Unique Spatial Patterns Research Articles

Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies.

Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.

Spatial Transcriptomics as a Novel Approach to Redefine Electrical Stimulation Safety.

Current standards for safe delivery of electrical stimulation to the central nervous system are based on foundational studies which examined post-mortem tissue for histological signs of damage. This set of observations and the subsequently proposed limits to safe stimulation, termed the “Shannon limits,” allow for a simple calculation (using charge per phase and charge density) to determine the intensity of electrical stimulation that can be delivered safely to brain tissue. In the three decades since the Shannon limits were reported, advances in molecular biology have allowed for more nuanced and detailed approaches to be used to expand current understanding of the physiological effects of stimulation. Here, we demonstrate the use of spatial transcriptomics (ST) in an exploratory investigation to assess the biological response to electrical stimulation in the brain. Electrical stimulation was delivered to the rat visual cortex with either acute or chronic electrode implantation procedures. To explore the influence of device type and stimulation parameters, we used carbon fiber ultramicroelectrode arrays (7 μm diameter) and microwire electrode arrays (50 μm diameter) delivering charge and charge density levels selected above and below reported tissue damage thresholds (range: 2–20 nC, 0.1–1 mC/cm2). Spatial transcriptomics was performed using Visium Spatial Gene Expression Slides (10x Genomics, Pleasanton, CA, United States), which enabled simultaneous immunohistochemistry and ST to directly compare traditional histological metrics to transcriptional profiles within each tissue sample. Our data give a first look at unique spatial patterns of gene expression that are related to cellular processes including inflammation, cell cycle progression, and neuronal plasticity. At the acute timepoint, an increase in inflammatory and plasticity related genes was observed surrounding a stimulating electrode compared to a craniotomy control. At the chronic timepoint, an increase in inflammatory and cell cycle progression related genes was observed both in the stimulating vs. non-stimulating microwire electrode comparison and in the stimulating microwire vs. carbon fiber comparison. Using the spatial aspect of this method as well as the within-sample link to traditional metrics of tissue damage, we demonstrate how these data may be analyzed and used to generate new hypotheses and inform safety standards for stimulation in cortex.

Genomic analysis of 1,25-dihydroxyvitamin D3 action in mouse intestine reveals compartment and segment-specific gene regulatory effects

1,25-dihydroxyvitamin D (VD) regulates intestinal calcium absorption in the small intestine (SI) and also reduces risk of colonic inflammation and cancer. However, the intestine compartment-specific target genes of VD signaling are unknown. Here, we examined VD action across three functional compartments of the intestine using RNA-seq to measure VD-induced changes in gene expression and Chromatin Immunoprecipitation with next generation sequencing to measure vitamin D receptor (VDR) genomic binding. We found that VD regulated the expression of 55 shared transcripts in the SI crypt, SI villi, and in the colon, including Cyp24a1, S100g, Trpv6, and Slc30a10. Other VD-regulated transcripts were unique to the SI crypt (162 up, 210 down), villi (199 up, 63 down), or colon (102 up, 28 down), but this did not correlate with mRNA levels of the VDR. Furthermore, bioinformatic analysis identified unique VD-regulated biological functions in each compartment. VDR-binding sites were found in 70% of upregulated genes from the colon and SI villi but were less common in upregulated genes from the SI crypt and among downregulated genes, suggesting some transcript-level VD effects are likely indirect. Consistent with this, we show that VD regulated the expression of other transcription factors and their downstream targets. Finally, we demonstrate that compartment-specific VD-mediated gene expression was associated with compartment-specific VDR-binding sites (<30% of targets) and enrichment of intestinal transcription factor–binding motifs within VDR-binding peaks. Taken together, our data reveal unique spatial patterns of VD action in the intestine and suggest novel mechanisms that could account for compartment-specific functions of this hormone.

Designer DNA nanostructures for viral inhibition.

Emerging viral diseases can substantially threaten national and global public health. Central to our ability to successfully tackle these diseases is the need to quickly detect the causative virus and neutralize it efficiently. Here we present the rational design of DNA nanostructures to inhibit dengue virus infection. The designer DNA nanostructure (DDN) can bind to complementary epitopes on antigens dispersed across the surface of a viral particle. Since these antigens are arranged in a defined geometric pattern that is unique to each virus, the structure of the DDN is designed to mirror the spatial arrangement of antigens on the viral particle, providing very high viral binding avidity. We describe how available structural data can be used to identify unique spatial patterns of antigens on the surface of a viral particle. We then present a procedure for synthesizing DDNs using a combination of in silico design principles, self-assembly, and characterization using gel electrophoresis, atomic force microscopy and surface plasmon resonance spectroscopy. Finally, we evaluate the efficacy of a DDN in inhibiting dengue virus infection via plaque-forming assays. We expect this protocol to take 2-3 d to complete virus antigen pattern identification from existing cryogenic electron microscopy data, ~2 weeks for DDN design, synthesis, and virus binding characterization, and ~2 weeks for DDN cytotoxicity and antiviral efficacy assays.

Metabarcoding Analysis of Harmful Algal Bloom Species in the Western Pacific Seamount Regions.

The Western Pacific is the most oligotrophic sea on Earth, with numerous seamounts. However, the plankton diversity and biogeography of the Western Pacific in general and the seamount regions in particular remains largely unexplored. In this project, we quantitatively analyzed the composition and distribution patterns of plankton species in the Western Pacific seamount regions by applying metabarcoding analysis. We identified 4601 amplicon sequence variants (ASVs) representing 34 classes in seven protist phyla/divisions in the Western Pacific seamount regions, among which Dinoflagellata was by far the most dominant division. Among the 336 annotated phytoplankton species (including species in Dinoflagellata), we identified 36 harmful algal bloom (HAB) species, many of which displayed unique spatial distribution patterns in the Western Pacific seamount regions. This study was the first attempt in applying ASV-based metabarcoding analysis in studying phytoplankton and HAB species in the Western Pacific seamount regions, which may facilitate further research on the potential correlation between HABs in the Western Pacific seamount regions and coastal regions.

Computational pathology reveals unique spatial patterns of immune response in H&E images from COVID-19 autopsies: preliminary findings.

Purpose: We used computerized image analysis and machine learning approaches to characterize spatial arrangement features of the immune response from digitized autopsied H&E tissue images of the lung in coronavirus disease 2019 (COVID-19) patients. Additionally, we applied our approach to tease out potential morphometric differences from autopsies of patients who succumbed to COVID-19 versus H1N1. Approach: H&E lung whole slide images from autopsy specimens of nine COVID-19 and two H1N1 patients were computationally interrogated. 606 image patches ( per patient) of were extracted from the 11 autopsied patient studies. A watershed-based segmentation approach in conjunction with a machine learning classifier was employed to identify two types of nuclei families: lymphocytes and non-lymphocytes (i.e., other nucleated cells such as pneumocytes, macrophages, and neutrophils). Based off the proximity of the individual nuclei, clusters for each nuclei family were constructed. For each of the resulting clusters, a series of quantitative measurements relating to architecture and density of nuclei clusters were calculated. A receiver operating characteristics-based feature selection method, violin plots, and the t-distributed stochastic neighbor embedding algorithm were employed to study differences in immune patterns. Results: In COVID-19, the immune response consistently showed multiple small-size lymphocyte clusters, suggesting that lymphocyte response is rather modest, possibly due to lymphocytopenia. In H1N1, we found larger lymphocyte clusters that were proximal to large clusters of non-lymphocytes, a possible reflection of increased prevalence of macrophages and other immune cells. Conclusion: Our study shows the potential of computational pathology to uncover immune response features that may not be obvious by routine histopathology visual inspection.

Measuring Urban Vibrancy of Residential Communities Using Big Crowdsourced Geotagged Data.

The pervasiveness of mobile and sensing technologies today has facilitated the creation of Big Crowdsourced Geotagged Data (BCGD) from individual users in real time and at different locations in the city. Such ubiquitous user-generated data allow us to infer various patterns of human behavior, which helps us understand the interactions between humans and cities. In this article, we aim to analyze BCGD, including mobile consumption check-ins, urban geography data, and human mobility data, to learn a model that can unveil the impact of urban geography and human mobility on the vibrancy of residential communities. Vibrant communities are defined as places that show diverse and frequent consumer activities. To effectively identify such vibrant communities, we propose a supervised data mining system to learn and mimic the unique spatial configuration patterns and social interaction patterns of vibrant communities using urban geography and human mobility data. Specifically, to prepare the benchmark vibrancy scores of communities for training, we first propose a fused scoring method by fusing the frequency and the diversity of consumer activities using mobile check-in data. Besides, we define and extract the features of spatial configuration and social interaction for each community by mining urban geography and human mobility data. In addition, we strategically combine a pairwise ranking objective with a sparsity regularization to learn a predictor of community vibrancy. And we develop an effective solution for the optimization problem. Finally, our experiment is instantiated on BCGD including real estate, point of interests, taxi and bus GPS trajectories, and mobile check-ins in Beijing. The experimental results demonstrate the competitive performances of both the extracted features and the proposed model. Our results suggest that a structurally diverse community usually shows higher social interaction and better business performance, and incompatible land uses may decrease the vibrancy of a community. Our studies demonstrate the potential of how to best make use of BCGD to create local economic matrices and sustain urban vibrancy in a fast, cheap, and meaningful way.

Metabarcoding dissection of harmful algal bloom species in the East China Sea off Southern Zhejiang Province in late spring

The coastal region of the East China Sea (ECS) is a famous “hotspot” for harmful algal blooms (HABs) in China. We hypothesize that such frequent occurrences of diverse HABs in the ECS are determined by the presence of unique HAB species in this region. In this project, we identified 3966 amplicon sequence variants (ASVs) representing 35 classes in six protist phyla/divisions. Among the 237 annotated protist species, we identified 58 HAB species, of which 23 HAB species had never been previously reported in the ECS. Many HAB species also displayed unique spatial distribution patterns in the ECS. Notably, we identified three HAB species Prorocentrum donghaiense, Lebouridinium glaucum and Noctiluca scintillans in the site S05-1 with substantially elevated abundance, suggesting that this sampling site was experiencing a multiple-species HAB event. This study was the first attempt in applying ASV-based metabarcoding analysis in studying protist and HAB species in the ECS.

Spatial clustering of fourteen tick species across districts of Zimbabwe

BackgroundTicks transmit several diseases that result in high morbidity and mortality in livestock. Tick-borne diseases are an economic burden that negatively affect livestock production, cost countries billions of dollars through vaccine procurement and other disease management efforts. Thus, understanding the spatial distribution of tick hotspots is critical for identifying potential areas of high tick-borne disease transmission and setting up priority areas for targeted tick disease management. In this study, optimised hotspot analysis was applied to detect hotspots and coldspots of 14 common tick species in Zimbabwe. Data on the spatial distribution of tick species were obtained from the Epidemiology Unit of the Division of Veterinary Field Services of Zimbabwe.ResultsA total of 55,133 ticks were collected with Rhipicephalus decoloratus being the most common species (28.7%), followed by Amblyomma hebraeum (20.6%), and Rhipicephalus sanguineus sensu lato (0.06%) being the least common species. Results also showed that tick hotspots are species-specific with particular tick species occupying defined localities in the country. For instance, Amblyomma variegatum, Rhipicephalus appendiculatus, Rhipicephalus decoloratus, Rhipicephalus compostus, Rhipicephalus microplus, Rhipicephalus pravus, and Rhipicephalus simus were concentrated in the north and north eastern districts of the country. In contrast, Amblyomma hebraeum, Hyalomma rufipes, Hyalomma trancatum and Rhipicephalus evertsi evertsi were prevalent in the southern districts of Zimbabwe.ConclusionThe occurrence of broadly similar hotspots of several tick species in different districts suggests presence of spatial overlaps in the niche of the tick species. As ticks are vectors of several tick-borne diseases, there is high likelihood of multiple disease transmission in the same geographic region. This study is the first in Zimbabwe to demonstrate unique spatial patterns in the distribution of several tick species across the country. The results of this study provide an important opportunity for the development of spatially-targeted tick-borne disease management strategies.

Assessment of mass-induced sea level variability in the Tropical Indian Ocean based on GRACE and altimeter observations

Assessment of mass-induced sea level (MISL) variability in the Tropical Indian Ocean (TIO) was studied using observations from the Gravity Recovery and Climate Experiment (GRACE) during 2003–2017 in conjunction with the steric effects in the sea level anomaly as measured by satellite altimeters. Two steric sea levels were estimated from the ocean model analysis and Argo gridded temperature and salinity fields. These datasets were consistent with each other and to the altimeter measured sea level records. They exhibited a coherent seasonal cycle with unique spatial patterns of amplitude maxima associated with annual and semi-annual harmonics. Steric component remained as a major contributor to the sea level variability at all the time scales. Addition of the GRACE measured MISL to the steric sea level improved the estimation of sea level (as measured by satellite altimeter) over most part of the TIO except over the northern part of the Arabian Sea. It was observed that the MISL had a significant contribution to the sea level variability at intra-seasonal and seasonal time scales and a minor contribution to the sea level inter-annual variability. During all the El Nino years, sea level underwent a large fluctuation coherent to the steric component. A linear barotropic vortex conservation model driven by ocean surface winds explained a major part of the observed MISL high-frequency variability in the Equatorial and southern TIO, and overestimated the observation in the northern TIO.

A review on the factors influencing energy efficiency of mosque buildings

Mosques are external load dominated buildings that are characterized by their intermittent and varying occupancy schedules. Most mosques employ some form of mechanical heating/cooling system in order to maintain suitable thermal comfort conditions for the users during prayer times. Due to the unique spatial characteristics and occupancy patterns of mosques, these systems are often found to be energy-intensive which impacts the overall energy efficiency of the building. The inefficiency in mosque energy usage has been typically attributed to the poor thermal performance of the buildings along with unsuitable operational strategies for the occupancy schedule of mosques. This paper reviews contemporary literature on mosque energy usage with an aim of identifying the factors that influence the energy efficiency of mosque buildings. Findings from the literature have been categorized according to different parameters of the building design as well as design and operational strategies of the heating/cooling systems. Discussion on the common practice and best practice has also been done with respect to thermal comfort standards and requirements. In addition to that, this paper compares and critically evaluates the studies that have aimed at reducing energy consumption and improving energy efficiency in mosques. Findings from multiple research suggest that as much as half of the energy usage can be reduced with the optimization of building design and operational strategies of mosques. The review of contemporary literature provides valuable insights into mosque energy usage patterns and identifies the important aspects to be considered in reducing energy consumption in mosque buildings. Through this literature review, numerous research gaps have been identified that may be pivotal in designing energy efficient mosques. Based on those, future potential research prospects have also been suggested.

Investigation of Stereometric and Fractal Patterns of Spin‐Coated LuMnO3 Thin Films

In this paper, we have performed qualitative and quantitative analysis of LuMnO3 thin films surfaces, deposited by spin coating over Pt(111)/TiO2/SiO2/Si substrates, to evaluate their spatial patterns as a function of the film’s sintering temperature. Atomic force microscopy was employed to obtain topographic maps that were extensively analyzed via image processing techniques and mathematical tools. 3D (three‐dimensional) topographical images revealed that films sintered at 650°C and 750°C presented the formation of smoother surfaces, while the film sintered at 850°C displayed a rougher surface with a root mean square roughness of ∼2.5 nm. On the other direction, the height distribution of the surface for all films has similar asymmetries and shape, although the film sintered using the highest temperature showed the lower density of rough peaks and a sharper peak shape. The advanced fractal parameters revealed that the film sintered at 850°C is dominated by low spatial frequencies, showing less spatial complexity, higher microtexture homogeneity, and uniform height distribution. These results suggest that the combination of stereometric and fractal parameters can be especially useful for identification of unique topographic spatial patterns in LuMnO3 thin films, helping in their implementation in technological applications, such as photovoltaic solar cells and information magnetic date storage and spintronic devices.

The dynamics of food shopping behavior: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling.

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

Structural and functional connectivity mapping of the human corpus callosum organization with white-matter functional networks

The corpus callosum serves as a crucial organization for understanding the information integration between the two hemispheres. Our previous study explored the functional connectivity between the corpus callosum and white-matter functional networks (WM-FNs), but the corresponding physical connectivity remains unknown. The current study uses the resting-state fMRI of Human Connectome Project data to identify ten WM-FNs in 108 healthy subjects, and then independently maps the structural and functional connectivity between the corpus callosum and above WM-FNs using the diffusion tensor images (DTI) tractography and resting-state functional connectivity (RSFC). Our results demonstrated that the structural and functional connectivity between the human corpus callosum and WM-FNs have the following high overall correspondence: orbitofrontal WM-FN, DTI map = 89% and RSFC map = 92%; sensorimotor middle WM-FN, DTI map = 47% and RSFC map = 77%; deep WM-FN, DTI map = 50% and RSFC map = 79%; posterior corona radiata WM-FN, DTI map = 82% and RSFC map = 73%. These findings reinforce the notion that the corpus callosum has unique spatial distribution patterns connecting to distinct WM-FNs. However, important differences between the structural and functional connectivity mapping results were also observed, which demonstrated a synergy between DTI tractography and RSFC toward better understanding the information integration of primary and higher-order functional systems in the human brain.

A spectral-spatial approach for detection of single-point natural gas leakage using hyperspectral imaging

Recent studies have shown that underground natural gas storage leaks can be indirectly detected through the spectral changes of surface vegetation. However, due to the phenomenon of different samples demonstrating the same spectrum, using a spectral-based approach may result in misdetection. Vegetation stressed by natural gas leakage has unique spatial patterns. Therefore, a field experiment of natural gas leakage vegetation stress was carried out. Hyperspectral images of bean, corn crops, and grasslands were obtained, which led to a proposed new spectral-spatial based methodology to detect natural gas leaks and areas of vegetation stress. First, the vegetation indices and the color index were extracted, then respectively segmented using the Otsu and the proposed threshold segmentation methods. Next, the shape parameters of the posture ratio and rectangularity of the segmented objects were used to construct a circular detection model. The accuracies of the detection results based on the vegetation indices and color index were 53 % and 56 %, respectively. Finally, based on the concentric ring spatial distribution pattern of the stress zones, the two types of detection results were fused using the linearly weighted fusion method, after which all the leakage points were accurately detected and localized, without any false alarms.

Occurrence and distribution of polyhalogenated carbazoles (PHCs) in sediments from the northern South China Sea

Polyhalogenated carbazoles (PHCs) have been frequently detected in various environments and have gained increasing attention due to their dioxin-like toxicity. In this study, 28 surface sediments and three sediment cores were collected from the northern South China Sea (SCS) to investigate the spatial and temporal distribution trends of PHCs. The total concentrations of PHCs in the surface sediments ranged from 0.25 ng/g to 3.10 ng/g, with a median concentration of 1.50 ng/g. The composition profiles of PHCs in the surface sediments were dominated by 3,6-dichlorocarbazole (36-CCZ), 3,6-dibromocarbazole (36-BCZ), and 1,3,6,8-tetrabromocarbazole (1368-BCZ). The total organic carbon (TOC) based concentrations of 36-CCZ, 1-bromo-3,6-dichlorocarbazole, 1,3,6,8-tetrachlorocarbazole, and 1368-BCZ showed significant positive correlation with water depth (r = 0.58–0.88, p values < 0.01). On the contrary, the TOC based concentration of 2,3,6,7-tetrachlorocarbazole displayed a significant negative correlation with the water depth (r = −0.52, p < 0.01). However, no significant correlation was observed for 3-chlorocarbazole, 36-BCZ, and 1,3,6-tribromocarbazole (p values > 0.05). PHCs in sediment cores showed that congener profiles and concentrations of PHCs remained largely stable throughout the 1890s and 2010s. In addition, all the detected PHCs displayed a significant positive correlation with TOC content of the sediments. These unique spatial and temporal distribution patterns suggest that both terrigenous and natural marine sources contributed the observed PHCs in sediments of the northern SCS.

Drosophila Insulin-Like Peptide 8 (DILP8) in Ovarian Follicle Cells Regulates Ovulation and Metabolism.

In Drosophila melanogaster eight insulin-like peptides (DILP1-8) are encoded on separate genes. These DILPs are characterized by unique spatial and temporal expression patterns during the lifecycle. Whereas, functions of several of the DILPs have been extensively investigated at different developmental stages, the role of DILP8 signaling is primarily known from larvae and pupae where it couples organ growth and developmental transitions. In adult female flies, a study showed that a specific set of neurons that express the DILP8 receptor, Lgr3, is involved in regulation of reproductive behavior. Here, we further investigated the expression of dilp8/DILP8 and Lgr3 in adult female flies and the functional role of DILP8 signaling. The only site where we found both dilp8 expression and DILP8 immunolabeling was in follicle cells around mature eggs. Lgr3 expression was detected in numerous neurons in the brain and ventral nerve cord, a small set of peripheral neurons innervating the abdominal heart, as well as in a set of follicle cells close to the oviduct. Ovulation was affected in dilp8 mutants as well as after dilp8-RNAi using dilp8 and follicle cell Gal4 drivers. More eggs were retained in the ovaries and fewer were laid, indicating that DILP8 is important for ovulation. Our data suggest that DILP8 signals locally to Lgr3 expressing follicle cells as well as systemically to Lgr3 expressing efferent neurons in abdominal ganglia that innervate oviduct muscle. Thus, DILP8 may act at two targets to regulate ovulation: follicle cell rupture and oviduct contractions. Furthermore, we could show that manipulations of dilp8 expression affect starvation resistance suggesting effects on metabolism. Possibly this reflects a feedback signaling between ovaries and the CNS that ensures nutrients for ovary development. In summary, it seems that DILP8 signaling in regulation of reproduction is an ancient function, conserved in relaxin signaling in mammals.

Headwaters drive streamflow and lowland tracer export in a large‐scale humid tropical catchment

AbstractHeadwaters are generally assumed to contribute the majority of water to downstream users, but how much water, of what quality and where it is generated are rarely known in the humid tropics. Here, using monthly monitoring in the data scarce (2,370 km2) San Carlos catchment in northeastern Costa Rica, we determined runoff‐area relationships linked to geochemical and isotope tracers. We established 46 monitoring sites covering the full range of climatic, land use and geological gradients in the catchment. Regression and cluster analysis revealed unique spatial patterns and hydrologically functional landscape units. These units were used for seasonal and annual Bayesian tracer mixing models to assess spatial water source contributions to the outlet. Generally, the Bayesian mixing analysis showed that the chemical and isotopic imprint at the outlet is throughout the year dominated by the adjacent lowland catchments (68%) with much less tracer influence from the headwaters. However, the headwater catchments contributed the bulk of water and tracers to the outlet during the dry season (&gt;50%) despite covering less than half of the total catchment area. Additionally, flow volumes seemed to be linearly scaled by area maintaining a link between the headwaters and the outlet particularly during high flows of the rainy season. Stable isotopes indicated mean recharge elevations above the mean catchment altitude, which further supports that headwaters were the primary source of downstream water. Our spatially detailed “snap‐shot” sampling enabled a viable alternative source of large‐scale hydrological process knowledge in the humid tropics with limited data availability.

Spatial patterns of intrinsic brain activity and functional connectivity in facial synkinesis patients

Objectives As one of the most objectionable sequelae of facial paralysis, patients with facial synkinesis are more likely to be depressed and have lower quality of life than other facial paralysis patients. However, there is no research on the spatial patterns of intrinsic brain activity and functional connectivity in these patients. The objective of this study was to investigate the spatial patterns and cerebral plasticity of facial synkinesis patients. Methods A total of 20 facial synkinesis patients (18 men and 2 women; mean age: 33.35 ± 6.97 years old) and 19 healthy controls (17 men and 2 women; mean age: 33.21 ± 6.75 years old) were enrolled in this study. resting-state functional magnetic resonance imaging (rs-fMRI) data were collected, and the amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated for each participant. Two-sample t-tests were performed to compare the ALFF, ReHo, and DC maps between the two groups. Results Compared with the healthy controls, facial synkinesis patients exhibited decreased ALFF in the fusiform gyrus, lingual gyrus, parahippocampal gyrus, triangular inferior frontal gyrus, precentral gyrus, postcentral gyrus, cingulate gyrus, superior frontal gyrus, precuneus, caudate nucleus and thalamus; decreased ReHo in the cingulate gyrus, superior frontal gyrus, insula, superior temporal gyrus, orbital middle frontal gyrus, caudate nucleus and thalamus; and decreased DC in the frontal lobe, insula, cingulate gyrus, superior temporal gyrus, lenticular putamen, hippocampus and parahippocampal gyrus. We found significant overlap in the superior frontal gyrus across the ALFF, ReHo and DC analyses. Conclusions In facial synkinesis patients, the neurological activity in brain areas is reduced and the local synchronization in motion-related brain regions is decreased. The superior frontal gyrus could be a crucial region in the unique spatial patterns of intrinsic brain activity and functional connectivity in these patients.

Dynamics, Variability, and Change in Seasonal Precipitation Reconstructions for North America

AbstractCool- and warm-season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December–April totals and 547 different chronologies correlated with May–July totals. These discrete seasonal chronologies are not significantly correlated with the alternate season; the December–April reconstructions are skillful over most of the southern and western United States and north-central Mexico, and the May–July estimates have skill over most of the United States, southwestern Canada, and northeastern Mexico. Both the strong continent-wide El Niño–Southern Oscillation (ENSO) signal embedded in the cool-season reconstructions and the Arctic Oscillation signal registered by the warm-season estimates faithfully reproduce the sign, intensity, and spatial patterns of these ocean–atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide insight into decadal droughts and pluvials. They indicate that the sixteenth-century megadrought, the most severe and sustained North American drought of the past 500 years, was the combined result of three distinct seasonal droughts, each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic multidecadal oscillation. Significant 200–500-yr-long trends toward increased precipitation have been detected in the cool- and warm-season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the eastern area that began as a result of natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change.