. Scatter correction factor k varied slightly (0.80-0.95) over a compressed

Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.

PubMed

Gao, Yi; Bouix, Sylvain

2016-05-01

Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative sampling of conformational heterogeneity of a DNA hairpin using molecular dynamics simulations and ultrafast fluorescence spectroscopy.

PubMed

Voltz, Karine; Léonard, Jérémie; Touceda, Patricia Tourón; Conyard, Jamie; Chaker, Ziyad; Dejaegere, Annick; Godet, Julien; Mély, Yves; Haacke, Stefan; Stote, Roland H

2016-04-20

Molecular dynamics (MD) simulations and time resolved fluorescence (TRF) spectroscopy were combined to quantitatively describe the conformational landscape of the DNA primary binding sequence (PBS) of the HIV-1 genome, a short hairpin targeted by retroviral nucleocapsid proteins implicated in the viral reverse transcription. Three 2-aminopurine (2AP) labeled PBS constructs were studied. For each variant, the complete distribution of fluorescence lifetimes covering 5 orders of magnitude in timescale was measured and the populations of conformers experimentally observed to undergo static quenching were quantified. A binary quantification permitted the comparison of populations from experimental lifetime amplitudes to populations of aromatically stacked 2AP conformers obtained from simulation. Both populations agreed well, supporting the general assumption that quenching of 2AP fluorescence results from pi-stacking interactions with neighboring nucleobases and demonstrating the success of the proposed methodology for the combined analysis of TRF and MD data. Cluster analysis of the latter further identified predominant conformations that were consistent with the fluorescence decay times and amplitudes, providing a structure-based rationalization for the wide range of fluorescence lifetimes. Finally, the simulations provided evidence of local structural perturbations induced by 2AP. The approach presented is a general tool to investigate fine structural heterogeneity in nucleic acid and nucleoprotein assemblies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Quantitative structure-activity relationship and molecular docking of artemisinin derivatives to vascular endothelial growth factor receptor 1.

PubMed

Saeed, Mohamed E M; Kadioglu, Onat; Seo, Ean-Jeong; Greten, Henry Johannes; Brenk, Ruth; Efferth, Thomas

2015-04-01

The antimalarial drug artemisinin has been shown to exert anticancer activity through anti-angiogenic effects. For further drug development, it may be useful to have derivatives with improved anti-angiogenic properties. We performed molecular docking of 52 artemisinin derivatives to vascular endothelial growth factor receptors (VEGFR1, VEGFR2), and VEGFA ligand using Autodock4 and AutodockTools-1.5.7.rc1 using the Lamarckian genetic algorithm. Quantitative structure-activity relationship (QSAR) analyses of the compounds prepared by Corina Molecular Networks were performed using the Molecular Operating Environment MOE 2012.10. A statistically significant inverse relationship was obtained between in silico binding energies to VEGFR1 and anti-angiogenic activity in vivo of a test-set of artemisinin derivatives (R=-0.843; p=0.035). This served as a control experiment to validate molecular docking predicting anti-angiogenc effects. Furthermore, 52 artemisinin derivatives were docked to VEGFR1 and in selected examples also to VEGFR2 and VEGFA. Higher binding affinities were calculated for receptors than for the ligand. The best binding affinities to VEGFR1 were found for an artemisinin dimer, 10-dihydroartemisinyl-2-propylpentanoate, and dihydroartemisinin α-hemisuccinate sodium salt. QSAR analyses revealed significant relationships between VEGFR1 binding energies and defined molecular descriptors of 35 artemisinins assigned to the training set (R=0.0848, p<0.0001) and 17 derivatives assigned to the test set (R=0.761, p<0.001). Molecular docking and QSAR calculations can be used to identify novel artemisinin derivatives with anti-angiogenic effects. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Role Of Social Networks In Resilience Of Naval Recruits: A Quantitative Analysis

DTIC Science & Technology

2016-06-01

comprises 1,297 total surveys from a total of eight divisions of recruits at two different time periods. Quantitative analyses using surveys and network... surveys from a total of eight divisions of recruits at two different time periods. Quantitative analyses using surveys and network data examine the effects...NETWORKS IN RESILIENCE OF NAVAL RECRUITS: A QUANTITATIVE ANALYSIS by Andrea M. Watling June 2016 Thesis Advisor: Edward H. Powley Co

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.

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.

Quantitative analysis of diffusion tensor orientation: theoretical framework.

PubMed

Wu, Yu-Chien; Field, Aaron S; Chung, Moo K; Badie, Benham; Alexander, Andrew L

2004-11-01

Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing. (c) 2004 Wiley-Liss, Inc.

A simple approach to quantitative analysis using three-dimensional spectra based on selected Zernike moments.

PubMed

Zhai, Hong Lin; Zhai, Yue Yuan; Li, Pei Zhen; Tian, Yue Li

2013-01-21

A very simple approach to quantitative analysis is proposed based on the technology of digital image processing using three-dimensional (3D) spectra obtained by high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD). As the region-based shape features of a grayscale image, Zernike moments with inherently invariance property were employed to establish the linear quantitative models. This approach was applied to the quantitative analysis of three compounds in mixed samples using 3D HPLC-DAD spectra, and three linear models were obtained, respectively. The correlation coefficients (R(2)) for training and test sets were more than 0.999, and the statistical parameters and strict validation supported the reliability of established models. The analytical results suggest that the Zernike moment selected by stepwise regression can be used in the quantitative analysis of target compounds. Our study provides a new idea for quantitative analysis using 3D spectra, which can be extended to the analysis of other 3D spectra obtained by different methods or instruments.

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

Quantitative analysis of flavanones from citrus fruits by using mesoporous molecular sieve-based miniaturized solid phase extraction coupled to ultrahigh-performance liquid chromatography and quadrupole time-of-flight mass spectrometry.

PubMed

Cao, Wan; Ye, Li-Hong; Cao, Jun; Xu, Jing-Jing; Peng, Li-Qing; Zhu, Qiong-Yao; Zhang, Qian-Yun; Hu, Shuai-Shuai

2015-08-07

An analytical procedure based on miniaturized solid phase extraction (SPE) and ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry was developed and validated for determination of six flavanones in Citrus fruits. The mesoporous molecular sieve SBA-15 as a solid sorbent was characterised by Fourier transform-infrared spectroscopy and scanning electron microscopy. Additionally, compared with reported extraction techniques, the mesoporous SBA-15 based SPE method possessed the advantages of shorter analysis time and higher sensitivity. Furthermore, considering the different nature of the tested compounds, all of the parameters, including the SBA-15 amount, solution pH, elution solvent, and the sorbent type, were investigated in detail. Under the optimum condition, the instrumental detection and quantitation limits calculated were less than 4.26 and 14.29ngmL(-1), respectively. The recoveries obtained for all the analytes were ranging from 89.22% to 103.46%. The experimental results suggested that SBA-15 was a promising material for the purification and enrichment of target flavanones from complex citrus fruit samples. Copyright © 2015 Elsevier B.V. All rights reserved.

A Comparative Assessment of Greek Universities' Efficiency Using Quantitative Analysis

ERIC Educational Resources Information Center

Katharaki, Maria; Katharakis, George

2010-01-01

In part due to the increased demand for higher education, typical evaluation frameworks for universities often address the key issue of available resource utilisation. This study seeks to estimate the efficiency of 20 public universities in Greece through quantitative analysis (including performance indicators, data envelopment analysis (DEA) and…

Quantitative ROESY analysis of computational models: structural studies of citalopram and β-cyclodextrin complexes by (1) H-NMR and computational methods.

PubMed

Ali, Syed Mashhood; Shamim, Shazia

2015-07-01

Complexation of racemic citalopram with β-cyclodextrin (β-CD) in aqueous medium was investigated to determine atom-accurate structure of the inclusion complexes. (1) H-NMR chemical shift change data of β-CD cavity protons in the presence of citalopram confirmed the formation of 1 : 1 inclusion complexes. ROESY spectrum confirmed the presence of aromatic ring in the β-CD cavity but whether one of the two or both rings was not clear. Molecular mechanics and molecular dynamic calculations showed the entry of fluoro-ring from wider side of β-CD cavity as the most favored mode of inclusion. Minimum energy computational models were analyzed for their accuracy in atomic coordinates by comparison of calculated and experimental intermolecular ROESY peak intensities, which were not found in agreement. Several least energy computational models were refined and analyzed till calculated and experimental intensities were compatible. The results demonstrate that computational models of CD complexes need to be analyzed for atom-accuracy and quantitative ROESY analysis is a promising method. Moreover, the study also validates that the quantitative use of ROESY is feasible even with longer mixing times if peak intensity ratios instead of absolute intensities are used. Copyright © 2015 John Wiley & Sons, Ltd.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

PubMed

McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

2012-04-01

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

PubMed Central

McGuire, Mary F.; Iyengar, M. Sriram; Mercer, David W.

2012-01-01

Motivation Although trauma is the leading cause of death for those below 45 years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. Results In the node/molecular analysis of the first 24 hours from trauma, PSA uncovered 7 molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which 3 molecules had not been previously associated with any shock / trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships – activation, expression, inhibition, and transcription – and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

PubMed Central

Giger, Maryellen L.; Chan, Heang-Ping; Boone, John

2008-01-01

algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more—from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis. PMID:19175137

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

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

Giger, Maryellen L.; Chan, Heang-Ping; Boone, John

2008-12-15

algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more--from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.« less

[Correspondence analysis between traditional commercial specifications and quantitative quality indices of Notopterygii Rhizoma et Radix].

PubMed

Jiang, Shun-Yuan; Sun, Hong-Bing; Sun, Hui; Ma, Yu-Ying; Chen, Hong-Yu; Zhu, Wen-Tao; Zhou, Yi

2016-03-01

This paper aims to explore a comprehensive assessment method combined traditional Chinese medicinal material specifications with quantitative quality indicators. Seventy-six samples of Notopterygii Rhizoma et Radix were collected on market and at producing areas. Traditional commercial specifications were described and assigned, and 10 chemical components and volatile oils were determined for each sample. Cluster analysis, Fisher discriminant analysis and correspondence analysis were used to establish the relationship between the traditional qualitative commercial specifications and quantitative chemical indices for comprehensive evaluating quality of medicinal materials, and quantitative classification of commercial grade and quality grade. A herb quality index (HQI) including traditional commercial specifications and chemical components for quantitative grade classification were established, and corresponding discriminant function were figured out for precise determination of quality grade and sub-grade of Notopterygii Rhizoma et Radix. The result showed that notopterol, isoimperatorin and volatile oil were the major components for determination of chemical quality, and their dividing values were specified for every grade and sub-grade of the commercial materials of Notopterygii Rhizoma et Radix. According to the result, essential relationship between traditional medicinal indicators, qualitative commercial specifications, and quantitative chemical composition indicators can be examined by K-mean cluster, Fisher discriminant analysis and correspondence analysis, which provide a new method for comprehensive quantitative evaluation of traditional Chinese medicine quality integrated traditional commodity specifications and quantitative modern chemical index. Copyright© by the Chinese Pharmaceutical Association.

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples.

PubMed

Oblinsky, Daniel G; Vanschouwen, Bryan M B; Gordon, Heather L; Rothstein, Stuart M

2009-12-14

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the beta1 domain of protein G.

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples

NASA Astrophysics Data System (ADS)

Oblinsky, Daniel G.; VanSchouwen, Bryan M. B.; Gordon, Heather L.; Rothstein, Stuart M.

2009-12-01

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the β1 domain of protein G.

Use of MRI in Differentiation of Papillary Renal Cell Carcinoma Subtypes: Qualitative and Quantitative Analysis.

PubMed

Doshi, Ankur M; Ream, Justin M; Kierans, Andrea S; Bilbily, Matthew; Rusinek, Henry; Huang, William C; Chandarana, Hersh

2016-03-01

The purpose of this study was to determine whether qualitative and quantitative MRI feature analysis is useful for differentiating type 1 from type 2 papillary renal cell carcinoma (PRCC). This retrospective study included 21 type 1 and 17 type 2 PRCCs evaluated with preoperative MRI. Two radiologists independently evaluated various qualitative features, including signal intensity, heterogeneity, and margin. For the quantitative analysis, a radiology fellow and a medical student independently drew 3D volumes of interest over the entire tumor on T2-weighted HASTE images, apparent diffusion coefficient parametric maps, and nephrographic phase contrast-enhanced MR images to derive first-order texture metrics. Qualitative and quantitative features were compared between the groups. For both readers, qualitative features with greater frequency in type 2 PRCC included heterogeneous enhancement, indistinct margin, and T2 heterogeneity (all, p < 0.035). Indistinct margins and heterogeneous enhancement were independent predictors (AUC, 0.822). Quantitative analysis revealed that apparent diffusion coefficient, HASTE, and contrast-enhanced entropy were greater in type 2 PRCC (p < 0.05; AUC, 0.682-0.716). A combined quantitative and qualitative model had an AUC of 0.859. Qualitative features within the model had interreader concordance of 84-95%, and the quantitative data had intraclass coefficients of 0.873-0.961. Qualitative and quantitative features can help discriminate between type 1 and type 2 PRCC. Quantitative analysis may capture useful information that complements the qualitative appearance while benefiting from high interobserver agreement.

Groping for quantitative digital 3-D image analysis: an approach to quantitative fluorescence in situ hybridization in thick tissue sections of prostate carcinoma.

PubMed

Rodenacker, K; Aubele, M; Hutzler, P; Adiga, P S

1997-01-01

In molecular pathology numerical chromosome aberrations have been found to be decisive for the prognosis of malignancy in tumours. The existence of such aberrations can be detected by interphase fluorescence in situ hybridization (FISH). The gain or loss of certain base sequences in the desoxyribonucleic acid (DNA) can be estimated by counting the number of FISH signals per cell nucleus. The quantitative evaluation of such events is a necessary condition for a prospective use in diagnostic pathology. To avoid occlusions of signals, the cell nucleus has to be analyzed in three dimensions. Confocal laser scanning microscopy is the means to obtain series of optical thin sections from fluorescence stained or marked material to fulfill the conditions mentioned above. A graphical user interface (GUI) to a software package for display, inspection, count and (semi-)automatic analysis of 3-D images for pathologists is outlined including the underlying methods of 3-D image interaction and segmentation developed. The preparative methods are briefly described. Main emphasis is given to the methodical questions of computer-aided analysis of large 3-D image data sets for pathologists. Several automated analysis steps can be performed for segmentation and succeeding quantification. However tumour material is in contrast to isolated or cultured cells even for visual inspection, a difficult material. For the present a fully automated digital image analysis of 3-D data is not in sight. A semi-automatic segmentation method is thus presented here.

Global analysis of the yeast lipidome by quantitative shotgun mass spectrometry.

PubMed

Ejsing, Christer S; Sampaio, Julio L; Surendranath, Vineeth; Duchoslav, Eva; Ekroos, Kim; Klemm, Robin W; Simons, Kai; Shevchenko, Andrej

2009-02-17

Although the transcriptome, proteome, and interactome of several eukaryotic model organisms have been described in detail, lipidomes remain relatively uncharacterized. Using Saccharomyces cerevisiae as an example, we demonstrate that automated shotgun lipidomics analysis enabled lipidome-wide absolute quantification of individual molecular lipid species by streamlined processing of a single sample of only 2 million yeast cells. By comparative lipidomics, we achieved the absolute quantification of 250 molecular lipid species covering 21 major lipid classes. This analysis provided approximately 95% coverage of the yeast lipidome achieved with 125-fold improvement in sensitivity compared with previous approaches. Comparative lipidomics demonstrated that growth temperature and defects in lipid biosynthesis induce ripple effects throughout the molecular composition of the yeast lipidome. This work serves as a resource for molecular characterization of eukaryotic lipidomes, and establishes shotgun lipidomics as a powerful platform for complementing biochemical studies and other systems-level approaches.

Quantitative Proteomic Profiling the Molecular Signatures of Annexin A5 in Lung Squamous Carcinoma Cells.

PubMed

Sun, Bing; Bai, Yuxin; Zhang, Liyuan; Gong, Linlin; Qi, Xiaoyu; Li, Huizhen; Wang, Faming; Chi, Xinming; Jiang, Yulin; Shao, Shujuan

Lung cancer remains the leading cancer killer around the world. It's crucial to identify newer mechanism-based targets to effectively manage lung cancer. Annexin A5 (ANXA5) is a protein kinase C inhibitory protein and calcium dependent phospholipid-binding protein, which may act as an endogenous regulator of various pathophysiological processes. However, its molecular mechanism in lung cancer remains poorly understood. This study was designed to determine the mechanism of ANXA5 in lung cancer with a hope to obtain useful information to provide a new therapeutic target. We used a stable isotope dimethyl labeling based quantitative proteomic method to identify differentially expressed proteins in NSCLC cell lines after ANXA5 transfection. Out of 314 proteins, we identified 26 and 44 proteins that were down- and up-regulated upon ANXA5 modulation, respectively. The IPA analysis revealed that glycolysis and gluconeogenesis were the predominant pathways modulated by ANXA5. Multiple central nodes, namely HSPA5, FN1, PDIA6, ENO1, ALDOA, JUP and KRT6A appeared to occupy regulatory nodes in the protein-protein networks upon ANXA5 modulation. Taken together, ANXA5 appears to have pleotropic effects, as it modulates multiple key signaling pathways, supporting the potential usefulness of ANXA5 as a potential target in lung cancer. This study might provide a new insight into the mechanism of ANXA5 in lung cancer.

Quantitative Analysis of Repertoire-Scale Immunoglobulin Properties in Vaccine-Induced B-Cell Responses

DTIC Science & Technology

2017-05-10

repertoire-wide properties. Finally, through 75 the use of appropriate statistical analyses, the repertoire profiles can be quantitatively compared and 76...cell response to eVLP and 503 quantitatively compare GC B-cell repertoires from immunization conditions. We partitioned the 504 resulting clonotype... Quantitative analysis of repertoire-scale immunoglobulin properties in vaccine-induced B-cell responses Ilja V. Khavrutskii1, Sidhartha Chaudhury*1

CUMULATIVE RISK ASSESSMENT: GETTING FROM TOXICOLOGY TO QUANTITATIVE ANALYSIS

EPA Science Inventory

INTRODUCTION: GETTING FROM TOXICOLOGY TO QUANTITATIVE ANALYSIS FOR CUMULATIVE RISK

Hugh A. Barton1 and Carey N. Pope2
1US EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, NC
2Department of...

Evaluation of shear wave elastography for differential diagnosis of breast lesions: A new qualitative analysis versus conventional quantitative analysis.

PubMed

Ren, Wei-Wei; Li, Xiao-Long; Wang, Dan; Liu, Bo-Ji; Zhao, Chong-Ke; Xu, Hui-Xiong

2018-04-13

To evaluate a special kind of ultrasound (US) shear wave elastography for differential diagnosis of breast lesions, using a new qualitative analysis (i.e. the elasticity score in the travel time map) compared with conventional quantitative analysis. From June 2014 to July 2015, 266 pathologically proven breast lesions were enrolled in this study. The maximum, mean, median, minimum, and standard deviation of shear wave speed (SWS) values (m/s) were assessed. The elasticity score, a new qualitative feature, was evaluated in the travel time map. The area under the receiver operating characteristic (AUROC) curves were plotted to evaluate the diagnostic performance of both qualitative and quantitative analyses for differentiation of breast lesions. Among all quantitative parameters, SWS-max showed the highest AUROC (0.805; 95% CI: 0.752, 0.851) compared with SWS-mean (0.786; 95% CI:0.732, 0.834; P = 0.094), SWS-median (0.775; 95% CI:0.720, 0.824; P = 0.046), SWS-min (0.675; 95% CI:0.615, 0.731; P = 0.000), and SWS-SD (0.768; 95% CI:0.712, 0.817; P = 0.074). The AUROC of qualitative analysis in this study obtained the best diagnostic performance (0.871; 95% CI: 0.825, 0.909, compared with the best parameter of SWS-max in quantitative analysis, P = 0.011). The new qualitative analysis of shear wave travel time showed the superior diagnostic performance in the differentiation of breast lesions in comparison with conventional quantitative analysis.

Quantitation of glycerophosphorylcholine by flow injection analysis using immobilized enzymes.

PubMed

Mancini, A; Del Rosso, F; Roberti, R; Caligiana, P; Vecchini, A; Binaglia, L

1996-09-20

A method for quantitating glycerophosphorylcholine by flow injection analysis is reported in the present paper. Glycerophosphorylcholine phosphodiesterase and choline oxidase, immobilized on controlled porosity glass beads, are packed in a small reactor inserted in a flow injection manifold. When samples containing glycerophosphorylcholine are injected, glycerophosphorylcholine is hydrolyzed into choline and sn-glycerol-3-phosphate. The free choline produced in this reaction is oxidized to betain and hydrogen peroxide. Hydrogen peroxide is detected amperometrically. Quantitation of glycerophosphorylcholine in samples containing choline and phosphorylcholine is obtained inserting ahead of the reactor a small column packed with a mixed bed ion exchange resin. The time needed for each determination does not exceed one minute. The present method, applied to quantitate glycerophosphorylcholine in samples of seminal plasma, gave results comparable with those obtained using the standard enzymatic-spectrophotometric procedure. An alternative procedure, making use of co-immobilized glycerophosphorylcholine phosphodiesterase and glycerol-3-phosphate oxidase for quantitating glycerophosphorylcholine, glycerophosphorylethanolamine and glycerophosphorylserine is also described.

Quantitative analysis to guide orphan drug development.

PubMed

Lesko, L J

2012-08-01

The development of orphan drugs for rare diseases has made impressive strides in the past 10 years. There has been a surge in orphan drug designations, but new drug approvals have not kept up. This article presents a three-pronged hierarchical strategy for quantitative analysis of data at the descriptive, mechanistic, and systems levels of the biological system that could represent a standardized and rational approach to orphan drug development. Examples are provided to illustrate the concept.

Qualitative and quantitative mass spectrometry imaging of drugs and metabolites

PubMed Central

Lietz, Christopher B.; Gemperline, Erin; Li, Lingjun

2013-01-01

Mass spectrometric imaging (MSI) has rapidly increased its presence in the pharmaceutical sciences. While quantitative whole-body autoradiography and microautoradiography are the traditional techniques for molecular imaging of drug delivery and metabolism, MSI provides advantageous specificity that can distinguish the parent drug from metabolites and modified endogenous molecules. This review begins with the fundamentals of MSI sample preparation/ionization, and then moves on to both qualitative and quantitative applications with special emphasis on drug discovery and delivery. Cutting-edge investigations on sub-cellular imaging and endogenous signaling peptides are also highlighted, followed by perspectives on emerging technology and the path for MSI to become a routine analysis technique. PMID:23603211

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

2D- and 3D-quantitative structure-activity relationship studies for a series of phenazine N,N'-dioxide as antitumour agents.

PubMed

Cunha, Jonathan Da; Lavaggi, María Laura; Abasolo, María Inés; Cerecetto, Hugo; González, Mercedes

2011-12-01

Hypoxic regions of tumours are associated with increased resistance to radiation and chemotherapy. Nevertheless, hypoxia has been used as a tool for specific activation of some antitumour prodrugs, named bioreductive agents. Phenazine dioxides are an example of such bioreductive prodrugs. Our 2D-quantitative structure activity relationship studies established that phenazine dioxides electronic and lipophilic descriptors are related to survival fraction in oxia or in hypoxia. Additionally, statistically significant models, derived by partial least squares, were obtained between survival fraction in oxia and comparative molecular field analysis standard model (r² = 0.755, q² = 0.505 and F = 26.70) or comparative molecular similarity indices analysis-combined steric and electrostatic fields (r² = 0.757, q² = 0.527 and F = 14.93), and survival fraction in hypoxia and comparative molecular field analysis standard model (r² = 0.736, q² = 0.521 and F = 18.63) or comparative molecular similarity indices analysis-hydrogen bond acceptor field (r² = 0.858, q² = 0.737 and F = 27.19). Categorical classification was used for the biological parameter selective cytotoxicity emerging also good models, derived by soft independent modelling of class analogy, with both comparative molecular field analysis standard model (96% of overall classification accuracy) and comparative molecular similarity indices analysis-steric field (92% of overall classification accuracy). 2D- and 3D-quantitative structure-activity relationships models provided important insights into the chemical and structural basis involved in the molecular recognition process of these phenazines as bioreductive agents and should be useful for the design of new structurally related analogues with improved potency. © 2011 John Wiley & Sons A/S.

Construction and analysis of circular RNA molecular regulatory networks in liver cancer.

PubMed

Ren, Shuangchun; Xin, Zhuoyuan; Xu, Yinyan; Xu, Jianting; Wang, Guoqing

2017-01-01

Liver cancer is the sixth most prevalent cancer, and the third most frequent cause of cancer-related deaths. Circular RNAs (circRNAs), a kind of special endogenous ncRNAs, have been coming back to the forefront of cancer genomics research. In this study, we used a systems biology approach to construct and analyze the circRNA molecular regulatory networks in the context of liver cancer. We detected a total of 127 differentially expressed circRNAs and 3,235 differentially expressed mRNAs. We selected the top-5 upregulated circRNAs to construct a circRNA-miRNA-mRNA network. We enriched the pathways and gene ontology items and determined their participation in cancer-related pathways such as p53 signaling pathway and pathways involved in angiogenesis and cell cycle. Quantitative real-time PCR was performed to verify the top-five circRNAs. ROC analysis showed circZFR, circFUT8, circIPO11 could significantly distinguish the cancer samples, with an AUC of 0.7069, 0.7575, and 0.7103, respectively. Our results suggest the circRNA-miRNA-mRNA network may help us further understand the molecular mechanisms of tumor progression in liver cancer, and reveal novel biomarkers and therapeutic targets.

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis

PubMed Central

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

ABSTRACT Introduction/Background: Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. Material and Methods: n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Results: Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Conclusion: Both Ki-67 and MCM-2 are

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis.

PubMed

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they

Molecular Dissection of a Major Gene Effect on a Quantitative Trait: The Level of Alcohol Dehydrogenase Expression in Drosophila Melanogaster

PubMed Central

Stam, L. F.; Laurie, C. C.

1996-01-01

A molecular mapping experiment shows that a major gene effect on a quantitative trait, the level of alcohol dehydrogenase expression in Drosophila melanogaster, is due to multiple polymorphisms within the Adh gene. These polymorphisms are located in an intron, the coding sequence, and the 3' untranslated region. Because of nonrandom associations among polymorphisms at different sites, the individual effects combine (in some cases epistatically) to produce ``superalleles'' with large effect. These results have implications for the interpretation of major gene effects detected by quantitative trait locus mapping methods. They show that large effects due to a single locus may be due to multiple associated polymorphisms (or sequential fixations in isolated populations) rather than individual mutations of large effect. PMID:8978044

Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy.

PubMed

Biglands, John D; Ibraheem, Montasir; Magee, Derek R; Radjenovic, Aleksandra; Plein, Sven; Greenwood, John P

2018-05-01

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial

The discovery of novel histone lysine methyltransferase G9a inhibitors (part 1): molecular design based on a series of substituted 2,4-diamino-7- aminoalkoxyquinazoline by molecular-docking-guided 3D quantitative structure-activity relationship studies.

PubMed

Feng, Taotao; Wang, Hai; Zhang, Xiaojin; Sun, Haopeng; You, Qidong

2014-06-01

Protein lysine methyltransferase G9a, which catalyzes methylation of lysine 9 of histone H3 (H3K9) and lysine 373 (K373) of p53, is overexpressed in human cancers. This suggests that small molecular inhibitors of G9a might be attractive antitumor agents. Herein we report our efforts on the design of novel G9a inhibitor based on the 3D quantitative structure-activity relationship (3D-QSAR) analysis of a series of 2,4-diamino-7-aminoalkoxyquinazolineas G9a inhibitors. The 3D-QSAR model was generated from 47 compounds using docking based molecular alignment. The best predictions were obtained with CoMFA standard model (q2 =0.700, r2 = 0.952) and CoMSIA model combined with steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields (q2 = 0.724, r2 =0.960). The structural requirements for substituted 2,4-diamino-7-aminoalkoxyquinazoline for G9a inhibitory activity can be obtained by analysing the COMSIA plots. Based on the information, six novel follow-up analogs were designed.

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.

Quantitative analysis of culture using millions of digitized books

PubMed Central

Michel, Jean-Baptiste; Shen, Yuan Kui; Aiden, Aviva P.; Veres, Adrian; Gray, Matthew K.; Pickett, Joseph P.; Hoiberg, Dale; Clancy, Dan; Norvig, Peter; Orwant, Jon; Pinker, Steven; Nowak, Martin A.; Aiden, Erez Lieberman

2011-01-01

We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of ‘culturomics’, focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. ‘Culturomics’ extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities. PMID:21163965

Quantitative analysis of culture using millions of digitized books.

PubMed

Michel, Jean-Baptiste; Shen, Yuan Kui; Aiden, Aviva Presser; Veres, Adrian; Gray, Matthew K; Pickett, Joseph P; Hoiberg, Dale; Clancy, Dan; Norvig, Peter; Orwant, Jon; Pinker, Steven; Nowak, Martin A; Aiden, Erez Lieberman

2011-01-14

We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.

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 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.

High-throughput quantitative analysis by desorption electrospray ionization mass spectrometry.

PubMed

Manicke, Nicholas E; Kistler, Thomas; Ifa, Demian R; Cooks, R Graham; Ouyang, Zheng

2009-02-01

A newly developed high-throughput desorption electrospray ionization (DESI) source was characterized in terms of its performance in quantitative analysis. A 96-sample array, containing pharmaceuticals in various matrices, was analyzed in a single run with a total analysis time of 3 min. These solution-phase samples were examined from a hydrophobic PTFE ink printed on glass. The quantitative accuracy, precision, and limit of detection (LOD) were characterized. Chemical background-free samples of propranolol (PRN) with PRN-d(7) as internal standard (IS) and carbamazepine (CBZ) with CBZ-d(10) as IS were examined. So were two other sample sets consisting of PRN/PRN-d(7) at varying concentration in a biological milieu of 10% urine or porcine brain total lipid extract, total lipid concentration 250 ng/microL. The background-free samples, examined in a total analysis time of 1.5 s/sample, showed good quantitative accuracy and precision, with a relative error (RE) and relative standard deviation (RSD) generally less than 3% and 5%, respectively. The samples in urine and the lipid extract required a longer analysis time (2.5 s/sample) and showed RSD values of around 10% for the samples in urine and 4% for the lipid extract samples and RE values of less than 3% for both sets. The LOD for PRN and CBZ when analyzed without chemical background was 10 and 30 fmol, respectively. The LOD of PRN increased to 400 fmol analyzed in 10% urine, and 200 fmol when analyzed in the brain lipid extract.

On the Need for Quantitative Bias Analysis in the Peer-Review Process.

PubMed

Fox, Matthew P; Lash, Timothy L

2017-05-15

Peer review is central to the process through which epidemiologists generate evidence to inform public health and medical interventions. Reviewers thereby act as critical gatekeepers to high-quality research. They are asked to carefully consider the validity of the proposed work or research findings by paying careful attention to the methodology and critiquing the importance of the insight gained. However, although many have noted problems with the peer-review system for both manuscripts and grant submissions, few solutions have been proposed to improve the process. Quantitative bias analysis encompasses all methods used to quantify the impact of systematic error on estimates of effect in epidemiologic research. Reviewers who insist that quantitative bias analysis be incorporated into the design, conduct, presentation, and interpretation of epidemiologic research could substantially strengthen the process. In the present commentary, we demonstrate how quantitative bias analysis can be used by investigators and authors, reviewers, funding agencies, and editors. By utilizing quantitative bias analysis in the peer-review process, editors can potentially avoid unnecessary rejections, identify key areas for improvement, and improve discussion sections by shifting from speculation on the impact of sources of error to quantification of the impact those sources of bias may have had. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells*

PubMed Central

Boisvert, François-Michel; Ahmad, Yasmeen; Gierliński, Marek; Charrière, Fabien; Lamont, Douglas; Scott, Michelle; Barton, Geoff; Lamond, Angus I.

2012-01-01

Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labeling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation, and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and stable isotope labeling with amino acids in cell culture, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualized using specialized software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear, and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was ∼20 h. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxyl terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multiprotein complexes, suggesting a general

Quantitative analysis of professionally trained versus untrained voices.

PubMed

Siupsinskiene, Nora

2003-01-01

The aim of this study was to compare healthy trained and untrained voices as well as healthy and dysphonic trained voices in adults using combined voice range profile and aerodynamic tests, to define the normal range limiting values of quantitative voice parameters and to select the most informative quantitative voice parameters for separation between healthy and dysphonic trained voices. Three groups of persons were evaluated. One hundred eighty six healthy volunteers were divided into two groups according to voice training: non-professional speakers group consisted of 106 untrained voices persons (36 males and 70 females) and professional speakers group--of 80 trained voices persons (21 males and 59 females). Clinical group consisted of 103 dysphonic professional speakers (23 males and 80 females) with various voice disorders. Eighteen quantitative voice parameters from combined voice range profile (VRP) test were analyzed: 8 of voice range profile, 8 of speaking voice, overall vocal dysfunction degree and coefficient of sound, and aerodynamic maximum phonation time. Analysis showed that healthy professional speakers demonstrated expanded vocal abilities in comparison to healthy non-professional speakers. Quantitative voice range profile parameters- pitch range, high frequency limit, area of high frequencies and coefficient of sound differed significantly between healthy professional and non-professional voices, and were more informative than speaking voice or aerodynamic parameters in showing the voice training. Logistic stepwise regression revealed that VRP area in high frequencies was sufficient to discriminate between healthy and dysphonic professional speakers for male subjects (overall discrimination accuracy--81.8%) and combination of three quantitative parameters (VRP high frequency limit, maximum voice intensity and slope of speaking curve) for female subjects (overall model discrimination accuracy--75.4%). We concluded that quantitative voice assessment

Quantitative Determination of Aluminum in Deodorant Brands: A Guided Inquiry Learning Experience in Quantitative Analysis Laboratory

ERIC Educational Resources Information Center

Sedwick, Victoria; Leal, Anne; Turner, Dea; Kanu, A. Bakarr

2018-01-01

The monitoring of metals in commercial products is essential for protecting public health against the hazards of metal toxicity. This article presents a guided inquiry (GI) experimental lab approach in a quantitative analysis lab class that enabled students' to determine the levels of aluminum in deodorant brands. The utility of a GI experimental…

Quantitative genetics

USDA-ARS?s Scientific Manuscript database

The majority of economically important traits targeted for cotton improvement are quantitatively inherited. In this chapter, the current state of cotton quantitative genetics is described and separated into four components. These components include: 1) traditional quantitative inheritance analysis, ...

Quantitative analysis on electrooculography (EOG) for neurodegenerative disease

NASA Astrophysics Data System (ADS)

Liu, Chang-Chia; Chaovalitwongse, W. Art; Pardalos, Panos M.; Seref, Onur; Xanthopoulos, Petros; Sackellares, J. C.; Skidmore, Frank M.

2007-11-01

Many studies have documented abnormal horizontal and vertical eye movements in human neurodegenerative disease as well as during altered states of consciousness (including drowsiness and intoxication) in healthy adults. Eye movement measurement may play an important role measuring the progress of neurodegenerative diseases and state of alertness in healthy individuals. There are several techniques for measuring eye movement, Infrared detection technique (IR). Video-oculography (VOG), Scleral eye coil and EOG. Among those available recording techniques, EOG is a major source for monitoring the abnormal eye movement. In this real-time quantitative analysis study, the methods which can capture the characteristic of the eye movement were proposed to accurately categorize the state of neurodegenerative subjects. The EOG recordings were taken while 5 tested subjects were watching a short (>120 s) animation clip. In response to the animated clip the participants executed a number of eye movements, including vertical smooth pursued (SVP), horizontal smooth pursued (HVP) and random saccades (RS). Detection of abnormalities in ocular movement may improve our diagnosis and understanding a neurodegenerative disease and altered states of consciousness. A standard real-time quantitative analysis will improve detection and provide a better understanding of pathology in these disorders.

Quantitative real-time analysis of collective cancer invasion and dissemination

NASA Astrophysics Data System (ADS)

Ewald, Andrew J.

2015-05-01

A grand challenge in biology is to understand the cellular and molecular basis of tissue and organ level function in mammals. The ultimate goals of such efforts are to explain how organs arise in development from the coordinated actions of their constituent cells and to determine how molecularly regulated changes in cell behavior alter the structure and function of organs during disease processes. Two major barriers stand in the way of achieving these goals: the relative inaccessibility of cellular processes in mammals and the daunting complexity of the signaling environment inside an intact organ in vivo. To overcome these barriers, we have developed a suite of tissue isolation, three dimensional (3D) culture, genetic manipulation, nanobiomaterials, imaging, and molecular analysis techniques to enable the real-time study of cell biology within intact tissues in physiologically relevant 3D environments. This manuscript introduces the rationale for 3D culture, reviews challenges to optical imaging in these cultures, and identifies current limitations in the analysis of complex experimental designs that could be overcome with improved imaging, imaging analysis, and automated classification of the results of experimental interventions.

Electroencephalography reactivity for prognostication of post-anoxic coma after cardiopulmonary resuscitation: A comparison of quantitative analysis and visual analysis.

PubMed

Liu, Gang; Su, Yingying; Jiang, Mengdi; Chen, Weibi; Zhang, Yan; Zhang, Yunzhou; Gao, Daiquan

2016-07-28

Electroencephalogram reactivity (EEG-R) is a positive predictive factor for assessing outcomes in comatose patients. Most studies assess the prognostic value of EEG-R utilizing visual analysis; however, this method is prone to subjectivity. We sought to categorize EEG-R with a quantitative approach. We retrospectively studied consecutive comatose patients who had an EEG-R recording performed 1-3 days after cardiopulmonary resuscitation (CPR) or during normothermia after therapeutic hypothermia. EEG-R was assessed via visual analysis and quantitative analysis separately. Clinical outcomes were followed-up at 3-month and dichotomized as recovery of awareness or no recovery of awareness. A total of 96 patients met the inclusion criteria, and 38 (40%) patients recovered awareness at 3-month followed-up. Of 27 patients with EEG-R measured with visual analysis, 22 patients recovered awareness; and of the 69 patients who did not demonstrated EEG-R, 16 patients recovered awareness. The sensitivity and specificity of visually measured EEG-R were 58% and 91%, respectively. The area under the receiver operating characteristic curve for the quantitative analysis was 0.92 (95% confidence interval, 0.87-0.97), with the best cut-off value of 0.10. EEG-R through quantitative analysis might be a good method in predicting the recovery of awareness in patients with post-anoxic coma after CPR. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Analysis of artifacts suggests DGGE should not be used for quantitative diversity analysis.

PubMed

Neilson, Julia W; Jordan, Fiona L; Maier, Raina M

2013-03-01

PCR-denaturing gradient gel electrophoresis (PCR-DGGE) is widely used in microbial ecology for the analysis of comparative community structure. However, artifacts generated during PCR-DGGE of mixed template communities impede the application of this technique to quantitative analysis of community diversity. The objective of the current study was to employ an artificial bacterial community to document and analyze artifacts associated with multiband signatures and preferential template amplification and to highlight their impacts on the use of this technique for quantitative diversity analysis. Six bacterial species (three Betaproteobacteria, two Alphaproteobacteria, and one Firmicutes) were amplified individually and in combinations with primers targeting the V7/V8 region of the 16S rRNA gene. Two of the six isolates produced multiband profiles demonstrating that band number does not correlate directly with α-diversity. Analysis of the multiple bands from one of these isolates confirmed that both bands had identical sequences which lead to the hypothesis that the multiband pattern resulted from two distinct structural conformations of the same amplicon. In addition, consistent preferential amplification was demonstrated following pairwise amplifications of the six isolates. DGGE and real time PCR analysis identified primer mismatch and PCR inhibition due to 16S rDNA secondary structure as the most probable causes of preferential amplification patterns. Reproducible DGGE community profiles generated in this study confirm that PCR-DGGE provides an excellent high-throughput tool for comparative community structure analysis, but that method-specific artifacts preclude its use for accurate comparative diversity analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

Polymer Molecular Weight Analysis by [Superscript 1]H NMR Spectroscopy

ERIC Educational Resources Information Center

Izunobi, Josephat U.; Higginbotham, Clement L.

2011-01-01

The measurement and analysis of molecular weight and molecular weight distribution remain matters of fundamental importance for the characterization and physical properties of polymers. Gel permeation chromatography (GPC) is the most routinely used method for the molecular weight determination of polymers whereas matrix-assisted laser…

Terahertz time-domain spectroscopy and quantitative analysis of metal gluconates.

PubMed

Li, Shaoxian; Yang, Jingqi; Zhao, Hongwei; Yang, Na; Jing, Dandan; Zhang, Jianbing; Li, Qingnuan; Han, Jiaguang

2015-01-01

A series of metal gluconates (Na(+), K(+), Mg(2+), Ca(2+), Fe(2+), Cu(2+), and Zn(2+)) were investigated by terahertz (THz) time-domain spectroscopy. The absorption coefficients and refractive indices of the samples were obtained in the frequency range of 0.5-2.6 THz. The gluconates showed distinct THz characteristic fingerprints, and the dissimilarities reflect their different structures, hydrogen-bond networks, and molecular interactions. In addition, some common features were observed among these gluconates, and the similarities probably come from the similar carbohydrate anion group. The X-ray powder diffraction measurements of these metal gluconates were performed, and the copper(II) gluconate was found to be amorphous, corresponding to the monotonic increase feature in the THz absorption spectrum. The results suggest that THz spectroscopy is sensitive to molecular structure and physical form. Binary and ternary mixtures of different gluconates were quantitatively analyzed based on the Beer-Lambert law. A chemical map of a tablet containing calcium D-gluconate monohydrate and α-lactose in the polyethylene host was obtained by THz imaging. The study shows that THz technology is a useful tool in pharmaceutical research and quality control applications.

Quantitative analysis of eyes and other optical systems in linear optics.

PubMed

Harris, William F; Evans, Tanya; van Gool, Radboud D

2017-05-01

To show that 14-dimensional spaces of augmented point P and angle Q characteristics, matrices obtained from the ray transference, are suitable for quantitative analysis although only the latter define an inner-product space and only on it can one define distances and angles. The paper examines the nature of the spaces and their relationships to other spaces including symmetric dioptric power space. The paper makes use of linear optics, a three-dimensional generalization of Gaussian optics. Symmetric 2 × 2 dioptric power matrices F define a three-dimensional inner-product space which provides a sound basis for quantitative analysis (calculation of changes, arithmetic means, etc.) of refractive errors and thin systems. For general systems the optical character is defined by the dimensionally-heterogeneous 4 × 4 symplectic matrix S, the transference, or if explicit allowance is made for heterocentricity, the 5 × 5 augmented symplectic matrix T. Ordinary quantitative analysis cannot be performed on them because matrices of neither of these types constitute vector spaces. Suitable transformations have been proposed but because the transforms are dimensionally heterogeneous the spaces are not naturally inner-product spaces. The paper obtains 14-dimensional spaces of augmented point P and angle Q characteristics. The 14-dimensional space defined by the augmented angle characteristics Q is dimensionally homogenous and an inner-product space. A 10-dimensional subspace of the space of augmented point characteristics P is also an inner-product space. The spaces are suitable for quantitative analysis of the optical character of eyes and many other systems. Distances and angles can be defined in the inner-product spaces. The optical systems may have multiple separated astigmatic and decentred refracting elements. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

Quantitative proteomic analysis of intact plastids.

PubMed

Shiraya, Takeshi; Kaneko, Kentaro; Mitsui, Toshiaki

2014-01-01

Plastids are specialized cell organelles in plant cells that are differentiated into various forms including chloroplasts, chromoplasts, and amyloplasts, and fulfill important functions in maintaining the overall cell metabolism and sensing environmental factors such as sunlight. It is therefore important to grasp the mechanisms of differentiation and functional changes of plastids in order to enhance the understanding of vegetality. In this chapter, details of a method for the extraction of intact plastids that makes analysis possible while maintaining the plastid functions are provided; in addition, a quantitative shotgun method for analyzing the composition and changes in the content of proteins in plastids as a result of environmental impacts is described.

Renal geology (quantitative renal stone analysis) by 'Fourier transform infrared spectroscopy'.

PubMed

Singh, Iqbal

2008-01-01

To prospectively determine the precise stone composition (quantitative analysis) by using infrared spectroscopy in patients with urinary stone disease presenting to our clinic. To determine an ideal method for stone analysis suitable for use in a clinical setting. After routine and a detailed metabolic workup of all patients of urolithiasis, stone samples of 50 patients of urolithiasis satisfying the entry criteria were subjected to the Fourier transform infrared spectroscopic analysis after adequate sample homogenization at a single testing center. Calcium oxalate monohydrate and dihydrate stone mixture was most commonly encountered in 35 (71%) followed by calcium phosphate, carbonate apatite, magnesium ammonium hexahydrate and xanthine stones. Fourier transform infrared spectroscopy allows an accurate, reliable quantitative method of stone analysis. It also helps in maintaining a computerized large reference library. Knowledge of precise stone composition may allow the institution of appropriate prophylactic therapy despite the absence of any detectable metabolic abnormalities. This may prevent and or delay stone recurrence.

Quantitative histogram analysis of images

NASA Astrophysics Data System (ADS)

Holub, Oliver; Ferreira, Sérgio T.

2006-11-01

loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

Quantitative scanning thermal microscopy of ErAs/GaAs superlattice structures grown by molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Park, K. W.; Nair, H. P.; Crook, A. M.; Bank, S. R.; Yu, E. T.

2013-02-01

A proximal probe-based quantitative measurement of thermal conductivity with ˜100-150 nm lateral and vertical spatial resolution has been implemented. Measurements on an ErAs/GaAs superlattice structure grown by molecular beam epitaxy with 3% volumetric ErAs content yielded thermal conductivity at room temperature of 9 ± 2 W/m K, approximately five times lower than that for GaAs. Numerical modeling of phonon scattering by ErAs nanoparticles yielded thermal conductivities in reasonable agreement with those measured experimentally and provides insight into the potential influence of nanoparticle shape on phonon scattering. Measurements of wedge-shaped samples created by focused ion beam milling provide direct confirmation of depth resolution achieved.

Piezoelectric sensors based on molecular imprinted polymers for detection of low molecular mass analytes.

PubMed

Uludağ, Yildiz; Piletsky, Sergey A; Turner, Anthony P F; Cooper, Matthew A

2007-11-01

Biomimetic recognition elements employed for the detection of analytes are commonly based on proteinaceous affibodies, immunoglobulins, single-chain and single-domain antibody fragments or aptamers. The alternative supra-molecular approach using a molecularly imprinted polymer now has proven utility in numerous applications ranging from liquid chromatography to bioassays. Despite inherent advantages compared with biochemical/biological recognition (which include robustness, storage endurance and lower costs) there are few contributions that describe quantitative analytical applications of molecularly imprinted polymers for relevant small molecular mass compounds in real-world samples. There is, however, significant literature describing the use of low-power, portable piezoelectric transducers to detect analytes in environmental monitoring and other application areas. Here we review the combination of molecularly imprinted polymers as recognition elements with piezoelectric biosensors for quantitative detection of small molecules. Analytes are classified by type and sample matrix presentation and various molecularly imprinted polymer synthetic fabrication strategies are also reviewed.

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

An Inexpensive Electrodeposition Device and Its Use in a Quantitative Analysis Laboratory Exercise

ERIC Educational Resources Information Center

Parker, Richard H.

2011-01-01

An experimental procedure, using an apparatus that is easy to construct, was developed to incorporate a quantitative electrogravimetric determination of the solution nickel content into an undergraduate or advanced high school quantitative analysis laboratory. This procedure produces results comparable to the procedure used for the gravimetric…

Quantitative Proteomics Analysis of Herbaceous Peony in Response to Paclobutrazol Inhibition of Lateral Branching

PubMed Central

Zhao, Daqiu; Gong, Saijie; Hao, Zhaojun; Meng, Jiasong; Tao, Jun

2015-01-01

Herbaceous peony (Paeonia lactiflora Pall.) is an emerging high-grade cut flower worldwide, which is usually used in wedding bouquets and known as the “wedding flower”. However, abundant lateral branches appear frequently in some excellent cultivars, and a lack of a method to remove Paeonia lactiflora lateral branches other than inefficient artificial methods is an obstacle for improving the quality of its cut flowers. In this study, paclobutrazol (PBZ) application was found to inhibit the growth of lateral branches in Paeonia lactiflora for the first time, including 96.82% decreased lateral bud number per branch, 77.79% and 42.31% decreased length and diameter of lateral branches, respectively, declined cell wall materials and changed microstructures. Subsequently, isobaric tag for relative and absolute quantitation (iTRAQ) technology was used for quantitative proteomics analysis of lateral branches under PBZ application and control. The results indicated that 178 differentially expressed proteins (DEPs) successfully obtained, 98 DEPs were up-regulated and 80 DEPs were down-regulated. Thereafter, 34 candidate DEPs associated with the inhibited growth of lateral branches were screened according to their function and classification. These PBZ-stress responsive candidate DEPs were involved in eight biological processes, which played a very important role in the growth and development of lateral branches together with the response to PBZ stress. These results provide a better understanding of the molecular theoretical basis for removing Paeonia lactiflora lateral branches using PBZ application. PMID:26473855

Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

Qualitative and quantitative mass spectrometry imaging of drugs and metabolites.

PubMed

Lietz, Christopher B; Gemperline, Erin; Li, Lingjun

2013-07-01

Mass spectrometric imaging (MSI) has rapidly increased its presence in the pharmaceutical sciences. While quantitative whole-body autoradiography and microautoradiography are the traditional techniques for molecular imaging of drug delivery and metabolism, MSI provides advantageous specificity that can distinguish the parent drug from metabolites and modified endogenous molecules. This review begins with the fundamentals of MSI sample preparation/ionization, and then moves on to both qualitative and quantitative applications with special emphasis on drug discovery and delivery. Cutting-edge investigations on sub-cellular imaging and endogenous signaling peptides are also highlighted, followed by perspectives on emerging technology and the path for MSI to become a routine analysis technique. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantitative DNA methylation analysis improves epigenotype-phenotype correlations in Beckwith-Wiedemann syndrome

PubMed Central

Calvello, Mariarosaria; Tabano, Silvia; Colapietro, Patrizia; Maitz, Silvia; Pansa, Alessandra; Augello, Claudia; Lalatta, Faustina; Gentilin, Barbara; Spreafico, Filippo; Calzari, Luciano; Perotti, Daniela; Larizza, Lidia; Russo, Silvia; Selicorni, Angelo; Sirchia, Silvia M; Miozzo, Monica

2013-01-01

Beckwith-Wiedemann syndrome (BWS) is a rare disorder characterized by overgrowth and predisposition to embryonal tumors. BWS is caused by various epigenetic and/or genetic alterations that dysregulate the imprinted genes on chromosome region 11p15.5. Molecular analysis is required to reinforce the clinical diagnosis of BWS and to identify BWS patients with cancer susceptibility. This is particularly crucial prenatally because most signs of BWS cannot be recognized in utero. We established a reliable molecular assay by pyrosequencing to quantitatively evaluate the methylation profiles of ICR1 and ICR2. We explored epigenotype-phenotype correlations in 19 patients that fulfilled the clinical diagnostic criteria for BWS, 22 patients with suspected BWS, and three fetuses with omphalocele. Abnormal methylation was observed in one prenatal case and 19 postnatal cases, including seven suspected BWS. Seven cases showed ICR1 hypermethylation, five cases showed ICR2 hypomethylation, and eight cases showed abnormal methylation of ICR1 and ICR2 indicating paternal uniparental disomy (UPD). More cases of ICR1 alterations and UPD were found than expected. This is likely due to the sensitivity of this approach, which can detect slight deviations in methylation from normal levels. There was a significant correlation (p < 0.001) between the percentage of ICR1 methylation and BWS features: severe hypermethylation (range: 75–86%) was associated with macroglossia, macrosomia, and visceromegaly, whereas mild hypermethylation (range: 55–59%) was associated with umbilical hernia and diastasis recti. Evaluation of ICR1 and ICR2 methylation by pyrosequencing in BWS can improve epigenotype-phenotype correlations, detection of methylation alterations in suspected cases, and identification of UPD. PMID:23917791

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

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

Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

PubMed

Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

2017-12-01

Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

[Relevance of big data for molecular diagnostics].

PubMed

Bonin-Andresen, M; Smiljanovic, B; Stuhlmüller, B; Sörensen, T; Grützkau, A; Häupl, T

2018-04-01

Big data analysis raises the expectation that computerized algorithms may extract new knowledge from otherwise unmanageable vast data sets. What are the algorithms behind the big data discussion? In principle, high throughput technologies in molecular research already introduced big data and the development and application of analysis tools into the field of rheumatology some 15 years ago. This includes especially omics technologies, such as genomics, transcriptomics and cytomics. Some basic methods of data analysis are provided along with the technology, however, functional analysis and interpretation requires adaptation of existing or development of new software tools. For these steps, structuring and evaluating according to the biological context is extremely important and not only a mathematical problem. This aspect has to be considered much more for molecular big data than for those analyzed in health economy or epidemiology. Molecular data are structured in a first order determined by the applied technology and present quantitative characteristics that follow the principles of their biological nature. These biological dependencies have to be integrated into software solutions, which may require networks of molecular big data of the same or even different technologies in order to achieve cross-technology confirmation. More and more extensive recording of molecular processes also in individual patients are generating personal big data and require new strategies for management in order to develop data-driven individualized interpretation concepts. With this perspective in mind, translation of information derived from molecular big data will also require new specifications for education and professional competence.

Principal Component Analysis of Lipid Molecule Conformational Changes in Molecular Dynamics Simulations.

PubMed

Buslaev, Pavel; Gordeliy, Valentin; Grudinin, Sergei; Gushchin, Ivan

2016-03-08

Molecular dynamics simulations of lipid bilayers are ubiquitous nowadays. Usually, either global properties of the bilayer or some particular characteristics of each lipid molecule are evaluated in such simulations, but the structural properties of the molecules as a whole are rarely studied. Here, we show how a comprehensive quantitative description of conformational space and dynamics of a single lipid molecule can be achieved via the principal component analysis (PCA). We illustrate the approach by analyzing and comparing simulations of DOPC bilayers obtained using eight different force fields: all-atom generalized AMBER, CHARMM27, CHARMM36, Lipid14, and Slipids and united-atom Berger, GROMOS43A1-S3, and GROMOS54A7. Similarly to proteins, most of the structural variance of a lipid molecule can be described by only a few principal components. These major components are similar in different simulations, although there are notable distinctions between the older and newer force fields and between the all-atom and united-atom force fields. The DOPC molecules in the simulations generally equilibrate on the time scales of tens to hundreds of nanoseconds. The equilibration is the slowest in the GAFF simulation and the fastest in the Slipids simulation. Somewhat unexpectedly, the equilibration in the united-atom force fields is generally slower than in the all-atom force fields. Overall, there is a clear separation between the more variable previous generation force fields and significantly more similar new generation force fields (CHARMM36, Lipid14, Slipids). We expect that the presented approaches will be useful for quantitative analysis of conformations and dynamics of individual lipid molecules in other simulations of lipid bilayers.

Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris.

PubMed

Waldmann, P; García-Gil, M R; Sillanpää, M J

2005-06-01

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.

ACVP-02: Plasma SIV/SHIV RNA Viral Load Measurements through the AIDS and Cancer Virus Program Quantitative Molecular Diagnostics Core | Frederick National Laboratory for Cancer Research

Cancer.gov

The SIV plasma viral load assay performed by the Quantitative Molecular Diagnostics Core (QMDC) utilizes reagents specifically designed to detect and accurately quantify the full range of SIV/SHIV viral variants and clones in common usage in the rese

Molecular Ionization-Desorption Analysis Source (MIDAS) for Mass Spectrometry: Thin-Layer Chromatography.

PubMed

Winter, Gregory T; Wilhide, Joshua A; LaCourse, William R

2016-02-01

Molecular ionization-desorption analysis source (MIDAS), which is a desorption atmospheric pressure chemical ionization (DAPCI) type source, for mass spectrometry has been developed as a multi-functional platform for the direct sampling of surfaces. In this article, its utility for the analysis of thin-layer chromatography (TLC) plates is highlighted. Amino acids, which are difficult to visualize without staining reagents or charring, were detected and identified directly from a TLC plate. To demonstrate the full potential of MIDAS, all active ingredients from an analgesic tablet, separated on a TLC plate, were successfully detected using both positive and negative ion modes. The identity of each of the compounds was confirmed from their mass spectra and compared against standards. Post separation, the chemical signal (blue permanent marker) as reference marks placed at the origin and solvent front were used to calculate retention factor (Rf) values from the resulting ion chromatogram. The quantitative capabilities of the device were exhibited by scanning caffeine spots on a TLC plate of increasing sample amount. A linear curve based on peak are, R2 = 0.994, was generated for seven spots ranging from 50 to 1000 ng of caffeine per spot.

Molecular Ionization-Desorption Analysis Source (MIDAS) for Mass Spectrometry: Thin-Layer Chromatography

NASA Astrophysics Data System (ADS)

Winter, Gregory T.; Wilhide, Joshua A.; LaCourse, William R.

2016-02-01

Molecular ionization-desorption analysis source (MIDAS), which is a desorption atmospheric pressure chemical ionization (DAPCI) type source, for mass spectrometry has been developed as a multi-functional platform for the direct sampling of surfaces. In this article, its utility for the analysis of thin-layer chromatography (TLC) plates is highlighted. Amino acids, which are difficult to visualize without staining reagents or charring, were detected and identified directly from a TLC plate. To demonstrate the full potential of MIDAS, all active ingredients from an analgesic tablet, separated on a TLC plate, were successfully detected using both positive and negative ion modes. The identity of each of the compounds was confirmed from their mass spectra and compared against standards. Post separation, the chemical signal (blue permanent marker) as reference marks placed at the origin and solvent front were used to calculate retention factor (Rf) values from the resulting ion chromatogram. The quantitative capabilities of the device were exhibited by scanning caffeine spots on a TLC plate of increasing sample amount. A linear curve based on peak are, R2 = 0.994, was generated for seven spots ranging from 50 to 1000 ng of caffeine per spot.

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

PubMed

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

DNA DAMAGE QUANTITATION BY ALKALINE GEL ELECTROPHORESIS.

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

SUTHERLAND,B.M.; BENNETT,P.V.; SUTHERLAND, J.C.

2004-03-24

Physical and chemical agents in the environment, those used in clinical applications, or encountered during recreational exposures to sunlight, induce damages in DNA. Understanding the biological impact of these agents requires quantitation of the levels of such damages in laboratory test systems as well as in field or clinical samples. Alkaline gel electrophoresis provides a sensitive (down to {approx} a few lesions/5Mb), rapid method of direct quantitation of a wide variety of DNA damages in nanogram quantities of non-radioactive DNAs from laboratory, field, or clinical specimens, including higher plants and animals. This method stems from velocity sedimentation studies of DNAmore » populations, and from the simple methods of agarose gel electrophoresis. Our laboratories have developed quantitative agarose gel methods, analytical descriptions of DNA migration during electrophoresis on agarose gels (1-6), and electronic imaging for accurate determinations of DNA mass (7-9). Although all these components improve sensitivity and throughput of large numbers of samples (7,8,10), a simple version using only standard molecular biology equipment allows routine analysis of DNA damages at moderate frequencies. We present here a description of the methods, as well as a brief description of the underlying principles, required for a simplified approach to quantitation of DNA damages by alkaline gel electrophoresis.« less

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

PubMed

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely

Kinetic Analysis of Amylase Using Quantitative Benedict's and Iodine Starch Reagents

ERIC Educational Resources Information Center

Cochran, Beverly; Lunday, Deborah; Miskevich, Frank

2008-01-01

Quantitative analysis of carbohydrates is a fundamental analytical tool used in many aspects of biology and chemistry. We have adapted a technique developed by Mathews et al. using an inexpensive scanner and open-source image analysis software to quantify amylase activity using both the breakdown of starch and the appearance of glucose. Breakdown…

Quantitative estimation of pesticide-likeness for agrochemical discovery.

PubMed

Avram, Sorin; Funar-Timofei, Simona; Borota, Ana; Chennamaneni, Sridhar Rao; Manchala, Anil Kumar; Muresan, Sorel

2014-12-01

The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP). In the assessment of these definitions, we relied on the concept of desirability functions. We found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides. The hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery. Graphical AbstractQuantitative models for pesticide-likeness were derived using the concept of desirability functions parameterized for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings.

Investment appraisal using quantitative risk analysis.

PubMed

Johansson, Henrik

2002-07-01

Investment appraisal concerned with investments in fire safety systems is discussed. Particular attention is directed at evaluating, in terms of the Bayesian decision theory, the risk reduction that investment in a fire safety system involves. It is shown how the monetary value of the change from a building design without any specific fire protection system to one including such a system can be estimated by use of quantitative risk analysis, the results of which are expressed in terms of a Risk-adjusted net present value. This represents the intrinsic monetary value of investing in the fire safety system. The method suggested is exemplified by a case study performed in an Avesta Sheffield factory.

Proteomic analysis provides insights into the molecular bases of hydrogen gas-induced cadmium resistance in Medicago sativa.

PubMed

Dai, Chen; Cui, Weiti; Pan, Jincheng; Xie, Yanjie; Wang, Jin; Shen, Wenbiao

2017-01-30

Recently, molecular hydrogen (H 2 ) has emerged as a bio-regulator both in animals and plants. Normally, functions of endogenous generated H 2 could be mimicked by exogenously applied hydrogen-rich water (HRW) or hydrogen-rich saline (particularly in animals). Although alfalfa seedlings showed more cadmium (Cd) resistance after the administration with HRW, corresponding molecular mechanism is still elusive. To address this gap, iTRAQ-based quantitative proteomics was used. The results showed that a total of 2377 proteins were identified with <1% FDR, and 1254 protein abundance perturbations were confidently assessed. Total of 248 significant differential proteins were identified in Cd- and/or HRW-treated samples. Furthermore, 92 proteins from the 248 proteins were selected for further bioinformatics analysis. Interestingly, results indicated that they were classified into seven categories: defense and response to stress, sulfur compound metabolic process, amino acid and protein metabolic process, carbohydrate and energy metabolic process, secondary metabolic process, oxidation-reduction process, and metal ion homeostasis. In addition, the protein expression patterns were consistent with the results of decreased lipid peroxidation, increased non-protein thiols abundance, as well as iron and zinc content. These suggest that HRW alleviates Cd toxicity mainly by decreasing oxidative damage, enhancing sulfur compound metabolic process, and maintaining nutrient element homeostasis. Contamination of soils by Cd has become a potential concern to crops. Medicago sativa is a widely used forage around the world. Recently, hydrogen gas (H 2 ) was suggested as a candidate of signal molecule, and found to effectively attenuate Cd-induced damage in alfalfa seedlings. However, the underlying molecular mechanism still needs to be further elucidated. In the present work, an iTRAQ-based quantitative proteomics was firstly carried out, and the results revealed the main molecular

A new approach for quantitative analysis of L-phenylalanine using a novel semi-sandwich immunometric assay.

PubMed

Kubota, Kazuyuki; Mizukoshi, Toshimi; Miyano, Hiroshi

2013-10-01

Here, we describe a novel method for L-phenylalanine analysis using a sandwich-type immunometric assay approach for use as a new method for amino acid analysis. To overcome difficulties of the preparation of high-affinity and selectivity monoclonal antibodies against L-phenylalanine and the inability to use sandwich-type immunometric assays due to their small molecular weight, three procedures were examined. First, amino groups of L-phenylalanine were modified by "N-Fmoc-L-cysteine" (FC) residues and the derivative (FC-Phe) was used as a hapten. Immunization of mice with bovine serum albumin/FC-Phe conjugate successfully yielded specific monoclonal anti-FC-Phe antibodies. Second, a new derivatization reagent, "biotin linker conjugate of FC-Phe N-succinimidyl ester" (FC(Biotin)-NHS), was synthesized to convert L-phenylalanine to FC-(Biotin)-Phe as a hapten structure. The biotin moiety linked to the thiol group of cysteine formed a second binding site for streptavidin/horseradish peroxidase (HRP) conjugates for optical detection. Third, a new semi-sandwich-type immunometric assay was established using pre-derivatized L-phenylalanine, the monoclonal anti-FC-Phe antibody, and streptavidin/HRP conjugate (without second antibody). Using the new "semi-sandwich" immunometric assay system, a detection limit of 35 nM (60 amol per analysis) and a detection range of 0.1-20 μM were attained using a standard L-phenylalanine solution. Rat plasma samples were analyzed to test reliability. Intra-day assay precision was within 6% of the coefficient of variation; inter-day variation was 0.1%. The recovery rates were from 92.4 to 123.7%. This is the first report of the quantitative determination of L-phenylalanine using a reliable semi-sandwich immunometric assay approach and will be applicable to the quantitative determination of other amino acids.

Quantitative proteomic analysis reveals that antioxidation mechanisms contribute to cold tolerance in plantain (Musa paradisiaca L.; ABB Group) seedlings.

PubMed

Yang, Qiao-Song; Wu, Jun-Hua; Li, Chun-Yu; Wei, Yue-Rong; Sheng, Ou; Hu, Chun-Hua; Kuang, Rui-Bin; Huang, Yong-Hong; Peng, Xin-Xiang; McCardle, James A; Chen, Wei; Yang, Yong; Rose, Jocelyn K C; Zhang, Sheng; Yi, Gan-Jun

2012-12-01

Banana and its close relative, plantain are globally important crops and there is considerable interest in optimizing their cultivation. Plantain has superior cold tolerance compared with banana and a thorough understanding of the molecular mechanisms and responses of plantain to cold stress has great potential value for developing cold tolerant banana cultivars. In this study, we used iTRAQ-based comparative proteomic analysis to investigate the temporal responses of plantain to cold stress. Plantain seedlings were exposed for 0, 6, and 24 h of cold stress at 8 °C and subsequently allowed to recover for 24 h at 28 °C. A total of 3477 plantain proteins were identified, of which 809 showed differential expression from the three treatments. The majority of differentially expressed proteins were predicted to be involved in oxidation-reduction, including oxylipin biosynthesis, whereas others were associated with photosynthesis, photorespiration, and several primary metabolic processes, such as carbohydrate metabolic process and fatty acid beta-oxidation. Western blot analysis and enzyme activity assays were performed on seven differentially expressed, cold-response candidate plantain proteins to validate the proteomics data. Similar analyses of the seven candidate proteins were performed in cold-sensitive banana to examine possible functional conservation, and to compare the results to equivalent responses between the two species. Consistent results were achieved by Western blot and enzyme activity assays, demonstrating that the quantitative proteomics data collected in this study are reliable. Our results suggest that an increase of antioxidant capacity through adapted ROS scavenging capability, reduced production of ROS, and decreased lipid peroxidation contribute to molecular mechanisms for the increased cold tolerance in plantain. To the best of our knowledge, this is the first report of a global investigation on molecular responses of plantain to cold stress by

Quantitative Proteomic Analysis Reveals that Antioxidation Mechanisms Contribute to Cold Tolerance in Plantain (Musa paradisiaca L.; ABB Group) Seedlings*

PubMed Central

Yang, Qiao-Song; Wu, Jun-Hua; Li, Chun-Yu; Wei, Yue-Rong; Sheng, Ou; Hu, Chun-Hua; Kuang, Rui-Bin; Huang, Yong-Hong; Peng, Xin-Xiang; McCardle, James A.; Chen, Wei; Yang, Yong; Rose, Jocelyn K. C.; Zhang, Sheng; Yi, Gan-Jun

2012-01-01

Banana and its close relative, plantain are globally important crops and there is considerable interest in optimizing their cultivation. Plantain has superior cold tolerance compared with banana and a thorough understanding of the molecular mechanisms and responses of plantain to cold stress has great potential value for developing cold tolerant banana cultivars. In this study, we used iTRAQ-based comparative proteomic analysis to investigate the temporal responses of plantain to cold stress. Plantain seedlings were exposed for 0, 6, and 24 h of cold stress at 8 °C and subsequently allowed to recover for 24 h at 28 °C. A total of 3477 plantain proteins were identified, of which 809 showed differential expression from the three treatments. The majority of differentially expressed proteins were predicted to be involved in oxidation-reduction, including oxylipin biosynthesis, whereas others were associated with photosynthesis, photorespiration, and several primary metabolic processes, such as carbohydrate metabolic process and fatty acid beta-oxidation. Western blot analysis and enzyme activity assays were performed on seven differentially expressed, cold-response candidate plantain proteins to validate the proteomics data. Similar analyses of the seven candidate proteins were performed in cold-sensitive banana to examine possible functional conservation, and to compare the results to equivalent responses between the two species. Consistent results were achieved by Western blot and enzyme activity assays, demonstrating that the quantitative proteomics data collected in this study are reliable. Our results suggest that an increase of antioxidant capacity through adapted ROS scavenging capability, reduced production of ROS, and decreased lipid peroxidation contribute to molecular mechanisms for the increased cold tolerance in plantain. To the best of our knowledge, this is the first report of a global investigation on molecular responses of plantain to cold stress by

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.

Molecular Diagnostics in Colorectal Carcinoma: Advances and Applications for 2018.

PubMed

Bhalla, Amarpreet; Zulfiqar, Muhammad; Bluth, Martin H

2018-06-01

The molecular pathogenesis and classification of colorectal carcinoma are based on the traditional adenomaecarcinoma sequence, serrated polyp pathway, and microsatellite instability (MSI). The genetic basis for hereditary nonpolyposis colorectal cancer is the detection of mutations in the MLH1, MSH2, MSH6, PMS2, and EPCAM genes. Genetic testing for Lynch syndrome includes MSI testing, methylator phenotype testing, BRAF mutation testing, and molecular testing for germline mutations in MMR genes. Molecular makers with predictive and prognostic implications include quantitative multigene reverse transcriptase polymerase chain reaction assay and KRAS and BRAF mutation analysis. Mismatch repair-deficient tumors have higher rates of programmed death-ligand 1 expression. Cell-free DNA analysis in fluids are proving beneficial for diagnosis and prognosis in these disease states towards effective patient management. Copyright © 2018 Elsevier Inc. All rights reserved.

Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology

DTIC Science & Technology

2000-01-20

numbers for hydrogen-filled molecular structure, hydrogen-suppressed molecular structure, and van der Waals volume. Van der Waals...relative covalent radii Geometrical Vw van der Waals volume 3DW 3-D Wiener number for the hydrogen-suppressed geometric distance matrix...molecular structure, and van der Waals volume. Van der Waals volume, Vw (Bondi 1964). was calculated using Sybyl 6.1 from Tripos As- sociates. Inc

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.

Combined analysis of mRNA and miRNA identifies dehydration and salinity responsive key molecular players in citrus roots.

PubMed

Xie, Rangjin; Zhang, Jin; Ma, Yanyan; Pan, Xiaoting; Dong, Cuicui; Pang, Shaoping; He, Shaolan; Deng, Lie; Yi, Shilai; Zheng, Yongqiang; Lv, Qiang

2017-02-06

Citrus is one of the most economically important fruit crops around world. Drought and salinity stresses adversely affected its productivity and fruit quality. However, the genetic regulatory networks and signaling pathways involved in drought and salinity remain to be elucidated. With RNA-seq and sRNA-seq, an integrative analysis of miRNA and mRNA expression profiling and their regulatory networks were conducted using citrus roots subjected to dehydration and salt treatment. Differentially expressed (DE) mRNA and miRNA profiles were obtained according to fold change analysis and the relationships between miRNAs and target mRNAs were found to be coherent and incoherent in the regulatory networks. GO enrichment analysis revealed that some crucial biological processes related to signal transduction (e.g. 'MAPK cascade'), hormone-mediated signaling pathways (e.g. abscisic acid- activated signaling pathway'), reactive oxygen species (ROS) metabolic process (e.g. 'hydrogen peroxide catabolic process') and transcription factors (e.g., 'MYB, ZFP and bZIP') were involved in dehydration and/or salt treatment. The molecular players in response to dehydration and salt treatment were partially overlapping. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-seq and sRNA-seq analysis. This study provides new insights into the molecular mechanisms how citrus roots respond to dehydration and salt treatment.

Combined analysis of mRNA and miRNA identifies dehydration and salinity responsive key molecular players in citrus roots

PubMed Central

Xie, Rangjin; Zhang, Jin; Ma, Yanyan; Pan, Xiaoting; Dong, Cuicui; Pang, Shaoping; He, Shaolan; Deng, Lie; Yi, Shilai; Zheng, Yongqiang; Lv, Qiang

2017-01-01

Citrus is one of the most economically important fruit crops around world. Drought and salinity stresses adversely affected its productivity and fruit quality. However, the genetic regulatory networks and signaling pathways involved in drought and salinity remain to be elucidated. With RNA-seq and sRNA-seq, an integrative analysis of miRNA and mRNA expression profiling and their regulatory networks were conducted using citrus roots subjected to dehydration and salt treatment. Differentially expressed (DE) mRNA and miRNA profiles were obtained according to fold change analysis and the relationships between miRNAs and target mRNAs were found to be coherent and incoherent in the regulatory networks. GO enrichment analysis revealed that some crucial biological processes related to signal transduction (e.g. ‘MAPK cascade’), hormone-mediated signaling pathways (e.g. abscisic acid- activated signaling pathway’), reactive oxygen species (ROS) metabolic process (e.g. ‘hydrogen peroxide catabolic process’) and transcription factors (e.g., ‘MYB, ZFP and bZIP’) were involved in dehydration and/or salt treatment. The molecular players in response to dehydration and salt treatment were partially overlapping. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-seq and sRNA-seq analysis. This study provides new insights into the molecular mechanisms how citrus roots respond to dehydration and salt treatment. PMID:28165059

Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-04-01

Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q 2 of 0.578, R 2 of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 of 0.554, R 2 of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r 2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative Glycoproteomics Analysis Reveals Changes in N-Glycosylation Level Associated with Pancreatic Ductal Adenocarcinoma

PubMed Central

2015-01-01

Glycosylation plays an important role in epithelial cancers, including pancreatic ductal adenocarcinoma. However, little is known about the glycoproteome of the human pancreas or its alterations associated with pancreatic tumorigenesis. Using quantitative glycoproteomics approach, we investigated protein N-glycosylation in pancreatic tumor tissue in comparison with normal pancreas and chronic pancreatitis tissue. The study lead to the discovery of a roster of glycoproteins with aberrant N-glycosylation level associated with pancreatic cancer, including mucin-5AC (MUC5AC), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), insulin-like growth factor binding protein (IGFBP3), and galectin-3-binding protein (LGALS3BP). Pathway analysis of cancer-associated aberrant glycoproteins revealed an emerging phenomenon that increased activity of N-glycosylation was implicated in several pancreatic cancer pathways, including TGF-β, TNF, NF-kappa-B, and TFEB-related lysosomal changes. In addition, the study provided evidence that specific N-glycosylation sites within certain individual proteins can have significantly altered glycosylation occupancy in pancreatic cancer, reflecting the complexity of the molecular mechanisms underlying cancer-associated glycosylation events. PMID:24471499

Quantitative glycoproteomics analysis reveals changes in N-glycosylation level associated with pancreatic ductal adenocarcinoma.

PubMed

Pan, Sheng; Chen, Ru; Tamura, Yasuko; Crispin, David A; Lai, Lisa A; May, Damon H; McIntosh, Martin W; Goodlett, David R; Brentnall, Teresa A

2014-03-07

Glycosylation plays an important role in epithelial cancers, including pancreatic ductal adenocarcinoma. However, little is known about the glycoproteome of the human pancreas or its alterations associated with pancreatic tumorigenesis. Using quantitative glycoproteomics approach, we investigated protein N-glycosylation in pancreatic tumor tissue in comparison with normal pancreas and chronic pancreatitis tissue. The study lead to the discovery of a roster of glycoproteins with aberrant N-glycosylation level associated with pancreatic cancer, including mucin-5AC (MUC5AC), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), insulin-like growth factor binding protein (IGFBP3), and galectin-3-binding protein (LGALS3BP). Pathway analysis of cancer-associated aberrant glycoproteins revealed an emerging phenomenon that increased activity of N-glycosylation was implicated in several pancreatic cancer pathways, including TGF-β, TNF, NF-kappa-B, and TFEB-related lysosomal changes. In addition, the study provided evidence that specific N-glycosylation sites within certain individual proteins can have significantly altered glycosylation occupancy in pancreatic cancer, reflecting the complexity of the molecular mechanisms underlying cancer-associated glycosylation events.

Quantitative analysis of small molecule-nucleic acid interactions with a biosensor surface and surface plasmon resonance detection.

PubMed

Liu, Yang; Wilson, W David

2010-01-01

Surface plasmon resonance (SPR) technology with biosensor surfaces has become a widely-used tool for the study of nucleic acid interactions without any labeling requirements. The method provides simultaneous kinetic and equilibrium characterization of the interactions of biomolecules as well as small molecule-biopolymer binding. SPR monitors molecular interactions in real time and provides significant advantages over optical or calorimetic methods for systems with strong binding coupled to small spectroscopic signals and/or reaction heats. A detailed and practical guide for nucleic acid interaction analysis using SPR-biosensor methods is presented. Details of the SPR technology and basic fundamentals are described with recommendations on the preparation of the SPR instrument, sensor chips, and samples, as well as extensive information on experimental design, quantitative and qualitative data analysis and presentation. A specific example of the interaction of a minor-groove-binding agent with DNA is evaluated by both kinetic and steady-state SPR methods to illustrate the technique. Since the molecules that bind cooperatively to specific DNA sequences are attractive for many applications, a cooperative small molecule-DNA interaction is also presented.

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Determining risk for severe leptospirosis by molecular analysis of environmental surface waters for pathogenic Leptospira.

PubMed

Ganoza, Christian A; Matthias, Michael A; Collins-Richards, Devon; Brouwer, Kimberly C; Cunningham, Calaveras B; Segura, Eddy R; Gilman, Robert H; Gotuzzo, Eduardo; Vinetz, Joseph M

2006-08-01

Although previous data indicate that the overall incidence of human leptospirosis in the Peruvian Amazon is similar in urban and rural sites, severe leptospirosis has been observed only in the urban context. As a potential explanation for this epidemiological observation, we tested the hypothesis that concentrations of more virulent Leptospira would be higher in urban than in rural environmental surface waters. A quantitative real-time PCR assay was used to compare levels of Leptospira in urban and rural environmental surface waters in sites in the Peruvian Amazon region of Iquitos. Molecular taxonomic analysis of a 1,200-bp segment of the leptospiral 16S ribosomal RNA gene was used to identify Leptospira to the species level. Pathogenic Leptospira species were found only in urban slum water sources (Fisher's exact test; p = 0.013). The concentration of pathogen-related Leptospira was higher in urban than rural water sources (approximately 10(3) leptospires/ml versus 0.5 x 10(2) leptospires/ml; F = 8.406, p < 0.05). Identical 16S rRNA gene sequences from Leptospira interrogans serovar Icterohaemorrhagiae were found in urban slum market area gutter water and in human isolates, suggesting a specific mode of transmission from rats to humans. In a prospective, population-based study of patients presenting with acute febrile illness, isolation of L. interrogans-related leptospires from humans was significantly associated with urban acquisition (75% of urban isolates); human isolates of other leptospiral species were associated with rural acquisition (78% of rural isolates) (chi-square analysis; p < 0.01). This distribution of human leptospiral isolates mirrored the distribution of leptospiral 16S ribosomal gene sequences in urban and rural water sources. Our findings data support the hypothesis that urban severe leptospirosis in the Peruvian Amazon is associated with higher concentrations of more pathogenic leptospires at sites of exposure and transmission. This

Determining Risk for Severe Leptospirosis by Molecular Analysis of Environmental Surface Waters for Pathogenic Leptospira

PubMed Central

Collins-Richards, Devon; Brouwer, Kimberly C; Cunningham, Calaveras B; Segura, Eddy R; Gilman, Robert H; Gotuzzo, Eduardo; Vinetz, Joseph M

2006-01-01

Background Although previous data indicate that the overall incidence of human leptospirosis in the Peruvian Amazon is similar in urban and rural sites, severe leptospirosis has been observed only in the urban context. As a potential explanation for this epidemiological observation, we tested the hypothesis that concentrations of more virulent Leptospira would be higher in urban than in rural environmental surface waters. Methods and Findings A quantitative real-time PCR assay was used to compare levels of Leptospira in urban and rural environmental surface waters in sites in the Peruvian Amazon region of Iquitos. Molecular taxonomic analysis of a 1,200-bp segment of the leptospiral 16S ribosomal RNA gene was used to identify Leptospira to the species level. Pathogenic Leptospira species were found only in urban slum water sources (Fisher's exact test; p = 0.013). The concentration of pathogen-related Leptospira was higher in urban than rural water sources (~103 leptospires/ml versus 0.5 × 102 leptospires/ml; F = 8.406, p < 0.05). Identical 16S rRNA gene sequences from Leptospira interrogans serovar Icterohaemorrhagiae were found in urban slum market area gutter water and in human isolates, suggesting a specific mode of transmission from rats to humans. In a prospective, population-based study of patients presenting with acute febrile illness, isolation of L. interrogans-related leptospires from humans was significantly associated with urban acquisition (75% of urban isolates); human isolates of other leptospiral species were associated with rural acquisition (78% of rural isolates) (chi-square analysis; p < 0.01). This distribution of human leptospiral isolates mirrored the distribution of leptospiral 16S ribosomal gene sequences in urban and rural water sources. Conclusions Our findings data support the hypothesis that urban severe leptospirosis in the Peruvian Amazon is associated with higher concentrations of more pathogenic leptospires at sites of exposure

Quantitative analysis of biological tissues using Fourier transform-second-harmonic generation imaging

NASA Astrophysics Data System (ADS)

Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.

2010-02-01

We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.

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.

Molecular cloning and expression profile analysis of porcine TCAP gene.

PubMed

Cheng, Hunjun; Xu, Xuewen; Zhao, Shuhong; Liu, Bang; Yu, Mei; Fan, Bin

2010-03-01

The gradually discovered sarcomeric proteins play important roles for structural integrity and signal transduction of sarcomere during myofibril genesis. TCAP (also described as telethonin, T-cap), one of the sarcomeric protein genes, is regulated developmentally. In this study, we reported the molecular characteristics of porcine TCAP gene. A 979 bp TCAP cDNA nucleotide sequence was obtained in pig and the deduced amino acid sequence had 92 and 91% identity to those of human and mouse homologous genes, respectively. One SNP was discovered and the allele frequency analysis showed that G allele frequency was low among 221 unrelated pigs from seven breeds. The tissue distribution patterns revealed that TCAP mRNA was expressed abundantly in skeletal and heart muscle tissue. Real-time quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) results displayed TCAP mRNA was up-regulated in both Tongcheng and Landrace pigs during prenatal skeletal muscle development stages. This study suggested that TCAP gene might be a prospective candidate gene affecting muscle mass and meat quality traits in the pig, and also implicated the possible significance of TCAP on sarcomere assembly.

[Quantitative Analysis of Heavy Metals in Water with LIBS Based on Signal-to-Background Ratio].

PubMed

Hu, Li; Zhao, Nan-jing; Liu, Wen-qing; Fang, Li; Zhang, Da-hai; Wang, Yin; Meng, De Shuo; Yu, Yang; Ma, Ming-jun

2015-07-01

There are many influence factors in the precision and accuracy of the quantitative analysis with LIBS technology. According to approximately the same characteristics trend of background spectrum and characteristic spectrum along with the change of temperature through in-depth analysis, signal-to-background ratio (S/B) measurement and regression analysis could compensate the spectral line intensity changes caused by system parameters such as laser power, spectral efficiency of receiving. Because the measurement dates were limited and nonlinear, we used support vector machine (SVM) for regression algorithm. The experimental results showed that the method could improve the stability and the accuracy of quantitative analysis of LIBS, and the relative standard deviation and average relative error of test set respectively were 4.7% and 9.5%. Data fitting method based on signal-to-background ratio(S/B) is Less susceptible to matrix elements and background spectrum etc, and provides data processing reference for real-time online LIBS quantitative analysis technology.

Quantitative PET/CT scanner performance characterization based upon the society of nuclear medicine and molecular imaging clinical trials network oncology clinical simulator phantom.

PubMed

Sunderland, John J; Christian, Paul E

2015-01-01

The Clinical Trials Network (CTN) of the Society of Nuclear Medicine and Molecular Imaging (SNMMI) operates a PET/CT phantom imaging program using the CTN's oncology clinical simulator phantom, designed to validate scanners at sites that wish to participate in oncology clinical trials. Since its inception in 2008, the CTN has collected 406 well-characterized phantom datasets from 237 scanners at 170 imaging sites covering the spectrum of commercially available PET/CT systems. The combined and collated phantom data describe a global profile of quantitative performance and variability of PET/CT data used in both clinical practice and clinical trials. Individual sites filled and imaged the CTN oncology PET phantom according to detailed instructions. Standard clinical reconstructions were requested and submitted. The phantom itself contains uniform regions suitable for scanner calibration assessment, lung fields, and 6 hot spheric lesions with diameters ranging from 7 to 20 mm at a 4:1 contrast ratio with primary background. The CTN Phantom Imaging Core evaluated the quality of the phantom fill and imaging and measured background standardized uptake values to assess scanner calibration and maximum standardized uptake values of all 6 lesions to review quantitative performance. Scanner make-and-model-specific measurements were pooled and then subdivided by reconstruction to create scanner-specific quantitative profiles. Different makes and models of scanners predictably demonstrated different quantitative performance profiles including, in some cases, small calibration bias. Differences in site-specific reconstruction parameters increased the quantitative variability among similar scanners, with postreconstruction smoothing filters being the most influential parameter. Quantitative assessment of this intrascanner variability over this large collection of phantom data gives, for the first time, estimates of reconstruction variance introduced into trials from allowing

Correlative SEM SERS for quantitative analysis of dimer nanoparticles.

PubMed

Timmermans, F J; Lenferink, A T M; van Wolferen, H A G M; Otto, C

2016-11-14

A Raman microscope integrated with a scanning electron microscope was used to investigate plasmonic structures by correlative SEM-SERS analysis. The integrated Raman-SEM microscope combines high-resolution electron microscopy information with SERS signal enhancement from selected nanostructures with adsorbed Raman reporter molecules. Correlative analysis is performed for dimers of two gold nanospheres. Dimers were selected on the basis of SEM images from multi aggregate samples. The effect of the orientation of the dimer with respect to the polarization state of the laser light and the effect of the particle gap size on the Raman signal intensity is observed. Additionally, calculations are performed to simulate the electric near field enhancement. These simulations are based on the morphologies observed by electron microscopy. In this way the experiments are compared with the enhancement factor calculated with near field simulations and are subsequently used to quantify the SERS enhancement factor. Large differences between experimentally observed and calculated enhancement factors are regularly detected, a phenomenon caused by nanoscale differences between the real and 'simplified' simulated structures. Quantitative SERS experiments reveal the structure induced enhancement factor, ranging from ∼200 to ∼20 000, averaged over the full nanostructure surface. The results demonstrate correlative Raman-SEM microscopy for the quantitative analysis of plasmonic particles and structures, thus enabling a new analytical method in the field of SERS and plasmonics.

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.

Identification and quantitation of semi-crystalline microplastics using image analysis and differential scanning calorimetry.

PubMed

Rodríguez Chialanza, Mauricio; Sierra, Ignacio; Pérez Parada, Andrés; Fornaro, Laura

2018-06-01

There are several techniques used to analyze microplastics. These are often based on a combination of visual and spectroscopic techniques. Here we introduce an alternative workflow for identification and mass quantitation through a combination of optical microscopy with image analysis (IA) and differential scanning calorimetry (DSC). We studied four synthetic polymers with environmental concern: low and high density polyethylene (LDPE and HDPE, respectively), polypropylene (PP), and polyethylene terephthalate (PET). Selected experiments were conducted to investigate (i) particle characterization and counting procedures based on image analysis with open-source software, (ii) chemical identification of microplastics based on DSC signal processing, (iii) dependence of particle size on DSC signal, and (iv) quantitation of microplastics mass based on DSC signal. We describe the potential and limitations of these techniques to increase reliability for microplastic analysis. Particle size demonstrated to have particular incidence in the qualitative and quantitative performance of DSC signals. Both, identification (based on characteristic onset temperature) and mass quantitation (based on heat flow) showed to be affected by particle size. As a result, a proper sample treatment which includes sieving of suspended particles is particularly required for this analytical approach.

Quantitative interpretation of molecular dynamics simulations for X-ray photoelectron spectroscopy of aqueous solutions

NASA Astrophysics Data System (ADS)

Olivieri, Giorgia; Parry, Krista M.; Powell, Cedric J.; Tobias, Douglas J.; Brown, Matthew A.

2016-04-01

Over the past decade, energy-dependent ambient pressure X-ray photoelectron spectroscopy (XPS) has emerged as a powerful analytical probe of the ion spatial distributions at the vapor (vacuum)-aqueous electrolyte interface. These experiments are often paired with complementary molecular dynamics (MD) simulations in an attempt to provide a complete description of the liquid interface. There is, however, no systematic protocol that permits a straightforward comparison of the two sets of results. XPS is an integrated technique that averages signals from multiple layers in a solution even at the lowest photoelectron kinetic energies routinely employed, whereas MD simulations provide a microscopic layer-by-layer description of the solution composition near the interface. Here, we use the National Institute of Standards and Technology database for the Simulation of Electron Spectra for Surface Analysis (SESSA) to quantitatively interpret atom-density profiles from MD simulations for XPS signal intensities using sodium and potassium iodide solutions as examples. We show that electron inelastic mean free paths calculated from a semi-empirical formula depend strongly on solution composition, varying by up to 30% between pure water and concentrated NaI. The XPS signal thus arises from different information depths in different solutions for a fixed photoelectron kinetic energy. XPS signal intensities are calculated using SESSA as a function of photoelectron kinetic energy (probe depth) and compared with a widely employed ad hoc method. SESSA simulations illustrate the importance of accounting for elastic-scattering events at low photoelectron kinetic energies (<300 eV) where the ad hoc method systematically underestimates the preferential enhancement of anions over cations. Finally, some technical aspects of applying SESSA to liquid interfaces are discussed.

Quantitative analysis of chromosome condensation in fission yeast.

PubMed

Petrova, Boryana; Dehler, Sascha; Kruitwagen, Tom; Hériché, Jean-Karim; Miura, Kota; Haering, Christian H

2013-03-01

Chromosomes undergo extensive conformational rearrangements in preparation for their segregation during cell divisions. Insights into the molecular mechanisms behind this still poorly understood condensation process require the development of new approaches to quantitatively assess chromosome formation in vivo. In this study, we present a live-cell microscopy-based chromosome condensation assay in the fission yeast Schizosaccharomyces pombe. By automatically tracking the three-dimensional distance changes between fluorescently marked chromosome loci at high temporal and spatial resolution, we analyze chromosome condensation during mitosis and meiosis and deduct defined parameters to describe condensation dynamics. We demonstrate that this method can determine the contributions of condensin, topoisomerase II, and Aurora kinase to mitotic chromosome condensation. We furthermore show that the assay can identify proteins required for mitotic chromosome formation de novo by isolating mutants in condensin, DNA polymerase ε, and F-box DNA helicase I that are specifically defective in pro-/metaphase condensation. Thus, the chromosome condensation assay provides a direct and sensitive system for the discovery and characterization of components of the chromosome condensation machinery in a genetically tractable eukaryote.

Quantitative Analysis of Chromosome Condensation in Fission Yeast

PubMed Central

Petrova, Boryana; Dehler, Sascha; Kruitwagen, Tom; Hériché, Jean-Karim; Miura, Kota

2013-01-01

Chromosomes undergo extensive conformational rearrangements in preparation for their segregation during cell divisions. Insights into the molecular mechanisms behind this still poorly understood condensation process require the development of new approaches to quantitatively assess chromosome formation in vivo. In this study, we present a live-cell microscopy-based chromosome condensation assay in the fission yeast Schizosaccharomyces pombe. By automatically tracking the three-dimensional distance changes between fluorescently marked chromosome loci at high temporal and spatial resolution, we analyze chromosome condensation during mitosis and meiosis and deduct defined parameters to describe condensation dynamics. We demonstrate that this method can determine the contributions of condensin, topoisomerase II, and Aurora kinase to mitotic chromosome condensation. We furthermore show that the assay can identify proteins required for mitotic chromosome formation de novo by isolating mutants in condensin, DNA polymerase ε, and F-box DNA helicase I that are specifically defective in pro-/metaphase condensation. Thus, the chromosome condensation assay provides a direct and sensitive system for the discovery and characterization of components of the chromosome condensation machinery in a genetically tractable eukaryote. PMID:23263988

Quantitative proteomic analysis of age-related subventricular zone proteins associated with neurodegenerative disease.

PubMed

Wang, Xianli; Dong, Chuanming; Sun, Lixin; Zhu, Liang; Sun, Chenxi; Ma, Rongjie; Ning, Ke; Lu, Bing; Zhang, Jinfu; Xu, Jun

2016-11-18

Aging is characterized by a progressive decline in the function of adult tissues which can lead to neurodegenerative disorders. However, little is known about the correlation between protein changes in the subventricular zone (SVZ) and neurodegenerative diseases with age. In the present study, neural stem cells (NSCs) were derived from the SVZ on postnatal 7 d, 1 m, and 12 m-old mice. With age, NSCs exhibited increased SA-β-gal activity and decreased proliferation and pool size in the SVZ zone, and were associated with elevated inflammatory chemokines and cytokines. Furthermore, quantitative proteomics and ingenuity pathway analysis were used to evaluate the significant age-related alterations in proteins and their functions. Some downregulated proteins such as DPYSL2, TPI1, ALDH, and UCHL1 were found to play critical roles in the neurological disease and PSMA1, PSMA3, PSMC2, PSMD11, and UCHL1 in protein homeostasis. Taken together, we have provided valuable insight into the cellular and molecular processes that underlie aging-associated declines in SVZ neurogenesis for the early detection of differences in gene expression and the potential risk of neurological disease, which is beneficial in the prevention of the diseases.

Quantitative Molecular Detection of Putative Periodontal Pathogens in Clinically Healthy and Periodontally Diseased Subjects

PubMed Central

Göhler, André; Hetzer, Adrian; Holtfreter, Birte; Geisel, Marie Henrike; Schmidt, Carsten Oliver; Steinmetz, Ivo; Kocher, Thomas

2014-01-01

Periodontitis is a multi-microbial oral infection with high prevalence among adults. Putative oral pathogens are commonly found in periodontally diseased individuals. However, these organisms can be also detected in the oral cavity of healthy subjects. This leads to the hypothesis, that alterations in the proportion of these organisms relative to the total amount of oral microorganisms, namely their abundance, rather than their simple presence might be important in the transition from health to disease. Therefore, we developed a quantitative molecular method to determine the abundance of various oral microorganisms and the portion of bacterial and archaeal nucleic acid relative to the total nucleic acid extracted from individual samples. We applied quantitative real-time PCRs targeting single-copy genes of periodontal bacteria and 16S-rRNA genes of Bacteria and Archaea. Testing tongue scrapings of 88 matched pairs of periodontally diseased and healthy subjects revealed a significantly higher abundance of P. gingivalis and a higher total bacterial abundance in diseased subjects. In fully adjusted models the risk of being periodontally diseased was significantly higher in subjects with high P. gingivalis and total bacterial abundance. Interestingly, we found that moderate abundances of A. actinomycetemcomitans were associated with reduced risk for periodontal disease compared to subjects with low abundances, whereas for high abundances, this protective effect leveled off. Moderate archaeal abundances were health associated compared to subjects with low abundances. In conclusion, our methodological approach unraveled associations of the oral flora with periodontal disease, which would have gone undetected if only qualitative data had been determined. PMID:25029268

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

NASA Astrophysics Data System (ADS)

Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

2015-03-01

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

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

Quantitative SIMS Imaging of Agar-Based Microbial Communities.

PubMed

Dunham, Sage J B; Ellis, Joseph F; Baig, Nameera F; Morales-Soto, Nydia; Cao, Tianyuan; Shrout, Joshua D; Bohn, Paul W; Sweedler, Jonathan V

2018-05-01

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

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.

Cytogenetic and molecular analysis in Angelman syndrome.

PubMed

Zackowski, J L; Nicholls, R D; Gray, B A; Bent-Williams, A; Gottlieb, W; Harris, P J; Waters, M F; Driscoll, D J; Zori, R T; Williams, C A

1993-04-01

We report on cytogenetic and molecular analyses of 29 Angelman syndrome (AS) individuals ascertained in 1990 through the first National Angelman Syndrome Conference. High resolution GTG- and GBG-banded chromosomes were studied. Standard molecular analysis with six 15q11q13 DNA sequences was used to analyze copy number and parental origin of 15q11q13. Concordance between molecular and cytogenetic data was excellent. The combined data showed that 23 of the 27 probands (85%) on whom we had definitive results have deletions of the chromosome 15q11q13 region. Two classes of deletion were detected molecularly: most patients were deleted for the 5 more proximal probes, but in 2 cases the deletion extended distally to include in sixth probe. In the 13 cases where the parental origin of the deleted chromosome 15 could be established, it was maternal. There were no cases of uniparental disomy. Cytological observations of the relative sizes of the heterochromatic regions of the short arm of chromosome 15 suggested that chromosomes with large heterochromatic blocks may be more prone to de novo deletion.

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.

[Comparative cost analysis of molecular biology methods in the diagnosis of sarcomas].

PubMed

Baffert, Sandrine; Italiano, Antoine; Pierron, Gaëlle; Traoré, Marie-Angèle; Rapp, Jocelyn; Escande, Fabienne; Ghnassia, Jean-Pierre; Terrier, Philippe; Voegeli, Anne-Claire; Ranchere-Vince, Dominique; Coindre, Jean-Michel; Pedeutour, Florence

2013-10-01

Sarcomas represent a complex and heterogeneous group of rare malignant tumors and their correct diagnosis is often difficult. Recent molecular biological techniques have been of great diagnostic use and there is a need to assess the cost of these procedures in routine clinical practice. Using prospective and observational data from eight molecular biology laboratories in France, we used "microcosting" method to assess the cost of molecular biological techniques in the diagnosis of five types of sarcoma. The mean cost of fluorescence in situ hybridization (FISH) was 318 € (273-393) per sample; mean reverse transcription polymerase chain reaction (RT-PCR) cost ranged from 300 € (229-481) per formalin-fixed, paraffin-embedded specimen to 258 € (213-339) per frozen specimen; mean quantitative polymerase chain reaction (Q-PCR) cost was 184 € (112-229) and mean CGH-array cost was 332 € (329-335). The cost of these recently implemented techniques varied according to the type of sarcoma; the method of tissue collection and local organizational factors including the level of local expertise and investment. The cost of molecular diagnostic techniques needs to be balanced against their respective performance.

Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

PubMed

Wolf, Antje; Kirschner, Karl N

2013-02-01

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained.

Quantitative spectroscopy for the analysis of GOME data

NASA Technical Reports Server (NTRS)

Chance, K.

1997-01-01

Accurate analysis of the global ozone monitoring experiment (GOME) data to obtain atmospheric constituents requires reliable, traceable spectroscopic parameters for atmospheric absorption and scattering. Results are summarized for research that includes: the re-determination of Rayleigh scattering cross sections and phase functions for the 200 nm to 1000 nm range; the analysis of solar spectra to obtain a high-resolution reference spectrum with excellent absolute vacuum wavelength calibration; Ring effect cross sections and phase functions determined directly from accurate molecular parameters of N2 and O2; O2 A band line intensities and pressure broadening coefficients; and the analysis of absolute accuracies for ultraviolet and visible absorption cross sections of O3 and other trace species measurable by GOME.

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

Impact of Cadmium on Intracellular Zinc Levels in HepG2 Cells: Quantitative Evaluations and Molecular Effects.

PubMed

Urani, Chiara; Melchioretto, Pasquale; Bruschi, Maurizio; Fabbri, Marco; Sacco, Maria Grazia; Gribaldo, Laura

2015-01-01

Cadmium is classified as a human carcinogen, and its disturbance in zinc homeostasis has been well established. However, its extent as well as molecular mechanisms involved in cadmium carcinogenesis has yet to be fully clarified. To this end, we used the zinc specific probe Zinquin to visualize and to quantitatively evaluate changes in the concentration of labile zinc, in an in vitro model of human hepatic cells (HepG2) exposed to cadmium. A very large increase (+93%) of intracellular labile zinc, displaced by cadmium from the zinc proteome, was measured when HepG2 were exposed to 10 µM cadmium for 24 hrs. Microarray expression profiling showed that in cells, featuring an increase of labile zinc after cadmium exposure, one of the top regulated genes is Snail1 (+3.6), which is included in the adherens junction pathway and linked to cancer. In the same pathway MET, TGF-βR, and two members of the Rho-family GTPase, Rac, and cdc42 all implicated in the loss of adherence features and acquisition of migratory and cancer properties were regulated, as well. The microRNAs analysis showed a downregulation of miR-34a and miR-200a, both implicated in the epithelial-mesenchymal transition. These microRNAs results support the role played by zinc in affecting gene expression at the posttranscriptional level.

A thioacidolysis method tailored for higher‐throughput quantitative analysis of lignin monomers

PubMed Central

Foster, Cliff; Happs, Renee M.; Doeppke, Crissa; Meunier, Kristoffer; Gehan, Jackson; Yue, Fengxia; Lu, Fachuang; Davis, Mark F.

2016-01-01

Abstract Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β‐O‐4 linkages. Current thioacidolysis methods are low‐throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non‐chlorinated organic solvent and is tailored for higher‐throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1–2 mg of biomass per assay and has been quantified using fast‐GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, including standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day‐to‐day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. The method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses. PMID:27534715

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

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

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

A thioacidolysis method tailored for higher-throughput quantitative analysis of lignin monomers

DOE PAGES

Harman-Ware, Anne E.; Foster, Cliff; Happs, Renee M.; ...

2016-09-14

Thioacidolysis is a method used to measure the relative content of lignin monomers bound by β-O-4 linkages. Current thioacidolysis methods are low-throughput as they require tedious steps for reaction product concentration prior to analysis using standard GC methods. A quantitative thioacidolysis method that is accessible with general laboratory equipment and uses a non-chlorinated organic solvent and is tailored for higher-throughput analysis is reported. The method utilizes lignin arylglycerol monomer standards for calibration, requires 1-2 mg of biomass per assay and has been quantified using fast-GC techniques including a Low Thermal Mass Modular Accelerated Column Heater (LTM MACH). Cumbersome steps, includingmore » standard purification, sample concentrating and drying have been eliminated to help aid in consecutive day-to-day analyses needed to sustain a high sample throughput for large screening experiments without the loss of quantitation accuracy. As a result, the method reported in this manuscript has been quantitatively validated against a commonly used thioacidolysis method and across two different research sites with three common biomass varieties to represent hardwoods, softwoods, and grasses.« less

QuASAR: quantitative allele-specific analysis of reads.

PubMed

Harvey, Chris T; Moyerbrailean, Gregory A; Davis, Gordon O; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-04-15

Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. http://github.com/piquelab/QuASAR. fluca@wayne.edu or rpique@wayne.edu Supplementary Material is available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

QuASAR: quantitative allele-specific analysis of reads

PubMed Central

Harvey, Chris T.; Moyerbrailean, Gregory A.; Davis, Gordon O.; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-01-01

Motivation: Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. Results: We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. Availability and implementation: http://github.com/piquelab/QuASAR. Contact: fluca@wayne.edu or rpique@wayne.edu Supplementary information: Supplementary Material is available at Bioinformatics online. PMID:25480375

Quantitative analysis of NMR spectra with chemometrics

NASA Astrophysics Data System (ADS)

Winning, H.; Larsen, F. H.; Bro, R.; Engelsen, S. B.

2008-01-01

The number of applications of chemometrics to series of NMR spectra is rapidly increasing due to an emerging interest for quantitative NMR spectroscopy e.g. in the pharmaceutical and food industries. This paper gives an analysis of advantages and limitations of applying the two most common chemometric procedures, Principal Component Analysis (PCA) and Multivariate Curve Resolution (MCR), to a designed set of 231 simple alcohol mixture (propanol, butanol and pentanol) 1H 400 MHz spectra. The study clearly demonstrates that the major advantage of chemometrics is the visualisation of larger data structures which adds a new exploratory dimension to NMR research. While robustness and powerful data visualisation and exploration are the main qualities of the PCA method, the study demonstrates that the bilinear MCR method is an even more powerful method for resolving pure component NMR spectra from mixtures when certain conditions are met.

Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

PubMed

Kaur, Punit; Asea, Alexzander

2011-01-01

Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

Quantitatively probing propensity for structural transitions in engineered virus nanoparticles by single-molecule mechanical analysis

NASA Astrophysics Data System (ADS)

Castellanos, Milagros; Carrillo, Pablo J. P.; Mateu, Mauricio G.

2015-03-01

Viruses are increasingly being studied from the perspective of fundamental physics at the nanoscale as biologically evolved nanodevices with many technological applications. In viral particles of the minute virus of mice (MVM), folded segments of the single-stranded DNA genome are bound to the capsid inner wall and act as molecular buttresses that increase locally the mechanical stiffness of the particle. We have explored whether a quantitative linkage exists in MVM particles between their DNA-mediated stiffening and impairment of a heat-induced, virus-inactivating structural change. A series of structurally modified virus particles with disrupted capsid-DNA interactions and/or distorted capsid cavities close to the DNA-binding sites were engineered and characterized, both in classic kinetics assays and by single-molecule mechanical analysis using atomic force microscopy. The rate constant of the virus inactivation reaction was found to decrease exponentially with the increase in elastic constant (stiffness) of the regions closer to DNA-binding sites. The application of transition state theory suggests that the height of the free energy barrier of the virus-inactivating structural transition increases linearly with local mechanical stiffness. From a virological perspective, the results indicate that infectious MVM particles may have acquired the biological advantage of increased survival under thermal stress by evolving architectural elements that rigidify the particle and impair non-productive structural changes. From a nanotechnological perspective, this study provides proof of principle that determination of mechanical stiffness and its manipulation by protein engineering may be applied for quantitatively probing and tuning the conformational dynamics of virus-based and other protein-based nanoassemblies.Viruses are increasingly being studied from the perspective of fundamental physics at the nanoscale as biologically evolved nanodevices with many technological

Quantitative self-assembly prediction yields targeted nanomedicines

NASA Astrophysics Data System (ADS)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

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.

Optical measurement of transverse molecular diffusion in a microchannel.

PubMed Central

Kamholz, A E; Schilling, E A; Yager, P

2001-01-01

Quantitative analysis of molecular diffusion is a necessity for the efficient design of most microfluidic devices as well as an important biophysical method in its own right. This study demonstrates the rapid measurement of diffusion coefficients of large and small molecules in a microfluidic device, the T-sensor, by means of conventional epifluorescence microscopy. Data were collected by monitoring the transverse flux of analyte from a sample stream into a second stream flowing alongside it. As indicated by the low Reynolds numbers of the system (< 1), flow is laminar, and molecular transport between streams occurs only by diffusion. Quantitative determinations were made by fitting data with predictions of a one-dimensional model. Analysis was made of the flow development and its effect on the distribution of diffusing analyte using a three-dimensional modeling software package. Diffusion coefficients were measured for four fluorescently labeled molecules: fluorescein-biotin, insulin, ovalbumin, and streptavidin. The resulting values differed from accepted results by an average of 2.4%. Microfluidic system parameters can be selected to achieve accurate diffusion coefficient measurements and to optimize other microfluidic devices that rely on precise transverse transport of molecules. PMID:11259309

Low-dose CT for quantitative analysis in acute respiratory distress syndrome

PubMed Central

2013-01-01

Introduction The clinical use of serial quantitative computed tomography (CT) to characterize lung disease and guide the optimization of mechanical ventilation in patients with acute respiratory distress syndrome (ARDS) is limited by the risk of cumulative radiation exposure and by the difficulties and risks related to transferring patients to the CT room. We evaluated the effects of tube current-time product (mAs) variations on quantitative results in healthy lungs and in experimental ARDS in order to support the use of low-dose CT for quantitative analysis. Methods In 14 sheep chest CT was performed at baseline and after the induction of ARDS via intravenous oleic acid injection. For each CT session, two consecutive scans were obtained applying two different mAs: 60 mAs was paired with 140, 15 or 7.5 mAs. All other CT parameters were kept unaltered (tube voltage 120 kVp, collimation 32 × 0.5 mm, pitch 0.85, matrix 512 × 512, pixel size 0.625 × 0.625 mm). Quantitative results obtained at different mAs were compared via Bland-Altman analysis. Results Good agreement was observed between 60 mAs and 140 mAs and between 60 mAs and 15 mAs (all biases less than 1%). A further reduction of mAs to 7.5 mAs caused an increase in the bias of poorly aerated and nonaerated tissue (-2.9% and 2.4%, respectively) and determined a significant widening of the limits of agreement for the same compartments (-10.5% to 4.8% for poorly aerated tissue and -5.9% to 10.8% for nonaerated tissue). Estimated mean effective dose at 140, 60, 15 and 7.5 mAs corresponded to 17.8, 7.4, 2.0 and 0.9 mSv, respectively. Image noise of scans performed at 140, 60, 15 and 7.5 mAs corresponded to 10, 16, 38 and 74 Hounsfield units, respectively. Conclusions A reduction of effective dose up to 70% has been achieved with minimal effects on lung quantitative results. Low-dose computed tomography provides accurate quantitative results and could be used to characterize lung compartment distribution and

Quantitative Imaging in Cancer Clinical Trials

PubMed Central

Yankeelov, Thomas E.; Mankoff, David A.; Schwartz, Lawrence H.; Lieberman, Frank S.; Buatti, John M.; Mountz, James M.; Erickson, Bradley J.; Fennessy, Fiona M.M.; Huang, Wei; Kalpathy-Cramer, Jayashree; Wahl, Richard L.; Linden, Hannah M.; Kinahan, Paul; Zhao, Binsheng; Hylton, Nola M.; Gillies, Robert J.; Clarke, Laurence; Nordstrom, Robert; Rubin, Daniel L.

2015-01-01

As anti-cancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. While traditional, anatomic CT and MRI exams are useful in many settings, there is increasing evidence that these methods cannot answer the fundamental biological and physiological questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients, and to provide a more efficient path for the development of improved targeted therapies. PMID:26773162

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors

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 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.

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

Augmented multivariate image analysis applied to quantitative structure-activity relationship modeling of the phytotoxicities of benzoxazinone herbicides and related compounds on problematic weeds.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2013-09-11

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.

Quantitative imaging as cancer biomarker

NASA Astrophysics Data System (ADS)

Mankoff, David A.

2015-03-01

The ability to assay tumor biologic features and the impact of drugs on tumor biology is fundamental to drug development. Advances in our ability to measure genomics, gene expression, protein expression, and cellular biology have led to a host of new targets for anticancer drug therapy. In translating new drugs into clinical trials and clinical practice, these same assays serve to identify patients most likely to benefit from specific anticancer treatments. As cancer therapy becomes more individualized and targeted, there is an increasing need to characterize tumors and identify therapeutic targets to select therapy most likely to be successful in treating the individual patient's cancer. Thus far assays to identify cancer therapeutic targets or anticancer drug pharmacodynamics have been based upon in vitro assay of tissue or blood samples. Advances in molecular imaging, particularly PET, have led to the ability to perform quantitative non-invasive molecular assays. Imaging has traditionally relied on structural and anatomic features to detect cancer and determine its extent. More recently, imaging has expanded to include the ability to image regional biochemistry and molecular biology, often termed molecular imaging. Molecular imaging can be considered an in vivo assay technique, capable of measuring regional tumor biology without perturbing it. This makes molecular imaging a unique tool for cancer drug development, complementary to traditional assay methods, and a potentially powerful method for guiding targeted therapy in clinical trials and clinical practice. The ability to quantify, in absolute measures, regional in vivo biologic parameters strongly supports the use of molecular imaging as a tool to guide therapy. This review summarizes current and future applications of quantitative molecular imaging as a biomarker for cancer therapy, including the use of imaging to (1) identify patients whose tumors express a specific therapeutic target; (2) determine

Quantitative analysis of titanium concentration using calibration-free laser-induced breakdown spectroscopy (LIBS)

NASA Astrophysics Data System (ADS)

Zaitun; Prasetyo, S.; Suliyanti, M. M.; Isnaeni; Herbani, Y.

2018-03-01

Laser-induced breakdown spectroscopy (LIBS) can be used for quantitative and qualitative analysis. Calibration-free LIBS (CF-LIBS) is a method to quantitatively analyze concentration of elements in a sample in local thermodynamic equilibrium conditions without using available matrix-matched calibration. In this study, we apply CF-LIBS for quantitative analysis of Ti in TiO2 sample. TiO2 powder sample was mixed with polyvinyl alcohol and formed into pellets. An Nd:YAG pulsed laser at a wavelength of 1064 nm was focused onto the sample to generate plasma. The spectrum of plasma was recorded using spectrophotometer then compared to NIST spectral line to determine energy levels and other parameters. The value of plasma temperature obtained using Boltzmann plot is 8127.29 K and electron density from calculation is 2.49×1016 cm-3. Finally, the concentration of Ti in TiO2 sample from this study is 97% that is in proximity with the sample certificate.

Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods

NASA Astrophysics Data System (ADS)

Gilbert, Kathleen M.; Skawinski, William J.; Misra, Milind; Paris, Kristina A.; Naik, Neelam H.; Buono, Ronald A.; Deutsch, Howard M.; Venanzi, Carol A.

2004-11-01

Methylphenidate (MP) binds to the cocaine binding site on the dopamine transporter and inhibits reuptake of dopamine, but does not appear to have the same abuse potential as cocaine. This study, part of a comprehensive effort to identify a drug treatment for cocaine abuse, investigates the effect of choice of calculation technique and of solvent model on the conformational potential energy surface (PES) of MP and a rigid methylphenidate (RMP) analogue which exhibits the same dopamine transporter binding affinity as MP. Conformational analysis was carried out by the AM1 and AM1/SM5.4 semiempirical molecular orbital methods, a molecular mechanics method (Tripos force field with the dielectric set equal to that of vacuum or water) and the HF/6-31G* molecular orbital method in vacuum phase. Although all three methods differ somewhat in the local details of the PES, the general trends are the same for neutral and protonated MP. In vacuum phase, protonation has a distinctive effect in decreasing the regions of space available to the local conformational minima. Solvent has little effect on the PES of the neutral molecule and tends to stabilize the protonated species. The random search (RS) conformational analysis technique using the Tripos force field was found to be capable of locating the minima found by the molecular orbital methods using systematic grid search. This suggests that the RS/Tripos force field/vacuum phase protocol is a reasonable choice for locating the local minima of MP. However, the Tripos force field gave significantly larger phenyl ring rotational barriers than the molecular orbital methods for MP and RMP. For both the neutral and protonated cases, all three methods found the phenyl ring rotational barriers for the RMP conformers/invertamers (denoted as cte, tte, and cta) to be: cte, tte> MP > cta. Solvation has negligible effect on the phenyl ring rotational barrier of RMP. The B3LYP/6-31G* density functional method was used to calculate the phenyl

Random Matrix Theory in molecular dynamics analysis.

PubMed

Palese, Luigi Leonardo

2015-01-01

It is well known that, in some situations, principal component analysis (PCA) carried out on molecular dynamics data results in the appearance of cosine-shaped low index projections. Because this is reminiscent of the results obtained by performing PCA on a multidimensional Brownian dynamics, it has been suggested that short-time protein dynamics is essentially nothing more than a noisy signal. Here we use Random Matrix Theory to analyze a series of short-time molecular dynamics experiments which are specifically designed to be simulations with high cosine content. We use as a model system the protein apoCox17, a mitochondrial copper chaperone. Spectral analysis on correlation matrices allows to easily differentiate random correlations, simply deriving from the finite length of the process, from non-random signals reflecting the intrinsic system properties. Our results clearly show that protein dynamics is not really Brownian also in presence of the cosine-shaped low index projections on principal axes. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative research.

PubMed

Watson, Roger

2015-04-01

This article describes the basic tenets of quantitative research. The concepts of dependent and independent variables are addressed and the concept of measurement and its associated issues, such as error, reliability and validity, are explored. Experiments and surveys – the principal research designs in quantitative research – are described and key features explained. The importance of the double-blind randomised controlled trial is emphasised, alongside the importance of longitudinal surveys, as opposed to cross-sectional surveys. Essential features of data storage are covered, with an emphasis on safe, anonymous storage. Finally, the article explores the analysis of quantitative data, considering what may be analysed and the main uses of statistics in analysis.

Quantitative analysis of background parenchymal enhancement in whole breast on MRI: Influence of menstrual cycle and comparison with a qualitative analysis.

PubMed

Jung, Yongsik; Jeong, Seong Kyun; Kang, Doo Kyoung; Moon, Yeorae; Kim, Tae Hee

2018-06-01

We quantitatively analyzed background parenchymal enhancement (BPE) in whole breast according to menstrual cycle and compared it with a qualitative analysis method. A data set of breast magnetic resonance imaging (MRI) from 273 breast cancer patients was used. For quantitative analysis, we used semiautomated in-house software with MATLAB. From each voxel of whole breast, the software calculated BPE using following equation: [(signal intensity [SI] at 1 min 30 s after contrast injection - baseline SI)/baseline SI] × 100%. In total, 53 patients had minimal, 108 mild, 87 moderate, and 25 marked BPE. On quantitative analysis, mean BPE values were 33.1% in the minimal, 42.1% in the mild, 59.1% in the moderate, and 81.9% in the marked BPE group showing significant difference (p = .009 for minimal vs. mild, p < 0.001 for other comparisons). Spearman's correlation test showed that there was strong significant correlation between qualitative and quantitative BPE (r = 0.63, p < 0.001). The mean BPE value was 48.7% for patients in the first week of the menstrual cycle, 43.5% in the second week, 49% in the third week, and 49.4% for those in the fourth week. The difference between the second and fourth weeks was significant (p = .005). Median, 90th percentile, and 10th percentile values were also significantly different between the second and fourth weeks but not different in other comparisons (first vs. second, first vs. third, first vs. fourth, second vs. third, or third vs. fourth). Quantitative analysis of BPE correlated well with the qualitative BPE grade. Quantitative BPE values were lowest in the second week and highest in the fourth week. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative analysis of periodontal pathogens by ELISA and real-time polymerase chain reaction.

PubMed

Hamlet, Stephen M

2010-01-01

The development of analytical methods enabling the accurate identification and enumeration of bacterial species colonizing the oral cavity has led to the identification of a small number of bacterial pathogens that are major factors in the etiology of periodontal disease. Further, these methods also underpin more recent epidemiological analyses of the impact of periodontal disease on general health. Given the complex milieu of over 700 species of microorganisms known to exist within the complex biofilms found in the oral cavity, the identification and enumeration of oral periodontopathogens has not been an easy task. In recent years however, some of the intrinsic limitations of the more traditional microbiological analyses previously used have been overcome with the advent of immunological and molecular analytical methods. Of the plethora of methodologies reported in the literature, the enzyme-linked immunosorbent assay (ELISA), which combines the specificity of antibody with the sensitivity of simple enzyme assays and the polymerase chain reaction (PCR), has been widely utilized in both laboratory and clinical applications. Although conventional PCR does not allow quantitation of the target organism, real-time PCR (rtPCR) has the ability to detect amplicons as they accumulate in "real time" allowing subsequent quantitation. These methods enable the accurate quantitation of as few as 10(2) (using rtPCR) to 10(4) (using ELISA) periodontopathogens in dental plaque samples.

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.

Quantitative analysis of chaperone network throughput in budding yeast

PubMed Central

Brownridge, Philip; Lawless, Craig; Payapilly, Aishwarya B; Lanthaler, Karin; Holman, Stephen W; Harman, Victoria M; Grant, Christopher M; Beynon, Robert J; Hubbard, Simon J

2013-01-01

The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the ‘throughput’ of protein molecules passing through individual chaperones and their groups on a proteome-wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub-cellular localisation of their targets. The novel integration of the interactome data with quantification supports re-estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance. PMID:23420633

The Quantitative Analysis of Chennai Automotive Industry Cluster

NASA Astrophysics Data System (ADS)

Bhaskaran, Ethirajan

2016-07-01

Chennai, also called as Detroit of India due to presence of Automotive Industry producing over 40 % of the India's vehicle and components. During 2001-2002, the Automotive Component Industries (ACI) in Ambattur, Thirumalizai and Thirumudivakkam Industrial Estate, Chennai has faced problems on infrastructure, technology, procurement, production and marketing. The objective is to study the Quantitative Performance of Chennai Automotive Industry Cluster before (2001-2002) and after the CDA (2008-2009). The methodology adopted is collection of primary data from 100 ACI using quantitative questionnaire and analyzing using Correlation Analysis (CA), Regression Analysis (RA), Friedman Test (FMT), and Kruskall Wallis Test (KWT).The CA computed for the different set of variables reveals that there is high degree of relationship between the variables studied. The RA models constructed establish the strong relationship between the dependent variable and a host of independent variables. The models proposed here reveal the approximate relationship in a closer form. KWT proves, there is no significant difference between three locations clusters with respect to: Net Profit, Production Cost, Marketing Costs, Procurement Costs and Gross Output. This supports that each location has contributed for development of automobile component cluster uniformly. The FMT proves, there is no significant difference between industrial units in respect of cost like Production, Infrastructure, Technology, Marketing and Net Profit. To conclude, the Automotive Industries have fully utilized the Physical Infrastructure and Centralised Facilities by adopting CDA and now exporting their products to North America, South America, Europe, Australia, Africa and Asia. The value chain analysis models have been implemented in all the cluster units. This Cluster Development Approach (CDA) model can be implemented in industries of under developed and developing countries for cost reduction and productivity

Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.

PubMed

Yamamoto, Shinya; Bamba, Takeshi; Sano, Atsushi; Kodama, Yukako; Imamura, Miho; Obata, Akio; Fukusaki, Eiichiro

2012-08-01

Soy sauces, produced from different ingredients and brewing processes, have variations in components and quality. Therefore, it is extremely important to comprehend the relationship between components and the sensory attributes of soy sauces. The current study sought to perform metabolite profiling in order to devise a method of assessing the attributes of soy sauces. Quantitative descriptive analysis (QDA) data for 24 soy sauce samples were obtained from well selected sensory panelists. Metabolite profiles primarily concerning low-molecular-weight hydrophilic components were based on gas chromatography with time-of-flightmass spectrometry (GC/TOFMS). QDA data for soy sauces were accurately predicted by projection to latent structure (PLS), with metabolite profiles serving as explanatory variables and QDA data set serving as a response variable. Moreover, analysis of correlation between matrices of metabolite profiles and QDA data indicated contributing compounds that were highly correlated with QDA data. Especially, it was indicated that sugars are important components of the tastes of soy sauces. This new approach which combines metabolite profiling with QDA is applicable to analysis of sensory attributes of food as a result of the complex interaction between its components. This approach is effective to search important compounds that contribute to the attributes. Copyright © 2012 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology

EPA Science Inventory

A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose–response, and time-course p...

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in

Liquid chromatography-diode array detection-mass spectrometry for compositional analysis of low molecular weight heparins.

PubMed

Wang, Zhangjie; Li, Daoyuan; Sun, Xiaojun; Bai, Xue; Jin, Lan; Chi, Lianli

2014-04-15

Low molecular weight heparins (LMWHs) are important artificial preparations from heparin polysaccharide and are widely used as anticoagulant drugs. To analyze the structure and composition of LMWHs, identification and quantitation of their natural and modified building blocks are indispensable. We have established a novel reversed-phase high-performance liquid chromatography-diode array detection-electrospray ionization-mass spectrometry approach for compositional analysis of LMWHs. After being exhaustively digested and labeled with 2-aminoacridone, the structural motifs constructing LMWHs, including 17 components from dalteparin and 15 components from enoxaparin, were well separated, identified, and quantified. Besides the eight natural heparin disaccharides, many characteristic structures from dalteparin and enoxaparin, such as modified structures from the reducing end and nonreducing end, 3-O-sulfated tetrasaccharides, and trisaccharides, have been unambiguously identified based on their retention time and mass spectra. Compared with the traditional heparin compositional analysis methods, the approach described here is not only robust but also comprehensive because it is capable of identifying and quantifying nearly all components from lyase digests of LMWHs. Copyright © 2014 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.

Quantitative prediction of solvation free energy in octanol of organic compounds.

PubMed

Delgado, Eduardo J; Jaña, Gonzalo A

2009-03-01

The free energy of solvation, DeltaGS0, in octanol of organic compounds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a DeltaGS0 range from about -50 to 0 kJ.mol(-1). The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ.mol(-1), just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set.

Visualization and Quantitative Analysis of Crack-Tip Plastic Zone in Pure Nickel

NASA Astrophysics Data System (ADS)

Kelton, Randall; Sola, Jalal Fathi; Meletis, Efstathios I.; Huang, Haiying

2018-05-01

Changes in surface morphology have long been thought to be associated with crack propagation in metallic materials. We have studied areal surface texture changes around crack tips in an attempt to understand the correlations between surface texture changes and crack growth behavior. Detailed profiling of the fatigue sample surface was carried out at short fatigue intervals. An image processing algorithm was developed to calculate the surface texture changes. Quantitative analysis of the crack-tip plastic zone, crack-arrested sites near triple points, and large surface texture changes associated with crack release from arrested locations was carried out. The results indicate that surface texture imaging enables visualization of the development of plastic deformation around a crack tip. Quantitative analysis of the surface texture changes reveals the effects of local microstructures on the crack growth behavior.

Characterization of breast lesion using T1-perfusion magnetic resonance imaging: Qualitative vs. quantitative analysis.

PubMed

Thakran, S; Gupta, P K; Kabra, V; Saha, I; Jain, P; Gupta, R K; Singh, A

2018-06-14

The objective of this study was to quantify the hemodynamic parameters using first pass analysis of T 1 -perfusion magnetic resonance imaging (MRI) data of human breast and to compare these parameters with the existing tracer kinetic parameters, semi-quantitative and qualitative T 1 -perfusion analysis in terms of lesion characterization. MRI of the breast was performed in 50 women (mean age, 44±11 [SD] years; range: 26-75) years with a total of 15 benign and 35 malignant breast lesions. After pre-processing, T 1 -perfusion MRI data was analyzed using qualitative approach by two radiologists (visual inspection of the kinetic curve into types I, II or III), semi-quantitative (characterization of kinetic curve types using empirical parameters), generalized-tracer-kinetic-model (tracer kinetic parameters) and first pass analysis (hemodynamic-parameters). Chi-squared test, t-test, one-way analysis-of-variance (ANOVA) using Bonferroni post-hoc test and receiver-operating-characteristic (ROC) curve were used for statistical analysis. All quantitative parameters except leakage volume (Ve), qualitative (type-I and III) and semi-quantitative curves (type-I and III) provided significant differences (P<0.05) between benign and malignant lesions. Kinetic parameters, particularly volume transfer coefficient (K trans ) provided a significant difference (P<0.05) between all grades except grade-II vs III. The hemodynamic parameter (relative-leakage-corrected-breast-blood-volume [rBBVcorr) provided a statistically significant difference (P<0.05) between all grades. It also provided highest sensitivity and specificity among all parameters in differentiation between different grades of malignant breast lesions. Quantitative parameters, particularly rBBVcorr and K trans provided similar sensitivity and specificity in differentiating benign from malignant breast lesions for this cohort. Moreover, rBBVcorr provided better differentiation between different grades of malignant breast

Feasibility of high-resolution quantitative perfusion analysis in patients with heart failure.

PubMed

Sammut, Eva; Zarinabad, Niloufar; Wesolowski, Roman; Morton, Geraint; Chen, Zhong; Sohal, Manav; Carr-White, Gerry; Razavi, Reza; Chiribiri, Amedeo

2015-02-12

Cardiac magnetic resonance (CMR) is playing an expanding role in the assessment of patients with heart failure (HF). The assessment of myocardial perfusion status in HF can be challenging due to left ventricular (LV) remodelling and wall thinning, coexistent scar and respiratory artefacts. The aim of this study was to assess the feasibility of quantitative CMR myocardial perfusion analysis in patients with HF. A group of 58 patients with heart failure (HF; left ventricular ejection fraction, LVEF ≤ 50%) and 33 patients with normal LVEF (LVEF >50%), referred for suspected coronary artery disease, were studied. All subjects underwent quantitative first-pass stress perfusion imaging using adenosine according to standard acquisition protocols. The feasibility of quantitative perfusion analysis was then assessed using high-resolution, 3 T kt perfusion and voxel-wise Fermi deconvolution. 30/58 (52%) subjects in the HF group had underlying ischaemic aetiology. Perfusion abnormalities were seen amongst patients with ischaemic HF and patients with normal LV function. No regional perfusion defect was observed in the non-ischaemic HF group. Good agreement was found between visual and quantitative analysis across all groups. Absolute stress perfusion rate, myocardial perfusion reserve (MPR) and endocardial-epicardial MPR ratio identified areas with abnormal perfusion in the ischaemic HF group (p = 0.02; p = 0.04; p = 0.02, respectively). In the Normal LV group, MPR and endocardial-epicardial MPR ratio were able to distinguish between normal and abnormal segments (p = 0.04; p = 0.02 respectively). No significant differences of absolute stress perfusion rate or MPR were observed comparing visually normal segments amongst groups. Our results demonstrate the feasibility of high-resolution voxel-wise perfusion assessment in patients with HF.

Detection of sex chromosome aneuploidies using quantitative fluorescent PCR in the Hungarian population.

PubMed

Nagy, Balint; Nagy, Richard Gyula; Lazar, Levente; Schonleber, Julianna; Papp, Csaba; Rigo, Janos

2015-05-20

Aneuploidies are the most frequent chromosomal abnormalities at birth. Autosomal aneuploidies cause serious malformations like trisomy 21, trisomy 18 and trisomy 13. However sex chromosome aneuploidies are causing less severe syndromes. For the detection of these aneuploidies, the "gold standard" method is the cytogenetic analysis of fetal cells, karyograms show all numerical and structural abnormalities, but it takes 2-4 weeks to get the reports. Molecular biological methods were developed to overcome the long culture time, thus, FISH and quantitative fluorescent PCR were introduced. In this work we show our experience with a commercial kit for the detection of sex chromosome aneuploidies. We analyzed 20.173 amniotic fluid samples for the period of 2006-2013 in our department. A conventional cytogenetic analysis was performed on the samples. We checked the reliability of quantitative fluorescent PCR and DNA fragment analysis on those samples where sex chromosomal aneuploidy was diagnosed. From the 20.173 amniotic fluid samples we found 50 samples with sex chromosome aneuploidy. There were 19 samples showing 46, XO, 17 samples with 46, XXY, 9 samples with 47, XXX and 5 samples with 47, XYY karyotypes. The applied quantitative fluorescent PCR and DNA fragment analyses method are suitable to detect all abnormal sex chromosome aneuploidies. Quantitative fluorescent PCR is a fast and reliable method for detection of sex chromosome aneuploidies. Copyright © 2015. Published by Elsevier B.V.

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 structure activity relationship and risk analysis of some pesticides in the goat milk.

PubMed

Muhammad, Faqir; Awais, Mian Muhammad; Akhtar, Masood; Anwar, Muhammad Irfan

2013-01-04

The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R2 = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality.

Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk

PubMed Central

2013-01-01

The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R2 = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality. PMID:23369514

Quantitative changes in proteins responsible for flavonoid and anthocyanin biosynthesis in strawberry fruit at different ripening stages: A targeted quantitative proteomic investigation employing multiple reaction monitoring.

PubMed

Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong

2015-06-03

To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides

Quantitative analysis of dinuclear manganese(II) EPR spectra

NASA Astrophysics Data System (ADS)

Golombek, Adina P.; Hendrich, Michael P.

2003-11-01

A quantitative method for the analysis of EPR spectra from dinuclear Mn(II) complexes is presented. The complex [(Me 3TACN) 2Mn(II) 2(μ-OAc) 3]BPh 4 ( 1) (Me 3TACN= N, N', N''-trimethyl-1,4,7-triazacyclononane; OAc=acetate 1-; BPh 4=tetraphenylborate 1-) was studied with EPR spectroscopy at X- and Q-band frequencies, for both perpendicular and parallel polarizations of the microwave field, and with variable temperature (2-50 K). Complex 1 is an antiferromagnetically coupled dimer which shows signals from all excited spin manifolds, S=1 to 5. The spectra were simulated with diagonalization of the full spin Hamiltonian which includes the Zeeman and zero-field splittings of the individual manganese sites within the dimer, the exchange and dipolar coupling between the two manganese sites of the dimer, and the nuclear hyperfine coupling for each manganese ion. All possible transitions for all spin manifolds were simulated, with the intensities determined from the calculated probability of each transition. In addition, the non-uniform broadening of all resonances was quantitatively predicted using a lineshape model based on D- and r-strain. As the temperature is increased from 2 K, an 11-line hyperfine pattern characteristic of dinuclear Mn(II) is first observed from the S=3 manifold. D- and r-strain are the dominate broadening effects that determine where the hyperfine pattern will be resolved. A single unique parameter set was found to simulate all spectra arising for all temperatures, microwave frequencies, and microwave modes. The simulations are quantitative, allowing for the first time the determination of species concentrations directly from EPR spectra. Thus, this work describes the first method for the quantitative characterization of EPR spectra of dinuclear manganese centers in model complexes and proteins. The exchange coupling parameter J for complex 1 was determined ( J=-1.5±0.3 cm-1; H ex=-2J S1· S2) and found to be in agreement with a previous

Modified HS-SPME for determination of quantitative relations between low-molecular oxygen compounds in various matrices.

PubMed

Dawidowicz, Andrzej L; Szewczyk, Joanna; Dybowski, Michal P

2016-09-07

Similar quantitative relations between individual constituents of the liquid sample established by its direct injection can be obtained applying Polydimethylsiloxane (PDMS) fiber in the headspace solid phase microextraction (HS-SPME) system containing the examined sample suspended in methyl silica oil. This paper proves that the analogous system composed of sample suspension/emulsion in polyethylene glycol (PEG) and Carbowax fiber allows to get similar quantitative relations between components of the mixture as those established by its direct analysis, but only for polar constituents. It is demonstrated for essential oil (EO) components of savory, sage, mint and thyme, and of artificial liquid mixture of polar constituents. The observed differences in quantitative relations between polar constituents estimated by both applied procedures are insignificant (Fexp < Fcrit). The presented results indicates that wider applicability of the system composed of a sample suspended in the oil of the same physicochemical character as that of used SPME fiber coating strongly depends on the character of interactions between analytes-suspending liquid and analytes-fiber coating. Copyright © 2016 Elsevier B.V. All rights reserved.

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data.

PubMed

Li, Xiaomei; Dong, Weiwei; Qu, Xueling; Zhao, Huixia; Wang, Shuo; Hao, Yixin; Li, Qiuwen; Zhu, Jianhua; Ye, Min; Xiao, Wenhua

2017-05-01

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.