Browsing by Author "Yang, C"

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Open Access
Abuse and dependence on prescription opioids in adults: a mixture categorical and dimensional approach to diagnostic classification.
(Psychological medicine, 2011-03) Wu, L-T; Woody, GE; Yang, C; Pan, J-J; Blazer, DG
For the emerging DSM-V, it has been recommended that dimensional and categorical methods be used simultaneously in diagnostic classification; however, little is known about this combined approach for abuse and dependence.Using data (n=37 708) from the 2007 National Survey on Drug Use and Health (NSDUH), DSM-IV criteria for prescription opioid abuse and dependence among non-prescribed opioid users (n=3037) were examined using factor analysis (FA), latent class analysis (LCA, categorical), item response theory (IRT, dimensional), and factor mixture (hybrid) approaches.A two-class factor mixture model (FMM) combining features of categorical latent classes and dimensional IRT estimates empirically fitted more parsimoniously to abuse and dependence criteria data than models from FA, LCA and IRT procedures respectively. This mixture model included a severely affected group (7%) with a comparatively moderate to high probability (0.32-0.88) of endorsing all abuse and dependence criteria items, and a less severely affected group (93%) with a low probability (0.003-0.16) of endorsing all criteria. The two empirically defined groups differed significantly in the pattern of non-prescribed opioid use, co-morbid major depression, and substance abuse treatment use.A factor mixture model integrating categorical and dimensional features of classification fits better to DSM-IV criteria for prescription opioid abuse and dependence in adults than a categorical or dimensional approach. Research is needed to examine the utility of this mixture classification for substance use disorders and treatment response.
Open Access
Association between attention-deficit/hyperactivity disorder symptoms and obesity and hypertension in early adulthood: a population-based study.
(Int J Obes (Lond), 2011-06) Fuemmeler, BF; Østbye, T; Yang, C; McClernon, FJ; Kollins, SH
OBJECTIVE: To examine the associations between attention-deficit/hyperactivity disorder (ADHD) symptoms, obesity and hypertension in young adults in a large population-based cohort. DESIGN, SETTING AND PARTICIPANTS: The study population consisted of 15,197 respondents from the National Longitudinal Study of Adolescent Health, a nationally representative sample of adolescents followed from 1995 to 2009 in the United States. Multinomial logistic and logistic models examined the odds of overweight, obesity and hypertension in adulthood in relation to retrospectively reported ADHD symptoms. Latent curve modeling was used to assess the association between symptoms and naturally occurring changes in body mass index (BMI) from adolescence to adulthood. RESULTS: Linear association was identified between the number of inattentive (IN) and hyperactive/impulsive (HI) symptoms and waist circumference, BMI, diastolic blood pressure and systolic blood pressure (all P-values for trend <0.05). Controlling for demographic variables, physical activity, alcohol use, smoking and depressive symptoms, those with three or more HI or IN symptoms had the highest odds of obesity (HI 3+, odds ratio (OR)=1.50, 95% confidence interval (CI) = 1.22-2.83; IN 3+, OR = 1.21, 95% CI = 1.02-1.44) compared with those with no HI or IN symptoms. HI symptoms at the 3+ level were significantly associated with a higher OR of hypertension (HI 3+, OR = 1.24, 95% CI = 1.01-1.51; HI continuous, OR = 1.04, 95% CI = 1.00-1.09), but associations were nonsignificant when models were adjusted for BMI. Latent growth modeling results indicated that compared with those reporting no HI or IN symptoms, those reporting 3 or more symptoms had higher initial levels of BMI during adolescence. Only HI symptoms were associated with change in BMI. CONCLUSION: Self-reported ADHD symptoms were associated with adult BMI and change in BMI from adolescence to adulthood, providing further evidence of a link between ADHD symptoms and obesity.
Open Access
Digital transformation and value chains: Introduction
(Global Networks) Butollo, F; Gereffi, G; Yang, C; Krzywdzinski, M
Open Access
ELSI: A Unified Software Interface for Kohn-Sham Electronic Structure Solvers
(2017-07-01) Yu, VWZ; Corsetti, F; García, A; Huhn, WP; Jacquelin, M; Jia, W; Lange, B; Lin, L; Lu, J; Mi, W; Seifitokaldani, A; Vázquez-Mayagoitia, Á; Yang, C; Yang, H; Blum, V
Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn-Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn-Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn-Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. Comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures.
Open Access
Massive clonal expansion of medulloblastoma-specific T cells during adoptive cellular therapy.
(Science advances, 2019-11-27) Flores, C; Wildes, T; Dean, B DiVita; Moore, G; Drake, J; Abraham, R; Gil, J; Yegorov, O; Yang, C; Dean, J; Moneypenny, C; Shin, D; Pham, C; Krauser, J; King, J; Grant, G; Driscoll, T; Kurtzberg, J; McLendon, R; Gururangan, S; Mitchell, D
In both human and murine systems, we have developed an adoptive cellular therapy platform against medulloblastoma and glioblastoma that uses dendritic cells pulsed with a tumor RNA transcriptome to expand polyclonal tumor-reactive T cells against a plurality of antigens within heterogeneous brain tumors. We demonstrate that peripheral TCR Vβ repertoire analysis after adoptive cellular therapy reveals that effective response to adoptive cellular therapy is concordant with massive in vivo expansion and persistence of tumor-specific T cell clones within the peripheral blood. In preclinical models of medulloblastoma and glioblastoma, and in a patient with relapsed medulloblastoma receiving adoptive cellular therapy, an early and massive expansion of tumor-reactive lymphocytes, coupled with prolonged persistence in the peripheral blood, is observed during effective therapeutic response to immunotherapy treatment.
Open Access
Mechanosensitive neurons on the internal reproductive tract contribute to egg-laying-induced acetic acid attraction in Drosophila.
(Cell Rep, 2014-10-23) Gou, B; Liu, Y; Guntur, A; Stern, U; Yang, C
Selecting a suitable site to deposit their eggs is an important reproductive need of Drosophila females. Although their choosiness toward egg-laying sites is well documented, the specific neural mechanism that activates females' search for attractive egg-laying sites is not known. Here, we show that distention and contraction of females' internal reproductive tract triggered by egg delivery through the tract plays a critical role in activating such search. We found that females start to exhibit acetic acid (AA) attraction prior to depositing each egg but no attraction when they are not laying eggs. Artificially distending the reproductive tract triggers AA attraction in non-egg-laying females, whereas silencing the mechanosensitive neurons we identified that can sense the contractile status of the tract eliminates such attraction. Our work uncovers the circuit basis of an important reproductive need of Drosophila females and provides a simple model for dissecting the neural mechanism that underlies a reproductive need-induced behavioral modification.