University of Massachusetts Boston

About: University of Massachusetts Boston is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Health care. The organization has 6541 authors who have published 12918 publications receiving 411731 citations. The organization is also known as: UMass Boston.

Clinical Assessment and Management of Toddlers With Suspected Autism Spectrum Disorder: Insights From Studies of High-Risk Infants

Abstract: With increased public awareness of the early signs and recent American Academy of Pediatrics recommendations that all 18- and 24-month-olds be screened for autism spectrum disorders, there is an increasing need for diagnostic assessment of very young children. However, unique challenges exist in applying current diagnostic guidelines for autism spectrum disorders to children under the age of 2 years. In this article, we address challenges related to early detection, diagnosis, and treatment of autism spectrum disorders in this age group. We provide a comprehensive review of findings from recent studies on the early development of children with autism spectrum disorders, summarizing current knowledge on early signs of autism spectrum disorders, the screening properties of early detection tools, and current best practice for diagnostic assessment of autism spectrum disorders before 2 years of age. We also outline principles of effective intervention for children under the age of 2 with suspected/confirmed autism spectrum disorders. It is hoped that ongoing studies will provide an even stronger foundation for evidence-based diagnostic and intervention approaches for this critically important age group.

Will Extreme Climatic Events Facilitate Biological Invasions

Abstract: Extreme climatic events (ECEs) – such as unusual heat waves, hurricanes, floods, and droughts – can dramatically affect ecological and evolutionary processes, and these events are projected to become more frequent and more intense with ongoing climate change. However, the implications of ECEs for biological invasions remain poorly understood. Using concepts and empirical evidence from invasion ecology, we identify mechanisms by which ECEs may influence the invasion process, from initial introduction through establishment and spread. We summarize how ECEs can enhance invasions by promoting the transport of propagules into new regions, by decreasing the resistance of native communities to establishment, and also sometimes by putting existing non-native species at a competitive disadvantage. Finally, we outline priority research areas and management approaches for anticipating future risks of unwanted invasions following ECEs. Given predicted increases in both ECE occurrence and rates of species introduction...

Effects of Yoga Versus Walking on Mood, Anxiety, and Brain GABA Levels: A Randomized Controlled MRS Study

Abstract: Objectives: Yoga and exercise have beneficial effects on mood and anxiety. γ-Aminobutyric acid (GABA)-ergic activity is reduced in mood and anxiety disorders. The practice of yoga postures is associated with increased brain GABA levels. This study addresses the question of whether changes in mood, anxiety, and GABA levels are specific to yoga or related to physical activity. Methods: Healthy subjects with no significant medical/psychiatric disorders were randomized to yoga or a metabolically matched walking intervention for 60 minutes 3 times a week for 12 weeks. Mood and anxiety scales were taken at weeks 0, 4, 8, 12, and before each magnetic resonance spectroscopy scan. Scan 1 was at baseline. Scan 2, obtained after the 12-week intervention, was followed by a 60-minute yoga or walking intervention, which was immediately followed by Scan 3. Results: The yoga subjects (n = 19) reported greater improvement in mood and greater decreases in anxiety than the walking group (n = 15). There were positiv...

Global Patterns and Predictions of Seafloor Biomass Using Random Forests

Abstract: A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

Condition indices for conservation: new uses for evolving tools

Abstract: Biologists have developed a wide range of morphological, biochemical and physiological metrics to assess the health and, in particular, the energetic status of individual animals. These metrics originated to quantify aspects of human health, but have also proven useful to address questions in life history, ecology and resource management of game and commercial animals. We review the application of condition indices (CI) for conservation studies and focus on measures that quantify fat reserves, known to be critical for energetically challenging activities such as migration, reproduction and survival during periods of scarcity. Standard methods score fat content, or rely on a ratio of body mass rationalized by some measure of size, usually a linear dimension such as wing length or total body length. Higher numerical values of these indices are interpreted to mean an animal has greater energy reserves. Such CIs can provide predictive information about habitat quality and reproductive output, which in turn can help managers with conservation assessments and policies. We review the issues about the methods and metrics of measurement and describe the linkage of CIs to measures of body shape. Debates in the literature about the best statistical methods to use in computing and comparing CIs remain unresolved. Next, we comment on the diversity of methods used to measure body composition and the diversity of physiological models that compute body composition and CIs. The underlying physiological regulatory systems that govern the allocation of energy and nutrients among compartments and processes within the body are poorly understood, especially for field situations, and await basic data from additional laboratory studies and advanced measurement systems including telemetry. For now, standard physiological CIs can provide supporting evidence and mechanistic linkages for population studies that have traditionally been the focus of conservation biology. Physiologists can provide guidance for the field application of conditions indices with validation studies and development of new instruments.