Enabling Real-Time Compensation in Fast Photochemical Oxidations of Proteins for the Determination of Protein Topography Changes.

Fast photochemical oxidation of proteins (FPOP) is a mass spectrometry-based structural biology technique that probes the solvent-accessible surface area of proteins. This technique relies on the reaction of amino acid side chains with hydroxyl radicals freely diffusing in solution. FPOP generates these radicals in situ by laser photolysis of hydrogen peroxide, creating a burst of hydroxyl radicals that is depleted on the order of a microsecond. When these hydroxyl radicals react with a solvent-accessible amino acid side chain, the reaction products exhibit a mass shift that can be measured and quantified by mass spectrometry. Since the rate of reaction of an amino acid depends in part on the average solvent accessible surface of that amino acid, measured changes in the amount of oxidation of a given region of a protein can be directly correlated to changes in the solvent accessibility of that region between different conformations (e.g., ligand-bound versus ligand-free, monomer vs. aggregate, etc.) FPOP has been applied in a number of problems in biology, including protein-protein interactions, protein conformational changes, and protein-ligand binding. As the available concentration of hydroxyl radicals varies based on many experimental conditions in the FPOP experiment, it is important to monitor the effective radical dose to which the protein analyte is exposed. This monitoring is efficiently achieved by incorporating an inline dosimeter to measure the signal from the FPOP reaction, with laser fluence adjusted in real-time to achieve the desired amount of oxidation. With this compensation, changes in protein topography reflecting conformational changes, ligand-binding surfaces, and/or protein-protein interaction interfaces can be determined in heterogeneous samples using relatively low sample amounts.

Improved Geocoding of Cancer Registry Addresses in Urban and Rural Oklahoma.

BACKGROUND: Between 1997 and 2013 (the included study years), approximately 23% of addresses in the Oklahoma Central Cancer Registry (OCCR) were not geocoded to the address level. Addresses in rural counties were geocoded with poorer quality, preventing the instructive geographic research that informs policymaking. METHODS: To improve the accuracy of the geocodes, we first utilized the United States Postal Service's LACSLink database to correct addresses; specifically, to convert old rural route-based addresses to modernized Enhanced 911 (E911) addresses. We created custom geocoders using regional E911 reference data sets and used existing national scope geocoders of NAVTEQ and the North American Association of Central Cancer Registries. We attempted to geocode 5,102 addresses, which are either regular street addresses or rural route addresses. In the process, we evaluated and tabulated performances of the address correction. Accordingly, we first tabulated how well each geocoder could geocode original and LACSLink corrected addresses. We then documented the overall performances of geocoders based on pairwise comparisons. RESULTS: We were able to geocode 1,945 addresses out of this data set using 5 distinct geocoders. We observed that the LACSLink correction and E911 data were useful in the specific purpose of geocoding rural addresses, as found in the literature. CONCLUSIONS: We conclude that both LACSLink correction and E911 data were useful for improving geocoding of cancer records, many of which were in rural areas. Future directions include further validation of the geocoding and plans to conduct spatial exploratory data analysis to generate hypotheses related to the distribution of cancer in Oklahoma.

Automated Noncontact Facial Topography Mapping, 3-Dimensional Printing, and Silicone Casting of Orbital Prosthesis.

PURPOSE: A proof-of-concept workflow study for the fabrication of custom orbital exenteration prostheses via automated noncontact scanning, 3D printing, and silicone casting. DESIGN: Noncomparative, interventional case series. METHODS: Setting: Single-center institutional study. StudyPopulation: Three patients who have discontinued wearing of the ocularist-made exenteration prosthesis due to altered fit, discoloration, or material degradation. InterventionProcedure: A digital representation of the exenteration socket and contralateral periocular region was captured through noncontact facial topography mapping. Digital construction of the anterior prosthesis surface was based on the mirrored image of the contralateral side, and the posterior surface contour was based on orbital cavity geometry. The anterior and posterior surface details were digitally merged. A 2-piece mold was designed and produced in a 3D printer. Colorimetry was used to create a custom blend of pigments for incorporation into the Shore 40 silicone elastomer to generate a prosthesis that approximates the patient's skin tone. MainOutcomeMeasures: Prosthesis symmetry, skin tone match, comfort of wear, and appearance. RESULTS: The first copy of every 3D-printed orbital prosthesis using this fabrication workflow produced good symmetry, color match, and prosthesis fit. In one case, the recontoured second copy with improved prosthesis edge-to-skin interface was made without the patient present. CONCLUSION: A noncontact 3D scanning, computer-aided design, 3D printing, and silicone casting for fabrication of orbital prosthesis was developed and validated. This production workflow has the potential to provide an efficient, standardized, reproducible exenteration prosthesis and to overcome the principal barriers to an affordable custom prosthesis worldwide: access and cost.

Topography in the Bursting Dynamics of Entorhinal Neurons.

Medial entorhinal cortex contains neural substrates for representing space. These substrates include grid cells that fire in repeating locations and increase in scale progressively along the dorsal-to-ventral entorhinal axis, with the physical distance between grid firing nodes increasing from tens of centimeters to several meters in rodents. Whether the temporal scale of grid cell spiking dynamics shows a similar dorsal-to-ventral organization remains unknown. Here, we report the presence of a dorsal-to-ventral gradient in the temporal spiking dynamics of grid cells in behaving mice. This gradient in bursting supports the emergence of a dorsal grid cell population with a high signal-to-noise ratio. In vitro recordings combined with a computational model point to a role for gradients in non-inactivating sodium conductances in supporting the bursting gradient in vivo. Taken together, these results reveal a complementary organization in the temporal and intrinsic properties of entorhinal cells.

Topography of the pain in classical trigeminal neuralgia: insights into somatotopic organization.

Trigeminal neuralgia is defined by its clinical characteristics of paroxysmal unilateral facial pain in a well-defined territory. Distribution of the pain may be in one or several of the cutaneous and/or mucous territories of the three divisions with V2 pain being the most frequent territory followed by V3 and V1. Factors determining the distribution of pain have not yet been systematically investigated. It is now well recognized that vascular compression factor is a predominant aetiology of classical trigeminal neuralgia. In this study we aimed to find whether there is a relation between the location of the vascular compression and the peripheral distribution of the pain. Patients with classical trigeminal neuralgia in whom microvascular decompression was performed were included. Data recorded pertained to the nature of the conflict, its degree and, most importantly, location around the root: supero-median, supero-lateral or inferior. Equally, clinical data for the distribution of pain were recorded. Most of the patients 318 (89.3%) had the compression coming from above, i.e. 220 (61.7%) had compression from a supero-medial direction and 98 (27.5%) from a supero-lateral direction; inferior compression was present in 38 patients (10.7%). Distribution of the pain was significantly different according to the location of the conflict (P = 0.0005, Fisher Exact test). Odds ratios were computed for each location of compression and painful territory involved. According to the overall distribution of pain, patients with supero-medial compression had an odds ratio of 2.7 [95% confidence interval (CI) 1.66-4.41] of manifesting with V1 pain. Conversely V3 pain was less likely to occur with supero-median compression than the other types of pain (odds ratio 0.53, 95% CI 0.34-0.83). Inferior compression on the other hand was more likely to manifest with V3 pain with an odds ratio of 2.56 (95% CI 1.21-5.45). Overall V2 pain had an odds ratio close to 1 regardless of the type of compression. These findings suggest an association between the location of the neurovascular conflict with its resulting insult and the distribution of pain supporting a somatotopic view of the organization of the trigeminal root and a role of the conflict in the clinical manifestation of trigeminal neuralgia.

Spatial scan statistics for matched case-control data.

Spatial scan statistics are widely used for cluster detection analysis in geographical disease surveillance. While this method has been developed for various types of data such as binary, count, and continuous data, spatial scan statistics for matched case-control data, which often arise in spatial epidemiology, have not been considered. We propose spatial scan statistics for matched case-control data. The proposed test statistics consider the correlations between matched pairs. We evaluate the statistical power and cluster detection accuracy of the proposed methods through simulations compared to the Bernoulli-based method. We illustrate the proposed methods using a real data example. The simulation study clearly revealed that the proposed methods had higher power and higher accuracy for detecting spatial clusters for matched case-control data than the Bernoulli-based spatial scan statistic. The cluster detection result of the real data example also appeared to reflect a higher power of the proposed methods. The proposed methods are very useful for spatial cluster detection for matched case-control data.

Methods for Evaluating the Association Between Alcohol Outlet Density and Violent Crime.

BACKGROUND: The objective of this analysis was to compare measurement methods-counts, proximity, mean distance, and spatial access-of calculating alcohol outlet density and violent crime using data from Baltimore, Maryland. METHODS: Violent crime data (n = 11,815) were obtained from the Baltimore City Police Department and included homicides, aggravated assaults, rapes, and robberies in 2016. We calculated alcohol outlet density and violent crime at the census block (CB) level (n = 13,016). We then weighted these CB-level measures to the census tract level (n = 197) and conducted a series of regressions. Negative binomial regression was used for count outcomes and linear regression for proximity and spatial access outcomes. Choropleth maps, partial R2 , Akaike's Information Criterion, and root mean squared error guided determination of which models yielded lower error and better fit. RESULTS: The inference depended on the measurement methods used. Eight models that used a count of alcohol outlets and/or violent crimes failed to detect an association between outlets and crime, and 3 other count-based models detected an association in the opposite direction. Proximity, mean distance, and spatial access methods consistently detected an association between outlets and crime and produced comparable model fits. CONCLUSIONS: Proximity, mean distance, and spatial access methods yielded the best model fits and had the lowest levels of error in this urban setting. Spatial access methods may offer conceptual strengths over proximity and mean distance. Conflicting findings in the field may be in part due to error in the way that researchers measure alcohol outlet density.

Multi-Parameter Relief Map from High-Resolution DEMs: A Case Study of Mudstone Badland.

Topographic parameters of high-resolution digital elevation models (DEMs) with meter to sub-meter spatial resolution, such as slope, curvature, openness, and wetness index, show the spatial properties and surface characterizations of terrains. The multi-parameter relief map, including two-parameter (2P) or three-parameter (3P) information, can visualize the topographic slope and terrain concavities and convexities in the hue, saturation, and value (HSV) color system. Various combinations of the topographic parameters can be used in the relief map, for instance, using wetness index for upstream representation. In particular, 3P relief maps are integrated from three critical topographic parameters including wetness or aspect, slope, and openness data. This study offers an effective way to explore the combination of topographic parameters in visualizing terrain features using multi-parameter relief maps in badlands and in showing the effects of smoothing and parameter selection. The multi-parameter relief images of high-resolution DEMs clearly show micro-topographic features, e.g., popcorn-like morphology and rill.

Autoencoding Topographic Factors.

Topographic factor models separate overlapping signals into latent spatial functions to identify correlation structure across observations. These methods require the underlying structure to be held fixed and are not robust to deviations commonly found across images. We present autoencoding topographic factors, a novel variational inference scheme, to decompose irregular observations on a lattice into a superposition of low-rank sources. By exploiting recent developments in variational autoencoders, we replace fixed sources with a nonlinear mapping that parameterizes an unnormalized distribution on the lattice. In doing so, we permit sources to drift dynamically, filtering residual differences in location across comparable areas of interest. This gives an implicit mapping to a unique latent representation while simultaneously forcing the posterior to model group variability in spatial structure. Simulation results and applications to functional imaging demonstrate the effectiveness of our method and its ability to outperform existing spatial factor models.

Risk maps for cities: Incorporating streets into geostatistical models.

Vector-borne diseases commonly emerge in urban landscapes, and Gaussian field models can be used to create risk maps of vector presence across a large environment. However, these models do not account for the possibility that streets function as permeable barriers for insect vectors. We describe a methodology to transform spatial point data to incorporate permeable barriers, by distorting the map to widen streets, with one additional parameter. We use Gaussian field models to estimate this additional parameter, and develop risk maps incorporating streets as permeable barriers. We demonstrate our method on simulated datasets and apply it to data on Triatoma infestans, a vector of Chagas disease in Arequipa, Peru. We found that the transformed landscape that best fit the observed pattern of Triatoma infestans infestation, approximately doubled the true Euclidean distance between neighboring houses on different city blocks. Our findings may better guide control of re-emergent insect populations.

Using spatiotemporal models to generate synthetic data for public use.

When agencies release public-use data, they must be cognizant of the potential risk of disclosure associated with making their data publicly available. This issue is particularly pertinent in disease mapping, where small counts pose both inferential challenges and potential disclosure risks. While the small area estimation, disease mapping, and statistical disclosure limitation literatures are individually robust, there have been few intersections between them. Here, we formally propose the use of spatiotemporal data analysis methods to generate synthetic data for public use. Specifically, we analyze ten years of county-level heart disease death counts for multiple age-groups using a Bayesian model that accounts for dependence spatially, temporally, and between age-groups; generating synthetic data from the resulting posterior predictive distribution will preserve these dependencies. After demonstrating the synthetic data's privacy-preserving features, we illustrate their utility by comparing estimates of urban/rural disparities from the synthetic data to those from data with small counts suppressed.

General Practice Clinical Data Help Identify Dementia Hotspots: A Novel Geospatial Analysis Approach.

We have a poor understanding of whether dementia clusters geographically, how this occurs, and how dementia may relate to socio-demographic factors. To shed light on these important questions, this study aimed to compute a dementia risk score for individuals to assess spatial variation of dementia risk, identify significant clusters (hotspots), and explore their association with socioeconomic status. We used clinical records from 16 general practices (468 Statistical Area level 1 s, N = 14,746) from the city of west Adelaide, Australia for the duration of 1 January 2012 to 31 December 2014. Dementia risk was estimated using The Australian National University-Alzheimer's Disease Risk Index. Hotspot analyses were applied to examine potential clusters in dementia risk at small area level. Significant hotspots were observed in eastern and southern areas while coldspots were observed in the western area within the study perimeter. Additionally, significant hotspots were observed in low socio-economic communities. We found dementia risk scores increased with age, sex (female), high cholesterol, no physical activity, living alone (widow, divorced, separated, or never married), and co-morbidities such as diabetes and depression. Similarly, smoking was associated with a lower dementia risk score. The identification of dementia risk clusters may provide insight into possible geographical variations in risk factors for dementia and quantify these risks at the community level. As such, this research may enable policy makers to tailor early prevention strategies to the correct individuals within their precise locations.

The rationale and cost-effectiveness of a confirmatory mapping tool for lymphatic filariasis: Examples from Ethiopia and Tanzania.

Endemicity mapping is required to determining whether a district requires mass drug administration (MDA). Current guidelines for mapping LF require that two sites be selected per district and within each site a convenience sample of 100 adults be tested for antigenemia or microfilaremia. One or more confirmed positive tests in either site is interpreted as an indicator of potential transmission, prompting MDA at the district-level. While this mapping strategy has worked well in high-prevalence settings, imperfect diagnostics and the transmission potential of a single positive adult have raised concerns about the strategy's use in low-prevalence settings. In response to these limitations, a statistically rigorous confirmatory mapping strategy was designed as a complement to the current strategy when LF endemicity is uncertain. Under the new strategy, schools are selected by either systematic or cluster sampling, depending on population size, and within each selected school, children 9-14 years are sampled systematically. All selected children are tested and the number of positive results is compared against a critical value to determine, with known probabilities of error, whether the average prevalence of LF infection is likely below a threshold of 2%. This confirmatory mapping strategy was applied to 45 districts in Ethiopia and 10 in Tanzania, where initial mapping results were considered uncertain. In 42 Ethiopian districts, and all 10 of the Tanzanian districts, the number of antigenemic children was below the critical cutoff, suggesting that these districts do not require MDA. Only three Ethiopian districts exceeded the critical cutoff of positive results. Whereas the current World Health Organization guidelines would have recommended MDA in all 55 districts, the present results suggest that only three of these districts requires MDA. By avoiding unnecessary MDA in 52 districts, the confirmatory mapping strategy is estimated to have saved a total of $9,293,219.

Nanotubular topography enhances the bioactivity of titanium implants.

Surface modification on titanium implants plays an important role in promoting mesenchymal stem cell (MSC) response to enhance osseointegration persistently. In this study, nano-scale TiO2 nanotube topography (TNT), micro-scale sand blasted-acid etched topography (SLA), and hybrid sand blasted-acid etched/nanotube topography (SLA/TNT) were fabricated on the surfaces of titanium implants. Although the initial cell adherence at 60 min among TNT, SLA and TNT/SLA was not different, SLA and SLA/TNT presented to be rougher and suppressed the proliferation of MSC. TNT showed hydrophilic surface and balanced promotion of cellular functions. After being implanted in rabbit femur models, TNT displayed the best osteogenesis inducing ability as well as strong bonding strength to the substrate. These results indicate that nano-scale TNT provides favorable surface topography for improving the clinical performance of endosseous implants compared with micro and hybrid micro/nano surfaces, suggesting a promising and reliable surface modification strategy of titanium implants for clinical application.

Familial aggregation in developmental topographical disorientation (DTD).

A variety of brain lesions may affect the ability to orient, resulting in what is termed "acquired topographical disorientation". In some individuals, however, topographical disorientation is present from childhood, with no apparent brain abnormalities and otherwise intact general cognitive abilities, a condition referred to as "developmental topographical disorientation" (DTD). Individuals affected by DTD often report relatives experiencing the same lifelong orientation difficulties. Here, we sought to assess the familial aggregation of DTD by investigating its occurrence in the families of DTD probands, and in the families of control probands who did not experience topographical disorientation. We found that DTD appears to cluster in the DTD families, with tested relatives displaying the trait, whereas in the control families we did not detect any individuals with DTD. These findings provide the very first evidence for the familial clustering of DTD and motivate further work investigating the genetic factors producing this clustering.

Spatial clustering of "measured" and "unmeasured" risk factors for HIV infections in hyper-endemic communities in KwaZulu-Natal, South Africa: results from geoadditive models.

Sub-Saharan Africa contains more than 60% of all HIV infections worldwide. HIV prevalence was currently estimated to be at least 15% in KwaZulu-Natal and the epidemic is described as hyper-endemic. Knowledge of spatial clustering of risk factors which are linked to new HIV infections is important for prioritizing areas to change the trajectory of the epidemic. Geoadditive models were used to investigate spatial characteristics of the risk factors from two clinical trial units (Umkomaas and Botha's Hill) in the province of KwaZulu-Natal, South Africa. Study population was a cohort of women who screened and enrolled in an HIV prevention biomedical intervention trial. The results suggest high HIV incidence rates (5.8 and 8 per 100 person-year). Considerable spatial variations in behavioural factors within a relatively small geographical region, low level of education, early age at sexual debut, higher number of sexual partners, not being married/cohabitating with a sexual partner and sexual activity in exchange for money, gift and drugs were all determined to be clustered in certain regions; they were accounted for 25% (Umkomaas) and 65% (Botha's Hill) of the excess new HIV infections in two clinical trial units. Results from our study highlighted existence of significant spatial heterogeneity in "measured" and "unmeasured" risk factors in a relatively small region. As the HIV funding has been declining, identifying, targeting and reaching the most-at-risk individuals will likely play a significant role in developing the most efficient and cost-effective prevention programmes and subsequently will change the trajectory of the epidemic.

Retinal topography maps in R: new tools for the analysis and visualization of spatial retinal data.

Retinal topography maps are a widely used tool in vision science, neuroscience, and visual ecology, providing an informative visualization of the spatial distribution of cell densities across the retinal hemisphere. Here, we introduce Retina, an R package for computational mapping, inspection of topographic model fits, and generation of average maps. Functions in Retina take cell count data obtained from retinal wholemounts using stereology software. Accurate visualizations and comparisons between different eyes have been difficult in the past, because of deformation and incisions of retinal wholemounts. We account for these issues by incorporation of the R package Retistruct, which results in a retrodeformation of the wholemount into a hemispherical shape, similar to the original eyecup. The maps are generated by thin plate splines, after the data were transformed into a two-dimensional space with an azimuthal equidistant plot projection. Retina users can compute retinal topography maps independent of stereology software choice and assess model fits with a variety of diagnostic plots. Functionality of Retina also includes species average maps, an essential feature for interspecific analyses. The Retina package will facilitate rigorous comparative studies in visual ecology by providing a robust quantitative approach to generate retinal topography maps.

A new approach for cleansing geographical dataset using Levenshtein distance, prior knowledge and contextual information.

Epidemiological studies are necessary to take public health decisions. Their relevance depends on the quality of data. Doctors in continuous care collect a big amount of data that can be used for epidemiological purpose, but spatial data may be dirty; based on city names, the localization is imprecise, even more if it is misspelled. The only way to identify a city without ambiguity is to use its identifier, which can be retrieved by cleansing geographical textual data. In France, cities are organized in administrative zones called departments and some city names are shared by several cities in several departments. The clear identification of the department and the city name allows to deduce the city unique identifier and to make some spatial analysis such as epidemiological studies. In this paper, we propose a method to cleanse such data, using several steps. After having standardized the text to cleanse, we use the Levenshtein distance to generate a first set of propositions. Finally, the propositions are filtered, by removing the less likely candidates, so that it remains only one, which becomes the chosen city. Tested on a dataset of 9818 entries, we obtained 89.1% of concordance, whereas the standard Levenshtein distance obtained 70.5%. This demonstrates that our method has better results.

Mapping transmission risk of Lassa fever in West Africa: the importance of quality control, sampling bias, and error weighting.

Lassa fever is a disease that has been reported from sites across West Africa; it is caused by an arenavirus that is hosted by the rodent M. natalensis. Although it is confined to West Africa, and has been documented in detail in some well-studied areas, the details of the distribution of risk of Lassa virus infection remain poorly known at the level of the broader region. In this paper, we explored the effects of certainty of diagnosis, oversampling in well-studied region, and error balance on results of mapping exercises. Each of the three factors assessed in this study had clear and consistent influences on model results, overestimating risk in southern, humid zones in West Africa, and underestimating risk in drier and more northern areas. The final, adjusted risk map indicates broad risk areas across much of West Africa. Although risk maps are increasingly easy to develop from disease occurrence data and raster data sets summarizing aspects of environments and landscapes, this process is highly sensitive to issues of data quality, sampling design, and design of analysis, with macrogeographic implications of each of these issues and the potential for misrepresenting real patterns of risk.