Using neighborhood characteristics to predict vacancy types: Comparing multi-scale conditions surrounding existing vacant lots
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ABSTRACT:
SUBMITTER: Lee R
PROVIDER: S-EPMC10653006 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
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Project description:In suburban regions, vacant lots potentially offer significant opportunities for biodiversity conservation. Recently, in Japan, due to an economic recession, some previously developed lands have become vacant. Little is known, however, about the legacy of earlier earthmoving, which involves topsoil removal and ground leveling before residential construction, on plant community composition in such vacant lots. To understand (dis)assembly processes in vacant lots, we studied 24 grasslands in a suburban region in Japan: 12 grasslands that had experienced earthmoving and 12 that had not. We surveyed plant community composition and species richness, and clarified compositional turnover (replacement of species) and nestedness (nonrandom species loss) by distance-based β-diversities, which were summarized by PCoA analysis. We used piecewise structural equation modeling to examine the effects of soil properties, mowing frequency, past and present habitat connectivities on compositional changes. As a result, past earthmoving, mowing frequency, soil properties, and past habitat connectivity were found to be the drivers of compositional turnover. In particular, we found legacy effects of earthmoving: earthmoving promoted turnover from native grassland species to weeds in arable lands or roadside by altering soil properties. Mowing frequency also promoted the same turnover, implying that extensive rather than intensive mowing can modify the negative legacy effects and maintain grassland species. Decrease in present habitat connectivity marginally enhanced nonrandom loss of native grassland species (nestedness). Present habitat connectivity had a positive effect on species richness, highlighting the important roles of contemporary dispersal. Our study demonstrates that community assembly is a result of multiple processes differing in spatial and temporal scales. We suggest that extensive mowing at local scale, as well as giving a high conservation priority to grasslands with high habitat connectivity at regional scale, is the promising actions to maintain endangered native grassland species in suburban landscapes with negative legacy effects of earthmoving.
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Project description:Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ an integrative approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, associations between cortical thickness similarity and traits were limited to anthropometrics such as height, weight, and birth weight, as well as a marker of neighborhood socioeconomic conditions. Common genetic variants explained significant proportions of variance across nearly all included outcomes, although estimates were somewhat lower than previous reports. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as neighborhood socioeconomic conditions and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample.
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Project description:For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.
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Project description:Exposure to adverse environmental and social conditions affects physical and mental health through complex mechanisms. Different racial/ethnic (R/E) groups may be more or less vulnerable to the same conditions, and the resilience mechanisms that can protect them likely operate differently in each population. We investigate how adverse neighborhood conditions (neighborhood disorder, NDis) differentially impact mental health (anxiety, Anx) in a sample of white and Black (African American) young women from Southeast Texas, USA. We illustrate a simple yet underutilized segmented regression model where linearity is relaxed to allow for a shift in the strength of the effect with the levels of the predictor. We compare how these effects change within R/E groups with the level of the predictor, but also how the "tipping points," where the effects change in strength, may differ by R/E. We find with classic linear regression that neighborhood disorder adversely affects Black women's anxiety, while in white women the effect seems negligible. Segmented regressions show that the Ndis → Anx effects in both groups of women appear to shift at similar levels, about one-fifth of a standard deviation below the mean of NDis, but the effect for Black women appears to start out as negative, then shifts in sign, i.e., to increase anxiety, while for white women, the opposite pattern emerges. Our findings can aid in devising better strategies for reducing health disparities that take into account different coping or resilience mechanisms operating differentially at distinct levels of adversity. We recommend that researchers investigate when adversity becomes exceedingly harmful and whether this happens differentially in distinct populations, so that intervention policies can be planned to reverse conditions that are more amenable to change, in effect pushing back the overall social risk factors below such tipping points.
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Project description:Pre-existing differences between individual cancer cells can predict which cells will become resistant upon the application of treatment. This understanding has been furthered by novel methods in DNA barcoding that allow tracking of clones and their cell states during treatment. However, previous studies using these techniques have been limited in their scope, focusing on how single cell-states lead to resistance to a single treatment. In this study, we performed multi-treatment, high-throughput clonal tracking and single-cell RNA-sequencing to trace rare clones through the development of resistance to many different treatments in parallel with the goal of identifying cell states associated with multi-treatment resistance. We found that clones that will go on to develop resistance to one treatment had an increased chance of separately developing resistance to other treatments with diverse mechanisms of action. Additionally, we identified high CD44 expression in treatment-naive cells as a predictor of future resistance to multiple different treatments. Furthermore, for cells within the same treatment condition, we found that differences in gene expression states prior to treatment can lead cells to follow divergent paths towards their ultimate resistance fate. This work provides a framework for extracting targetable gene expression states from complex resistance dynamics across multiple treatments to eliminate multi-treatment resistance.
2024-10-14 | GSE279162 | GEO
Project description:ObjectivesTo investigate the impact of SARS-CoV-2 on self-reported mood, coping and health behaviours of people living with existing health conditions in the UK to understand how to improve coping responses to the threat of SARS-CoV-2.DesignQuantitative design using a cross-sectional survey.SettingOnline survey in the UK.ParticipantsUK adults (18+ years) were eligible to participate. A total of 9110 people participated. Of these, 4377 (48%) reported at least one existing health condition, 874 (10%) reported having two or more existing conditions, and 715 (8%) reported having an existing mental health condition.Primary and secondary outcome measuresMultivariable linear regression and sequential multiple mediation analysis were used to estimate differences in average scores for active and avoidant coping response scores due to pre-existing health conditions, and to investigate the extent to which these differences are explained by differences in perceptions, beliefs, concerns and mood.ResultsPeople with pre-existing physical (+1.11 higher; 95% CI 0.88 to 1.34) and especially mental health conditions (3.06 higher; 95% CI 2.65 to 3.48) reported poorer health and used more avoidant coping compared with healthy participants. Under some strong untestable assumptions, we estimate that experiencing low mood or concern related to SARS-CoV-2 mostly explained the relationship between existing health conditions and avoidant coping.ConclusionPsychological support and interventions including behaviour change are required to mitigate the psychological burden of the SARS-CoV-2 pandemic and increase autonomy in people with and without pre-existing conditions during this highly uncertain time. Psychologists are well placed to support clinicians and people with existing health conditions to minimise the psychological impact of SARS-CoV-2, in order to alleviate the subsequent strain on healthcare services.
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Project description:To investigate transcriptomic differences between Cushing's disease adenomas and adjacent normal tissues We performed RNAseq analysis on CD adenomas versus their adjacent normal tissues
2022-07-16 | GSE208107 | GEO
Project description:BackgroundThe communities we live in are central to our health. Neighborhood disadvantage is associated with worse physical and mental health and even early mortality, while resident sense of safety and positive neighborhood sentiment has been repeatedly linked to better physical and mental health outcomes. Therefore, understanding where negative neighborhood sentiment and safety are salient concerns can help inform public health interventions and as a result, improve health outcomes. To date, fear of crime and neighborhood sentiment data or indices have largely been based on the administration of time consuming and costly standardized surveys.ObjectiveThe current study aims to develop a Neighborhood Sentiment and Safety Index (NSSI) at the census tract level, building on publicly available data repositories, including the US Census and ACS surveys, Data Axle, and ESRI repositories.MethodsThe NSSI was created using Principal Component Analysis. Mineigen and minimum loading values were 1 and 0.3, respectively. Throughout the step-wise PCA process, variables were excluded if their loading value was below 0.3 or if variables loaded into multiple components.ResultsThe novel index was validated against standardized survey items from a longitudinal cohort study in the Northeastern United States characterizing experiences of (1) Neighborhood Characteristics with a Pearson correlation of -0.34 (p < 0.001) and, (2) Neighborhood Behavior Impact with a Pearson correlation of -0.33 (p < 0.001). It also accurately predicted the Share Care Community Well Being Index (Spearman correlation = 0.46) and the neighborhood deprivation index (NDI) (Spearman correlation = -0.75).SignificanceOur NSSI can serve as a predictor of neighborhood experience where data is either unavailable or too resource consuming to practically implement in planned studies.Impact statementTo date, fear of crime and neighborhood sentiment data or indices have largely been based on the administration of time consuming and costly standardized surveys. The current study aims to develop a Neighborhood Sentiment and Safety Index (NSSI) at the census tract level, building on publicly available data repositories, including the US Census and ACS surveys, Data Axle, and ESRI repositories. The NSSI was validated against four separate measures and can serve as a predictor of neighborhood experience where data is either unavailable or too resource consuming to practically implement in planned studies.
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Project description:Sensing physical forces is a critical first step in mechano-transduction of cells. Zyxin, a LIM domain-containing protein, is recruited to force-bearing actin filaments and is thought to repair and strengthen them. Yet, the precise force-induced protein interactions surrounding zyxin remain unclear. Using BioID analysis, we identified proximal proteins surrounding zyxin under normal and force-bearing conditions by label-free mass spectrometry analysis. Under force-bearing conditions, increased biotinylation of α-actinin 1, α-actinin 4, and AFAP1 were detected, and these proteins accumulated along force-bearing actin fibers independently from zyxin, albeit at a lower intensity than zyxin. VASP also accumulated along force-bearing actin fibers in a zyxin-dependent manner, but the biotinylation of VASP remained constant regardless of force, supporting the model of a free zyxin-VASP complex in the cytoplasm being corecruited to tensed actin fibers. In addition, ARHGAP42, a RhoA GAP, was also identified as a proximal protein of zyxin and colocalized with zyxin along contractile actin bundles. The overexpression of ARHGAP42 reduced the rate of small wound closure, a zyxin-dependent process. These results demonstrate that the application of proximal biotinylation can resolve the proximity and composition of protein complexes as a function of force, which had not been possible with traditional biochemical analysis.
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Project description:Vacancy engineering effectively modulates the electronic properties of electrode materials, thereby improving their electrochemical performance. In this study, we prepared selenium-deficient NiCo2Se4 (Sev-NCS) using ethylene glycol as a reducing agent in NaOH alkaline environment, and investigated its potential as an electrode material for supercapacitors. Both theoretical and experimental results confirmed that the introduction of vacancies altered the morphology and electronic structure of NiCo2Se4, which in turn synergistically improved the conductivity and the diffusion capability of electrolyte ions. The optimized Sev-NCS electrode achieved an excellent specific capacitance of 2962.7 F g-1 at a current density of 1 A g-1 and superior cycling stability with a capacitance retention of 89.5% even after 10,000 cycles. Furthermore, an asymmetric device composed of the optimized Sev-NCS electrode as the positive electrode and activated carbon as the negative electrode achieved an energy density of 55.6 Wh kg-1 at a power density of 800 W kg-1. Therefore, this work offers novel insights into the role of vacancy engineering in improving the performance of transition metal compound-based electrode materials for supercapacitor.
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