The Spatial Scale and Spread of Child Victimization.

Previous research shows that large, densely populated urban areas have higher rates of child victimization that have persisted over time. However, few investigations have inquired about the processes that produce and sustain hot and cold spots of child victimization. As a result, the mechanisms that produce the observed spatial clustering of child victimization, and hence "why" harms against children tend to cluster in space, remains unknown. Does the likelihood of being a victim of violence in one location depend on a similar event happening in a nearby location within a specified timeframe? Rather, are child victims of violence more likely to reside in suboptimal neighborhood conditions? This paper aims to present an analytical and theoretical framework for distinguishing between these locational (point) processes to determine whether the empirical spatial patterns undergirding child victimization are more reflective of the "spread" via contagion (i.e., dependency) or whether they are produced by neighborhood structural inequality resulting from spatial heterogeneity. To detect spatial dependence, we applied the inhomogeneous K-function to Los Angeles Medical Examiner data on child homicide victim locations while controlling for regional differences in victimization events (i.e., heterogeneity). Our analysis found strong evidence of spatial clustering in child victimization at small spatial scales but inhibition at larger scales. We further found limited support for the spatiotemporal clustering of child victimization indicative of a contagion effect. Overall, our results support the role of neighborhood structural vulnerability in the underlying mechanisms producing patterns of child victimization across Los Angeles County. We conclude by discussing the policy implications for understanding this spatial patterning in geographical context and for developing effective and targeted preventive interventions.

A Hypothesis Test for Detecting Distance-Specific Clustering and Dispersion in Areal Data.

Spatial clustering detection has a variety of applications in diverse fields, including identifying infectious disease outbreaks, pinpointing crime hotspots, and identifying clusters of neurons in brain imaging applications. Ripley's K-function is a popular method for detecting clustering (or dispersion) in point process data at specific distances. Ripley's K-function measures the expected number of points within a given distance of any observed point. Clustering can be assessed by comparing the observed value of Ripley's K-function to the expected value under complete spatial randomness. While performing spatial clustering analysis on point process data is common, applications to areal data commonly arise and need to be accurately assessed. Inspired by Ripley's K-function, we develop the positive area proportion function (PAPF) and use it to develop a hypothesis testing procedure for the detection of spatial clustering and dispersion at specific distances in areal data. We compare the performance of the proposed PAPF hypothesis test to that of the global Moran's I statistic, the Getis-Ord general G statistic, and the spatial scan statistic with extensive simulation studies. We then evaluate the real-world performance of our method by using it to detect spatial clustering in land parcels containing conservation easements and US counties with high pediatric overweight/obesity rates.

Sex-based differences in the distribution of Aujeszky's disease-seropositive Japanese wild boar.

BACKGROUND: Aujeszky's disease virus (ADV) primarily infects domestic pigs and wild boars, causing the abortion and death of young piglets due to central nervous system disorders. In Japan, the national eradication program for ADV in domestic pigs has been successful in most prefectures; however, concern has been raised regarding ADV-infected wild boars as a source of transmission to domestic pigs. RESULTS: We assessed the nationwide seroprevalence of ADV among wild boars (Sus scrofa) in Japan. Moreover, we determined the sex-based differences in the spatial clustering of seropositive animals. Serum samples were obtained from a total of 1383 wild boars acquired by hunting in 41 prefectures in three fiscal years (April-March in 2014, 2015, and 2017). Seropositivity tests for ADV using enzyme-linked immunosorbent assay, the latex agglutination and neutralization tests showed 29 boars seropositive for ADV (29/1383, 2.1% [95% confidence interval, CI: 1.4-3.0%]), with 28 of these boars originating from three prefectures in the Kii Peninsula (28/121, 23.1% [95% CI: 16.0-31.7%]). The degree of spatial clustering of these ADV-seropositive adult boars in the Kii Peninsula was evaluated using the K-function and data from sera samples of 46 (14 seropositive) male and 54 (12 seropositive) female boars. The degree of clustering among females was significantly higher in seropositive animals than in tested animals; however, such a difference was not observed for seropositive males. CONCLUSIONS: The spatial dynamics of ADV among adult wild boars may be characterized based on sex, and is likely due to sex-based differences in behavioral patterns including dispersal among wild boars.

Spatial organization of lysosomal exocytosis relies on membrane tension gradients.

Lysosomal exocytosis is involved in many key cellular processes but its spatiotemporal regulation is poorly known. Using total internal reflection fluorescence microscopy (TIRFM) and spatial statistics, we observed that lysosomal exocytosis is not random at the adhesive part of the plasma membrane of RPE1 cells but clustered at different scales. Although the rate of exocytosis is regulated by the actin cytoskeleton, neither interfering with actin or microtubule dynamics by drug treatments alters its spatial organization. Exocytosis events partially co-appear at focal adhesions (FAs) and their clustering is reduced upon removal of FAs. Changes in membrane tension following a hypo-osmotic shock or treatment with methyl-ß-cyclodextrin were found to increase clustering. To investigate the link between FAs and membrane tension, cells were cultured on adhesive ring-shaped micropatterns, which allow to control the spatial organization of FAs. By using a combination of TIRFM and fluorescence lifetime imaging microscopy (FLIM), we revealed the existence of a radial gradient in membrane tension. By changing the diameter of micropatterned substrates, we further showed that this gradient as well as the extent of exocytosis clustering can be controlled. Together, our data indicate that the spatial clustering of lysosomal exocytosis relies on membrane tension patterning controlled by the spatial organization of FAs.

Point pattern analysis and classification on compact two-point homogeneous spaces evolving time.

This paper introduces a new modeling framework for the statistical analysis of point patterns on a manifold Md, defined by a connected and compact two-point homogeneous space, including the special case of the sphere. The presented approach is based on temporal Cox processes driven by a L2(Md)-valued log-intensity. Different aggregation schemes on the manifold of the spatiotemporal point-referenced data are implemented in terms of the time-varying discrete Jacobi polynomial transform of the log-risk process. The n-dimensional microscale point pattern evolution in time at different manifold spatial scales is then characterized from such a transform. The simulation study undertaken illustrates the construction of spherical point process models displaying aggregation at low Legendre polynomial transform frequencies (large scale), while regularity is observed at high frequencies (small scale). K-function analysis supports these results under temporal short, intermediate and long range dependence of the log-risk process.

Identifying community-level disparities in access to driver education and training: Toward a definition of driver training deserts.

OBJECTIVE: Obtaining a license may be challenging for teens due to access to driving instruction; in some states, behind-the-wheel (BTW) instruction is required to secure a license before age 18. We investigate spatial accessibility to BTW centers, and how this geographic distribution intersects with metrics of social disparity at the metropolitan level, toward identifying Driver Training Deserts (DTDs): geographic areas of disconnection to driver training. METHODS: For the Columbus OH region, we collect socioeconomic variables at the Census tract unit of analysis and geocoded locations of public and private BTW training centers and estimate travel time to the nearest BTW training center. We define travel time as either the mean or the maximum travel time to BTW centers across all 1 km × 1 km grid cells within a Census tract. We employ spatial statistical approaches, including homogeneous/inhomogeneous K functions, to determine whether BTW training centers are clustered. Next, we define DTDs as Census tracts with a poverty rate and travel time to BTW centers larger than the 75th percentile values across the region. RESULTS: BTW training centers are spatially clustered across the region; the magnitude of this clustering is so great that BTW centers exhibit statistically significant patterns of clustering, even when considering the underlying spatial distribution of socio-economic characteristics. We find that 11-27 Census tracts are identified as DTDs depending on the definition of travel time. DTDs contain a disproportionate percent of the high poverty population (8.7-23.5%) and, depending on the definition of travel time, a disproportionately large African American population. CONCLUSIONS: Methodologically, defining DTDs necessitates a fine-grained spatial approach as suburban and rural Census tracts tend to be large and thus can be poorly represented by travel times averaged over the Census tract. Defining DTDs as a measure of individual-specific variables - income and impedance - allows DTDs to be addressed with policy interventions. The findings motivate future research correlating DTDs with licensure rates, enrollment in driver training, and safe driving outcomes to understand if DTDs can help explain health equity outcomes related to young driver safety.

Pairwise interaction Markov model for 3D epidermal nerve fibre endings.

In this paper, the spatial arrangement and possible interactions between epidermal nerve fibre endings are investigated and modelled by using confocal microscopy data. We are especially interested in possible differences between patterns from healthy volunteers and patients suffering from mild diabetic neuropathy. The locations of the points, where nerves enter the epidermis, the first branching points and the points where the nerve fibres terminate, are regarded as realizations of spatial point processes. We propose an anisotropic point process model for the locations of the nerve fibre endings in three dimensions, where the points interact in cylindrical regions. First, the locations of end points in R 2 $\mathbb {R}^2$ are modelled as clusters around the branching points and then, the model is extended to three dimensions using a pairwise interaction Markov field model with cylindrical neighbourhood for the z-coordinates conditioned on the planar locations of the points. We fit the model to samples taken from healthy subjects and subjects suffering from diabetic neuropathy. In both groups, after a hardcore radius, there is some attraction between the end points. However, the range and strength of attraction are not the same in the two groups. Performance of the model is evaluated by using a cylindrical version of Ripley's K function due to the anisotropic nature of the data. Our findings suggest that the proposed model is able to capture the 3D spatial structure of the end points.

Spatial distribution characteristics of stomata at the areole level in Michelia cavaleriei var. platypetala (Magnoliaceae).

BACKGROUND AND AIMS: In hierarchically reticulate venation patterns, smaller orders of veins form areoles in which stomata are located. This study aimed to quantify the spatial relationship among stomata at the areole level. METHODS: For each of 12 leaves of M. cavaleriei var. platypetala, we assumed that stomatal characteristics were symmetrical on either side of the midrib, and divided the leaf surface on one side of the midrib into six layers equidistantly spaced along the apical-basal axis. We then further divided each layer into three positions equidistantly spaced from midrib to leaf margin, resulting in a total of 18 sampling locations. In addition, for 60 leaves, we sampled three positions from midrib to margin within only the widest layer of the leaf. Stomatal density and mean nearest neighbour distance (MNND) were calculated for each section. A replicated spatial point pattern approach quantified stomatal spatial relationships at different distances (0-300 µm). KEY RESULTS: A tendency towards regular arrangement (inhibition as opposed to attraction or clustering) was observed between stomatal centres at distances <100 µm. Leaf layer (leaf length dimension) had no significant effect on local stomatal density, MNND or the spatial distribution characteristics of stomatal centres. In addition, we did not find greater inhibition at the centre of areoles, and in positions farther from the midrib. CONCLUSIONS: Spatial inhibition might be caused by the one-cell-spacing rule, resulting in more regular arrangement of stomata, and it was found to exist at distances up to ~100 µm. This work implies that leaf hydraulic architecture, consisting of both vascular and mesophyll properties, is sufficient to prevent important spatial variability in water supply at the areole level.

Super-Resolution Imaging and Spatial Analysis of RAS on Intact Plasma Membrane Sheets.

The function of lipid-anchored small GTPases RAS proteins is mostly compartmentalized to the plasma membrane (PM). Complex biophysical interactions between the C-terminal membrane-anchoring domains of RAS isoforms and PM lipids drive spatial segregation of RAS molecules in the formation of nanometer-sized domains, termed as nanoclusters. These RAS/lipid proteolipid nano-assemblies are the main sites for efficient effector recruitment and signal transduction. Here, we describe a super-resolution imaging method to quantify the nanometer-sized nanoclustering of RAS over a length scale between 8 and 240 nm on intact PM sheets of mammalian cells. Detailed molecular spatial distribution parameters, including the extent of nanoclustering, average cluster size, clustered fraction, and population distribution can be obtained by the univariate spatial distribution analysis. Intermolecular associations between different RAS isoforms, RAS and various PM lipids, as well as RAS and diverse effectors can be quantified via bivariate co-localization analysis.

Spatial heterogeneity assessment of factors affecting sewer pipe blockages and predictions.

Efficient management of sewer blockages requires increased preventive maintenance planning. Conventional approaches to the management of blockages in sewer pipe networks constitute largely unplanned maintenance stemming from a lack of adequate information and diagnosis of blockage causative mechanisms. This study mainly investigated a spatial statistical approach to determine the influence of explanatory factors on increased blockage propensity in sewers based on spatial heterogeneity. The approach consisted of the network K-function analysis, which provided an understanding of the significance of the spatial variation of blockages. A geographically-weighted Poisson regression then showed the degree of influence that explanatory factors had on increased blockage propensity in differentiated segments of the sewer pipe network. Lastly, blockage recurrence predictions were carried out with Random Forest ensembles. This approach was applied to three municipalities. Explanatory factors such as material type, number of service connections, self-cleaning velocity, sagging pipes, root intrusion risk, closed-circuit television inspection grade and distance to restaurants showed significant spatial heterogeneity and varying impacts on blockage propensity. The Random Forest ensemble predicted blockage recurrence with 60-80% accuracy for data from two municipalities and below 50% for the last. This approach provides knowledge that supports proactive maintenance planning in the management of blockages in sewer pipe networks.

Spatial distribution of six managed tree species is influenced by topography conditions in the Central Amazon.

In tropical forests, the spatial distribution of trees may present random, uniform, or grouped patterns that can simultaneously be affected by site and species characteristics. In Central Amazon, topographic gradients and soil water levels drive differences in tree species distribution and in forest dynamics at local scales. Knowing this kind of information can be useful for a forest manager to plan harvesting operations considering the microhabitat preference of merchantable species to reduce the disturbances caused by logging activities. Thus, the spatial variation of tree species is an important information to be considered to support the planning process of forest logging. The present study aims to evaluate the spatial distribution pattern of six species and analyze the relationship between the topography and the population densities and stem size of those species. The study was carried out in a forest production compartment managed by a private company located in the municipality of Silves, state of Amazonas, Brazil. The spatial pattern of the six species was characterized by Ripley's K function. Spatial distribution of diameter at breast height (DBH) and tree density based on kernel incidence calculation were evaluated for topographic classes of slope, elevation, and distance from streams, which were mapped using geographic information systems (GIS). The means of DBH and density of each species were compared among topographic classes by ANOVA and Tukey's test. The results demonstrated the predominance of the aggregate distribution pattern for the six species up to 1105 m (p < 0.01). The tree species Minquartia guianensis Aubl., Protium puncticulatum J.F.Macbr, Manilkara elata (Allemão ex Miq.) Monach, and Caryocar glabrum Aubl. Pers showed an increase in the tree density as the distance from the streams and elevation increased, standing spatially incident on plateaus. Kernel densities of Dinizia excelsa Ducke and Goupia glabra Aubl. were higher closer to streams. The DBH averages followed similar trends of population density for M. guianensis, M. elata, and C. glabrum, and the opposite pattern for D. excelsa, which presented larger individuals in less densely populated areas. P. puncticulatum and G. glabra mean DBH distribution was not affected by the topographic variables analyzed. Topography-related variables showed effects on variations of density and tree size, suggesting that species may be spatially sensitive to the habitat variability available in the study area. In view of logging planning, spatial distribution must be considered in decisions related to cutting down trees and maintenance of remaining trees, especially because some species are more aggregated in smaller scales. Moreover, as topographic variations affect the spatial distribution of size and density, the timber yield will vary spatially in the area, bringing implications for planning logging intensities, roads, skid trails and forest operations. Finally, the procedures and information generated in this study can be reproduced and applied to other species and managed areas to support the planning toward minimizing impacts on the spatial structure of commercial species, as well as to increase the chances of future stock recovery of managed forests in the Amazon.

Three dimensional cluster analysis for atom probe tomography using Ripley's K-function and machine learning.

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley's K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K(r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K(r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. We find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K(r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

Spatial Outcomes of Soft Tissue Sarcoma in Southern West Virginia.

Introduction Dioxins, polychlorinated biphenyls (PCBs), and 2,3,7,8-Tetrachlorodibenzodioxin (TCDDs) are persistent organic pollutants widely distributed in the food chain. For over 50 years, the Monsanto plant in Nitro, West Virginia, created dioxin waste while producing herbicides, Agent Orange (during the Vietnam War), and different forms of rubber. Recent and past literature has established a link between the Monsanto plant and increased cancer cases within the region. Soft tissue sarcoma is one of the few specific cancers that has been linked to dioxin exposure. This pilot study examined whether sarcoma cases were clustered or randomly distributed within Kanawha County, West Virginia over the years 2000 to 2013. We hypothesize that sarcoma cancer cases will be spatially clustered. Methods This study assessed the spatial distribution of cancer patients with addresses within the Nitro, West Virginia, and study area. The Charleston Area Medical Center shared soft tissue sarcoma (n = 97) cases from 2000 to 2013. An unweighted K function with confidence intervals (99 Monte Carlo permutations) and 10 distance at 2800 meters each band analyzed the distribution of cases. Results The results suggest that sarcoma cases are slightly clustered within the study area. The region also has a high concentration of chemical and industrial sites. The eighth distance band exhibited the greatest difference (11384), between the expected versus the observed K function. Conclusion The unweighted K function shows non-random clustering. Future studies could investigate possible associations to industrial, chemical, or other possible point source contamination within the study area.

Schistosoma japonicum-infected sentinel mice: Surveillance and spatial point pattern analysis in Hubei province, China, 2010-2018.

OBJECTIVES: Progress in national schistosomiasis control in China has successfully reduced disease transmission in many districts. However, a low transmission rate hinders conventional snail surveys in identifying areas at risk. In this study, Schistosoma japonicum-infected sentinel mice surveillance was conducted to identify high-risk areas of schistosomiasis transmission in Hubei province, China. METHODS: The risk of schistosomiasis transmission was assessed using sentinel mice monitoring in Hubei province from 2010 to 2018. Field detections were undertaken in June and September, and the sentinel mice were kept for approximately 35 days in a laboratory. They were then dissected to determine whether schistosome infection was present. Ripley's K-function and kernel density estimation were applied to analyze the spatial distribution and positive point pattern of schistosomiasis transmission. RESULTS: In total, 190 sentinel mice surveillance sites were selected to detect areas of schistosomiasis infection from 2010 to 2018, with 29 (15.26%) sites showing infected mice. Of 4723 dissected mice, 256 adult worms were detected in 112 infected mice. The infection rate was 2.37%, with an average of 2.28 worms detected per infected mouse. Significantly more infected mice were detected in the June samples than in the September samples (χ2=12.11, p<0.01). Ripley's L(d) index analysis showed that, when the distance was ≤34.52km, the sentinel mice infection pattern showed aggregation, with the strongest aggregation occurring at 7.86km. Three hotspots were detected using kernel density estimation: at the junction of Jingzhou District, Gong'an County, and Shashi District in Jingzhou City; in Wuhan City at the border of the Huangpi and Dongxihu Districts, and in the Hannan and Caidian Districts. CONCLUSION: The results showed that sentinel mice surveillance is useful in identifying high-risk areas, and could provide valuable information for schistosomiasis prevention and control, especially concerning areas along the Yangtze River, such as the Fu-Lun, Dongjing-Tongshun, and Juzhang River basins.

Spatio-temporal analysis of oak decline process in open woodlands: A case study in SW Spain.

This study aims to characterize at landscape level the spatio-temporal dynamics of a massive oak decline that is occurring in dehesas ecosystems. We are looking at possibilities of matching with Phytophthora disease behavior, a harmful disease detected in the studied area, in order to interpret its implications within the context of the disease management. Spatial locations of affected trees from 2001, 2009 and 2016 identified through photointerpretation were analyzed with the inhomogeneous Ripley's K-function to assess their spatial pattern. Multivariate Adaptive Regression Splines (MARS), a non-parametric data mining method, was used to investigate the influence of a range of landscape descriptors of different nature on the proneness to oak decline, using the location of affected trees in comparison with that of healthy spots (points randomly extracted from areas covered by healthy trees). Affected trees showed a strong clustering pattern that decreased over time. The reported spatial patterns align with the hypothesis of Phytophthora cinnamomi Rands. being the main cause of oak decline in Mediterranean forests. Location of affected trees detected in different years was found to be spatially related, suggesting the implication of a contagion process. MARS models from 2001, 2009 and 2016 reported Area Under the Curve (AUC) values of 0.707, 0.671 and 0.651, respectively. Slope was the most influential landscape descriptor across the three years, with distance to afforestations being the second for 2001 and 2009. Landscape descriptors linked to human factors and soil water content seem to influence oak decline caused by Phytophthora cinnamomi at landscape level. Afforestations carried out as part of the afforestation subsidy program promoted by the European Commission in 1992 could have acted as an initial source of Phytophthora cinnamomi infection. These findings together with the consideration of the spatial and temporal scale of the spreading are essential when planning the management of oak decline in open woodlands.

Cattle influence on the population structure of yerba mate (Ilex paraguariensis) in Araucaria Forest / Influência do gado na estrutura populacional de erva-mate (Ilex paraguariensis) em Floresta com Araucárias

ABSTRACT: This study characterized the demography and spatial pattern of a yerba mate (Ilex paraguariensis A.St.-Hil) population covering areas with different use histories (Presence and Absence of Cattle) in a Araucaria Forest. Data collection was performed in three ha, half in each area. The frequency of individuals by height, spatial distribution pattern, diameter distribution (for reproductive individuals) and sexual ratio were evaluated. An inverted "J" pattern predominated, being exclusive to an area with Cattle Presence, a place which presented a lower density of individuals. The predominant spatial distribution pattern was aggregated, and the reproductive individuals have a preferentially random pattern at the shortest distances. Results indicated that cattle presence changes the density of I. paraguariensis individuals and the proportion of individuals in the evaluated demographic classes.

RESUMO: Foi caracterizada a demografia e o padrão espacial de uma população de erva-mate (Ilex paraguariensis A.St.-Hil) abrangendo áreas em diferentes históricos de uso (presença e ausência de gado), em Floresta com Araucárias. A coleta de dados foi realizada em três ha, metade em cada área. Foi avaliada a frequência de indivíduos por classe de altura, padrão de distribuição espacial, distribuição diamétrica (para indivíduos reprodutivos) e razão sexual. O padrão "J" invertido foi predominante, sendo exclusivo para área com presença de gado, local que apresentou uma menor densidade de indivíduos. O padrão de distribuição espacial predominante foi o agregado, sendo que os indivíduos reprodutivos possuem preferencialmente padrão aleatório nas menores distâncias. Os resultados indicam que a presença do gado altera a densidade de I. paraguariensis e a proporção de indivíduos nas classes demográficas avaliadas.

Spatial point pattern analysis of hemorrhagic fever with renal syndrome in Jingzhou, Hubei Province, 2017 / 中华疾病控制杂志

Objective To analyze the spatial point pattern distribution characteristics of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou city, Hubei province during the two seasons spring- summer and autumn-winter of 2017, to discuss its high incidence area and reason, and to provide basis for the resource allocation of public health. Methods The analytical data was collected from Infectious Disease Reporting Information System in China, and the spring-summer season was from March to August of 2017, while the autumn-winter was from the September of 2017 to the February of 2018. The Ripley's K-function and kernel density estimation were applied to analyze the spatial point pattern distribution and compare the distribution characteristics of spatial point pattern between the two seasons. Results In 2017, 133 cases of HFRS were reported in Jingzhou city, including the spring- summer and autumn-winter two pick incidences. The strongest aggregation distance was 17.77km in spring-summer season, and 14.40 km in autumn-winter season. The spatial gathering center was located in the north of Jianli County in spring-summer, and it moved to the south of Jiangling County and Shashi District in autumn-winter. Conclusions The key areas for the prevention and control of HFRS in Jingzhou City are Jiangling County, the southern part of Shashi District and the northern part of jianli county. The key groups are the residents of the urban-rural junction in the southern part of Shashi City, residents along the route of large-scale projects, and farmers engaged in agricultural planting or crayfish breeding in the gathering areas.

Spatial patterns and interactions of dominant tree species in an Amazon tropical rainforest / Patrones e interacciones espaciales de especies arbóreas dominantes en un bosque tropical en la Amazonia

Abstract Knowledge of spatial patterns and interactions of tree species allows for understanding the ecological processes of spatiotemporal structures of tropical forests, becoming essential for the establishment of strategies for the conservation and management of their resources in the long term. The aim of this study was to investigate the spatial patterns and interactions of Astronium lecointei, Dinizia excelsa and Peltogyne paniculata, three dominant timber tree species in the Jamari National Forest, Rondônia, Brazilian Amazon. The Kernel estimator was used aiming to verify the possible influence of first-order factors on species distributions. Inhomogeneous K-functions were applied to analyze species spatial patterns and interactions by means of second-order factors. Univariate analyses revealed different scale-dependent spatial patterns for the species. Aggregation related to ecological characteristics, such as habitat preference and dispersal limitation, was verified for A. lecointei and P. paniculata. D. excelsa presented a random spatial pattern, explained by specific features of its establishment, such as the need for clearings due to light requirements. Interspecific associations were evidenced by bivariate analyses, in which spatial attraction of species resulted from the same preference for microhabitats and the repulsion was a result of niche segregation. Rev. Biol. Trop. 66(3): 1009-1017. Epub 2018 September 01.

Resumen El conocimiento de los patrones e interacciones espaciales de las especies arbóreas permite la comprensión de los procesos ecológicos de estructuración espacio-temporal de los bosques tropicales, tornándose imprescindible para el establecimiento de estrategias de conservación y manejo de sus recursos a largo plazo. El objetivo de este estudio fue investigar los patrones y las interacciones espaciales de Astronium lecointei, Dinizia excelsa y Peltogyne paniculata, tres especies arbóreas madereras dominantes en la Selva Nacional del Jamari, Rondônia, Amazonia Brasileña. Para ello, se utilizó el estimador Kernel, con el objetivo de verificar la posible influencia de factores de primer orden en la distribución de las especies. Para el análisis de los patrones e interacciones espaciales de las especies por medio de los factores de segundo orden, se empleó la función K no homogénea. Los análisis univariados revelaron diferentes patrones espaciales dependientes de la escala para las especies. Agregación relacionada a características ecológicas, como preferencia de hábitat y limitación de la dispersión, fue constatada para A. lecointei y P. paniculata. Dinizia excelsa presentó un patrón espacial aleatorio, explicado por características particulares de su establecimiento, como la necesidad de claros debido a sus requisitos lumínicos. Las asociaciones interespecíficas fueron evidenciadas por los análisis bivariados, en que la atracción espacial de las especies resultó de la misma preferencia por micro hábitats y la repulsión fue resultado de la segregación de nichos.

Some inequalities involving the extended gamma function and the Kummer confluent hypergeometric k-function.

In the paper, the authors present some inequalities involving the extended gamma function and the Kummer confluent hypergeometric k-function via some classical inequalities such as Chebychev's inequality for synchronous (or asynchronous, respectively) mappings, give a new proof of the log-convexity of the extended gamma function by using the Hölder inequality, and introduce a Turán type mean inequality for the Kummer confluent k-hypergeometric function.

3D super-resolution microscopy reflects mitochondrial cristae alternations and mtDNA nucleoid size and distribution.

3D super-resolution microscopy based on the direct stochastic optical reconstruction microscopy (dSTORM) with primary Alexa-Fluor-647-conjugated antibodies is a powerful method for accessing changes of objects that could be normally resolved only by electron microscopy. Despite the fact that mitochondrial cristae yet to become resolved, we have indicated changes in cristae width and/or morphology by dSTORM of ATP-synthase F1 subunit α (F1α). Obtained 3D images were analyzed with the help of Ripley's K-function modeling spatial patterns or transferring them into distance distribution function. Resulting histograms of distances frequency distribution provide most frequent distances (MFD) between the localized single antibody molecules. In fasting state of model pancreatic ß-cells, INS-1E, MFD between F1α were ~80 nm at 0 and 3 mM glucose, whereas decreased to 61 nm and 57 nm upon glucose-stimulated insulin secretion (GSIS) at 11 mM and 20 mM glucose, respectively. Shorter F1α interdistances reflected cristae width decrease upon GSIS, since such repositioning of F1α correlated to average 20 nm and 15 nm cristae width at 0 and 3 mM glucose, and 9 nm or 8 nm after higher glucose simulating GSIS (11, 20 mM glucose, respectively). Also, submitochondrial entities such as nucleoids of mtDNA were resolved e.g. after bromo-deoxyuridine (BrDU) pretreatment using anti-BrDU dSTORM. MFD in distances distribution histograms reflected an average nucleoid diameter (<100 nm) and average distances between nucleoids (~1000 nm). Double channel PALM/dSTORM with Eos-lactamase-ß plus anti-TFAM dSTORM confirmed the latter average inter-nucleoid distance. In conclusion, 3D single molecule (dSTORM) microscopy is a reasonable tool for studying mitochondrion.