Receipt from James A. Eddy to John Wright

https://digitalcommons.salve.edu/ochre-court/1222/thumbnail.jp

Predictors of Dietary Supplement Use Among Adolescent Athletes

This study sought to predict the use of dietary supplements marketed to enhance athletic performance among 1,737 adolescent athletes. An anonymous, paper-and-pencil, self-report survey was administered to the participants. Grade level, participation in multiple sports, and scales representing attitudes, subjective norms, and intention were all significant predictors of current dietary supplement use. The results of this study allow for the development of more appropriate prevention and intervention strategies that can target specific groups of adolescent athletes. The authors recommend that attitudes of adolescent athletes be addressed in interventions and that salient others be included in program planning

Effect of GaN surface treatment on Al2O3/n-GaN MOS capacitors

Citation: Hossain, T., Wei, D., Edgar, J. H., Garces, N. Y., Nepal, N., Hite, J. K., . . . Meyer H.M, III. (2015). Effect of GaN surface treatment on Al2O3/n-GaN MOS capacitors. Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics, 33(6). doi:10.1116/1.4931793The surface preparation for depositing Al2O3 for fabricating Au/Ni/Al2O3/n-GaN (0001) metal oxide semiconductor (MOS) capacitors was optimized as a step toward realization of high performance GaN MOSFETs. The GaN surface treatments studied included cleaning with piranha (H2O2:H2SO4 = 1:5), (NH4)2S, and 30% HF etches. By several metrics, the MOS capacitor with the piranha-etched GaN had the best characteristics. It had the lowest capacitance–voltage hysteresis, the smoothest Al2O3 surface as determined by atomic force microscopy (0.2 nm surface roughness), the lowest carbon concentration (∼0.78%) at the Al2O3/n-GaN interface (from x-ray photoelectron spectroscopy), and the lowest oxide-trap charge (QT = 1.6 × 1011 cm−2eV−1). Its interface trap density (Dit = 3.7 × 1012 cm−2eV−1), as measured with photon-assisted capacitance– voltage method, was the lowest from conduction band-edge to midgap

Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major

Systems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of which were validated using published data with approximately 70% accuracy. Additionally, we generated hypothetical annotations to dozens of previously uncharacterized genes in the L. major genome and proposed a minimal medium for growth. We further demonstrated the utility of a network reconstruction with two proof-of-concept examples that yielded insight into robustness of the network in the presence of enzymatic inhibitors and delineation of promastigote/amastigote stage-specific metabolism. This reconstruction and the associated network analyses of L. major is the first of its kind for a protozoan. It can serve as a tool for clarifying discrepancies between data sources, generating hypotheses that can be experimentally validated and identifying ideal therapeutic targets

Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

<p>Abstract</p> <p>Background</p> <p>Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. <it>C. beijerinckii </it>is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating <it>C. beijerinckii </it>metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications.</p> <p>Results</p> <p>We present the first genome-scale metabolic model (<it>i</it>CM925) for <it>C. beijerinckii</it>, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate <it>i</it>CM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (<it>P </it>= 3.52 × 10^-9, Fisher's exact test). Inhibition of the hydrogenase reaction was found to have a strong effect on butanol formation--as experimentally observed.</p> <p>Conclusions</p> <p>Microbial production of butanol by <it>C. beijerinckii </it>offers a promising, sustainable, method for generation of this important chemical and potential biofuel. <it>i</it>CM925 is a predictive model that can accurately reproduce physiological behavior and provide insight into the underlying mechanisms of microbial butanol production. As such, the model will be instrumental in efforts to better understand, and metabolically engineer, this microorganism for improved butanol production.</p

Kinomic exploration of temozolomide and radiation resistance in Glioblastoma multiforme xenolines

Glioblastoma multiforme (GBM) represents the most common and deadly primary brain malignancy, particularly due to temozolomide (TMZ) and radiation (RT) resistance. To better understand resistance mechanisms, we examined global kinase activity (kinomic profiling) in both treatment sensitive and resistant human GBM patient-derived xenografts (PDX or “xenolines”)