Light pollution affects invasive and native plant traits important to plant competition and herbivorous insects

Biological Invasions - Invasions in urban settings have been understudied in terms of how invasions are impacted by uniquely urban stressors, such as streetlights. Plant physiology and phenology...     

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy.     

Direct and indirect effects of light pollution on the performance of an herbivorous insect

Light pollution is a global disturbance with resounding impacts on a wide variety of organisms, but our understanding of these impacts is restricted to relatively few higher vertebrate species. We tested the direct effects of light pollution on herbivore performance as well as indirect effects mediated by host plant quality. We found that artificial light from streetlights alters plant toughness. Additionally, we found evidence of both direct and indirect effects of light pollution on the performance of an herbivorous insect, which indicates that streetlights can have cascading impacts on multiple trophic levels. Our novel findings suggest that light pollution can alter plant-insect interactions and thus may have important community-wide consequences.     

Experiences of Domestic Violence and Mental Disorders: A Systematic Review and Meta-Analysis

Background

Little is known about the extent to which being a victim of domestic violence is associated with different mental disorders in men and women. We aimed to estimate the prevalence and odds of being a victim of domestic violence by diagnostic category and sex.

Methods

Study design: Systematic review and meta-analysis. Data Sources: Eighteen biomedical and social sciences databases (including MEDLINE, EMBASE, PsycINFO); journal hand searches; scrutiny of references and citation tracking of included articles; expert recommendations, and an update of a systematic review on victimisation and mental disorder. Inclusion criteria: observational and intervention studies reporting prevalence or odds of being a victim of domestic violence in men and women (aged ≥16 years), using validated diagnostic measures of mental disorder. Procedure: Data were extracted and study quality independently appraised by two reviewers. Analysis: Random effects meta-analyses were used to pool estimates of prevalence and odds.

Results

Forty-one studies were included. There is a higher risk of experiencing adult lifetime partner violence among women with depressive disorders (OR 2.77 (95% CI 1.96–3.92), anxiety disorders (OR 4.08 (95% CI 2.39–6.97), and PTSD (OR 7.34 95% CI 4.50–11.98), compared to women without mental disorders. Insufficient data were available to calculate pooled odds for other mental disorders, family violence (i.e. violence perpetrated by a non-partner), or violence experienced by men. Individual studies reported increased odds for women and men for all diagnostic categories, including psychoses, with a higher prevalence reported for women. Few longitudinal studies were found so the direction of causality could not be investigated.

Conclusions

There is a high prevalence and increased likelihood of being a victim of domestic violence in men and women across all diagnostic categories, compared to people without disorders. Longitudinal studies are needed to identify pathways to being a victim of domestic violence to optimise healthcare responses.     

Mitochondrial DNA polymorphism A4917G is independently associated with age-related macular degeneration

The objective of this study was to determine if MTND2*LHON4917G (4917G), a specific non-synonymous polymorphism in the mitochondrial genome previously associated with neurodegenerative phenotypes, is associated with increased risk for age-related macular degeneration (AMD). A preliminary study of 393 individuals (293 cases and 100 controls) ascertained at Vanderbilt revealed an increased occurrence of 4917G in cases compared to controls (15.4% vs.9.0%, p = 0.11). Since there was a significant age difference between cases and controls in this initial analysis, we extended the study by selecting Caucasian pairs matched at the exact age at examination. From the 1547 individuals in the Vanderbilt/Duke AMD population association study (including 157 in the preliminary study), we were able to match 560 (280 cases and 280 unaffected) on exact age at examination. This study population was genotyped for 4917G plus specific AMD-associated nuclear genome polymorphisms in CFH, LOC387715 and ApoE. Following adjustment for the listed nuclear genome polymorphisms, 4917G independently predicts the presence of AMD (OR = 2.16, 95%CI 1.20-3.91, p = 0.01). In conclusion, a specific mitochondrial polymorphism previously implicated in other neurodegenerative phenotypes (4917G) appears to convey risk for AMD independent of recently discovered nuclear DNA polymorphisms.     

RNA‐based fluorescent biosensors for live cell detection of bacterial sRNA

Bacteria contain a diverse set of RNAs to provide tight regulation of gene expression in response to environmental stimuli. Bacterial small RNAs (sRNAs) work in conjunction with protein cofactors to bind complementary mRNA sequences in the cell, leading to up‐ or downregulation of protein synthesis. In vivo imaging of sRNAs can aid in understanding their spatiotemporal dynamics in real time, which inspires new ways to manipulate these systems for a variety of applications including synthetic biology and therapeutics. Current methods for sRNA imaging are quite limited in vivo and do not provide real‐time information about fluctuations in sRNA levels. Herein, we describe our efforts toward the development of an RNA‐based fluorescent biosensor for bacterial sRNA both in vitro and in vivo. We validated these sensors for three different bacterial sRNAs in Escherichia coli and demonstrated that the designs provide a bright, sequence‐specific signal output in response to exogenous and endogenous RNA targets.