Georgia State University

About: Georgia State University is a education organization based out in Atlanta, Georgia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 13988 authors who have published 35895 publications receiving 1164332 citations. The organization is also known as: GSU & Georgia State.

Deep learning for neuroimaging: A validation study

Abstract: Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Targeted zwitterionic near-infrared fluorophores for improved optical imaging

Abstract: The signal-to-background ratio (SBR) is the key determinant of sensitivity, detectability and linearity in optical imaging. As signal strength is often constrained by fundamental limits, background reduction becomes an important approach for improving the SBR. We recently reported that a zwitterionic near-infrared (NIR) fluorophore, ZW800-1, exhibits low background. Here we show that this fluorophore provides a much-improved SBR when targeted to cancer cells or proteins by conjugation with a cyclic RGD peptide, fibrinogen or antibodies. ZW800-1 outperforms the commercially available NIR fluorophores IRDye800-CW and Cy5.5 in vitro for immunocytometry, histopathology and immunoblotting and in vivo for image-guided surgery. In tumor model systems, a tumor-to-background ratio of 17.2 is achieved at 4 h after injection of ZW800-1 conjugated to cRGD compared to ratios of 5.1 with IRDye800-CW and 2.7 with Cy5.5. Our results suggest that introducing zwitterionic properties into targeted fluorophores may be a general strategy for improving the SBR in diagnostic and therapeutic applications.

Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians.

Abstract: Objectives: To assess whether overweight Asians, assessed on the basis of WHO criteria, are at greater mortality risk than overweight Caucasians, and to determine whether alternative cut-off points (BMI 5 23?0–24?9 kg/m 2 for overweight and BMI $ 25?0 kg/m 2 for obesity) suggested by the WHO Western Pacific Regional Office are appropriate. Design: The cohort was followed prospectively until the end of 2001. All-cause and CVD mortality risks of the overweight and obese group, relative to the reference group (BMI 5 18?5–24? 9o r 18?5–22? 9k g/m 2 ), were assessed using Cox regression analysis, adjusting for age, smoking and gender. Excess deaths were estimated with a method proposed by the US Centers for Disease Control and Prevention. Setting: National Health Interview Survey (NHIS 2001) and a middle-aged perspective cohort in Taiwan. Subjects: Subjects comprised 36 386 civil servants and school teachers, aged 40 years and older, who underwent a medical examination during 1989–1992. Results: In the WHO-defined overweight group, Asians showed a significant increase in all-cause mortality risk compared with Caucasians. Asians showed risks equivalent to Caucasians’ at lower BMI (around 5 units). Every unit of BMI increase, at 25?0 kg/m 2 or above, was associated with a 9 % increase in relative mortality risk from all causes. Applying a cut-off point of 25?0 kg/m 2 for obesity would result a prevalence of 27?1 %, while the traditional WHO cut-off point of 30?0 kg/m 2 yielded obesity prevalence of 4?1 %. Excess deaths due to obesity accounted for 8?6 % of all deaths and 21?1 % of CVD deaths, based on the alternative cut-offs. Conclusions: In this Asian population, significant mortality risks started at BMI $ 25?0 kg/m 2 , rather than at BMI $ 30?0 kg/m 2 . The study supports the use of BMI $ 25?0 kg/m 2 as a new cut-off point for obesity and BMI 5 23?0–24?9 kg/m 2 for overweight. The magnitude of obesity-attributable deaths has been hitherto under-appreciated among Asians.

Why primate models matter

Abstract: Research involving nonhuman primates (NHPs) has played a vital role in many of the medical and scientific advances of the past century. NHPs are used because of their similarity to humans in physiology, neuroanatomy, reproduction, development, cognition, and social complexity-yet it is these very similarities that make the use of NHPs in biomedical research a considered decision. As primate researchers, we feel an obligation and responsibility to present the facts concerning why primates are used in various areas of biomedical research. Recent decisions in the United States, including the phasing out of chimpanzees in research by the National Institutes of Health and the pending closure of the New England Primate Research Center, illustrate to us the critical importance of conveying why continued research with primates is needed. Here, we review key areas in biomedicine where primate models have been, and continue to be, essential for advancing fundamental knowledge in biomedical and biological research.