Stony Brook University

About: Stony Brook University is a education organization based out in Stony Brook, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32534 authors who have published 68218 publications receiving 3035131 citations. The organization is also known as: State University of New York at Stony Brook & SUNY Stony Brook.

The Persistence of Attention to Emotion: Brain Potentials During and After Picture Presentation

Abstract: Emotional stimuli have been shown to elicit increased perceptual processing and attentional allocation. The late positive potential (LPP) is a sustained P300-like component of the event-related potential that is enhanced after the presentation of pleasant and unpleasant pictures as compared with neutral pictures. In this study, the LPP was measured using dense array electroencephalograph both before and after pleasant, neutral, and unpleasant images to examine the time course of attentional allocation toward emotional stimuli. Results from 17 participants confirmed that the LPP was larger after emotional than neutral images and that this effect persisted for 800 ms after pleasant picture offset and at least 1,000 ms after unpleasant picture offset. The persistence of increased attention after unpleasant compared to pleasant stimuli is consistent with the existence of a negativity bias. Overall, these results indicate that attentional capture of emotion continues well beyond picture presentation and that this can be measured with the LPP. Implications and directions for future research are discussed.

Adverse effects of citrate/gold nanoparticles on human dermal fibroblasts.

Abstract: Nanoscale engineering is one of the most dynamically growing areas at the interface between electronics, physics, biology, and medicine. As there are no safety regulations yet, concerns about future health problems are rising. We investigated the effects of citrate/gold nanoparticles at different concentrations and exposure times on human dermal fibroblasts. We found that, as a result of intracellular nanoparticle presence, actin stress fibers disappeared, thereby inducing major adverse effects on cell viability. Thus, properties such as cell spreading and adhesion, cell growth, and protein synthesis to form the extracellular matrix were altered dramatically. These results suggest that the internal cell activities have been damaged.

Long-term frontal brain metabolic changes in cocaine abusers.

Abstract: Neurological complications from cocaine use are well recognized. We propose that chronic cocaine use can also cause clinically silent brain dysfunction. We investigated brain glucose metabolism with positron emission tomography (PET) and 2-deoxy-2[18F] fluoro-D-glucose (FDG) in 21 neurologically intact chronic cocaine abusers (C) and 18 normal controls (N). The cocaine abusers were tested 1-6 weeks after the last use of cocaine and seven were retested after a 3 month drug-free period. Global cerebral glucose metabolism was not significantly different between controls and cocaine abusers (N = 38.4 +/- 3, C = 36.5 +/- 5 mumol/100 g of tissue, min). However, cocaine abusers had significantly (P less than 0.05) lower metabolic activity in 16 of the 21 left frontal regions and 8 of the 21 right frontal regions. These decreases persisted after 3-4 months of detoxification and were correlated with the dose (P less than or equal to 0.01) and the years of cocaine use (P less than or equal to 0.05). This study shows reduced rates of frontal metabolism in neurologically intact cocaine abusers that persist even after 3-4 months of detoxification.

Hypertension, Cardiovascular Disease, and Age-Related Macular Degeneration

Abstract: Objectives To describe a case-control study of risk factors for neovascular and non-neovascular age-related macular degeneration (AMD) and to present findings on associations with systemic hypertension and cardiovascular disease. Methods Participants with and without neovascular and non-neovascular AMD were recruited from 11 ophthalmology practices in the New York, NY, metropolitan area. Comprehensive data collection included (1) a standardized interview, (2) blood pressure measurements, and (3) blood samples. Cases and controls were classified from fundus photograph gradings. Polychotomous logistic regression analyses were used to evaluate associations. Results Classification of 1222 sets of available photographs resulted in the inclusion of a neovascular case group (n = 182), a non-neovascular case group (n = 227), and a control group (n = 235). Neovascular AMD was positively associated with diastolic blood pressure greater than 95 mm Hg (odds ratio [OR] = 4.4), self-reported use of potent antihypertensive medication (OR = 2.1), physician-reported history of hypertension (OR = 1.8), use of antihypertensive medication (OR = 2.5), combinations of self-reported and physician-reported data on hypertension and its treatment (OR = 1.7), high-density lipoprotein level (OR = 2.3), and dietary cholesterol level (OR = 2.2). Non-neovascular AMD was unrelated to hypertension or cholesterol level. No associations were found between either AMD type and other definitions of hypertension or other cardiovascular disease. Conclusions These findings suggest that neovascular AMD is associated with moderate to severe hypertension, particularly among patients receiving antihypertensive treatment. They also support the hypotheses that neovascular and non-neovascular AMD may have a different pathogenesis and that neovascular AMD and hypertensive disease may have a similar underlying systemic process.

Boundary recognition in sensor networks by topological methods

Abstract: Wireless sensor networks are tightly associated with the underlying environment in which the sensors are deployed. The global topology of the network is of great importance to both sensor network applications and the implementation of networking functionalities. In this paper we study the problem of topology discovery, in particular, identifying boundaries in a sensor network. Suppose a large number of sensor nodes are scattered in a geometric region, with nearby nodes communicating with each other directly. Our goal is to find the boundary nodes by using only connectivity information. We do not assume any knowledge of the node locations or inter-distances, nor do we enforce that the communication graph follows the unit disk graph model. We propose a simple, distributed algorithm that correctly detects nodes on the boundaries and connects them into meaningful boundary cycles. We obtain as a byproduct the medial axis of the sensor field, which has applications in creating virtual coordinates for routing. We show by extensive simulation that the algorithm gives good results even for networks with low density. We also prove rigorously the correctness of the algorithm for continuous geometric domains.