Angiotensinergic and noradrenergic neurons in the rat and human heart.

Although the physiological and pharmacological evidences suggest a role for angiotensin II (Ang II) with the mammalian heart, the source and precise location of Ang II are unknown. To visualize and quantitate Ang II in atria, ventricular walls and interventricular septum of the rat and human heart and to explore the feasibility of local Ang II production and function, we investigated by different methods the expression of proteins involved in the generation and function of Ang II. We found mRNA of angiotensinogen (Ang-N), of angiotensin converting enzyme, of the angiotensin type receptors AT(1A) and AT(2) (AT(1B) not detected) as well as of cathepsin D in any part of the hearts. No renin mRNA was traceable. Ang-N mRNA was visualized by in situ hybridization in atrial ganglial neurons. Ang II and dopamine-β-hydroxylase (DβH) were either colocalized inside the same neuronal cell or the neurons were specialized for Ang II or DβH. Within these neurons, the vesicular acetylcholine transporter (VAChT) was neither colocalized with Ang II nor DβH, but VAChT-staining was found with synapses en passant encircle these neuronal cells. The fibers containing Ang II exhibited with blood vessels and with cardiomyocytes supposedly angiotensinergic synapses en passant. In rat heart, right atrial median Ang II concentration appeared higher than septal and ventricular Ang II. The distinct colocalization of neuronal Ang II with DβH in the heart may indicate that Ang II participates together with norepinephrine in the regulation of cardiac functions: Produced as a cardiac neurotransmitter Ang II may have inotropic, chronotropic or dromotropic effects in atria and ventricles and contributes to blood pressure regulation.

Evaluation of Bias in the Hamburg Wheel Tracking Device, RB00-010, 2013

As the list of states adopting the HWTD continues to grow, there is a need to evaluate how results are utilized. AASHTO T 324 does not standardize the analysis and reporting of test results. Furthermore, processing and reporting of the results among manufacturers is not uniform. This is partly due to the variation among agency reporting requirements. Some include only the midpoint rut depth, while others include the average across the entire length of the wheel track. To eliminate bias in reporting, statistical analysis was performed on over 150 test runs on gyratory specimens. Measurement location was found to be a source of significant variation in the HWTD. This is likely due to the nonuniform wheel speed across the specimen, geometry of the specimen, and air void profile. Eliminating this source of bias when reporting results is feasible though is dependent upon the average rut depth at the final pass. When reporting rut depth at the final pass, it is suggested for poor performing samples to average measurement locations near the interface of the adjoining gyratory specimens. This is necessary due to the wheel lipping on the mold. For all other samples it is reasonable to only eliminate the 3 locations furthest from the gear house. For multi‐wheel units, wheel side was also found to be significant for poor and good performing samples. After eliminating the suggested measurements from the analysis, the wheel was no longer a significant source of variation.

An illustration of the ALLOC 6B location-allocation analysis system, 1984

The programs included in this Discussion Paper no. 17 are Distance, Unravel, Retrench and Alloc 6B that deal with location-allocation analyses first published in 1973 by the Department of Geography, The University of Iowa.

Location referencing system team report : final report, 1998

This report is a culmination of the Location Referencing System (LRS) team. The team was charged with defining a system that coordinates the collection storage, and access to location referencing information by developing an LRS to be used throughout the Iowa DOT.

Source-wavelet estimation during full-waveform inversion of ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.

GIS-based debris flow source and runout susceptibility assessment from DEM data - a case study in NW Nicaragua

In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.

Impacts on Safety of Left-Turn Treatment at High Speed Signalized Intersections, HR-347, 1994

Left-turning traffic is a major source of conflicts at intersections. Though an average of only 10% to 15% of all approach traffic turns left, these vehicles are involved in approximately 45% of all accidents. This report presents the results of research conducted to develop models which estimate approach accident rates at high speed signalized intersections. The objective of the research was to quantify the relationship between traffic and intersection characteristics, and accident potential of different left turn treatments. Geometric, turning movement counts, and traffic signal phasing data were collected at 100 intersections in Iowa using a questionnaire sent to municipalities. Not all questionnaires resulted in complete data and ultimately complete data were derived for 63 intersections providing a database of 248 approaches. Accident data for the same approaches were obtained from the Iowa Department of Transportation Accident Location and Analysis System (ALAS). Regression models were developed for two different dependent variables: 1) the ratio of the number of left turn accidents per approach to million left turning vehicles per approach, and 2) the ratio of accidents per approach to million traffic movements per approach. A number of regression models were developed for both dependent variables. One model using each dependent variable was developed for intersections with low, medium, and high left turning traffic volumes. As expected, the research indicates that protected left turn phasing has a lower accident potential than protected/permitted or permitted phasing. Left turn lanes and multiple lane approaches are beneficial for reducing accident rates, while raised medians increase the likelihood of accidents. Signals that are part of a signal system tend to have lower accident rates than isolated signals. The resulting regression models may be used to determine the likely impact of various left turn treatments on intersection accident rates. When designing an intersection approach, a traffic engineer may use the models to estimate the accident rate reduction as a result of improved lane configurations and left turn treatments. The safety benefits may then be compared to any costs associated with operational effects to the intersection (i.e., increased delay) to determine the benefits and costs of making intersection safety improvements.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

High precision anatomy for MEG.

Precise MEG estimates of neuronal current flow are undermined by uncertain knowledge of the head location with respect to the MEG sensors. This is either due to head movements within the scanning session or systematic errors in co-registration to anatomy. Here we show how such errors can be minimized using subject-specific head-casts produced using 3D printing technology. The casts fit the scalp of the subject internally and the inside of the MEG dewar externally, reducing within session and between session head movements. Systematic errors in matching to MRI coordinate system are also reduced through the use of MRI-visible fiducial markers placed on the same cast. Bootstrap estimates of absolute co-registration error were of the order of 1mm. Estimates of relative co-registration error were <1.5mm between sessions. We corroborated these scalp based estimates by looking at the MEG data recorded over a 6month period. We found that the between session sensor variability of the subject's evoked response was of the order of the within session noise, showing no appreciable noise due to between-session movement. Simulations suggest that the between-session sensor level amplitude SNR improved by a factor of 5 over conventional strategies. We show that at this level of coregistration accuracy there is strong evidence for anatomical models based on the individual rather than canonical anatomy; but that this advantage disappears for errors of greater than 5mm. This work paves the way for source reconstruction methods which can exploit very high SNR signals and accurate anatomical models; and also significantly increases the sensitivity of longitudinal studies with MEG.

Relationship between estrogen receptor alpha location and gene induction reveals the importance of downstream sites and cofactors.

BACKGROUND: To understand cancer-related modifications to transcriptional programs requires detailed knowledge about the activation of signal-transduction pathways and gene expression programs. To investigate the mechanisms of target gene regulation by human estrogen receptor alpha (hERalpha), we combine extensive location and expression datasets with genomic sequence analysis. In particular, we study the influence of patterns of DNA occupancy by hERalpha on expression phenotypes. RESULTS: We find that strong ChIP-chip sites co-localize with strong hERalpha consensus sites and detect nucleotide bias near hERalpha sites. The localization of ChIP-chip sites relative to annotated genes shows that weak sites are enriched near transcription start sites, while stronger sites show no positional bias. Assessing the relationship between binding configurations and expression phenotypes, we find binding sites downstream of the transcription start site (TSS) to be equally good or better predictors of hERalpha-mediated expression as upstream sites. The study of FOX and SP1 cofactor sites near hERalpha ChIP sites shows that induced genes frequently have FOX or SP1 sites. Finally we integrate these multiple datasets to define a high confidence set of primary hERalpha target genes. CONCLUSION: Our results support the model of long-range interactions of hERalpha with the promoter-bound cofactor SP1 residing at the promoter of hERalpha target genes. FOX motifs co-occur with hERalpha motifs along responsive genes. Importantly we show that the spatial arrangement of sites near the start sites and within the full transcript is important in determining response to estrogen signaling.