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.

Anxiety and Sensory Over-Responsivity in Toddlers with Autism Spectrum Disorders: Bidirectional Effects Across Time

Abstract: This report focuses on the emergence of and bidirectional effects between anxiety and sensory over-responsivity (SOR) in toddlers with autism spectrum disorders (ASD). Participants were 149 toddlers with ASD and their mothers, assessed at 2 annual time points. A cross-lag analysis showed that anxiety symptoms increased over time while SOR remained relatively stable. SOR positively predicted changes in anxiety over and above child age, autism symptom severity, NVDQ, and maternal anxiety, but anxiety did not predict changes in SOR. Results suggest that SOR emerges earlier than anxiety, and predicts later development of anxiety.

Population growth, human development, and deforestation in biodiversity hotspots.

Abstract: Human population and development activities affect the rate of deforestation in biodiversity hotspots. We quantified the effect of human population growth and development on rates of deforestation and analyzed the relationship between these causal factors in the 1980s and 1990s. We compared the averages of population growth, human development index (HDI, which measures income, health, and education), and deforestation rate and computed correlations among these variables for countries that contain biodiversity hotspots. When population growth was high and HDI was low there was a high rate of deforestation, but when HDI was high, rate of deforestation was low, despite high population growth. The correlation among variables was significant for the 1990s but not for the 1980s. The relationship between population growth and HDI had a regional pattern that reflected the historical process of development. Based on the changes in HDI and deforestation rate over time, we identified two drivers of deforestation: policy choice and human-development constraints. Policy choices that disregard conservation may cause the loss of forests even in countries that are relatively developed. Lack of development in other countries, on the other hand, may increase the pressure on forests to meet the basic needs of the human population. Deforestation resulting from policy choices may be easier to fix than deforestation arising from human development constraints. To prevent deforestation in the countries that have such constraints, transfer of material and intellectual resources from developed countries may be needed. Popular interest in sustainable development in developed countries can facilitate the transfer of these resources.

Autism: the micro-movement perspective.

Abstract: The current assessment of behaviors in the inventories to diagnose autism spectrum disorders (ASD) focus on observation and discrete categorizations. Behaviors require movements, yet measurements of physical movements are seldom included. Their inclusion however, could provide an objective characterization of behavior to help unveil interactions between the peripheral and the central nervous systems. Such interactions are critical for the development and maintenance of spontaneous autonomy, self-regulation and voluntary control. At present, current approaches cannot deal with the heterogeneous, dynamic and stochastic nature of development. Accordingly, they leave no avenues for real-time or longitudinal assessments of change in a coping system continuously adapting and developing compensatory mechanisms. We offer a new unifying statistical framework to reveal re-afferent kinesthetic features of the individual with ASD. The new methodology is based on the non-stationary stochastic patterns of minute fluctuations (micro-movements) inherent to our natural actions. Such patterns of behavioral variability provide re-entrant sensory feedback contributing to the autonomous regulation and coordination of the motor output. From an early age, this feedback supports centrally driven volitional control and fluid, flexible transitions between intentional and spontaneous behaviors. We show that in ASD there is a disruption in the maturation of this form of proprioception. Despite this disturbance, each individual has unique adaptive compensatory capabilities that we can unveil and exploit to evoke faster and more accurate decisions. Measuring the kinesthetic re-afference in tandem with stimuli variations we can detect changes in their micro-movements indicative of a more predictive and reliable kinesthetic percept. Our methods address the heterogeneity of ASD with a personalized approach grounded in the inherent sensory-motor abilities that the individual has already developed.

Direct-bandgap GeSn grown on silicon with 2230 nm photoluminescence

Abstract: Material and optical characterizations have been conducted for epitaxially grown Ge1−xSnx thin films on Si with Sn composition up to 10%. A direct bandgap Ge0.9Sn0.1 alloy has been identified by temperature-dependent photoluminescence (PL) study based on the single peak spectrum and the narrow line-width. Room temperature PL emission as long as 2230 nm has also been observed from the same sample.

Identification of novel candidate oncogenes and tumor suppressors in malignant pleural mesothelioma using large-scale transcriptional profiling.

Abstract: Malignant pleural mesothelioma (MPM) is a highly lethal, poorly understood neoplasm that is typically associated with asbestos exposure. We performed transcriptional profiling using high-density oligonucleotide microarrays containing ∼22,000 genes to elucidate potential molecular and pathobiological pathways in MPM using discarded human MPM tumor specimens (n = 40), normal lung specimens (n = 4), normal pleura specimens (n = 5), and MPM and SV40-immortalized mesothelial cell lines (n = 5). In global expression analysis using unsupervised clustering techniques, we found two potential subclasses of mesothelioma that correlated loosely with tumor histology. We also identified sets of genes with expression levels that distinguish between multiple tumor subclasses, normal and tumor tissues, and tumors with different morphologies. Microarray gene expression data were confirmed using quantitative reverse transcriptase-polymerase chain reaction and protein analysis for three novel candidate oncogenes (NME2, CRI1, and PDGFC) and one candidate tumor suppressor (GSN). Finally, we used bioinformatics tools (ie, software) to create and explore complex physiological pathways. Combined, all of these data may advance our understanding of mesothelioma tumorigenesis, pathobiology, or both.