Quantitative Susceptibility Mapping and R2* Measured Changes during White Matter Lesion Development in Multiple Sclerosis: Myelin Breakdown, Myelin Debris Degradation and Removal, and Iron Accumulation.

PubMed

Zhang, Y; Gauthier, S A; Gupta, A; Chen, W; Comunale, J; Chiang, G C-Y; Zhou, D; Askin, G; Zhu, W; Pitt, D; Wang, Y

2016-09-01

Quantitative susceptibility mapping and R2* are sensitive to myelin and iron changes in multiple sclerosis lesions. This study was designed to characterize lesion changes on quantitative susceptibility mapping and R2* at various gadolinium-enhancement stages. This study included 64 patients with MS with different enhancing patterns in white matter lesions: nodular, shell-like, nonenhancing < 1 year old, and nonenhancing 1-3 years old. These represent acute, late acute, early chronic, and late chronic lesions, respectively. Susceptibility values measured on quantitative susceptibility mapping and R2* values were compared among the 4 lesion types. Their differences were assessed with a generalized estimating equation, controlling for Expanded Disability Status Scale score, age, and disease duration. We analyzed 203 lesions: 80 were nodular-enhancing, of which 77 (96.2%) were isointense on quantitative susceptibility mapping; 33 were shell-enhancing, of which 30 (90.9%) were hyperintense on quantitative susceptibility mapping; and 49 were nonenhancing lesions < 1 year old and 41 were nonenhancing lesions 1-3 years old, all of which were hyperintense on quantitative susceptibility mapping. Their relative susceptibility/R2* values were 0.5 ± 4.4 parts per billion/-5.6 ± 2.9 Hz, 10.2 ± 5.4 parts per billion/-8.0 ± 2.6 Hz, 20.2 ± 7.8 parts per billion/-3.1 ± 2.3 Hz, and 33.2 ± 8.2 parts per billion/-2.0 ± 2.6 Hz, respectively, and were significantly different (P < .005). Early active MS lesions with nodular enhancement show R2* decrease but no quantitative susceptibility mapping change, reflecting myelin breakdown; late active lesions with peripheral enhancement show R2* decrease and quantitative susceptibility mapping increase in the lesion center, reflecting further degradation and removal of myelin debris; and early or late chronic nonenhancing lesions show both quantitative susceptibility mapping and R2* increase, reflecting iron accumulation. © 2016 by

Lateral Asymmetry and Spatial Difference of Iron Deposition in the Substantia Nigra of Patients with Parkinson Disease Measured with Quantitative Susceptibility Mapping.

PubMed

Azuma, M; Hirai, T; Yamada, K; Yamashita, S; Ando, Y; Tateishi, M; Iryo, Y; Yoneda, T; Kitajima, M; Wang, Y; Yamashita, Y

2016-05-01

Quantitative susceptibility mapping is useful for assessing iron deposition in the substantia nigra of patients with Parkinson disease. We aimed to determine whether quantitative susceptibility mapping is useful for assessing the lateral asymmetry and spatial difference in iron deposits in the substantia nigra of patients with Parkinson disease. Our study population comprised 24 patients with Parkinson disease and 24 age- and sex-matched healthy controls. They underwent 3T MR imaging by using a 3D multiecho gradient-echo sequence. On reconstructed quantitative susceptibility mapping, we measured the susceptibility values in the anterior, middle, and posterior parts of the substantia nigra, the whole substantia nigra, and other deep gray matter structures in both hemibrains. To identify the more and less affected hemibrains in patients with Parkinson disease, we assessed the severity of movement symptoms for each hemibrain by using the Unified Parkinson's Disease Rating Scale. In the posterior substantia nigra of patients with Parkinson disease, the mean susceptibility value was significantly higher in the more than the less affected hemibrain substantia nigra (P < .05). This value was significantly higher in both the more and less affected hemibrains of patients with Parkinson disease than in controls (P < .05). Asymmetry of the mean susceptibility values was significantly greater for patients than controls (P < .05). Receiver operating characteristic analysis showed that quantitative susceptibility mapping of the posterior substantia nigra in the more affected hemibrain provided the highest power for discriminating patients with Parkinson disease from the controls. Quantitative susceptibility mapping is useful for assessing the lateral asymmetry and spatial difference of iron deposition in the substantia nigra of patients with Parkinson disease. © 2016 by American Journal of Neuroradiology.

Ex-vivo quantitative susceptibility mapping of human brain hemispheres

PubMed Central

Kotrotsou, Aikaterini; Tamhane, Ashish A.; Dawe, Robert J.; Kapasi, Alifiya; Leurgans, Sue E.; Schneider, Julie A.; Bennett, David A.; Arfanakis, Konstantinos

2017-01-01

Ex-vivo brain quantitative susceptibility mapping (QSM) allows investigation of brain characteristics at essentially the same point in time as histopathologic examination, and therefore has the potential to become an important tool for determining the role of QSM as a diagnostic and monitoring tool of age-related neuropathologies. In order to be able to translate the ex-vivo QSM findings to in-vivo, it is crucial to understand the effects of death and chemical fixation on brain magnetic susceptibility measurements collected ex-vivo. Thus, the objective of this work was twofold: a) to assess the behavior of magnetic susceptibility in both gray and white matter of human brain hemispheres as a function of time postmortem, and b) to establish the relationship between in-vivo and ex-vivo gray matter susceptibility measurements on the same hemispheres. Five brain hemispheres from community-dwelling older adults were imaged ex-vivo with QSM on a weekly basis for six weeks postmortem, and the longitudinal behavior of ex-vivo magnetic susceptibility in both gray and white matter was assessed. The relationship between in-vivo and ex-vivo gray matter susceptibility measurements was investigated using QSM data from eleven older adults imaged both antemortem and postmortem. No systematic change in ex-vivo magnetic susceptibility of gray or white matter was observed over time postmortem. Additionally, it was demonstrated that, gray matter magnetic susceptibility measured ex-vivo may be well modeled as a linear function of susceptibility measured in-vivo. In conclusion, magnetic susceptibility in gray and white matter measured ex-vivo with QSM does not systematically change in the first six weeks after death. This information is important for future cross-sectional ex-vivo QSM studies of hemispheres imaged at different postmortem intervals. Furthermore, the linear relationship between in-vivo and ex-vivo gray matter magnetic susceptibility suggests that ex-vivo QSM captures

Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions.

PubMed

Yao, Y; Nguyen, T D; Pandya, S; Zhang, Y; Hurtado Rúa, S; Kovanlikaya, I; Kuceyeski, A; Liu, Z; Wang, Y; Gauthier, S A

2018-02-01

A hyperintense rim on susceptibility in chronic MS lesions is consistent with iron deposition, and the purpose of this study was to quantify iron-related myelin damage within these lesions as compared with those without rim. Forty-six patients had 2 longitudinal quantitative susceptibility mapping with automatic zero reference scans with a mean interval of 28.9 ± 11.4 months. Myelin water fraction mapping by using fast acquisition with spiral trajectory and T2 prep was obtained at the second time point to measure myelin damage. Mixed-effects models were used to assess lesion quantitative susceptibility mapping and myelin water fraction values. Quantitative susceptibility mapping scans were on average 6.8 parts per billion higher in 116 rim-positive lesions compared with 441 rim-negative lesions ( P < .001). All rim-positive lesions retained a hyperintense rim over time, with increasing quantitative susceptibility mapping values of both the rim and core regions ( P < .001). Quantitative susceptibility mapping scans and myelin water fraction in rim-positive lesions decreased from rim to core, which is consistent with rim iron deposition. Whole lesion myelin water fractions for rim-positive and rim-negative lesions were 0.055 ± 0.07 and 0.066 ± 0.04, respectively. In the mixed-effects model, rim-positive lesions had on average 0.01 lower myelin water fraction compared with rim-negative lesions ( P < .001). The volume of the rim at the initial quantitative susceptibility mapping scan was negatively associated with follow-up myelin water fraction ( P < .01). Quantitative susceptibility mapping rim-positive lesions maintained a hyperintense rim, increased in susceptibility, and had more myelin damage compared with rim-negative lesions. Our results are consistent with the identification of chronic active MS lesions and may provide a target for therapeutic interventions to reduce myelin damage. © 2018 by American Journal of Neuroradiology.

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.

PubMed

Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce

2018-06-15

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.

The impact of white matter fiber orientation in single-acquisition quantitative susceptibility mapping.

PubMed

Lancione, Marta; Tosetti, Michela; Donatelli, Graziella; Cosottini, Mirco; Costagli, Mauro

2017-11-01

The aim of this work was to assess the impact of tissue structural orientation on quantitative susceptibility mapping (QSM) reliability, and to provide a criterion to identify voxels in which measures of magnetic susceptibility (χ) are most affected by spatial orientation effects. Four healthy volunteers underwent 7-T magnetic resonance imaging (MRI). Multi-echo, gradient-echo sequences were used to obtain quantitative maps of frequency shift (FS) and χ. Information from diffusion tensor imaging (DTI) was used to investigate the relationship between tissue orientation and FS measures and QSM. After sorting voxels on the basis of their fractional anisotropy (FA), the variations in FS and χ values over tissue orientation were measured. Using a K-means clustering algorithm, voxels were separated into two groups depending on the variability of measures within each FA interval. The consistency of FS and QSM values, observed at low FA, was disrupted for FA > 0.6. The standard deviation of χ measured at high FA (0.0103 ppm) was nearly five times that at low FA (0.0022 ppm). This result was consistent through data across different head positions and for different brain regions considered separately, which confirmed that such behavior does not depend on structures with different bulk susceptibility oriented along particular angles. The reliability of single-orientation QSM anticorrelates with local FA. QSM provides replicable values with little variability in brain regions with FA < 0.6, but QSM should be interpreted cautiously in major and coherent fiber bundles, which are strongly affected by structural anisotropy and magnetic susceptibility anisotropy. Copyright © 2017 John Wiley & Sons, Ltd.

Quantitative Susceptibility Mapping Indicates a Disturbed Brain Iron Homeostasis in Neuromyelitis Optica - A Pilot Study.

PubMed

Doring, Thomas Martin; Granado, Vanessa; Rueda, Fernanda; Deistung, Andreas; Reichenbach, Juergen R; Tukamoto, Gustavo; Gasparetto, Emerson Leandro; Schweser, Ferdinand

2016-01-01

Dysregulation of brain iron homeostasis is a hallmark of many neurodegenerative diseases and can be associated with oxidative stress. The objective of this study was to investigate brain iron in patients with Neuromyelitis Optica (NMO) using quantitative susceptibility mapping (QSM), a quantitative iron-sensitive MRI technique. 12 clinically confirmed NMO patients (6 female and 6 male; age 35.4y±14.2y) and 12 age- and sex-matched healthy controls (7 female and 5 male; age 33.9±11.3y) underwent MRI of the brain at 3 Tesla. Quantitative maps of the effective transverse relaxation rate (R2*) and magnetic susceptibility were calculated and a blinded ROI-based group comparison analysis was performed. Normality of the data and differences between patients and controls were tested by Kolmogorov-Smirnov and t-test, respectively. Correlation with age was studied using Spearman's rank correlation and an ANCOVA-like analysis. Magnetic susceptibility values were decreased in the red nucleus (p<0.01; d>0.95; between -15 and -22 ppb depending on reference region) with a trend toward increasing differences with age. R2* revealed significantly decreased relaxation in the optic radiations of five of the 12 patients (p<0.0001; -3.136±0.567 s-1). Decreased relaxation in the optic radiation is indicative for demyelination, which is in line with previous findings. Decreased magnetic susceptibility in the red nucleus is indicative for a lower brain iron concentration, a chemical redistribution of iron into less magnetic forms, or both. Further investigations are necessary to elucidate the pathological cause or consequence of this finding.

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

PubMed

Lim, Issel Anne L; Faria, Andreia V; Li, Xu; Hsu, Johnny T C; Airan, Raag D; Mori, Susumu; van Zijl, Peter C M

2013-11-15

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray

STrategically Acquired Gradient Echo (STAGE) imaging, part I: Creating enhanced T1 contrast and standardized susceptibility weighted imaging and quantitative susceptibility mapping.

PubMed

Chen, Yongsheng; Liu, Saifeng; Wang, Yu; Kang, Yan; Haacke, E Mark

2018-02-01

To provide whole brain grey matter (GM) to white matter (WM) contrast enhanced T1W (T1WE) images, multi-echo quantitative susceptibility mapping (QSM), proton density (PD) weighted images, T1 maps, PD maps, susceptibility weighted imaging (SWI), and R2* maps with minimal misregistration in scanning times <5min. Strategically acquired gradient echo (STAGE) imaging includes two fully flow compensated double echo gradient echo acquisitions with a resolution of 0.67×1.33×2.0mm 3 acquired in 5min for 64 slices. Ten subjects were recruited and scanned at 3 Tesla. The optimum pair of flip angles (6° and 24° with TR=25ms at 3T) were used for both T1 mapping with radio frequency (RF) transmit field correction and creating enhanced GM/WM contrast (the T1WE). The proposed T1WE image was created from a combination of the proton density weighted (6°, PDW) and T1W (24°) images and corrected for RF transmit field variations. Prior to the QSM calculation, a multi-echo phase unwrapping strategy was implemented using the unwrapped short echo to unwrap the longer echo to speed up computation. R2* maps were used to mask deep grey matter and veins during the iterative QSM calculation. A weighted-average sum of susceptibility maps was generated to increase the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR). The proposed T1WE image has a significantly improved CNR both for WM to deep GM and WM to cortical GM compared to the acquired T1W image (the first echo of 24° scan) and the T1MPRAGE image. The weighted-average susceptibility maps have 80±26%, 55±22%, 108±33% SNR increases across the ten subjects compared to the single echo result of 17.5ms for the putamen, caudate nucleus, and globus pallidus, respectively. STAGE imaging offers the potential to create a standardized brain imaging protocol providing four pieces of quantitative tissue property information and multiple types of qualitative information in just 5min. Published by Elsevier Inc.

A new discrete dipole kernel for quantitative susceptibility mapping.

PubMed

Milovic, Carlos; Acosta-Cabronero, Julio; Pinto, José Miguel; Mattern, Hendrik; Andia, Marcelo; Uribe, Sergio; Tejos, Cristian

2018-09-01

Most approaches for quantitative susceptibility mapping (QSM) are based on a forward model approximation that employs a continuous Fourier transform operator to solve a differential equation system. Such formulation, however, is prone to high-frequency aliasing. The aim of this study was to reduce such errors using an alternative dipole kernel formulation based on the discrete Fourier transform and discrete operators. The impact of such an approach on forward model calculation and susceptibility inversion was evaluated in contrast to the continuous formulation both with synthetic phantoms and in vivo MRI data. The discrete kernel demonstrated systematically better fits to analytic field solutions, and showed less over-oscillations and aliasing artifacts while preserving low- and medium-frequency responses relative to those obtained with the continuous kernel. In the context of QSM estimation, the use of the proposed discrete kernel resulted in error reduction and increased sharpness. This proof-of-concept study demonstrated that discretizing the dipole kernel is advantageous for QSM. The impact on small or narrow structures such as the venous vasculature might by particularly relevant to high-resolution QSM applications with ultra-high field MRI - a topic for future investigations. The proposed dipole kernel has a straightforward implementation to existing QSM routines. Copyright © 2018 Elsevier Inc. All rights reserved.

Quantitative susceptibility mapping of multiple sclerosis lesions at various ages.

PubMed

Chen, Weiwei; Gauthier, Susan A; Gupta, Ajay; Comunale, Joseph; Liu, Tian; Wang, Shuai; Pei, Mengchao; Pitt, David; Wang, Yi

2014-04-01

To assess multiple sclerosis (MS) lesions at various ages by using quantitative susceptibility mapping (QSM) and conventional magnetic resonance (MR) imaging. Retrospectively selected were 32 clinically confirmed MS patients (nine men and 23 women; 39.3 years ± 10.9) who underwent two MR examinations (interval, 0.43 years ± 0.16) with three-dimensional gradient-echo sequence from August 2011 to August 2012. To estimate the ages of MS lesions, MR examinations performed 0.3-10.6 years before study examinations were studied. Hyperintensity on T2-weighted images was used to define MS lesions. QSM images were reconstructed from gradient-echo data. Susceptibility of MS lesions and temporal rates of change were obtained from QSM images. Lesion susceptibilities were analyzed by t test with intracluster correlation adjustment and Bonferroni correction in multiple comparisons. MR imaging of 32 patients depicted 598 MS lesions, of which 162 lesions (27.1%) in 23 patients were age measurable and six (1.0%) were only visible at QSM. The susceptibilities relative to normal-appearing white matter (NAWM) were 0.53 ppb ± 3.34 for acute enhanced lesions, 38.43 ppb ± 13.0 (positive; P < .01) for early to intermediately aged nonenhanced lesions, and 4.67 ppb ± 3.18 for chronic nonenhanced lesions. Temporal rates of susceptibility changes relative to cerebrospinal fluid were 12.49 ppb/month ± 3.15 for acute enhanced lesions, 1.27 ppb/month ± 2.31 for early to intermediately aged nonenhanced lesions, and -0.004 ppb/month ± 0 for chronic nonenhanced lesions. Magnetic susceptibility of MS lesions increased rapidly as it changed from enhanced to nonenhanced, it attained a high susceptibility value relative to NAWM during its initial few years (approximately 4 years), and it gradually dissipated back to susceptibility similar to that of NAWM as it aged, which may provide new insight into pathophysiologic features of MS lesions. Online supplemental material is available for this

Magnetic Susceptibility Changes in the Basal Ganglia and Brain Stem of Patients with Wilson's Disease: Evaluation with Quantitative Susceptibility Mapping.

PubMed

Doganay, Selim; Gumus, Kazim; Koc, Gonca; Bayram, Ayse Kacar; Dogan, Mehmet Sait; Arslan, Duran; Gumus, Hakan; Gorkem, Sureyya Burcu; Ciraci, Saliha; Serin, Halil Ibrahim; Coskun, Abdulhakim

2018-01-10

Wilson's disease (WD) is characterized with the accumulation of copper in the liver and brain. The objective of this study is to quantitatively measure the susceptibility changes of basal ganglia and brain stem of pediatric patients with neurological WD using quantitative susceptibility mapping (QSM) in comparison to healthy controls. Eleven patients with neurological WD (mean age 15 ± 3.3 years, range 10-22 years) and 14 agematched controls were prospectively recruited. Both groups were scanned on a 1.5 Tesla clinical scanner. In addition to T 1 - and T 2 -weighted MR images, a 3D multi-echo spoiled gradient echo (GRE) sequence was acquired and QSM images were derived offline. The quantitative measurement of susceptibility of corpus striatum, thalamus of each hemisphere, midbrain, and pons were assessed with the region of interest analysis on the QSM images. The susceptibility values for the patient and control groups were compared using twosample t-test. One patient with WD had T 1 shortening in the bilateral globus pallidus. Another one had hyperintensity in the bilateral putamen, caudate nuclei, and substantia nigra on T 2 -weighted images. The rest of the patients with WD and all subjects of the control group had no signal abnormalities on conventional MR images. The susceptibility measures of right side of globus pallidus, putamen, thalamus, midbrain, and entire pons were significantly different in patients compared to controls (P < 0.05). QSM method exhibits increased susceptibility differences of basal ganglia and brain stem in patients with WD that have neurologic impairment even if no signal alteration is detected on T 1 - and T 2 -weighted MR images.

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

PubMed Central

Lim, Issel Anne L.; Faria, Andreia V.; Li, Xu; Hsu, Johnny T.C.; Airan, Raag D.; Mori, Susumu; van Zijl, Peter C. M.

2013-01-01

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a “deep gray matter parcellation map” (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established “white matter parcellation map” (WMPM) from the same subject’s T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the “Everything Parcellation Map in Eve Space,” also known as the “EvePM.” It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting “almost perfect” agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron

Cerebral Metabolic Rate of Oxygen (CMRO2 ) Mapping by Combining Quantitative Susceptibility Mapping (QSM) and Quantitative Blood Oxygenation Level-Dependent Imaging (qBOLD).

PubMed

Cho, Junghun; Kee, Youngwook; Spincemaille, Pascal; Nguyen, Thanh D; Zhang, Jingwei; Gupta, Ajay; Zhang, Shun; Wang, Yi

2018-03-07

To map the cerebral metabolic rate of oxygen (CMRO 2 ) by estimating the oxygen extraction fraction (OEF) from gradient echo imaging (GRE) using phase and magnitude of the GRE data. 3D multi-echo gradient echo imaging and perfusion imaging with arterial spin labeling were performed in 11 healthy subjects. CMRO 2 and OEF maps were reconstructed by joint quantitative susceptibility mapping (QSM) to process GRE phases and quantitative blood oxygen level-dependent (qBOLD) modeling to process GRE magnitudes. Comparisons with QSM and qBOLD alone were performed using ROI analysis, paired t-tests, and Bland-Altman plot. The average CMRO 2 value in cortical gray matter across subjects were 140.4 ± 14.9, 134.1 ± 12.5, and 184.6 ± 17.9 μmol/100 g/min, with corresponding OEFs of 30.9 ± 3.4%, 30.0 ± 1.8%, and 40.9 ± 2.4% for methods based on QSM, qBOLD, and QSM+qBOLD, respectively. QSM+qBOLD provided the highest CMRO 2 contrast between gray and white matter, more uniform OEF than QSM, and less noisy OEF than qBOLD. Quantitative CMRO 2 mapping that fits the entire complex GRE data is feasible by combining QSM analysis of phase and qBOLD analysis of magnitude. © 2018 International Society for Magnetic Resonance in Medicine.

Quantitative Susceptibility Mapping by Inversion of a Perturbation Field Model: Correlation with Brain Iron in Normal Aging

PubMed Central

Poynton, Clare; Jenkinson, Mark; Adalsteinsson, Elfar; Sullivan, Edith V.; Pfefferbaum, Adolf; Wells, William

2015-01-01

There is increasing evidence that iron deposition occurs in specific regions of the brain in normal aging and neurodegenerative disorders such as Parkinson's, Huntington's, and Alzheimer's disease. Iron deposition changes the magnetic susceptibility of tissue, which alters the MR signal phase, and allows estimation of susceptibility differences using quantitative susceptibility mapping (QSM). We present a method for quantifying susceptibility by inversion of a perturbation model, or ‘QSIP’. The perturbation model relates phase to susceptibility using a kernel calculated in the spatial domain, in contrast to previous Fourier-based techniques. A tissue/air susceptibility atlas is used to estimate B0 inhomogeneity. QSIP estimates in young and elderly subjects are compared to postmortem iron estimates, maps of the Field-Dependent Relaxation Rate Increase (FDRI), and the L1-QSM method. Results for both groups showed excellent agreement with published postmortem data and in-vivo FDRI: statistically significant Spearman correlations ranging from Rho = 0.905 to Rho = 1.00 were obtained. QSIP also showed improvement over FDRI and L1-QSM: reduced variance in susceptibility estimates and statistically significant group differences were detected in striatal and brainstem nuclei, consistent with age-dependent iron accumulation in these regions. PMID:25248179

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping.

PubMed

Zhang, Yuyao; Wei, Hongjiang; Cronin, Matthew J; He, Naying; Yan, Fuhua; Liu, Chunlei

2018-05-01

Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1-83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

Cerebral metabolic rate of oxygen (CMRO2 ) mapping with hyperventilation challenge using quantitative susceptibility mapping (QSM).

PubMed

Zhang, Jingwei; Zhou, Dong; Nguyen, Thanh D; Spincemaille, Pascal; Gupta, Ajay; Wang, Yi

2017-05-01

Our objective was to demonstrate the feasibility of using hyperventilation as an efficient vasoconstrictive challenge and prior knowledge as denoising constraints for cerebral metabolic rate of oxygen (CMRO 2 ) mapping based upon quantitative susceptibility mapping (QSM). Three-dimensional (3D) multi-echo gradient echo and arterial spin labeling imaging were performed to calculate QSM and perfusion maps before and after a hyperventilation challenge in 11 healthy subjects. For comparison, this was repeated using a caffeine challenge. Whole-brain CMRO 2 and oxygen extraction fraction (OEF) maps were computed using constrained optimization. Hyperventilation scans were repeated to measure reproducibility. Regional agreement of CMRO 2 and OEF maps was analyzed within the cortical gray matter (CGM) using t-test and Bland-Altman plots. Hyperventilation challenge eliminates the 30-min waiting time needed for caffeine to exert its vasoconstrictive effects. Mean CMRO 2 (in µmol/100g/min) obtained in CGM using the caffeine and repeated hyperventilation scans were 149 ± 16, 153 ± 19, and 150 ± 20, respectively. This corresponded to an OEF of 33.6 ± 3.4%, 32.3 ± 3.2%, and 34.1 ± 3.8% at baseline state and 39.8 ± 4.8%, 43.6 ± 6.2%, and 42.8 ± 6.8% at challenged state, respectively. Hyperventilation scans produced a good agreement of CMRO 2 and OEF values. Hyperventilation is a feasible, reproducible, and efficient vasoconstrictive challenge for QSM-based quantitative CMRO 2 mapping. Magn Reson Med 77:1762-1773, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Quantitative Susceptibility Mapping Reveals an Association between Brain Iron Load and Depression Severity

PubMed Central

Yao, Shun; Zhong, Yi; Xu, Yuhao; Qin, Jiasheng; Zhang, Ningning; Zhu, Xiaolan; Li, Yuefeng

2017-01-01

Previous studies have detected abnormal serum ferritin levels in patients with depression; however, the results have been inconsistent. This study used quantitative susceptibility mapping (QSM) for the first time to examine brain iron concentration in depressed patients and evaluated whether it is related to severity. We included three groups of age- and gender-matched participants: 30 patients with mild-moderate depression (MD), 14 patients with major depression disorder (MDD) and 20 control subjects. All participants underwent MR scans with a 3D gradient-echo sequence reconstructing for QSM and performed the 17-item Hamilton Depression Rating Scale (HDRS) test. In MDD, the susceptibility value in the bilateral putamen was significantly increased compared with MD or control subjects. In addition, a significant difference was also observed in the left thalamus in MDD patients compared with controls. However, the susceptibility values did not differ between MD patients and controls. The susceptibility values positively correlated with the severity of depression as indicated by the HDRS scores. Our results provide evidence that brain iron deposition may be associated with depression and may even be a biomarker for investigating the pathophysiological mechanism of depression. PMID:28900391

On the influence of zero-padding on the nonlinear operations in Quantitative Susceptibility Mapping

PubMed Central

Eskreis-Winkler, Sarah; Zhou, Dong; Liu, Tian; Gupta, Ajay; Gauthier, Susan A.; Wang, Yi; Spincemaille, Pascal

2016-01-01

Purpose Zero padding is a well-studied interpolation technique that improves image visualization without increasing image resolution. This interpolation is often performed as a last step before images are displayed on clinical workstations. Here, we seek to demonstrate the importance of zero padding before rather than after performing non-linear post-processing algorithms, such as Quantitative Susceptibility Mapping (QSM). To do so, we evaluate apparent spatial resolution, relative error and depiction of multiple sclerosis (MS) lesions on images that were zero padded prior to, in the middle of, and after the application of the QSM algorithm. Materials and Methods High resolution gradient echo (GRE) data were acquired on twenty MS patients, from which low resolution data were derived using k-space cropping. Pre-, mid-, and post-zero padded QSM images were reconstructed from these low resolution data by zero padding prior to field mapping, after field mapping, and after susceptibility mapping, respectively. Using high resolution QSM as the gold standard, apparent spatial resolution, relative error, and image quality of the pre-, mid-, and post-zero padded QSM images were measured and compared. Results Both the accuracy and apparent spatial resolution of the pre-zero padded QSM was higher than that of mid-zero padded QSM (p < 0.001; p < 0.001), which was higher than that of post-zero padded QSM (p < 0.001; p < 0.001). The image quality of pre-zero padded reconstructions was higher than that of mid- and post-zero padded reconstructions (p = 0.004; p < 0.001). Conclusion Zero padding of the complex GRE data prior to nonlinear susceptibility mapping improves image accuracy and apparent resolution compared to zero padding afterwards. It also provides better delineation of MS lesion geometry, which may improve lesion subclassification and disease monitoring in MS patients. PMID:27587225

On the influence of zero-padding on the nonlinear operations in Quantitative Susceptibility Mapping.

PubMed

Eskreis-Winkler, Sarah; Zhou, Dong; Liu, Tian; Gupta, Ajay; Gauthier, Susan A; Wang, Yi; Spincemaille, Pascal

2017-01-01

Zero padding is a well-studied interpolation technique that improves image visualization without increasing image resolution. This interpolation is often performed as a last step before images are displayed on clinical workstations. Here, we seek to demonstrate the importance of zero padding before rather than after performing non-linear post-processing algorithms, such as Quantitative Susceptibility Mapping (QSM). To do so, we evaluate apparent spatial resolution, relative error and depiction of multiple sclerosis (MS) lesions on images that were zero padded prior to, in the middle of, and after the application of the QSM algorithm. High resolution gradient echo (GRE) data were acquired on twenty MS patients, from which low resolution data were derived using k-space cropping. Pre-, mid-, and post-zero padded QSM images were reconstructed from these low resolution data by zero padding prior to field mapping, after field mapping, and after susceptibility mapping, respectively. Using high resolution QSM as the gold standard, apparent spatial resolution, relative error, and image quality of the pre-, mid-, and post-zero padded QSM images were measured and compared. Both the accuracy and apparent spatial resolution of the pre-zero padded QSM was higher than that of mid-zero padded QSM (p<0.001; p<0.001), which was higher than that of post-zero padded QSM (p<0.001; p<0.001). The image quality of pre-zero padded reconstructions was higher than that of mid- and post-zero padded reconstructions (p=0.004; p<0.001). Zero padding of the complex GRE data prior to nonlinear susceptibility mapping improves image accuracy and apparent resolution compared to zero padding afterwards. It also provides better delineation of MS lesion geometry, which may improve lesion subclassification and disease monitoring in MS patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker

PubMed Central

Wang, Yi; Liu, Tian

2015-01-01

In MRI, the main magnetic field polarizes the electron cloud of a molecule, generating a chemical shift for observer protons within the molecule and a magnetic susceptibility inhomogeneity field for observer protons outside the molecule. The number of water protons surrounding a molecule for detecting its magnetic susceptibility is vastly greater than the number of protons within the molecule for detecting its chemical shift. However, the study of tissue magnetic susceptibility has been hindered by poor molecular specificities of hitherto used methods based on MRI signal phase and T2* contrast, which depend convolutedly on surrounding susceptibility sources. Deconvolution of the MRI signal phase can determine tissue susceptibility but is challenged by the lack of MRI signal in the background and by the zeroes in the dipole kernel. Recently, physically meaningful regularizations, including the Bayesian approach, have been developed to enable accurate quantitative susceptibility mapping (QSM) for studying iron distribution, metabolic oxygen consumption, blood degradation, calcification, demyelination, and other pathophysiological susceptibility changes, as well as contrast agent biodistribution in MRI. This paper attempts to summarize the basic physical concepts and essential algorithmic steps in QSM, to describe clinical and technical issues under active development, and to provide references, codes, and testing data for readers interested in QSM. Magn Reson Med 73:82–101, 2015. © 2014 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance. This is an open access article under the terms of the Creative commons Attribution License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. PMID:25044035

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain

NASA Astrophysics Data System (ADS)

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C. M.; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions

Landslide susceptibility map: from research to application

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Reichenbach, Paola; Ardizzone, Francesca; Rossi, Mauro; Felicioni, Giulia; Antonini, Guendalina

2014-05-01

qualitatively classifying the territory according to slope classes. For the Perugia Municipality the susceptibility map was obtained combining results of statistical multivariate models and landslide density map. In particular, in the first phase a susceptibility zonation was prepared using different single and combined probability statistical multivariate techniques. The zonation was then combined and compared with the landslide density map in order to reclassify the false negative (portion of the territory classified by the model as stable affected by slope failures). The semi-quantitative resulting map was classified in five susceptibility classes. For each class a set of technical regulation was established to manage the territory.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain.

PubMed

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C M; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions

Quantitative Susceptibility Mapping of Amyloid-β Aggregates in Alzheimer's Disease with 7T MR.

PubMed

Tiepolt, Solveig; Schäfer, Andreas; Rullmann, Michael; Roggenhofer, Elisabeth; Gertz, Hermann-Josef; Schroeter, Matthias L; Patt, Marianne; Bazin, Pierre-Louis; Jochimsen, Thies H; Turner, Robert; Sabri, Osama; Barthel, Henryk

2018-05-28

PET imaging is an established technique to detect cerebral amyloid-β (Aβ) plaques in vivo. Some preclinical and postmortem data report an accumulation of redox-active iron near Aβ plaques. Quantitative susceptibility mapping (QSM) at high-field MRI enables iron deposits to be depicted with high spatial resolution. Aim of this study was to examine whether iron and Aβ plaque accumulation is related and thus, whether 7T MRI might be an additive diagnostic tool to Aβ PET imaging. Postmortem human Alzheimer's disease (AD) and healthy control (HC) frontal gray matter (GM) was imaged with 7T MRI which resulted in T1 maps and QSM. Aβ plaque load was determined by histopathology. In vivo, 10 Aβ PET-positive AD patients (74.1±6.0a) and 10 Aβ PET-negative HCs (67.1±4.4a) underwent 7T MR examination and QSM maps were analyzed. Severity of cognitive deficits was determined by MMSE. Postmortem, the susceptibility of Aβ plaque-containing GM were higher than those of Aβ plaque-free GM (0.011±0.002 versus - 0.008±0.003 ppm, p <  0.001). In vivo, only the bilateral globus pallidus showed significantly higher susceptibility in AD patients compared to HCs (right: 0.277±0.018 versus - 0.009±0.009 ppm; left: 0.293±0.014 versus - 0.007±0.012 ppm, p <  0.0001). The pallidal QSM values were negatively correlated with those of the MMSE (r = - 0.69, p = 0.001). The postmortem study revealed significant susceptibility differences between the Aβ plaque-containing and Aβ plaque-free GM, whereas in vivo only the QSM values of the globus pallidus differed significantly between AD and HC group. The pallidal QSM values correlated with the severity of cognitive deficits. These findings encourage efforts to optimize the 7T-QSM methodology.

Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping

PubMed Central

Stüber, Carsten; Pitt, David; Wang, Yi

2016-01-01

Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS. PMID:26784172

Quantitative susceptibility map analysis in preterm neonates with germinal matrix-intraventricular hemorrhage.

PubMed

Tortora, Domenico; Severino, Mariasavina; Sedlacik, Jan; Toselli, Benedetta; Malova, Mariya; Parodi, Alessandro; Morana, Giovanni; Fato, Marco Massimo; Ramenghi, Luca Antonio; Rossi, Andrea

2018-05-10

Germinal matrix-intraventricular hemorrhage (GMH-IVH) is a common form of intracranial hemorrhage occurring in preterm neonates that may affect normal brain development. Although the primary lesion is easily identified on MRI by the presence of blood products, its exact extent may not be recognizable with conventional sequences. Quantitative susceptibility mapping (QSM) quantify the spatial distribution of magnetic susceptibility within biological tissues, including blood degradation products. To evaluate magnetic susceptibility of normal-appearing white (WM) and gray matter regions in preterm neonates with and without GMH-IVH. Retrospective case-control. A total of 127 preterm neonates studied at term equivalent age: 20 had mild GMH-IVH (average gestational age 28.7 ± 2.1 weeks), 15 had severe GMH-IVH (average gestational age 29.3 ± 1.8 weeks), and 92 had normal brain MRI (average gestational age 29.8 ± 1.8 weeks). QSM at 1.5 Tesla. QSM analysis was performed for each brain hemisphere with a region of interest-based approach including five WM regions (centrum semiovale, frontal, parietal, temporal, and cerebellum), and a subcortical gray matter region (basal ganglia/thalami). Changes in magnetic susceptibility were explored using a one-way analysis of covariance, according to GMH-IVH severity (P < 0.05). In preterm neonates with normal brain MRI, all white and subcortical gray matter regions had negative magnetic susceptibility values (diamagnetic). Neonates with severe GMH-IVH showed higher positive magnetic susceptibility values (i.e. paramagnetic) in the centrum semiovale (0.0019 versus -0.0014 ppm; P < 0.001), temporal WM (0.0011 versus -0.0012 ppm; P = 0.037), and parietal WM (0.0005 versus -0.0001 ppm; P = 0.002) compared with controls. No differences in magnetic susceptibility were observed between neonates with mild GMH-IVH and controls (P = 0.236). Paramagnetic susceptibility changes occur in several normal

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

Simultaneous Quantitative MRI Mapping of T1, T2* and Magnetic Susceptibility with Multi-Echo MP2RAGE

PubMed Central

Kober, Tobias; Möller, Harald E.; Schäfer, Andreas

2017-01-01

The knowledge of relaxation times is essential for understanding the biophysical mechanisms underlying contrast in magnetic resonance imaging. Quantitative experiments, while offering major advantages in terms of reproducibility, may benefit from simultaneous acquisitions. In this work, we demonstrate the possibility of simultaneously recording relaxation-time and susceptibility maps with a prototype Multi-Echo (ME) Magnetization-Prepared 2 RApid Gradient Echoes (MP2RAGE) sequence. T1 maps can be obtained using the MP2RAGE sequence, which is relatively insensitive to inhomogeneities of the radio-frequency transmit field, B1+. As an extension, multiple gradient echoes can be acquired in each of the MP2RAGE readout blocks, which permits the calculation of T2* and susceptibility maps. We used computer simulations to explore the effects of the parameters on the precision and accuracy of the mapping. In vivo parameter maps up to 0.6 mm nominal resolution were acquired at 7 T in 19 healthy volunteers. Voxel-by-voxel correlations and the test-retest reproducibility were used to assess the reliability of the results. When using optimized paramenters, T1 maps obtained with ME-MP2RAGE and standard MP2RAGE showed excellent agreement for the whole range of values found in brain tissues. Simultaneously obtained T2* and susceptibility maps were of comparable quality as Fast Low-Angle SHot (FLASH) results. The acquisition times were more favorable for the ME-MP2RAGE (≈ 19 min) sequence as opposed to the sum of MP2RAGE (≈ 12 min) and FLASH (≈ 10 min) acquisitions. Without relevant sacrifice in accuracy, precision or flexibility, the multi-echo version may yield advantages in terms of reduced acquisition time and intrinsic co-registration, provided that an appropriate optimization of the acquisition parameters is performed. PMID:28081157

Effects of white matter microstructure on phase and susceptibility maps.

PubMed

Wharton, Samuel; Bowtell, Richard

2015-03-01

To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contributions. © 2014 Wiley Periodicals, Inc.

Increased Iron Deposition on Brain Quantitative Susceptibility Mapping Correlates with Decreased Cognitive Function in Alzheimer's Disease.

PubMed

Du, Lei; Zhao, Zifang; Cui, Ailing; Zhu, Yijiang; Zhang, Lu; Liu, Jing; Shi, Sumin; Fu, Chao; Han, Xiaowei; Gao, Wenwen; Song, Tianbin; Xie, Lizhi; Wang, Lei; Sun, Shilong; Guo, Runcai; Ma, Guolin

2018-05-15

The excessive accumulation of iron in deep gray structures is an important pathological characteristic in patients with Alzheimer's disease (AD). Quantitative susceptibility mapping (QSM) is more specific than other imaging-based iron measurement modalities and allows noninvasive assessment of tissue magnetic susceptibility, which has been shown to correlate well with brain iron levels. This study aimed to investigate the correlations between the magnetic susceptibility values of deep gray matter nuclei and the cognitive functions assessed by mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) in patients with mild and moderate AD. Thirty subjects with mild and moderate AD and 30 age- and sex-matched healthy controls were scanned with a 3.0 T magnetic resonance imaging (MRI) scanner. The magnetic susceptibilities of the regions of interest (ROIs), including caudate nucleus (Cd), putamen (Pt), globus pallidus (Gp), thalamus (Th), red nucleus (Rn), substantia nigra (Sn), and dentate nucleus (Dn), were quantified by QSM. We found that the susceptibility values of the bilateral Cd and Pt were significantly higher in AD patients than the controls ( P < 0.05). In contrast, bilateral Rn had significantly lower susceptibility values in AD than the controls. Regardless of gender and age, the increase of magnetic susceptibility in the left Cd was significantly correlated with the decrease of MMSE scores and MoCA scores ( P < 0.05). Our study indicated that magnetic susceptibility value of left Cd could be potentially used as a biomarker of disease severity in mild and moderate AD.

Multiscale/multiresolution landslides susceptibility mapping

NASA Astrophysics Data System (ADS)

Grozavu, Adrian; Cătălin Stanga, Iulian; Valeriu Patriche, Cristian; Toader Juravle, Doru

2014-05-01

Within the European strategies, landslides are considered an important threatening that requires detailed studies to identify areas where these processes could occur in the future and to design scientific and technical plans for landslide risk mitigation. In this idea, assessing and mapping the landslide susceptibility is an important preliminary step. Generally, landslide susceptibility at small scale (for large regions) can be assessed through qualitative approach (expert judgements), based on a few variables, while studies at medium and large scale requires quantitative approach (e.g. multivariate statistics), a larger set of variables and, necessarily, the landslide inventory. Obviously, the results vary more or less from a scale to another, depending on the available input data, but also on the applied methodology. Since it is almost impossible to have a complete landslide inventory on large regions (e.g. at continental level), it is very important to verify the compatibility and the validity of results obtained at different scales, identifying the differences and fixing the inherent errors. This paper aims at assessing and mapping the landslide susceptibility at regional level through a multiscale-multiresolution approach from small scale and low resolution to large scale and high resolution of data and results, comparing the compatibility of results. While the first ones could be used for studies at european and national level, the later ones allows results validation, including through fields surveys. The test area, namely the Barlad Plateau (more than 9000 sq.km) is located in Eastern Romania, covering a region where both the natural environment and the human factor create a causal context that favor these processes. The landslide predictors were initially derived from various databases available at pan-european level and progressively completed and/or enhanced together with scale and the resolution: the topography (from SRTM at 90 meters to digital

A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field.

PubMed

Cronin, Matthew John; Wharton, Samuel; Al-Radaideh, Ali; Constantinescu, Cris; Evangelou, Nikos; Bowtell, Richard; Gowland, Penny Anne

2016-06-01

The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition. Thirty-nine Subjects were scanned at 7 T, using 3D T 2*-weighted and T 1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm. Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast. Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings.

Effects of White Matter Microstructure on Phase and Susceptibility Maps

PubMed Central

Wharton, Samuel; Bowtell, Richard

2015-01-01

Purpose To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). Methods The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. Results The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Conclusion Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contributions. Magn Reson Med 73:1258–1269, 2015. © 2014 Wiley Periodicals, Inc. PMID:24619643

Background field removal technique based on non-regularized variable kernels sophisticated harmonic artifact reduction for phase data for quantitative susceptibility mapping.

PubMed

Kan, Hirohito; Arai, Nobuyuki; Takizawa, Masahiro; Omori, Kazuyoshi; Kasai, Harumasa; Kunitomo, Hiroshi; Hirose, Yasujiro; Shibamoto, Yuta

2018-06-11

We developed a non-regularized, variable kernel, sophisticated harmonic artifact reduction for phase data (NR-VSHARP) method to accurately estimate local tissue fields without regularization for quantitative susceptibility mapping (QSM). We then used a digital brain phantom to evaluate the accuracy of the NR-VSHARP method, and compared it with the VSHARP and iterative spherical mean value (iSMV) methods through in vivo human brain experiments. Our proposed NR-VSHARP method, which uses variable spherical mean value (SMV) kernels, minimizes L2 norms only within the volume of interest to reduce phase errors and save cortical information without regularization. In a numerical phantom study, relative local field and susceptibility map errors were determined using NR-VSHARP, VSHARP, and iSMV. Additionally, various background field elimination methods were used to image the human brain. In a numerical phantom study, the use of NR-VSHARP considerably reduced the relative local field and susceptibility map errors throughout a digital whole brain phantom, compared with VSHARP and iSMV. In the in vivo experiment, the NR-VSHARP-estimated local field could sufficiently achieve minimal boundary losses and phase error suppression throughout the brain. Moreover, the susceptibility map generated using NR-VSHARP minimized the occurrence of streaking artifacts caused by insufficient background field removal. Our proposed NR-VSHARP method yields minimal boundary losses and highly precise phase data. Our results suggest that this technique may facilitate high-quality QSM. Copyright © 2017. Published by Elsevier Inc.

Positive Contrast Visualization of Nitinol Devices using Susceptibility Gradient Mapping

PubMed Central

Vonken, Evert-jan P.A.; Schär, Michael; Stuber, Matthias

2008-01-01

MRI visualization of devices is traditionally based on the signal loss due to T2* effects originating from the local susceptibility differences. To visualize nitinol devices with positive contrast a recently introduced post processing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center of mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualization of a nitinol wire and two stents are shown for illustration. PMID:18727096

Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study

PubMed Central

Langkammer, Christian; Schweser, Ferdinand; Krebs, Nikolaus; Deistung, Andreas; Goessler, Walter; Scheurer, Eva; Sommer, Karsten; Reishofer, Gernot; Yen, Kathrin; Fazekas, Franz; Ropele, Stefan; Reichenbach, Jürgen R.

2012-01-01

Quantitative susceptibility mapping (QSM) is a novel technique which allows determining the bulk magnetic susceptibility distribution of tissue in vivo from gradient echo magnetic resonance phase images. It is commonly assumed that paramagnetic iron is the predominant source of susceptibility variations in gray matter as many studies have reported a reasonable correlation of magnetic susceptibility with brain iron concentrations in vivo. Instead of performing direct comparisons, however, all these studies used the putative iron concentrations reported in the hallmark study by Hallgren and Sourander (1958) for their analysis. Consequently, the extent to which QSM can serve to reliably assess brain iron levels is not yet fully clear. To provide such information we investigated the relation between bulk tissue magnetic susceptibility and brain iron concentration in unfixed (in situ) post mortem brains of 13 subjects using MRI and inductively coupled plasma mass spectrometry. A strong linear correlation between chemically determined iron concentration and bulk magnetic susceptibility was found in gray matter structures (r = 0.84, p < 0.001), whereas the correlation coefficient was much lower in white matter (r = 0.27, p < 0.001). The slope of the overall linear correlation was consistent with theoretical considerations of the magnetism of ferritin supporting that most of the iron in the brain is bound to ferritin proteins. In conclusion, iron is the dominant source of magnetic susceptibility in deep gray matter and can be assessed with QSM. In white matter regions the estimation of iron concentrations by QSM is less accurate and more complex because the counteracting contribution from diamagnetic myelinated neuronal fibers confounds the interpretation. PMID:22634862

Noninvasive Assessment of Oxygen Extraction Fraction in Chronic Ischemia Using Quantitative Susceptibility Mapping at 7 Tesla.

PubMed

Uwano, Ikuko; Kudo, Kohsuke; Sato, Ryota; Ogasawara, Kuniaki; Kameda, Hiroyuki; Nomura, Jun-Ichi; Mori, Futoshi; Yamashita, Fumio; Ito, Kenji; Yoshioka, Kunihiro; Sasaki, Makoto

2017-08-01

The oxygen extraction fraction (OEF) is an effective metric to evaluate metabolic reserve in chronic ischemia. However, OEF is considered to be accurately measured only when using positron emission tomography (PET). Thus, we investigated whether OEF maps generated by magnetic resonance quantitative susceptibility mapping (QSM) at 7 Tesla enabled detection of OEF changes when compared with those obtained with PET. Forty-one patients with chronic stenosis/occlusion of the unilateral internal carotid artery or middle cerebral artery were examined using 7 Tesla-MRI and PET scanners. QSM images were obtained from 3-dimensional T2*-weighted images, using a multiple dipole-inversion algorithm. OEF maps were generated based on susceptibility differences between venous structures and brain tissues on QSM images. OEF ratios of the ipsilateral middle cerebral artery territory against the contralateral side were calculated on the QSM-OEF and PET-OEF images, using an anatomic template. The OEF ratio in the middle cerebral artery territory showed significant correlations between QSM-OEF and PET-OEF maps ( r =0.69; P <0.001), especially in patients with a substantial increase in the PET-OEF ratio of 1.09 ( r =0.79; P =0.004), although showing significant systematic biases for the agreements. An increased QSM-OEF ratio of >1.09, as determined by receiver operating characteristic analysis, showed a sensitivity and specificity of 0.82 and 0.86, respectively, for the substantial increase in the PET-OEF ratio. Absolute QSM-OEF values were significantly correlated with PET-OEF values in the patients with increased PET-OEF. OEF ratios on QSM-OEF images at 7 Tesla showed a good correlation with those on PET-OEF images in patients with unilateral steno-occlusive internal carotid artery/middle cerebral artery lesions, suggesting that noninvasive OEF measurement by MRI can be a substitute for PET. © 2017 American Heart Association, Inc.

Quantitative susceptibility mapping as a biomarker for evaluating white matter alterations in Parkinson's disease.

PubMed

Guan, Xiaojun; Huang, Peiyu; Zeng, Qiaoling; Liu, Chunlei; Wei, Hongjiang; Xuan, Min; Gu, Quanquan; Xu, Xiaojun; Wang, Nian; Yu, Xinfeng; Luo, Xiao; Zhang, Minming

2018-02-07

Myelinated white matter showing diamagnetic susceptibility is important for information transfer in the brain. In Parkinson's disease (PD), the white matter is also suffering degenerative alterations. Quantitative susceptibility mapping (QSM) is a novel technique for noninvasive assessment of regional white matter ultrastructure, and provides different information of white matter in addition to standard diffusion tensor imaging (DTI). In this study, we used QSM to detect spatial white matter alterations in PD patients (n = 65) and age- and sex-matched normal controls (n = 46). Voxel-wise tract-based spatial statistics were performed to analyze QSM and DTI data. QSM showed extensive white matter involvement-including regions adjacent to the frontal, parietal, and temporal lobes-in PD patients, which was more widespread than that observed using DTI. Both QSM and DTI showed similar alterations in the left inferior longitudinal fasciculus and right cerebellar hemisphere. Further, alterations in the white matter were correlated with motor impairment and global disease severity in PD patients. We suggest that QSM may provide a novel approach for detecting white matter alterations and underlying network disruptions in PD. Further, the combination of QSM and DTI would provide a more complete evaluation of the diseased brain by analyzing different biological tissue properties.

Primal-dual and forward gradient implementation for quantitative susceptibility mapping.

PubMed

Kee, Youngwook; Deh, Kofi; Dimov, Alexey; Spincemaille, Pascal; Wang, Yi

2017-12-01

To investigate the computational aspects of the prior term in quantitative susceptibility mapping (QSM) by (i) comparing the Gauss-Newton conjugate gradient (GNCG) algorithm that uses numerical conditioning (ie, modifies the prior term) with a primal-dual (PD) formulation that avoids this, and (ii) carrying out a comparison between a central and forward difference scheme for the discretization of the prior term. A spatially continuous formulation of the regularized QSM inversion problem and its PD formulation were derived. The Chambolle-Pock algorithm for PD was implemented and its convergence behavior was compared with that of GNCG for the original QSM. Forward and central difference schemes were compared in terms of the presence of checkerboard artifacts. All methods were tested and validated on a gadolinium phantom, ex vivo brain blocks, and in vivo brain MRI data with respect to COSMOS. The PD approach provided a faster convergence rate than GNCG. The GNCG convergence rate slowed considerably with smaller (more accurate) values of the conditioning parameter. Using a forward difference suppressed the checkerboard artifacts in QSM, as compared with the central difference. The accuracy of PD and GNCG were validated based on excellent correlation with COSMOS. The PD approach with forward difference for the gradient showed improved convergence and accuracy over the GNCG method using central difference. Magn Reson Med 78:2416-2427, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Thalamic white matter in multiple sclerosis: A combined diffusion-tensor imaging and quantitative susceptibility mapping study.

PubMed

Bergsland, Niels; Schweser, Ferdinand; Dwyer, Michael G; Weinstock-Guttman, Bianca; Benedict, Ralph H B; Zivadinov, Robert

2018-06-19

Thalamic white matter (WM) injury in multiple sclerosis (MS) remains relatively poorly understood. Combining multiple imaging modalities, sensitive to different tissue properties, may aid in further characterizing thalamic damage. Forty-five MS patients and 17 demographically-matched healthy controls (HC) were scanned with 3T MRI to obtain quantitative measures of diffusivity and magnetic susceptibility. Participants underwent cognitive evaluation with the Brief International Cognitive Assessment for Multiple Sclerosis battery. Tract-based spatial statistics identified thalamic WM. Non-parametric combination (NPC) analysis was used to perform joint inference on fractional anisotropy (FA), mean diffusivity (MD) and magnetic susceptibility measures. The association of surrounding WM lesions and thalamic WM pathology was investigated with lesion probability mapping. Compared to HCs, the greatest extent of thalamic WM damage was reflected by the combination of increased MD and decreased magnetic susceptibility (63.0% of thalamic WM, peak p = .001). Controlling for thalamic volume resulted in decreased FA and magnetic susceptibility (34.1%, peak p = .004) as showing the greatest extent. In MS patients, the most widespread association with information processing speed was found with the combination of MD and magnetic susceptibility (67.6%, peak p = .0005), although this was not evident after controlling for thalamic volume. For memory measures, MD alone yielded the most widespread associations (45.9%, peak p = .012 or 76.7%, peak p = .001), even after considering thalamic volume, albeit with smaller percentages. White matter lesions were related to decreased FA (peak p = .0063) and increased MD (peak p = .007), but not magnetic susceptibility, of thalamic WM. Our study highlights the complex nature of thalamic pathology in MS. © 2018 Wiley Periodicals, Inc.

Hemisphere, gender and age-related effects on iron deposition in deep gray matter revealed by quantitative susceptibility mapping.

PubMed

Gong, Nan-Jie; Wong, Chun-Sing; Hui, Edward S; Chan, Chun-Chung; Leung, Lam-Ming

2015-10-01

The purpose of this work was to investigate the effects of hemispheric location, gender and age on susceptibility value, as well as the association between susceptibility value and diffusional metrics, in deep gray matter. Iron content was estimated in vivo using quantitative susceptibility mapping. Microstructure was probed using diffusional kurtosis imaging. Regional susceptibility and diffusional metrics were measured for the putamen, caudate nucleus, globus pallidus, thalamus, substantia nigra and red nucleus in 42 healthy adults (age range 25-78 years). Susceptibility value was significantly higher in the left than the right side of the caudate nucleus (P = 0.043) and substantia nigra (P < 0.001). Women exhibited lower susceptibility values than men in the thalamus (P < 0.001) and red nucleus (P = 0.032). Significant age-related increases of susceptibility were observed in the putamen (P < 0.001), red nucleus (P < 0.001), substantia nigra (P = 0.004), caudate nucleus (P < 0.001) and globus pallidus (P = 0.017). The putamen exhibited the highest rate of iron accumulation with aging (slope of linear regression = 0.73 × 10(-3) ppm/year), which was nearly twice those in substantia nigra (slope = 0.40 × 10(-3) ppm/year) and caudate nucleus (slope = 0.39 × 10(-3) ppm/year). Significant positive correlations between the susceptibility value and diffusion measurements were observed for fractional anisotropy (P = 0.045) and mean kurtosis (P = 0.048) in the putamen without controlling for age. Neither correlation was significant after controlling for age. Hemisphere, gender and age-related differences in iron measurements were observed in deep gray matter. Notably, the putamen exhibited the highest rate of increase in susceptibility with aging. Correlations between susceptibility value and microstructural measurements were inconclusive. These findings could provide new clues for unveiling mechanisms underlying iron-related neurodegenerative diseases. Copyright �

An interleaved sequence for simultaneous magnetic resonance angiography (MRA), susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM).

PubMed

Chen, Yongsheng; Liu, Saifeng; Buch, Sagar; Hu, Jiani; Kang, Yan; Haacke, E Mark

2018-04-01

To image the entire vasculature of the brain with complete suppression of signal from background tissue using a single 3D excitation interleaved rephased/dephased multi-echo gradient echo sequence. This ensures no loss of signal from fast flow and provides co-registered susceptibility weighted images (SWI) and quantitative susceptibility maps (QSM) from the same scan. The suppression of background tissue was accomplished by subtracting the flow-dephased images from the flow-rephased images with the same echo time of 12.5ms to generate a magnetic resonance angiogram and venogram (MRAV). Further, a 2.5ms flow-compensated echo was added in the rephased portion to provide sufficient signal for major arteries with fast flow. The QSM data from the rephased 12.5ms echo was used to suppress veins on the MRAV to generate an artery-only MRA. The proposed approach was tested on five healthy volunteers at 3T. This three-echo interleaved GRE sequence provided complete background suppression of stationary tissues, while the short echo data gave high signal in the internal carotid and middle cerebral arteries (MCA). The contrast-to-noise ratio (CNR) of the arteries was significantly improved in the M3 territory of the MCA compared to the non-linear subtraction MRA and TOF-MRA. Veins were suppressed successfully utilizing the QSM data. The background tissue can be properly suppressed using the proposed interleaved MRAV sequence. One can obtain whole brain MRAV, MRA, SWI, true-SWI (or tSWI) and QSM data simultaneously from a single scan. Published by Elsevier Inc.

Progress in landslide susceptibility mapping over Europe using Tier-based approaches

NASA Astrophysics Data System (ADS)

Günther, Andreas; Hervás, Javier; Reichenbach, Paola; Malet, Jean-Philippe

2010-05-01

the same or equivalent thematic data as for the one above has been generated for six French departments using a heuristic, weighting-based multi-criteria evaluation model applied also to raster-cell mapping units. In this experiment, thematic data class weights have been differentiated for two stratification areas, namely mountains and plains, and four main landslide types. Separate susceptibility maps for each landslide type and a combined map for all types have been produced. Results have been validated using BRGM's BDMvT landslide inventory. Unlike "Tier 1", "Tier 2" assessment requires landslide inventory data and additional thematic data on conditioning factors which may not be available for all European countries. For the "Tier 2", a nation-wide quantitative landslide susceptibility assessment has been performed for Italy by applying a statistical model. In this assessment, multivariate analysis was applied using bedrock, soil and climate data together with a number of derivatives from SRTM90 DEM. In addition, separate datasets from a historical landslide inventory were used for model training and validation respectively. The mapping units selected were based on administrative boundaries (municipalities). The performance of this nation-wide, quantitative susceptibility assessment has been evaluated using multi-temporal landslide inventory data. Finally, model limitations for "Tier 1" are discussed, and recommendations for enhanced Tier 1 and Tier 2 models including additional thematic data for conditioning factors are drawn. This project is part of the collaborative research carried out within the European Landslide Expert Group coordinated by JRC in support to the EU Soil Thematic Strategy. It is also supported by the International Programme on Landslides of the International Consortium on Landslides.

Storm-Induced Slope Failure Susceptibility Mapping

DOT National Transportation Integrated Search

2018-01-01

A pilot study was conducted to characterize and map the areas susceptible to slope failure using state-wide available data. The objective was to determine whether it would be possible to provide slope-failure susceptibility mapping that could be used...

Bone quantitative susceptibility mapping using a chemical species-specific R2* signal model with ultrashort and conventional echo data.

PubMed

Dimov, Alexey V; Liu, Zhe; Spincemaille, Pascal; Prince, Martin R; Du, Jiang; Wang, Yi

2018-01-01

To develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping. Three-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the chemical species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT. Compared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R 2  = 0.77). Bone QSM was successfully generated in all subjects. The QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Reduced deep regional cerebral venous oxygen saturation in hemodialysis patients using quantitative susceptibility mapping.

PubMed

Chai, Chao; Liu, Saifeng; Fan, Linlin; Liu, Lei; Li, Jinping; Zuo, Chao; Qian, Tianyi; Haacke, E Mark; Shen, Wen; Xia, Shuang

2018-02-01

Cerebral venous oxygen saturation (SvO 2 ) is an important indicator of brain function. There was debate about lower cerebral oxygen metabolism in hemodialysis patients and there were no reports about the changes of deep regional cerebral SvO 2 in hemodialysis patients. In this study, we aim to explore the deep regional cerebral SvO 2 from straight sinus using quantitative susceptibility mapping (QSM) and the correlation with clinical risk factors and neuropsychiatric testing . 52 hemodialysis patients and 54 age-and gender-matched healthy controls were enrolled. QSM reconstructed from original phase data of 3.0 T susceptibility-weighted imaging was used to measure the susceptibility of straight sinus. The susceptibility was used to calculate the deep regional cerebral SvO 2 and compare with healthy individuals. Correlation analysis was performed to investigate the correlation between deep regional cerebral SvO 2 , clinical risk factors and neuropsychiatric testing. The deep regional cerebral SvO 2 of hemodialysis patients (72.5 ± 3.7%) was significantly lower than healthy controls (76.0 ± 2.1%) (P < 0.001). There was no significant difference in the measured volume of interests of straight sinus between hemodialysis patients (250.92 ± 46.65) and healthy controls (249.68 ± 49.68) (P = 0.859). There were no significant correlations between the measured susceptibility and volume of interests in hemodialysis patients (P = 0.204) and healthy controls (P = 0.562), respectively. Hematocrit (r = 0.480, P < 0.001, FDR corrected), hemoglobin (r = 0.440, P < 0.001, FDR corrected), red blood cell (r = 0.446, P = 0.003, FDR corrected), dialysis duration (r = 0.505, P = 0.002, FDR corrected) and parathyroid hormone (r = -0.451, P = 0.007, FDR corrected) were risk factors for decreased deep regional cerebral SvO 2 in patients. The Mini-Mental State Examination (MMSE) scores of hemodialysis patients were

Landslides susceptibility mapping at Gunung Ciremai National Park

NASA Astrophysics Data System (ADS)

Faizin; Nur, Bambang Azis

2018-02-01

In addition to agriculture, tourism became one of primary economic income for communities around Mount Ciremai, West, Java. Unfortunately, the landscape of West Java has many potential causes to disasters, mainly landslides. Mapping of disaster susceptibility area is needed as a consideration of tourism planning. The study was conducted in Gunung Ciremai National Park, West Java. This paper propose a methodology to map landslides susceptibilities based on spatial data. Using Geographic Information System tools, several environmental parameters such as slope, land use, elevation, and lithology are scored to build a landslide susceptibility map. Then, susceptibility map is overlaid with Utilization Zone.

Computed inverse resonance imaging for magnetic susceptibility map reconstruction.

PubMed

Chen, Zikuan; Calhoun, Vince

2012-01-01

This article reports a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a 2-step computational approach. The forward T2*-weighted MRI (T2*MRI) process is broken down into 2 steps: (1) from magnetic susceptibility source to field map establishment via magnetization in the main field and (2) from field map to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes 2 inverse steps to reverse the T2*MRI procedure: field map calculation from MR-phase image and susceptibility source calculation from the field map. The inverse step from field map to susceptibility map is a 3-dimensional ill-posed deconvolution problem, which can be solved with 3 kinds of approaches: the Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from an MR-phase image with high fidelity (spatial correlation ≈ 0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by 2 computational steps: calculating the field map from the phase image and reconstructing the susceptibility map from the field map. The crux of CIMRI lies in an ill-posed 3-dimensional deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm.

Mapping landslide susceptibility using data-driven methods.

PubMed

Zêzere, J L; Pereira, S; Melo, R; Oliveira, S C; Garcia, R A C

2017-07-01

Most epistemic uncertainty within data-driven landslide susceptibility assessment results from errors in landslide inventories, difficulty in identifying and mapping landslide causes and decisions related with the modelling procedure. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from: (i) the selection of the statistical method; (ii) the selection of the terrain mapping unit; and (iii) the selection of the feature type to represent landslides in the model (polygon versus point). The work is performed in a single study area (Silveira Basin - 18.2km 2 - Lisbon Region, Portugal) using a unique database of geo-environmental landslide predisposing factors and an inventory of 82 shallow translational slides. The logistic regression, the discriminant analysis and two versions of the information value were used and we conclude that multivariate statistical methods perform better when computed over heterogeneous terrain units and should be selected to assess landslide susceptibility based on slope terrain units, geo-hydrological terrain units or census terrain units. However, evidence was found that the chosen terrain mapping unit can produce greater differences on final susceptibility results than those resulting from the chosen statistical method for modelling. The landslide susceptibility should be assessed over grid cell terrain units whenever the spatial accuracy of landslide inventory is good. In addition, a single point per landslide proved to be efficient to generate accurate landslide susceptibility maps, providing the landslides are of small size, thus minimizing the possible existence of heterogeneities of predisposing factors within the landslide boundary. Although during last years the ROC curves have been preferred to evaluate the susceptibility model's performance, evidence was found that the model with the highest AUC ROC is not necessarily the best landslide susceptibility model, namely when terrain

Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter.

PubMed

Elkady, Ahmed M; Sun, Hongfu; Wilman, Alan H

2016-05-01

Quantitative Susceptibility Mapping (QSM) is an emerging area of brain research with clear application to brain iron studies in deep gray matter. However, acquisition of standard whole brain QSM can be time-consuming. One means to reduce scan time is to use a focal acquisition restricted only to the regions of interest such as deep gray matter. However, the non-local dipole field necessary for QSM reconstruction extends far beyond the structure of interest. We demonstrate the practical implications of these non-local fields on the choice of brain volume for QSM. In an illustrative numerical simulation and then in human brain experiments, we examine the effect on QSM of volume reduction in each dimension. For the globus pallidus, as an example of iron-rich deep gray matter, we demonstrate that substantial errors can arise even when the field-of-view far exceeds the physical structural boundaries. Thus, QSM reconstruction requires a non-local field-of-view prescription to ensure minimal errors. An axial QSM acquisition, centered on the globus pallidus, should encompass at least 76mm in the superior-inferior direction to conserve susceptibility values from the globus pallidus. This dimension exceeds the physical coronal extent of this structure by at least five-fold. As QSM sees wider use in the neuroscience community, its unique requirement for an extended field-of-view needs to be considered. Copyright © 2016 Elsevier Inc. All rights reserved.

Preliminary soil-slip susceptibility maps, southwestern California

USGS Publications Warehouse

Morton, Douglas M.; Alvarez, Rachel M.; Campbell, Russell H.; Digital preparation by Bovard, Kelly R.; Brown, D.T.; Corriea, K.M.; Lesser, J.N.

2003-01-01

This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of “where”, “when”, and “how big”. These maps empirically show part of the “where” of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to “when” the process might begin is developed. “When” is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. “When” information is not provided on the maps but is described later in this narrative. The prediction of “how big” is addressed indirectly by restricting the maps to a single type of landslide process—soil slip-debris flows. The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as

A landslide susceptibility map of Africa

NASA Astrophysics Data System (ADS)

Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

2017-04-01

Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important

MRI Estimates of Brain Iron Concentration in Normal Aging Using Quantitative Susceptibility Mapping

PubMed Central

Bilgic, Berkin; Pfefferbaum, Adolf; Rohlfing, Torsten; Sullivan, Edith V.; Adalsteinsson, Elfar

2011-01-01

Quantifying tissue iron concentration in vivo is instrumental for understanding the role of iron in physiology and in neurological diseases associated with abnormal iron distribution. Herein, we use recently-developed Quantitative Susceptibility Mapping (QSM) methodology to estimate the tissue magnetic susceptibility based on MRI signal phase. To investigate the effect of different regularization choices, we implement and compare ℓ1 and ℓ2 norm regularized QSM algorithms. These regularized approaches solve for the underlying magnetic susceptibility distribution, a sensitive measure of the tissue iron concentration, that gives rise to the observed signal phase. Regularized QSM methodology also involves a pre-processing step that removes, by dipole fitting, unwanted background phase effects due to bulk susceptibility variations between air and tissue and requires data acquisition only at a single field strength. For validation, performances of the two QSM methods were measured against published estimates of regional brain iron from postmortem and in vivo data. The in vivo comparison was based on data previously acquired using Field-Dependent Relaxation Rate Increase (FDRI), an estimate of MRI relaxivity enhancement due to increased main magnetic field strength, requiring data acquired at two different field strengths. The QSM analysis was based on susceptibility-weighted images acquired at 1.5T, whereas FDRI analysis used Multi-Shot Echo-Planar Spin Echo images collected at 1.5T and 3.0T. Both datasets were collected in the same healthy young and elderly adults. The in vivo estimates of regional iron concentration comported well with published postmortem measurements; both QSM approaches yielded the same rank ordering of iron concentration by brain structure, with the lowest in white matter and the highest in globus pallidus. Further validation was provided by comparison of the in vivo measurements, ℓ1-regularized QSM versus FDRI and ℓ2-regularized QSM versus

A Heuristic Approach to Global Landslide Susceptibility Mapping

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.

2017-01-01

Landslides can have significant and pervasive impacts to life and property around the world. Several attempts have been made to predict the geographic distribution of landslide activity at continental and global scales. These efforts shared common traits such as resolution, modeling approach, and explanatory variables. The lessons learned from prior research have been applied to build a new global susceptibility map from existing and previously unavailable data. Data on slope, faults, geology, forest loss, and road networks were combined using a heuristic fuzzy approach. The map was evaluated with a Global Landslide Catalog developed at the National Aeronautics and Space Administration, as well as several local landslide inventories. Comparisons to similar susceptibility maps suggest that the subjective methods commonly used at this scale are, for the most part, reproducible. However, comparisons of landslide susceptibility across spatial scales must take into account the susceptibility of the local subset relative to the larger study area. The new global landslide susceptibility map is intended for use in disaster planning, situational awareness, and for incorporation into global decision support systems.

Land subsidence susceptibility and hazard mapping: the case of Amyntaio Basin, Greece

NASA Astrophysics Data System (ADS)

Tzampoglou, P.; Loupasakis, C.

2017-09-01

Landslide susceptibility and hazard mapping has been applying for more than 20 years succeeding the assessment of the landslide risk and the mitigation the phenomena. On the contrary, equivalent maps aiming to study and mitigate land subsidence phenomena caused by the overexploitation of the aquifers are absent from the international literature. The current study focuses at the Amyntaio basin, located in West Macedonia at Florina prefecture. As proved by numerous studies the wider area has been severely affected by the overexploitation of the aquifers, caused by the mining and the agricultural activities. The intensive ground water level drop has triggered extensive land subsidence phenomena, especially at the perimeter of the open pit coal mine operating at the site, causing damages to settlements and infrastructure. The land subsidence susceptibility and risk maps were produced by applying the semi-quantitative WLC (Weighted Linear Combination) method, especially calibrated for this particular catastrophic event. The results were evaluated by using detailed field mapping data referring to the spatial distribution of the surface ruptures caused by the subsidence. The high correlation between the produced maps and the field mapping data, have proved the great value of the maps and of the applied technique on the management and the mitigation of the phenomena. Obviously, these maps can be safely used by decision-making authorities for the future urban safety development.

Simultaneous quantitative susceptibility mapping and Flutemetamol-PET suggests local correlation of iron and β-amyloid as an indicator of cognitive performance at high age.

PubMed

van Bergen, J M G; Li, X; Quevenco, F C; Gietl, A F; Treyer, V; Meyer, R; Buck, A; Kaufmann, P A; Nitsch, R M; van Zijl, P C M; Hock, C; Unschuld, P G

2018-03-13

The accumulation of β-amyloid plaques is a hallmark of Alzheimer's disease (AD), and recently published data suggest that increased brain iron burden may reflect pathologies that synergistically contribute to the development of cognitive dysfunction. While preclinical disease stages are considered most promising for therapeutic intervention, the link between emerging AD-pathology and earliest clinical symptoms remains largely unclear. In the current study we therefore investigated local correlations between iron and β-amyloid plaques, and their possible association with cognitive performance in healthy older adults. 116 older adults (mean age 75 ± 7.4 years) received neuropsychological testing to calculate a composite cognitive score of performance in episodic memory, executive functioning, attention, language and communication. All participants were scanned on a combined PET-MRI instrument and were administered T1-sequences for anatomical mapping, quantitative susceptibility mapping (QSM) for assessing iron, and 18F-Flutemetamol-PET for estimating β-amyloid plaque load. Biological parametric mapping (BPM) was used to generate masks indicating voxels with significant (p < 0.05) correlation between susceptibility and 18F-Flutemetamol-SUVR. We found a bilateral pattern of clusters characterized by a statistical relationship between magnetic susceptibility and 18F-Flutemetamol-SUVR, indicating local correlations between iron and β-amyloid plaque deposition. For two bilateral clusters, located in the frontal and temporal cortex, significant relationships (p<0.05) between local β-amyloid and the composite cognitive performance score could be observed. No relationship between whole-cortex β-amyloid plaque load and cognitive performance was observable. Our data suggest that the local correlation of β-amyloid plaque load and iron deposition may provide relevant information regarding cognitive performance of healthy older adults. Further studies are needed

Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti

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

Severson, D.W.; Thathy, V.; Mori, A.

Susceptibility of the mosquito Aedes aegypti to the malarial parasite Plasmodium gallinaceum was investigated as a quantitative trait using restriction fragment length polymorphisms (RFLP). Two F{sub 2} populations of mosquitoes were independently prepared from pairwise matings between a highly susceptible and a refractory strain of A. aegypti. RFLP were tested for association with oocyst development on the mosquito midgut. Two putative quantitative trait loci (QTL) were identified that significantly affect susceptibility. One QTL, pgs [2,LF98], is located on chromosome 2 and accounted for 65 and 49% of the observed phenotypic variance in the two populations, respectively. A second QTL, pgs[3,MalI],more » is located on chromosome 3 and accounted for 14 and 10% of the observed phenotypic variance in the two populations, respectively. Both QTL exhibit a partial dominance effect on susceptibility, wherein the dominance effect is derived from the refractory parent. No indication of epistasis between these QTL was detected. Evidence suggests that either a tightly linked cluster of independent genes or a single locus affecting susceptibility to various mosquito-borne parasites and pathogens has evolved near the LF98 locus; in addition to P. gallinaceum susceptibility, this general genome region has previously been implicated in susceptibility to the filaria nematode Brugia malayi and the yellow fever virus. 35 refs., 2 figs., 3 tabs.« less

Evaluation and Quantitative trait loci mapping of resistance to powdery mildew in lettuce

USDA-ARS?s Scientific Manuscript database

Lettuce (Lactuca sativa L.) is the major leafy vegetable that is susceptible to powdery mildew disease under greenhouse and field conditions. We mapped quantitative trait loci (QTLs) for resistance to powdery mildew under greenhouse conditions in an interspecific population derived from a cross betw...

Computed inverse MRI for magnetic susceptibility map reconstruction

PubMed Central

Chen, Zikuan; Calhoun, Vince

2015-01-01

Objective This paper reports on a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a two-step computational approach. Methods The forward T2*-weighted MRI (T2*MRI) process is decomposed into two steps: 1) from magnetic susceptibility source to fieldmap establishment via magnetization in a main field, and 2) from fieldmap to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes two inverse steps to reverse the T2*MRI procedure: fieldmap calculation from MR phase image and susceptibility source calculation from the fieldmap. The inverse step from fieldmap to susceptibility map is a 3D ill-posed deconvolution problem, which can be solved by three kinds of approaches: Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Results Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from a MR phase image with high fidelity (spatial correlation≈0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. Conclusions The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by two computational steps: calculating the fieldmap from the phase image and reconstructing the susceptibility map from the fieldmap. The crux of CIMRI lies in an ill-posed 3D deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm. PMID:22446372

Quantitative susceptibility mapping across two clinical field strengths: Contrast-to-noise ratio enhancement at 1.5T.

PubMed

Ippoliti, Matteo; Adams, Lisa C; Winfried, Brenner; Hamm, Bernd; Spincemaille, Pascal; Wang, Yi; Makowski, Marcus R

2018-04-16

Quantitative susceptibility mapping (QSM) is an MRI postprocessing technique that allows quantification of the spatial distribution of tissue magnetic susceptibility in vivo. Contributing sources include iron, blood products, calcium, myelin, and lipid content. To evaluate the reproducibility and consistency of QSM across clinical field strengths of 1.5T and 3T and to optimize the contrast-to-noise ratio (CNR) at 1.5T through bandwidth tuning. Prospective. Sixteen healthy volunteers (10 men, 6 women; age range 24-37; mean age 27.8 ± 3.2 years). 1.5T and 3T systems from the same vendor. Four spoiled gradient echo (SPGR) sequences were designed with different acquisition bandwidths. QSM reconstruction was achieved through a nonlinear morphology-enabled dipole inversion (MEDI) algorithm employing L1 regularization. CNR was calculated in seven regions of interest (ROIs), while reproducibility and consistency of QSM measurements were evaluated through voxel-based and region-specific linear correlation analyses and Bland-Altman plots. Interclass correlation, Wilcoxon rank sum test, linear regression analysis, Bland-Altman analysis, Welch's t-test. CNR analysis showed a statistically significant (P < 0.05) increase in four out of seven ROIs for the lowest bandwidth employed with respect to the highest (25.18% increase in CNR of caudate nucleus). All sequences reported an excellent correlation across field strength and bandwidth variation (R ≥ 0.96, widest limits of agreement from -18.7 to 25.8 ppb) in the ROI-based analysis, while the correlation was found to be good for the voxel-based analysis of averaged maps (R ≥ 0.90, widest limits of agreement from -9.3 to 9.1 ppb). CNR of QSM images reconstructed from 1.5T acquisitions can be enhanced through bandwidth tuning. MEDI-based QSM reconstruction demonstrated to be reproducible and consistent both across field strengths (1.5T and 3T) and bandwidth variation. 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018

Landslide susceptibility mapping using a neuro-fuzzy

NASA Astrophysics Data System (ADS)

Lee, S.; Choi, J.; Oh, H.

2009-12-01

This paper develops and applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. A neuro-fuzzy system is based on a fuzzy system that is trained by a learning algorithm derived from the neural network theory. The learning procedure operates on local information, and causes only local modifications in the underlying fuzzy system. The study area, Boun, suffered much damage following heavy rain in 1998 and was selected as a suitable site for the evaluation of the frequency and distribution of landslides. Boun is located in the central part of Korea. Landslide-related factors such as slope, soil texture, wood type, lithology, and density of lineament were extracted from topographic, soil, forest, and lineament maps. Landslide locations were identified from interpretation of aerial photographs and field surveys. Landslide-susceptible areas were analyzed by the ANFIS method and mapped using occurrence factors. In particular, we applied various membership functions (MFs) and analysis results were verified using the landslide location data. The predictive maps using triangular, trapezoidal, and polynomial MFs were the best individual MFs for modeling landslide susceptibility maps (84.96% accuracy), proving that ANFIS could be very effective in modeling landslide susceptibility mapping. Various MFs were used in this study, and after verification, the difference in accuracy according to the MFs was small, between 84.81% and 84.96%. The difference was just 0.15% and therefore the choice of MFs was not important in the study. Also, compared with the likelihood ratio model, which showed 84.94%, the accuracy was similar. Thus, the ANFIS could be applied to other study areas with different data and other study methods such as cross-validation. The developed ANFIS learns the if-then rules between landslide-related factors and landslide

Assessment of MR-based R2* and quantitative susceptibility mapping for the quantification of liver iron concentration in a mouse model at 7T.

PubMed

Simchick, Gregory; Liu, Zhi; Nagy, Tamas; Xiong, May; Zhao, Qun

2018-03-25

To assess the feasibility of quantifying liver iron concentration (LIC) using R2* and quantitative susceptibility mapping (QSM) at a high field strength of 7 Tesla (T). Five different concentrations of Fe-dextran were injected into 12 mice to produce various degrees of liver iron overload. After mice were sacrificed, blood and liver samples were harvested. Ferritin enzyme-linked immunosorbent assay (ELISA) and inductively coupled plasma mass spectrometry were performed to quantify serum ferritin concentration and LIC. Multiecho gradient echo MRI was conducted to estimate R2* and the magnetic susceptibility of each liver sample through complex nonlinear least squares fitting and a morphology enabled dipole inversion method, respectively. Average estimates of serum ferritin concentration, LIC, R2*, and susceptibility all show good linear correlations with injected Fe-dextran concentration; however, the standard deviations in the estimates of R2* and susceptibility increase with injected Fe-dextran concentration. Both R2* and susceptibility measurements also show good linear correlations with LIC (R 2  = 0.78 and R 2  = 0.91, respectively), and a susceptibility-to-LIC conversion factor of 0.829 ppm/(mg/g wet) is derived. The feasibility of quantifying LIC using MR-based  R2* and QSM at a high field strength of 7T is demonstrated. Susceptibility quantification, which is an intrinsic property of tissues and benefits from being field-strength independent, is more robust than R2* quantification in this ex vivo study. A susceptibility-to-LIC conversion factor is presented that agrees relatively well with previously published QSM derived results obtained at 1.5T and 3T. © 2018 International Society for Magnetic Resonance in Medicine.

Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds.

PubMed

Cronin, Matthew J; Wang, Nian; Decker, Kyle S; Wei, Hongjiang; Zhu, Wen-Zhen; Liu, Chunlei

2017-04-01

Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al., 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions. In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC. Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship. Copyright © 2017 Elsevier Inc. All rights reserved.

Positive visualization of implanted devices with susceptibility gradient mapping using the original resolution.

PubMed

Varma, Gopal; Clough, Rachel E; Acher, Peter; Sénégas, Julien; Dahnke, Hannes; Keevil, Stephen F; Schaeffter, Tobias

2011-05-01

In magnetic resonance imaging, implantable devices are usually visualized with a negative contrast. Recently, positive contrast techniques have been proposed, such as susceptibility gradient mapping (SGM). However, SGM reduces the spatial resolution making positive visualization of small structures difficult. Here, a development of SGM using the original resolution (SUMO) is presented. For this, a filter is applied in k-space and the signal amplitude is analyzed in the image domain to determine quantitatively the susceptibility gradient for each pixel. It is shown in simulations and experiments that SUMO results in a better visualization of small structures in comparison to SGM. SUMO is applied to patient datasets for visualization of stent and prostate brachytherapy seeds. In addition, SUMO also provides quantitative information about the number of prostate brachytherapy seeds. The method might be extended to application for visualization of other interventional devices, and, like SGM, it might also be used to visualize magnetically labelled cells. Copyright © 2010 Wiley-Liss, Inc.

Deep gray matter iron measurement in patients with liver cirrhosis using quantitative susceptibility mapping: Relationship with pallidal T1 hyperintensity.

PubMed

Lee, Song; Nam, Yoonho; Jang, Jinhee; Na, Gun Hyung; Kim, Dong Goo; Shin, Na-Young; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2018-05-01

The liver is a central organ for the metabolism of iron and manganese and the places where those metals are commonly deposited overlap in the brain. To elucidate the relationship between pallidal T 1 hyperintensity and iron deposition in the deep gray matter of liver cirrhosis patients using quantitative susceptibility mapping (QSM). Retrospective case-control study SUBJECTS: In all, 38 consecutive liver cirrhosis patients who received brain magnetic resonance imaging (MRI) as pretransplant evaluation. QSM was reconstructed from 3D multi- or single-echo phase images at 3T. T 1 -weighted images were used for the assessment of pallidal hyperintensity and pallidal index (PI). Patients were divided into two groups according to the presence of pallidal hyperintensity by consensus of two radiologists. Susceptibility values were acquired for five deep gray matter structures. QSM measures were compared between two groups using the t-test. We also calculated Pearson correlations between QSM measures and PI. In all, 26 patients showed pallidal hyperintensity (T 1 h group) and 12 did not (T 1 n group). The susceptibility of the globus pallidus (GP) in the T 1 h group (120.6 ± 38.1 ppb) was significantly lower than that in the T 1 n group (150.0 ± 35.2, P = 0.030). The susceptibility of the dentate nucleus (DN) in the T 1 h group (88.1 ± 31.0) was significantly lower than that in the T 1 n group (125.6 ± 30.6, P = 0.001). Negative correlation between the susceptibility of GP (r = -0.37, P = 0.022) and the PI, and between DN (r = -0.43, P < 0.001) and the PI was found. Liver cirrhosis patients with pallidal T 1 hyperintensity had lower susceptibility values in the GP and DN than those without it. This suggests a possible interaction between iron and manganese in the brains of liver cirrhosis patients. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1342-1349. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative Oxygenation Venography from MRI Phase

PubMed Central

Fan, Audrey P.; Bilgic, Berkin; Gagnon, Louis; Witzel, Thomas; Bhat, Himanshu; Rosen, Bruce R.; Adalsteinsson, Elfar

2014-01-01

Purpose To demonstrate acquisition and processing methods for quantitative oxygenation venograms that map in vivo oxygen saturation (SvO2) along cerebral venous vasculature. Methods Regularized quantitative susceptibility mapping (QSM) is used to reconstruct susceptibility values and estimate SvO2 in veins. QSM with ℓ1 and ℓ2 regularization are compared in numerical simulations of vessel structures with known magnetic susceptibility. Dual-echo, flow-compensated phase images are collected in three healthy volunteers to create QSM images. Bright veins in the susceptibility maps are vectorized and used to form a three-dimensional vascular mesh, or venogram, along which to display SvO2 values from QSM. Results Quantitative oxygenation venograms that map SvO2 along brain vessels of arbitrary orientation and geometry are shown in vivo. SvO2 values in major cerebral veins lie within the normal physiological range reported by 15O positron emission tomography. SvO2 from QSM is consistent with previous MR susceptometry methods for vessel segments oriented parallel to the main magnetic field. In vessel simulations, ℓ1 regularization results in less than 10% SvO2 absolute error across all vessel tilt orientations and provides more accurate SvO2 estimation than ℓ2 regularization. Conclusion The proposed analysis of susceptibility images enables reliable mapping of quantitative SvO2 along venograms and may facilitate clinical use of venous oxygenation imaging. PMID:24006229

Map and map database of susceptibility to slope failure by sliding and earthflow in the Oakland area, California

USGS Publications Warehouse

Pike, R.J.; Graymer, R.W.; Roberts, Sebastian; Kalman, N.B.; Sobieszczyk, Steven

2001-01-01

Map data that predict the varying likelihood of landsliding can help public agencies make informed decisions on land use and zoning. This map, prepared in a geographic information system from a statistical model, estimates the relative likelihood of local slopes to fail by two processes common to an area of diverse geology, terrain, and land use centered on metropolitan Oakland. The model combines the following spatial data: (1) 120 bedrock and surficial geologic-map units, (2) ground slope calculated from a 30-m digital elevation model, (3) an inventory of 6,714 old landslide deposits (not distinguished by age or type of movement and excluding debris flows), and (4) the locations of 1,192 post-1970 landslides that damaged the built environment. The resulting index of likelihood, or susceptibility, plotted as a 1:50,000-scale map, is computed as a continuous variable over a large area (872 km2) at a comparatively fine (30 m) resolution. This new model complements landslide inventories by estimating susceptibility between existing landslide deposits, and improves upon prior susceptibility maps by quantifying the degree of susceptibility within those deposits. Susceptibility is defined for each geologic-map unit as the spatial frequency (areal percentage) of terrain occupied by old landslide deposits, adjusted locally by steepness of the topography. Susceptibility of terrain between the old landslide deposits is read directly from a slope histogram for each geologic-map unit, as the percentage (0.00 to 0.90) of 30-m cells in each one-degree slope interval that coincides with the deposits. Susceptibility within landslide deposits (0.00 to 1.33) is this same percentage raised by a multiplier (1.33) derived from the comparative frequency of recent failures within and outside the old deposits. Positive results from two evaluations of the model encourage its extension to the 10-county San Francisco Bay region and elsewhere. A similar map could be prepared for any area

Mapping Landslides Susceptibility in a Traditional Northern Nigerian City

NASA Astrophysics Data System (ADS)

Oluwafemi, Olawale A.; Yakubu, Tahir A.; Muhammad, Mahmud U.; Shitta, Nyofo; Akinwumiju, Akinola S.

2018-05-01

As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.

Map showing landslide susceptibility in Prince Georges County, Maryland

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

Pomeroy, J.S.

1989-01-01

Prince Georges County was identified during a statewide investigation of landslide susceptibility (MF-2048) as the county with the most serious slope-stability problems. This map uses a ranking system ranging from 1 (nil to very low susceptibility) to 4 (moderate to severe susceptibility). Geologic factors and precipitation are major elements in the initiation of landslides in the county. The Potomac Group and the Marlboro Clay are the most slideprone units. This map should enable users to make a rapid, generalized evaluation of the potential for mass movement. Planners, engineers, soil scientists, geologist, university faculty, and elected officials should find it usefulmore » in the assessment of slope hazards for county-wide analyses.« less

Analysis of training sample selection strategies for regression-based quantitative landslide susceptibility mapping methods

NASA Astrophysics Data System (ADS)

Erener, Arzu; Sivas, A. Abdullah; Selcuk-Kestel, A. Sevtap; Düzgün, H. Sebnem

2017-07-01

All of the quantitative landslide susceptibility mapping (QLSM) methods requires two basic data types, namely, landslide inventory and factors that influence landslide occurrence (landslide influencing factors, LIF). Depending on type of landslides, nature of triggers and LIF, accuracy of the QLSM methods differs. Moreover, how to balance the number of 0 (nonoccurrence) and 1 (occurrence) in the training set obtained from the landslide inventory and how to select which one of the 1's and 0's to be included in QLSM models play critical role in the accuracy of the QLSM. Although performance of various QLSM methods is largely investigated in the literature, the challenge of training set construction is not adequately investigated for the QLSM methods. In order to tackle this challenge, in this study three different training set selection strategies along with the original data set is used for testing the performance of three different regression methods namely Logistic Regression (LR), Bayesian Logistic Regression (BLR) and Fuzzy Logistic Regression (FLR). The first sampling strategy is proportional random sampling (PRS), which takes into account a weighted selection of landslide occurrences in the sample set. The second method, namely non-selective nearby sampling (NNS), includes randomly selected sites and their surrounding neighboring points at certain preselected distances to include the impact of clustering. Selective nearby sampling (SNS) is the third method, which concentrates on the group of 1's and their surrounding neighborhood. A randomly selected group of landslide sites and their neighborhood are considered in the analyses similar to NNS parameters. It is found that LR-PRS, FLR-PRS and BLR-Whole Data set-ups, with order, yield the best fits among the other alternatives. The results indicate that in QLSM based on regression models, avoidance of spatial correlation in the data set is critical for the model's performance.

Implementation of landslide susceptibility maps in Lower Austria as part of risk governance

NASA Astrophysics Data System (ADS)

Bell, Rainer; Petschko, Helene; Bauer, Christian; Glade, Thomas; Granica, Klaus; Heiss, Gerhard; Leopold, Philip; Pomaroli, Gilbert; Proske, Herwig; Schweigl, Joachim

2013-04-01

Landslides frequently cause damage to agricultural land and infrastructure in Lower Austria - a province of Austria. Also settlements and people are threatened by landslides. To reduce landslide risks and to prevent the establishment of new settlements in highly landslide prone areas, the project "MoNOE" (Method development for landslide susceptibility modeling in Lower Austria) was set up by the provincial government. The main aim of the project is the development of methods to model rock fall and slide susceptibility for an area of approx. 15,900 km2 and to implement the resulting susceptibility maps into the spatial planning strategies of the state. Right from the beginning of the project a close cooperation between the involved scientists and the stakeholders from the Geological Survey of Lower Austria and the Department of Spatial Planning and Regional Policy of Lower Austria was established to ensure that method development and final susceptibility maps meet exactly the needs and demands of the stakeholders. This posed huge challenges, together with its realization in the large study area and a (heterogeneous) complex geological situation,. Limitations were given by restricted data availability (e.g. for geology or landslide inventories) in such a large study area. Rock fall susceptibility was modeled by a combined approach of determining rock fall release areas by empirical slope thresholds (dependent on geology) followed by empirical run-out modeling. Slide susceptibility was modeled based on the statistical approaches of weights of evidence (WofE) and generalized additive models (GAM) by two different research groups. Huge efforts were spent on the validation of all susceptibility models. In a later stage of the project we found that the best scientific maps are not necessarily the best maps to be implemented in spatial planning strategies. Thus, in close cooperation with the stakeholders, decisions had to be taken to find the best resolution of the maps

Quantitative trait locus gene mapping: a new method for locating alcohol response genes.

PubMed

Crabbe, J C

1996-01-01

Alcoholism is a multigenic trait with important non-genetic determinants. Studies with genetic animal models of susceptibility to several of alcohol's effects suggest that several genes contributing modest effects on susceptibility (Quantitative Trait Loci, or QTLs) are important. A new technique of QTL gene mapping has allowed the identification of the location in mouse genome of several such QTLs. The method is described, and the locations of QTLs affecting the acute alcohol withdrawal reaction are described as an example of the method. Verification of these QTLs in ancillary studies is described and the strengths, limitations, and future directions to be pursued are discussed. QTL mapping is a promising method for identifying genes in rodents with the hope of directly extrapolating the results to the human genome. This review is based on a paper presented at the First International Congress of the Latin American Society for Biomedical Research on Alcoholism, Santiago, Chile, November 1994.

Investigation of BOLD fMRI Resonance Frequency Shifts and Quantitative Susceptibility Changes at 7 T

PubMed Central

Bianciardi, Marta; van Gelderen, Peter; Duyn, Jeff H.

2013-01-01

Although blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) experiments of brain activity generally rely on the magnitude of the signal, they also provide frequency information that can be derived from the phase of the signal. However, because of confounding effects of instrumental and physiological origin, BOLD related frequency information is difficult to extract and therefore rarely used. Here, we explored the use of high field (7 T) and dedicated signal processing methods to extract frequency information and use it to quantify and interpret blood oxygenation and blood volume changes. We found that optimized preprocessing improves detection of task-evoked and spontaneous changes in phase signals and resonance frequency shifts over large areas of the cortex with sensitivity comparable to that of magnitude signals. Moreover, our results suggest the feasibility of mapping BOLD quantitative susceptibility changes in at least part of the activated area and its largest draining veins. Comparison with magnitude data suggests that the observed susceptibility changes originate from neuronal activity through induced blood volume and oxygenation changes in pial and intracortical veins. Further, from frequency shifts and susceptibility values, we estimated that, relative to baseline, the fractional oxygen saturation in large vessels increased by 0.02–0.05 during stimulation, which is consistent to previously published estimates. Together, these findings demonstrate that valuable information can be derived from fMRI imaging of BOLD frequency shifts and quantitative susceptibility changes. PMID:23897623

Integration of Murine and Human Studies for Mapping Periodontitis Susceptibility.

PubMed

Nashef, A; Qabaja, R; Salaymeh, Y; Botzman, M; Munz, M; Dommisch, H; Krone, B; Hoffmann, P; Wellmann, J; Laudes, M; Berger, K; Kocher, T; Loos, B; van der Velde, N; Uitterlinden, A G; de Groot, L C P G M; Franke, A; Offenbacher, S; Lieb, W; Divaris, K; Mott, R; Gat-Viks, I; Wiess, E; Schaefer, A; Iraqi, F A; Haddad, Y H

2018-05-01

Periodontitis is one of the most common inflammatory human diseases with a strong genetic component. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWASs) of chronic periodontitis (CP) have largely been unsuccessful in identifying common susceptibility factors. A combination of quantitative trait loci (QTL) mapping in mice with association studies in humans has the potential to discover novel risk loci. To this end, we assessed alveolar bone loss in response to experimental periodontal infection in 25 lines (286 mice) from the Collaborative Cross (CC) mouse population using micro-computed tomography (µCT) analysis. The orthologous human chromosomal regions of the significant QTL were analyzed for association using imputed genotype data (OmniExpress BeadChip arrays) derived from case-control samples of aggressive periodontitis (AgP; 896 cases, 7,104 controls) and chronic periodontitis (CP; 2,746 cases, 1,864 controls) of northwest European and European American descent, respectively. In the mouse genome, QTL mapping revealed 2 significant loci (-log P = 5.3; false discovery rate = 0.06) on chromosomes 1 ( Perio3) and 14 ( Perio4). The mapping resolution ranged from ~1.5 to 3 Mb. Perio3 overlaps with a previously reported QTL associated with residual bone volume in F2 cross and includes the murine gene Ccdc121. Its human orthologue showed previously a nominal significant association with CP in humans. Use of variation data from the genomes of the CC founder strains further refined the QTL and suggested 7 candidate genes ( CAPN8, DUSP23, PCDH17, SNORA17, PCDH9, LECT1, and LECT2). We found no evidence of association of these candidates with the human orthologues. In conclusion, the CC populations enabled mapping of confined QTL that confer susceptibility to alveolar bone loss in mice and larger human phenotype-genotype samples and additional expression data from gingival

Amplified fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the yellow fever mosquito Aedes aegypti.

PubMed

Zhong, Daibin; Menge, David M; Temu, Emmanuel A; Chen, Hong; Yan, Guiyun

2006-07-01

The yellow fever mosquito Aedes aegypti has been the subject of extensive genetic research due to its medical importance and the ease with which it can be manipulated in the laboratory. A molecular genetic linkage map was constructed using 148 amplified fragment length polymorphism (AFLP) and six single-strand conformation polymorphism (SSCP) markers. Eighteen AFLP primer combinations were used to genotype two reciprocal F2 segregating populations. Each primer combination generated an average of 8.2 AFLP markers eligible for linkage mapping. The length of the integrated map was 180.9 cM, giving an average marker resolution of 1.2 cM. Composite interval mapping revealed a total of six QTL significantly affecting Plasmodium susceptibility in the two reciprocal crosses of Ae. aegypti. Two common QTL on linkage group 2 were identified in both crosses that had similar effects on the phenotype, and four QTL were unique to each cross. In one cross, the four main QTL accounted for 64% of the total phenotypic variance, and digenic epistasis explained 11.8% of the variance. In the second cross, the four main QTL explained 66% of the variance, and digenic epistasis accounted for 16% of the variance. The actions of these QTL were either dominance or underdominance. Our results indicated that at least three new QTL were mapped on chromosomes 1 and 3. The polygenic nature of susceptibility to P. gallinaceum and epistasis are important factors for significant variation within or among mosquito strains. The new map provides additional information useful for further genetic investigation, such as identification of new genes and positional cloning.

Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

Progress in national-scale landslide susceptibility mapping in Romania using a combined statistical-heuristical approach

NASA Astrophysics Data System (ADS)

Bălteanu, Dan; Micu, Mihai; Malet, Jean-Philippe; Jurchescu, Marta; Sima, Mihaela; Kucsicsa, Gheorghe; Dumitrică, Cristina; Petrea, Dănuţ; Mărgărint, Ciprian; Bilaşco, Ştefan; Văcăreanu, Radu; Georgescu, Sever; Senzaconi, Francisc

2017-04-01

Landslide processes represent a very widespread geohazard in Romania, affecting mainly the hilly and plateau regions as well as the mountain sectors developed on flysch formations. Two main projects provided the framework for improving the existing national landslide susceptibility map (Bălteanu et al. 2010): the ELSUS (Pan-European and nation-wide landslide susceptibility assessment, EC-CERG) and the RO-RISK (Disaster Risk Evaluation at National Level, ESF-POCA) projects. The latter one, a flagship project aiming at strengthening risk prevention and management in Romania, focused on a national-level evaluation of the main risks in the country including landslides. The strategy for modeling landslide susceptibility was designed based on the experience gained from continental and national level assessments conducted in the frame of the International Programme on Landslides (IPL) project IPL-162, the European Landslides Expert Group - JRC and the ELSUS project. The newly proposed landslide susceptibility model used as input a reduced set of landslide conditioning factor maps available at scales of 1:100,000 - 1:200,000 and consisting of lithology, slope angle and land cover. The input data was further differentiated for specific natural environments, defined here as morpho-structural units in order to incorporate differences induced by elevation (vertical climatic zonation), morpho-structure as well as neotectonic features. In order to best discern the specific landslide conditioning elements, the analysis has been carried out for one single process category, namely slides. The existence of a landslide inventory covering the whole country's territory ( 30,000 records, Micu et al. 2014), although affected by incompleteness and lack of homogeneity, allowed for the application of a semi-quantitative, mixed statistical-heuristical approach having the advantage of combining the objectivity of statistics with expert-knowledge in calibrating class and factor weights. The

An innovative tool for landslide susceptibility mapping in Kyrgyzstan, Central Asia

NASA Astrophysics Data System (ADS)

Saponaro, Annamaria; Pilz, Marco; Wieland, Marc; Bindi, Dino; Parolai, Stefano

2013-04-01

Kyrgyzstan is among the most exposed countries in the world to landslide susceptibility. The high seismicity of the area, the presence of high mountain ridges and topographic relieves, the geology of the local materials and the occurrence of heavy precipitations represent the main factors responsible for slope failures. In particular, the large variability of material properties and slope conditions as well as the difficulties in forecasting heavy precipitations locally and in quantifying the level of ground shaking call for harmonized procedures for reducing the negative impact of these factors. Several studies have recently been carried out aiming at preparing landslide susceptibility and hazard maps; however, some of them - qualitative-based - suffer from the application of subjective decision rules from experts in the classification of parameters that influence the occurrence of a landslide. On the other hand, statistical methods provide objectivity over qualitative ones since they allow a numerical evaluation of landslide spatial distribution with landslide potential factors. For this reason, we will make use of a bivariate technique known as Weight-Of-Evidence method to evaluate the influence of landslide predictive factors. The aim of this study is to identify areas in Kyrgyzstan being more prone to earthquake-triggered landslides. An innovative approach which exploits the new advances of GIS technology together with statistical concepts is presented. A range of conditioning factors and their potential impact on landslide activation is quantitatively assessed on the basis of landslide spatial distribution and seismic zonation. Results show areas which are more susceptible to landslides induced by earthquakes. Our approach can be used to fill the gap of subjectivity that typically affects already performed qualitative analysis. The resulting landslide susceptibility map represents a potentially supportive tool for disaster management and planning activities

Spatially explicit shallow landslide susceptibility mapping over large areas

USGS Publications Warehouse

Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

Mapping Magnetic Susceptibility Anisotropies of White Matter in vivo in the Human Brain at 7 Tesla

PubMed Central

Li, Xu; Vikram, Deepti S; Lim, Issel Anne L; Jones, Craig K; Farrell, Jonathan A.D.; van Zijl, Peter C. M.

2012-01-01

High-resolution magnetic resonance phase- or frequency- shift images acquired at high field show contrast related to magnetic susceptibility differences between tissues. Such contrast varies with the orientation of the organ in the field, but the development of quantitative susceptibility mapping (QSM) has made it possible to reproducibly image the intrinsic tissue susceptibility contrast. However, recent studies indicate that magnetic susceptibility is anisotropic in brain white matter and, as such, needs to be described by a symmetric second-rank tensor (χ¯¯). To fully determine the elements of this tensor, it would be necessary to acquire frequency data at six or more orientations. Assuming cylindrical symmetry of the susceptibility tensor in myelinated white matter fibers, we propose a simplified method to reconstruct the susceptibility tensor in terms of a mean magnetic susceptibility, MMS = (χ∥ + 2χ⊥)/3 and a magnetic susceptibility anisotropy, MSA = χ∥ − χ⊥, where χ∥ and χ⊥ are susceptibility parallel and perpendicular to the white matter fiber direction, respectively. Computer simulations show that with a practical head rotation angle of around 20°–30°, four head orientations suffice to reproducibly reconstruct the tensor with good accuracy. We tested this approach on whole brain 1×1×1 mm3 frequency data acquired from five healthy subjects at 7 T. The frequency information from phase images collected at four head orientations was combined with the fiber direction information extracted from diffusion tensor imaging (DTI) to map the white matter susceptibility tensor. The MMS and MSA were quantified for regions in several large white matter fiber structures, including the corona radiata, posterior thalamic radiation and corpus callosum. MMS ranged from −0.037 to −0.053 ppm (referenced to CSF being about zero). MSA values could be quantified without the need for a reference and ranged between 0.004 and 0.029 ppm, in line with

Susceptibility Tensor Imaging (STI) of the Brain

PubMed Central

Li, Wei; Liu, Chunlei; Duong, Timothy Q.; van Zijl, Peter C.M.; Li, Xu

2016-01-01

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping (QSM) to remove such dependence. Similar to diffusion tensor imaging (DTI), STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of susceptibility anisotropy in brain white matter is myelin. Another unique feature of susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. PMID:27120169

Accuracy of MRI-based Magnetic Susceptibility Measurements

NASA Astrophysics Data System (ADS)

Russek, Stephen; Erdevig, Hannah; Keenan, Kathryn; Stupic, Karl

Magnetic Resonance Imaging (MRI) is increasingly used to map tissue susceptibility to identify microbleeds associated with brain injury and pathologic iron deposits associated with neurologic diseases such as Parkinson's and Alzheimer's disease. Field distortions with a resolution of a few parts per billion can be measured using MRI phase maps. The field distortion map can be inverted to obtain a quantitative susceptibility map. To determine the accuracy of MRI-based susceptibility measurements, a set of phantoms with paramagnetic salts and nano-iron gels were fabricated. The shapes and orientations of features were varied. Measured susceptibility of 1.0 mM GdCl3 solution in water as a function of temperature agreed well with the theoretical predictions, assuming Gd+3 is spin 7/2. The MRI susceptibility measurements were compared with SQUID magnetometry. The paramagnetic susceptibility sits on top of the much larger diamagnetic susceptibility of water (-9.04 x 10-6), which leads to errors in the SQUID measurements. To extract out the paramagnetic contribution using standard magnetometry, measurements must be made down to low temperature (2K). MRI-based susceptometry is shown to be as or more accurate than standard magnetometry and susceptometry techniques.

Mapcurves: a quantitative method for comparing categorical maps.

Treesearch

William W. Hargrove; M. Hoffman Forrest; Paul F. Hessburg

2006-01-01

We present Mapcurves, a quantitative goodness-of-fit (GOF) method that unambiguously shows the degree of spatial concordance between two or more categorical maps. Mapcurves graphically and quantitatively evaluate the degree of fit among any number of maps and quantify a GOF for each polygon, as well as the entire map. The Mapcurve method indicates a perfect fit even if...

Landslide Inventory and Susceptibility Mapping in Tropical Areas - Southern Mexico

NASA Astrophysics Data System (ADS)

Gaidzik, K.; Ramirez-Herrera, M. T.; Regmi, N. R.; Leshchinsky, B. A.

2016-12-01

Landslides are one of the common catastrophic phenomena in the world. In regions of humid-warm tropical climate they are triggered by extreme storms causing loss of life and economic devastation. In this study we mapped susceptibility to landslides in the tropical mountains of Guerrero (South Mexico) based on the inventory of landslide features triggered by the hurricane Manuel of September 2013. Landslide inventory was produced using interpretation of satellite images and automatic identification of landslides employing the Contour Connection Method (CCM). A map of susceptibility to landslides was developed by computing probability of landslide occurrence from statistical relationships of existing landslides using LiDAR elevation model and derived landslide-causing factors using a logistic regression method. Landslide inventory includes 419 features produced by the hurricane Manuel on the area of 22 km2, and > 1,000 older features, suggesting high landslide activity in this area. Most landslides in the region are small, but some large slides exist, such as the catastrophic landslide in La Pintada that caused 71 fatalities and destroyed a large part of the village. Our results indicate that the distance to streams, human activity, presence or absence of dense vegetation and orientation of slopes (on some areas) strongly influence the spatial distribution of landslides. Results showed high susceptibility zones encompass 30% of the study area and occur mostly along topographic convergence. Applied approach identified most of the landslides within the high susceptibility zone and suggested that it is a valid applicable method to map areas susceptible to landslides in southern Mexico but also on other humid-warm tropical regions.

Effects of tissue susceptibility on brain temperature mapping.

PubMed

Maudsley, Andrew A; Goryawala, Mohammed Z; Sheriff, Sulaiman

2017-02-01

A method for mapping of temperature over a large volume of the brain using volumetric proton MR spectroscopic imaging has been implemented and applied to 150 normal subjects. Magnetic susceptibility-induced frequency shifts in gray- and white-matter regions were measured and included as a correction in the temperature mapping calculation. Additional sources of magnetic susceptibility variations of the individual metabolite resonance frequencies were also observed that reflect the cellular-level organization of the brain metabolites, with the most notable differences being attributed to changes of the N-Acetylaspartate resonance frequency that reflect the intra-axonal distribution and orientation of the white-matter tracts with respect to the applied magnetic field. These metabolite-specific susceptibility effects are also shown to change with age. Results indicate no change of apparent brain temperature with age from 18 to 84 years old, with a trend for increased brain temperature throughout the cerebrum in females relative for males on the order of 0.1°C; slightly increased temperatures in the left hemisphere relative to the right; and a lower temperature of 0.3°C in the cerebellum relative to that of cerebral white-matter. This study presents a novel acquisition method for noninvasive measurement of brain temperature that is of potential value for diagnostic purposes and treatment monitoring, while also demonstrating limitations of the measurement due to the confounding effects of tissue susceptibility variations. Copyright © 2016 Elsevier Inc. All rights reserved.

Landslide susceptibility mapping using a bivariate statistical model in a tropical hilly area of southeastern Brazil

NASA Astrophysics Data System (ADS)

Araújo, J. P. C.; DA Silva, L. M.; Dourado, F. A. D.; Fernandes, N.

2015-12-01

Landslides are the most damaging natural hazard in the mountainous region of Rio de Janeiro State in Brazil, responsible for thousands of deaths and important financial and environmental losses. However, this region has currently few landslide susceptibility maps implemented on an adequate scale. Identification of landslide susceptibility areas is fundamental in successful land use planning and management practices to reduce risk. This paper applied the Bayes' theorem based on weight of evidence (WoE) using 8 landslide-related factors in a geographic information system (GIS) for landslide susceptibility mapping. 378 landslide locations were identified and mapped on a selected basin in the city of Nova Friburgo, triggered by the January 2011 rainfall event. The landslide scars were divided into two subsets: training and validation subsets. The 8 landslide-related factors weighted by WoE were performed using chi-square test to indicate which variables are conditionally independent of each other to be used in the final map. Finally, the maps of weighted factors were summed up to construct the landslide susceptibility map and validated by the validation landslide subset. According to the results, slope, aspect and contribution area showed the higher positive spatial correlation with landslides. In the landslide susceptibility map, 21% of the area presented very low and low susceptibilities with 3% of the validation scars, 41% presented medium susceptibility with 22% of the validation scars and 38% presented high and very high susceptibilities with 75% of the validation scars. The very high susceptibility class stands for 16% of the basin area and has 54% of the all scars. The approach used in this study can be considered very useful since 75% of the area affected by landslides was included in the high and very high susceptibility classes.

Comparing two models for post-wildfire debris flow susceptibility mapping

NASA Astrophysics Data System (ADS)

Cramer, J.; Bursik, M. I.; Legorreta Paulin, G.

2017-12-01

Traditionally, probabilistic post-fire debris flow susceptibility mapping has been performed based on the typical method of failure for debris flows/landslides, where slip occurs along a basal shear zone as a result of rainfall infiltration. Recent studies have argued that post-fire debris flows are fundamentally different in their method of initiation, which is not infiltration-driven, but surface runoff-driven. We test these competing models by comparing the accuracy of the susceptibility maps produced by each initiation method. Debris flow susceptibility maps are generated according to each initiation method for a mountainous region of Southern California that recently experienced wildfire and subsequent debris flows. A multiple logistic regression (MLR), which uses the occurrence of past debris flows and the values of environmental parameters, was used to determine the probability of future debris flow occurrence. The independent variables used in the MLR are dependent on the initiation method; for example, depth to slip plane, and shear strength of soil are relevant to the infiltration initiation, but not surface runoff. A post-fire debris flow inventory serves as the standard to compare the two susceptibility maps, and was generated by LiDAR analysis and field based ground-truthing. The amount of overlap between the true locations where debris flow erosion can be documented, and where the MLR predicts high probability of debris flow initiation was statistically quantified. The Figure of Merit in Space (FMS) was used to compare the two models, and the results of the FMS comparison suggest that surface runoff-driven initiation better explains debris flow occurrence. Wildfire can breed conditions that induce debris flows in areas that normally would not be prone to them. Because of this, nearby communities at risk may not be equipped to protect themselves against debris flows. In California, there are just a few months between wildland fire season and the wet

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes

DTIC Science & Technology

2013-03-14

SUPPLEMENTARY NOTES 14. ABSTRACT Autism is an extremely common and heterogeneous neurodevelopmental disorder. While genetic factors are known to play...AFRL-SA-WP-TR-2013-0013 Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes...Genetic Mapping for the Discovery of Autism Susceptibility Genes 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER N/A 6

Non-Motor Symptom Burdens Are Not Associated with Iron Accumulation in Early Parkinson's Disease: a Quantitative Susceptibility Mapping Study.

PubMed

Shin, Chaewon; Lee, Seon; Lee, Jee Young; Rhim, Jung Hyo; Park, Sun Won

2018-03-26

Quantitative susceptibility mapping (QSM) has been used to measure iron accumulation in the deep nuclei of patients with Parkinson's disease (PD). This study examined the relationship between non-motor symptoms (NMSs) and iron accumulation in the deep nuclei of patients with PD. The QSM data were acquired from 3-Tesla magnetic resonance imaging (MRI) in 29 patients with early PD and 19 normal controls. The Korean version of the NMS scale (K-NMSS) was used for evaluation of NMSs in patients. The patients were divided into high NMS and low NMS groups. The region-of-interest analyses were performed in the following deep nuclei: red nucleus, substantia nigra pars compacta, substantia nigra pars reticulata, dentate nucleus, globus pallidus, putamen, and head of the caudate nucleus. Thirteen patients had high NMS scores (total K-NMSS score, mean = 32.1), and 16 had low NMS scores (10.6). The QSM values in the deep were not different among the patients with high NMS scores, low NMS scores, and controls. The QSM values were not correlated linearly with K-NMSS total score after adjusting the age at acquisition of brain MRI. The study demonstrated that the NMS burdens are not associated with iron accumulation in the deep nuclei of patients with PD. These results suggest that future neuroimaging studies on the pathology of NMSs in PD should use more specific and detailed clinical tools and recruit PD patients with severe NMSs. © 2018 The Korean Academy of Medical Sciences.

Quantitative comparison between a multiecho sequence and a single-echo sequence for susceptibility-weighted phase imaging.

PubMed

Gilbert, Guillaume; Savard, Geneviève; Bard, Céline; Beaudoin, Gilles

2012-06-01

The aim of this study was to investigate the benefits arising from the use of a multiecho sequence for susceptibility-weighted phase imaging using a quantitative comparison with a standard single-echo acquisition. Four healthy adult volunteers were imaged on a clinical 3-T system using a protocol comprising two different three-dimensional susceptibility-weighted gradient-echo sequences: a standard single-echo sequence and a multiecho sequence. Both sequences were repeated twice in order to evaluate the local noise contribution by a subtraction of the two acquisitions. For the multiecho sequence, the phase information from each echo was independently unwrapped, and the background field contribution was removed using either homodyne filtering or the projection onto dipole fields method. The phase information from all echoes was then combined using a weighted linear regression. R2 maps were also calculated from the multiecho acquisitions. The noise standard deviation in the reconstructed phase images was evaluated for six manually segmented regions of interest (frontal white matter, posterior white matter, globus pallidus, putamen, caudate nucleus and lateral ventricle). The use of the multiecho sequence for susceptibility-weighted phase imaging led to a reduction of the noise standard deviation for all subjects and all regions of interest investigated in comparison to the reference single-echo acquisition. On average, the noise reduction ranged from 18.4% for the globus pallidus to 47.9% for the lateral ventricle. In addition, the amount of noise reduction was found to be strongly inversely correlated to the estimated R2 value (R=-0.92). In conclusion, the use of a multiecho sequence is an effective way to decrease the noise contribution in susceptibility-weighted phase images, while preserving both contrast and acquisition time. The proposed approach additionally permits the calculation of R2 maps. Copyright © 2012 Elsevier Inc. All rights reserved.

Weights of Evidence Method for Landslide Susceptibility Mapping in Takengon, Central Aceh, Indonesia

NASA Astrophysics Data System (ADS)

Pamela; Sadisun, Imam A.; Arifianti, Yukni

2018-02-01

Takengon is an area prone to earthquake disaster and landslide. On July 2, 2013, Central Aceh earthquake induced large numbers of landslides in Takengon area, which resulted in casualties of 39 people. This location was chosen to assess the landslide susceptibility of Takengon, using a statistical method, referred to as the weight of evidence (WoE). This WoE model was applied to indicate the main factors influencing the landslide susceptible area and to derive landslide susceptibility map of Takengon. The 251 landslides randomly divided into two groups of modeling/training data (70%) and validation/test data sets (30%). Twelve thematic maps of evidence are slope degree, slope aspect, lithology, land cover, elevation, rainfall, lineament, peak ground acceleration, curvature, flow direction, distance to river and roads used as landslide causative factors. According to the AUC, the significant factor controlling the landslide is the slope, the slope aspect, peak ground acceleration, elevation, lithology, flow direction, lineament, and rainfall respectively. Analytical result verified by using test data of landslide shows AUC prediction rate is 0.819 and AUC success rate with all landslide data included is 0.879. This result showed the selective factors and WoE method as good models for assessing landslide susceptibility. The landslide susceptibility map of Takengon shows the probabilities, which represent relative degrees of susceptibility for landslide proneness in Takengon area.

Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand

NASA Astrophysics Data System (ADS)

Oh, Hyun-Joo; Lee, Saro; Chotikasathien, Wisut; Kim, Chang Hwan; Kwon, Ju Hyoung

2009-04-01

For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence, such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42% in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover.

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

Quantitative Susceptibility Mapping as a Possible Tool to Radiographically Diagnose Sentinel Headache Associated with Intracranial Aneurysm: Case Report.

PubMed

Nakagawa, Daichi; Cushing, Cameron; Nagahama, Yasunori; Allan, Lauren; Hasan, David

2017-07-01

Sentinel headache (SH) occurs before aneurysm rupture in an estimated 15%-60% of cases of aneurysmal subarachnoid hemorrhage (aSAH). By definition, noncontrast computed tomography (CT) scan of the brain and lumbar puncture are both negative in patients presenting with SH. One of the theories explaining this phenomenon is that microhemorrhage (MH) from the aneurysm wall contribute to iron deposition in the interface between the aneurysm wall and brain parenchyma. Quantitative susceptibility mapping (QSM) is a recently introduced magnetic resonance imaging (MRI) technique that has proven capable of localizing the deposition of paramagnetic metals, particularly ferric iron. Thus, the QSM sequence may be able to detect iron deposition secondary to MH. A 76-year-old male presented with the "worst headache of my life." Noncontrast head CT scan and lumbar puncture were negative. Magnetic resonance angiography (MRA) of the brain revealed an anterior communicating artery (A-com) aneurysm measuring 7 mm with a large bleb. T1-weighted imaging (WI), T2-WI, MRA, T2 star-weighted angiography (SWAN), and QSM sequences were obtained. T2-WI, SWAN, and QSM revealed isointense, hypointense, and hyperintense signals, respectively, at the interface of the aneurysm wall and brain tissue. These findings were consistent with deposition of ferric iron at this interface. The A-com aneurysm was treated with coil embolization, and the patient exhibited no postoperative deficits. The MRI QSM sequence can localize iron deposition resulting from MH within an aneurysmal wall. This sequence may be a promising imaging tool for screening patients presenting with SH. Copyright © 2017 Elsevier Inc. All rights reserved.

GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

NASA Astrophysics Data System (ADS)

Mancini, F.; Ceppi, C.; Ritrovato, G.

2010-09-01

This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

Mass Movement Susceptibility Mapping Using Satellite Optical Imagery Compared With INSAR Monitoring: Zigui County, Three Gorges Region, China

NASA Astrophysics Data System (ADS)

Kincal, Cem; Singleton, Andrew; Liu, Peng; Li, Zhenhong; Drummond, Jane; Hoey, Trevor; Muller, Jan-Peter; Qu, Wei; Zeng, Qiming; Zhang, Jingfa; Du, Peijun

2010-10-01

Mass movements on steep slopes are a major hazard to communities and infrastructure in the Three Gorges region, China. Developing susceptibility maps of mass movements is therefore very important in both current and future land use planning. This study employed satellite optical imagery and an ASTER GDEM (15 m) to derive various parameters (namely geology; slope gradient; proximity to drainage networks and proximity to lineaments) in order to create a GIS-based map of mass movement susceptibility. This map was then evaluated using highly accurate deformation signals processed using the Persistent Scatterer (PS) InSAR technique. Areas of high susceptibility correspond well to points of high subsidence, which provides a strong support of our susceptibility map.

Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

NASA Astrophysics Data System (ADS)

Kumar, Deepak; Thakur, Manoj; Dubey, Chandra S.; Shukla, Dericks P.

2017-10-01

In recent years, various machine learning techniques have been applied for landslide susceptibility mapping. In this study, three different variants of support vector machine viz., SVM, Proximal Support Vector Machine (PSVM) and L2-Support Vector Machine - Modified Finite Newton (L2-SVM-MFN) have been applied on the Mandakini River Basin in Uttarakhand, India to carry out the landslide susceptibility mapping. Eight thematic layers such as elevation, slope, aspect, drainages, geology/lithology, buffer of thrusts/faults, buffer of streams and soil along with the past landslide data were mapped in GIS environment and used for landslide susceptibility mapping in MATLAB. The study area covering 1625 km2 has merely 0.11% of area under landslides. There are 2009 pixels for past landslides out of which 50% (1000) landslides were considered as training set while remaining 50% as testing set. The performance of these techniques has been evaluated and the computational results show that L2-SVM-MFN obtains higher prediction values (0.829) of receiver operating characteristic curve (AUC-area under the curve) as compared to 0.807 for PSVM model and 0.79 for SVM. The results obtained from L2-SVM-MFN model are found to be superior than other SVM prediction models and suggest the usefulness of this technique to problem of landslide susceptibility mapping where training data is very less. However, these techniques can be used for satisfactory determination of susceptible zones with these inputs.

Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area

NASA Astrophysics Data System (ADS)

Oh, Hyun-Joo; Pradhan, Biswajeet

2011-09-01

This paper presents landslide-susceptibility mapping using an adaptive neuro-fuzzy inference system (ANFIS) using a geographic information system (GIS) environment. In the first stage, landslide locations from the study area were identified by interpreting aerial photographs and supported by an extensive field survey. In the second stage, landslide-related conditioning factors such as altitude, slope angle, plan curvature, distance to drainage, distance to road, soil texture and stream power index (SPI) were extracted from the topographic and soil maps. Then, landslide-susceptible areas were analyzed by the ANFIS approach and mapped using landslide-conditioning factors. In particular, various membership functions (MFs) were applied for the landslide-susceptibility mapping and their results were compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curve for all landslide susceptibility maps were drawn and the areas under curve values were calculated. The ROC curve technique is based on the plotting of model sensitivity — true positive fraction values calculated for different threshold values, versus model specificity — true negative fraction values, on a graph. Landslide test locations that were not used during the ANFIS modeling purpose were used to validate the landslide susceptibility maps. The validation results revealed that the susceptibility maps constructed by the ANFIS predictive models using triangular, trapezoidal, generalized bell and polynomial MFs produced reasonable results (84.39%), which can be used for preliminary land-use planning. Finally, the authors concluded that ANFIS is a very useful and an effective tool in regional landslide susceptibility assessment.

Semi Quantitative MALDI TOF for Antimicrobial Susceptibility Testing in Staphylococcus aureus

DTIC Science & Technology

2017-08-31

Semi- quantitative MALDI-TOF for antimicrobial susceptibility testing in Staphylococcus 1 aureus 2 3 4 Tucker Maxson,a Cheryl L. Taylor-Howell,a...Timothy D. Minoguea# 5 6 Diagnostic Systems Division, United States Army Medical Research Institute of Infectious 7 Disease, Fort Detrick, MD...USAa 8 9 Running Title: Quantitative MALDI for AST in S. aureus 10 #Address correspondence to Timothy D. Minogue, timothy.d.minogue.civ@mail.mil

Mapping quantitative trait loci for traits defined as ratios.

PubMed

Yang, Runqing; Li, Jiahan; Xu, Shizhong

2008-03-01

Many traits are defined as ratios of two quantitative traits. Methods of QTL mapping for regular quantitative traits are not optimal when applied to ratios due to lack of normality for traits defined as ratios. We develop a new method of QTL mapping for traits defined as ratios. The new method uses a special linear combination of the two component traits, and thus takes advantage of the normal property of the new variable. Simulation study shows that the new method can substantially increase the statistical power of QTL detection relative to the method which treats ratios as regular quantitative traits. The new method also outperforms the method that uses Box-Cox transformed ratio as the phenotype. A real example of QTL mapping for relative growth rate in soybean demonstrates that the new method can detect more QTL than existing methods of QTL mapping for traits defined as ratios.

The landslide susceptibility mapping and assessment with ZY satellite data

NASA Astrophysics Data System (ADS)

Zhang, R.; Zhang, Z.; Zhao, Y.

2012-12-01

Natural hazards can result in enormous property damage and casualties in mountainous regions. In China, the direct loss of hazards is about 400 million yuan in 2011. Especially the landslide, the most common natural hazards, got the wide attention of each country. Landslide susceptibility mapping is of great importance for landslide hazard mitigation efforts throughout the world. In Southwest Hubei, there are much mineral mining activities, which may trigger the landslide. In addition the Three Gorges reservoir is located in this area, and the storage changed the geological and hydrological environment, which may increase the frequency of the ancient landslide reactivation, and the new landslide occurrence. There are more than 200 landslide hazards happened since 2003. So producing a regional-scaled landslide susceptibility map is necessary. For the above purpose, the landslide susceptibility mapping was produced by using the ZY-3 and ZY-1-02C satellite data, the DEMs and the conventional topographic data.(1) The DEM derivatives slope gradient, the slope aspect and the topographic wetness index (TWI) ; (2) in order to acquire the spatially continuous vegetation information, Normalized Difference Vegetation Index (NDVI) was computed using ZY-1-02C and ZY-3; (3) the regional lithologic information (i.e. mineral distribution) and the tectonic information obtained from remote sensing data in combination with regional geological survey; (4) the regional hydrogeological information was produced by using the remote sensing data in combination with the DEMs; (5) the existed landslides information obtained from remote sensing. To model the landslide hazard assessment using variety of statistic methods and evaluation methods, the cross application model yields reasonable results which can be applied for preliminary landslide hazard mapping and the hazard grade division.

Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

Mapping Quantitative Field Resistance Against Apple Scab in a 'Fiesta' x 'Discovery' Progeny.

PubMed

Liebhard, R; Koller, B; Patocchi, A; Kellerhals, M; Pfammatter, W; Jermini, M; Gessler, C

2003-04-01

ABSTRACT Breeding of resistant apple cultivars (Malus x domestica) as a disease management strategy relies on the knowledge and understanding of the underlying genetics. The availability of molecular markers and genetic linkage maps enables the detection and the analysis of major resistance genes as well as of quantitative trait loci (QTL) contributing to the resistance of a genotype. Such a genetic linkage map was constructed, based on a segregating population of the cross between apple cvs. Fiesta (syn. Red Pippin) and Discovery. The progeny was observed for 3 years at three different sites in Switzerland and field resistance against apple scab (Venturia inaequalis) was assessed. Only a weak correlation was detected between leaf scab and fruit scab. A QTL analysis was performed, based on the genetic linkage map consisting of 804 molecular markers and covering all 17 chromosomes of apple. With the maximum likelihood-based interval mapping method, eight genomic regions were identified, six conferring resistance against leaf scab and two conferring fruit scab resistance. Although cv. Discovery showed a much stronger resistance against scab in the field, most QTL identified were attributed to the more susceptible parent 'Fiesta'. This indicated a high degree of homozygosity at the scab resistance loci in 'Discovery', preventing their detection in the progeny due to the lack of segregation.

A comparative quantitative analysis of magnetic susceptibility artifacts in echo planar and PROPELLER diffusion-weighted images

NASA Astrophysics Data System (ADS)

Cho, Jae-Hwan; Lee, Hae-Kag; Yang, Han-Joon; Lee, Gui-Won; Park, Yong-Soon; Chung, Woon-Kwan

2013-01-01

In this study, the authors investigated whether periodically-rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) diffusion-weighted imaging (DWI) can remove magnetic susceptibility artifacts and compared apparent diffusion coefficient (ADC) values for PROPELLER DWI and the common echo planar (EP) DWI. Twenty patients that underwent brain MRI with a metal dental implant were selected. A 3.0T MR scanner was then used to obtain EP DWI, PROPELLER DWI, and corresponding apparent diffusion coefficient (ADC) maps for a b-value of 0 and 1,000 s/mm2. The frequencies of magnetic susceptibility artifacts in four parts of the brain (bilateral temporal lobes, pons, and orbit) were selected. In the ADC maps, we measured the ADC values of both sides of the temporal lobe and the pons. According to the study results, the frequency of magnetic susceptibility artifacts in PROPELLER DW images was lower than it was in EP DW images. In ADC maps, the ADC values of the bilateral temporal lobes and the pons were all higher in PROPELLER ADC maps than in EP ADC maps. Our findings show that when a high-field MRI machine is used, magnetic susceptibility artifacts can distort anatomical structures and produce high-intensity signals. Furthermore, our findings suggest that in many cases, PROPELLER DWI would be helpful in terms of achieving a correct diagnosis.

Evaluating and comparing methods of sinkhole susceptibility mapping in the Ebro Valley evaporite karst (NE Spain)

NASA Astrophysics Data System (ADS)

Galve, J. P.; Gutiérrez, F.; Remondo, J.; Bonachea, J.; Lucha, P.; Cendrero, A.

2009-10-01

Multiple sinkhole susceptibility models have been generated in three study areas of the Ebro Valley evaporite karst (NE Spain) applying different methods (nearest neighbour distance, sinkhole density, heuristic scoring system and probabilistic analysis) for each sinkhole type separately (cover collapse sinkholes, cover and bedrock collapse sinkholes and cover and bedrock sagging sinkholes). The quantitative and independent evaluation of the predictive capability of the models reveals that: (1) The most reliable susceptibility models are those derived from the nearest neighbour distance and sinkhole density. These models can be generated in a simple and rapid way from detailed geomorphological maps. (2) The reliability of the nearest neighbour distance and density models is conditioned by the degree of clustering of the sinkholes. Consequently, the karst areas in which sinkholes show a higher clustering are a priori more favourable for predicting new occurrences. (3) The predictive capability of the best models obtained in this research is significantly higher (12.5-82.5%) than that of the heuristic sinkhole susceptibility model incorporated into the General Urban Plan for the municipality of Zaragoza. Although the probabilistic approach provides lower quality results than the methods based on sinkhole proximity and density, it helps to identify the most significant factors and select the most effective mitigation strategies and may be applied to model susceptibility in different future scenarios.

Debris flows susceptibility mapping under tropical rain conditions in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Nsengiyumva, Jean-Baptiste; BUgnon, Pierre-Charles; Jaboyedoff, Michel; Derron, Marc-Henri

2017-04-01

Rwanda is a densely populated country. It means that all the space is exploited, including sometimes areas with very steep slopes. This has as for consequences that during the rainy season slopes with human activities are affected by gravitational processes, mostly debris and mud flows and shallow landslides. The events of early May 2016 (May 8 and 9), with more than 50 deaths, are an illustration of these frequents landslides and inundations. The goal of this work is to produce a susceptibility map for debris/mud flows at regional/national scale. Main available pieces of data are a national digital terrain model at 10m resolution, bedrock and soil maps, and information collected during field visits on some specific localities. The first step is the characterization of the slope angle distribution for the different types of bedrock or soils (decomposition in Gaussian populations). Then, the combination of this information with other geomorphic and hydrologic parameters is used to define potential source areas of debris flows. Finally, propagation maps of debris flows are produced using FLOW-R (Horton et al. 2013). Horton, P., Jaboyedoff, M., Rudaz, B., and Zimmermann, M.: Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale, Nat. Hazards Earth Syst. Sci., 13, 869-885, doi:10.5194/nhess-13-869-2013, 2013. The paper is in open access.

An application of adaptive neuro-fuzzy inference system to landslide susceptibility mapping (Klang valley, Malaysia)

NASA Astrophysics Data System (ADS)

Sezer, Ebru; Pradhan, Biswajeet; Gokceoglu, Candan

2010-05-01

Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. Recently, the Klang Valley area of Selangor state has faced numerous landslide and mudflow events and much damage occurred in these areas. However, only little effort has been made to assess or predict these events which resulted in serious damages. Through scientific analyses of these landslides, one can assess and predict landslide-susceptible areas and even the events as such, and thus reduce landslide damages through proper preparation and/or mitigation. For this reason , the purpose of the present paper is to produce landslide susceptibility maps of a part of the Klang Valley areas in Malaysia by employing the results of the adaptive neuro-fuzzy inference system (ANFIS) analyses. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments and NDVI were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, plan curvature, distance from drainage, soil type, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to construct the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were obtained by using ANFIS results. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 98% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient

A quantitative analysis of IRAS maps of molecular clouds

NASA Technical Reports Server (NTRS)

Wiseman, Jennifer J.; Adams, Fred C.

1994-01-01

We present an analysis of IRAS maps of five molecular clouds: Orion, Ophiuchus, Perseus, Taurus, and Lupus. For the classification and description of these astrophysical maps, we use a newly developed technique which considers all maps of a given type to be elements of a pseudometric space. For each physical characteristic of interest, this formal system assigns a distance function (a pseudometric) to the space of all maps: this procedure allows us to measure quantitatively the difference between any two maps and to order the space of all maps. We thus obtain a quantitative classification scheme for molecular clouds. In this present study we use the IRAS continuum maps at 100 and 60 micrometer(s) to produce column density (or optical depth) maps for the five molecular cloud regions given above. For this sample of clouds, we compute the 'output' functions which measure the distribution of density, the distribution of topological components, the self-gravity, and the filamentary nature of the clouds. The results of this work provide a quantitative description of the structure in these molecular cloud regions. We then order the clouds according to the overall environmental 'complexity' of these star-forming regions. Finally, we compare our results with the observed populations of young stellar objects in these clouds and discuss the possible environmental effects on the star-formation process. Our results are consistent with the recently stated conjecture that more massive stars tend to form in more 'complex' environments.

Quantifying changes in nigrosomes using quantitative susceptibility mapping and neuromelanin imaging for the diagnosis of early-stage Parkinson's disease.

PubMed

Takahashi, Hiroto; Watanabe, Yoshiyuki; Tanaka, Hisashi; Mihara, Masahito; Mochizuki, Hideki; Liu, Tian; Wang, Yi; Tomiyama, Noriyuki

2018-06-01

To quantify nigral changes with a focus on their spatial variation within the substantia nigra pars compacta (SNpc) for diagnosing early-stage Parkinson's disease (PD). The study participants were 18 patients with early-stage PD (PD group) and 18 healthy controls (HC group) who underwent quantitative susceptibility mapping (QSM) and neuromelanin imaging. The QSM and neuromelanin values in each whole SNpc containing the entire nigrosome and dorsolateral SNpc containing nigrosome 1 were calculated. The neuromelanin area was defined as the volume with a signal-to-noise ratio higher than that of the background region. The significance of intergroup differences in the QSM value and neuromelanin area in each SNpc region was tested. Logit (p) was used to estimate the probability of PD in relation to the QSM value and the neuromelanin area, and receiver operating characteristic analyses were performed for each value. In both SNpc, QSM values were significantly higher and neuromelanin areas were significantly lower in the PD group compared with the HC group (p < 0.05). The respective areas under the receiver operating characteristic curve for the two groups were 0.70/0.73 for the QSM value, 0.81/0.78 for the neuromelanin area in the whole/dorsolateral SNpc, and 0.86 for logit (p) in relation to the QSM value of the dorsolateral SNpc and the neuromelanin area of the whole SNpc. Comprehensive MRI assessment of the abnormality involving the nigrosomes can yield a high diagnostic performance for early-stage PD. Advances in knowledge: Focusing on spatial differences in nigral changes within the SNpc can increase the sensitivity of the detection of PD-related neurodegenerative changes.

Recent developments in machine learning applications in landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Lun, Na Kai; Liew, Mohd Shahir; Matori, Abdul Nasir; Zawawi, Noor Amila Wan Abdullah

2017-11-01

While the prediction of spatial distribution of potential landslide occurrences is a primary interest in landslide hazard mitigation, it remains a challenging task. To overcome the scarceness of complete, sufficiently detailed geomorphological attributes and environmental conditions, various machine-learning techniques are increasingly applied to effectively map landslide susceptibility for large regions. Nevertheless, limited review papers are devoted to this field, particularly on the various domain specific applications of machine learning techniques. Available literature often report relatively good predictive performance, however, papers discussing the limitations of each approaches are quite uncommon. The foremost aim of this paper is to narrow these gaps in literature and to review up-to-date machine learning and ensemble learning techniques applied in landslide susceptibility mapping. It provides new readers an introductory understanding on the subject matter and researchers a contemporary review of machine learning advancements alongside the future direction of these techniques in the landslide mitigation field.

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM).

PubMed

Feng, Xiang; Deistung, Andreas; Dwyer, Michael G; Hagemeier, Jesper; Polak, Paul; Lebenberg, Jessica; Frouin, Frédérique; Zivadinov, Robert; Reichenbach, Jürgen R; Schweser, Ferdinand

2017-06-01

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T 1 -weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative X-ray mapping, scatter diagrams and the generation of correction maps to obtain more information about your material

NASA Astrophysics Data System (ADS)

Wuhrer, R.; Moran, K.

2014-03-01

Quantitative X-ray mapping with silicon drift detectors and multi-EDS detector systems have become an invaluable analysis technique and one of the most useful methods of X-ray microanalysis today. The time to perform an X-ray map has reduced considerably with the ability to map minor and trace elements very accurately due to the larger detector area and higher count rate detectors. Live X-ray imaging can now be performed with a significant amount of data collected in a matter of minutes. A great deal of information can be obtained from X-ray maps. This includes; elemental relationship or scatter diagram creation, elemental ratio mapping, chemical phase mapping (CPM) and quantitative X-ray maps. In obtaining quantitative x-ray maps, we are able to easily generate atomic number (Z), absorption (A), fluorescence (F), theoretical back scatter coefficient (η), and quantitative total maps from each pixel in the image. This allows us to generate an image corresponding to each factor (for each element present). These images allow the user to predict and verify where they are likely to have problems in our images, and are especially helpful to look at possible interface artefacts. The post-processing techniques to improve the quantitation of X-ray map data and the development of post processing techniques for improved characterisation are covered in this paper.

Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

NASA Astrophysics Data System (ADS)

Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

2014-05-01

In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted

Quantitative landslide risk assessment and mapping on the basis of recent occurrences

NASA Astrophysics Data System (ADS)

Remondo, Juan; Bonachea, Jaime; Cendrero, Antonio

A quantitative procedure for mapping landslide risk is developed from considerations of hazard, vulnerability and valuation of exposed elements. The approach based on former work by the authors, is applied in the Bajo Deba area (northern Spain) where a detailed study of landslide occurrence and damage in the recent past (last 50 years) was carried out. Analyses and mapping are implemented in a Geographic Information System (GIS). The method is based on a susceptibility model developed previously from statistical relationships between past landslides and terrain parameters related to instability. Extrapolations based on past landslide behaviour were used to calculate failure frequency for the next 50 years. A detailed inventory of direct damage due to landslides during the study period was carried out and the main elements at risk in the area identified and mapped. Past direct (monetary) losses per type of element were estimated and expressed as an average 'specific loss' for events of a given magnitude (corresponding to a specified scenario). Vulnerability was assessed by comparing losses with the actual value of the elements affected and expressed as a fraction of that value (0-1). From hazard, vulnerability and monetary value, risk was computed for each element considered. Direct risk maps (€/pixel/year) were obtained and indirect losses from the disruption of economic activities due to landslides assessed. The final result is a risk map and table combining all losses per pixel for a 50-year period. Total monetary value at risk for the Bajo Deba area in the next 50 years is about 2.4 × 10 6 Euros.

Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

NASA Astrophysics Data System (ADS)

Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

2013-04-01

The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing; Wang, Rongxun; Qiao, Jianping; Qin, Cheng-Zhi; Chen, Yongbo; Liu, Jing; Du, Fei; Lin, Yang; Zhu, Tongxin

2014-06-01

This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

NASA Astrophysics Data System (ADS)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

Quantitative evaluation of phase processing approaches in susceptibility weighted imaging

NASA Astrophysics Data System (ADS)

Li, Ningzhi; Wang, Wen-Tung; Sati, Pascal; Pham, Dzung L.; Butman, John A.

2012-03-01

Susceptibility weighted imaging (SWI) takes advantage of the local variation in susceptibility between different tissues to enable highly detailed visualization of the cerebral venous system and sensitive detection of intracranial hemorrhages. Thus, it has been increasingly used in magnetic resonance imaging studies of traumatic brain injury as well as other intracranial pathologies. In SWI, magnitude information is combined with phase information to enhance the susceptibility induced image contrast. Because of global susceptibility variations across the image, the rate of phase accumulation varies widely across the image resulting in phase wrapping artifacts that interfere with the local assessment of phase variation. Homodyne filtering is a common approach to eliminate this global phase variation. However, filter size requires careful selection in order to preserve image contrast and avoid errors resulting from residual phase wraps. An alternative approach is to apply phase unwrapping prior to high pass filtering. A suitable phase unwrapping algorithm guarantees no residual phase wraps but additional computational steps are required. In this work, we quantitatively evaluate these two phase processing approaches on both simulated and real data using different filters and cutoff frequencies. Our analysis leads to an improved understanding of the relationship between phase wraps, susceptibility effects, and acquisition parameters. Although homodyne filtering approaches are faster and more straightforward, phase unwrapping approaches perform more accurately in a wider variety of acquisition scenarios.

Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihood-frequency ratio and weighted linear combination models

NASA Astrophysics Data System (ADS)

Akgun, Aykut; Dag, Serhat; Bulut, Fikri

2008-05-01

Landslides are very common natural problems in the Black Sea Region of Turkey due to the steep topography, improper use of land cover and adverse climatic conditions for landslides. In the western part of region, many studies have been carried out especially in the last decade for landslide susceptibility mapping using different evaluation methods such as deterministic approach, landslide distribution, qualitative, statistical and distribution-free analyses. The purpose of this study is to produce landslide susceptibility maps of a landslide-prone area (Findikli district, Rize) located at the eastern part of the Black Sea Region of Turkey by likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model and to compare the results obtained. For this purpose, landslide inventory map of the area were prepared for the years of 1983 and 1995 by detailed field surveys and aerial-photography studies. Slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. The differences between the susceptibility maps derived by the LRM and the WLC models are relatively minor when broad-based classifications are taken into account. However, the WLC map showed more details but the other map produced by LRM model produced weak results. The reason for this result is considered to be the fact that the majority of pixels in the LRM map have high values than the WLC-derived susceptibility map. In order to validate the two susceptibility maps, both of them were compared with the landslide inventory map. Although the landslides do not exist in the very high susceptibility class of the both maps, 79% of the landslides fall into the high and very high susceptibility zones of the WLC map while this is 49% for the LRM map. This shows that the WLC model exhibited higher performance than the LRM model.

Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Pradhan, Biswajeet; Lofman, Owe; Revhaug, Inge; Dick, Oystein B.

2012-08-01

The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps. The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

Global, quantitative and dynamic mapping of protein subcellular localization.

PubMed

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg Hh

2016-06-09

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

Fine Mapping of the Barley Chromosome 6H Net Form Net Blotch Susceptibility Locus

PubMed Central

Richards, Jonathan; Chao, Shiaoman; Friesen, Timothy; Brueggeman, Robert

2016-01-01

Net form net blotch, caused by the necrotrophic fungal pathogen Pyrenophora teres f. teres, is a destructive foliar disease of barley with the potential to cause significant yield loss in major production regions throughout the world. The complexity of the host–parasite genetic interactions in this pathosystem hinders the deployment of effective resistance in barley cultivars, warranting a deeper understanding of the interactions. Here, we report on the high-resolution mapping of the dominant susceptibility locus near the centromere of chromosome 6H in the barley cultivars Rika and Kombar, which are putatively targeted by necrotrophic effectors from P. teres f. teres isolates 6A and 15A, respectively. Utilization of progeny isolates derived from a cross of P. teres f. teres isolates 6A × 15A harboring single major virulence loci (VK1, VK2, and VR2) allowed for the Mendelization of single inverse gene-for-gene interactions in a high-resolution population consisting of 2976 Rika × Kombar recombinant gametes. Brachypodium distachyon synteny was exploited to develop and saturate the susceptibility region with markers, delimiting it to ∼0.24 cM and a partial physical map was constructed. This genetic and physical characterization further resolved the dominant susceptibility locus, designated Spt1 (susceptibility to P. teres f. teres). The high-resolution mapping and cosegregation of the Spt1.R and Spt1.K gene/s indicates tightly linked genes in repulsion or alleles possibly targeted by different necrotrophic effectors. Newly developed barley genomic resources greatly enhance the efficiency of positional cloning efforts in barley, as demonstrated by the Spt1 fine mapping and physical contig identification reported here. PMID:27172206

Quantitative use of multiincidence-angle SAR for geologic mapping

NASA Technical Reports Server (NTRS)

Farr, T. G.; Albee, A. L.; Evans, D. L.; Solomon, J. E.; Daily, M. I.; Labotka, T. C.; Smith, M. O.

1984-01-01

It is proposed that techniques be developed and used for quantitative interpretation of shuttle imaging radar-B (SIR-B) data for lithologic identification and mapping. The use of backscatter versus incidence angle signatures derived from SIR-B images is to be investigated. The use of SIR-B with other sensors for geologic mapping is also to be considered. Anticipated results are discussed in terms of geologic mapping.

Accuracy of magnetic resonance based susceptibility measurements

NASA Astrophysics Data System (ADS)

Erdevig, Hannah E.; Russek, Stephen E.; Carnicka, Slavka; Stupic, Karl F.; Keenan, Kathryn E.

2017-05-01

Magnetic Resonance Imaging (MRI) is increasingly used to map the magnetic susceptibility of tissue to identify cerebral microbleeds associated with traumatic brain injury and pathological iron deposits associated with neurodegenerative diseases such as Parkinson's and Alzheimer's disease. Accurate measurements of susceptibility are important for determining oxygen and iron content in blood vessels and brain tissue for use in noninvasive clinical diagnosis and treatment assessments. Induced magnetic fields with amplitude on the order of 100 nT, can be detected using MRI phase images. The induced field distributions can then be inverted to obtain quantitative susceptibility maps. The focus of this research was to determine the accuracy of MRI-based susceptibility measurements using simple phantom geometries and to compare the susceptibility measurements with magnetometry measurements where SI-traceable standards are available. The susceptibilities of paramagnetic salt solutions in cylindrical containers were measured as a function of orientation relative to the static MRI field. The observed induced fields as a function of orientation of the cylinder were in good agreement with simple models. The MRI susceptibility measurements were compared with SQUID magnetometry using NIST-traceable standards. MRI can accurately measure relative magnetic susceptibilities while SQUID magnetometry measures absolute magnetic susceptibility. Given the accuracy of moment measurements of tissue mimicking samples, and the need to look at small differences in tissue properties, the use of existing NIST standard reference materials to calibrate MRI reference structures is problematic and better reference materials are required.

Global, quantitative and dynamic mapping of protein subcellular localization

PubMed Central

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg HH

2016-01-01

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology. DOI: http://dx.doi.org/10.7554/eLife.16950.001 PMID:27278775

Assessment of Groundwater Susceptibility to Non-Point Source Contaminants Using Three-Dimensional Transient Indexes.

PubMed

Zhang, Yong; Weissmann, Gary S; Fogg, Graham E; Lu, Bingqing; Sun, HongGuang; Zheng, Chunmiao

2018-06-05

Groundwater susceptibility to non-point source contamination is typically quantified by stable indexes, while groundwater quality evolution (or deterioration globally) can be a long-term process that may last for decades and exhibit strong temporal variations. This study proposes a three-dimensional (3- d ), transient index map built upon physical models to characterize the complete temporal evolution of deep aquifer susceptibility. For illustration purposes, the previous travel time probability density (BTTPD) approach is extended to assess the 3- d deep groundwater susceptibility to non-point source contamination within a sequence stratigraphic framework observed in the Kings River fluvial fan (KRFF) aquifer. The BTTPD, which represents complete age distributions underlying a single groundwater sample in a regional-scale aquifer, is used as a quantitative, transient measure of aquifer susceptibility. The resultant 3- d imaging of susceptibility using the simulated BTTPDs in KRFF reveals the strong influence of regional-scale heterogeneity on susceptibility. The regional-scale incised-valley fill deposits increase the susceptibility of aquifers by enhancing rapid downward solute movement and displaying relatively narrow and young age distributions. In contrast, the regional-scale sequence-boundary paleosols within the open-fan deposits "protect" deep aquifers by slowing downward solute movement and displaying a relatively broad and old age distribution. Further comparison of the simulated susceptibility index maps to known contaminant distributions shows that these maps are generally consistent with the high concentration and quick evolution of 1,2-dibromo-3-chloropropane (DBCP) in groundwater around the incised-valley fill since the 1970s'. This application demonstrates that the BTTPDs can be used as quantitative and transient measures of deep aquifer susceptibility to non-point source contamination.

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Soil magnetic susceptibility: A quantitative proxy of soil drainage for use in ecological restoration

USGS Publications Warehouse

Grimley, D.A.; Wang, J.-S.; Liebert, D.A.; Dawson, J.O.

2008-01-01

Flooded, saturated, or poorly drained soils are commonly anaerobic, leading to microbially induced magnetite/maghemite dissolution and decreased soil magnetic susceptibility (MS). Thus, MS is considerably higher in well-drained soils (MS typically 40-80 ?? 10-5 standard international [SI]) compared to poorly drained soils (MS typically 10-25 ?? 10-5 SI) in Illinois, other soil-forming factors being equal. Following calibration to standard soil probings, MS values can be used to rapidly and precisely delineate hydric from nonhydric soils in areas with relatively uniform parent material. Furthermore, soil MS has a moderate to strong association with individual tree species' distribution across soil moisture regimes, correlating inversely with independently reported rankings of a tree species' flood tolerance. Soil MS mapping can thus provide a simple, rapid, and quantitative means for precisely guiding reforestation with respect to plant species' adaptations to soil drainage classes. For instance, in native woodlands of east-central Illinois, Quercus alba , Prunus serotina, and Liriodendron tulipifera predominantly occur in moderately well-drained soils (MS 40-60 ?? 10-5 SI), whereas Acer saccharinum, Carya laciniosa, and Fraxinus pennsylvanica predominantly occur in poorly drained soils (MS <20 ?? 10-5 SI). Using a similar method, an MS contour map was used to guide restoration of mesic, wet mesic, and wet prairie species to pre-settlement distributions at Meadowbrook Park (Urbana, IL, U.S.A.). Through use of soil MS maps calibrated to soil drainage class and native vegetation occurrence, restoration efforts can be conducted more successfully and species distributions more accurately reconstructed at the microecosystem level. ?? 2008 Society for Ecological Restoration International.

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

PubMed Central

Pasyukova, E G; Vieira, C; Mackay, T F

2000-01-01

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested. PMID:11063689

Susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

NASA Astrophysics Data System (ADS)

Legorreta Paulin, G.; Bursik, M. I.; Lugo Hubp, J.; Paredes Mejía, L.; Aceves Quesada, F.

2013-12-01

In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. This poster provides an overview of the on-going research project (Grant SEP-CONACYT no 167495) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using Geographic Information Systems (GIS). The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 5.2 km2 with elevations ranging from 2676.79 to 4248.2 m a.s.l. and hillslopes between 5° and 56°. The stream system of Río El Estado catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. The first level builds a historic landslide inventory. In the study area, an inventory of more than 100 landslides was mapped from interpretation of multi-temporal aerial orthophotographs and local field surveys to assess and describe landslide distribution. All landslides were digitized into a GIS, and the spatial geo-database of landslides was constructed from standardized GIS datasets. The second level calculates the susceptibility for the watershed. Multiple Logistic Regression (MLR) was used to examine the relationship between landsliding and several independent variables (elevation, slope, terrain curvature, flow direction, saturation, contributing area, land use, and geology

Rainfall thresholds and susceptibility mapping for shallow landslides and debris flows in Scotland

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

2017-04-01

Shallow translational slides and debris flows (hereafter 'landslides') pose a significant threat to life and cause significant annual economic impacts (e.g. by damage and disruption of infrastructure). The focus of this research is on the definition of objective rainfall thresholds using a weather radar system and landslide susceptibility mapping. In the study area Scotland, an inventory of 75 known landslides was used for the period 2003 to 2016. First, the effect of using different rain records (i.e. time series length) on two threshold selection techniques in receiver operating characteristic (ROC) analysis was evaluated. The results show that thresholds selected by 'Threat Score' (minimising false alarms) are sensitive to rain record length and which is not routinely considered, whereas thresholds selected using 'Optimal Point' (minimising failed alarms) are not; therefore these may be suited to establishing lower limit thresholds and be of interest to those developing early warning systems. Robust thresholds are found for combinations of normalised rain duration and accumulation at 1 and 12 day's antecedence respectively; these are normalised using the rainy-day normal and an equivalent measure for rain intensity. This research indicates that, in Scotland, rain accumulation provides a better indicator than rain intensity and that landslides may be generated by threshold conditions lower than previously thought. Second, a landslide susceptibility map is constructed using a cross-validated logistic regression model. A novel element of the approach is that landslide susceptibility is calculated for individual hillslope sections. The developed thresholds and susceptibility map are combined to assess potential hazards and impacts posed to the national highway network in Scotland.

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.

Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

NASA Astrophysics Data System (ADS)

Tazik, E.; Jahantab, Z.; Bakhtiari, M.; Rezaei, A.; Kazem Alavipanah, S.

2014-10-01

Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

Maps of Quaternary Deposits and Liquefaction Susceptibility in the Central San Francisco Bay Region, California

USGS Publications Warehouse

Witter, Robert C.; Knudsen, Keith L.; Sowers, Janet M.; Wentworth, Carl M.; Koehler, Richard D.; Randolph, Carolyn E.; Brooks, Suzanna K.; Gans, Kathleen D.

2006-01-01

This report presents a map and database of Quaternary deposits and liquefaction susceptibility for the urban core of the San Francisco Bay region. It supercedes the equivalent area of U.S. Geological Survey Open-File Report 00-444 (Knudsen and others, 2000), which covers the larger 9-county San Francisco Bay region. The report consists of (1) a spatial database, (2) two small-scale colored maps (Quaternary deposits and liquefaction susceptibility), (3) a text describing the Quaternary map and liquefaction interpretation (part 3), and (4) a text introducing the report and describing the database (part 1). All parts of the report are digital; part 1 describes the database and digital files and how to obtain them by downloading across the internet. The nine counties surrounding San Francisco Bay straddle the San Andreas fault system, which exposes the region to serious earthquake hazard (Working Group on California Earthquake Probabilities, 1999). Much of the land adjacent to the Bay and the major rivers and streams is underlain by unconsolidated deposits that are particularly vulnerable to earthquake shaking and liquefaction of water-saturated granular sediment. This new map provides a consistent detailed treatment of the central part of the 9-county region in which much of the mapping of Open-File Report 00-444 was either at smaller (less detailed) scale or represented only preliminary revision of earlier work. Like Open-File Report 00-444, the current mapping uses geomorphic expression, pedogenic soils, inferred depositional environments, and geologic age to define and distinguish the map units. Further scrutiny of the factors controlling liquefaction susceptibility has led to some changes relative to Open-File Report 00-444: particularly the reclassification of San Francisco Bay mud (Qhbm) to have only MODERATE susceptibility and the rating of artificial fills according to the Quaternary map units inferred to underlie them (other than dams - adf). The two colored

Methodology for Elaborating Regional Susceptibility Maps of Slope Instability: the State of Guerrero (mexico) Case Study

NASA Astrophysics Data System (ADS)

González Huesca, A. E.; Ferrés, D.; Domínguez-M, L.

2013-05-01

Numerous cases of different types of slope instability occur every year in the mountain areas of México. Sometimes these instabilities severely affect the exposed communities, roads and infrastructure, causing deaths and serious material damage, mainly in the states of Puebla, Veracruz, Oaxaca, Guerrero and Chiapas, at the central and south sectors of the country. The occurrence of the slope instability is the result of the combination of climatic, geologic, hydrologic, geomorphologic and anthropogenic factors. The National Center for Disaster Prevention (CENAPRED) is developing several projects in order to offer civil protection authorities of the Mexican states some methodologies to address the hazard assessment for different natural phenomena in a regional level. In this framework, during the past two years, a methodology was prepared to construct susceptibility maps for slope instability at regional (≤ 1:100 000) and national (≤ 1:1 000 000) levels. This research was addressed in accordance to the criteria established by the International Association of Engineering Geology, which is the highest international authority in this topic. The state of Guerrero has been taken as a pilot scheme to elaborate the susceptibility map for slope instability at a regional level. The major constraints considered in the methodology to calculate susceptibility are: a) the slope of the surface, b) the geology and c) the land use, which were integrated using a Geographic Information System (GIS). The arithmetic sum and weighting factors to obtain the final susceptibility map were based on the average values calculated in the individual study of several cases of slope instability occurred in the state in the past decade. For each case, the evaluation format proposed by CENAPRED in 2006 in the "Guía Básica para la elaboración de Atlas Estatales y Municipales de Peligros y Riesgos" to evaluate instabilities in a local level, was applied. The resulting susceptibility map shows

Susceptibility Evaluation and Mapping of CHINA'S Landslide Disaster Based on Multi-Temporal Ground and Remote Sensing Satellite Data

NASA Astrophysics Data System (ADS)

Liu, C.; Li, W.; Lu, P.; Sang, K.; Hong, Y.; Li, R.

2012-07-01

Under the circumstances of global climate change, nowadays landslide occurs in China more frequently than ever before. The landslide hazard and risk assessment remains an international focus on disaster prevention and mitigation. It is also an important approach for compiling and quantitatively characterizing landslide damages. By integrating empirical models for landslide disasters, and through multi-temporal ground data and remote sensing data, this paper will perform a landslide susceptibility assessment throughout China. A landslide susceptibility (LS) map will then be produced, which can be used for disaster evaluation, and provide basis for analyzing China's major landslide-affected regions. Firstly, based on previous research of landslide susceptibility assessment, this paper collects and analyzes the historical landslide event data (location, quantity and distribution) of past sixty years in China as a reference for late-stage studies. Secondly, this paper will make use of regional GIS data of the whole country provided by the National Geomatics Centre and China Meteorological Administration, including regional precipitation data, and satellite remote sensing data such as from TRMM and MODIS. By referring to historical landslide data of past sixty years, it is possible to develop models for assessing LS, including producing empirical models for prediction, and discovering both static and dynamic key factors, such as topography and landforms (elevation, curvature and slope), geologic conditions (lithology of the strata), soil type, vegetation cover, hydrological conditions (flow distribution). In addition, by analyzing historical data and combining empirical models, it is possible to synthesize a regional statistical model and perform a LS assessment. Finally, based on the 1km×1km grid, the LS map is then produced by ANN learning and multiplying the weighted factor layers. The validation is performed with reference to the frequency and distribution of

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Blaschke, Thomas

2014-03-04

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster-Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster-Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Blaschke, Thomas

2014-01-01

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC

Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms.

PubMed

Razavi Termeh, Seyed Vahid; Kornejady, Aiding; Pourghasemi, Hamid Reza; Keesstra, Saskia

2018-02-15

Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom Township in Fars Province using a combination of adaptive neuro-fuzzy inference systems (ANFIS) with different metaheuristics algorithms such as ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO) and comparing their accuracy. A total number of 53 flood locations areas were identified, 35 locations of which were randomly selected in order to model flood susceptibility and the remaining 16 locations were used to validate the models. Learning vector quantization (LVQ), as one of the supervised neural network methods, was employed in order to estimate factors' importance. Nine flood conditioning factors namely: slope degree, plan curvature, altitude, topographic wetness index (TWI), stream power index (SPI), distance from river, land use/land cover, rainfall, and lithology were selected and the corresponding maps were prepared in ArcGIS. The frequency ratio (FR) model was used to assign weights to each class within particular controlling factor, then the weights was transferred into MATLAB software for further analyses and to combine with metaheuristic models. The ANFIS-PSO was found to be the most practical model in term of producing the highly focused flood susceptibility map with lesser spatial distribution related to highly susceptible classes. The chi-square result attests the same, where the ANFIS-PSO had the highest spatial differentiation within flood susceptibility classes over the study area. The area under the curve (AUC) obtained from ROC curve indicated the accuracy of 91.4%, 91.8%, 92.6% and 94.5% for the respective models of FR, ANFIS-ACO, ANFIS-GA, and ANFIS-PSO ensembles. So, the ensemble of ANFIS-PSO was introduced as the

OdorMapComparer: an application for quantitative analyses and comparisons of fMRI brain odor maps.

PubMed

Liu, Nian; Xu, Fuqiang; Miller, Perry L; Shepherd, Gordon M

2007-01-01

Brain odor maps are reconstructed flat images that describe the spatial activity patterns in the glomerular layer of the olfactory bulbs in animals exposed to different odor stimuli. We have developed a software application, OdorMapComparer, to carry out quantitative analyses and comparisons of the fMRI odor maps. This application is an open-source window program that first loads two odor map images being compared. It allows image transformations including scaling, flipping, rotating, and warping so that the two images can be appropriately aligned to each other. It performs simple subtraction, addition, and average of signals in the two images. It also provides comparative statistics including the normalized correlation (NC) and spatial correlation coefficient. Experimental studies showed that the rodent fMRI odor maps for aliphatic aldehydes displayed spatial activity patterns that are similar in gross outlines but somewhat different in specific subregions. Analyses with OdorMapComparer indicate that the similarity between odor maps decreases with increasing difference in the length of carbon chains. For example, the map of butanal is more closely related to that of pentanal (with a NC = 0.617) than to that of octanal (NC = 0.082), which is consistent with animal behavioral studies. The study also indicates that fMRI odor maps are statistically odor-specific and repeatable across both the intra- and intersubject trials. OdorMapComparer thus provides a tool for quantitative, statistical analyses and comparisons of fMRI odor maps in a fashion that is integrated with the overall odor mapping techniques.

Mapping erosion susceptibility by a multivariate statistical method: A case study from the Ayvalık region, NW Turkey

NASA Astrophysics Data System (ADS)

Akgün, Aykut; Türk, Necdet

2011-09-01

Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayvalık region in Balıkesir (NW Turkey). The following were our assessment parameters: weathering grades of rocks, slope gradient, structural lineament density, drainage density, land cover, stream power index (SPI) and profile curvature. These were processed by Idrisi Kilimanjaro GIS software. We used logistic regression analysis to relate predictor variables to the occurrence or non-occurrence of gully erosion sites within geographic cells, and then we used this relationship to produce a probability map for future erosion sites. The results indicate that lineament density, weathering grades of rocks and drainage density are the most important variables governing erosion susceptibility. Other variables, such as land cover and slope gradient, were revealed as secondary important variables. Highly weathered basalt, andesite, basaltic andesite and lacustrine sediments were the units most susceptible to erosion. In order to calculate the prediction accuracy of the erosion susceptibility map generated, we compared it with the map showing the gully erosion areas. On the basis of this comparison, the area under curvature (AUC) value was found to be 0.81. This result suggests that the erosion susceptibility map we generated is accurate.

Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI.

PubMed

Liu, Tian; Spincemaille, Pascal; de Rochefort, Ludovic; Kressler, Bryan; Wang, Yi

2009-01-01

Magnetic susceptibility differs among tissues based on their contents of iron, calcium, contrast agent, and other molecular compositions. Susceptibility modifies the magnetic field detected in the MR signal phase. The determination of an arbitrary susceptibility distribution from the induced field shifts is a challenging, ill-posed inverse problem. A method called "calculation of susceptibility through multiple orientation sampling" (COSMOS) is proposed to stabilize this inverse problem. The field created by the susceptibility distribution is sampled at multiple orientations with respect to the polarization field, B(0), and the susceptibility map is reconstructed by weighted linear least squares to account for field noise and the signal void region. Numerical simulations and phantom and in vitro imaging validations demonstrated that COSMOS is a stable and precise approach to quantify a susceptibility distribution using MRI.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

NASA Astrophysics Data System (ADS)

Blais-Stevens, A.; Behnia, P.

2016-02-01

This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC), by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect, surficial geology, plan curvature, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high-resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g. 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

NASA Astrophysics Data System (ADS)

Blais-Stevens, A.; Behnia, P.

2015-05-01

This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC) by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect (derived from a 5 m × 5 m DEM), surficial geology, permafrost distribution, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g., 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

Landslide susceptibility mapping in three selected target zones in Afghanistan

NASA Astrophysics Data System (ADS)

Schwanghart, Wolfgang; Seegers, Joe; Zeilinger, Gerold

2015-04-01

In May 2014, a large and mobile landslide destroyed the village Ab Barek, a village in Badakshan Province, Afghanistan. The landslide caused several hundred fatalities and once again demonstrated the vulnerability of Afghanistan's population to extreme natural events following more than 30 years of civil war and violent conflict. Increasing the capacity of Afghanistan's population by strengthening the disaster preparedness and management of responsible government authorities and institutions is thus a major component of international cooperation and development strategies. Afghanistan is characterized by high relief and widely varying rock types that largely determine the spatial distribution as well as emplacement modes of mass movements. The major aim of our study is to characterize this variability by conducting a landslide susceptibility analysis in three selected target zones: Greater Kabul Area, Badakhshan Province and Takhar Province. We expand on an existing landslide database by mapping landforms diagnostic for landslides (e.g. head scarps, normal faults and tension cracks), and historical landslide scars and landslide deposits by visual interpretation of high-resolution satellite imagery. We conduct magnitude frequency analysis within subregional physiogeographic classes based on geological maps, climatological and topographic data to identify regional parameters influencing landslide magnitude and frequency. In addition, we prepare a landslide susceptibility map for each area using the Weight-of-Evidence model. Preliminary results show that the three selected target zones vastly differ in modes of landsliding. Low magnitude but frequent rockfall events are a major hazard in the Greater Kabul Area threatening buildings and infrastructure encroaching steep terrain in the city's outskirts. Mass movements in loess covered areas of Badakshan are characterized by medium to large magnitudes. This spatial variability of characteristic landslide magnitudes and

Mapping of risk and susceptibility of shallow-landslide in the city of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Listo, Fabrizio de Luiz Rosito; Carvalho Vieira, Bianca

2012-10-01

In the city of São Paulo, where about 11 million people live, landslides and flooding occur frequently, especially during the summer. These landslides cause the destruction of houses and urban equipment, economic damage, and the loss of lives. The number of areas threatened by landslides has been increasing each year. The objective of this article is to analyze the probability of risk and susceptibility to shallow landslides in the Limoeiro River basin, which is located at the head of the Aricanduva River basin, one of the main hydrographic basins in the city of São Paulo. To map areas of risk, we created a cadastral survey form to evaluate landslide risk in the field. Risk was categorized into four levels based on natural and anthropogenic factors: R1 (low risk), R2 (average risk), R3 (high risk), and R4 (very high risk). To analyze susceptibility to shallow landslides, we used the SHALSTAB (Shallow Landsliding Stability) mathematical model and calculated the Distribution Frequency (DF) of the susceptibility classes for the entire basin. Finally, we performed a joint analysis of the average Risk Concentration (RC) and Risk Potential (RP). We mapped 14 risk sectors containing approximately 685 at-risk homes, more than half of which presented a high (R3) or very high (R4) probability of risk to the population. In the susceptibility map, 41% of the area was classified as stable and 20% as unconditionally unstable. Although the latter category accounted a smaller proportion of the total area, it contained a concentration (RC) of 41% of the mapped risk areas with a risk potential (RP) of 12%. We found that the locations of areas predicted to be unstable by the model coincided with the risk areas mapped in the field. This combination of methods can be applied to evaluate the risk of shallow landslides in densely populated areas and can assist public managers in defining areas that are unstable and inappropriate for occupation.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

PubMed Central

Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R.; Mahajan, Anubha; Asimit, Jennifer L.; Ferreira, Teresa; Locke, Adam E.; Robertson, Neil R.; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E.; Tam, Claudia H.T.; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I.; Blangero, John; Burtt, Noél P.; Duggirala, Ravindranath; Florez, Jose C.; Hanis, Craig L.; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C.N.; Ma, Ronald C.W.; Froguel, Philippe; Wilson, James G.; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B.; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S.; Chambers, John C.; Saleheen, Danish; Kadowaki, Takashi; Tai, E. Shyong; Mohlke, Karen L.; Cox, Nancy J.; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I.; Morris, Andrew P.

2016-01-01

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. PMID:26911676

Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes

DTIC Science & Technology

2012-12-05

Bisgaier J, Levinson D, Cutts DB, & Rhodes KV., (2011) Access to autism evaluation appointments with developmental-behavioral and neurodevelopmental ...W403 Columbus, OH 43205 Final Report Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes...QFOXGHDUHDFRGH 1.0 Summary In 2006, the Central Ohio Registry for Autism (CORA) was initiated as a collaboration between Wright-Patterson Air

Landslide susceptibility mapping in the coastal region in the State of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Alvala, R. C.; Camarinha, P. I.; Canavesi, V.

2013-05-01

, land use and pedology. As a result, we obtain 5 susceptibility classes: very low, low, medium, high and very high. To validate the methodology, there was overlapped the Landslides Susceptibility Map with real risk areas previously mapped, provided by the National Centre for Monitoring and Alert of Natural Disasters. This step is important especially to assess the methodology adherence to evaluate the classes that was mapped with high and very high susceptibility. The preliminary results indicate that over 70% of the the mapped risks areas are located into the classes more susceptible. We observed small inconsistencies that are related with spatial displacement of the various databases considered, which has different resolutions and scales. Therefore, the results indicated that the methodology is robust and showed the high vulnerability of the counties analyzed, which further highlights that the landslides susceptibility should be monitored carefully by the decision makers in order to prevent and minimize the natural disasters impact, so that provide better territorial planning.

QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

NASA Astrophysics Data System (ADS)

Bartolini, S.; Cappello, A.; Martí, J.; Del Negro, C.

2013-08-01

One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision-making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps, i.e. the spatial probability of a future vent opening given the past eruptive activity of a volcano. This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source Geographic Information System Quantum GIS, that is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows to select an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input datasets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

QVAST: a new Quantum GIS plugin for estimating volcanic susceptibility

NASA Astrophysics Data System (ADS)

Bartolini, S.; Cappello, A.; Martí, J.; Del Negro, C.

2013-11-01

One of the most important tasks of modern volcanology is the construction of hazard maps simulating different eruptive scenarios that can be used in risk-based decision making in land-use planning and emergency management. The first step in the quantitative assessment of volcanic hazards is the development of susceptibility maps (i.e., the spatial probability of a future vent opening given the past eruptive activity of a volcano). This challenging issue is generally tackled using probabilistic methods that use the calculation of a kernel function at each data location to estimate probability density functions (PDFs). The smoothness and the modeling ability of the kernel function are controlled by the smoothing parameter, also known as the bandwidth. Here we present a new tool, QVAST, part of the open-source geographic information system Quantum GIS, which is designed to create user-friendly quantitative assessments of volcanic susceptibility. QVAST allows the selection of an appropriate method for evaluating the bandwidth for the kernel function on the basis of the input parameters and the shapefile geometry, and can also evaluate the PDF with the Gaussian kernel. When different input data sets are available for the area, the total susceptibility map is obtained by assigning different weights to each of the PDFs, which are then combined via a weighted summation and modeled in a non-homogeneous Poisson process. The potential of QVAST, developed in a free and user-friendly environment, is here shown through its application in the volcanic fields of Lanzarote (Canary Islands) and La Garrotxa (NE Spain).

Comparison of two landslide susceptibility assessments in the Champagne-Ardenne region (France)

NASA Astrophysics Data System (ADS)

Den Eeckhaut, M. Van; Marre, A.; Poesen, J.

2010-02-01

The vineyards of the Montagne de Reims are mostly planted on steep south-oriented cuesta fronts receiving a maximum of sun radiation. Due to the location of the vineyards on steep hillslopes, the viticultural activity is threatened by slope failures. This study attempts to better understand the spatial patterns of landslide susceptibility in the Champagne-Ardenne region by comparing a heuristic (qualitative) and a statistical (quantitative) model in a 1120 km² study area. The heuristic landslide susceptibility model was adopted from the Bureau de Recherches Géologiques et Minières, the GEGEAA - Reims University and the Comité Interprofessionnel du Vin de Champagne. In this model, expert knowledge of the region was used to assign weights to all slope classes and lithologies present in the area, but the final susceptibility map was never evaluated with the location of mapped landslides. For the statistical landslide susceptibility assessment, logistic regression was applied to a dataset of 291 'old' (Holocene) landslides. The robustness of the logistic regression model was evaluated and ROC curves were used for model calibration and validation. With regard to the variables assumed to be important environmental factors controlling landslides, the two models are in agreement. They both indicate that present and future landslides are mainly controlled by slope gradient and lithology. However, the comparison of the two landslide susceptibility maps through (1) an evaluation with the location of mapped 'old' landslides and through (2) a temporal validation with spatial data of 'recent' (1960-1999; n = 48) and 'very recent' (2000-2008; n = 46) landslides showed a better prediction capacity for the statistical model produced in this study compared to the heuristic model. In total, the statistically-derived landslide susceptibility map succeeded in correctly classifying 81.0% of the 'old' and 91.6% of the 'recent' and 'very recent' landslides. On the susceptibility map

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, T. A.; Kirschbaum, D. B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregons SLIDO or NASAs Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modelling landslide susceptibility with heavily biased inventories.

Rapid quantitative chemical mapping of surfaces with sub-2 nm resolution

NASA Astrophysics Data System (ADS)

Lai, Chia-Yun; Perri, Saverio; Santos, Sergio; Garcia, Ricardo; Chiesa, Matteo

2016-05-01

We present a theory that exploits four observables in bimodal atomic force microscopy to produce maps of the Hamaker constant H. The quantitative H maps may be employed by the broader community to directly interpret the high resolution of standard bimodal AFM images as chemical maps while simultaneously quantifying chemistry in the non-contact regime. We further provide a simple methodology to optimize a range of operational parameters for which H is in the closest agreement with the Lifshitz theory in order to (1) simplify data acquisition and (2) generalize the methodology to any set of cantilever-sample systems.We present a theory that exploits four observables in bimodal atomic force microscopy to produce maps of the Hamaker constant H. The quantitative H maps may be employed by the broader community to directly interpret the high resolution of standard bimodal AFM images as chemical maps while simultaneously quantifying chemistry in the non-contact regime. We further provide a simple methodology to optimize a range of operational parameters for which H is in the closest agreement with the Lifshitz theory in order to (1) simplify data acquisition and (2) generalize the methodology to any set of cantilever-sample systems. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00496b

Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

PubMed Central

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

2009-01-01

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

Quantitative interpretation of the magnetic susceptibility frequency dependence

NASA Astrophysics Data System (ADS)

Ustra, Andrea; Mendonça, Carlos A.; Leite, Aruã; Jovane, Luigi; Trindade, Ricardo I. F.

2018-05-01

Low-field mass-specific magnetic susceptibility (MS) measurements using multifrequency alternating fields are commonly used to evaluate concentration of ferrimagnetic particles in the transition of superparamagnetic (SP) to stable single domain (SSD). In classical palaeomagnetic analyses, this measurement serves as a preliminary assessment of rock samples providing rapid, non-destructive, economical and easy information of magnetic properties. The SP-SSD transition is relevant in environmental studies because it has been associated with several geological and biogeochemical processes affecting magnetic mineralogy. MS is a complex function of mineral-type and grain-size distribution, as well as measuring parameters such as external field magnitude and frequency. In this work, we propose a new technique to obtain quantitative information on grain-size variations of magnetic particles in the SP-SSD transition by inverting frequency-dependent susceptibility. We introduce a descriptive parameter named as `limiting frequency effect' that provides an accurate estimation of MS loss with frequency. Numerical simulations show the methodology capability in providing data fitting and model parameters in many practical situations. Real-data applications with magnetite nanoparticles and core samples from sediments of Poggio le Guaine section of Umbria-Marche Basin (Italy) provide additional information not clearly recognized when interpreting cruder MS data. Caution is needed when interpreting frequency dependence in terms of single relaxation processes, which are not universally applicable and depend upon the nature of magnetic mineral in the material. Nevertheless, the proposed technique is a promising tool for SP-SSD content analyses.

Mapping of Mcs30, a new mammary carcinoma susceptibility quantitative trait locus (QTL30) on rat chromosome 12: identification of fry as a candidate Mcs gene.

PubMed

Ren, Xuefeng; Graham, Jessica C; Jing, Lichen; Mikheev, Andrei M; Gao, Yuan; Lew, Jenny Pan; Xie, Hong; Kim, Andrea S; Shang, Xiuling; Friedman, Cynthia; Vail, Graham; Fang, Ming Zhu; Bromberg, Yana; Zarbl, Helmut

2013-01-01

Rat strains differ dramatically in their susceptibility to mammary carcinogenesis. On the assumption that susceptibility genes are conserved across mammalian species and hence inform human carcinogenesis, numerous investigators have used genetic linkage studies in rats to identify genes responsible for differential susceptibility to carcinogenesis. Using a genetic backcross between the resistant Copenhagen (Cop) and susceptible Fischer 344 (F344) strains, we mapped a novel mammary carcinoma susceptibility (Mcs30) locus to the centromeric region on chromosome 12 (LOD score of ∼8.6 at the D12Rat59 marker). The Mcs30 locus comprises approximately 12 Mbp on the long arm of rat RNO12 whose synteny is conserved on human chromosome 13q12 to 13q13. After analyzing numerous genes comprising this locus, we identified Fry, the rat ortholog of the furry gene of Drosophila melanogaster, as a candidate Mcs gene. We cloned and determined the complete nucleotide sequence of the 13 kbp Fry mRNA. Sequence analysis indicated that the Fry gene was highly conserved across evolution, with 90% similarity of the predicted amino acid sequence among eutherian mammals. Comparison of the Fry sequence in the Cop and F344 strains identified two non-synonymous single nucleotide polymorphisms (SNPs), one of which creates a putative, de novo phosphorylation site. Further analysis showed that the expression of the Fry gene is reduced in a majority of rat mammary tumors. Our results also suggested that FRY activity was reduced in human breast carcinoma cell lines as a result of reduced levels or mutation. This study is the first to identify the Fry gene as a candidate Mcs gene. Our data suggest that the SNPs within the Fry gene contribute to the genetic susceptibility of the F344 rat strain to mammary carcinogenesis. These results provide the foundation for analyzing the role of the human FRY gene in cancer susceptibility and progression.

SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy

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

Ito, K; Kadoya, N; Chiba, M

2016-06-15

Purpose: The aim of this study is to develop radiation treatment planning using magnetic susceptibility obtained from quantitative susceptibility mapping (QSM) via MR imaging. This study demonstrates the feasibility of a method for generating a substitute for a CT image from an MRI. Methods: The head of a healthy volunteer was scanned using a CT scanner and a 3.0 T MRI scanner. The CT imaging was performed with a slice thickness of 2.5 mm at 80 and 120 kV (dual-energy scan). These CT images were converted to relative electron density (rED) using the CT-rED conversion table generated by a previousmore » dual-energy CT scan. The CT-rED conversion table was generated using the conversion of the energy-subtracted CT number to rED via a single linear relationship. One T2 star-weighted 3D gradient echo-based sequence with four different echo times images was acquired using the MRI scanner. These T2 star-weighted images were used to estimate the phase data. To estimate the local field map, a Laplacian unwrapping of the phase and background field removal algorithm were implemented to process phase data. To generate a magnetic susceptibility map from the local field map, we used morphology enabled dipole inversion method. The rED map was resampled to the same resolution as magnetic susceptibility, and the magnetic susceptibility-rED conversion table was obtained via voxel-by-voxel mapping between the magnetic susceptibility and rED maps. Results: A correlation between magnetic susceptibility and rED is not observed through our method. Conclusion: Our results show that the correlation between magnetic susceptibility and rED is not observed. As the next step, we assume that the voxel of the magnetic susceptibility map comprises two materials, such as water (0 ppm) and bone (-2.2 ppm) or water and marrow (0.81ppm). The elements of each voxel were estimated from the ratio of the two materials.« less

Utilizing NASA Earth Observations to Assess Landslide Characteristics and Devlelop Susceptibility and Exposure Maps in Malawi

NASA Astrophysics Data System (ADS)

Klug, M.; Cissell, J.; Grossman, M.

2017-12-01

Malawi has become increasingly prone to landslides in the past few decades. This can be attributed to the terrain, types of soil and vegetation, increased human interference, and heavy flooding after long periods of drought. In addition to the floods and droughts, landslides cause extra stress to farmlands, thus exacerbating the current food security crisis in the country. It can be difficult to pinpoint just how many people are affected by landslides in Malawi because landslides often occur in rural areas or are grouped with other disasters, such as floods or earthquakes. This project created a Landslide Susceptibility Map to assess landslide-prone areas in Malawi using variables such as slope, distance to roads, distance to streams, soil type, and precipitation. These variables were derived using imagery from Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission Version 3 (SRTM-v3), Global Precipitation Measurement (GPM), and Tropical Rainfall Measuring Mission (TRMM) satellites. Furthermore, this project created a Landslide Exposure Map to estimate how much of the local population lives in susceptible areas by intersecting population data with the Landslide Susceptibility Map. Additionally, an assessment of GPM and TRMM precipitation measurements was generated to better understand the reliability of both measurements for landslide monitoring. Finally, this project updated NASA SERVIR's Global Landslide Catalog (GLC) for Malawi by using WorldView data from Google Earth and Landsat 8 OLI. These end products were used by NASA SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for aiding in disaster management throughout Malawi.

Educational Software for Mapping Quantitative Trait Loci (QTL)

ERIC Educational Resources Information Center

Helms, T. C.; Doetkott, C.

2007-01-01

This educational software was developed to aid teachers and students in their understanding of how the process of identifying the most likely quantitative trait loci (QTL) position is determined between two flanking DNA markers. The objective of the software that we developed was to: (1) show how a QTL is mapped to a position on a chromosome using…

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.

Development of a quantitative pachytene chromosome map and its unification with somatic chromosome and linkage maps of rice (Oryza sativa L.).

PubMed

Ohmido, Nobuko; Iwata, Aiko; Kato, Seiji; Wako, Toshiyuki; Fukui, Kiichi

2018-01-01

A quantitative pachytene chromosome map of rice (Oryza sativa L.) was developed using imaging methods. The map depicts not only distribution patterns of chromomeres specific to pachytene chromosomes, but also the higher order information of chromosomal structures, such as heterochromatin (condensed regions), euchromatin (decondensed regions), the primary constrictions (centromeres), and the secondary constriction (nucleolar organizing regions, NOR). These features were image analyzed and quantitatively mapped onto the map by Chromosome Image Analyzing System ver. 4.0 (CHIAS IV). Correlation between H3K9me2, an epigenetic marker and formation and/or maintenance of heterochromatin, thus was, clearly visualized. Then the pachytene chromosome map was unified with the existing somatic chromosome and linkage maps by physically mapping common DNA markers among them, such as a rice A genome specific tandem repeat sequence (TrsA), 5S and 45S ribosomal RNA genes, five bacterial artificial chromosome (BAC) clones, four P1 bacteriophage artificial chromosome (PAC) clones using multicolor fluorescence in situ hybridization (FISH). Detailed comparison between the locations of the DNA probes on the pachytene chromosomes using multicolor FISH, and the linkage map enabled determination of the chromosome number and short/long arms of individual pachytene chromosomes using the chromosome number and arm assignment designated for the linkage map. As a result, the quantitative pachytene chromosome map was unified with two other major rice chromosome maps representing somatic prometaphase chromosomes and genetic linkages. In conclusion, the unification of the three rice maps serves as an indispensable basic information, not only for an in-depth comparison between genetic and chromosomal data, but also for practical breeding programs.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

PubMed

Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R; Mahajan, Anubha; Asimit, Jennifer L; Ferreira, Teresa; Locke, Adam E; Robertson, Neil R; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E; Tam, Claudia H T; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I; Blangero, John; Burtt, Noél P; Duggirala, Ravindranath; Florez, Jose C; Hanis, Craig L; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C N; Ma, Ronald C W; Froguel, Philippe; Wilson, James G; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S; Chambers, John C; Saleheen, Danish; Kadowaki, Takashi; Tai, E Shyong; Mohlke, Karen L; Cox, Nancy J; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I; Morris, Andrew P

2016-05-15

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. © The Author 2016. Published by Oxford University Press.

Susceptibility analysis for slides and rockfall: an example from the Northern Calcareous Alps (Vorarlberg, Austria)

NASA Astrophysics Data System (ADS)

Ruff, Michael; Rohn, Joachim

2008-07-01

In this paper a tool for semi-quantitative susceptibility assessment at a regional scale is presented which is applicable at areas with complex geological setting. At a study area within the Northern Calcareous Alps geotechnical mappings were implemented into a Geographical Information System and analysed as grid data with a cell size of 25 m. The susceptibility to sliding and falling processes was considered according to five classes (very low, low, medium, high, very high). Susceptibility to sliding was analysed using an index method. The layers of lithology, bedding conditions, tectonic faults, slope angle, slope aspect, vegetation and erosion were combined iteratively. Dropout zones of rockfall material were determined with help of a Digital Elevation Model. The movement of rolling rock samples was modelled by a cost analysis of all potential rockfall trajectories. These trajectories were also divided into five susceptibility classes. The susceptibility maps are presented in a general way to be used by communities and spatial planners. Conflict areas of susceptibility and landuse were located and can be presented destinctively.

Mapping and Sequencing of the Canine NRAMP1 Gene and Identification of Mutations in Leishmaniasis-Susceptible Dogs

PubMed Central

Altet, Laura; Francino, Olga; Solano-Gallego, Laia; Renier, Corinne; Sánchez, Armand

2002-01-01

The NRAMP1 gene (Slc11a1) encodes an ion transporter protein involved in the control of intraphagosomal replication of parasites and in macrophage activation. It has been described in mice as the determinant of natural resistance or susceptibility to infection with antigenically unrelated pathogens, including Leishmania. Our aims were to sequence and map the canine Slc11a1 gene and to identify mutations that may be associated with resistance or susceptibility to Leishmania infection. The canine Slc11a1 gene has been mapped to dog chromosome CFA37 and covers 9 kb, including a 700-bp promoter region, 15 exons, and a polymorphic microsatellite in intron 1. It encodes a 547-amino-acid protein that has over 87% identity with the Slc11a1 proteins of different mammalian species. A case-control study with 33 resistant and 84 susceptible dogs showed an association between allele 145 of the microsatellite and susceptible dogs. Sequence variant analysis was performed by direct sequencing of the cDNA and the promoter region of four unrelated beagles experimentally infected with Leishmania infantum to search for possible functional mutations. Two of the dogs were classified as susceptible and the other two were classified as resistant based on their immune responses. Two important mutations were found in susceptible dogs: a G-rich region in the promoter that was common to both animals and a complete deletion of exon 11, which encodes the consensus transport motif of the protein, in the unique susceptible dog that needed an additional and prolonged treatment to avoid continuous relapses. A study with a larger dog population would be required to prove the association of these sequence variants with disease susceptibility. PMID:12010961

Developing and applying quantitative skills maps for STEM curricula, with a focus on different modes of learning

NASA Astrophysics Data System (ADS)

Reid, Jackie; Wilkes, Janelle

2016-08-01

Mapping quantitative skills across the science, technology, engineering and mathematics (STEM) curricula will help educators identify gaps and duplication in the teaching, practice and assessment of the necessary skills. This paper describes the development and implementation of quantitative skills mapping tools for courses in STEM at a regional university that offers both on-campus and distance modes of study. Key elements of the mapping project included the identification of key graduate quantitative skills, the development of curriculum mapping tools to record in which unit(s) and at what level of attainment each quantitative skill is taught, practised and assessed, and identification of differences in the way quantitative skills are developed for on-campus and distance students. Particular attention is given to the differences that are associated with intensive schools, which consist of concentrated periods of face-to-face learning over a three-four day period, and are available to distance education students enrolled in STEM units. The detailed quantitative skills mapping process has had an impact on the review of first-year mathematics units, resulted in crucial changes to the curriculum in a number of courses, and contributed to a more integrated approach, and a collective responsibility, to the development of students' quantitative skills for both face-to-face and online modes of learning.

Mapping soil magnetic susceptibility and mineralogy in Ukraine

NASA Astrophysics Data System (ADS)

Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr; Sukhorada, Anatoliy

2017-04-01

Soil suatainable planning is fundamental for agricultural areas. Soil mapping and modeling are increasingly used in agricultural areas in the entire world (Brevik et al., 2016). They are beneficial to land managers, to reduce soil degradation, increase soil productivity and their restoration. Magnetic susceptibility (MS) methods are low cost and accurate for the developing maps of agricultural areas.. The objective of this work is to identify the minerals responsible for MS increase in soils from the two study areas in Poltava and Kharkiv region. The thermomagnetic analyses were conducted using the KLY-4 with an oven apparatus. The hysteresis parameters were measured with the Rotating Magnetometer at the Geophysical Centre Dourbes, Belgium. The results showed that all of samples from Kharkiv area and the majortity of the samples collected in Poltava area represent the pseudo single domain (PSD) zone particles in Day plot. According to Hanesch et al. (2006), the transformation of goethite, ferrihydrite or hematite to a stronger ferrimagnetic phase like magnetite or maghemite is common in strongly magnetic soils with high values of organic carbon content. In our case of thermomagnetic study, the first peak on the heating curve near 260 ˚C indicates the presence of ferrihydrite which gradually transforms into maghemite (Jordanova et al., 2013). A further decrease in the MS identified on the heating curve may be related to the transformation of the maghemite to hematite. A second MS peak on the heating curve near 530 ˚C and the ultimate loss of magnetic susceptibility near 580 ˚C were caused by the reduction of hematite to magnetite. The shape of the thermomagnetic curves suggests the presence of single domain (SD) particles at room temperature and their transformation to a superparamagnetic (SP) state under heating. Magnetic mineralogical analyses suggest the presence of highly magnetic minerals like magnetite and maghemite as well as slightly magnetic goethite

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

EM Algorithm for Mapping Quantitative Trait Loci in Multivalent Tetraploids

USDA-ARS?s Scientific Manuscript database

Multivalent tetraploids that include many plant species, such as potato, sugarcane and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such ...

TRIGRS Application for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Sugiarti, K.; Sukristiyanti, S.

2018-02-01

Research on landslide susceptibility has been carried out using several different methods. TRIGRS is a modeling program for landslide susceptibility by considering pore water pressure changes due to infiltration of rainfall. This paper aims to present a current state-of-the-art science on the development and application of TRIGRS. Some limitations of TRIGRS, some developments of it to improve its modeling capability, and some examples of the applications of some versions of it to model the effect of rainfall variation on landslide susceptibility are reviewed and discussed.

Towards quantitative usage of EMI-data for Digital Soil Mapping

NASA Astrophysics Data System (ADS)

Nüsch, A.-K.; Wunderlich, T.; Kathage, S.; Werban, U.; Dietrich, P.

2009-04-01

As formulated in the Thematic Strategy for Soil Protection prepared by the European Commission soil degradation is a serious problem in Europe. The degradation is driven or exacerbated by human activity and has a direct impact on water and air quality, biodiversity, climate and human life-quality. High-resolution soil property maps are one major prerequisite for the specific protection of soil function and restoration of degraded soils as well as sustainable land use, water and environmental management. However, the currently available techniques for (digital) soil mapping still have deficiencies in terms of reliability and precision, the feasibility of investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats at this scale. The focus of the iSOIL (Interactions between soil related science - Linking geophysics, soil science and digital soil mapping) project is on improving fast and reliable mapping of soil properties, soil functions and soil degradation threats. This requires the improvement as well as integration of geophysical and spectroscopic measurement techniques in combination with advanced soil sampling approaches, pedometrical and pedophysical approaches. Many commercially available geophysical sensors and equipment (EMI, DC, gamma-spectroscopy, magnetics) are ready to use for measurements of different parameters. Data collection with individual sensors is well developed and numerously described. However comparability of data of different sensor types as well as reproducibility of data is not self-evident. In particular handling of sensors has to be carried out accurately, e.g. consistent calibration. Soil parameters will be derived from geophysical properties to create comprehensive soil maps. Therefore one prerequisite is the comparison of different geophysical properties not only qualitative but also quantitative. At least reproducibility is one of the most important conditions for monitoring tasks. The

Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.

PubMed

Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Chen, Wei

2018-06-01

In China, floods are considered as the most frequent natural disaster responsible for severe economic losses and serious damages recorded in agriculture and urban infrastructure. Based on the international experience prevention of flood events may not be completely possible, however identifying susceptible and vulnerable areas through prediction models is considered as a more visible task with flood susceptibility mapping being an essential tool for flood mitigation strategies and disaster preparedness. In this context, the present study proposes a novel approach to construct a flood susceptibility map in the Poyang County, JiangXi Province, China by implementing fuzzy weight of evidence (fuzzy-WofE) and data mining methods. The novelty of the presented approach is the usage of fuzzy-WofE that had a twofold purpose. Firstly, to create an initial flood susceptibility map in order to identify non-flood areas and secondly to weight the importance of flood related variables which influence flooding. Logistic Regression (LR), Random Forest (RF) and Support Vector Machines (SVM) were implemented considering eleven flood related variables, namely: lithology, soil cover, elevation, slope angle, aspect, topographic wetness index, stream power index, sediment transport index, plan curvature, profile curvature and distance from river network. The efficiency of this new approach was evaluated using area under curve (AUC) which measured the prediction and success rates. According to the outcomes of the performed analysis, the fuzzy WofE-SVM model was the model with the highest predictive performance (AUC value, 0.9865) which also appeared to be statistical significant different from the other predictive models, fuzzy WofE-RF (AUC value, 0.9756) and fuzzy WofE-LR (AUC value, 0.9652). The proposed methodology and the produced flood susceptibility map could assist researchers and local governments in flood mitigation strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative evaluation of susceptibility effects caused by dental materials in head magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Strocchi, S.; Ghielmi, M.; Basilico, F.; Macchi, A.; Novario, R.; Ferretti, R.; Binaghi, E.

2016-03-01

This work quantitatively evaluates the effects induced by susceptibility characteristics of materials commonly used in dental practice on the quality of head MR images in a clinical 1.5T device. The proposed evaluation procedure measures the image artifacts induced by susceptibility in MR images by providing an index consistent with the global degradation as perceived by the experts. Susceptibility artifacts were evaluated in a near-clinical setup, using a phantom with susceptibility and geometric characteristics similar to that of a human head. We tested different dentist materials, called PAL Keramit, Ti6Al4V-ELI, Keramit NP, ILOR F, Zirconia and used different clinical MR acquisition sequences, such as "classical" SE and fast, gradient, and diffusion sequences. The evaluation is designed as a matching process between reference and artifacts affected images recording the same scene. The extent of the degradation induced by susceptibility is then measured in terms of similarity with the corresponding reference image. The matching process involves a multimodal registration task and the use an adequate similarity index psychophysically validated, based on correlation coefficient. The proposed analyses are integrated within a computer-supported procedure that interactively guides the users in the different phases of the evaluation method. 2-Dimensional and 3-dimensional indexes are used for each material and each acquisition sequence. From these, we drew a ranking of the materials, averaging the results obtained. Zirconia and ILOR F appear to be the best choice from the susceptibility artefacts point of view, followed, in order, by PAL Keramit, Ti6Al4V-ELI and Keramit NP.

Susceptibility Testing by Polymerase Chain Reaction DNA Quantitation: A Method to Measure Drug Resistance of Human Immunodeficiency Virus Type 1 Isolates

NASA Astrophysics Data System (ADS)

Eron, Joseph J.; Gorczyca, Paul; Kaplan, Joan C.; D'Aquila, Richard T.

1992-04-01

Polymerase chain reaction (PCR) DNA quantitation (PDQ) susceptibility testing rapidly and directly measures nucleoside sensitivity of human immunodeficiency virus type 1 (HIV-1) isolates. PCR is used to quantitate the amount of HIV-1 DNA synthesized after in vitro infection of peripheral blood mononuclear cells. The relative amounts of HIV-1 DNA in cell lysates from cultures maintained at different drug concentrations reflect drug inhibition of virus replication. The results of PDQ susceptibility testing of 2- or 3-day cultures are supported by assays measuring HIV-1 p24 antigen production in supernatants of 7- or 10-day cultures. DNA sequence analyses to identify mutations in the reverse transcriptase gene that cause resistance to 3'-azido-3'-deoxythymidine also support the PDQ results. With the PDQ method, both infectivity titration and susceptibility testing can be performed on supernatants from primary cultures of peripheral blood mononuclear cells. PDQ susceptibility testing should facilitate epidemiologic studies of the clinical significance of drug-resistant HIV-1 isolates.

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

PubMed Central

Hashim, Mazlan

2015-01-01

This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning. PMID:25898919

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

PubMed

Shahabi, Himan; Hashim, Mazlan

2015-04-22

This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

A method of mapping sinkhole susceptibility using a geographic information system : a case study for interstates in the karst counties of Virginia.

DOT National Transportation Integrated Search

2015-02-01

This study proposes the use of a geographic information system (GIS) to create a susceptibility map, pinpointing : regions in the karst counties of Virginia, in particular, along interstates, most susceptible to future sinkhole : development, determi...

Mapping surface charge density of lipid bilayers by quantitative surface conductivity microscopy

PubMed Central

Klausen, Lasse Hyldgaard; Fuhs, Thomas; Dong, Mingdong

2016-01-01

Local surface charge density of lipid membranes influences membrane–protein interactions leading to distinct functions in all living cells, and it is a vital parameter in understanding membrane-binding mechanisms, liposome design and drug delivery. Despite the significance, no method has so far been capable of mapping surface charge densities under physiologically relevant conditions. Here, we use a scanning nanopipette setup (scanning ion-conductance microscope) combined with a novel algorithm to investigate the surface conductivity near supported lipid bilayers, and we present a new approach, quantitative surface conductivity microscopy (QSCM), capable of mapping surface charge density with high-quantitative precision and nanoscale resolution. The method is validated through an extensive theoretical analysis of the ionic current at the nanopipette tip, and we demonstrate the capacity of QSCM by mapping the surface charge density of model cationic, anionic and zwitterionic lipids with results accurately matching theoretical values. PMID:27561322

Mapping surface charge density of lipid bilayers by quantitative surface conductivity microscopy

NASA Astrophysics Data System (ADS)

Klausen, Lasse Hyldgaard; Fuhs, Thomas; Dong, Mingdong

2016-08-01

Local surface charge density of lipid membranes influences membrane-protein interactions leading to distinct functions in all living cells, and it is a vital parameter in understanding membrane-binding mechanisms, liposome design and drug delivery. Despite the significance, no method has so far been capable of mapping surface charge densities under physiologically relevant conditions. Here, we use a scanning nanopipette setup (scanning ion-conductance microscope) combined with a novel algorithm to investigate the surface conductivity near supported lipid bilayers, and we present a new approach, quantitative surface conductivity microscopy (QSCM), capable of mapping surface charge density with high-quantitative precision and nanoscale resolution. The method is validated through an extensive theoretical analysis of the ionic current at the nanopipette tip, and we demonstrate the capacity of QSCM by mapping the surface charge density of model cationic, anionic and zwitterionic lipids with results accurately matching theoretical values.

Mapping surface charge density of lipid bilayers by quantitative surface conductivity microscopy.

PubMed

Klausen, Lasse Hyldgaard; Fuhs, Thomas; Dong, Mingdong

2016-08-26

Local surface charge density of lipid membranes influences membrane-protein interactions leading to distinct functions in all living cells, and it is a vital parameter in understanding membrane-binding mechanisms, liposome design and drug delivery. Despite the significance, no method has so far been capable of mapping surface charge densities under physiologically relevant conditions. Here, we use a scanning nanopipette setup (scanning ion-conductance microscope) combined with a novel algorithm to investigate the surface conductivity near supported lipid bilayers, and we present a new approach, quantitative surface conductivity microscopy (QSCM), capable of mapping surface charge density with high-quantitative precision and nanoscale resolution. The method is validated through an extensive theoretical analysis of the ionic current at the nanopipette tip, and we demonstrate the capacity of QSCM by mapping the surface charge density of model cationic, anionic and zwitterionic lipids with results accurately matching theoretical values.

Development and testing of method for assessing and mapping agricultural areas susceptible to atrazine leaching in the state of Washington

USGS Publications Warehouse

Voss, Frank D.

2003-01-01

In a joint effort by the Washington State Department of Agriculture, the Washington Department of Ecology, and the U.S. Geological Survey, the Environmental Protection Agency's Pesticide Root Zone Model and a Geographic Information System were used to develop and test a method for screening and mapping the susceptibility of ground water in agricultural areas to pesticide contamination. The objective was to produce a map that would be used by the Washington State Department of Agriculture to allocate resources for monitoring pesticide levels in ground water. The method was tested by producing a map showing susceptibility to leaching of the pesticide atrazine for the Columbia Basin Irrigation Project, which encompasses an area of intensive agriculture in eastern Washington. The reliability of the atrazine map was assessed by using statistical procedures to determine whether the median of the percentage of atrazine simulated to leach below the root zone in wells where atrazine was detected was statistically greater than the median percentage at wells where atrazine was not detected (at or above 0.001 microgram per liter) in 134 wells sampled by the U.S. Geological Survey. A statistical difference in medians was not found when all 134 wells were compared. However, a statistical difference was found in medians for two subsets of the 134 wells that were used in land-use studies (studies examining the quality of ground water beneath specific crops). The statistical results from wells from the land-use studies indicate that the model potentially can be used to map the relative susceptibility of agricultural areas to atrazine leaching. However, the distinction between areas of high and low susceptibility may not yet be sufficient to use the method for allocating resources to monitor water quality. Several options are offered for improving the reliability of future simulations.

GIS-aided Statistical Landslide Susceptibility Modeling And Mapping Of Antipolo Rizal (Philippines)

NASA Astrophysics Data System (ADS)

Dumlao, A. J.; Victor, J. A.

2015-09-01

Slope instability associated with heavy rainfall or earthquake is a familiar geotechnical problem in the Philippines. The main objective of this study is to perform a detailed landslide susceptibility assessment of Antipolo City. The statistical method of assessment used was logistic regression. Landslide inventory was done through interpretation of aerial photographs and satellite images with corresponding field verification. In this study, morphologic and non-morphologic factors contributing to landslide occurrence and their corresponding spatial relationships were considered. The analysis of landslide susceptibility was implemented in a Geographic Information System (GIS). The 17320 randomly selected datasets were divided into training and test data sets. K- cross fold validation is done with k= 5. The subsamples are then fitted five times with k-1 training data set and the remaining fold as the validation data set. The AUROC of each model is validated using each corresponding data set. The AUROC of the five models are; 0.978, 0.977, 0.977, 0.974, and 0.979 respectively, implying that the models are effective in correctly predicting the occurrence and nonoccurrence of landslide activity. Field verification was also done. The landslide susceptibility map was then generated from the model. It is classified into four categories; low, moderate, high and very high susceptibility. The study also shows that almost 40% of Antipolo City has been assessed to be potentially dangerous areas in terms of landslide occurrence.

Quantitative Trait Loci Mapping of Genome Regions Controlling Permethrin Resistance in the Mosquito Aedes aegypti

PubMed Central

Saavedra-Rodriguez, Karla; Strode, Clare; Flores Suarez, Adriana; Fernandez Salas, Ildefonso; Ranson, Hilary; Hemingway, Janet; Black, William C.

2008-01-01

The mosquito Aedes aegypti is the principal vector of dengue and yellow fever flaviviruses. Permethrin is an insecticide used to suppress Ae. aegypti adult populations but metabolic and target site resistance to pyrethroids has evolved in many locations worldwide. Quantitative trait loci (QTL) controlling permethrin survival in Ae. aegypti were mapped in an F3 advanced intercross line. Parents came from a collection of mosquitoes from Isla Mujeres, México, that had been selected for permethrin resistance for two generations and a reference permethrin-susceptible strain originally from New Orleans. Following a 1-hr permethrin exposure, 439 F3 adult mosquitoes were phenotyped as knockdown resistant, knocked down/recovered, or dead. For QTL mapping, single nucleotide polymorphisms (SNPs) were identified at 22 loci with potential antixenobiotic activity including genes encoding cytochrome P450s (CYP), esterases (EST), or glutathione transferases (GST) and at 12 previously mapped loci. Seven antixenobiotic genes mapped to chromosome I, six to chromosome II, and nine to chromosome III. Two QTL of major effect were detected on chromosome III. One corresponds with a SNP previously associated with permethrin resistance in the para sodium channel gene and the second with the CCEunk7o esterase marker. Additional QTL but of relatively minor effect were also found. These included two sex-linked QTL on chromosome I affecting knockdown and recovery and a QTL affecting survival and recovery. On chromosome II, one QTL affecting survival and a second affecting recovery were detected. The patterns confirm that mutations in the para gene cause target-site insensitivity and are the major source of permethrin resistance but that other genes dispersed throughout the genome contribute to recovery and survival of mosquitoes following permethrin exposure. PMID:18723882

Methods for landslide susceptibility modelling in Lower Austria

NASA Astrophysics Data System (ADS)

Bell, Rainer; Petschko, Helene; Glade, Thomas; Leopold, Philip; Heiss, Gerhard; Proske, Herwig; Granica, Klaus; Schweigl, Joachim; Pomaroli, Gilbert

2010-05-01

Landslide susceptibility modelling and implementation of the resulting maps is still a challenge for geoscientists, spatial and infrastructure planners. Particularly on a regional scale landslide processes and their dynamics are poorly understood. Furthermore, the availability of appropriate spatial data in high resolution is often a limiting factor for modelling high quality landslide susceptibility maps for large study areas. However, these maps form an important basis for preventive spatial planning measures. Thus, new methods have to be developed, especially focussing on the implementation of final maps into spatial planning processes. The main objective of the project "MoNOE" (Method development for landslide susceptibility modelling in Lower Austria) is to design a method for landslide susceptibility modelling for a large study area (about 10.200 km²) and to produce landslide susceptibility maps which are finally implemented in the spatial planning strategies of the Federal state of Lower Austria. The project focuses primarily on the landslide types fall and slide. To enable susceptibility modelling, landslide inventories for the respective landslide types must be compiled and relevant data has to be gathered, prepared and homogenized. Based on this data new methods must be developed to tackle the needs of the spatial planning strategies. Considerable efforts will also be spent on the validation of the resulting maps for each landslide type. A great challenge will be the combination of the susceptibility maps for slides and falls in just one single susceptibility map (which is requested by the government) and the definition of the final visualisation. Since numerous landslides have been favoured or even triggered by human impact, the human influence on landslides will also have to be investigated. Furthermore possibilities to integrate respective findings in regional susceptibility modelling will be explored. According to these objectives the project is

Semi-quantitative MALDI-TOF for antimicrobial susceptibility testing in Staphylococcus aureus.

PubMed

Maxson, Tucker; Taylor-Howell, Cheryl L; Minogue, Timothy D

2017-01-01

Antibiotic resistant bacterial infections are a significant problem in the healthcare setting, in many cases requiring the rapid administration of appropriate and effective antibiotic therapy. Diagnostic assays capable of quickly and accurately determining the pathogen resistance profile are therefore crucial to initiate or modify care. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is a standard method for species identification in many clinical microbiology laboratories and is well positioned to be applied towards antimicrobial susceptibility testing. One recently reported approach utilizes semi-quantitative MALDI-TOF MS for growth rate analysis to provide a resistance profile independent of resistance mechanism. This method was previously successfully applied to Gram-negative pathogens and mycobacteria; here, we evaluated this method with the Gram-positive pathogen Staphylococcus aureus. Specifically, we used 35 strains of S. aureus and four antibiotics to optimize and test the assay, resulting in an overall accuracy rate of 95%. Application of the optimized assay also successfully determined susceptibility from mock blood cultures, allowing both species identification and resistance determination for all four antibiotics within 3 hours of blood culture positivity.

Application of LiDAR Date to Assess the Landslide Susceptibility Map Using Weights of Evidence Method - AN Example from Podhale Region (southern Poland)

NASA Astrophysics Data System (ADS)

Kamiński, Mirosław

2016-06-01

Podhale is a region in southern Poland, which is the northernmost part of the Central Carpathian Mountains. It is characterized by the presence of a large number of landslides that threaten the local infrastructure. In an article presents application of LiDAR data and geostatistical methods to assess landslides susceptibility map. Landslide inventory map were performed using LiDAR data and field work. The Weights of Evidence method was applied to assess landslides susceptibility map. Used factors for modeling: slope gradient, slope aspect, elevation, drainage density, faults density, lithology and curvature. All maps were subdivided into different classes. Then were converted to grid format in the ArcGIS 10.0. The conditional independence test was carried out to determine factors that are conditionally independent of each other with landslides. As a result, chi-square test for further GIS analysis used only five factors: slope gradient, slope aspect, elevation, drainage density and lithology. The final prediction results, it is concluded that the susceptibility map gives useful information both on present instability of the area and its possible future evolution in agreement with the morphological evolution of the area.

Low signal-to-noise FDEM in-phase data: Practical potential for magnetic susceptibility modelling

NASA Astrophysics Data System (ADS)

Delefortrie, Samuël; Hanssens, Daan; De Smedt, Philippe

2018-05-01

In this paper, we consider the use of land-based frequency-domain electromagnetics (FDEM) for magnetic susceptibility modelling. FDEM data comprises both out-of-phase and in-phase components, which can be related to the electrical conductivity and magnetic susceptibility of the subsurface. Though applying the FDEM method to obtain information on the subsurface conductivity is well established in various domains (e.g. through the low induction number approximation of subsurface apparent conductivity), the potential for susceptibility mapping is often overlooked. Especially given a subsurface with a low magnetite and maghemite content (e.g. most sedimentary environments), it is generally assumed that susceptibility is negligible. Nonetheless, the heterogeneity of the near surface and the impact of anthropogenic disturbances on the soil can cause sufficient variation in susceptibility for it to be detectable in a repeatable way. Unfortunately, it can be challenging to study the potential for susceptibility mapping due to systematic errors, an often poor low signal-to-noise ratio, and the intricacy of correlating in-phase responses with subsurface susceptibility and conductivity. Alongside use of an accurate forward model - accounting for out-of-phase/in-phase coupling - any attempt at relating the in-phase response with subsurface susceptibility requires overcoming instrument-specific limitations that burden the real-world application of FDEM susceptibility mapping. Firstly, the often erratic and drift-sensitive nature of in-phase responses calls for relative data levelling. In addition, a correction for absolute levelling offsets may be equally necessary: ancillary (subsurface) susceptibility data can be used to assess the importance of absolute in-phase calibration though hereby accurate in-situ data is required. To allow assessing the (importance of) in-phase calibration alongside the potential of FDEM data for susceptibility modelling, we consider an experimental

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

PubMed

Chen, Zikuan; Calhoun, Vince D

2016-03-01

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

Landslide susceptibility assessment and validation in the framework of municipal planning in Portugal: the case of Loures Municipality.

PubMed

Guillard, Clemence; Zezere, Jose

2012-10-01

The legislation that demands the evaluation of landslide susceptibility in Portugal at the municipal level is the National Ecological Reserve (NER). A methodology for the evaluation of landslide susceptibility to be used in municipal planning is applied in Loures Municipality (169.3 km²) located north of Lisbon (Portugal). A landslide inventory was made for the whole area interpreting orthophoto maps and aerial photographs and using standard geomorphologic techniques in field work. It consists of 686 polygons, each polygon representing a rotational, a deep translational or a shallow translational slide, and is integrated into a GIS database. Landslide susceptibility is evaluated using algorithms based on statistical/probabilistic analysis (Information Value Method) over unique-condition terrain units in a raster basis. Three susceptibility models are elaborated independently according to the type of slide (rotational, deep translational, shallow translational). The landslide susceptibility maps are prepared by sorting all pixels according to the pixel susceptibility value in descending order. The robustness and accuracy of the landslide susceptibility models are evaluated by prediction-rate curves, which are used for the quantitative interpretation of the landslide susceptibility maps. Unstable slopes that have to be included into the National Ecological Reserve are extracted from the three susceptibility maps following the general rules to draw the NER that state that the area to be included in the NER should guarantee the inclusion of at least 70 % of the landslides identified in the landslide inventory. The obtained results allow us to conclude that 70 % of the future landslides should occur in these areas, classified as most susceptible to landslides corresponding to 20.3 % of the total area of Municipality. Thus, the consideration of these 20.3 % as regards prevention and protection of landslide risk could potentially reduce damage resulting from 70�

Validating national landslide susceptibility and hazard maps for Caribbean island countries: the case of Dominica and tropical storm Erika.

NASA Astrophysics Data System (ADS)

van Westen, Cees; Jetten, Victor; Alkema, Dinand

2016-04-01

The aim of this study was to generate national-scale landslide susceptibility and hazard maps for four Caribbean islands, as part of the World Bank project CHARIM (Caribbean Handbook on Disaster Geoinformation Management, www.charim.net). This paper focuses on the results for the island country of Dominica, located in the Eastern part of the Caribbean, in-between Guadalupe and Martinique. The available data turned out to be insufficient to generate reliable results. We therefore generated a new database of disaster events for Dominica using all available data, making use of many different sources. We compiled landslide inventories for five recent rainfall events from the maintenance records of the Ministry of Public Works, and generated a completely new landslide inventory using multi-temporal visual image interpretation, and generated an extensive landslide database for Dominica. We analyzed the triggering conditions for landslides as far as was possible given the available data, and generated rainfall magnitude-frequency relations. We applied a method for landslide susceptibility assessment which combined bi-variate statistical analysis, that provided indications on the importance of the possible contributing factors, with an expert-based iterative weighing approach using Spatial Multi-Criteria Evaluation. The method is transparent, as the stakeholders (e.g. the engineers and planners from the four countries) and other consultants can consult the criteria trees and evaluate the standardization and weights, and make adjustments. The landslide susceptibility map was converted into a landslide hazard map using landslide density and frequencies for so called major, moderate and minor triggering events. The landslide hazard map was produced in May 2015. A major rainfall event occurred on Dominica following the passage of tropical storm Erika on 26 to 28 August 2015. An event-based landslide inventory for this event was produced by UNOSAT using very high resolution

Developing and Applying Quantitative Skills Maps for STEM Curricula, with a Focus on Different Modes of Learning

ERIC Educational Resources Information Center

Reid, Jackie; Wilkes, Janelle

2016-01-01

Mapping quantitative skills across the science, technology, engineering and mathematics (STEM) curricula will help educators identify gaps and duplication in the teaching, practice and assessment of the necessary skills. This paper describes the development and implementation of quantitative skills mapping tools for courses in STEM at a regional…

PXK locus in systemic lupus erythematosus: fine mapping and functional analysis reveals novel susceptibility gene ABHD6.

PubMed

Oparina, Nina Y; Delgado-Vega, Angelica M; Martinez-Bueno, Manuel; Magro-Checa, César; Fernández, Concepción; Castro, Rafaela Ortega; Pons-Estel, Bernardo A; D'Alfonso, Sandra; Sebastiani, Gian Domenico; Witte, Torsten; Lauwerys, Bernard R; Endreffy, Emoke; Kovács, László; Escudero, Alejandro; López-Pedrera, Chary; Vasconcelos, Carlos; da Silva, Berta Martins; Frostegård, Johan; Truedsson, Lennart; Martin, Javier; Raya, Enrique; Ortego-Centeno, Norberto; de Los Angeles Aguirre, Maria; de Ramón Garrido, Enrique; Palma, María-Jesús Castillo; Alarcon-Riquelme, Marta E; Kozyrev, Sergey V

2015-03-01

To perform fine mapping of the PXK locus associated with systemic lupus erythematosus (SLE) and study functional effects that lead to susceptibility to the disease. Linkage disequilibrium (LD) mapping was conducted by using 1251 SNPs (single nucleotide polymorphism) covering a 862 kb genomic region on 3p14.3 comprising the PXK locus in 1467 SLE patients and 2377 controls of European origin. Tag SNPs and genotypes imputed with IMPUTE2 were tested for association by using SNPTEST and PLINK. The expression QTLs data included three independent datasets for lymphoblastoid cells of European donors: HapMap3, MuTHER and the cross-platform eQTL catalogue. Correlation analysis of eQTLs was performed using Vassarstats. Alternative splicing for the PXK gene was analysed on mRNA from PBMCs. Fine mapping revealed long-range LD (>200 kb) extended over the ABHD6, RPP14, PXK, and PDHB genes on 3p14.3. The highly correlated variants tagged an SLE-associated haplotype that was less frequent in the patients compared with the controls (OR=0.89, p=0.00684). A robust correlation between the association with SLE and enhanced expression of ABHD6 gene was revealed, while neither expression, nor splicing alterations associated with SLE susceptibility were detected for PXK. The SNP allele frequencies as well as eQTL pattern analysed in the CEU and CHB HapMap3 populations indicate that the SLE association and the effect on ABHD6 expression are specific to Europeans. These results confirm the genetic association of the locus 3p14.3 with SLE in Europeans and point to the ABHD6 and not PXK, as the major susceptibility gene in the region. We suggest a pathogenic mechanism mediated by the upregulation of ABHD6 in individuals carrying the SLE-risk variants. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2013-02-01

The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e

Linkage disequilibrium interval mapping of quantitative trait loci.

PubMed

Boitard, Simon; Abdallah, Jihad; de Rochambeau, Hubert; Cierco-Ayrolles, Christine; Mangin, Brigitte

2006-03-16

For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods. Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations. Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.

Rockfall susceptibility mapping of Yosemite Valley (USA) using a high-resolution digital elevation model

NASA Astrophysics Data System (ADS)

Pannatier, A.; Oppikofer, T.; Jaboyedoff, M.; Stock, G. M.

2009-04-01

In Yosemite National Park (California, USA) rockfalls from the steep valley flanks are frequent (>600 documented events in 150 years) and threaten infrastructure in this popular tourist area. This study focuses on a methodology to map the susceptibility to rockfall initiation based on a high-resolution digital elevation model (HRDEM) obtained from aerial laser scanning (1 meter cell size). This methodology is based on geometric factors derived from the HRDEM, i.e., the steepness of the topography, the presence of joints or fractures enabling either a planar or a wedge failure mechanism, and a high denudation potential. The slope angle histogram computed using standard GIS routines was simulated using Gaussian distributions, which were attributed to different parts of the topography, i.e., the cliffs, the valley flanks and the valley floor. Slopes steeper than 36° are found to form cliffs and thus potentially lead to rockfalls. A morpho-structural analysis of the HRDEM was performed in Coltop3D software to determine the major discontinuity sets that shape the topography. Kinematic analyses were made for each of these 7 discontinuity sets in order to determine the HRDEM cells that fulfil the geometric criteria for a planar or wedge failure mechanism. Most of the cliffs in Yosemite Valley enable one or both of these failure mechanisms. The denudation potential was assessed using the sloping local base level (SLBL) concept. The SLBL defines a basal erosion surface and the above lying rock masses (up to 400 m in some of the vertical cliffs) are susceptible to erosion by mass wasting. A thickness of 20 m above the SLBL surface was chosen as lower limit for the denudation potential criterion. The HRDEM cells that satisfy 1, 2 or all 3 criteria are considered having low, moderate and high susceptibility to rockfall initiation. The areas with highest susceptibility (El Capitan, Glacier Point, Yosemite Falls and Half Dome) coincide well with post-glacial talus accumulations

High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

PubMed

Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

2017-07-14

Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

NASA Astrophysics Data System (ADS)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

Spatial analysis for susceptibility of second-time karst sinkholes: A case study of Jili Village in Guangxi, China

NASA Astrophysics Data System (ADS)

Zhou, Guoqing; Yan, Hongbo; Chen, Kunhua; Zhang, Rongting

2016-04-01

After a big karst sinkhole happened in Jili Village of Guangxi, China, the local government was eager to quantitatively analyze and map susceptible areas of the potential second-time karst sinkholes in order to make timely decisions whether the residents living in the first-time sinkhole areas should move. For this reason, karst sinkholes susceptibility geospatial analysis is investigated using multivariate spatial data, logistic regression model (LRM) and Geographical Information System (GIS). Ten major karst sinkholes related factors, including (1) formation lithology, (2) soil structure, (3) profile curvature, (4) groundwater depth, (5) fluctuation of groundwater level, (6) percolation rate of soil, (7) degree of karst development, (8) distance from fault, (9) distance from the traffic route, and (10) overburden thickness were selected, and then each of factors was classified and quantitated with the three or four levels. The LRM was applied to evaluate which factor makes significant contributions to sinkhole. The results demonstrated that formation lithology, soil structure, profile curvature, groundwater depth, ground water level, percolation rate of soil, and degree of karst development, the distance from fault, and overburden thickness are positive, while one factor, the distance from traffic routes is negative, which is deleted from LRM model. The susceptibility of the potential sinkholes in the study area is estimated and mapped using the solved impact factors. The susceptible degrees of the study area are classified into five levels, very high, high, moderate, low, and ignore susceptibility. It has been found that that both very high and high susceptibility areas are along Datou Hill and the foothills of the study area. This finding is verified by field observations. With the investigations conducted in this paper, it can be concluded that the susceptibility maps produced in this paper are reliable and accurate, and useful as a reference for local

Susceptibility of coastal plain aquifers to contamination, Fairfax County, Virginia; a computer composite map

USGS Publications Warehouse

Johnston, Richard H.; Van Driel, J. Nicholas

1978-01-01

A map is presented that classifies the Coastal Plain of Fairfax County, Virginia according to the susceptibility of the principal sand aquifers to contamination from surface sources. The following classification is used: (1) areas where leachate can readily enter the principal sand aquifers, (2) areas offering great natural protection against migration of leachate into the aquifers, and, (3) areas where the contamination risk is uncertain and onsite investigations are needed. Approximately 20 percent of the area is in the high-risk category. The map is computer generated and was made by combining four source maps depicting those hydrogeologic factors related to movement of contaminants into the aquifers. These factors are (1) lithologic character of the upper 25 feet of sediments, (2) clay thickness above uppermost sand aquifer, (3) hydraulic gradient direction and head difference between water table and artesian head in principal aquifer, and (4) areal occurrence of moderate to high transmissiviry aquifers. The map is designed to be used by planners with little or no earth-science background, however, a technical discussion for hydrologists and geologists is also provided. (Woodard-USGS)

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

Spatial access priority mapping (SAPM) with fishers: a quantitative GIS method for participatory planning.

PubMed

Yates, Katherine L; Schoeman, David S

2013-01-01

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions, is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here a readily accessible, novel method for quantitatively mapping fishers' spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers' willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process

Object-based Classification for Detecting Landslides and Stochastic Procedure to landslide susceptibility maps - A Case at Baolai Village, SW Taiwan

NASA Astrophysics Data System (ADS)

Lin, Ying-Tong; Chang, Kuo-Chen; Yang, Ci-Jian

2017-04-01

As the result of global warming in the past decades, Taiwan has experienced more and more extreme typhoons with hazardous massive landslides. In this study, we use object-oriented analysis method to classify landslide area at Baolai village by using Formosat-2 satellite images. We used for multiresolution segmented to generate the blocks, and used hierarchical logic to classified 5 different kinds of features. After that, classification the landslide into different type of landslide. Beside, we use stochastic procedure to integrate landslide susceptibility maps. This study assumed that in the extreme event, 2009 Typhoon Morakot, which precipitation goes to 1991.5mm in 5 days, and the highest landslide susceptible area. The results show that study area's landslide area was greatly changes, most of landslide was erosion by gully and made dip slope slide, or erosion by the stream, especially at undercut bank. From the landslide susceptibility maps, we know that the old landslide area have high potential to occur landslides in the extreme event. This study demonstrates the changing of landslide area and the landslide susceptible area. Keywords: Formosat-2, object-oriented, segmentation, classification, landslide, Baolai Village, SW Taiwan, FS

GhMAP3K65, a Cotton Raf-Like MAP3K Gene, Enhances Susceptibility to Pathogen Infection and Heat Stress by Negatively Modulating Growth and Development in Transgenic Nicotiana benthamiana.

PubMed

Zhai, Na; Jia, Haihong; Liu, Dongdong; Liu, Shuchang; Ma, Manli; Guo, Xingqi; Li, Han

2017-11-21

Mitogen-activated protein kinase kinase kinases (MAP3Ks), the top components of MAPK cascades, modulate many biological processes, such as growth, development and various environmental stresses. Nevertheless, the roles of MAP3Ks remain poorly understood in cotton. In this study, GhMAP3K65 was identified in cotton, and its transcription was inducible by pathogen infection, heat stress, and multiple signalling molecules. Silencing of GhMAP3K65 enhanced resistance to pathogen infection and heat stress in cotton. In contrast, overexpression of GhMAP3K65 enhanced susceptibility to pathogen infection and heat stress in transgenic Nicotiana benthamiana . The expression of defence-associated genes was activated in transgenic N. benthamiana plants after pathogen infection and heat stress, indicating that GhMAP3K65 positively regulates plant defence responses. Nevertheless, transgenic N. benthamiana plants impaired lignin biosynthesis and stomatal immunity in their leaves and repressed vitality of their root systems. In addition, the expression of lignin biosynthesis genes and lignin content were inhibited after pathogen infection and heat stress. Collectively, these results demonstrate that GhMAP3K65 enhances susceptibility to pathogen infection and heat stress by negatively modulating growth and development in transgenic N. benthamiana plants.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia

2018-06-11

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Comparative mapping of Raphanus sativus genome using Brassica markers and quantitative trait loci analysis for the Fusarium wilt resistance trait.

PubMed

Yu, Xiaona; Choi, Su Ryun; Ramchiary, Nirala; Miao, Xinyang; Lee, Su Hee; Sun, Hae Jeong; Kim, Sunggil; Ahn, Chun Hee; Lim, Yong Pyo

2013-10-01

Fusarium wilt (FW), caused by the soil-borne fungal pathogen Fusarium oxysporum is a serious disease in cruciferous plants, including the radish (Raphanus sativus). To identify quantitative trait loci (QTL) or gene(s) conferring resistance to FW, we constructed a genetic map of R. sativus using an F2 mapping population derived by crossing the inbred lines '835' (susceptible) and 'B2' (resistant). A total of 220 markers distributed in 9 linkage groups (LGs) were mapped in the Raphanus genome, covering a distance of 1,041.5 cM with an average distance between adjacent markers of 4.7 cM. Comparative analysis of the R. sativus genome with that of Arabidopsis thaliana and Brassica rapa revealed 21 and 22 conserved syntenic regions, respectively. QTL mapping detected a total of 8 loci conferring FW resistance that were distributed on 4 LGs, namely, 2, 3, 6, and 7 of the Raphanus genome. Of the detected QTL, 3 QTLs (2 on LG 3 and 1 on LG 7) were constitutively detected throughout the 2-year experiment. QTL analysis of LG 3, flanked by ACMP0609 and cnu_mBRPGM0085, showed a comparatively higher logarithm of the odds (LOD) value and percentage of phenotypic variation. Synteny analysis using the linked markers to this QTL showed homology to A. thaliana chromosome 3, which contains disease-resistance gene clusters, suggesting conservation of resistance genes between them.

Water erosion susceptibility mapping by applying Stochastic Gradient Treeboost to the Imera Meridionale River Basin (Sicily, Italy)

NASA Astrophysics Data System (ADS)

Angileri, Silvia Eleonora; Conoscenti, Christian; Hochschild, Volker; Märker, Michael; Rotigliano, Edoardo; Agnesi, Valerio

2016-06-01

Soil erosion by water constitutes a serious problem affecting various countries. In the last few years, a number of studies have adopted statistical approaches for erosion susceptibility zonation. In this study, the Stochastic Gradient Treeboost (SGT) was tested as a multivariate statistical tool for exploring, analyzing and predicting the spatial occurrence of rill-interrill erosion and gully erosion. This technique implements the stochastic gradient boosting algorithm with a tree-based method. The study area is a 9.5 km2 river catchment located in central-northern Sicily (Italy), where water erosion processes are prevalent, and affect the agricultural productivity of local communities. In order to model soil erosion by water, the spatial distribution of landforms due to rill-interrill and gully erosion was mapped and 12 environmental variables were selected as predictors. Four calibration and four validation subsets were obtained by randomly extracting sets of negative cases, both for rill-interrill erosion and gully erosion models. The results of validation, based on receiving operating characteristic (ROC) curves, showed excellent to outstanding accuracies of the models, and thus a high prediction skill. Moreover, SGT allowed us to explore the relationships between erosion landforms and predictors. A different suite of predictor variables was found to be important for the two models. Elevation, aspect, landform classification and land-use are the main controlling factors for rill-interrill erosion, whilst the stream power index, plan curvature and the topographic wetness index were the most important independent variables for gullies. Finally, an ROC plot analysis made it possible to define a threshold value to classify cells according to the presence/absence of the two erosion processes. Hence, by heuristically combining the resulting rill-interrill erosion and gully erosion susceptibility maps, an integrated water erosion susceptibility map was created. The

Landslide Susceptibility Mapping Using Geospatial Technology in South Eastern Part of Nilgiri District, Tamilnadu, India

NASA Astrophysics Data System (ADS)

Thangasamy, N.; Varathan, R.

2013-05-01

Landslides are often destructive and periodically affect the Nilgiris district. Two method viz., Frequency ratio (FR) and Weights of evidence (WofE) were used to reclassify the sub-variables and the landslide susceptibility index (LSI) was calculated by weighted sum overlay analysis. The final LS Zonation map was prepared from the LSI and the area was classified into two zones. Validation of the LSM was the next step and was accomplished by excluding some landslide points in the GIS analyses and overlying the unused landslides points over the LSM. The LSMs prepared using the FR and WofE methods are reliable as more than 75% of the excluded slides fall in high and very high landslide susceptibility zones and the error of mismatch in the two maps is negligible.During the course of this study landslides devastated the Kethi, Coonoor, Barliyar and Kothagiri areas due to an extreme event with 374 to 1,171 mm rainfall received in these stations in just three days on 8th to 10th November, 2009. The rainfall event is unprecedented and such extreme rainfall has not occurred in the region since meteorological records are maintained. Over 100 landslides took place in the area of which 75 are major slides and more 43 people died and 200 houses were damaged. The event was documented and a data base containing the location, details of death, slide characteristics and photographs was prepared. Further, the probability of landslide occurrence may change over time due to changes in land use, unscientific massive developmental activities and establishing settlements without adopting proper safety measures. The study also highlights the need for maintenance of landslide database and installation of more rain gauge stations to update and improve the LSM so as to reduce the risk of landslide hazard faced by the Community. NaveenRaj.T INDIA LANDSLIDE SUSCEPTIBILITY MAPPING USING GEOSPATIAL TECHNOLOGY IN SOUTH EASTERN PART OF NILGIRI DISTRICT, TAMILNADU, INDIA.

Quantitative architectural analysis: a new approach to cortical mapping.

PubMed

Schleicher, A; Palomero-Gallagher, N; Morosan, P; Eickhoff, S B; Kowalski, T; de Vos, K; Amunts, K; Zilles, K

2005-12-01

Recent progress in anatomical and functional MRI has revived the demand for a reliable, topographic map of the human cerebral cortex. Till date, interpretations of specific activations found in functional imaging studies and their topographical analysis in a spatial reference system are, often, still based on classical architectonic maps. The most commonly used reference atlas is that of Brodmann and his successors, despite its severe inherent drawbacks. One obvious weakness in traditional, architectural mapping is the subjective nature of localising borders between cortical areas, by means of a purely visual, microscopical examination of histological specimens. To overcome this limitation, more objective, quantitative mapping procedures have been established in the past years. The quantification of the neocortical, laminar pattern by defining intensity line profiles across the cortical layers, has a long tradition. During the last years, this method has been extended to enable a reliable, reproducible mapping of the cortex based on image analysis and multivariate statistics. Methodological approaches to such algorithm-based, cortical mapping were published for various architectural modalities. In our contribution, principles of algorithm-based mapping are described for cyto- and receptorarchitecture. In a cytoarchitectural parcellation of the human auditory cortex, using a sliding window procedure, the classical areal pattern of the human superior temporal gyrus was modified by a replacing of Brodmann's areas 41, 42, 22 and parts of area 21, with a novel, more detailed map. An extension and optimisation of the sliding window procedure to the specific requirements of receptorarchitectonic mapping, is also described using the macaque central sulcus and adjacent superior parietal lobule as a second, biologically independent example. Algorithm-based mapping procedures, however, are not limited to these two architectural modalities, but can be applied to all images in

Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

NASA Astrophysics Data System (ADS)

Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

2017-12-01

Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall

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

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

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

Saturation pulse design for quantitative myocardial T1 mapping.

PubMed

Chow, Kelvin; Kellman, Peter; Spottiswoode, Bruce S; Nielles-Vallespin, Sonia; Arai, Andrew E; Salerno, Michael; Thompson, Richard B

2015-10-01

Quantitative saturation-recovery based T1 mapping sequences are less sensitive to systematic errors than the Modified Look-Locker Inversion recovery (MOLLI) technique but require high performance saturation pulses. We propose to optimize adiabatic and pulse train saturation pulses for quantitative T1 mapping to have <1 % absolute residual longitudinal magnetization (|MZ/M0|) over ranges of B0 and [Formula: see text] (B1 scale factor) inhomogeneity found at 1.5 T and 3 T. Design parameters for an adiabatic BIR4-90 pulse were optimized for improved performance within 1.5 T B0 (±120 Hz) and [Formula: see text] (0.7-1.0) ranges. Flip angles in hard pulse trains of 3-6 pulses were optimized for 1.5 T and 3 T, with consideration of T1 values, field inhomogeneities (B0 = ±240 Hz and [Formula: see text]=0.4-1.2 at 3 T), and maximum achievable B1 field strength. Residual MZ/M0 was simulated and measured experimentally for current standard and optimized saturation pulses in phantoms and in-vivo human studies. T1 maps were acquired at 3 T in human subjects and a swine using a SAturation recovery single-SHot Acquisition (SASHA) technique with a standard 90°-90°-90° and an optimized 6-pulse train. Measured residual MZ/M0 in phantoms had excellent agreement with simulations over a wide range of B0 and [Formula: see text]. The optimized BIR4-90 reduced the maximum residual |MZ/M0| to <1 %, a 5.8× reduction compared to a reference BIR4-90. An optimized 3-pulse train achieved a maximum residual |MZ/M0| <1 % for the 1.5 T optimization range compared to 11.3 % for a standard 90°-90°-90° pulse train, while a 6-pulse train met this target for the wider 3 T ranges of B0 and [Formula: see text]. The 6-pulse train demonstrated more uniform saturation across both the myocardium and entire field of view than other saturation pulses in human studies. T1 maps were more spatially homogeneous with 6-pulse train SASHA than the reference 90°-90°-90° SASHA in both

Mapping of a disease susceptibility locus in chromosome 6p in Japanese patients with ulcerative colitis.

PubMed

Nomura, E; Kinouchi, Y; Negoro, K; Kojima, Y; Oomori, S; Sugimura, M; Hiroki, M; Takagi, S; Aihara, H; Takahashi, S; Hiwatashi, N; Shimosegawa, T

2004-09-01

Ulcerative colitis (UC) is a multifactorial disorder with both genetic and environmental factors. HLA-B*52 and DRB1*1502 are reported to be strongly associated with UC in Japan. However, the actual susceptible gene has not been identified yet. In this study, to map precisely the susceptible locus for UC, we performed association mapping in the chromosome 6p using 24 microsatellite markers distributed over 16 Mb. A total of 183 patients with UC and 186 healthy controls (HC) were included in this study. In all, 15 markers around the human leukocyte antigen (HLA) region showed statistical significance in the genotypic differentiation test concerned with the allelic distribution between the UC and HC. Especially, the markers between the centromeric region of HLA class I and the telomeric region of class III showed remarkably low P-values and the allele239 of C2-4-4 in class I marker showed the strongest association (Pc=2.9 x 10(-9): OR=3.74, 95% CI=2.50-5.60). Furthermore, we found strong linkage disequilibrium (LD) between the allele239 of C2-4-4 and HLA-B*52 in haplotype analysis. These results provide evidence that, in Japanese, important determinants of disease susceptibility to UC may exist in HLA, especially between the centromeric region of class I and the telomeric region of class III, under the strong LD with HLA-B*52.

Quantitative DNA fiber mapping

DOEpatents

Gray, Joe W.; Weier, Heinz-Ulrich G.

1998-01-01

The present invention relates generally to the DNA mapping and sequencing technologies. In particular, the present invention provides enhanced methods and compositions for the physical mapping and positional cloning of genomic DNA. The present invention also provides a useful analytical technique to directly map cloned DNA sequences onto individual stretched DNA molecules.

In silico mapping of quantitative trait loci in maize.

PubMed

Parisseaux, B; Bernardo, R

2004-08-01

Quantitative trait loci (QTL) are most often detected through designed mapping experiments. An alternative approach is in silico mapping, whereby genes are detected using existing phenotypic and genomic databases. We explored the usefulness of in silico mapping via a mixed-model approach in maize (Zea mays L.). Specifically, our objective was to determine if the procedure gave results that were repeatable across populations. Multilocation data were obtained from the 1995-2002 hybrid testing program of Limagrain Genetics in Europe. Nine heterotic patterns comprised 22,774 single crosses. These single crosses were made from 1,266 inbreds that had data for 96 simple sequence repeat (SSR) markers. By a mixed-model approach, we estimated the general combining ability effects associated with marker alleles in each heterotic pattern. The numbers of marker loci with significant effects--37 for plant height, 24 for smut [Ustilago maydis (DC.) Cda.] resistance, and 44 for grain moisture--were consistent with previous results from designed mapping experiments. Each trait had many loci with small effects and few loci with large effects. For smut resistance, a marker in bin 8.05 on chromosome 8 had a significant effect in seven (out of a maximum of 18) instances. For this major QTL, the maximum effect of an allele substitution ranged from 5.4% to 41.9%, with an average of 22.0%. We conclude that in silico mapping via a mixed-model approach can detect associations that are repeatable across different populations. We speculate that in silico mapping will be more useful for gene discovery than for selection in plant breeding programs. Copyright 2004 Springer-Verlag

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

PubMed

Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati; Robillard, Lilliane; Barthelet, Antoine; Lin, Kevin K; Shah, Khyati N; Simmons, Andy D; Raponi, Mitch; Harding, Thomas C; Bandyopadhyay, Sourav

2018-04-17

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Heterogeneity mapping of protein expression in tumors using quantitative immunofluorescence.

PubMed

Faratian, Dana; Christiansen, Jason; Gustavson, Mark; Jones, Christine; Scott, Christopher; Um, InHwa; Harrison, David J

2011-10-25

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor(1,2), and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension(3), or on macrodissection(4). A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue(5), providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative

High-throughput SNP genotyping in Cucurbita pepo for map construction and quantitative trait loci mapping

PubMed Central

2012-01-01

Background Cucurbita pepo is a member of the Cucurbitaceae family, the second- most important horticultural family in terms of economic importance after Solanaceae. The "summer squash" types, including Zucchini and Scallop, rank among the highest-valued vegetables worldwide. There are few genomic tools available for this species. The first Cucurbita transcriptome, along with a large collection of Single Nucleotide Polymorphisms (SNP), was recently generated using massive sequencing. A set of 384 SNP was selected to generate an Illumina GoldenGate assay in order to construct the first SNP-based genetic map of Cucurbita and map quantitative trait loci (QTL). Results We herein present the construction of the first SNP-based genetic map of Cucurbita pepo using a population derived from the cross of two varieties with contrasting phenotypes, representing the main cultivar groups of the species' two subspecies: Zucchini (subsp. pepo) × Scallop (subsp. ovifera). The mapping population was genotyped with 384 SNP, a set of selected EST-SNP identified in silico after massive sequencing of the transcriptomes of both parents, using the Illumina GoldenGate platform. The global success rate of the assay was higher than 85%. In total, 304 SNP were mapped, along with 11 SSR from a previous map, giving a map density of 5.56 cM/marker. This map was used to infer syntenic relationships between C. pepo and cucumber and to successfully map QTL that control plant, flowering and fruit traits that are of benefit to squash breeding. The QTL effects were validated in backcross populations. Conclusion Our results show that massive sequencing in different genotypes is an excellent tool for SNP discovery, and that the Illumina GoldenGate platform can be successfully applied to constructing genetic maps and performing QTL analysis in Cucurbita. This is the first SNP-based genetic map in the Cucurbita genus and is an invaluable new tool for biological research, especially considering that most

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations.

PubMed

Swaminathan, Sivakumar; Abeysekara, Nilwala S; Knight, Joshua M; Liu, Min; Dong, Jia; Hudson, Matthew E; Bhattacharyya, Madan K; Cianzio, Silvia R

2018-05-01

Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars. Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing 'A95-684043', a high-yielding maturity group (MG) II line resistant to SCN, with 'LS94-3207' and 'LS98-0582' of MG IV, resistant to both F. virguliforme and SCN. Two hundred F 7 derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis.

PubMed

García-Nieto, Pablo E; Schwartz, Erin K; King, Devin A; Paulsen, Jonas; Collas, Philippe; Herrera, Rafael E; Morrison, Ashby J

2017-10-02

The development of many sporadic cancers is directly initiated by carcinogen exposure. Carcinogens induce malignancies by creating DNA lesions (i.e., adducts) that can result in mutations if left unrepaired. Despite this knowledge, there has been remarkably little investigation into the regulation of susceptibility to acquire DNA lesions. In this study, we present the first quantitative human genome-wide map of DNA lesions induced by ultraviolet (UV) radiation, the ubiquitous carcinogen in sunlight that causes skin cancer. Remarkably, the pattern of carcinogen susceptibility across the genome of primary cells significantly reflects mutation frequency in malignant melanoma. Surprisingly, DNase-accessible euchromatin is protected from UV, while lamina-associated heterochromatin at the nuclear periphery is vulnerable. Many cancer driver genes have an intrinsic increase in carcinogen susceptibility, including the BRAF oncogene that has the highest mutation frequency in melanoma. These findings provide a genome-wide snapshot of DNA injuries at the earliest stage of carcinogenesis. Furthermore, they identify carcinogen susceptibility as an origin of genome instability that is regulated by nuclear architecture and mirrors mutagenesis in cancer. © 2017 The Authors.

Use of single nucleotide polymorphisms (SNP) to fine-map quantitative trait loci (QTL) in swine

USDA-ARS?s Scientific Manuscript database

Mapping quantitative trait loci (QTL) in swine at the US Meat Animal Research Center has relied heavily on linkage mapping in either F2 or Backcross families. QTL identified in the initial scans typically have very broad confidence intervals and further refinement of the QTL’s position is needed bef...

Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

NASA Astrophysics Data System (ADS)

Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

2017-04-01

The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

PubMed Central

Horne, Hisani N.; Chung, Charles C.; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Hopper, John L.; Southey, Melissa C.; Schmidt, Marjanka K.; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A.; Beckmann, Matthias W.; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J.; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E.; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K.; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V.; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H.; ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J.; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; Haiman, Christopher A.; Marchand, Loic Le; Goldberg, Mark S.; Teo, Soo H.; Taib, Nur A. M.; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L.; Knight, Julia A.; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W. M.; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S.; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D. P.

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive. PMID:27556229

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus.

PubMed

Horne, Hisani N; Chung, Charles C; Zhang, Han; Yu, Kai; Prokunina-Olsson, Ludmila; Michailidou, Kyriaki; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Hopper, John L; Southey, Melissa C; Schmidt, Marjanka K; Broeks, Annegien; Muir, Kenneth; Lophatananon, Artitaya; Fasching, Peter A; Beckmann, Matthias W; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; Benitez, Javier; González-Neira, Anna; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Arndt, Volker; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Nevanlinna, Heli; Khan, Sofia; Matsuo, Keitaro; Iwata, Hiroji; Dörk, Thilo; Bogdanova, Natalia V; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Chenevix-Trench, Georgia; Wu, Anna H; Ven den Berg, David; Smeets, Ann; Zhao, Hui; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Barile, Monica; Couch, Fergus J; Vachon, Celine; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Marchand, Loic Le; Goldberg, Mark S; Teo, Soo H; Taib, Nur A M; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Zheng, Wei; Shrubsole, Martha; Winqvist, Robert; Jukkola-Vuorinen, Arja; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; García-Closas, Montserrat; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; Martens, John W M; Li, Jingmei; Lu, Wei; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Shah, Mitul; Luccarini, Craig; Baynes, Caroline; Harrington, Patricia; Kang, Daehee; Choi, Ji-Yeob; Hartman, Mikael; Chia, Kee Seng; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Sangrajrang, Suleeporn; Brennan, Paul; Slager, Susan; Yannoukakos, Drakoulis; Shen, Chen-Yang; Hou, Ming-Feng; Swerdlow, Anthony; Orr, Nick; Simard, Jacques; Hall, Per; Pharoah, Paul D P; Easton, Douglas F; Chanock, Stephen J; Dunning, Alison M; Figueroa, Jonine D

2016-01-01

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

New Tool Quantitatively Maps Minority-Carrier Lifetime of Multicrystalline Silicon Bricks (Fact Sheet)

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

Not Available

2011-11-01

NREL's new imaging tool could provide manufacturers with insight on their processes. Scientists at the National Renewable Energy Laboratory (NREL) have used capabilities within the Process Development and Integration Laboratory (PDIL) to generate quantitative minority-carrier lifetime maps of multicrystalline silicon (mc-Si) bricks. This feat has been accomplished by using the PDIL's photoluminescence (PL) imaging system in conjunction with transient lifetime measurements obtained using a custom NREL-designed resonance-coupled photoconductive decay (RCPCD) system. PL imaging can obtain rapid high-resolution images that provide a qualitative assessment of the material lifetime-with the lifetime proportional to the pixel intensity. In contrast, the RCPCD technique providesmore » a fast quantitative measure of the lifetime with a lower resolution and penetrates millimeters into the mc-Si brick, providing information on bulk lifetimes and material quality. This technique contrasts with commercially available minority-carrier lifetime mapping systems that use microwave conductivity measurements. Such measurements are dominated by surface recombination and lack information on the material quality within the bulk of the brick. By combining these two complementary techniques, we obtain high-resolution lifetime maps at very fast data acquisition times-attributes necessary for a production-based diagnostic tool. These bulk lifetime measurements provide manufacturers with invaluable feedback on their silicon ingot casting processes. NREL has been applying the PL images of lifetime in mc-Si bricks in collaboration with a U.S. photovoltaic industry partner through Recovery Act Funded Project ARRA T24. NREL developed a new tool to quantitatively map minority-carrier lifetime of multicrystalline silicon bricks by using photoluminescence imaging in conjunction with resonance-coupled photoconductive decay measurements. Researchers are not hindered by surface recombination and can

The Calcitonin Receptor Gene Is a Candidate for Regulation of Susceptibility to Herpes simplex Type 1 Neuronal Infection Leading to Encephalitis in Rat

PubMed Central

Abdelmagid, Nada; Bereczky-Veress, Biborka; Guerreiro-Cacais, André Ortlieb; Bergman, Petra; Luhr, Katarina M.; Bergström, Tomas; Sköldenberg, Birgit; Piehl, Fredrik

2012-01-01

Herpes simplex encephalitis (HSE) is a fatal infection of the central nervous system (CNS) predominantly caused by Herpes simplex virus type 1. Factors regulating the susceptibility to HSE are still largely unknown. To identify host gene(s) regulating HSE susceptibility we performed a genome-wide linkage scan in an intercross between the susceptible DA and the resistant PVG rat. We found one major quantitative trait locus (QTL), Hse1, on rat chromosome 4 (confidence interval 24.3–31 Mb; LOD score 29.5) governing disease susceptibility. Fine mapping of Hse1 using recombinants, haplotype mapping and sequencing, as well as expression analysis of all genes in the interval identified the calcitonin receptor gene (Calcr) as the main candidate, which also is supported by functional studies. Thus, using unbiased genetic approach variability in Calcr was identified as potentially critical for infection and viral spread to the CNS and subsequent HSE development. PMID:22761571

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

Analyzing the texture changes in the quantitative phase maps of adipocytes

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Preliminary maps of Quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay region, California: a digital database

USGS Publications Warehouse

Knudsen, Keith L.; Sowers, Janet M.; Witter, Robert C.; Wentworth, Carl M.; Helley, Edward J.; Nicholson, Robert S.; Wright, Heather M.; Brown, Katherine H.

2000-01-01

This report presents a preliminary map and database of Quaternary deposits and liquefaction susceptibility for the nine-county San Francisco Bay region, together with a digital compendium of ground effects associated with past earthquakes in the region. The report consists of (1) a spatial database of fivedata layers (Quaternary deposits, quadrangle index, and three ground effects layers) and two text layers (a labels and leaders layer for Quaternary deposits and for ground effects), (2) two small-scale colored maps (Quaternary deposits and liquefaction susceptibility), (3) a text describing the Quaternary map, liquefaction interpretation, and the ground effects compendium, and (4) the databse description pamphlet. The nine counties surrounding San Francisco Bay straddle the San Andreas fault system, which exposes the region to serious earthquake hazard (Working Group on California Earthquake Probabilities, 1999). Much of the land adjacent to the Bay and the major rivers and streams is underlain by unconsolidated deposits that are particularly vulnerable to earthquake shaking and liquefaction of water-saturated granular sediment. This new map provides a modern and regionally consistent treatment of Quaternary surficial deposits that builds on the pioneering mapping of Helley and Lajoie (Helley and others, 1979) and such intervening work as Atwater (1982), Helley and others (1994), and Helley and Graymer (1997a and b). Like these earlier studies, the current mapping uses geomorphic expression, pedogenic soils, and inferred depositional environments to define and distinguish the map units. In contrast to the twelve map units of Helley and Lajoie, however, this new map uses a complex stratigraphy of some forty units, which permits a more realistic portrayal of the Quaternary depositional system. The two colored maps provide a regional summary of the new mapping at a scale of 1:275,000, a scale that is sufficient to show the general distribution and relationships of

Mapping quantitative trait loci for binary trait in the F2:3 design.

PubMed

Zhu, Chengsong; Zhang, Yuan-Ming; Guo, Zhigang

2008-12-01

In the analysis of inheritance of quantitative traits with low heritability, an F(2:3) design that genotypes plants in F(2) and phenotypes plants in F(2:3) progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F(2:3) design have been well developed, those for binary traits of biological interest and economic importance are seldom addressed. In this study, an attempt was made to map binary trait loci (BTL) in the F(2:3) design. The fundamental idea was: the F(2) plants were genotyped, all phenotypic values of each F(2:3) progeny were measured for binary trait, and these binary trait values and the marker genotype informations were used to detect BTL under the penetrance and liability models. The proposed method was verified by a series of Monte-Carlo simulation experiments. These results showed that maximum likelihood approaches under the penetrance and liability models provide accurate estimates for the effects and the locations of BTL with high statistical power, even under of low heritability. Moreover, the penetrance model is as efficient as the liability model, and the F(2:3) design is more efficient than classical F(2) design, even though only a single progeny is collected from each F(2:3) family. With the maximum likelihood approaches under the penetrance and the liability models developed in this study, we can map binary traits as we can do for quantitative trait in the F(2:3) design.

Evaluating the Variations in the Flood Susceptibility Maps Accuracies due to the Alterations in the Type and Extent of the Flood Inventory

NASA Astrophysics Data System (ADS)

Tehrany, M. Sh.; Jones, S.

2017-10-01

This paper explores the influence of the extent and density of the inventory data on the final outcomes. This study aimed to examine the impact of different formats and extents of the flood inventory data on the final susceptibility map. An extreme 2011 Brisbane flood event was used as the case study. LR model was applied using polygon and point formats of the inventory data. Random points of 1000, 700, 500, 300, 100 and 50 were selected and susceptibility mapping was undertaken using each group of random points. To perform the modelling Logistic Regression (LR) method was selected as it is a very well-known algorithm in natural hazard modelling due to its easily understandable, rapid processing time and accurate measurement approach. The resultant maps were assessed visually and statistically using Area under Curve (AUC) method. The prediction rates measured for susceptibility maps produced by polygon, 1000, 700, 500, 300, 100 and 50 random points were 63 %, 76 %, 88 %, 80 %, 74 %, 71 % and 65 % respectively. Evidently, using the polygon format of the inventory data didn't lead to the reasonable outcomes. In the case of random points, raising the number of points consequently increased the prediction rates, except for 1000 points. Hence, the minimum and maximum thresholds for the extent of the inventory must be set prior to the analysis. It is concluded that the extent and format of the inventory data are also two of the influential components in the precision of the modelling.

Mapping debris flow susceptibility using analytical network process in Kodaikkanal Hills, Tamil Nadu (India)

NASA Astrophysics Data System (ADS)

Sujatha, Evangelin Ramani; Sridhar, Venkataramana

2017-12-01

Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds > 10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the stage for the event are the availability of materials, type of materials, stream power, slope gradient, aspect and curvature, lithology, land use and land cover, lineament density, and drainage. Rainfall is the most common triggering factor that causes debris flow in the Palar subwatershed and seismicity is not considered as it is a stable continental region and moderate seismic zone. Also, there are no records of major seismic activities in the past. In this study, one of the less explored heuristic methods known as the analytical network process (ANP) is used to map the spatial propensity of debris flow. This method is based on top-down decision model and is a multi-criteria, decision-making tool that translates subjective assessment of relative importance to weights or scores and is implemented in the Palar subwatershed which is part of the Western Ghats in southern India. The results suggest that the factors influencing debris flow susceptibility in this region are the availability of material on the slope, peak flow, gradient of the slope, land use and land cover, and proximity to streams. Among all, peak discharge is identified as the chief factor causing debris flow. The use of micro-scale watersheds demonstrated in this study to develop the susceptibility map can be very effective for local level planning and land management.

Improving fieldwork by using GIS for quantitative exploration, data management and digital mapping

NASA Astrophysics Data System (ADS)

Marra, Wouter; Alberti, Koko; van de Grint, Liesbeth; Karssenberg, Derek

2016-04-01

Fieldwork is an essential part of teaching geosciences. The essence of a fieldwork is to study natural phenomena in its proper context. Fieldworks dominantly utilize a learning-by-experiencing learning style and are often light on abstract thinking skills. We introduce more of the latter skills to a first-year fieldwork of several weeks by using Geographical Information Systems (GIS). We use simple techniques as the involved students had no prior experience with GIS. In our project, we introduced new tutorials prior to the fieldwork where students explored their research area using aerial photos, satellite images, an elevation model and slope-map using Google Earth and QGIS. The goal of these tutorials was to get acquainted with the area, plan the first steps of the fieldwork, and formulate hypotheses in form of a preliminary map based on quantitative data. During the actual fieldwork, half of the students processed and managed their field data using GIS, used elevation data as additional data source, and made digital geomorphological maps. This was in contrast to the other half of the students that used classic techniques with paper maps. We evaluated the learning benefits by two questionnaires (one before and one after the fieldwork), and a group interview with students that used GIS in the field. Students liked the use of Google Earth and GIS, and many indicate the added value of using quantitative maps. The hypotheses and fieldwork plans of the students were quickly superseded by insights during the fieldwork itself, but making these plans and hypotheses in advance improved the student's ability to perform empirical research. Students were very positive towards the use of GIS for their fieldwork, mainly because they experienced it as a modern and relevant technique for research and the labour market. Tech-savvy students were extra motivated and explored additional methods. There were some minor technical difficulties with using GIS during the fieldwork, but

A GIS-based automated procedure for landslide susceptibility mapping by the Conditional Analysis method: the Baganza valley case study (Italian Northern Apennines)

NASA Astrophysics Data System (ADS)

Clerici, Aldo; Perego, Susanna; Tellini, Claudio; Vescovi, Paolo

2006-08-01

Among the many GIS based multivariate statistical methods for landslide susceptibility zonation, the so called “Conditional Analysis method” holds a special place for its conceptual simplicity. In fact, in this method landslide susceptibility is simply expressed as landslide density in correspondence with different combinations of instability-factor classes. To overcome the operational complexity connected to the long, tedious and error prone sequence of commands required by the procedure, a shell script mainly based on the GRASS GIS was created. The script, starting from a landslide inventory map and a number of factor maps, automatically carries out the whole procedure resulting in the construction of a map with five landslide susceptibility classes. A validation procedure allows to assess the reliability of the resulting model, while the simple mean deviation of the density values in the factor class combinations, helps to evaluate the goodness of landslide density distribution. The procedure was applied to a relatively small basin (167 km2) in the Italian Northern Apennines considering three landslide types, namely rotational slides, flows and complex landslides, for a total of 1,137 landslides, and five factors, namely lithology, slope angle and aspect, elevation and slope/bedding relations. The analysis of the resulting 31 different models obtained combining the five factors, confirms the role of lithology, slope angle and slope/bedding relations in influencing slope stability.

Susceptibility quantitative trait loci for pathogenic leucocytosis in SCG/Kj mice, a spontaneously occurring crescentic glomerulonephritis and vasculitis model

PubMed Central

Hamano, Y; Abe, M; Matsuoka, S; Zhang, D; Kondo, Y; Kagami, Y; Ishigami, A; Maruyama, N; Tsuruta, Y; Yumura, W; Suzuki, K

2014-01-01

The spontaneous crescentic glomerulonephritis-forming/Kinjoh (SCG/Kj) mouse, a model of human crescentic glomerulonephritis (CrGN) and systemic vasculitis, is characterized by the production of myeloperoxidase-specific anti-neutrophil cytoplasmic autoantibody (MPO-ANCA) and marked leucocytosis. This study was performed to identify the specific populations of leucocytes associated with CrGN and susceptibility loci for pathogenic leucocytosis. Four hundred and twenty female (C57BL/6 × SCG/Kj) F2 intercross mice were subjected to serial flow cytometry examination of the peripheral blood (PB). Kidney granulocytes and monocytes were examined histopathologically. Linkage analyses were performed with 109 polymorphic microsatellite markers. Correlation studies revealed that increase of the granulocytes, F4/80+ cells, CD3+CD4−CD8− T cells and dendritic cells (DCs) in peripheral blood (PB) were associated significantly with glomerulonephritis, crescent formation and vasculitis. In kidney sections, F4/80low cells were observed in crescent, while F4/80high cells were around the Bowman's capsules and in the interstitium. Numbers of F4/80+ cells in crescents correlated significantly with F4/80+ cell numbers in PB, but not with numbers of F4/80+ cells in the interstitium. Genome-wide quantitative trait locus (QTL) mapping revealed three SCG/Kj-derived non-Fas QTLs for leucocytosis, two on chromosome 1 and one on chromosome 17. QTLs on chromosome 1 affected DCs, granulocytes and F4/80+ cells, but QTL on chromosome 17 affected DCs and granulocytes. We found CrGN-associated leucocytes and susceptibility QTLs with their positional candidate genes. F4/80+ cells in crescents are considered as recruited inflammatory macrophages. The results provide information for leucocytes to be targeted and genetic elements in CrGN and vasculitis. PMID:24654803

Susceptibility quantitative trait loci for pathogenic leucocytosis in SCG/Kj mice, a spontaneously occurring crescentic glomerulonephritis and vasculitis model.

PubMed

Hamano, Y; Abe, M; Matsuoka, S; Zhang, D; Kondo, Y; Kagami, Y; Ishigami, A; Maruyama, N; Tsuruta, Y; Yumura, W; Suzuki, K

2014-07-01

The spontaneous crescentic glomerulonephritis-forming/Kinjoh (SCG/Kj) mouse, a model of human crescentic glomerulonephritis (CrGN) and systemic vasculitis, is characterized by the production of myeloperoxidase-specific anti-neutrophil cytoplasmic autoantibody (MPO-ANCA) and marked leucocytosis. This study was performed to identify the specific populations of leucocytes associated with CrGN and susceptibility loci for pathogenic leucocytosis. Four hundred and twenty female (C57BL/6 × SCG/Kj) F2 intercross mice were subjected to serial flow cytometry examination of the peripheral blood (PB). Kidney granulocytes and monocytes were examined histopathologically. Linkage analyses were performed with 109 polymorphic microsatellite markers. Correlation studies revealed that increase of the granulocytes, F4/80(+) cells, CD3(+) CD4(-) CD8(-) T cells and dendritic cells (DCs) in peripheral blood (PB) were associated significantly with glomerulonephritis, crescent formation and vasculitis. In kidney sections, F4/80(low) cells were observed in crescent, while F4/80(high) cells were around the Bowman's capsules and in the interstitium. Numbers of F4/80(+) cells in crescents correlated significantly with F4/80(+) cell numbers in PB, but not with numbers of F4/80(+) cells in the interstitium. Genome-wide quantitative trait locus (QTL) mapping revealed three SCG/Kj-derived non-Fas QTLs for leucocytosis, two on chromosome 1 and one on chromosome 17. QTLs on chromosome 1 affected DCs, granulocytes and F4/80(+) cells, but QTL on chromosome 17 affected DCs and granulocytes. We found CrGN-associated leucocytes and susceptibility QTLs with their positional candidate genes. F4/80(+) cells in crescents are considered as recruited inflammatory macrophages. The results provide information for leucocytes to be targeted and genetic elements in CrGN and vasculitis. © 2014 British Society for Immunology.

Evaluation of MRI sequences for quantitative T1 brain mapping

NASA Astrophysics Data System (ADS)

Tsialios, P.; Thrippleton, M.; Glatz, A.; Pernet, C.

2017-11-01

T1 mapping constitutes a quantitative MRI technique finding significant application in brain imaging. It allows evaluation of contrast uptake, blood perfusion, volume, providing a more specific biomarker of disease progression compared to conventional T1-weighted images. While there are many techniques for T1-mapping there is a wide range of reported T1-values in tissues, raising the issue of protocols reproducibility and standardization. The gold standard for obtaining T1-maps is based on acquiring IR-SE sequence. Widely used alternative sequences are IR-SE-EPI, VFA (DESPOT), DESPOT-HIFI and MP2RAGE that speed up scanning and fitting procedures. A custom MRI phantom was used to assess the reproducibility and accuracy of the different methods. All scans were performed using a 3T Siemens Prisma scanner. The acquired data processed using two different codes. The main difference was observed for VFA (DESPOT) which grossly overestimated T1 relaxation time by 214 ms [126 270] compared to the IR-SE sequence. MP2RAGE and DESPOT-HIFI sequences gave slightly shorter time than IR-SE (~20 to 30ms) and can be considered as alternative and time-efficient methods for acquiring accurate T1 maps of the human brain, while IR-SE-EPI gave identical result, at a cost of a lower image quality.

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. III

Treesearch

Kathleen D. Jermstad; Daniel L. Bassoni; Keith S. Jech; Gary A. Ritchie; Nicholas C. Wheeler; David B. Neale

2003-01-01

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring...

Susceptibility and triggering scenarios at a regional scale for shallow landslides

NASA Astrophysics Data System (ADS)

Gullà, G.; Antronico, L.; Iaquinta, P.; Terranova, O.

2008-07-01

The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an ˜ 15,075 km 2 extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing. Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors. The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps. On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility. Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been

Landslide susceptibility mapping in Mawat area, Kurdistan Region, NE Iraq: a comparison of different statistical models

NASA Astrophysics Data System (ADS)

Othman, A. A.; Gloaguen, R.; Andreani, L.; Rahnama, M.

2015-03-01

During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate hazard assessment. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damage due to mass wasting. The aim of this study is to evaluate and compare frequency ratio (FR), weight of evidence (WOE), logistic regression (LR) and probit regression (PR) approaches in combination with new geomorphological indices to determine the landslide susceptibility index (LSI). We tested these four methods in Mawat area, Kurdistan Region, NE Iraq, where landslides occur frequently. For this purpose, we evaluated 16 geomorphological, geological and environmental predicting factors mainly derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite. The available reference inventory includes 351 landslides representing a cumulative surface of 3.127 km2. This reference inventory was mapped from QuickBird data by manual delineation and partly verified by field survey. The areas under curve (AUC) of the receiver operating characteristic (ROC), and relative landslide density (R index) show that all models perform similarly and that focus should be put on the careful selection of proxies. The results indicate that the lithology and the slope aspects play major roles for landslide occurrences. Furthermore, this paper demonstrates that using hypsometric integral as a prediction factor instead of slope curvature gives better results and increases the accuracy of the LSI.

Quantitative EPMA Compositional Mapping of NWA 2995: Characterization, and Petrologic Interpretation of Mafic Clasts

NASA Technical Reports Server (NTRS)

Carpenter, P. K.; Hahn, T. M.; Korotev, R. L.; Ziegler, R. A.; Jolliff, B. L.

2017-01-01

We present the first fully quantitative compositional maps of lunar meteorite NWA 2995 using electron microprobe stage mapping, and compare selected clast mineralogy and chemistry. NWA 2995 is a feldspathic fragmental breccia containing numerous highland fine grained lithologies, including anorthosite, norite, olivine basalt, subophitic basalt, gabbro, KREEP-like basalt, granulitic and glassy impact melts, coarse-grained mineral fragments, Fe-Ni metal, and glassy matrix [1]. Chips of NWA 2995, representing these diverse materials, were analyzed by INAA and fused-bead electron-probe microanalysis (EPMA); comparison of analytical data suggests grouping of lunar meteorites NWA 2995, 2996, 3190, 4503, 5151, and 5152. The mean composition of NWA 2995 corresponds to a 2:1 mixture of feldspathic and mare material, with approximately 5% KREEP component [2]. Clast mineral chemistry and petrologic interpretation of paired stone NWA 2996 has been reported by Mercer et al. [3], and Gross et al. [4]. This study combines advances in quantitative EPMA compositional mapping and data analysis, as applied to selected mafic clasts in a polished section of NWA 2995, to investigate the origin of mafic lithic components and to demonstrate a procedural framework for petrologic analysis.

Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

NASA Astrophysics Data System (ADS)

Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.

2016-12-01

Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study

PubMed Central

Abdallah, Jihad M; Goffinet, Bruno; Cierco-Ayrolles, Christine; Pérez-Enciso, Miguel

2003-01-01

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance. PMID:12939203

Quantitative inference of population response properties across eccentricity from motion-induced maps in macaque V1

PubMed Central

Chen, Ming; Wu, Si; Lu, Haidong D.; Roe, Anna W.

2013-01-01

Interpreting population responses in the primary visual cortex (V1) remains a challenge especially with the advent of techniques measuring activations of large cortical areas simultaneously with high precision. For successful interpretation, a quantitatively precise model prediction is of great importance. In this study, we investigate how accurate a spatiotemporal filter (STF) model predicts average response profiles to coherently drifting random dot motion obtained by optical imaging of intrinsic signals in V1 of anesthetized macaques. We establish that orientation difference maps, obtained by subtracting orthogonal axis-of-motion, invert with increasing drift speeds, consistent with the motion streak effect. Consistent with perception, the speed at which the map inverts (the critical speed) depends on cortical eccentricity and systematically increases from foveal to parafoveal. We report that critical speeds and response maps to drifting motion are excellently reproduced by the STF model. Our study thus suggests that the STF model is quantitatively accurate enough to be used as a first model of choice for interpreting responses obtained with intrinsic imaging methods in V1. We show further that this good quantitative correspondence opens the possibility to infer otherwise not easily accessible population receptive field properties from responses to complex stimuli, such as drifting random dot motions. PMID:23197457

Reporting of quantitative oxygen mapping in EPR imaging

NASA Astrophysics Data System (ADS)

Subramanian, Sankaran; Devasahayam, Nallathamby; McMillan, Alan; Matsumoto, Shingo; Munasinghe, Jeeva P.; Saito, Keita; Mitchell, James B.; Chandramouli, Gadisetti V. R.; Krishna, Murali C.

2012-01-01

Oxygen maps derived from electron paramagnetic resonance spectral-spatial imaging (EPRI) are based upon the relaxivity of molecular oxygen with paramagnetic spin probes. This technique can be combined with MRI to facilitate mapping of pO 2 values in specific anatomic locations with high precision. The co-registration procedure, which matches the physical and digital dimensions of EPR and MR images, may present the pO 2 map at the higher MRI resolution, exaggerating the spatial resolution of oxygen, making it difficult to precisely distinguish hypoxic regions from normoxic regions. The latter distinction is critical in monitoring the treatment of cancer by radiation and chemotherapy, since it is well-established that hypoxic regions are three or four times more resistant to treatment compared to normoxic regions. The aim of this article is to describe pO 2 maps based on the intrinsic resolution of EPRI. A spectral parameter that affects the intrinsic spatial resolution of EPRI is the full width at half maximum (FWHM) height of the gradient-free EPR absorption line in frequency-encoded imaging. In single point imaging too, the transverse relaxation times (T2∗) limit the resolution since the signal decays by exp(-tp/T2∗) where the delay time after excitation pulse, t p, is related to the resolution. Although the spin densities of two point objects may be resolved at this separation, it is inadequate to evaluate quantitative changes of pO 2 levels since the linewidths are proportionately affected by pO 2. A spatial separation of at least twice this resolution is necessary to correctly identify a change in pO 2 level. In addition, the pO 2 values are blurred by uncertainties arising from spectral dimensions. Blurring due to noise and low resolution modulates the pO 2 levels at the boundaries of hypoxic and normoxic regions resulting in higher apparent pO 2 levels in hypoxic regions. Therefore, specification of intrinsic resolution and pO 2 uncertainties are

Simultaneous MR quantification of hepatic fat content, fatty acid composition, transverse relaxation time and magnetic susceptibility for the diagnosis of non-alcoholic steatohepatitis.

PubMed

Leporq, B; Lambert, S A; Ronot, M; Vilgrain, V; Van Beers, B E

2017-10-01

Non-alcoholic steatohepatitis (NASH) is characterized at histology by steatosis, hepatocyte ballooning and inflammatory infiltrates, with or without fibrosis. Although diamagnetic material in fibrosis and inflammation can be detected with quantitative susceptibility imaging, fatty acid composition changes in NASH relative to simple steatosis have also been reported. Therefore, our aim was to develop a single magnetic resonance (MR) acquisition and post-processing scheme for the diagnosis of steatohepatitis by the simultaneous quantification of hepatic fat content, fatty acid composition, T 2 * transverse relaxation time and magnetic susceptibility in patients with non-alcoholic fatty liver disease. MR acquisition was performed at 3.0 T using a three-dimensional, multi-echo, spoiled gradient echo sequence. Phase images were unwrapped to compute the B 0 field inhomogeneity (ΔB 0 ) map. The ΔB 0 -demodulated real part images were used for fat-water separation, T 2 * and fatty acid composition quantification. The external and internal fields were separated with the projection onto dipole field method. Susceptibility maps were obtained after dipole inversion from the internal field map with single-orientation Bayesian regularization including spatial priors. Method validation was performed in 32 patients with biopsy-proven, non-alcoholic fatty liver disease from which 12 had simple steatosis and 20 NASH. Liver fat fraction and T 2 * did not change significantly between patients with simple steatosis and NASH. In contrast, the saturated fatty acid fraction increased in patients with NASH relative to patients with simple steatosis (48 ± 2% versus 44 ± 4%; p < 0.05) and the magnetic susceptibility decreased (-0.30 ± 0.27 ppm versus 0.10 ± 0.14 ppm; p < 0.001). The area under the receiver operating characteristic curve for magnetic susceptibility as NASH marker was 0.91 (95% CI: 0.79-1.0). Simultaneous MR quantification of fat content, fatty acid

Mapping flood and flooding potential indices: a methodological approach to identifying areas susceptible to flood and flooding risk. Case study: the Prahova catchment (Romania)

NASA Astrophysics Data System (ADS)

Zaharia, Liliana; Costache, Romulus; Prăvălie, Remus; Ioana-Toroimac, Gabriela

2017-04-01

Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scales. Therefore, a basic phase is elaborating hazard and flood risk maps, documents which are an essential support for flood risk management. The aim of this paper is to develop an approach that allows for the identification of flash-flood and flood-prone susceptible areas based on computing and mapping of two indices: FFPI (Flash-Flood Potential Index) and FPI (Flooding Potential Index). These indices are obtained by integrating in a GIS environment several geographical variables which control runoff (in the case of the FFPI) and favour flooding (in the case of the FPI). The methodology was applied in the upper (mountainous) and middle (hilly) catchment of the Prahova River, a densely populated and socioeconomically well-developed area which has been affected repeatedly by water-related hazards over the past decades. The resulting maps showing the spatialization of the FFPI and FPI allow for the identification of areas with high susceptibility to flashfloods and flooding. This approach can provide useful mapped information, especially for areas (generally large) where there are no flood/hazard risk maps. Moreover, the FFPI and FPI maps can constitute a preliminary step for flood risk and vulnerability assessment.

Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion

NASA Astrophysics Data System (ADS)

Rahmati, Omid; Tahmasebipour, Nasser; Haghizadeh, Ali; Pourghasemi, Hamid Reza; Feizizadeh, Bakhtiar

2017-12-01

Gully erosion constitutes a serious problem for land degradation in a wide range of environments. The main objective of this research was to compare the performance of seven state-of-the-art machine learning models (SVM with four kernel types, BP-ANN, RF, and BRT) to model the occurrence of gully erosion in the Kashkan-Poldokhtar Watershed, Iran. In the first step, a gully inventory map consisting of 65 gully polygons was prepared through field surveys. Three different sample data sets (S1, S2, and S3), including both positive and negative cells (70% for training and 30% for validation), were randomly prepared to evaluate the robustness of the models. To model the gully erosion susceptibility, 12 geo-environmental factors were selected as predictors. Finally, the goodness-of-fit and prediction skill of the models were evaluated by different criteria, including efficiency percent, kappa coefficient, and the area under the ROC curves (AUC). In terms of accuracy, the RF, RBF-SVM, BRT, and P-SVM models performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.9), which resulted in accurate predictions. Therefore, these models can be used in other gully erosion studies, as they are capable of rapidly producing accurate and robust gully erosion susceptibility maps (GESMs) for decision-making and soil and water management practices. Furthermore, it was found that performance of RF and RBF-SVM for modelling gully erosion occurrence is quite stable when the learning and validation samples are changed.

The influence of brain iron and myelin on magnetic susceptibility and effective transverse relaxation - A biochemical and histological validation study.

PubMed

Hametner, Simon; Endmayr, Verena; Deistung, Andreas; Palmrich, Pilar; Prihoda, Max; Haimburger, Evelin; Menard, Christian; Feng, Xiang; Haider, Thomas; Leisser, Marianne; Köck, Ulrike; Kaider, Alexandra; Höftberger, Romana; Robinson, Simon; Reichenbach, Jürgen R; Lassmann, Hans; Traxler, Hannes; Trattnig, Siegfried; Grabner, Günther

2018-06-15

Quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2*) mapping are both highly sensitive to variations in brain iron content. Clinical Magnetic Resonance Imaging (MRI) studies report changes of susceptibilities and relaxation rates in various neurological diseases which are often equated with changes in regional brain iron content. However, these mentioned metrics lack specificity for iron, since they are also influenced by the presence of myelin. In this study, we assessed the extent to which QSM and R2* reflect iron concentration as well as histological iron and myelin intensities. Six unfixed human post-mortem brains were imaged in situ with a 7 T MRI scanner. After formalin fixation, the brains were sliced axially and punched. 671 tissue punches were subjected to ferrozine iron quantification. Subsequently, brain slices were embedded in paraffin, and histological double-hemispheric axial brain slices were stained for Luxol fast blue (myelin) and diaminobenzidine (DAB)-enhanced Turnbull blue (iron). 3331 regions of interest (ROIs) were drawn on the histological stainings to assess myelin and iron intensities, which were compared with MRI data in corresponding ROIs. QSM more closely reflected quantitative ferrozine iron values (r = 0.755 vs. 0.738), whereas R2* correlated better with iron staining intensities (r = 0.619 vs. 0.445). Myelin intensities correlated negatively with QSM (r = -0.352), indicating a diamagnetic effect of myelin on susceptibility. Myelin intensities were higher in the thalamus than in the basal ganglia. A significant relationship was nonetheless observed between quantitative iron values and QSM, confirming the applicability of the latter in this brain region for iron quantification. Copyright © 2018. Published by Elsevier Inc.

Imaging Cerebral Microhemorrhages in Military Service Members with Chronic Traumatic Brain Injury.

PubMed

Liu, Wei; Soderlund, Karl; Senseney, Justin S; Joy, David; Yeh, Ping-Hong; Ollinger, John; Sham, Elyssa B; Liu, Tian; Wang, Yi; Oakes, Terrence R; Riedy, Gerard

2016-02-01

To detect cerebral microhemorrhages in military service members with chronic traumatic brain injury by using susceptibility-weighted magnetic resonance (MR) imaging. The longitudinal evolution of microhemorrhages was monitored in a subset of patients by using quantitative susceptibility mapping. The study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants underwent two-dimensional conventional gradient-recalled-echo MR imaging and three-dimensional flow-compensated multiecho gradient-recalled-echo MR imaging (processed to generate susceptibility-weighted images and quantitative susceptibility maps), and a subset of patients underwent follow-up imaging. Microhemorrhages were identified by two radiologists independently. Comparisons of microhemorrhage number, size, and magnetic susceptibility derived from quantitative susceptibility maps between baseline and follow-up imaging examinations were performed by using the paired t test. Among the 603 patients, cerebral microhemorrhages were identified in 43 patients, with six excluded for further analysis owing to artifacts. Seventy-seven percent (451 of 585) of the microhemorrhages on susceptibility-weighted images had a more conspicuous appearance than on gradient-recalled-echo images. Thirteen of the 37 patients underwent follow-up imaging examinations. In these patients, a smaller number of microhemorrhages were identified at follow-up imaging compared with baseline on quantitative susceptibility maps (mean ± standard deviation, 9.8 microhemorrhages ± 12.8 vs 13.7 microhemorrhages ± 16.6; P = .019). Quantitative susceptibility mapping-derived quantitative measures of microhemorrhages also decreased over time: -0.85 mm(3) per day ± 1.59 for total volume (P = .039) and -0.10 parts per billion per day ± 0.14 for mean magnetic susceptibility (P = .016). The number of microhemorrhages and quantitative susceptibility

A Method for Comprehensive Glycosite-Mapping and Direct Quantitation of Serum Glycoproteins.

PubMed

Hong, Qiuting; Ruhaak, L Renee; Stroble, Carol; Parker, Evan; Huang, Jincui; Maverakis, Emanual; Lebrilla, Carlito B

2015-12-04

A comprehensive glycan map was constructed for the top eight abundant glycoproteins in plasma using both specific and nonspecific enzyme digestions followed by nano liquid chromatography (LC)-chip/quadrupole time-of-flight mass spectrometry (MS) analysis. Glycopeptides were identified using an in-house software tool, GPFinder. A sensitive and reproducible multiple reaction monitoring (MRM) technique on a triple quadrupole MS was developed and applied to quantify immunoglobulins G, A, M, and their site-specific glycans simultaneously and directly from human serum/plasma without protein enrichments. A total of 64 glycopeptides and 15 peptides were monitored for IgG, IgA, and IgM in a 20 min ultra high performance (UP)LC gradient. The absolute protein contents were quantified using peptide calibration curves. The glycopeptide ion abundances were normalized to the respective protein abundances to separate protein glycosylation from protein expression. This technique yields higher method reproducibility and less sample loss when compared with the quantitation method that involves protein enrichments. The absolute protein quantitation has a wide linear range (3-4 orders of magnitude) and low limit of quantitation (femtomole level). This rapid and robust quantitation technique, which provides quantitative information for both proteins and glycosylation, will further facilitate disease biomarker discoveries.

Integration of landslide susceptibility products in the environmental plans

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Reichenbach, Paola; Rossi, Mauro; Cardinali, Mauro; Guzzetti, Fausto

2015-04-01

Landslides are one of the most destructive natural hazard that causes damages to urban area worldwide. The knowledge of where a landslide could occur is essential for the strategic management of the territory and for a good urban planning . In this contest landslide susceptibility zoning (LSZ) is crucial to provide information on the degree to which an area can be affected by future slope movements. Despite landslide susceptibility maps have been prepared extensively during the last decades, there are few examples of application is in the environmental plans (EP). In this work we present a proposal for the integration of the landslide inventory map with the following landslide susceptibility products: (i) landslide susceptibility zonation , (ii) the associated error map and (iii) the susceptibility uncertainty map. Moreover we proposed to incorporate detailed morphological studies for the evaluation of landslide risk associated to local parceling plan. The integration of all this information is crucial for the management of landslide risk in urban expansions forecasts. Municipality, province and regional administration are often not able to support the costs of landslide risk evaluation for extensive areas but should concentrate their financial resources to specific hazardous and unsafe situations defined by the result of the integration of landslide susceptibility products. Zonation and detail morphological analysis should be performed taking into account the existing laws and regulations, and could become a starting point to discuss new regulations for the landslide risk management.

Mapping basin-wide subaquatic slope failure susceptibility as a tool to assess regional seismic and tsunami hazards

NASA Astrophysics Data System (ADS)

Strasser, Michael; Hilbe, Michael; Anselmetti, Flavio S.

2010-05-01

With increasing awareness of oceanic geohazards, submarine landslides are gaining wide attention because of their catastrophic impacts on both offshore infrastructures (e.g. pipelines, cables and platforms) and coastal areas (e.g. landslide-induced tsunamis). They also are of great interest because they can be directly related to primary trigger mechanisms including earthquakes, rapid sedimentation, gas release, glacial and tidal loading, wave action, or clathrate dissociation, many of which represent potential geohazards themselves. In active tectonic environments, for instance, subaquatic landslide deposits can be used to make inferences regarding the hazard derived from seismic activity. Enormous scientific and economic efforts are thus being undertaken to better determine and quantify causes and effects of natural hazards related to subaquatic landslides. In order to achieve this fundamental goal, the detailed study of past events, the assessment of their recurrence intervals and the quantitative reconstruction of magnitudes and intensities of both causal and subsequent processes and impacts are key requirements. Here we present data and results from a study using fjord-type Lake Lucerne in central Switzerland as a "model ocean" to test a new concept for the assessment of regional seismic and tsunami hazard by basin-wide mapping of critical slope stability conditions for subaquatic landslide initiation. Previously acquired high-resolution bathymetry and reflection seismic data as well as sedimentological and in situ geotechnical data, provide a comprehensive data base to investigate subaquatic landslides and related geohazards. Available data are implemented into a basin-wide slope model. In a Geographic Information System (GIS)-framework, a pseudo-static limit equilibrium infinite slope stability equation is solved for each model point representing reconstructed slope conditions at different times in the past, during which earthquake-triggered landslides

Landslide Hazard Assessment and Mapping in the Guil Catchment (Queyras, Southern French Alps): From Landslide Inventory to Susceptibility Modelling

NASA Astrophysics Data System (ADS)

Roulleau, Louise; Bétard, François; Carlier, Benoît; Lissak, Candide; Fort, Monique

2016-04-01

Landslides are common natural hazards in the Southern French Alps, where they may affect human lives and cause severe damages to infrastructures. As a part of the SAMCO research project dedicated to risk evaluation in mountain areas, this study focuses on the Guil river catchment (317 km2), Queyras, to assess landslide hazard poorly studied until now. In that area, landslides are mainly occasional, low amplitude phenomena, with limited direct impacts when compared to other hazards such as floods or snow avalanches. However, when interacting with floods during extreme rainfall events, landslides may have indirect consequences of greater importance because of strong hillslope-channel connectivity along the Guil River and its tributaries (i.e. positive feedbacks). This specific morphodynamic functioning reinforces the need to have a better understanding of landslide hazards and their spatial distribution at the catchment scale to prevent local population from disasters with multi-hazard origin. The aim of this study is to produce a landslide susceptibility mapping at 1:50 000 scale as a first step towards global estimation of landslide hazard and risk. The three main methodologies used for assessing landslide susceptibility are qualitative (i.e. expert opinion), deterministic (i.e. physics-based models) and statistical methods (i.e. probabilistic models). Due to the rapid development of geographical information systems (GIS) during the last two decades, statistical methods are today widely used because they offer a greater objectivity and reproducibility at large scales. Among them, multivariate analyses are considered as the most robust techniques, especially the logistic regression method commonly used in landslide susceptibility mapping. However, this method like others is strongly dependent on the accuracy of the input data to avoid significant errors in the final results. In particular, a complete and accurate landslide inventory is required before the modelling

Slope, Scarp and Sea Cliff Instability Susceptibility Mapping for Planning Regulations in Almada County, Portugal

NASA Astrophysics Data System (ADS)

Marques, Fernando; Queiroz, Sónia; Gouveia, Luís; Vasconcelos, Manuel

2017-12-01

In Portugal, the modifications introduced in 2008 and 2012 in the National Ecological Reserve law (REN) included the mandatory study of slope instability, including slopes, natural scarps, and sea cliffs, at municipal or regional scale, with the purpose of avoiding the use of hazardous zones with buildings and other structures. The law also indicates specific methods to perform these studies, with different approaches for slope instability, natural scarps and sea cliffs. The methods used to produce the maps required by REN law, with modifications and improvements to the law specified methods, were applied to the 71 km2 territory of Almada County, and included: 1) Slope instability mapping using the statistically based Information Value method validated with the landslide inventory using ROC curves, which provided an AAC=0.964, with the higher susceptibility zones which cover at least 80% of the landslides of the inventory to be included in REN map. The map was object of a generalization process to overcome the inconveniences of the use of a pixel based approach. 2) Natural scarp mapping including setback areas near the top, defined according to the law and setback areas near the toe defined by the application of the shadow angle calibrated with the major rockfalls which occurred in the study area; 3) Sea cliffs mapping including two levels of setback zones near the top, and one setback zone at the cliffs toe, which were based on systematic inventories of cliff failures occurred between 1947 and 2010 in a large scale regional littoral monitoring project. In the paper are described the methods used and the results obtained in this study, which correspond to the final maps of areas to include in REN. The results obtained in this study may be considered as an example of good practice of the municipal authorities in terms of solid, technical and scientifically supported regulation definitions, hazard prevention and safe and sustainable land use management.

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

PubMed Central

Zhang, Yin; Wang, Lei

2013-01-01

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

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

PubMed

Zhang, Yin; Wang, Lei; Diao, Tianxi

2013-12-01

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

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

PubMed

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I; Padyukov, Leonid; Toes, Rene E M; Huizinga, Tom W J; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I W; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert M; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-12-01

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Evaluation of Renal Oxygenation Level Changes after Water Loading Using Susceptibility-Weighted Imaging and T2* Mapping.

PubMed

Ding, Jiule; Xing, Wei; Wu, Dongmei; Chen, Jie; Pan, Liang; Sun, Jun; Xing, Shijun; Dai, Yongming

2015-01-01

To assess the feasibility of susceptibility-weighted imaging (SWI) while monitoring changes in renal oxygenation level after water loading. Thirty-two volunteers (age, 28.0 ± 2.2 years) were enrolled in this study. SWI and multi-echo gradient echo sequence-based T2(*) mapping were used to cover the kidney before and after water loading. Cortical and medullary parameters were measured using small regions of interest, and their relative changes due to water loading were calculated based on baseline and post-water loading data. An intraclass correlation coefficient analysis was used to assess inter-observer reliability of each parameter. A receiver operating characteristic curve analysis was conducted to compare the performance of the two methods for detecting renal oxygenation changes due to water loading. Both medullary phase and medullary T2(*) values increased after water loading (p < 0.001), although poor correlations were found between the phase changes and the T2(*) changes (p > 0.05). Interobserver reliability was excellent for the T2(*) values, good for SWI cortical phase values, and moderate for the SWI medullary phase values. The area under receiver operating characteristic curve of the SWI medullary phase values was 0.85 and was not different from the medullary T2(*) value (0.84). Susceptibility-weighted imaging enabled monitoring changes in the oxygenation level in the medulla after water loading, and may allow comparable feasibility to detect renal oxygenation level changes due to water loading compared with that of T2(*) mapping.

Integrated platform for genome-wide screening and construction of high-density genetic interaction maps in mammalian cells

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2013-01-01

A major challenge of the postgenomic era is to understand how human genes function together in normal and disease states. In microorganisms, high-density genetic interaction (GI) maps are a powerful tool to elucidate gene functions and pathways. We have developed an integrated methodology based on pooled shRNA screening in mammalian cells for genome-wide identification of genes with relevant phenotypes and systematic mapping of all GIs among them. We recently demonstrated the potential of this approach in an application to pathways controlling the susceptibility of human cells to the toxin ricin. Here we present the complete quantitative framework underlying our strategy, including experimental design, derivation of quantitative phenotypes from pooled screens, robust identification of hit genes using ultra-complex shRNA libraries, parallel measurement of tens of thousands of GIs from a single double-shRNA experiment, and construction of GI maps. We describe the general applicability of our strategy. Our pooled approach enables rapid screening of the same shRNA library in different cell lines and under different conditions to determine a range of different phenotypes. We illustrate this strategy here for single- and double-shRNA libraries. We compare the roles of genes for susceptibility to ricin and Shiga toxin in different human cell lines and reveal both toxin-specific and cell line-specific pathways. We also present GI maps based on growth and ricin-resistance phenotypes, and we demonstrate how such a comparative GI mapping strategy enables functional dissection of physical complexes and context-dependent pathways. PMID:23739767

Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides

NASA Astrophysics Data System (ADS)

Lee, Saro; Dan, Nguyen Tu

2005-09-01

This study evaluates the susceptibility of landslides in the Lai Chau province of Vietnam using Geographic Information System (GIS) and remote sensing data to focus on the relationship between tectonic fractures and landslides. Landslide locations were identified from aerial photographs and field surveys. Topographic, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image-processing techniques. A scheme of the tectonic fracturing of crust in the Lai Chau region was established. Lai Chau was identified as a region with many crustal fractures, where the grade of tectonic fracture is closely related to landslide occurrence. The influencing factors of landslide occurrence were: distance from a tectonic fracture, slope, aspect, curvature, soil, and vegetative land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using landslide location data and showed 83.47% prediction accuracy. That emphasized a strong relationship between the susceptibility map and the existing landslide location data. The results of this study can form a basis stable development and land use planning for the region.

Colorectal carcinoma: Ex vivo evaluation using 3-T high-spatial-resolution quantitative T2 mapping and its correlation with histopathologic findings.

PubMed

Yamada, Ichiro; Yoshino, Norio; Hikishima, Keigo; Miyasaka, Naoyuki; Yamauchi, Shinichi; Uetake, Hiroyuki; Yasuno, Masamichi; Saida, Yukihisa; Tateishi, Ukihide; Kobayashi, Daisuke; Eishi, Yoshinobu

2017-05-01

In this study, we aimed to evaluate the feasibility of determining the mural invasion depths of colorectal carcinomas using high-spatial-resolution (HSR) quantitative T2 mapping on a 3-T magnetic resonance (MR) scanner. Twenty colorectal specimens containing adenocarcinomas were imaged on a 3-T MR system equipped with a 4-channel phased-array surface coil. HSR quantitative T2 maps were acquired using a spin-echo sequence with a repetition time/echo time of 7650/22.6-361.6ms (16 echoes), 87×43.5-mm field of view, 2-mm section thickness, 448×224 matrix, and average of 1. HSR fast-spin-echo T2-weighted images were also acquired. Differences between the T2 values (ms) of the tumor tissue, colorectal wall layers, and fibrosis were measured, and the MR images and histopathologic findings were compared. In all specimens (20/20, 100%), the HSR quantitative T2 maps clearly depicted an 8-layer normal colorectal wall in which the T2 values of each layer differed from those of the adjacent layer(s) (P<0.001). Using this technique, fibrosis (73.6±9.4ms) and tumor tissue (104.2±6.4ms) could also be clearly differentiated (P<0.001). In 19 samples (95%), the HSR quantitative T2 maps and histopathologic data yielded the same findings regarding the tumor invasion depth. Our results indicate that 3-T HSR quantitative T2 mapping is useful for distinguishing colorectal wall layers and differentiating tumor and fibrotic tissues. Accordingly, this technique could be used to determine mural invasion by colorectal carcinomas with a high level of accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Quantitative Risk Mapping of Urban Gas Pipeline Networks Using GIS

NASA Astrophysics Data System (ADS)

Azari, P.; Karimi, M.

2017-09-01

Natural gas is considered an important source of energy in the world. By increasing growth of urbanization, urban gas pipelines which transmit natural gas from transmission pipelines to consumers, will become a dense network. The increase in the density of urban pipelines will influence probability of occurring bad accidents in urban areas. These accidents have a catastrophic effect on people and their property. Within the next few years, risk mapping will become an important component in urban planning and management of large cities in order to decrease the probability of accident and to control them. Therefore, it is important to assess risk values and determine their location on urban map using an appropriate method. In the history of risk analysis of urban natural gas pipeline networks, the pipelines has always been considered one by one and their density in urban area has not been considered. The aim of this study is to determine the effect of several pipelines on the risk value of a specific grid point. This paper outlines a quantitative risk assessment method for analysing the risk of urban natural gas pipeline networks. It consists of two main parts: failure rate calculation where the EGIG historical data are used and fatal length calculation that involves calculation of gas release and fatality rate of consequences. We consider jet fire, fireball and explosion for investigating the consequences of gas pipeline failure. The outcome of this method is an individual risk and is shown as a risk map.

Quantitative evaluation of dual-flip-angle T1 mapping on DCE-MRI kinetic parameter estimation in head and neck

PubMed Central

Chow, Steven Kwok Keung; Yeung, David Ka Wai; Ahuja, Anil T; King, Ann D

2012-01-01

Purpose To quantitatively evaluate the kinetic parameter estimation for head and neck (HN) dynamic contrast-enhanced (DCE) MRI with dual-flip-angle (DFA) T1 mapping. Materials and methods Clinical DCE-MRI datasets of 23 patients with HN tumors were included in this study. T1 maps were generated based on multiple-flip-angle (MFA) method and different DFA combinations. Tofts model parameter maps of kep, Ktrans and vp based on MFA and DFAs were calculated and compared. Fitted parameter by MFA and DFAs were quantitatively evaluated in primary tumor, salivary gland and muscle. Results T1 mapping deviations by DFAs produced remarkable kinetic parameter estimation deviations in head and neck tissues. In particular, the DFA of [2º, 7º] overestimated, while [7º, 12º] and [7º, 15º] underestimated Ktrans and vp, significantly (P<0.01). [2º, 15º] achieved the smallest but still statistically significant overestimation for Ktrans and vp in primary tumors, 32.1% and 16.2% respectively. kep fitting results by DFAs were relatively close to the MFA reference compared to Ktrans and vp. Conclusions T1 deviations induced by DFA could result in significant errors in kinetic parameter estimation, particularly Ktrans and vp, through Tofts model fitting. MFA method should be more reliable and robust for accurate quantitative pharmacokinetic analysis in head and neck. PMID:23289084

Multidisciplinary approach to evaluate landslide susceptibility along highway in northern Calabria, Italy

NASA Astrophysics Data System (ADS)

Muto, Francesco; Conforti, Massimo; Critelli, Salvatore; Fabbricatore, Davide; Filomena, Luciana; Rago, Valeria; Robustelli, Gaetano; Scarciglia, Fabio; Versace, Pasquale

2014-05-01

The interaction of landslides with linear infrastructures is often the cause of disasters. In Italy landslide impact on roads, railways and buildings cause millions of Euro per year in damage and restoration as well. The proposed study is aimed to the landslide susceptibility evaluation using a multidisciplinary approach: geological and geomorphological survey, statistical analysis and GIS technique, along a section of highway "A3 (Salerno-Reggio Calabria)" between Cosenza Sud and Altilia, northern Calabria. This study is included in a wider research project, named: PON01-01503, Landslides Early Warning-Sistemi integrati per il monitoraggio e la mitigazione del rischio idrogeologico lungo le grandi vie di comunicazione - aimed at the hydrogeological risk mitigation and at the early warning along the highways. The work was first based on air-photo interpretations and field investigations, in order to realize the geological map, geomorphological map and landslide inventory map. In the study area the geomorphology is strongly controlled by its bedrock geology and tectonics. The bedrock geology consists of Neogene sedimentary rocks that cover a thick stack of allochthonous nappes. These nappes consist of crystalline rocks mainly gneiss, phyllite and schist. A total of 835 landslides were mapped and the type of movement are represented mainly by slides and complex and subordinately flow. In order to estimate and validate landslide susceptibility the landslides were divided in two group. One group (training set) was used to prepare susceptibility map and the second group (validation set) to validate the map. Then, the selection of predisposing factors was performed, according with the geological and geomorphological settings of the study area: lithology, distance from tectonic elements, land use, slope, aspect, stream power index (SPI) and plan curvature. In order to evaluate landslide susceptibility Conditional Analysis was applied to Unique Conditions Units (UCUs

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

Nashef, Aysar; Agbaria, Mahmoud; Shusterman, Ariel; Lorè, Nicola Ivan; Bragonzi, Alessandra; Wiess, Ervin; Houri-Haddad, Yael; Iraqi, Fuad A

2017-01-01

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Mapping quantitative trait loci for fear-like behaviors in mice.

PubMed

Gershenfeld, H K; Paul, S M

1997-11-15

Two mouse models developed for screening anxiolytic drugs were selected for genetic analysis, namely "wall-seeking" tendency in an open field ("thigmotaxis") and the light-to-dark transition (LD) paradigm, a conflict test. These tests measure differences in naturalistic tendencies of mice to explore a novel environment and to avoid a bright light or the center of an open field. In an F2 intercross of two strains of mice (A/J and C57BL/6J) that differ markedly in these behaviors, we estimated a broad sense heritability ranging from 0.3 to 0.59. With this intercross (n = 518), we have mapped several quantitative trait loci (QTL) for these behaviors by performing a genome-wide search. A significant QTL on chromosome 10 (near D10Mit237; LOD of 9.3) that affects LD behavior was identified, and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6, 15, 19, and X. For center time behaviors, QTL were identified on chromosome 1 (LOD of 7.7 and 4.0 for the initial 5-min epoch and the first trial average of the next two 5-min epochs, respectively), and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6 and 14. These QTL individually explain from 2.3 to 8.4% of the phenotypic variance. Collectively, the multiple independent QTL explain from 3.5 to 26.5% of the F2 population's phenotypic variance, depending on the trait. The complexity and heterogeneity of the genetic factors underlying these fear-like behaviors are illustrated by the lack of shared QTL between paradigms and by mapping different QTL for repeated trials of behavior. The identification of QTL affecting individual differences in fear-like behavior may lead to the identification of new gene products and pathways that modulate behavior, providing targets for rational drug design.

Physical Confirmation and Comparative Genomics of the Rat Mammary carcinoma susceptibility 3 Quantitative Trait Locus.

PubMed

Le, Saasha; Martin, Zachary C; Samuelson, David J

2017-06-07

Human breast and rat mammary cancer susceptibility are complex phenotypes where complete sets of risk associated loci remain to be identified for both species. We tested multiple congenic rat strains to physically confirm and positionally map rat Mammary carcinoma susceptibility 3 ( Mcs3 )-a mammary cancer resistance allele previously predicted at Rattus norvegicus chromosome 1 ( RNO1 ). The mammary cancer susceptible Wistar Furth (WF) strain was the recipient, and the mammary cancer resistant Copenhagen (Cop) strain was the RNO1 -segment donor for congenics. Inbred WF females averaged 6.3 carcinogen-induced mammary carcinomas per rat. Two WF.Cop congenic strains averaged 2.8 and 3.4 mammary carcinomas per rat, which confirmed Mcs3 as an independently acting allele. Two other WF.Cop congenic strains averaged 6.6 and 8.1 mammary carcinomas per rat, and, thus, did not contain Mcs3 Rat Mcs3 was delimited to 27.8 Mb of RNO1 from rs8149408 to rs105131702 ( RNO1 :143700228-171517317 of RGSC 6.0/rn6). Human genetic variants with p values for association to breast cancer risk below 10 -7 had not been reported for Mcs3 orthologous loci; however, human variants located in Mcs3 -orthologous regions with potential association to risk (10 -7  <  p  < 10 -3 ) were listed in some population-based studies. Further, rat Mcs3 contains sequence orthologous to human 11q13/14 -a region frequently amplified in female breast cancer. We conclude that Mcs3 is an independently acting mammary carcinoma resistance allele. Human population-based, genome-targeted association studies interrogating Mcs3 orthologous loci may yield novel breast cancer risk associated variants and genes. Copyright © 2017 Le et al.

A GIS-based susceptibility map for landslides at the Franconian Alb, Germany

NASA Astrophysics Data System (ADS)

Jaeger, Daniel; Wilde, Martina; Lorenz, Michael; Terhorst, Birgit; Neuhäuser, Bettina; Damm, Bodo; Bemm, Stefan

2014-05-01

In general, slopes of cuesta scarps like the Franconian Alb are highly prone to slide activity due to susceptible geological and geomorphological conditions. The geological setting with alternating permeable and non-permeable bedrock results in the characteristic cuesta landforms of almost flat backslopes and steeper front slopes. Furthermore, this bipartite structure leads to a strong disposition for mass movements. The slopes of the study area near the town of Ebermannstadt are affected by different types of mass movements, such as topples, slides, lateral spreads and flows, either in single or in combined occurrence. In the years 1625, 1957, 1961 and 1979, four large landslides took place in the area of Ebermannstadt, reaching close to the town limits and causing major destructions to traffic facilities. In the study area, slopes are covered by debris and slide masses, thus they are prone to remobilization and further mass movements. In order to assess hazardous areas, a GIS-based susceptibility modelling was generated for the study area. The susceptibtibility modeling was processed with the slope stability model SINMAP (Stability Index Mapping), developed by TARBOTON (1997) and PACK et al. (1999). As SINMAP was particularly designed to model shallow translational slides, it should be well designed for describing the conditions of the study area in a sufficient way. SINMAP is based on the "infinite slope stability model" by HAMMONT et al. (1992) and MONTGOMERY & DIETRICH (1994), which focuses on the relation of stabilizing (cohesiveness, friction angle) and destabilizing (gravitation) factors on a plain surface. By adding a slope gradient, as well as soil mechanical and climatical data, indices of slope stabilities are calculated. For a more detailed modeling of the slope conditions, SINMAP computes different "calibration regions", which merge similar parameters of soil, land-use, vegetation, and geology. Due to the fact that vegetation, land-use, and soils only

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Quantitative maps of geomagnetic perturbation vectors during substorm onset and recovery

PubMed Central

Pothier, N M; Weimer, D R; Moore, W B

2015-01-01

We have produced the first series of spherical harmonic, numerical maps of the time-dependent surface perturbations in the Earth's magnetic field following the onset of substorms. Data from 124 ground magnetometer stations in the Northern Hemisphere at geomagnetic latitudes above 33° were used. Ground station data averaged over 5 min intervals covering 8 years (1998–2005) were used to construct pseudo auroral upper, auroral lower, and auroral electrojet (AU*, AL*, and AE*) indices. These indices were used to generate a list of substorms that extended from 1998 to 2005, through a combination of automated processing and visual checks. Events were sorted by interplanetary magnetic field (IMF) orientation (at the Advanced Composition Explorer (ACE) satellite), dipole tilt angle, and substorm magnitude. Within each category, the events were aligned on substorm onset. A spherical cap harmonic analysis was used to obtain a least error fit of the substorm disturbance patterns at 5 min intervals up to 90 min after onset. The fits obtained at onset time were subtracted from all subsequent fits, for each group of substorm events. Maps of the three vector components of the averaged magnetic perturbations were constructed to show the effects of substorm currents. These maps are produced for several specific ranges of values for the peak |AL*| index, IMF orientation, and dipole tilt angle. We demonstrate an influence of the dipole tilt angle on the response to substorms. Our results indicate that there are downward currents poleward and upward currents just equatorward of the peak in the substorms' westward electrojet. Key Points Show quantitative maps of ground geomagnetic perturbations due to substorms Three vector components mapped as function of time during onset and recovery Compare/contrast results for different tilt angle and sign of IMF Y-component PMID:26167445

Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

NASA Astrophysics Data System (ADS)

Yusof, Norbazlan M.; Pradhan, Biswajeet

2014-06-01

PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data

Quantitative water content mapping at clinically relevant field strengths: a comparative study at 1.5 T and 3 T.

PubMed

Abbas, Zaheer; Gras, Vincent; Möllenhoff, Klaus; Oros-Peusquens, Ana-Maria; Shah, Nadim Joni

2015-02-01

Quantitative water content mapping in vivo using MRI is a very valuable technique to detect, monitor and understand diseases of the brain. At 1.5 T, this technology has already been successfully used, but it has only recently been applied at 3T because of significantly increased RF field inhomogeneity at the higher field strength. To validate the technology at 3T, we estimate and compare in vivo quantitative water content maps at 1.5 T and 3T obtained with a protocol proposed recently for 3T MRI. The proposed MRI protocol was applied on twenty healthy subjects at 1.5 T and 3T; the same post-processing algorithms were used to estimate the water content maps. The 1.5 T and 3T maps were subsequently aligned and compared on a voxel-by-voxel basis. Statistical analysis was performed to detect possible differences between the estimated 1.5 T and 3T water maps. Our analysis indicates that the water content values obtained at 1.5 T and 3T did not show significant systematic differences. On average the difference did not exceed the standard deviation of the water content at 1.5 T. Furthermore, the contrast-to-noise ratio (CNR) of the estimated water content map was increased at 3T by a factor of at least 1.5. Vulnerability to RF inhomogeneity increases dramatically with the increasing static magnetic field strength. However, using advanced corrections for the sensitivity profile of the MR coils, it is possible to preserve quantitative accuracy while benefiting from the increased CNR at the higher field strength. Indeed, there was no significant difference in the water content values obtained in the brain at 1.5 T and 3T. Copyright © 2014 Elsevier Inc. All rights reserved.

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

PubMed Central

Orr, Nick; Dudbridge, Frank; Dryden, Nicola; Maguire, Sarah; Novo, Daniela; Perrakis, Eleni; Johnson, Nichola; Ghoussaini, Maya; Hopper, John L.; Southey, Melissa C.; Apicella, Carmel; Stone, Jennifer; Schmidt, Marjanka K.; Broeks, Annegien; Van't Veer, Laura J.; Hogervorst, Frans B.; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Gibson, Lorna; Aitken, Zoe; Warren, Helen; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Chistof; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Sanchez, Marie; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Benitez, Javier; Zamora, Maria Pilar; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Hamann, Ute; Brauch, Hiltrud; Justenhoven, Christina; Brüning, Thomas; Ko, Yon-Dschun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Bogdanova, Natalia; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Chenevix-Trench, Georgia; Beesley, Jonathan; Lambrechts, Diether; Moisse, Matthieu; Floris, Guiseppe; Beuselinck, Benoit; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Peissel, Bernard; Pensotti, Valeria; Couch, Fergus J.; Olson, Janet E.; Slettedahl, Seth; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Kristensen, Vessela; Alnæs, Grethe Grenaker; Nord, Silje; Borresen-Dale, Anne-Lise; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robertus A. E. M.; Seynaeve, Caroline M.; Van Asperen, Christi J.; Garcia-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J.; Lissowska, Jolanta; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Klevebring, Daniel; Hooning, Maartje J.; Hollestelle, Antoinette; van Deurzen, Carolien H. M.; Kriege, Mieke; Hall, Per; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Pharoah, Paul D. P.; Dunning, Alison M.; Shah, Mitul; Perkins, Barbara J.; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Ashworth, Alan; Swerdlow, Anthony; Jones, Michael; Schoemaker, Minouk J.; Meindl, Alfons; Schmutzler, Rita K.; Olswold, Curtis; Slager, Susan; Toland, Amanda E.; Yannoukakos, Drakoulis; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Matsuo, Keitaro; Ito, Hidema; Iwata, Hiroji; Ishiguro, Junko; Wu, Anna H.; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O.; Teo, Soo Hwang; Yip, Cheng Har; Kang, Peter; Ikram, Mohammad Kamran; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Lee, Soo Chin; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; Mckay, James; Wu, Pei-Ei; Hou, Ming-Feng; Yu, Jyh-Cherng; Shen, Chen-Yang; Blot, William; Cai, Qiuyin; Signorello, Lisa B.; Luccarini, Craig; Bayes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S.; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Hunter, David J.; Lindstrom, Sara; Dennis, Joe; Michailidou, Kyriaki; Bolla, Manjeet K.; Easton, Douglas F.; dos Santos Silva, Isabel; Fletcher, Olivia; Peto, Julian

2015-01-01

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88–0.92]; P-value = 1.58 × 10−25). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08–1.17]; P-value = 7.89 × 10−09) and rs13294895 (OR = 1.09 [1.06–1.12]; P-value = 2.97 × 10−11). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06–1.18]; P-value = 2.77 × 10−05). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis. PMID:25652398

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2.

PubMed

Orr, Nick; Dudbridge, Frank; Dryden, Nicola; Maguire, Sarah; Novo, Daniela; Perrakis, Eleni; Johnson, Nichola; Ghoussaini, Maya; Hopper, John L; Southey, Melissa C; Apicella, Carmel; Stone, Jennifer; Schmidt, Marjanka K; Broeks, Annegien; Van't Veer, Laura J; Hogervorst, Frans B; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Gibson, Lorna; Aitken, Zoe; Warren, Helen; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Chistof; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Sanchez, Marie; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Benitez, Javier; Zamora, Maria Pilar; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Anton-Culver, Hoda; Neuhausen, Susan L; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Hamann, Ute; Brauch, Hiltrud; Justenhoven, Christina; Brüning, Thomas; Ko, Yon-Dschun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Bogdanova, Natalia; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Chenevix-Trench, Georgia; Beesley, Jonathan; Lambrechts, Diether; Moisse, Matthieu; Floris, Guiseppe; Beuselinck, Benoit; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Peissel, Bernard; Pensotti, Valeria; Couch, Fergus J; Olson, Janet E; Slettedahl, Seth; Vachon, Celine; Giles, Graham G; Milne, Roger L; McLean, Catriona; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Kristensen, Vessela; Alnæs, Grethe Grenaker; Nord, Silje; Borresen-Dale, Anne-Lise; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robertus A E M; Seynaeve, Caroline M; Van Asperen, Christi J; Garcia-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J; Lissowska, Jolanta; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Klevebring, Daniel; Hooning, Maartje J; Hollestelle, Antoinette; van Deurzen, Carolien H M; Kriege, Mieke; Hall, Per; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Pharoah, Paul D P; Dunning, Alison M; Shah, Mitul; Perkins, Barbara J; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Ashworth, Alan; Swerdlow, Anthony; Jones, Michael; Schoemaker, Minouk J; Meindl, Alfons; Schmutzler, Rita K; Olswold, Curtis; Slager, Susan; Toland, Amanda E; Yannoukakos, Drakoulis; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Matsuo, Keitaro; Ito, Hidema; Iwata, Hiroji; Ishiguro, Junko; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Teo, Soo Hwang; Yip, Cheng Har; Kang, Peter; Ikram, Mohammad Kamran; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Noh, Dong-Young; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Lee, Soo Chin; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; Mckay, James; Wu, Pei-Ei; Hou, Ming-Feng; Yu, Jyh-Cherng; Shen, Chen-Yang; Blot, William; Cai, Qiuyin; Signorello, Lisa B; Luccarini, Craig; Bayes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Hunter, David J; Lindstrom, Sara; Dennis, Joe; Michailidou, Kyriaki; Bolla, Manjeet K; Easton, Douglas F; dos Santos Silva, Isabel; Fletcher, Olivia; Peto, Julian

2015-05-15

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis. © The Author 2015. Published by Oxford University Press.

Dual-pathway multi-echo sequence for simultaneous frequency and T2 mapping

NASA Astrophysics Data System (ADS)

Cheng, Cheng-Chieh; Mei, Chang-Sheng; Duryea, Jeffrey; Chung, Hsiao-Wen; Chao, Tzu-Cheng; Panych, Lawrence P.; Madore, Bruno

2016-04-01

Purpose: To present a dual-pathway multi-echo steady state sequence and reconstruction algorithm to capture T2, T2∗ and field map information. Methods: Typically, pulse sequences based on spin echoes are needed for T2 mapping while gradient echoes are needed for field mapping, making it difficult to jointly acquire both types of information. A dual-pathway multi-echo pulse sequence is employed here to generate T2 and field maps from the same acquired data. The approach might be used, for example, to obtain both thermometry and tissue damage information during thermal therapies, or susceptibility and T2 information from a same head scan, or to generate bonus T2 maps during a knee scan. Results: Quantitative T2, T2∗ and field maps were generated in gel phantoms, ex vivo bovine muscle, and twelve volunteers. T2 results were validated against a spin-echo reference standard: A linear regression based on ROI analysis in phantoms provided close agreement (slope/R2 = 0.99/0.998). A pixel-wise in vivo Bland-Altman analysis of R2 = 1/T2 showed a bias of 0.034 Hz (about 0.3%), as averaged over four volunteers. Ex vivo results, with and without motion, suggested that tissue damage detection based on T2 rather than temperature-dose measurements might prove more robust to motion. Conclusion: T2, T2∗ and field maps were obtained simultaneously, from the same datasets, in thermometry, susceptibility-weighted imaging and knee-imaging contexts.

Soil magnetic susceptibility mapping as a pollution and provenance tool: an example from southern New Zealand

NASA Astrophysics Data System (ADS)

Martin, A. P.; Ohneiser, C.; Turnbull, R. E.; Strong, D. T.; Demler, S.

2018-02-01

The presence or absence, degree and variation of heavy metal contamination in New Zealand soils is a matter of ongoing debate as it affects soil quality, agriculture and human health. In many instances, however, the soil heavy metal concentration data do not exist to answer these questions and the debate is ongoing. To address this, magnetic susceptibility (a common proxy for heavy metal contamination) values were measured in topsoil (0-30 cm) and subsoil (50-70 cm) at grid sites spaced at 8 km intervals across ca. 20 000 km2 of southern New Zealand. Samples were measured for both mass- and volume-specific magnetic susceptibility, with results being strongly, positively correlated. Three different methods of determining anomalies were applied to the data including the topsoil-subsoil difference method, Tukey boxplot method and geoaccumulation index method, with each method filtering out progressively more anomalies. Additional soil magnetic (hysteresis, isothermal remanence and thermomagnetic) measurements were made on a select subset of samples from anomalous sites. Magnetite is the dominant remanence carrying mineral, and magnetic susceptibility is governed by that minerals concentration in soils, rather than mineral type. All except two anomalous sites have a dominant geogenic source (cf. anthropogenic). By proxy, heavy metal contamination in southern New Zealand soils is minimal, making them relatively pristine. The provenance of the magnetic minerals in the anomalous sites can be traced back to likely sources in outcrops of igneous rocks within the same catchment, terrane or rock type: a distance of <100 km but frequently <1 km. Soil provenance is a key step when mapping element or isotopic distribution, vectoring to mineralization or studying soil for agricultural suitability, water quality or environmental regulation. Measuring soil magnetic susceptibility is a useful, quick and inexpensive tool that usefully supplements soil geochemical data.

Construction of a high-density linkage map and mapping quantitative trait loci for somatic embryogenesis using leaf petioles as explants in upland cotton (Gossypium hirsutum L.).

PubMed

Xu, Zhenzhen; Zhang, Chaojun; Ge, Xiaoyang; Wang, Ni; Zhou, Kehai; Yang, Xiaojie; Wu, Zhixia; Zhang, Xueyan; Liu, Chuanliang; Yang, Zuoren; Li, Changfeng; Liu, Kun; Yang, Zhaoen; Qian, Yuyuan; Li, Fuguang

2015-07-01

The first high-density linkage map was constructed to identify quantitative trait loci (QTLs) for somatic embryogenesis (SE) in cotton ( Gossypium hirsutum L.) using leaf petioles as explants. Cotton transformation is highly limited by only a few regenerable genotypes and the lack of understanding of the genetic and molecular basis of somatic embryogenesis (SE) in cotton (Gossypium hirsutum L.). To construct a more saturated linkage map and further identify quantitative trait loci (QTLs) for SE using leaf petioles as explants, a high embryogenesis frequency line (W10) from the commercial Chinese cotton cultivar CRI24 was crossed with TM-1, a genetic standard upland cotton with no embryogenesis frequency. The genetic map spanned 2300.41 cM in genetic distance and contained 411 polymorphic simple sequence repeat (SSR) loci. Of the 411 mapped loci, 25 were developed from unigenes identified for SE in our previous study. Six QTLs for SE were detected by composite interval mapping method, each explaining 6.88-37.07% of the phenotypic variance. Single marker analysis was also performed to verify the reliability of QTLs detection, and the SSR markers NAU3325 and DPL0209 were detected by the two methods. Further studies on the relatively stable and anchoring QTLs/markers for SE in an advanced population of W10 × TM-1 and other cross combinations with different SE abilities may shed light on the genetic and molecular mechanism of SE in cotton.

The magnetic susceptibility of soils in Krakow, southern Poland

NASA Astrophysics Data System (ADS)

Wojas, Anna

2017-06-01

Studies into the magnetic susceptibility have been used to assess the soils contamination in the Krakow area. The results of topsoil (over a 2 × 2 km grid), subsoil (37 shallow holes) and soil samples (112) measurements were presented as maps of soil magnetic susceptibility (both volume and mass) illustrating the distribution of parameters in topsoil horizon (0-10 cm) and differential magnetic susceptibility maps between topsoil horizon and subsoil (40-60 cm). All evidence leads to the finding that the highest values of magnetic susceptibility of soil are found exclusively in industrial areas. Taking into consideration the type of land use, the high median value (89.8 × 10-8 m3kg-1) was obtained for samples of cultivated soils and is likely to be connected with occurrence of fertile soil (chernozem). Moreover, enrichment of soils with Pb and Zn accompanies magnetic susceptibility anomalies in the vicinity of the high roads and in the steelworks area, respectively.

MR Measurement of Alloy Magnetic Susceptibility: Towards Developing Tissue-Susceptibility Matched Metals

PubMed Central

Astary, Garrett W.; Peprah, Marcus K.; Fisher, Charles R.; Stewart, Rachel L.; Carney, Paul R.; Sarntinoranont, Malisa; Meisel, Mark W.; Manuel, Michele V.; Mareci, Thomas H.

2013-01-01

Magnetic resonance imaging (MRI) can be used to relate structure to function mapped with high-temporal resolution electrophysiological recordings using metal electrodes. Additionally, MRI may be used to guide the placement of electrodes or conductive cannula in the brain. However, the magnetic susceptibility mismatch between implanted metals and surrounding brain tissue can severely distort MR images and spectra, particularly in high magnetic fields. In this study, we present a modified MR method of characterizing the magnetic susceptibility of materials that can be used to develop biocompatible, metal alloys that match the susceptibility of host tissue in order to eliminate MR distortions proximal to the implant. This method was applied at 4.7 T and 11.1 T to measure the susceptibility of a model solid-solution alloy of Cu and Sn, which is inexpensive but not biocompatible. MR-derived relative susceptibility values of four different compositions of Cu-Sn alloy deviated by less than 3.1% from SQUID magnetometry absolute susceptibility measurements performed up to 7 T. These results demonstrate that the magnetic susceptibility varies linearly with atomic percentage in these solid-solution alloys, but are not simply the weighted average of Cu and Sn magnetic susceptibilities. Therefore susceptibility measurements are necessary when developing susceptibility-matched, solid-solution alloys for the elimination of susceptibility artifacts in MR. This MR method does not require any specialized equipment and is free of geometrical constraints, such as sample shape requirements associated with SQUID magnetometry, so the method can be used at all stages of fabrication to guide the development of a susceptibility matched, biocompatible device. PMID:23727587

Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process

NASA Astrophysics Data System (ADS)

Galindo, I.; Romero, M. C.; Sánchez, N.; Morales, J. M.

2016-06-01

Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures.

Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process

PubMed Central

Galindo, I.; Romero, M. C.; Sánchez, N.; Morales, J. M.

2016-01-01

Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures. PMID:27265878

Quantitative volcanic susceptibility analysis of Lanzarote and Chinijo Islands based on kernel density estimation via a linear diffusion process.

PubMed

Galindo, I; Romero, M C; Sánchez, N; Morales, J M

2016-06-06

Risk management stakeholders in high-populated volcanic islands should be provided with the latest high-quality volcanic information. We present here the first volcanic susceptibility map of Lanzarote and Chinijo Islands and their submarine flanks based on updated chronostratigraphical and volcano structural data, as well as on the geomorphological analysis of the bathymetric data of the submarine flanks. The role of the structural elements in the volcanic susceptibility analysis has been reviewed: vents have been considered since they indicate where previous eruptions took place; eruptive fissures provide information about the stress field as they are the superficial expression of the dyke conduit; eroded dykes have been discarded since they are single non-feeder dykes intruded in deep parts of Miocene-Pliocene volcanic edifices; main faults have been taken into account only in those cases where they could modified the superficial movement of magma. The application of kernel density estimation via a linear diffusion process for the volcanic susceptibility assessment has been applied successfully to Lanzarote and could be applied to other fissure volcanic fields worldwide since the results provide information about the probable area where an eruption could take place but also about the main direction of the probable volcanic fissures.

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring.

PubMed

Everss-Villalba, Estrella; Melgarejo-Meseguer, Francisco Manuel; Blanco-Velasco, Manuel; Gimeno-Blanes, Francisco Javier; Sala-Pla, Salvador; Rojo-Álvarez, José Luis; García-Alberola, Arcadi

2017-10-25

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported

Epitope mapping and targeted quantitation of the cardiac biomarker troponin by SID-MRM mass spectrometry.

PubMed

Zhao, Cheng; Trudeau, Beth; Xie, Helen; Prostko, John; Fishpaugh, Jeffrey; Ramsay, Carol

2014-06-01

The absolute quantitation of the targeted protein using MS provides a promising method to evaluate/verify biomarkers used in clinical diagnostics. In this study, a cardiac biomarker, troponin I (TnI), was used as a model protein for method development. The epitope peptide of TnI was characterized by epitope excision followed with LC/MS/MS method and acted as the surrogate peptide for the targeted protein quantitation. The MRM-based MS assay using a stable internal standard that improved the selectivity, specificity, and sensitivity of the protein quantitation. Also, plasma albumin depletion and affinity enrichment of TnI by anti-TnI mAb-coated microparticles reduced the sample complexity, enhanced the dynamic range, and further improved the detecting sensitivity of the targeted protein in the biological matrix. Therefore, quantitation of TnI, a low abundant protein in human plasma, has demonstrated the applicability of the targeted protein quantitation strategy through its epitope peptide determined by epitope mapping method. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers

PubMed Central

Huo, Dezheng

2013-01-01

Numerous single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified by genome-wide association studies (GWAS). However, these SNPs were primarily discovered and validated in women of European and Asian ancestry. Because linkage disequilibrium is ancestry-dependent and heterogeneous among racial/ethnic populations, we evaluated common genetic variants at 22 GWAS-identified breast cancer susceptibility loci in a pooled sample of 1502 breast cancer cases and 1378 controls of African ancestry. None of the 22 GWAS index SNPs could be validated, challenging the direct generalizability of breast cancer risk variants identified in Caucasians or Asians to other populations. Novel breast cancer risk variants for women of African ancestry were identified in regions including 5p12 (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.11–1.76; P = 0.004), 5q11.2 (OR = 1.22, 95% CI = 1.09–1.36; P = 0.00053) and 10p15.1 (OR = 1.22, 95% CI = 1.08–1.38; P = 0.0015). We also found positive association signals in three regions (6q25.1, 10q26.13 and 16q12.1–q12.2) previously confirmed by fine mapping in women of African ancestry. In addition, polygenic model indicated that eight best markers in this study, compared with 22 GWAS-identified SNPs, could better predict breast cancer risk in women of African ancestry (per-allele OR = 1.21, 95% CI = 1.16–1.27; P = 9.7 × 10–16). Our results demonstrate that fine mapping is a powerful approach to better characterize the breast cancer risk alleles in diverse populations. Future studies and new GWAS in women of African ancestry hold promise to discover additional variants for breast cancer susceptibility with clinical implications throughout the African diaspora. PMID:23475944

Metabolic Mapping: Quantitative Enzyme Cytochemistry and Histochemistry to Determine the Activity of Dehydrogenases in Cells and Tissues.

PubMed

Molenaar, Remco J; Khurshed, Mohammed; Hira, Vashendriya V V; Van Noorden, Cornelis J F

2018-05-26

Altered cellular metabolism is a hallmark of many diseases, including cancer, cardiovascular diseases and infection. The metabolic motor units of cells are enzymes and their activity is heavily regulated at many levels, including the transcriptional, mRNA stability, translational, post-translational and functional level. This complex regulation means that conventional quantitative or imaging assays, such as quantitative mRNA experiments, Western Blots and immunohistochemistry, yield incomplete information regarding the ultimate activity of enzymes, their function and/or their subcellular localization. Quantitative enzyme cytochemistry and histochemistry (i.e., metabolic mapping) show in-depth information on in situ enzymatic activity and its kinetics, function and subcellular localization in an almost true-to-nature situation. We describe a protocol to detect the activity of dehydrogenases, which are enzymes that perform redox reactions to reduce cofactors such as NAD(P) + and FAD. Cells and tissue sections are incubated in a medium that is specific for the enzymatic activity of one dehydrogenase. Subsequently, the dehydrogenase that is the subject of investigation performs its enzymatic activity in its subcellular site. In a chemical reaction with the reaction medium, this ultimately generates blue-colored formazan at the site of the dehydrogenase's activity. The formazan's absorbance is therefore a direct measure of the dehydrogenase's activity and can be quantified using monochromatic light microscopy and image analysis. The quantitative aspect of this protocol enables researchers to draw statistical conclusions from these assays. Besides observational studies, this technique can be used for inhibition studies of specific enzymes. In this context, studies benefit from the true-to-nature advantages of metabolic mapping, giving in situ results that may be physiologically more relevant than in vitro enzyme inhibition studies. In all, metabolic mapping is an

Functional mapping of quantitative trait loci associated with rice tillering.

PubMed

Liu, G F; Li, M; Wen, J; Du, Y; Zhang, Y-M

2010-10-01

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang-Lan-Ding mathematical model. Four biologically meaningful parameters in this model--the potential maximum for tiller number (K), the optimum tiller time (t(0)), and the increased rate (r), or the reduced rate (c) at the time of deviation from t(0)--were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49-8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.

Mapping Fusarium solani and Aphanomyces euteiches root rot resistance and root architecture quantitative trait loci in common bean (Phaseolus vulgaris)

USDA-ARS?s Scientific Manuscript database

Root rot diseases of bean (Phaseolus vulgaris L.) are a constraint to dry and snap bean production. We developed the RR138 RIL mapping population from the cross of OSU5446, a susceptible line that meets current snap bean processing industry standards, and RR6950, a root rot resistant dry bean in th...

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

PubMed Central

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

Mapping Adipose and Muscle Tissue Expression Quantitative Trait Loci in African Americans to Identify Genes for Type 2 Diabetes and Obesity

PubMed Central

Sajuthi, Satria P.; Sharma, Neeraj K.; Chou, Jeff W.; Palmer, Nicholette D.; McWilliams, David R.; Beal, John; Comeau, Mary E.; Ma, Lijun; Calles-Escandon, Jorge; Demons, Jamehl; Rogers, Samantha; Cherry, Kristina; Menon, Lata; Kouba, Ethel; Davis, Donna; Burris, Marcie; Byerly, Sara J.; Ng, Maggie C.Y.; Maruthur, Nisa M.; Patel, Sanjay R.; Bielak, Lawrence F.; Lange, Leslie; Guo, Xiuqing; Sale, Michèle M.; Chan, Kei Hang; Monda, Keri L.; Chen, Gary K.; Taylor, Kira; Palmer, Cameron; Edwards, Todd L; North, Kari E.; Haiman, Christopher A.; Bowden, Donald W.; Freedman, Barry I.; Langefeld, Carl D.; Das, Swapan K.

2016-01-01

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes. PMID:27193597

Quantitative autoradiographic mapping of herpes simplex virus encephalitis with a radiolabeled antiviral drug

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

Saito, Y.; Price, R.W.; Rottenberg, D.A.

1982-09-17

2'-Fluoro-5-methyl-1-..beta..-D-arabinosyluracil (FMAU) labeled with carbon-14 was used to image herpes simplex virus type 1-infected regions of rat brain by quantitative autoradiography. FMAU is a potent antiviral pyrimidine nucleoside which is selectively phosphorylated by virus-coded thymidine kinase. When the labeled FMAU was administered 6 hours before the rats were killed, the selective uptake and concentration of the drug and its metabolites by infected cells (defined by immunoperoxidase staining of viral antigens) allowed quantitative definition and mapping of HSV-1-infected structures in autoradiograms of brain sections. These results shown that quantitative autoradiography can be used to characterize the local metabolism of antiviral drugsmore » by infected cells in vivo. They also suggest that the selective uptake of drugs that exploit viral thymidine kinase for their antiviral effect can, by appropriate labeling, be used in conjunction with clinical neuroimaging techniques to define infected regions of human brain, thereby providing a new approach to the diagnosis of herpes encephalitis in man.« less

Quantitatively Mapping Cellular Viscosity with Detailed Organelle Information via a Designed PET Fluorescent Probe

PubMed Central

Liu, Tianyu; Liu, Xiaogang; Spring, David R.; Qian, Xuhong; Cui, Jingnan; Xu, Zhaochao

2014-01-01

Viscosity is a fundamental physical parameter that influences diffusion in biological processes. The distribution of intracellular viscosity is highly heterogeneous, and it is challenging to obtain a full map of cellular viscosity with detailed organelle information. In this work, we report 1 as the first fluorescent viscosity probe which is able to quantitatively map cellular viscosity with detailed organelle information based on the PET mechanism. This probe exhibited a significant ratiometric fluorescence intensity enhancement as solvent viscosity increases. The emission intensity increase was attributed to combined effects of the inhibition of PET due to restricted conformational access (favorable for FRET, but not for PET), and the decreased PET efficiency caused by viscosity-dependent twisted intramolecular charge transfer (TICT). A full map of subcellular viscosity was successfully constructed via fluorescent ratiometric detection and fluorescence lifetime imaging; it was found that lysosomal regions in a cell possess the highest viscosity, followed by mitochondrial regions. PMID:24957323

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

PubMed

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

HapMap-based study of CIP2A gene polymorphisms and HCC susceptibility

PubMed Central

LI, YUCHUN; WANG, KAIJUAN; DAI, LIPING; WANG, PENG; SONG, CHUNHUA; SHI, JIANXIANG; REN, PENGFEI; YE, HUA; ZHANG, JIANYING

2012-01-01

CIP2A is a human oncoprotein that inhibits PP2A and stabilizes c-myc in human malignancies. Autoantibodies to CIP2A protein have been reported to be present in higher levels in sera from patients with hepatocellular carcinoma (HCC) than in sera of healthy individuals. The CIP2A gene has been demonstrated as a potential cancer susceptibility gene. To elucidate whether common CIP2A variants are associated with HCC susceptibility, we conducted a case-control study comprising 233 cases of HCC and 280 controls matched on age, gender and ethnicity in the Chinese Han population. Two haplotype-tagging single nucleotide polymorphisms (htSNPs) (rs2278911 and rs4855656) from the HapMap database were analyzed, which provide an almost complete coverage of the genetic variations in the CIP2A gene. We found that neither of these htSNPs and haplotypes were associated with the risk of HCC. However, an interaction was observed between hepatitis virus B and C infection (HBV and HCV) and the C carriers (TC or CC) of rs2278911 on HCC risk (OR=12.35; 95% CI, 4.93–19.87). No such association was found for rs4855656. Our study also demonstrated that two htSNPs (rs2278911 and rs4855656) in the CIP2A gene are not associated with the risk of HCC. HBV and HCV infection was found to exert a synergistic effect on the risk of HCC in individuals with the C carriers (TC or CC) of rs2278911 in the Chinese Han population. PMID:22844383

Correlation of quantitative dual-energy computed tomography iodine maps and abdominal computed tomography perfusion measurements: are single-acquisition dual-energy computed tomography iodine maps more than a reduced-dose surrogate of conventional computed tomography perfusion?

PubMed

Stiller, Wolfram; Skornitzke, Stephan; Fritz, Franziska; Klauss, Miriam; Hansen, Jens; Pahn, Gregor; Grenacher, Lars; Kauczor, Hans-Ulrich

2015-10-01

Study objectives were the quantitative evaluation of whether conventional abdominal computed tomography (CT) perfusion measurements mathematically correlate with quantitative single-acquisition dual-energy CT (DECT) iodine concentration maps, the determination of the optimum time of acquisition for achieving maximum correlation, and the estimation of the potential for radiation exposure reduction when replacing conventional CT perfusion by single-acquisition DECT iodine concentration maps. Dual-energy CT perfusion sequences were dynamically acquired over 51 seconds (34 acquisitions every 1.5 seconds) in 24 patients with histologically verified pancreatic carcinoma using dual-source DECT at tube potentials of 80 kVp and 140 kVp. Using software developed in-house, perfusion maps were calculated from 80-kVp image series using the maximum slope model after deformable motion correction. In addition, quantitative iodine maps were calculated for each of the 34 DECT acquisitions per patient. Within a manual segmentation of the pancreas, voxel-by-voxel correlation between the perfusion map and each of the iodine maps was calculated for each patient to determine the optimum time of acquisition topt defined as the acquisition time of the iodine map with the highest correlation coefficient. Subsequently, regions of interest were placed inside the tumor and inside healthy pancreatic tissue, and correlation between mean perfusion values and mean iodine concentrations within these regions of interest at topt was calculated for the patient sample. The mean (SD) topt was 31.7 (5.4) seconds after the start of contrast agent injection. The mean (SD) perfusion values for healthy pancreatic and tumor tissues were 67.8 (26.7) mL per 100 mL/min and 43.7 (32.2) mL per 100 mL/min, respectively. At topt, the mean (SD) iodine concentrations were 2.07 (0.71) mg/mL in healthy pancreatic and 1.69 (0.98) mg/mL in tumor tissue, respectively. Overall, the correlation between perfusion values and

Ultrahigh resolution optical coherence tomography for quantitative topographic mapping of retinal and intraretinal architectural morphology

NASA Astrophysics Data System (ADS)

Ko, Tony H.; Hartl, Ingmar; Drexler, Wolfgang; Ghanta, Ravi K.; Fujimoto, James G.

2002-06-01

Quantitative, three-dimensional mapping of retinal architectural morphology was achieved using an ultrahigh resolution ophthalmic OCT system. This OCT system utilizes a broad bandwidth titanium-sapphire laser light source generating bandwidths of up to 300 nm near 800 nm center wavelength. The system enables real-time cross-sectional imaging of the retina with ~3 micrometers axial resolution. The macula and the papillomacular axis of a normal human subject were systematically mapped using a series of linear scans. Edge detection and segmentation algorithms were developed to quantify retinal and intraretinal thicknesses. Topographic mapping of the total retinal thickness and the total ganglion cell/inner plexiform layer thickness was achieved around the macula. A topographic mapping quantifying the progressive thickening of the nerve fiber layer (NFL) nasally approaching the optic disk was also demonstrated. The ability to create three-dimensional topographic mapping of retinal architectural morphology at ~3 micrometers axial resolution will be relevant for the diagnosis of many retinal diseases. The topographic quantification of these structures can serve as a powerful tool for developing algorithms and clinical scanning protocols for the screening and staging of ophthalmic diseases such as glaucoma.

Quantitative trait locus mapping in mice identifies phospholipase Pla2g12a as novel atherosclerosis modifier.

PubMed

Nicolaou, Alexandros; Northoff, Bernd H; Sass, Kristina; Ernst, Jana; Kohlmaier, Alexander; Krohn, Knut; Wolfrum, Christian; Teupser, Daniel; Holdt, Lesca M

2017-10-01

In a previous work, a female-specific atherosclerosis risk locus on chromosome (Chr) 3 was identified in an intercross of atherosclerosis-resistant FVB and atherosclerosis-susceptible C57BL/6 (B6) mice on the LDL-receptor deficient (Ldlr -/- ) background. It was the aim of the current study to identify causative genes at this locus. We established a congenic mouse model, where FVB.Chr3 B6/B6 mice carried an 80 Mb interval of distal Chr3 on an otherwise FVB.Ldlr -/- background, to validate the Chr3 locus. Candidate genes were identified using genome-wide expression analyses. Differentially expressed genes were validated using quantitative PCRs in F0 and F2 mice and their functions were investigated in pathophysiologically relevant cells. Fine-mapping of the Chr3 locus revealed two overlapping, yet independent subloci for female atherosclerosis susceptibility: when transmitted by grandfathers to granddaughters, the B6 risk allele increased atherosclerosis and downregulated the expression of the secreted phospholipase Pla2g12a (2.6 and 2.2 fold, respectively); when inherited by grandmothers, the B6 risk allele induced vascular cell adhesion molecule 1 (Vcam1). Down-regulation of Pla2g12a and up-regulation of Vcam1 were validated in female FVB.Chr3 B6/B6 congenic mice, which developed 2.5 greater atherosclerotic lesions compared to littermate controls (p=0.039). Pla2g12a was highly expressed in aortic endothelial cells in vivo, and knocking-down Pla2g12a expression by RNAi in cultured vascular endothelial cells or macrophages increased their adhesion to ECs in vitro. Our data establish Pla2g12a as an atheroprotective candidate gene in mice, where high expression levels in ECs and macrophages may limit the recruitment and accumulation of these cells in nascent atherosclerotic lesions. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative validation of sensory mapping in persistent postherniorrhaphy inguinal pain patients undergoing triple neurectomy.

PubMed

Bjurström, M F; Álvarez, R; Nicol, A L; Olmstead, R; Amid, P K; Chen, D C

2017-04-01

Neurectomy of the inguinal nerves may be considered for selected refractory cases of chronic postherniorrhaphy inguinal pain (CPIP). There is to date a paucity of easily applicable clinical tools to identify neuropathic pain and examine the neurosensory effects of remedial surgery. The present quantitative sensory testing (QST) pilot study evaluates a sensory mapping technique. Longitudinal (preoperative, immediate postoperative, and late postoperative) dermatomal sensory mapping and a comprehensive QST protocol were conducted in CPIP patients with unilateral, predominantly neuropathic inguinodynia presenting for triple neurectomy (n = 13). QST was conducted in four areas on the affected, painful side and in one contralateral comparison site. QST variables were compared according to sensory mapping outcomes: (o)/normal sensation, (+)/pain, and (-)/numbness. Diagnostic ability of the sensory mapping outcomes to detect QST-assessed allodynia or hypoesthesia was estimated through calculation of specificity and sensitivity values. Preoperatively, patients exhibited mechanical hypoesthesia and allodynia and pressure allodynia and hyperalgesia in painful areas mapped (+) (p < .05); sensory mapping outcome (+) demonstrated high ability to detect mechanical allodynia [sensitivity 0.74 (95% CI 0.61-0.86), specificity 0.94 (0.84-1.00)] and pressure allodynia [sensitivity 0.96 (0.89-1.00), specificity 1.00 (1.00-1.00)], but not thermal allodynia. Postoperatively, mapped areas of numbness (-) were associated with mechanical and thermal hypoesthesia (p < .05); (-) showed high sensitivity and specificity to detect mechanical and cold hypoesthesia. Sensory mapping provides an accurate clinical neuropathic assessment with strong correlation to QST findings of preoperative mechanical and pressure allodynia, and postoperative mechanical and thermal hypoesthesia in CPIP patients undergoing neurectomy.

Current status of antifungal susceptibility testing methods.

PubMed

Arikan, Sevtap

2007-11-01

Antifungal susceptibility testing is a very dynamic field of medical mycology. Standardization of in vitro susceptibility tests by the Clinical and Laboratory Standards Institute (CLSI) and the European Committee for Antimicrobial Susceptibility Testing (EUCAST), and current availability of reference methods constituted the major remarkable steps in the field. Based on the established minimum inhibitory concentration (MIC) breakpoints, it is now possible to determine the susceptibilities of Candida strains to fluconazole, itraconazole, voriconazole, and flucytosine. Moreover, utility of fluconazole antifungal susceptibility tests as an adjunct in optimizing treatment of candidiasis has now been validated. While the MIC breakpoints and clinical significance of susceptibility testing for the remaining fungi and antifungal drugs remain yet unclear, modifications of the available methods as well as other methodologies are being intensively studied to overcome the present drawbacks and limitations. Among the other methods under investigation are Etest, colorimetric microdilution, agar dilution, determination of fungicidal activity, flow cytometry, and ergosterol quantitation. Etest offers the advantage of practical application and favorable agreement rates with the reference methods that are frequently above acceptable limits. However, MIC breakpoints for Etest remain to be evaluated and established. Development of commercially available, standardized colorimetric panels that are based on CLSI method parameters has added more to the antifungal susceptibility testing armamentarium. Flow cytometry, on the other hand, appears to offer rapid susceptibility testing but requires specified equipment and further evaluation for reproducibility and standardization. Ergosterol quantitation is another novel approach, which appears potentially beneficial particularly in discrimination of azole-resistant isolates from heavy trailers. The method is yet investigational and requires to

Quantitative evaluation of lumbar intervertebral disc degeneration by axial T2* mapping.

PubMed

Huang, Leitao; Liu, Yuan; Ding, Yi; Wu, Xia; Zhang, Ning; Lai, Qi; Zeng, Xianjun; Wan, Zongmiao; Dai, Min; Zhang, Bin

2017-12-01

To quantitatively evaluate the clinical value and demonstrate the potential benefits of biochemical axial T2* mapping-based grading of early stages of degenerative disc disease (DDD) using 3.0-T magnetic resonance imaging (MRI) in a clinical setting.Fifty patients with low back pain and 20 healthy volunteers (control) underwent standard MRI protocols including axial T2* mapping. All the intervertebral discs (IVDs) were classified morphologically. Lumbar IVDs were graded using Pfirrmann score (I to IV). The T2* values of the anterior annulus fibrosus (AF), posterior AF, and nucleus pulposus (NP) of each lumbar IVD were measured. The differences between groups were analyzed regarding specific T2* pattern at different regions of interest.The T2* values of the NP and posterior AF in the patient group were significantly lower than those in the control group (P < .01). The T2* value of the anterior AF was not significantly different between the patients and the controls (P > .05). The mean T2*values of the lumbar IVD in the patient group were significantly lower, especially the posterior AF, followed by the NP, and finally, the anterior AF. In the anterior AF, comparison of grade I with grade III and grade I with grade IV showed statistically significant differences (P = .07 and P = .08, respectively). Similarly, in the NP, comparison of grade I with grade III, grade I with grade IV, grade II with grade III, and grade II with grade IV showed statistically significant differences (P < .001). In the posterior AF, comparison of grade II with grade IV showed a statistically significant difference (P = .032). T2 values decreased linearly with increasing degeneration based on the Pfirrmann scoring system (ρ < -0.5, P < .001).Changes in the T2* value can signify early degenerative IVD diseases. Hence, T2* mapping can be used as a diagnostic tool for quantitative assessment of IVD degeneration. Copyright © 2017 The Authors. Published by Wolters

Mapping of quantitative trait loci associated with partial resistance to phytophthora sojae and flooding tolerance in soybean

USDA-ARS?s Scientific Manuscript database

Phytophthora root rot (PRR) caused by Phytophthora sojae Kaufm. & Gerd. and flooding can limit growth and productivity, of soybean [Glycine max (L.) Merr.], especially on poorly drained soils. The primary objective of this research project was to map quantitative trait loci (QTL) associated with f...

A 96-well-plate-based optical method for the quantitative and qualitative evaluation of Pseudomonas aeruginosa biofilm formation and its application to susceptibility testing.

PubMed

Müsken, Mathias; Di Fiore, Stefano; Römling, Ute; Häussler, Susanne

2010-08-01

A major reason for bacterial persistence during chronic infections is the survival of bacteria within biofilm structures, which protect cells from environmental stresses, host immune responses and antimicrobial therapy. Thus, there is concern that laboratory methods developed to measure the antibiotic susceptibility of planktonic bacteria may not be relevant to chronic biofilm infections, and it has been suggested that alternative methods should test antibiotic susceptibility within a biofilm. In this paper, we describe a fast and reliable protocol for using 96-well microtiter plates for the formation of Pseudomonas aeruginosa biofilms; the method is easily adaptable for antimicrobial susceptibility testing. This method is based on bacterial viability staining in combination with automated confocal laser scanning microscopy. The procedure simplifies qualitative and quantitative evaluation of biofilms and has proven to be effective for standardized determination of antibiotic efficiency on P. aeruginosa biofilms. The protocol can be performed within approximately 60 h.

Quantitative T2 mapping of recurrent glioblastoma under bevacizumab improves monitoring for non-enhancing tumor progression and predicts overall survival

PubMed Central

Hattingen, Elke; Jurcoane, Alina; Daneshvar, Keivan; Pilatus, Ulrich; Mittelbronn, Michel; Steinbach, Joachim P.; Bähr, Oliver

2013-01-01

Background Anti-angiogenic treatment in recurrent glioblastoma patients suppresses contrast enhancement and reduces vasogenic edema while non-enhancing tumor progression is common. Thus, the importance of T2-weighted imaging is increasing. We therefore quantified T2 relaxation times, which are the basis for the image contrast on T2-weighted images. Methods Conventional and quantitative MRI procedures were performed on 18 patients with recurrent glioblastoma before treatment with bevacizumab and every 8 weeks thereafter until further tumor progression. We segmented the tumor on conventional MRI into 3 subvolumes: enhancing tumor, non-enhancing tumor, and edema. Using coregistered quantitative maps, we followed changes in T2 relaxation time in each subvolume. Moreover, we generated differential T2 maps by a voxelwise subtraction using the first T2 map under bevacizumab as reference. Results Visually segmented areas of tumor and edema did not differ in T2 relaxation times. Non-enhancing tumor volume did not decrease after commencement of bevacizumab treatment but strikingly increased at progression. Differential T2 maps clearly showed non-enhancing tumor progression in previously normal brain. T2 relaxation times decreased under bevacizumab without re-increasing at tumor progression. A decrease of <26 ms in the enhancing tumor following exposure to bevacizumab was associated with longer overall survival. Conclusions Combining quantitative MRI and tumor segmentation improves monitoring of glioblastoma patients under bevacizumab. The degree of change in T2 relaxation time under bevacizumab may be an early response parameter predictive of overall survival. The sustained decrease in T2 relaxation times toward values of healthy tissue masks progressive tumor on conventional T2-weighted images. Therefore, quantitative T2 relaxation times may detect non-enhancing progression better than conventional T2-weighted imaging. PMID:23925453

Spatially quantitative seafloor habitat mapping: Example from the northern South Carolina inner continental shelf

USGS Publications Warehouse

Ojeda, G.Y.; Gayes, P.T.; Van Dolah, R. F.; Schwab, W.C.

2004-01-01

Naturally occurring hard bottom areas provide the geological substrate that can support diverse assemblages of sessile benthic organisms, which in turn, attract many reef-dwelling fish species. Alternatively, defining the location and extent of bottom sand bodies is relevant for potential nourishment projects as well as to ensure that transient sediment does not affect reef habitats, particularly in sediment-starved continental margins. Furthermore, defining sediment transport pathways documents the effects these mobile bedforms have on proximal reef habitats. Thematic mapping of these substrates is therefore crucial in safeguarding critical habitats and offshore resources of coastal nations. This study presents the results of a spatially quantitative mapping approach based on classification of sidescan-sonar imagery. By using bottom video for image-to-ground control, digital image textural features for pattern recognition, and an artificial neural network for rapid, quantitative, multivariable decision-making, this approach resulted in recognition rates of hard bottom as high as 87%. The recognition of sand bottom was less successful (31%). This approach was applied to a large (686 km2), high-quality, 2-m resolution sidescan-sonar mosaic of the northern South Carolina inner continental shelf. Results of this analysis indicate that both surficial sand and hard bottoms of variable extent are present over the study area. In total, 59% of the imaged area was covered by hard bottom, while 41% was covered by sand. Qualitative spatial correlation between bottom type and bathymetry appears possible from comparison of our interpretive map and available bathymetry. Hard bottom areas tend to be located on flat, low-lying areas, and sandy bottoms tend to reside on areas of positive relief. Published bio-erosion rates were used to calculate the potential sediment input from the mapped hard bottom areas rendering sediment volumes that may be as high as 0.8 million m3/yr for

Quantitative Analysis of Localized Sources Identified by Focal Impulse and Rotor Modulation Mapping in Atrial Fibrillation

PubMed Central

Benharash, Peyman; Buch, Eric; Frank, Paul; Share, Michael; Tung, Roderick; Shivkumar, Kalyanam; Mandapati, Ravi

2015-01-01

Background New approaches to ablation of atrial fibrillation (AF) include focal impulse and rotor modulation (FIRM) mapping, and initial results reported with this technique have been favorable. We sought to independently evaluate the approach by analyzing quantitative characteristics of atrial electrograms used to identify rotors and describe acute procedural outcomes of FIRM-guided ablation. Methods and Results All FIRM-guided ablation procedures (n=24; 50% paroxysmal) at University of California, Los Angeles Medical Center were included for analysis. During AF, unipolar atrial electrograms collected from a 64-pole basket catheter were used to construct phase maps and identify putative AF sources. These sites were targeted for ablation, in conjunction with pulmonary vein isolation in most patients (n=19; 79%). All patients had rotors identified (mean, 2.3±0.9 per patient; 72% in left atrium). Prespecified acute procedural end point was achieved in 12 of 24 (50%) patients: AF termination (n=1), organization (n=3), or >10% slowing of AF cycle length (n=8). Basket electrodes were within 1 cm of 54% of left atrial surface area, and a mean of 31 electrodes per patient showed interpretable atrial electrograms. Offline analysis revealed no differences between rotor and distant sites in dominant frequency or Shannon entropy. Electroanatomic mapping showed no rotational activation at FIRM-identified rotor sites in 23 of 24 patients (96%). Conclusions FIRM-identified rotor sites did not exhibit quantitative atrial electrogram characteristics expected from rotors and did not differ quantitatively from surrounding tissue. Catheter ablation at these sites, in conjunction with pulmonary vein isolation, resulted in AF termination or organization in a minority of patients (4/24; 17%). Further validation of this approach is necessary. PMID:25873718

The first genetic map of the American cranberry: exploration of synteny conservation and quantitative trait loci.

PubMed

Georgi, Laura; Johnson-Cicalese, Jennifer; Honig, Josh; Das, Sushma Parankush; Rajah, Veeran D; Bhattacharya, Debashish; Bassil, Nahla; Rowland, Lisa J; Polashock, James; Vorsa, Nicholi

2013-03-01

The first genetic map of cranberry (Vaccinium macrocarpon) has been constructed, comprising 14 linkage groups totaling 879.9 cM with an estimated coverage of 82.2 %. This map, based on four mapping populations segregating for field fruit-rot resistance, contains 136 distinct loci. Mapped markers include blueberry-derived simple sequence repeat (SSR) and cranberry-derived sequence-characterized amplified region markers previously used for fingerprinting cranberry cultivars. In addition, SSR markers were developed near cranberry sequences resembling genes involved in flavonoid biosynthesis or defense against necrotrophic pathogens, or conserved orthologous set (COS) sequences. The cranberry SSRs were developed from next-generation cranberry genomic sequence assemblies; thus, the positions of these SSRs on the genomic map provide information about the genomic location of the sequence scaffold from which they were derived. The use of SSR markers near COS and other functional sequences, plus 33 SSR markers from blueberry, facilitates comparisons of this map with maps of other plant species. Regions of the cranberry map were identified that showed conservation of synteny with Vitis vinifera and Arabidopsis thaliana. Positioned on this map are quantitative trait loci (QTL) for field fruit-rot resistance (FFRR), fruit weight, titratable acidity, and sound fruit yield (SFY). The SFY QTL is adjacent to one of the fruit weight QTL and may reflect pleiotropy. Two of the FFRR QTL are in regions of conserved synteny with grape and span defense gene markers, and the third FFRR QTL spans a flavonoid biosynthetic gene.

A journey from a SSR-based low density map to a SNP-based high density map for identification of disease resistance quantitative trait loci in peanut

USDA-ARS?s Scientific Manuscript database

Mapping and identification of quantitative trait loci (QTLs) are important for efficient marker-assisted breeding. Diseases such as leaf spots and Tomato spotted wilt virus (TSWV) cause significant loses to peanut growers. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to...

Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda.

PubMed

Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

2018-01-31

Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model's performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.

Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

PubMed Central

Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

2018-01-01

Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management. PMID:29385096

Identification of a psoriasis susceptibility candidate gene by linkage disequilibrium mapping with a localized single nucleotide polymorphism map.

PubMed

Hewett, Duncan; Samuelsson, Lena; Polding, Joanne; Enlund, Fredrik; Smart, Devi; Cantone, Kathryn; See, Chee Gee; Chadha, Sapna; Inerot, Annica; Enerback, Charlotta; Montgomery, Doug; Christodolou, Chris; Robinson, Phil; Matthews, Paul; Plumpton, Mary; Wahlstrom, Jan; Swanbeck, Gunnar; Martinsson, Tommy; Roses, Allen; Riley, John; Purvis, Ian

2002-03-01

Psoriasis is a chronic inflammatory disease of the skin with both genetic and environmental risk factors. Here we describe the creation of a single-nucleotide polymorphism (SNP) map spanning 900-1200 kb of chromosome 3q21, which had been previously recognized as containing a psoriasis susceptibility locus, PSORS5. We genotyped 644 individuals, from 195 Swedish psoriatic families, for 19 polymorphisms. Linkage disequilibrium (LD) between marker and disease was assessed using the transmission/disequilibrium test (TDT). In the TDT analysis, alleles of three of these SNPs showed significant association with disease (P<0.05). A 160-kb interval encompassing these three SNPs was sequenced, and a coding sequence consisting of 13 exons was identified. The predicted protein shares 30-40% homology with the family of cation/chloride cotransporters. A five-marker haplotype spanning the 3' half of this gene is associated with psoriasis to a P value of 3.8<10(-5). We have called this gene SLC12A8, coding for a member of the solute carrier family 12 proteins. It belongs to a class of genes that were previously unrecognized as playing a role in psoriasis pathogenesis.

Complex geohazard susceptibility zoning for effective landuse planning and catastroph prevention in developing countries

NASA Astrophysics Data System (ADS)

Hradecky, P.; Baron, I.

2012-04-01

The Czech Geological Survey conducted projects of geological mapping and complex geohazard susceptibility zoning in Nicaragua in the years 1997-2009. For selected areas in vicinity of major cities and towns basic geological maps at a scalle 1:50,000, maps of geomorphic features (Geomorphic Inventory Maps), Morphostructural Maps of estimated fault zones, and derived Geohazard Susceptibility maps were done. These maps were prepared during field campaigns by direct field mapping, analysis of remote-sensing data, communicating the local authorities, interwieving the local inhabitants and with very close cooperation with the local partner of the projects - the Instituto Nicaragüense de Estudios Territoriales (INETER). The resulting maps and explanatory reports presented the dangerous natural processes that occurred in each respective area in the past and proposed preventive measures in detail. Zones evaluated as highly susceptible, e.g., to (i) mass movements, (ii) large inundations, (iii) torrential flooding, (iv) seismogenic liquefaction, etc., were presented in bold colours on the maps. Such maps and reports were presented to local authorities and inhabitants of respective cities during public breefings at the end of each mapping campaign. In such a way, areas of Pacific volcanic ridge (1997-2003), Jinotega (2004), Somoto (2005), Estelí (2006), Boaco and Santa Lucia (2007, 2008), Sebaco (2008) and Jalapa (2009) were elaborated. The maps then served to the INETER for implementation into the landuse plans, evacuation routes and other preventive measures to protect and save human lives and inftrastructure. This approach could serve as a muster for a simple, cost effective and relatively fast geohazards susceptibility evaluation of any area in any developing country. The projects also paid attention to capacity building of our Nicaraguan partners. These projects of the Czech Geological Survey were conducted as the international aid of the Czech Republic to Nicaragua

Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain

USDA-ARS?s Scientific Manuscript database

In this study, quantitative trait loci (QTLs) affecting the concentrations of 16 elements in whole, unmilled rice (Oryza sativa L.) grain were identified. Two rice mapping populations, the ‘Lemont’ x ‘TeQing’ recombinant inbred lines (LT-RILs), and the TeQing-into-Lemont backcross introgression lin...

Iterative framework radiation hybrid mapping

USDA-ARS?s Scientific Manuscript database

Building comprehensive radiation hybrid maps for large sets of markers is a computationally expensive process, since the basic mapping problem is equivalent to the traveling salesman problem. The mapping problem is also susceptible to noise, and as a result, it is often beneficial to remove markers ...

Tractography optimization using quantitative T1 mapping in the human optic radiation.

PubMed

Schurr, Roey; Duan, Yiran; Norcia, Anthony M; Ogawa, Shumpei; Yeatman, Jason D; Mezer, Aviv A

2018-06-21

Diffusion MRI tractography is essential for reconstructing white-matter projections in the living human brain. Yet tractography results miss some projections and falsely identify others. A challenging example is the optic radiation (OR) that connects the thalamus and the primary visual cortex. Here, we tested whether OR tractography can be optimized using quantitative T1 mapping. Based on histology, we proposed that myelin-sensitive T1 values along the OR should remain consistently low compared with adjacent white matter. We found that complementary information from the T1 map allows for increasing the specificity of the reconstructed OR tract by eliminating falsely identified projections. This T1-filtering outperforms other, diffusion-based tractography filters. These results provide evidence that the smooth microstructural signature along the tract can be used as constructive input for tractography. Finally, we demonstrate that this approach can be generalized to the HCP-available MRI measurements. We conclude that multimodal MRI microstructural information can be used to eliminate spurious tractography results in the case of the OR. Copyright © 2018. Published by Elsevier Inc.

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

Imaging Cerebral Microhemorrhages in Military Service Members with Chronic Traumatic Brain Injury

PubMed Central

Liu, Wei; Soderlund, Karl; Senseney, Justin S.; Joy, David; Yeh, Ping-Hong; Ollinger, John; Sham, Elyssa B.; Liu, Tian; Wang, Yi; Oakes, Terrence R.; Riedy, Gerard

2017-01-01

Purpose To detect cerebral microhemorrhages in military service members with chronic traumatic brain injury by using susceptibility-weighted magnetic resonance (MR) imaging. The longitudinal evolution of microhemorrhages was monitored in a subset of patients by using quantitative susceptibility mapping. Materials and Methods The study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants underwent two-dimensional conventional gradient-recalled-echo MR imaging and three-dimensional flow-compensated multi-echo gradient-recalled-echo MR imaging (processed to generate susceptibility-weighted images and quantitative susceptibility maps), and a subset of patients underwent follow-up imaging. Microhemorrhages were identified by two radiologists independently. Comparisons of microhemorrhage number, size, and magnetic susceptibility derived from quantitative susceptibility maps between baseline and follow-up imaging examinations were performed by using the paired t test. Results Among the 603 patients, cerebral microhemorrhages were identified in 43 patients, with six excluded for further analysis owing to artifacts. Seventy-seven percent (451 of 585) of the microhemorrhages on susceptibility-weighted images had a more conspicuous appearance than on gradient-recalled-echo images. Thirteen of the 37 patients underwent follow-up imaging examinations. In these patients, a smaller number of microhemorrhages were identified at follow-up imaging compared with baseline on quantitative susceptibility maps (mean ± standard deviation, 9.8 microhemorrhages ± 12.8 vs 13.7 microhemorrhages ± 16.6; P = .019). Quantitative susceptibility mapping–derived quantitative measures of microhemorrhages also decreased over time: −0.85 mm3 per day ± 1.59 for total volume (P = .039) and −0.10 parts per billion per day ± 0.14 for mean magnetic susceptibility (P = .016). Conclusion The number of

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

PubMed

He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

2015-01-01

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

Mapping of thermal injury in biologic tissues using quantitative pathologic techniques

NASA Astrophysics Data System (ADS)

Thomsen, Sharon L.

1999-05-01

Qualitative and quantitative pathologic techniques can be used for (1) mapping of thermal injury, (2) comparisons lesion sizes and configurations for different instruments or heating sources and (3) comparisons of treatment effects. Concentric zones of thermal damage form around a single volume heat source. The boundaries between some of these zones are distinct and measurable. Depending on the energy deposition, heating times and tissue type, the zones can include the following beginning at the hotter center and progressing to the cooler periphery: (1) tissue ablation, (2) carbonization, (3) tissue water vaporization, (4) structural protein denaturation (thermal coagulation), (5) vital enzyme protein denaturation, (6) cell membrane disruption, (7) hemorrhage, hemostasis and hyperhemia, (8) tissue necrosis and (9) wound organization and healing.

The comparison between a ground based and a space based probabilistic landslide susceptibility assessment

NASA Astrophysics Data System (ADS)

Reichenbach, P.; Mondini, A.; Guzzetti, F.; Rossi, M.; Ardizzone, F.; Cardinali, M.

2009-04-01

Probabilistic landslide susceptibility assessments attempt to predict the location and threat posed by known landslides. Under the assumption that landslides will occur in the future because of the same conditions that produced them in the past, geomorphologists use susceptibility assessments to predict the location of future landslides. We present an attempt to exploit satellite data to prepare a landslide susceptibility zonation for a the Collazzone area that extends for 79 sq km in the Umbria region, Central Italy. For the study area we have prepared a map of the Normalized Difference Vegetation Index (NDVI) obtained by processing raw NIR and RED channels (b2 and b3 bands) at 15 m x 15 m resolution of an image acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), on board the TERRA satellite, and a map of Land Surface Temperature (LST) obtained by processing raw TIR channels (b11 to b15 bands) at 90 m × 90 m resolution from the same image. Both maps, in general proxy for soil moisture maps, were obtained through standard algorithms. As expected, there is a strong correspondence between NDVI and LST, but, when the NDVI does not change, elevation effects and others are predominant in LST. For the Collazzone area we prepared two different susceptibility models. The first was prepared through multivariate analysis of thematic data (including morphometry, lithology, structure and land use) obtained through traditional methods, primarily the interpretation of aerial photographs and field work. The second susceptibility model was prepared using terrain morphology and information obtained processing satellite data. The two models were compared in term of model fit and model performance and were validated exploiting landslide inventories not used to build the models. The two susceptibility models are very similar from a geographic and a classification point of view. This is good news, as it tells us that for landslide susceptibility

Non-Susceptible Landslide Areas in Italy and in the Mediterranean Region

NASA Astrophysics Data System (ADS)

Alvioli, Massimiliano; Ardizzone, Francesca; Guzzetti, Fausto; Marchesini, Ivan; Rossi, Mauro

2014-05-01

Landslide susceptibility is the likelihood of a landslide occurring in a given area. Over the past three decades, researchers, and planning and environmental organisations have worked to assess landslide susceptibility at different geographical scales, and to produce maps portraying landslide susceptibility zonation. Little effort was made to determine where landslides are not expected, where susceptibility is null, or negligible. This is surprising because planners and decision makers are also interesting in knowing where landslides are not foreseen, or cannot occur in an area. We propose a method for the definition of non-susceptible landslide areas, at the synoptic scale. We applied the method in Italy and to the territory surrounding the Mediterranean Sea and we produced two synoptic-scale maps showing areas where landslides are not expected in Italy and in the Mediterranean area. To construct the method we used digital terrain elevation and landslide information. The digital terrain consisted in the 3-arc-second SRTM DEM, the landslide information was obtained for 13 areas in Italy where landslide inventory maps were available to us. We tested three different models to determine the non-susceptible landslide areas, including a linear model (LR), a quantile linear model (QLR), and a quantile non-linear model (QNL). Model performances have been evaluated using independent landslide information represented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non- susceptible landslide areas was intersected in a GIS with geographical census data for Italy. The results show that the 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility was expected to be null or negligible, while the remaining 42.5% in areas where some landslide susceptibility was significant or not negligible. We applied the QNL model to the

Both qualitative and quantitative genetic variation of MHC class II molecules may influence susceptibility to autoimmune diseases: the case of endemic pemphigus foliaceus.

PubMed

Piovezan, Bruno Zagonel; Petzl-Erler, Maria Luiza

2013-09-01

The MHC class II transactivator (CIITA) is a key regulator in expression of the HLA class II genes. It is well known that HLA-DRB1 genotypes have a strong influence on the risk of multifactorial autoimmune diseases, but the effect of CIITA genotypes remains controversial. We tested in a case-control study whether CIITA polymorphisms influence the risk of developing endemic pemphigus foliaceus (EPF) and whether CIITA and HLA-DRB1 interact as regards susceptibility to the disease. The rs4774 SNP is not associated to EPF, while rs3087456 in the CIITA gene promoter is associated with susceptibility [odds ratio (OR) = 2.6, p < 0.001 and OR = 2.0 p = 0.003 for genotypes G/G and G/A, respectively]. We suggest that the associations result from the effect of genetically controlled levels of CIITA on expression of the susceptible and protective HLA class II molecules. Remarkably, the interaction between CIITA and HLA-DRB1 genotypes is strong and additive. The OR for individuals having two susceptible HLA-DRB1 alleles is 14.1 in presence of the susceptible CIITA G/G or G/A genotypes and much lower (2.2) in presence of the protective CIITA A/A genotype. We conclude that quantitative as well as qualitative variation of HLA class II molecules have an effect on the risk of an individual developing EPF. Copyright © 2013 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Quantitative evaluation of lumbar intervertebral disc degeneration by axial T2∗ mapping

PubMed Central

Huang, Leitao; Liu, Yuan; Ding, Yi; Wu, Xia; Zhang, Ning; Lai, Qi; Zeng, Xianjun; Wan, Zongmiao; Dai, Min; Zhang, Bin

2017-01-01

Abstract To quantitatively evaluate the clinical value and demonstrate the potential benefits of biochemical axial T2∗ mapping-based grading of early stages of degenerative disc disease (DDD) using 3.0-T magnetic resonance imaging (MRI) in a clinical setting. Fifty patients with low back pain and 20 healthy volunteers (control) underwent standard MRI protocols including axial T2∗ mapping. All the intervertebral discs (IVDs) were classified morphologically. Lumbar IVDs were graded using Pfirrmann score (I to IV). The T2∗ values of the anterior annulus fibrosus (AF), posterior AF, and nucleus pulposus (NP) of each lumbar IVD were measured. The differences between groups were analyzed regarding specific T2∗ pattern at different regions of interest. The T2∗ values of the NP and posterior AF in the patient group were significantly lower than those in the control group (P < .01). The T2∗ value of the anterior AF was not significantly different between the patients and the controls (P > .05). The mean T2∗values of the lumbar IVD in the patient group were significantly lower, especially the posterior AF, followed by the NP, and finally, the anterior AF. In the anterior AF, comparison of grade I with grade III and grade I with grade IV showed statistically significant differences (P = .07 and P = .08, respectively). Similarly, in the NP, comparison of grade I with grade III, grade I with grade IV, grade II with grade III, and grade II with grade IV showed statistically significant differences (P < .001). In the posterior AF, comparison of grade II with grade IV showed a statistically significant difference (P = .032). T2∗ values decreased linearly with increasing degeneration based on the Pfirrmann scoring system (ρ < −0.5, P < .001). Changes in the T2∗ value can signify early degenerative IVD diseases. Hence, T2∗ mapping can be used as a diagnostic tool for quantitative assessment of IVD degeneration. PMID:29390547

Comparative mapping reveals quantitative trait loci that affect spawning time in coho salmon (Oncorhynchus kisutch)

PubMed Central

Araneda, Cristian; Díaz, Nelson F.; Gomez, Gilda; López, María Eugenia; Iturra, Patricia

2012-01-01

Spawning time in salmonids is a sex-limited quantitative trait that can be modified by selection. In rainbow trout (Oncorhynchus mykiss), various quantitative trait loci (QTL) that affect the expression of this trait have been discovered. In this study, we describe four microsatellite loci associated with two possible spawning time QTL regions in coho salmon (Oncorhynchus kisutch). The four loci were identified in females from two populations (early and late spawners) produced by divergent selection from the same base population. Three of the loci (OmyFGT34TUF, One2ASC and One19ASC) that were strongly associated with spawning time in coho salmon (p < 0.0002) were previously associated with QTL for the same trait in rainbow trout; a fourth loci (Oki10) with a suggestive association (p = 0.00035) mapped 10 cM from locus OmyFGT34TUF in rainbow trout. The changes in allelic frequency observed after three generations of selection were greater than expected because of genetic drift. This work shows that comparing information from closely-related species is a valid strategy for identifying QTLs for marker-assisted selection in species whose genomes are poorly characterized or lack a saturated genetic map. PMID:22888302

Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Zhang, Li Yan; Shu, Meiyan; Yang, Guijun

2018-02-01

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. The study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. The correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. Then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. The study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

Magnetic susceptibility mapping of fly ash in soil samples near a coal-burning power plant in Pointe Coupee Parish, Louisiana.

NASA Astrophysics Data System (ADS)

Elhelou, O.; Richter, C.

2015-12-01

Atmospheric deposition of pollutants is a major health and environmental concern. In a 2010 study, the CATF attributed over 13,000 deaths each year to fly ash and other fine particles emitted by U.S. coal-burning power plants. The magnetic properties of fly ash allows for mapping an area suspect of PM pollution faster and more efficiently than by conducting chemical analysis as the former alternative. The objective of this study is to detect the presence of magnetic particles related to the migration of fly ash from a nearby coal power plant over parts of Pointe Coupee Parish, LA. This is based on the idea that the fly ash that is released into the atmosphere during the coal burning process contains heavy metals and magnetic particles in the form of ferrospheres, which can be used to trace back to the source. Maps of the top and sub soil were generated to differentiate the magnetic susceptibility values of the heavy metals potentially attributed to the migration and settling of fly ash onto the surface from any pre-existing or naturally occurring heavy metals in the sub soil. A 60 km2 area in Pointe Coupee Parish was investigated in approximately 0.5 km2 subsets. The area in Pointe Coupee Parish, LA was selected because land use is predominantly rural with the Big Cajun II power plant as the main contributor for air borne contaminants. Samples of fly ash obtained directly from the source below one of the power plant's precipitators were also analyzed to verify the field and laboratory analysis. Contour maps representing the spatial distribution of fly ash over Pointe Coupee, LA, along with histograms of magnetic susceptibility values, and chemical analysis all indicate a correlation between the proximity to the power plant and the predominant wind direction. Acquisition curves of the isothermal remnant magnetization demonstrate the presence of predominantly low coercivity minerals (magnetite) with a small amount of a high-coercivity phase. The microstructure of the

Comparing physically-based and statistical landslide susceptibility model outputs - a case study from Lower Austria

NASA Astrophysics Data System (ADS)

Canli, Ekrem; Thiebes, Benni; Petschko, Helene; Glade, Thomas

2015-04-01

By now there is a broad consensus that due to human-induced global change the frequency and magnitude of heavy precipitation events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as the most common triggering agent for landslide initiation, also an increased landside activity can be expected there. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled. The present and well known problems in modelling landslide susceptibility and hazard give uncertain results in the prediction. This includes the lack of a universal applicable modelling solution for adequately assessing landslide susceptibility (which can be seen as the relative indication of the spatial probability of landslide initiation). Generally speaking, there are three major approaches for performing landslide susceptibility analysis: heuristic, statistical and deterministic models, all with different assumptions, its distinctive data requirements and differently interpretable outcomes. Still, detailed comparison of resulting landslide susceptibility maps are rare. In this presentation, the susceptibility modelling outputs of a deterministic model (Stability INdex MAPping - SINMAP) and a statistical modelling approach (generalized additive model - GAM) are compared. SINMAP is an infinite slope stability model which requires parameterization of soil mechanical parameters. Modelling with the generalized additive model, which represents a non-linear extension of a generalized linear model, requires a high quality landslide inventory that serves as the dependent variable in the statistical approach. Both methods rely on topographical data derived from the DTM. The comparison has been carried out in a study area located in the district of Waidhofen/Ybbs in Lower Austria. For the whole district (ca. 132 km²), 1063 landslides have been mapped and partially used within the analysis and the validation of the model outputs. The respective

Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice

PubMed Central

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Wei, Haibin; Feng, Fangjun; Wang, Pei; Xia, Hui; Li, Tiemei; Luo, Lijun

2015-01-01

Deep rooting is a very important trait for plants’ drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding. PMID:26022253

Quantitative evaluation of fatty degeneration of the supraspinatus and infraspinatus muscles using T2 mapping.

PubMed

Matsuki, Keisuke; Watanabe, Atsuya; Ochiai, Shunsuke; Kenmoku, Tomonori; Ochiai, Nobuyasu; Obata, Takayuki; Toyone, Tomoaki; Wada, Yuichi; Okubo, Toshiyuki

2014-05-01

Although fatty degeneration of the rotator cuff muscles has been reported to affect the outcomes of rotator cuff repairs, only a few studies have attempted to quantitatively evaluate this degeneration. T2 mapping is a quantitative magnetic resonance imaging technique that potentially evaluates the concentration of fat in muscles. The purpose of this study was to investigate fatty degeneration of the rotator cuff muscles by using T2 mapping, as well as to evaluate the reliability of T2 measurement. We obtained magnetic resonance images including T2 mapping from 184 shoulders (180 patients; 110 male patients [112 shoulders] and 70 female patients [72 shoulders]; mean age, 62 years [range, 16-84 years]). Eighty-three shoulders had no rotator cuff tear (group A), whereas 101 shoulders had tears, of which 62 were incomplete to medium (group B) and 39 were large to massive (group C). T2 values of the supraspinatus and infraspinatus muscles were measured and compared among groups. Intraobserver and interobserver variabilities also were examined. The mean T2 values of the supraspinatus in groups A, B, and C were 36.3 ± 4.7 milliseconds, 44.2 ± 11.3 milliseconds, and 57.0 ± 18.8 milliseconds, respectively. The mean T2 values of the infraspinatus in groups A, B, and C were 36.1 ± 5.1 milliseconds, 40.0 ± 11.1 milliseconds, and 51.9 ± 18.2 milliseconds, respectively. The T2 value significantly increased with the extent of the tear in both muscles. Both intraobserver and interobserver variabilities were more than 0.99. T2 mapping can be a reliable tool to quantify fatty degeneration of the rotator cuff muscles. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

Mapping Forest Fire Susceptibility in Temperate Mountain Areas with Expert Knowledge. A Case Study from Iezer Mountains, Romanian Carpathians

NASA Astrophysics Data System (ADS)

Mihai, Bogdan; Savulescu, Ionut

2014-05-01

Forest fires in Romanian Carpathians became a frequent phenomenon during the last decade, although local climate and other environmental features did not create typical conditions. From 2004, forest fires affect in Romania more than 100 hectares/year of different forest types (deciduous and coniferous). Their magnitude and frequency are not known, since a historical forest fire inventory does not exist (only press papers and local witness for some selected events). Forest fires features the summer dry periods but there are dry autumns and early winter periods with events of different magnitudes. The application we propose is based on an empirical modeling of forest fire susceptibility in a typical mountain area from the Southern Carpathians, the Iezer Mountains (2462 m). The study area features almost all the altitudinal vegetation zones of the European temperate mountains, from the beech zone, to the coniferous zone, the subalpine and the alpine zones (Mihai et al., 2007). The analysis combines GIS and remote sensing models (Chuvieco et al., 2012), starting from the ideas that forest fires are featured by the ignition zones and then by the fire propagation zones. The first data layer (ignition zones) is the result of the crossing between the ignition factors: lightning - points of multitemporal occurence and anthropogenic activities (grazing, tourism and traffic) and the ignition zones (forest fuel zonation - forest stands, soil cover and topoclimatic factor zonation). This data is modelled from different sources: the MODIS imagery fire product (Hantson et al., 2012), detailed topographic maps, multitemporal orthophotos at 0.5 m resolution, Landsat multispectral imagery, forestry cadastre maps, detailed soil maps, meteorological data (the WorldClim digital database) as well as the field survey (mapping using GPS and local observation). The second data layer (fire propagation zones) is the result of the crossing between the forest fuel zonation, obtained with the

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

NASA Astrophysics Data System (ADS)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

ANFIS modeling for the assessment of landslide susceptibility for the Cameron Highland (Malaysia)

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet; Sezer, Ebru; Gokceoglu, Candan; Buchroithner, Manfred F.

2010-05-01

Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. In landslide literature, there are several approaches such as probabilistic, bivariate and multivariate statistical models, fuzzy and artificial neural network models etc. However, a neuro-fuzzy application on the landslide susceptibility assessment has not been encountered in the literature. For this reason, this study presents the results of an adaptive neuro-fuzzy inference system (ANFIS) using remote sensing data and GIS for landslide susceptibility analysis in a part of the Cameron Highland areas in Malaysia. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments, NDVI and land cover were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, curvature, distance from drainage, lithology, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to produce the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were constructed. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values were calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 97% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient agreement between the obtained susceptibility map and the existing data on landslide areas. Qualitatively, the model yields reasonable results which can be used for preliminary land

Global Lithospheric Apparent Susceptibility Distribution Converted from Geomagnetic Models by CHAMP and Swarm Satellite Magnetic Measurements

NASA Astrophysics Data System (ADS)

Du, Jinsong; Chen, Chao; Xiong, Xiong; Li, Yongdong; Liang, Qing

2016-04-01

Recently, because of continually accumulated magnetic measurements by CHAMP satellite and Swarm constellation of three satellites and well developed methodologies and techniques of data processing and geomagnetic field modeling etc., global lithospheric magnetic anomaly field models become more and more reliable. This makes the quantitative interpretation of lithospheric magnetic anomaly field possible for having an insight into large-scale magnetic structures in the crust and uppermost mantle. Many different approaches have been utilized to understand the magnetized sources, such as forward, inversion, statistics, correlation analysis, Euler deconvolution, signal transformations etc. Among all quantitative interpretation methods, the directly converting a magnetic anomaly map into a magnetic susceptibility anomaly map proposed by Arkani-Hamed & Strangway (1985) is, we think, the most fast quantitative interpretation tool for global studies. We just call this method AS85 hereinafter for short. Although Gubbins et al. (2011) provided a formula to directly calculate the apparent magnetic vector distribution, the AS85 method introduced constraints of magnetized direction and thus corresponding results are expected to be more robust especially in world-wide continents. Therefore, in this study, we first improved the AS85 method further considering non-axial dipolar inducing field using formulae by Nolte & Siebert (1987), initial model or priori information for starting coefficients in the apparent susceptibility conversion, hidden longest-wavelength components of lithospheric magnetic field and field contaminations from global oceanic remanent magnetization. Then, we used the vertically integrated susceptibility model by Hemant & Maus (2005) and vertically integrated remanent magnetization model by Masterton et al. (2013) to test the validity of our improved method. Subsequently, we applied the conversion method to geomagnetic field models by CHAMP and Swarm satellite

Local delivery of molecules from a nanopipette for quantitative receptor mapping on live cells.

PubMed

Babakinejad, Babak; Jönsson, Peter; López Córdoba, Ainara; Actis, Paolo; Novak, Pavel; Takahashi, Yasufumi; Shevchuk, Andrew; Anand, Uma; Anand, Praveen; Drews, Anna; Ferrer-Montiel, Antonio; Klenerman, David; Korchev, Yuri E

2013-10-01

Using nanopipettes to locally deliver molecules to the surface of living cells could potentially open up studies of biological processes down to the level of single molecules. However, in order to achieve precise and quantitative local delivery it is essential to be able to determine the amount and distribution of the molecules being delivered. In this work, we investigate how the size of the nanopipette, the magnitude of the applied pressure or voltage, which drives the delivery, and the distance to the underlying surface influences the number and spatial distribution of the delivered molecules. Analytical expressions describing the delivery are derived and compared with the results from finite element simulations and experiments on delivery from a 100 nm nanopipette in bulk solution and to the surface of sensory neurons. We then developed a setup for rapid and quantitative delivery to multiple subcellular areas, delivering the molecule capsaicin to stimulate opening of Transient Receptor Potential Vanilloid subfamily member 1 (TRPV1) channels, membrane receptors involved in pain sensation. Overall, precise and quantitative delivery of molecules from nanopipettes has been demonstrated, opening up many applications in biology such as locally stimulating and mapping receptors on the surface of live cells.

Interspecies synteny mapping identifies a quantitative trait locus for bone mineral density on human chromosome Xp22.

PubMed

Parsons, Claire A; Mroczkowski, H Joel; McGuigan, Fiona E A; Albagha, Omar M E; Manolagas, Stavros; Reid, David M; Ralston, Stuart H; Shmookler Reis, Robert J

2005-11-01

Bone mineral density (BMD) is a complex trait with a strong genetic component and an important predictor of osteoporotic fracture risk. Here we report the use of a cross-species strategy to identify genes that regulate BMD, proceeding from quantitative trait mapping in mice to association mapping of the syntenic region in the human genome. We identified a quantitative trait locus (QTL) on the mouse X-chromosome for post-maturity change in spine BMD in a cross of SAMP6 and AKR/J mice and conducted association mapping of the syntenic region on human chromosome Xp22. We studied 76 single nucleotide polymorphisms (SNP) from the human region in two sets of DNA pools prepared from individuals with lumbar spine-BMD (LS-BMD) values falling into the top and bottom 13th percentiles of a population-based study of 3100 post-menopausal women. This procedure identified a region of significant association for two adjacent SNP (rs234494 and rs234495) within the Xp22 locus (P<0.001). Individual genotyping for rs234494 in the BMD pools confirmed the presence of an association for alleles (P=0.018) and genotypes (P=0.008). Analysis of rs234494 and rs234495 in 1053 women derived from the same population who were not selected for BMD values showed an association with LS-BMD for rs234495 (P=0.01) and for haplotypes defined by both SNP (P=0.002). Our study illustrates that interspecies synteny can be used to identify and refine QTL for complex traits and represents the first example where a human QTL for BMD regulation has been mapped using this approach.

Application of Physically based landslide susceptibility models in Brazil

NASA Astrophysics Data System (ADS)

Carvalho Vieira, Bianca; Martins, Tiago D.

2017-04-01

Shallow landslides and floods are the processes responsible for most material and environmental damages in Brazil. In the last decades, some landslides events induce a high number of deaths (e.g. Over 1000 deaths in one event) and incalculable social and economic losses. Therefore, the prediction of those processes is considered an important tool for land use planning tools. Among different methods the physically based landslide susceptibility models having been widely used in many countries, but in Brazil it is still incipient when compared to other ones, like statistical tools and frequency analyses. Thus, the main objective of this research was to assess the application of some Physically based landslide susceptibility models in Brazil, identifying their main results, the efficiency of susceptibility mapping, parameters used and limitations of the tropical humid environment. In order to achieve that, it was evaluated SHALSTAB, SINMAP and TRIGRS models in some studies in Brazil along with the Geotechnical values, scales, DEM grid resolution and the results based on the analysis of the agreement between predicted susceptibility and the landslide scar's map. Most of the studies in Brazil applied SHALSTAB, SINMAP and to a lesser extent the TRIGRS model. The majority researches are concentrated in the Serra do Mar mountain range, that is a system of escarpments and rugged mountains that extends more than 1,500 km along the southern and southeastern Brazilian coast, and regularly affected by heavy rainfall that generates widespread mass movements. Most part of these studies used conventional topographic maps with scales ranging from 1:2000 to 1:50000 and DEM-grid resolution between 2 and 20m. Regarding the Geotechnical and hydrological values, a few studies use field collected data which could produce more efficient results, as indicated by international literature. Therefore, even though they have enormous potential in the susceptibility mapping, even for comparison

Landslide Susceptibility Analysis by the comparison and integration of Random Forest and Logistic Regression methods; application to the disaster of Nova Friburgo - Rio de Janeiro, Brasil (January 2011)

NASA Astrophysics Data System (ADS)

Esposito, Carlo; Barra, Anna; Evans, Stephen G.; Scarascia Mugnozza, Gabriele; Delaney, Keith

2014-05-01

The study of landslide susceptibility by multivariate statistical methods is based on finding a quantitative relationship between controlling factors and landslide occurrence. Such studies have become popular in the last few decades thanks to the development of geographic information systems (GIS) software and the related improved data management. In this work we applied a statistical approach to an area of high landslide susceptibility mainly due to its tropical climate and geological-geomorphological setting. The study area is located in the south-east region of Brazil that has frequently been affected by flood and landslide hazard, especially because of heavy rainfall events during the summer season. In this work we studied a disastrous event that occurred on January 11th and 12th of 2011, which involved Região Serrana (the mountainous region of Rio de Janeiro State) and caused more than 5000 landslides and at least 904 deaths. In order to produce susceptibility maps, we focused our attention on an area of 93,6 km2 that includes Nova Friburgo city. We utilized two different multivariate statistic methods: Logistic Regression (LR), already widely used in applied geosciences, and Random Forest (RF), which has only recently been applied to landslide susceptibility analysis. With reference to each mapping unit, the first method (LR) results in a probability of landslide occurrence, while the second one (RF) gives a prediction in terms of % of area susceptible to slope failure. With this aim in mind, a landslide inventory map (related to the studied event) has been drawn up through analyses of high-resolution GeoEye satellite images, in a GIS environment. Data layers of 11 causative factors have been created and processed in order to be used as continuous numerical or discrete categorical variables in statistical analysis. In particular, the logistic regression method has frequent difficulties in managing numerical continuous and discrete categorical variables

Urbanization and climate change implications in flood risk management: Developing an efficient decision support system for flood susceptibility mapping.

PubMed

Mahmoud, Shereif H; Gan, Thian Yew

2018-04-26

The effects of urbanization and climate change impact to the flood risk of two governorates in Egypt were analyzed. Non-parametric change point and trend detection algorithms were applied to the annual rainfall, rainfall anomaly, and temperature anomaly of both study sites. Next, change points and trends of the annual and monthly surface runoff data generated by the Curve Number method over 1948-2014 were also analyzed to detect the effects of urbanization on the surface runoff. Lastly, a GIS decision support system was developed to delineate flood susceptibility zones for the two governorates. The significant decline in annual rainfall and rainfall anomaly after 1994 at 8.96 and 15.3 mm/decade respectively was likely due to climate change impact, especially significant warming trend since 1976 at 0.16 °C/decade, though that could partly be attributed to rapid urbanization. Since 1970, effects of urbanization to flood risk are clear, because despite a decline in rainfall, the annual surface runoff and runoff anomaly show positive trends of 12.7 and of 14.39 mm/decade, respectively. Eleven flood contributing factors have been identified and used in mapping flood susceptibility zones of both sites. In the El-Beheira governorate, 9.2%, 17.9%, 32.3%, 28.3% and 12.3% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Similarly, in Alexandria governorate, 15.9%, 33.5%, 41%, 8.8% and 0.8% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Very high and high susceptible zones are located in the northern, northwestern and northeastern parts of the Beheira governorates, and in the northeastern and northwestern parts of Alexandria. The flood related information obtained in this study will be useful to assist mitigating potential flood damages and future land use planning of both governorates of Egypt. Copyright © 2018 Elsevier B.V. All

Hypertensive renal disease: susceptibility and resistance in inbred hypertensive rat lines.

PubMed

Braun, Michael C; Herring, Stacy M; Gokul, Nisha; Monita, Monique; Bell, Rebecca; Hicks, M John; Wenderfer, Scott E; Doris, Peter A

2013-10-01

Spontaneously hypertensive rat (SHR) lines differ in their susceptibility to hypertensive end-organ disease and may provide an informative model of genetic risk of disease. Lines derived from the original SHR-B and SHR-C clades are highly resistant to hypertensive end-organ disease, whereas lines derived from the SHR-A clade were selected for stroke susceptibility and experience hypertensive renal disease. Here we characterize the temporal development of progressive renal injury in SHR-A3 animals consuming 0.3% sodium in the diet and drinking water. SHR-A3 rats demonstrate albuminuria, glomerular damage, tubulointerstitial injury, and renal fibrosis that emerge at 18 weeks of age and progress. Mortality of SHR-A3 animals was 50% at 40 weeks of age, and animals surviving to this age had reduced renal function. In contrast SHR-B2, which are 87% genetically identical to SHR-A3, are substantially protected from renal injury and demonstrate only moderate changes in albuminuria and renal histological injury over this time period. At 40 weeks of age, electron microscopy of the renal glomerulus revealed severe podocyte effacement in SHR-A3, but slit diaphragm architecture in SHR-B2 at this age was well preserved. Renal injury traits in the F1 and F2 progeny of an intercross between SHR-A3 and SHR-B2 were measured to determine heritability of renal injury in this model. Heritability of albuminuria, glomerular injury, and tubulointerstitial injury were estimated at 48.9, 66.5 and 58.6%, respectively. We assessed the relationship between blood pressure and renal injury measures in the F2 animals and found some correlation between these variables that explain up to 26% of the trait variation. Quantitative trait locus (QTL) mapping was performed using over 200 single nucleotide polymorphism markers distributed across the 13% of the genome that differs between these two closely related lines. Mapping of albuminuria, tubulointerstitial injury, and renal fibrosis failed to

Mapping lupus susceptibility genes in the NZM2410 mouse model.

PubMed

Morel, Laurence

2012-01-01

Considerable efforts have been deployed over the years to decipher the genetic basis of systemic lupus erythematosus (SLE). The NZM2410 strain is murine model in which the genetic analysis of SLE is the most advanced. NZM2410 studies have shown that, as in SLE patients, lupus susceptibility is achieved by the coexpression of many susceptibility alleles, each of which with a small contribution to the overall disease phenotype. This mouse model has also revealed the critical role played by gene-gene interactions, which are believed to be an essential contribution to human SLE heritability, although it has been much more difficult to characterize. We have now reached a phase in which NZM2410 susceptibility genes have been identified, all them novel in their association with lupus or even with immune functions. Ongoing studies geared at understanding how these genes impact immune tolerance and interact with each other in the mouse, and their impact on the human immune system or target organs, will undoubtedly lead to important discovery for a better understanding on the disease and potential identification of therapeutic targets. Copyright © 2012 Elsevier Inc. All rights reserved.

Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

PubMed

Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

2017-06-01

Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

RFLP-facilitated investigation of the quantitative resistance of rice to brown planthopper ( Nilaparvata lugens).

PubMed

Xu, X. F.; Mei, H. W.; Luo, L. J.; Cheng, X. N.; Li, Z. K.

2002-02-01

Quantitative trait loci (QTLs), conferring quantitative resistance to rice brown planthopper (BPH), were investigated using 160 F(11) recombinant inbred lines (RILs) from the Lemont/Teqing cross, a complete RFLP map, and replicated phenotyping of seedbox inoculation. The paternal indica parent, Teqing, was more-resistant to BPH than the maternal japonica parent, Lemont. The RILs showed transgressive segregation for resistance to BPH. Seven main-effect QTLs and many epistatic QTL pairs were identified and mapped on the 12 rice chromosomes. Collectively, the main-effect and epistatic QTLs accounted for over 70% of the total variation in damage scores. Teqing has the resistance allele at four main-effect QTLs, and the Lemont allele resulted in resistance at the other three. Of the main-effect QTLs identified, QBphr5b was mapped to the vicinity of gl1, a major gene controlling leaf and stem pubescence. The Teqing allele controlling leaf and stem pubescence was associated with resistance, while the Lemont allele for glabrous stem and leaves was associated with susceptibility, indicating that this gene may have contributed to resistance through antixenosis. Similar to the reported BPH resistance genes, the other six detected main-effect QTLs were all mapped to regions where major disease resistance genes locate, suggesting they might have contributed either to antibiosis or tolerance. Our results indicated that marker-aided pyramiding of major resistance genes and QTLs should provide effective and stable control over this devastating pest.

Comparison and validation of shallow landslides susceptibility maps generated by bi-variate and multi-variate linear probabilistic GIS-based techniques. A case study from Ribeira Quente Valley (S. Miguel Island, Azores)

NASA Astrophysics Data System (ADS)

Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.

2009-04-01

Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling

Taking stock of four decades of quantitative research on stakeholder participation and evaluation use: a systematic map.

PubMed

Daigneault, Pierre-Marc

2014-08-01

Stakeholder participation and evaluation use have attracted a lot of attention from practitioners, theorists and researchers. A common hypothesis is that participation is positively associated with evaluation use. Whereas the number of empirical studies conducted on this topic is impressive, quantitative research has held a minority position within this scientific production. This study mobilizes systematic review methods to 'map' the empirical literature that has quantitatively studied participation and use. The goal is to take stock and assess the strength of evidence of this literature (but not to synthesize the findings) and, based on this assessment, to provide directions for future research. Copyright © 2014 Elsevier Ltd. All rights reserved.

Propagation of error from parameter constraints in quantitative MRI: Example application of multiple spin echo T2 mapping.

PubMed

Lankford, Christopher L; Does, Mark D

2018-02-01

Quantitative MRI may require correcting for nuisance parameters which can or must be constrained to independently measured or assumed values. The noise and/or bias in these constraints propagate to fitted parameters. For example, the case of refocusing pulse flip angle constraint in multiple spin echo T 2 mapping is explored. An analytical expression for the mean-squared error of a parameter of interest was derived as a function of the accuracy and precision of an independent estimate of a nuisance parameter. The expression was validated by simulations and then used to evaluate the effects of flip angle (θ) constraint on the accuracy and precision of T⁁2 for a variety of multi-echo T 2 mapping protocols. Constraining θ improved T⁁2 precision when the θ-map signal-to-noise ratio was greater than approximately one-half that of the first spin echo image. For many practical scenarios, constrained fitting was calculated to reduce not just the variance but the full mean-squared error of T⁁2, for bias in θ⁁≲6%. The analytical expression derived in this work can be applied to inform experimental design in quantitative MRI. The example application to T 2 mapping provided specific cases, depending on θ⁁ accuracy and precision, in which θ⁁ measurement and constraint would be beneficial to T⁁2 variance or mean-squared error. Magn Reson Med 79:673-682, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Comparison of the landslide susceptibility models in Taipei Water Source Domain, Taiwan

NASA Astrophysics Data System (ADS)

WU, C. Y.; Yeh, Y. C.; Chou, T. H.

2017-12-01

Taipei Water Source Domain, locating at the southeast of Taipei Metropolis, is the main source of water resource in this region. Recently, the downstream turbidity often soared significantly during the typhoon period because of the upstream landslides. The landslide susceptibilities should be analysed to assess the influence zones caused by different rainfall events, and to ensure the abilities of this domain to serve enough and quality water resource. Generally, the landslide susceptibility models can be established based on either a long-term landslide inventory or a specified landslide event. Sometimes, there is no long-term landslide inventory in some areas. Thus, the event-based landslide susceptibility models are established widely. However, the inventory-based and event-based landslide susceptibility models may result in dissimilar susceptibility maps in the same area. So the purposes of this study were to compare the landslide susceptibility maps derived from the inventory-based and event-based models, and to interpret how to select a representative event to be included in the susceptibility model. The landslide inventory from Typhoon Tim in July, 1994 and Typhoon Soudelor in August, 2015 was collected, and used to establish the inventory-based landslide susceptibility model. The landslides caused by Typhoon Nari and rainfall data were used to establish the event-based model. The results indicated the high susceptibility slope-units were located at middle upstream Nan-Shih Stream basin.

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

PubMed