Spatial transcriptional mapping of the human nephrogenic program

Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlage, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single-cell RNA sequencing identified progenitor states, which were spatially mapped to the nephron anatomy, enabling the generation of functional gene networks predicting interactions within and between nephron cell types. Network mining identified known developmental disease genes and predicted targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease and enhance efforts to generate new kidney structures.

Differential Retinoic Acid Signaling in the Hippocampus of Aged Rats with and without Memory Impairment

Retinoic acid (RA), a metabolite of vitamin A, has many physiological functions, and mounting evidence points to important roles in cognition. In vitro experiments indicate that RA is involved in homeostatic synaptic scaling in the hippocampus, which supports overall network stability during learning. It has been previously determined that disrupted RA signaling in the hippocampus causes deterioration of memory, that RA signaling declines with age in brain, and that application of RA reverses this decline. Here, we explore whether RA signaling is altered in an animal model of neurocognitive aging. We used a Morris water maze protocol to study cognitive decline in aged rats, which assesses hippocampus-dependent spatial memory and reveals substantial interindividual differences in aged animals. Aged unimpaired (AU) rats perform on par with young (Y), while aged impaired (AI) animals exhibit spatial memory deficits. We show that the major substrate for RA, retinol binding protein 4 (RBP4), is decreased in AU rats, and retinol cell surface receptor declines with chronological age. Other affected components of RA signaling include selective increases in AI animals in hippocampal synthesis (RALDH1) and catabolism of RA (CYP26B1), RA receptor α, the RA regulated ionotropic glutamate receptor (GluR1), as well as fragile X mental retardation protein (FMRP). The results support the conclusion that, surprisingly, increased RA signaling in the aged hippocampus is associated with poor cognitive outcome.

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this paper, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

The HexMaze: A Previous Knowledge Task on Map Learning for Mice

New information is rarely learned in isolation; instead, most of what we experience can be incorporated into or uses previous knowledge networks in some form. Previous knowledge in form of a cognitive map can facilitate knowledge acquisition and will influence how we learn new spatial information. Here, we developed a new spatial navigation task where food locations are learned in a large, gangway maze to test how mice learn a large spatial map over a longer time period—the HexMaze. Analyzing performance across sessions as well as on specific trials, we can show simple memory effects as well as multiple effects of previous knowledge of the map accelerating both online learning and performance increases over offline periods when incorporating new information. We could identify the following three main phases: (1) learning the initial goal location; (2) faster learning after 2 weeks when learning a new goal location; and then (3) the ability to express one-session learning, leading to long-term memory effect after 12 weeks. Importantly, we are the first to show that buildup of a spatial map is dependent on how much time passes, not how often the animal is trained.

Auditory processing in schizophrenia: Behavioural evidence of abnormal spatial awareness

Spatial processing deficits are the reason for many daily life problems of schizophrenia (SCZ) patients. In this study, we aimed to examine the possibility of abnormal bias to one hemifield, in form of hemispatial neglect and extinction, in auditory modality in SCZ. Twenty-five SCZ patients and 25 healthy individuals were compared on speech tasks to study the auditory neglect and extinction, as well as an auditory localization task for studying neglect. In the speech tasks, participants reproduced some nonsense syllables, played from one or two speakers on the right and/or left sides. On the localization task, examinees discriminated the subjective location of the noise stimuli presented randomly from five speakers. On the speech task, patients had significantly lower hit rates for the right ear compared with controls (p = 0.01). While healthy controls showed right ear advantage, SCZs showed a left ear priority. In the localization task, although both groups had a left-side bias, this bias was much more prominent for the patients (all p < 0.05). SCZ could potentially alter the auditory spatial function, which may appear in the form of auditory neglect and extinction on the right side, depending on the characteristics of patient population.

Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea

Anemia is a major public health problem in Africa, affecting an increasing number of children under five years. Guinea is one of the most affected countries. In 2018, the prevalence rate in Guinea was 75% for children under five years. This study sought to identify the factors associated with anemia and to map spatial variation of anemia across the eight (8) regions in Guinea for children under five years, which can provide guidance for control programs for the reduction of the disease. Data from the Guinea Multiple Indicator Cluster Survey (MICS5) 2016 was used for this study. A total of 2609 children under five years who had full covariate information were used in the analysis. Spatial binomial logistic regression methodology was undertaken via Bayesian estimation based on Markov chain Monte Carlo (MCMC) using WinBUGS software version 1.4. The findings in this study revealed that 77% of children under five years in Guinea had anemia, and the prevalences in the regions ranged from 70.32% (Conakry) to 83.60% (NZerekore) across the country. After adjusting for non-spatial and spatial random effects in the model, older children (48-59 months) (OR: 0.47, CI [0.29 0.70]) were less likely to be anemic compared to those who are younger (0-11 months). Children whose mothers had completed secondary school or above had a 33% reduced risk of anemia (OR: 0.67, CI [0.49 0.90]), and children from household heads from the Kissi ethnic group are less likely to have anemia than their counterparts whose leaders are from Soussou (OR: 0.48, CI [0.23 0.92]).

Hysterectomy in India: Spatial and multilevel analysis

Objective:

Using the unit-level data of women aged 15–49 years from National Family Health Survey-IV (2015–2016), the article maps the prevalence of hysterectomy across districts in India and examines its determinants.

Methods:

Descriptive statistics, multivariate techniques, Moran’s Index and Local indicators of Spatial Association were used to understand the objectives. The data were analysed in STATA 14.2, Geo-Da and Arc-GIS.

Results:

In India, the prevalence of hysterectomy operation was 3.2%, the highest in Andhra Pradesh (8.9%) and the lowest in Assam (0.9%). Rural India had higher a prevalence than urban India. The majority of women underwent the operation in private hospitals. Hysterectomy prevalence ranged between 3% and 5% in 126 districts, 5% and 7% in 47 districts and more than 7% in 26 districts. Moran’s Index (0.58) indicated the positive autocorrelation for the prevalence of hysterectomy among districts; a total of 202 districts had significant neighbourhood association. Variation in the prevalence of hysterectomy was attributed to the factors at the primary sampling unit, district and state level. Age, parity, wealth and insurance were positively associated with the prevalence of hysterectomy, whereas education and sterilization was negatively associated.

Conclusion:

Hysterectomy operation in India presented the geographical, socio-economic, demographic and medical phenomenon. The high prevalence of hysterectomy in many parts of the country suggested conducting in-depth studies, considering the life cycle approach and providing counselling and education to women about their reproductive rights and informed choice. Surveillance and medical audits and promoting the judicial use of health insurance can be of great help.

A spatial model of COVID-19 transmission in England and Wales: early spread, peak timing and the impact of seasonality

An outbreak of a novel coronavirus was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable human-to-human transmission in England. We adapted an existing national-scale metapopulation model to capture the spread of COVID-19 in England and Wales. We used 2011 census data to inform population sizes and movements, together with parameter estimates from the outbreak in China. We predict that the epidemic will peak 126 to 147 days (approx. 4 months) after the start of person-to-person transmission in the absence of controls. Assuming biological parameters remain unchanged and transmission persists from February, we expect the peak to occur in June. Starting location and model stochasticity have a minimal impact on peak timing. However, realistic parameter uncertainty leads to peak time estimates ranging from 78 to 241 days following sustained transmission. Seasonal changes in transmission rate can substantially impact the timing and size of the epidemic. We provide initial estimates of the epidemic potential of COVID-19. These results can be refined with more precise parameters. Seasonal changes in transmission could shift the timing of the peak into winter, with important implications for healthcare capacity planning.

This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK.

Spatial and temporal variability in summer diet of gray wolves (Canis lupus) in the Greater Yellowstone Ecosystem

The role of predation by large carnivores in suppressing prey populations and structuring ecosystems is highly debated, calling for a detailed understanding of carnivore diets. Wolves (Canis lupus) roam across three continents and persist throughout widely different ecosystems. Their diet is flexible and may vary spatially as well as seasonally, which requires analysis of diet on different spatial and temporal scales. Few studies have investigated the summer diet of wolves, which is more variable, consists of smaller prey, and requires different methods than studying their winter diet. To better understand the summer diet of wolves, we combined three independently collected wolf scat data sets from three distinctly different portions of the Greater Yellowstone Ecosystem: Yellowstone National Park (2009), Grand Teton National Park (2003 – 2009), and the Absaroka-Beartooth Wilderness (2009 – 2010). These areas represent different ecological conditions and management regimes, which may impact wolf diet. We estimated relative biomass and compared occurrence of different prey species among packs, years, as well as the three regions. In total, we analyzed 1,906 wolf scats and found that neonate cervids, adult elk, and adult deer were the most important prey species in the summer diet of the wolves. We found dietary variation among packs residing in the same area, as well as across years. The occurrence of neonate cervids displayed the most variation, and low occurrence of this prey type often was associated with a more diverse diet. Wolf packs within the national parks had a higher occurrence of medium-sized prey (~ 50 – 70 kg) and lower occurrence of small-sized prey (≤ 20 kg) compared to wolves in the Absaroka-Beartooth Wilderness. These results demonstrate flexibility in summer diet across packs, years, and between regions within the Greater Yellowstone Ecosystem.

Site- and Taxa-Specific Disease-Associated Oral Microbial Structures Distinguish Inflammatory Bowel Diseases

BACKGROUND

The gut and oral microbiome have independently been shown to be associated with inflammatory bowel disease (IBD). However, it is not known to what extent gut and oral microbial disease markers converge in terms of their composition in IBD. Further, the spatial and temporal variation within the oral microenvironments of IBD remain to be elucidated.

PATIENTS AND METHODS

We used a prospectively recruited cohort of patients with IBD (n = 47) and unrelated healthy control patients (n = 18) to examine the spatial and temporal distribution of microbiota within the various oral microenvironments, represented by saliva, tongue, buccal mucosa, and plaque, and compared them with stool. Microbiome characterization was performed using 16S rRNA gene sequencing.

RESULTS

The oral microbiome displayed IBD-associated dysbiosis, in a site- and taxa-specific manner. Plaque samples depicted a relatively severe degree of dysbiosis, and the disease-associated dysbiotic bacterial groups were predominantly the members of the phylum Firmicutes. Our 16S rRNA gene analyses show that oral microbiota can distinguish patients with IBD from healthy control patients, with salivary microbiota performing the best, closely matched by stool and other oral sites. Longitudinal profiles of microbial composition suggest that some taxa are more consistently perturbed than others, preferentially in a site-dependent fashion.

CONCLUSIONS

Collectively, these data indicate the potential of using oral microbial profiles in screening and monitoring patients with IBD. Furthermore, these results support the importance of spatial and longitudinal microbiome sampling to interpret disease-associated dysbiotic states and eventually to gain insights into disease pathogenesis.

Toward a neurobiology of internal selective attention

A recent study in non-human primates (NHPs) by Panichello and Buschman brings the investigation of selective attention within visual working memory to the systems and cellular neuroscience levels. We reflect on this breakthrough in light of nearly 20 years of related research in humans and highlight some of the lessons to help frame future work.

General statistical scaling laws for stability in ecological systems

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity.

Spatial and temporal genetic variation in an exploited reef fish: The effects of exploitation on cohort genetic structure

Many coral reef fishes are fished, often resulting in detrimental genetic effects; however, reef fishes often show unpredictable patterns of genetic variation, which potentially mask the effects of fishing. Our goals were to characterize spatial and temporal genetic variation and determine the effects of fishing on an exploited reef fish, Plectropomus leopardus, Lacepède (the common coral trout). To determine population structure, we genotyped 417 Great Barrier Reef coral trout from four populations sampled in 2 years (1996 and 2004) at nine microsatellite loci. To test for exploitation effects, we additionally genotyped 869 individuals from a single cohort (ages 3-5) across eight different reefs, including fished and control populations. Genetic structure differed substantially in the two sampled years, with only 1 year exhibiting isolation by distance. Thus, genetic drift likely plays a role in shaping population genetic structure in this species. Although we found no loss of genetic diversity associated with exploitation, our relatedness patterns show that pulse fishing likely affects population genetics. Additionally, genetic structure in the cohort samples likely reflected spatial variation in recruitment contributing to genetic structure at the population level. Overall, we show that fishing does impact coral reef fishes, highlighting the importance of repeated widespread sampling to accurately characterize the genetic structure of reef fishes, as well as the power of analysing cohorts to avoid the impacts of recruitment-related genetic swamping. The high temporal and spatial variability in genetic structure, combined with possible selection effects, will make conservation/management of reef fish species complex.

Uncovering the different scales in deer-forest interactions

Deer are regarded to be a keystone species as they play a crucial role in the way an ecosystem functions. Most deer-forest interaction studies apply a single scale - process of analyzing ecological interactions by only taking into account one dependent variable - to understand how deer browsing behavior shapes different forest components, but they overlook the fact that forests respond to multiple scales simultaneously. This research evaluates the effect of browsing by wild deer on temperate and boreal forests at different scales by synthesizing seminal papers, specifically (a) what are the effects of deer population density in forest regeneration? (b) What are the effects of deer when forests present diverging spatial characteristics? (c) What are the effects on vegetation at different temporal scales? and (d) What are the hierarchical effects of deer when considering other trophic levels? Additionally, a framework based on modern technology is proposed to answer the multiscale research questions previously identified. When analyzing deer-forest interactions at different scales, the strongest relationships occur at the extremes. For example: when deer assemblage occurs in low or high density and is composed of a mix of small and large species. As forests on poor soils remain restrained in size, isolated and chronically browsed. When forests harbor incomplete trophic levels, the effects spill over to lower trophic levels. To better understand the complexities in deer-forest interactions, researchers should combine technology-based instruments like fixed sensors and drones with field-tested methods such observational studies and experiments to tackle multiscale research questions.

Modeling the Potential Future Distribution of Anthrax Outbreaks under Multiple Climate Change Scenarios for Kenya

The climate is changing, and such changes are projected to cause global increase in the prevalence and geographic ranges of infectious diseases such as anthrax. There is limited knowledge in the tropics with regards to expected impacts of climate change on anthrax outbreaks. We determined the future distribution of anthrax in Kenya with representative concentration pathways (RCP) 4.5 and 8.5 for year 2055. Ecological niche modelling (ENM) of boosted regression trees (BRT) was applied in predicting the potential geographic distribution of anthrax for current and future climatic conditions. The models were fitted with presence-only anthrax occurrences (n = 178) from historical archives (2011-2017), sporadic outbreak surveys (2017-2018), and active surveillance (2019-2020). The selected environmental variables in order of importance included rainfall of wettest month, mean precipitation (February, October, December, July), annual temperature range, temperature seasonality, length of longest dry season, potential evapotranspiration and slope. We found a general anthrax risk areal expansion i.e., current, 36,131 km2, RCP 4.5, 40,012 km2, and RCP 8.5, 39,835 km2. The distribution exhibited a northward shift from current to future. This prediction of the potential anthrax distribution under changing climates can inform anticipatory measures to mitigate future anthrax risk.

Functional Traits in Lichen Ecology: A Review of Challenge and Opportunity

Community ecology has experienced a major transition, from a focus on patterns in taxonomic composition, to revealing the processes underlying community assembly through the analysis of species functional traits. The power of the functional trait approach is its generality, predictive capacity such as with respect to environmental change, and, through linkage of response and effect traits, the synthesis of community assembly with ecosystem function and services. Lichens are a potentially rich source of information about how traits govern community structure and function, thereby creating opportunity to better integrate lichens into 'mainstream' ecological studies, while lichen ecology and conservation can also benefit from using the trait approach as an investigative tool. This paper brings together a range of author perspectives to review the use of traits in lichenology, particularly with respect to European ecosystems from the Mediterranean to the Arctic-Alpine. It emphasizes the types of traits that lichenologists have used in their studies, both response and effect, the bundling of traits towards the evolution of life-history strategies, and the critical importance of scale (both spatial and temporal) in functional trait ecology.

Spatial skew-normal/independent models for nonrandomly missing clustered data

Clinical studies on periodontal disease (PD) often lead to data collected which are clustered in nature (viz. clinical attachment level, or CAL, measured at tooth-sites and clustered within subjects) that are routinely analyzed under a linear mixed model framework, with underlying normality assumptions of the random effects and random errors. However, a careful look reveals that these data might exhibit skewness and tail behavior, and hence the usual normality assumptions might be questionable. Besides, PD progression is often hypothesized to be spatially associated, that is, a diseased tooth-site may influence the disease status of a set of neighboring sites. Also, the presence/absence of a tooth is informative, as the number and location of missing teeth informs about the periodontal health in that region. In this paper, we develop a (shared) random effects model for site-level CAL and binary presence/absence status of a tooth under a Bayesian paradigm. The random effects are modeled using a spatial skew-normal/independent (S-SNI) distribution, whose dependence structure is conditionally autoregressive (CAR). Our S-SNI density presents an attractive parametric tool to model spatially referenced asymmetric thick-tailed structures. Both simulation studies and application to a clinical dataset recording PD status reveal the advantages of our proposition in providing a significantly improved fit, over models that do not consider these features in a unified way.

Associations between Greenspace and Gentrification-Related Sociodemographic and Housing Cost Changes in Major Metropolitan Areas across the United States

Neighborhood greenspace may attract new residents and lead to sociodemographic or housing cost changes. We estimated relationships between greenspace and gentrification-related changes in the 43 largest metropolitan statistical areas (MSAs) of the United States (US). We used the US National Land Cover and Brown University Longitudinal Tracts databases, as well as spatial lag models, to estimate census tract-level associations between percentage greenspace (years 1990, 2000) and subsequent changes (1990–2000, 2000–2010) in percentage college-educated, percentage working professional jobs, race/ethnic composition, household income, percentage living in poverty, household rent, and home value. We also investigated effect modification by racial/ethnic composition. We ran models for each MSA and time period and used random-effects meta-analyses to derive summary estimates for each period. Estimates were modest in magnitude and heterogeneous across MSAs. After adjusting for census-tract level population density in 1990, compared to tracts with low percentage greenspace in 1992 (defined as ≤50th percentile of the MSA-specific distribution in 1992), those with high percentage greenspace (defined as >75th percentile of the MSA-specific distribution) experienced higher 1990–2000 increases in percentage of the employed civilian aged 16+ population working professional jobs (β: 0.18, 95% confidence interval (CI): 0.11, 0.26) and in median household income (β: 0.23, 95% CI: 0.15, 0.31). Adjusted estimates for the 2000–2010 period were near the null. We did not observe evidence of effect modification by race/ethnic composition. We observed evidence of modest associations between greenspace and gentrification trends. Further research is needed to explore reasons for heterogeneity and to quantify health implications.

Immediate Impact of Hurricane Lane on Microbiological Quality of Coastal Water in Hilo Bay, Hawaii

Hurricanes and associated stormwater runoff events are expected to greatly impact coastal marine water quality, yet little is known about their immediate effects on microbiological quality of near-shore water. This study sampled Hilo Bay immediately after the impact of Hurricane Lane to understand the spatial and temporal variations of the abundance and diversity of fecal indicator enterococci, common fecal pathogens, and antibiotic resistance genes (ARGs). Water samples from seven sampling sites over 7 days were collected and analyzed, which showed that the overall microbiological water quality parameters [enterococci geometric mean (GM): 6-22 cfu/100 mL] fell within water quality standards and that the temporal dynamics indicated continuing water quality recovery. However, considerable spatial variation was observed, with the most contaminated site exhibiting impaired water quality (GM = 144 cfu/100 mL). The Enterococcus population also showed distinct genotypic composition at the most contaminated site. Although marker genes for typical fecal pathogens (invA for Salmonella, hipO for Campylobacter, mip for Legionella pneumophila, and eaeA for enteropathogenic Escherichia coli) were not detected, various ARGs (ermB, qurS, tetM, blaTEM, and sul1) and integron-associated integrase intI1 were detected at high levels. Understanding the temporal and spatial variation of microbiological water quality at fine granularity is important for balancing economic and recreational uses of coastal water and the protection of public health post the impact of major hurricane events.

Structured Spatial Modeling and Mapping of Domestic Violence Against Women of Reproductive Age in Rwanda

The main objective of this study was to assess the risk factors and spatial correlates of domestic violence against women of reproductive age in Rwanda. A structured spatial approach was used to account for the nonlinear nature of some covariates and the spatial variability on domestic violence. The nonlinear effect was modeled through second-order random walk, and the structured spatial effect was modeled through Gaussian Markov Random Fields specified as an intrinsic conditional autoregressive model. The data from the Rwanda Demographic and Health Survey 2014/2015 were used as an application. The findings of this study revealed that the risk factors of domestic violence against women are the wealth quintile of the household, the size of the household, the husband or partner's age, the husband or partner's level of education, ownership of the house, polygamy, the alcohol consumption status of the husband or partner, the woman's perception of wife-beating attitude, and the use of contraceptive methods. The study also highlighted the significant spatial variation of domestic violence against women at district level.

Suicide and the agent-host-environment triad: leveraging surveillance sources to inform prevention

Suicide in the US has increased in the last decade, across virtually every age and demographic group. Parallel increases have occurred in non-fatal self-harm as well. Research on suicide across the world has consistently demonstrated that suicide shares many properties with a communicable disease, including person-to-person transmission and point-source outbreaks. This essay illustrates the communicable nature of suicide through analogy to basic infectious disease principles, including evidence for transmission and vulnerability through the agent-host-environment triad. We describe how mathematical modeling, a suite of epidemiological methods, which the COVID-19 pandemic has brought into renewed focus, can and should be applied to suicide in order to understand the dynamics of transmission and to forecast emerging risk areas. We describe how new and innovative sources of data, including social media and search engine data, can be used to augment traditional suicide surveillance, as well as the opportunities and challenges for modeling suicide as a communicable disease process in an effort to guide clinical and public health suicide prevention efforts.

Time is of the essence: Exploring temporal and spatial organisation in episodic memory

There is disagreement in the literature as to whether episodic memory maintains an inherent temporal organisation, that is, whether learned items are necessarily organised along some temporal dimension or whether temporal organisation is a task-specific occurrence. The current series of experiments explored this issue. In Experiment 1, we tested whether temporal or spatial contiguity was present in an incidental encoding task where either strategy (but not both together) could be employed at test. In Experiment 2, we attempted to facilitate the use of a spatial retrieval strategy at test by asking participants to recall the location where target items had been displayed at study, after incidental encoding. Experiment 3 explored the role of study-test congruency by informing participants at encoding that they would be tested on either their memory for the temporal sequence or spatial locations, and then testing both at retrieval. Finally, Experiment 4 employed a masking task at encoding to ensure participants could not predict the true nature of the task, despite it being incidental, and a surprise free recall task. Predominantly, participants displayed recall performance consistent with temporal contiguity, although there was evidence for spatial contiguity under certain conditions. These results are consistent with the notion that episodic memory has a stable and predictable temporal organisation.

Associative recognition memory for identity, spatial and temporal relations in healthy aging

The ability to generate associative representations and to retrieve them from long-term episodic memory generally declines in healthy aging. However, it is unclear whether healthy aging has differential effects on associative memory for identity, spatial configuration, and temporal order relationships. In the current study, we assessed how healthy aging impacts on associative memory for identity, spatial, or temporal relationships between pairs of visual objects via discrimination of intact and rearranged pairs. Accuracy and response time performance of healthy older adults (aged 65-80) were compared with young adults (ages 19-30). Age-related declines in associative memory were observed equally for all types of associations, but these declines differed by associative status: aging most strongly affected ability to discriminate rearranged pairs. These results suggest that associative memory for identity, spatial, and temporal relationships are equally affected by healthy aging, and may all depend on a shared set of basic associative mechanisms.

Spatial analysis and risk factors of suicide among people living with HIV/AIDS who committed suicide

Poor mental health may confer worse health outcomes among people living with HIV/AIDS (PLWH). Suicidal behaviors are symptoms of a depressive episode. The goal was to explore characteristics for spatial distribution and risk factors for suicide among PLWH. This study was conducted in Mainland China with the annual newly reported data of PLWH from 2013 to 2018. We compared the spatial distribution differences between the HIV epidemic and suicide mortality and analyzed the global and local spatial analysis of suicide. Further, we explored the possible risk factors of suicide in PLWH by multivariate regression and a decision tree model. High suicide mortality regions in PLWH in China were inconsistent with that of the high prevalence of PLWH, which showed that there was distribution discordance between the HIV epidemic and suicide mortality. Multivariate regression showed that the possible risk factors of PLWH who committed suicide were younger age, with Han nationality, single, having a higher educational level, and homosexual infection route. The decision tree model showed that age was the primary factor. In conclusion, there was a discordance between HIV prevalence and suicide mortality; lower HIV prevalence regions might have higher mortality due to suicide. Concern is merited amongst PLWH with poor mental health.

Predicting and Interpreting Spatial Accidents through MDLSTM

Predicting and interpreting the spatial location and causes of traffic accidents is one of the current hot topics in traffic safety. This research purposed a multi-dimensional long-short term memory neural network model (MDLSTM) to fit the non-linear relationships between traffic accident characteristics and land use properties, which are further interpreted to form local and general rules. More variables are taken into account as the input land use properties and the output traffic accident characteristics. Five types of traffic accident characteristics are simultaneously predicted with higher accuracy, and three levels of interpretation, including the hidden factor-traffic potential, the potential-determine factors, which varies between grid cells, and the general rules across the whole study area are analyzed. Based on the model, some interesting insights were revealed including the division line in the potential traffic accidents in Shenyang (China). It is also purposed that the relationship between land use and accidents differ from previous researches in the neighboring and regional aspects. Neighboring grids have strong spatial connections so that the relationship of accidents in a continuous area is relatively similar. In a larger region, the spatial location is found to have a great influence on the traffic accident and has a strong directionality.