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.

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.

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.

People living in hilly residential areas in metropolitan Perth have less diabetes: spurious association or important environmental determinant?

BACKGROUND: Variations in 'slope' (how steep or flat the ground is) may be good for health. As walking up hills is a physiologically vigorous physical activity and can contribute to weight control, greater neighbourhood slopes may provide a protective barrier to weight gain, and help prevent Type 2 diabetes onset. We explored whether living in 'hilly' neighbourhoods was associated with diabetes prevalence among the Australian adult population. METHODS: Participants (≥25 years; n = 11,406) who completed the Western Australian Health and Wellbeing Surveillance System Survey (2003-2009) were asked whether or not they had medically-diagnosed diabetes. Geographic Information Systems (GIS) software was used to calculate a neighbourhood mean slope score, and other built environment measures at 1600 m around each participant's home. Logistic regression models were used to predict the odds of self-reported diabetes after progressive adjustment for individual measures (i.e., age, sex), socioeconomic status (i.e., education, income), built environment, destinations, nutrition, and amount of walking. RESULTS: After full adjustment, the odds of self-reported diabetes was 0.72 (95% CI 0.55-0.95) and 0.52 (95% CI 0.39-0.69) for adults living in neighbourhoods with moderate and higher levels of slope, respectively, compared with adults living in neighbourhoods with the lowest levels of slope. The odds of having diabetes was 13% lower (odds ratio 0.87; 95% CI 0.80-0.94) for each increase of one percent in mean slope. CONCLUSIONS: Living in a hilly neighbourhood may be protective of diabetes onset or this finding is spurious. Nevertheless, the results are promising and have implications for future research and the practice of flattening land in new housing developments.

Impact of temperature and precipitation on propagation of intestinal schistosomiasis in an irrigated region in Ethiopia: suitability of satellite datasets.

OBJECTIVE: To assess the suitability of satellite temperature and precipitation datasets for investigating the dependence of Schistosoma mansoni disease transmission on meteorological conditions in an irrigated agricultural region in Ethiopia. METHODS: Data used were monthly number of patients infected with S. mansoni and seeking treatment at the local hospital, monthly maximum air temperature from a local weather station, monthly average land surface temperature from MODIS satellite data, monthly total precipitation from a local rain gauge and precipitation estimates from four widely used satellite products, namely, TMPA 3B42RT, TMPA 3B42, CMORPH and PERSIANN. The number of patients was used as proxy for vector abundance. RESULTS: Temperature and precipitation play a role in the transmission of S. mansoni disease. There is a weak but significant positive correlation between monthly maximum air temperature derived from a meteorological station (or average land surface temperature derived from MODIS satellite product) and the number of patients in the same month. There is a significant negative correlation between monthly precipitation volume (derived from rain gauge or satellite data) and number of patients at lags of 1 and 2 months. CONCLUSION: Satellite temperature and precipitation products provide useful information to understand and infer the relationship between meteorological conditions and S. mansoni prevalence.

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

Geoadditive models to assess spatial variation of HIV infections among women in local communities of Durban, South Africa.

BACKGROUND: The severity of the HIV/AIDS epidemic in South Africa varies between and within provinces, with differences noted even at the suburban scale. We investigated the geographical variability of HIV infection in rural areas of the eThekwini Metropolitan Municipality in KwaZulu-Natal province, South Africa. METHOD: We used geoadditive models to assess nonlinear geographical variation in HIV prevalence while simultaneously controlling for important demographic and sexual risk factors. A total of 3,469 women who were screened for a Phase-III randomized trial were included in the current analysis. RESULTS: We found significant spatial patterns that could not be explained by demographic and sexual risk behaviors. In particular, the epidemic was determined to be much worse 44 km south of Durban after controlling for all demographic and sexual risk behaviors. CONCLUSION: The study revealed significant geographic variability in HIV infection in the eThekwini Metropolitan Municipality in KwaZulu-Natal, South Africa.

New tools for epidemiology: a space odyssey.

Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.

The use of remote sensing in the identification of the eco-environmental factors associated with the risk of human visceral leishmaniasis (kala-azar) on the Gangetic plain, in north-eastern India.

Human visceral leishmaniasis (VL) or kala-azar remains a major cause of mortality, particularly in the developing world. The disease is common in the internal regions of north-eastern India, which have a tropical or sub-tropical climate. In a recent study on VL in this region, the relationship between the incidence of VL and certain physio-environmental factors was explored, using a combination of a geographical information system (GIS), satellite imagery and data collected 'on the ground'. Some eco-environmental parameters were then used to map and describe the spatial heterogeneity seen in the transmission of the parasite (Leishmania donovani) that causes VL in India, and to identify those habitats, on the Gangetic plain, where the sandfly vectors might thrive. It was found that the presence of waterbodies, woodland and urban, built-up areas, soil of the fluvisol type, air temperatures of 25.0-27.5 degrees C, relative humidities of 66%-75%, and an annual rainfall of 100-<160 cm were all positively associated with the incidence of VL. A VL map was created and stratified into areas of 'risk' and 'non-risk' for the disease, based on calculations of risk indices.

Exposure to particulate air pollution at different living locations and respiratory symptoms in Hong Kong--an application of satellite information.

Respiratory ill-health effects due to particulate air exposure at different geographical locations in Hong Kong that aggregate individual living locations were estimated based on satellite information. We assessed the presence of respiratory symptoms of a frequent cough or sputum in school students aged 11-20 years old (n = 9,881). Daily particulate air pollution levels at students' living locations were derived from the surface extinction coefficients measured by satellite and measurements from the air pollutant monitoring stations at ground level. Adjusted odds ratio (OR) [95% CI] of respiratory symptoms was 1.047 [1.005, 1.091] per 10 microg m(-3) increase in PM(10) concentration. Specificity tests showed that adjusted OR of having other symptoms is not significant (p = 0.20-0.94). Exposures to PM(10) at different geographical locations is associated with increased odds of having respiratory symptoms (cough or sputum) but not with other symptoms unrelated to air pollution.

Obesity atlas and methodbox: towards an open framework for sharing public health intelligence workflows.

The large growth in data sources relevant to public health has not been matched by a growth in human resource for producing intelligence to support decisions or generate new insights. There is a need to bring scarce public health expertise into closer alignment with data and data processing methods to support timely public health analysis. The difficulties of developing and sharing this expertise in large organisations such as the UK's National Health Service have long been recognised. We report findings in this area across two projects Obesity Atlas and Methodbox, which are developing and sharing best practice between Public Health Analysts in England, and we address the relevant generic knowledge management problems in the Public Health community.

Spatiotemporal antibiotic resistance pattern monitoring using geographical information system based hierarchical cluster analysis.

Bacterial antimicrobial resistance in both the medical and agricultural fields has become a serious problem worldwide. Antibiotic resistant strains of bacteria are an increasing threat to human health, with resistance mechanisms having been described to all known antimicrobials currently available for clinical use. Monitoring the geotemporal variations of antibiotic resistance pattern is crucial factor in planning a successful therapeutic guidelines preventing further emergence of antibiotic resistance. This study is based on the retrospective spatiotemporal analysis of laboratory results of Antibiotic Sensitivity Tests, time stamped with the date and time of the microbiological specimen dispatched to the laboratory. Geographic location of the isolated bacterial colony is specified with the latitude and the longitude of the patient's location. Agglomerative Hierarchical Clustering was performed on antimicrobial resistance findings based on the geographic locations generating series of Heatmaps to visualize the extent of the resistance pattern. Sequential Hierarchical cluster analysis was proven to be effective in visualization of antibiotic resistance using Heatmaps demonstrating the temporal variations of the antibiotic resistance patterns.

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.

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.

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.

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.

Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review.

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed.