Association of behavioural and social-communicative profiles in children with 16p11.2 copy number variants: a multi-site study.

BACKGROUND: Despite the established knowledge that recurrent copy number variants (CNVs) at the 16p11.2 locus BP4-BP5 confer risk for behavioural and language difficulties, limited research has been conducted on the association between behavioural and social-communicative profiles. The current study aims to further delineate the prevalence, nature and severity of, and the association between, behavioural and social-communicative features of school-aged children with 16p11.2 deletion syndrome (16p11.2DS) and 16p11.2 duplication (16p11.2Dup). METHODS: A total of 68 individuals (n = 47 16p11.2DS and n = 21 16p11.2Dup) aged 6-17 years participated. Standardised intelligence tests were administered, and behavioural and social-communicative skills were assessed by standardised questionnaires. Scores of both groups were compared with population norms and across CNVs. The influence of confounding factors was investigated, and correlation analyses were performed. RESULTS: Compared with the normative sample, children with 16p11.2DS showed high rates of social responsiveness (67%) and communicative problems (69%), while approximately half (52%) of the patients displayed behavioural problems. Children with 16p11.2Dup demonstrated even higher rates of social-communicative problems (80-90%) with statistically significantly more externalising and overall behavioural challenges (89%). In both CNV groups, there was a strong positive correlation between behavioural and social-communicative skills. CONCLUSIONS: School-aged children with 16p11.2 CNVs show high rates of behavioural, social responsiveness and communicative problems compared with the normative sample. These findings point to the high prevalence of autistic traits and diagnoses in these CNV populations. Moreover, there is a high comorbidity between behavioural and social-communicative problems. Patients with difficulties in both domains are vulnerable and need closer clinical follow-up and care.

Monitoring vegetation change and dynamics on U.S. Army training lands using satellite image time series analysis.

Given the significant land holdings of the U.S. Department of Defense, and the importance of those lands to support a variety of inherently damaging activities, application of sound natural resource conservation principles and proactive monitoring practices are necessary to manage military training lands in a sustainable manner. This study explores a method for, and the utility of, analyzing vegetation condition and trends as sustainability indicators for use by military commanders and land managers, at both the national and local levels, in identifying when and where vegetation-related environmental impacts might exist. The BFAST time series decomposition method was applied to a ten-year MODIS NDVI time series dataset for the Fort Riley military installation and Konza Prairie Biological Station (KPBS) in northeastern Kansas. Imagery selected for time-series analysis were 16-day MODIS NDVI (MOD13Q1 Collection 5) composites capable of characterizing vegetation change induced by human activities and climate variability. Three indicators related to gradual interannual or abrupt intraannual vegetation change for each pixel were calculated from the trend component resulting from the BFAST decomposition. Assessment of gradual interannual NDVI trends showed the majority of Fort Riley experienced browning between 2001 and 2010. This result is supported by validation using high spatial resolution imagery. The observed versus expected frequency of linear trends detected at Fort Riley and KPBS were significantly different and suggest a causal link between military training activities and/or land management practices. While both sites were similar with regards to overall disturbance frequency and the relative spatial extents of monotonic or interrupted trends, vegetation trajectories after disturbance were significantly different. This suggests that the type and magnitude of disturbances characteristic of each location result in distinct post-disturbance vegetation responses. Using a remotely-sensed vegetation index time series with BFAST and the indicators outlined here provides a consistent and relatively rapid assessment of military training lands with applicability outside of grassland biomes. Characterizing overall trends and disturbance responses of vegetation can promote sustainable use of military lands and assist land managers in targeting specific areas for various rehabilitation activities.