Comparison of angle-to-angle distance and corneal diameter in pediatric eyes using ultrasound biomicroscopy.

OBJECTIVE: To investigate the relationship between corneal diameter and internal corneal span determined from angle-to-angle distance using ultrasound biomicroscopy (UBM) in an observational cross-sectional patient population comprised of 54 eyes (28 healthy control eyes, ages 0.1 to 11.3 years; 26 eyes with primary congenital glaucoma, ages 0.1 to 3.5 years) from 41 pediatric participants ages 0.1 to 11.3 years (mean age: 3±3 years, median age: 2 years). METHODS: Forty cornea photographs with reference ruler and 110 UBM images were obtained. Three observers measured horizontal and vertical corneal diameter and angle-to-angle distance in each cornea photo and UBM image using ImageJ and the average values were used. Main outcome measures were Pearson correlation coefficient, linear regression, mean difference between corneal diameter and angle-to-angle distance, and intra-class correlation coefficients among measurements from all three observers for each parameter. RESULTS: Corneal diameter and angle-to-angle distance had a strong positive correlation horizontally (Pearson r = 0.89, p<0.001) and vertically (r = 0.93, p<0.001). Correlation was consistent regardless of presence of primary congenital glaucoma and participant age. Regression analysis demonstrated a linear relationship between the parameters for horizontal (CD = 0.99*AA+0.28, R2 = 0.81, p<0.001) and vertical (CD = 0.91 *AA+1.32, R2 = 0.85, p<0.001) dimensions. Overall, reliability was good-excellent, ranging from an ICC of 0.76 for vertical corneal diameter to 0.90 for horizontal angle-to-angle distance. CONCLUSIONS: Based on the strong positive correlation found between corneal diameter and angle-to-angle distance in our study population, UBM image analysis can be used to accurately estimate corneal diameter from angle-to-angle distance in children with healthy eyes and primary congenital glaucoma. UBM may provide a useful intraocular alternative for estimating corneal diameter and monitoring diseases that affect the cornea in infants and children, such as congenital glaucoma.

Approach to non-compressive myeloneuropathy through a rendezvous of 11 cases from an Indian backdrop.

Introduction: Myeloneuropathy is a diagnosis ascribed to disorders that concomitantly affect the spinal cord and peripheral nerves. Recognizing this syndrome may sometimes be arduous, even for the most consummate clinicians, because symptomatology can mimic either spinal cord or peripheral nerve disease. Besides, examination findings suggest a predominantly myelopathic or neuropathic picture. This article reports a rendezvous of rare cases of clinically diagnosed myeloneuropathy with different etiological backgrounds and therapeutic responses. Methods: Eleven cases of non-compressive myeloneuropathy were admitted to the Department of General Medicine of Burdwan Medical College and Hospital, Burdwan, West Bengal, India, between May 2018 and May 2022. Results: We report the cases of 11 patients (6 men and 5 women) who presented with myeloneuropathy of different etiologies (vitamin B12, copper, and vitamin E deficiencies, organophosphate poisoning, chronic alcohol abuse, illicit substances abuse, anti-thyroid peroxidase/anti-thyroglobulin antibody-related neurologic disorder responsive to steroids, Sjögren syndrome, chikungunya infection, paraneoplastic, and hereditary). Conclusion: Meticulous historical analysis, careful clinical examination, and apposite utilization and interpretation of biochemical, electrophysiological, and neuroimaging findings are sine-qua-non for an accurate and consistent approach to evaluating a suspected case of myeloneuropathy, facilitating early treatment and recovery. Differential identification of these disorders needs an in-depth perception of the mode of onset of symptoms, the course of progression of the disease, the pattern of myelopathic/neuropathic findings, and recognition of other neurological or systemic manifestations. For untroubled understanding, etiologies of myeloneuropathies should be subdivided into a few broad categories, e.g., metabolic (nutritional), toxic (toxin-induced), infectious, inflammatory (immune-mediated), paraneoplastic, and hereditary disorders.

Introducción: La mieloneuropatía es un síndrome que afecta concomitantemente la médula espinal y los nervios periféricos. Reconocerlo a veces puede ser arduo, incluso para los médicos más experimentados, porque la sintomatología puede simular una enfermedad de la médula espinal o de los nervios periféricos. Además, los hallazgos del examen sugieren un cuadro predominantemente mielopático o neuropático. Este artículo describe una serie de casos raros de mieloneuropatía de distintas causas y con respuestas terapéuticas distintas. Métodos: Once casos de mieloneuropatía no compresiva fueron ingresados en el Departamento de Medicina General del Burdwan Medical College, and Hospital, Burdwan, Bengala Occidental, India, entre mayo de 2018 y mayo de 2022. Resultados: Presentamos 11 pacientes (seis hombres y cinco mujeres) con mieloneuropatía de diferentes etiologías (deficiencias de vitamina B12, cobre y vitamina E, intoxicación por organofosforados, abuso crónico de alcohol, abuso de sustancias ilícitas, trastorno neurológico relacionado con anticuerpos anti-tiroglobulina / antiperoxidasa tiroidea que responde a esteroides, síndrome de Sjögren, infección por chikungunya, paraneoplásico y hereditario). Conclusión: El análisis meticuloso de la historia y del examen clínico, así como la utilización e interpretación adecuadas de los hallazgos bioquímicos, electrofisiológicos y de neuroimagen son condiciones sine qua non para un enfoque preciso y consistente para evaluar un caso sospechoso de mieloneuropatía, lo que facilita el tratamiento temprano y su recuperación. El diagnóstico diferencial de esta patología requiere un conocimiento del modo de inicio de los síntomas, su progresión, el patrón de hallazgos mielopáticos/neuropáticos y el reconocimiento de otras manifestaciones neurológicas o sistémicas. Las etiologías de las mieloneuropatías deben subdividirse en trastornos metabólicos (nutricionales), tóxicos (inducidos por toxinas), infecciosos, inflamatorios (mediados por mecanismos inmunitarios), paraneoplásicos y hereditarias.

Development and validation of mortality prediction models based on the social determinants of health.

BACKGROUND: There is no standardised approach to screening adults for social risk factors. The goal of this study was to develop mortality risk prediction models based on the social determinants of health (SDoH) for clinical risk stratification. METHODS: Data were used from REasons for Geographic And Racial Differences in Stroke (REGARDS) study, a national, population-based, longitudinal cohort of black and white Americans aged ≥45 recruited between 2003 and 2007. Analysis was limited to participants with available SDoH and mortality data (n=20 843). All-cause mortality, available through 31 December 2018, was modelled using Cox proportional hazards with baseline individual, area-level and business-level SDoH as predictors. The area-level Social Vulnerability Index (SVI) was included for comparison. All models were adjusted for age, sex and sampling region and underwent internal split-sample validation. RESULTS: The baseline prediction model including only age, sex and REGARDS sampling region had a c-statistic of 0.699. An individual-level SDoH model (Model 1) had a higher c-statistic than the SVI (0.723 vs 0.708, p<0.001) in the testing set. Sequentially adding area-level SDoH (c-statistic 0.723) and business-level SDoH (c-statistics 0.723) to Model 1 had minimal improvement in model discrimination. Structural racism variables were associated with all-cause mortality for black participants but did not improve model discrimination compared with Model 1 (p=0.175). CONCLUSION: In conclusion, SDoH can improve mortality prediction over 10 years relative to a baseline model and have the potential to identify high-risk patients for further evaluation or intervention if validated externally.

Fluvoxamine Ameliorates the Damage to the Neuro-Behavioral Status of Rats Caused by the Administration of Valproic Acid by Preventing Cognitive Memory Deficits and Decreased Hippocampal Cellular Proliferation.

Fluvoxamine is a major antidepressant of the selective serotonin-reuptake inhibitor class, previously studied as a drug that improves cognitive memory by enhancing hippocampal cell division and proliferation. Valproic acid (VPA) is a commonly used antiepileptic drug and mood stabilizer that has negative effects on cognitive memory as it inhibits cellular division and proliferation in the hippocampus. This study assessed the protective effects of fluvoxamine treatment versus the memory impairment, decreased hippocampal cellular proliferation, and weight loss produced by VPA treatment. The cognitive memory of 40 male Sprague-Dawley rats was assessed by the novel object location (NOL) test. Immunostaining by Ki67 and glutathione peroxidase 1 (GPX-1) was performed to quantify the number of dividing cells in the subgranular zone (SGZ) of the dentate gyrus and to assess the antioxidant activity of different treatments, respectively. Results showed that the VPA group had fewer Ki67-positive cells than the control group (p < 0.001), indicating reduced hippocampal proliferation. In contrast, the VPA and fluvoxamine combination group showed increased proliferation (p < 0.001) compared to VPA alone. Notably, fluvoxamine treatment significantly differed in cell counts compared to other groups (p < 0.001). Fluvoxamine also attenuated the weight loss caused by VPA (p < 0.0001). Our data suggested that fluvoxamine therapy attenuated the VPA-induced decrease in SGZ cellular proliferation, memory, and weight in rats.

Molecular dissection of the pseudokinase ZED1 expands effector recognition to the tomato immune receptor ZAR1.

The highly conserved angiosperm immune receptor HOPZ-ACTIVATED RESISTANCE 1 (ZAR1) is a bacterial pathogen recognition hub that mediates resistance by guarding host kinases for modification by pathogen effectors. The pseudokinase HOPZ-ETI DEFICIENT 1 (ZED1) is the only known ZAR1-guarded protein that interacts directly with a pathogen effector, HopZ1a, from the bacterial pathogen Pseudomonas syringae, making it a promising system for rational design of effector recognition for plant immunity. Here, we conducted an in-depth molecular analysis of ZED1. We generated a library of 164 random ZED1 mutants and identified 50 mutants that could not recognize the effector HopZ1a when transiently expressed in Nicotiana benthamiana. Based on our random mutants, we generated a library of 27 point mutants and found evidence of minor functional divergence between Arabidopsis (Arabidopsis thaliana) and N. benthamiana ZAR1 orthologs. We leveraged our point mutant library to identify regions in ZED1 critical for ZAR1 and HopZ1a interactions and identified two likely ZED1-HopZ1a binding conformations. We explored ZED1 nucleotide and cation binding activity and showed that ZED1 is a catalytically dead pseudokinase, functioning solely as an allosteric regulator upon effector recognition. We used our library of ZED1 point mutants to identify the ZED1 activation loop regions as the most likely cause of interspecies ZAR1-ZED1 incompatibility. Finally, we identified a mutation that abolished ZAR1-ZED1 interspecies incompatibility while retaining the ability to mediate HopZ1a recognition, which enabled recognition of HopZ1a through tomato (Solanum lycopersicum) ZAR1. This provides an example of expanded effector recognition through a ZAR1 ortholog from a non-model species.

Systematic Review of Longitudinal Evidence and Methodologies for Research on Neighborhood Characteristics and Brain Health.

Objective: Synthesize longitudinal research evaluating neighborhood environments and cognition to identify methodological approaches, findings, and gaps. Methods: Included studies evaluated associations between neighborhood and cognition longitudinally among adults >45 years (or mean age of 65 years) living in developed nations. We extracted data on sample characteristics, exposures, outcomes, methods, overall findings, and assessment of disparities. Results: Forty studies met our inclusion criteria. Most (65%) measured exposure only once and a majority focused on green space and/or blue space (water), neighborhood socioeconomic status, and recreation/physical activity facilities. Similarly, over half studied incident impairment, cognitive function or decline (70%), with one examining MRI (2.5%) or Alzheimer's disease (7.5%). While most studies used repeated measures analysis to evaluate changes in the brain health outcome (51%), many studies did not account for any type of correlation within neighborhoods (35%). Less than half evaluated effect modification by race/ethnicity, socioeconomic status, and/or sex/gender. Evidence was mixed and dependent on exposure or outcome assessed. Conclusion: Although longitudinal research evaluating neighborhood and cognitive decline has expanded, gaps remain in types of exposures, outcomes, analytic approaches, and sample diversity.

Genomic signatures of climate adaptation in bank voles.

Evidence for divergent selection and adaptive variation across the landscape can provide insight into a species' ability to adapt to different environments. However, despite recent advances in genomics, it remains difficult to detect the footprints of climate-mediated selection in natural populations. Here, we analysed ddRAD sequencing data (21,892 SNPs) in conjunction with geographic climate variation to search for signatures of adaptive differentiation in twelve populations of the bank vole (Clethrionomys glareolus) distributed across Europe. To identify the loci subject to selection associated with climate variation, we applied multiple genotype-environment association methods, two univariate and one multivariate, and controlled for the effect of population structure. In total, we identified 213 candidate loci for adaptation, 74 of which were located within genes. In particular, we identified signatures of selection in candidate genes with functions related to lipid metabolism and the immune system. Using the results of redundancy analysis, we demonstrated that population history and climate have joint effects on the genetic variation in the pan-European metapopulation. Furthermore, by examining only candidate loci, we found that annual mean temperature is an important factor shaping adaptive genetic variation in the bank vole. By combining landscape genomic approaches, our study sheds light on genome-wide adaptive differentiation and the spatial distribution of variants underlying adaptive variation influenced by local climate in bank voles.

How to account for behavioral states in step-selection analysis: a model comparison.

Step-selection models are widely used to study animals' fine-scale habitat selection based on movement data. Resource preferences and movement patterns, however, often depend on the animal's unobserved behavioral states, such as resting or foraging. As this is ignored in standard (integrated) step-selection analyses (SSA, iSSA), different approaches have emerged to account for such states in the analysis. The performance of these approaches and the consequences of ignoring the states in step-selection analysis, however, have rarely been quantified. We evaluate the recent idea of combining iSSAs with hidden Markov models (HMMs), which allows for a joint estimation of the unobserved behavioral states and the associated state-dependent habitat selection. Besides theoretical considerations, we use an extensive simulation study and a case study on fine-scale interactions of simultaneously tracked bank voles (Myodes glareolus) to compare this HMM-iSSA empirically to both the standard and a widely used classification-based iSSA (i.e., a two-step approach based on a separate prior state classification). Moreover, to facilitate its use, we implemented the basic HMM-iSSA approach in the R package HMMiSSA available on GitHub.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

A tale of many neighborhoods: Latent profile analysis to derive a national neighborhood typology for the US.

INTRODUCTION: Neighborhoods are complex and multi-faceted. Analytic strategies used to model neighborhoods should reflect this complexity, with the potential to better understand how neighborhood characteristics together impact health. We used latent profile analysis (LPA) to derive a residential neighborhood typology applicable for census tracts across the US. METHODS: From tract-level 2015-2019 American Community Survey (ACS) five-year estimates, we selected five indicators that represent four neighborhood domains: demographic composition, commuting, socioeconomic composition, and built environment. We compared model fit statistics for up to eight profiles to identify the optimal number of latent profiles of the selected neighborhood indicators for the entire US. We then examined differences in national tract-level 2019 prevalence estimates of physical and mental health derived from CDC's PLACES dataset between derived profiles using one-way analysis of variance (ANOVA). RESULTS: The 6-profile LPA model was the optimal categorization of neighborhood profiles based on model fit statistics and interpretability. Neighborhood types were distinguished most by demographic composition, followed by commuting and built environment domains. Neighborhood profiles were associated with meaningful differences in the prevalence of health outcomes. Specifically, tracts characterized as "Less educated non-immigrant racial and ethnic minority active transiters" (n = 3,132, 4%) had the highest poor health prevalence (Mean poor physical health: 18.6 %, SD: 4.30; Mean poor mental health: 19.6 %, SD: 3.85), whereas tracts characterized as "More educated metro/micropolitans" (n = 15, 250, 21%) had the lowest prevalence of poor mental and physical health (Mean poor physical health: 10.6 %, SD: 2.41; Mean poor mental health: 12.4 %, SD: 2.67; p < 0.001). CONCLUSION: LPA can be used to derive meaningful and standardized profiles of tracts sensitive to the spatial patterning of social and built conditions, with observed differences in mental and physical health by neighborhood type in the US.

Features of the Physical and Social Neighborhood Environment and Neighborhood-Level Alzheimer's Disease and Related Dementia in South Carolina.

BACKGROUND: Studies are increasingly examining the relationship between the neighborhood environment and cognitive decline; yet, few have investigated associations between multiple neighborhood features and Alzheimer's disease and related dementias (ADRD). OBJECTIVE: We investigated the relationship between neighborhood features and ADRD cumulative incidence from 2010 to 2014 in the South Carolina Alzheimer's Disease Registry (SCADR). METHODS: Diagnosed ADRD cases ≥50 years of age were ascertained from the SCADR by ZIP code and census tract. Neighborhood features from multiple secondary sources included poverty, air pollution [particulate matter with a diameter of 2.5 micrometers or less (PM2.5)], and rurality at the census-tract level and access to healthy food, recreation facilities, and diabetes screening at the county level. In addition to using Poisson generalized linear regression to estimate ADRD incident rate ratios (IRR) with 95% confidence intervals (CIs), we applied integrated nested Laplace approximations and stochastic partial differential equations (INLA-SPDE) to address disparate spatial scales. We estimated associations between neighborhood features and ADRD cumulative incidence. RESULTS: The average annual ADRD cumulative incidence was 690 per 100,000 people per census tract (95% CI: 660, 710). The analysis was limited to 98% of census tracts with a population ≥50 years old (i.e., 1,081 of 1,103). The average percent of families living below the federal poverty line per census tract was 18.8%, and ∼20% of census tracts were considered rural. The average percent of households with limited access to healthy food was 6.4%. In adjusted models, every 5µg/m3) increase of PM2.5 was associated with 65% higher ADRD cumulative incidence (IRR=1.65; 95% CI: 1.30, 2.09), where PM2.5 at or below 12 µg/m3 is considered healthy. Compared to large urban census tracts, rural and small urban tracts had 10% (IRR=1.10; 95% CI: 1.00, 1.23) and 5% (IRR=1.05; 95% CI: 0.96, 1.16) higher ADRD, respectively. For every percent increase of the county population with limited access to healthy food, ADRD was 2% higher (IRR=1.02; 95% CI: 1.01, 1.04). CONCLUSIONS: Neighborhood environment features, such as higher air pollution levels, were associated with higher neighborhood ADRD incidence. The INLA-SPDE method could have broad applicability to data collected across disparate spatial scales. https://doi.org/10.1289/EHP13183.

A Segmented Regression Analysis of Household Income and Recurrent Falls Among Adults in a National Cohort Study.

Falls can have life-altering consequences for older adults, including extended recovery periods and compromised independence. Higher household income may mitigate the risk of falls by providing financial resources for mobility tools, remediation of environmental hazards, and needed supports, or it may buffer the impact of an initial fall on subsequent risk through improved assistance and care. Household income has not had a consistently observed association with falls in older adults; however, a segmented association may exist such that associations are attenuated above a certain income threshold. In this study, we utilized segmented negative binomial regression analysis to examine the association between household income and recurrent falls among 2,302 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited between 2003 and 2007. Income-fall association segments separated by changes in slope were considered. Model results indicated a 2-segment association between household income and recurrent falls in the past year. In the range below the breakpoint, household income was negatively associated with the rate of recurrent falls across all age groups examined; in a higher income range (from $20,000-$49,999 to ≥$150,000), the association was attenuated (weaker negative trend) or reversed (positive trend). These findings point to potential benefits of ensuring that incomes for lower-income adults exceed the threshold needed to confer a reduced risk of recurrent falls.

Places for Healthy Play: A Multi-Pronged Evaluation of Context, Design, and Perceptions for Play Space Improvements.

Community design interventions have prioritized the creation of quality play space, especially in easy to access public places, to improve health outcomes and to reduce health inequities. Evaluations of health-relevant play interventions often fail to assess essential context, design, and perceptions. The Play Everywhere Philadelphia Challenge, led by KABOOM!, funded 16 play spaces to support child health and development and literacy skills for low-income neighborhoods across Philadelphia. In June-October 2022, our interdisciplinary team conducted a process evaluation of completed play space installations (k=9) to identify site aspects that facilitated greater use. We mapped neighborhood context (e.g., child amenities, sociodemographics, pedestrian and bike accessibility), and conducted direct and systematic observations of play space design (e.g., signage, shade), visitation (i.e., number of visitors/hour), and engagement. We summarized visitation and engagement across contextual and design data. While many visitors passed through sites, over half of the children we observed engaged with the installation. Installations with poor condition (i.e., cleanliness and maintenance) had the lowest visitation and engagement. More active/kinetic installations drew more children and engagement. This process evaluation comprehensively analyzed play space design elements and neighborhood context and provides evidence to inform recommendations to increase use of urban play spaces.

Neighborhood greenspace and neighborhood income associated with white matter grade worsening: Cardiovascular Health Study.

INTRODUCTION: We examined whether a combined measure of neighborhood greenspace and neighborhood median income was associated with white matter hyperintensity (WMH) and ventricle size changes. METHODS: The sample included 1260 cognitively normal ≥ 65-year-olds with two magnetic resonance images (MRI; ≈ 5 years apart). WMH and ventricular size were graded from 0 (least) to 9 (most) abnormal (worsening = increase of ≥1 grade from initial to follow-up MRI scans). The four-category neighborhood greenspace-income measure was based on median neighborhood greenspace and income values at initial MRI. Multivariable logistic regression tested associations between neighborhood greenspace-income and MRI measures (worsening vs. not). RESULTS: White matter grade worsening was more likely for those in lower greenspace-lower income neighborhoods than higher greenspace-higher income neighborhoods (odds ratio = 1.73; 95% confidence interval = 1.19-2.51). DISCUSSION: The combination of lower neighborhood income and lower greenspace may be a risk factor for worsening white matter grade on MRI. However, findings need to be replicated in more diverse cohorts. HIGHLIGHTS: Population-based cohort of older adults (≥ 65 years) with greenspace and MRI dataCombined measure of neighborhood greenspace and neighborhood income at initial MRIMRI outcomes included white matter hyperintensities (WMH) and ventricular sizeLongitudinal change in MRI outcomes measured approximately 5 years apartWorsening WMH over time more likely for lower greenspace-lower income neighborhoods.

Neighborhood gentrification, wealth, and co-ethnic density associations with acculturation stressors among Chinese immigrants.

Objective: This study examined the cross-sectional relationships between neighborhood social composition and gentrification, and acculturation stressors. Methods: Person-level data came from first-generation Chinese immigrants enrolled in the Immigrant Enclaves Study (Philadelphia, Pennsylvania, baseline 2018-2020, N = 512). A validated scale was used to assess 22 stressors associated with migration or acculturation. Neighborhood characteristics from the American Community Survey 2015-2019 and 2008-2012 included: tract proportion of foreign born Chinese, neighborhood wealth, and past decade gentrification. Most neighborhood exposures were modeled as continuous as well as binary variables (intended to represent highest level of neighborhood exposure). Multivariable negative binomial regression adjusted for age, gender, income, education, employment, language, years in the U.S., and neighborhood variables (proportion co-ethnic, and neighborhood per capita income). Results: The majority of participants spoke Mandarin (68% vs Cantonese 32%), mean participant age was 52.7 years old, years in the US was 18, and nearly one-half of the sample had less than 8 years of education. Mean number of stressors was 5.9 with nearly 20% of participants reporting 11 or more stressors. Multivariable results found the number of acculturation stressors was 18% lower for residents in the highest co-ethnic density neighborhoods and 13% lower for residents in the highest wealth areas, compared to other areas (expß 0.82, 95% CI [CI] 0.69, 0.98; expß 0.87, CI 0.75, 1.01, respectively). Stressors were no different whether participants lived in gentrified areas or not. Conclusions: Among middle-aged Chinese immigrants, acculturation stress was lower for residents in neighborhoods with higher proportion of Chinese immigrants and for residents in neighborhoods with higher wealth, whereas gentrification had no influence on acculturation stress. More work on this topic is needed with vulnerable populations such as this one, informed by local context.

The timid invasion: behavioural adjustments and range expansion in a non-native rodent.

Animal behaviour can moderate biological invasion processes, and the native fauna's ability to adapt. The importance and nature of behavioural traits favouring colonization success remain debated. We investigated behavioural responses associated with risk-taking and exploration, both in non-native bank voles (Myodes glareolus, N = 225) accidentally introduced to Ireland a century ago, and in native wood mice (Apodemus sylvaticus, N = 189), that decline in numbers with vole expansion. We repeatedly sampled behavioural responses in three colonization zones: established bank vole populations for greater than 80 years (2 sites), expansion edge vole populations present for 1-4 years (4) and pre-arrival (2). All zones were occupied by wood mice. Individuals of both species varied consistently in risk-taking and exploration. Mice had not adjusted their behaviour to the presence of non-native voles, as it did not differ between the zones. Male voles at the expansion edge were initially more risk-averse but habituated faster to repeated testing, compared to voles in the established population. Results thus indicate spatial sorting for risk-taking propensity along the expansion edge in the dispersing sex. In non-native prey species the ability to develop risk-averse phenotypes may thus represent a fundamental component for range expansions.

So many choices, so little time: Food preference and movement vary with the landscape of fear.

Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.

Cumulative Experience of Neighborhood Walkability and Change in Weight and Waist Circumference in REGARDS.

Neighborhood walkability-features of the built environment that promote pedestrian activity-has been associated with greater physical activity and lower body mass index (BMI; calculated as weight (kg)/height (m)2) among neighborhood residents. However, much of the literature has been cross-sectional and only a few cohort studies have assessed neighborhood features throughout follow-up. Using data from the Reasons for Geographic and Racial Differences in Stroke Study (2003-2016) and a neighborhood walkability index (NWI) measured annually during follow-up, we assessed whether the cumulative experience of neighborhood walkability (NWI-years) predicted BMI and waist circumference after approximately 10 years of follow-up, controlling for these anthropometric measures at enrollment. Analyses were adjusted for individual-level sociodemographic covariates and the cumulative experience of neighborhood poverty rate and neighborhood greenspace coverage. Almost a third (29%) of participants changed address at least once during follow-up. The first change of residence, on average, brought the participants to neighborhoods with higher home values and lower NWI scores than their originating neighborhoods. Compared with those having experienced the lowest quartile of cumulative NWI-years, those who experienced the highest quartile had 0.83 lower BMI (95% confidence interval, -1.5, -0.16) and 1.07-cm smaller waist circumference (95% confidence interval, -1.96, -0.19) at follow-up. These analyses provide additional longitudinal evidence that residential neighborhood features that support pedestrian activity are associated with lower adiposity.