Early life stress, MAOA, and gene-environment interactions predict behavioral disinhibition in children

Several, but not all, studies have shown that the monoamine oxidase A functional promoter polymorphism ( MAOA-LPR ) interacts with childhood adversity to predict adolescent and adult antisocial behavior. However, it is not known whether MAOA-LPR interacts with early life (pre-birth–3 years) stressors to influence behavior in prepubertal children.
The Avon Longitudinal Study of Parents and Children, UK, is a community-representative cohort study of children followed from pre-birth onwards. The impact of family adversity from pre-birth to age 3 years and stressful life events from 6 months to 7 years on behavioral disinhibition was determined in 7500 girls and boys. Behavioral disinhibition measures were: mother-reported hyperactivity and conduct disturbances (Strengths and Difficulties Questionnaire) at ages 4 and 7 years.
In both sexes, exposure to family adversity and stressful life events in the first 3 years of life predicted behavioral disinhibition at age 4, persisting until age 7. In girls, MAOA-LPR interacted with stressful life events experienced from 6 months to 3.5 years to influence hyperactivity at ages 4 and 7. In boys, the interaction of MAOA-LPR with stressful life events between 1.5 and 2.5 years predicted hyperactivity at age 7 years. The low activity MAOA-LPR variant was associated with increased hyperactivity in girls and boys exposed to high stress. In contrast, there was no MAOA-LPR interaction with family adversity.
In a general population sample of prepubertal children, exposure to common stressors from pre-birth to 3 years predicted behavioral disinhibition, and MAOA-LPR – stressful life event interactions specifically predicted hyperactivity.     

Projected climate change effects on Alberta's boreal forests imply future challenges for oil sands reclamation

Climate change will drive significant changes in vegetation cover and also impact efforts to restore ecosystems that have been disturbed by human activities. Bitumen mining in the Alberta oil sands region of western Canada requires reclamation to “equivalent land capability,” implying establishment of vegetation similar to undisturbed boreal ecosystems. However, there is consensus that this region will be exposed to relatively severe climate warming, causing increased occurrence of drought and wildfire, which threaten the persistence of both natural and reclaimed ecosystems. We used a landscape model, LANDIS‐II, to simulate plant responses to climate change and disturbances, forecasting changes to boreal forests within the oil sands region. Under the most severe climate forcing scenarios (representative concentration pathway [RCP] 8.5) the model projected substantial decreases in forest biomass, with the future forest being dominated by drought‐ and fire‐tolerant species characteristic of parkland or prairie ecosystems. In contrast, less extreme climate forcing scenarios (RCPs 2.6 and 4.5) had relatively minor effects on forest composition and biomass with boreal conifers continuing to dominate the landscape. If the climate continues to change along a trajectory similar to those simulated by climate models for the RCP 8.5 forcing scenario, current reclamation goals to reestablish spruce‐dominated boreal forest will likely be difficult to achieve. Results from scenario modeling studies such as ours, and continued monitoring of change in the boreal forest, will help inform reclamation practices, which could include establishment of species better adapted to warmer and drier conditions.     

Moderate disturbances accelerate forest transition dynamics under climate change in the temperate–boreal ecotone of eastern North America

Several temperate tree species are expected to migrate northward and colonize boreal forests in response to climate change. Tree migrations could lead to transitions in forest types, but these could be influenced by several non‐climatic factors, such as disturbances and soil conditions. We analysed over 10,000 forest inventory plots, sampled from 1970 to 2018 in meridional Québec, Canada, to identify what environmental conditions promote or prevent regional‐scale forest transitions. We used a continuous‐time multi‐state Markov model to quantify the probabilities of transitions between forest states (temperate, boreal, mixed, pioneer) as a function of climate (mean temperature and climate moisture index during the growing season), soil conditions (pH and drainage) and disturbances (severity levels of natural disturbances and logging). We further investigate how different disturbance types and severities impact forests' short‐term transient dynamics and long‐term equilibrium using properties of Markov transition matrices. The most common transitions observed during the study period were from mixed to temperate states, as well as from pioneer to boreal forests. In our study, transitions were mainly driven by natural and anthropogenic disturbances and secondarily by climate, whereas soil characteristics exerted relatively minor constraints. While major disturbances only promoted transitions to the pioneer state, moderate disturbances increased the probability of transition from mixed to temperate states. Long‐term projections of our model under the current environmental conditions indicate that moderate disturbances would promote a northward shift of the temperate forest. Moreover, disturbances reduced turnover and convergence time for all transitions, thereby accelerating forest dynamics. Contrary to our expectation, mixed to temperate transitions were not driven by temperate tree recruitment but by mortality and growth. Overall, our results suggest that moderate disturbances could catalyse rapid forest transitions and accelerate broad‐scale biome shifts.     

The suitability of actigraphy,diary data,and urinary melatonin profiles for quantitative assessment of sleep disturbances in schizophrenia: A case report

Sleep disruption is a commonly encountered clinical feature in schizophrenic patients, and one important concern is to determine the extent of this disruption under “real” life situations. Simultaneous wrist actigraphy, diary records, and repeated urine collection for urinary 6‐sulphatoxymelatonin (aMT6s) profiles are appropriate tools to assess circadian rhythms and sleep patterns in field studies. Their suitability for long‐term recordings of schizophrenic patients living in the community has not been evaluated. In this case report, we document long‐term simultaneous wrist actigraphy, light detection, repeated urine collection, and diary records as a suitable combination of non‐invasive techniques to quantify and assess changes in sleep‐wake cycles, light exposure, and melatonin profiles in a schizophrenic patient. The actigraph was well‐tolerated by the patient, and compliance to diary records and 48 h urine collection was particularly good with assistance from family members. The data obtained by these techniques are illustrated, and the results reveal remarkable abnormal patterns of rest‐activity patterns, light exposure, and melatonin production. We observed various rest‐activity patterns, including phase‐shifts, highly delayed sleep on‐ and offsets, and irregular rest‐activity phases. The period of the rest‐activity rhythm, light‐dark cycle, and melatonin rhythm was longer than 24 h. These circadian abnormalities may reinforce the altered sleep patterns and the problems of cognitive function and social engagement associated with schizophrenic.     

The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation‐by‐distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation‐by‐distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long‐standing natural features (e.g. water bodies) co‐exist on the landscape.     

Neutral communities may lead to decreasing diversity-disturbance relationships: insights from a generic simulation model

Many attempts have been made to confirm or reject the unimodal relationship between disturbance and diversity stated by the intermediate disturbance hypothesis (IDH). However, the reasons why the predictions of the IDH apply or fail in particular systems are not always obvious. Here, we use a spatially explicit, individual-based community model that simulates species coexistence in a landscape subjected to disturbances to compare diversity-disturbance curves of communities with different coexistence mechanisms: neutrality, trade-off mechanism and intraspecific density dependence. We show that the shape of diversity-disturbance curves differs considerably depending on the type of coexistence mechanism assumed: (1) Neutral communities generally show decreasing diversity-disturbance curves with maximum diversity at zero disturbance rates contradicting the IDH, whereas trade-off communities generally show unimodal relationships confirming the IDH and (2) density-dependent mechanisms do increase the diversity of both neutral and trade-off communities. Finally, we discuss how these mechanisms determine diversity in disturbed landscapes.     

Mean square stability of uncertain stochastic BAM neural networks with interval time-varying delays

The robust asymptotic stability analysis for uncertain BAM neural networks with both interval time-varying delays and stochastic disturbances is considered. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which takes into account the ranges for delays, some new stability criteria are established to guarantee the delayed BAM neural networks to be robustly asymptotically stable in the mean square. Unlike the most existing mean square stability conditions for BAM neural networks, the supplementary requirements that the time derivatives of time-varying delays must be smaller than 1 are released and the lower bounds of time varying delays are not restricted to be 0. Furthermore, in the proposed scheme, the stability conditions are delay-range-dependent and rate-dependent/independent. As a result, the new criteria are applicable to both fast and slow time-varying delays. Three numerical examples are given to illustrate the effectiveness of the proposed criteria.     

A Desktop Apparatus for Studying Interactions Between Microorganisms and Small-Scale Fluid Motion

Low levels of kinetic energy dissipation were successfully generated in a reactor using two submersible speakers. A software programme controlled the amplitude and frequency of the signal fed to each speaker and achieved good repeatability of flow conditions. The flow reactor had a near isotropic flow regime with a low mean flow, values were calculated from particle image velocimetry measurements. The flow characteristics compared well with grid turbulence reactors, though as no moving parts are present in this reactor design the strain rates were lower compared to oscillating grid set-ups. The low range of Reynolds numbers based on Taylor microscales (Re_λ~0.5–5.9) covered both turbulent and non-turbulent flow regimes. The small-scale fluid motion produced over the entire volume of this reactor makes it suitable for experiments examining the physiological responses of fluid motion on microorganisms.