Tuesday, July 18, 2017

Neuronal metal manganese effect on arginase activity implicated in Huntington's disease

Assistant Professor of Neuroscience Gunnar Kwakye is one of 22 collaborators in this research, from institutions in England, Illinois, Italy, Michigan, New York, Ohio, Pennsylvania, Tennessee and Texas.

Bichell TJV, Wegrzynowicz M, Tipps KG, Bradley EM, Uhouse MA, Bryan M, Horning K, Fisher N, Dudek K, Halbesma T, et al. 2017.

Reduced bioavailable manganese causes striatal urea cycle pathology in Huntington's disease mouse model. Biochimica Et Biophysica Acta-Molecular Basis of Disease 1863(6):1596-604

Huntington's disease (HD) is caused by a mutation in the huntingtin gene (HIT), resulting in profound striatal neurodegeneration through an unknown mechanism. Perturbations in the urea cycle have been reported in HD models and in HD patient blood and brain. In neurons, arginase is a central urea cycle enzyme, and the metal manganese (Mn) is an essential cofactor. Deficient biological responses to Mn, and reduced Mn accumulation have been observed in HD striatal mouse and cell models. Here we report in vivo and ex vivo evidence of a urea cycle metabolic phenotype in a prodromal HD mouse model. Further, either in vivo or in vitro Mn supplementation reverses the urea-cycle pathology by restoring arginase activity. We show that Arginase 2 (ARG2) is the arginase enzyme present in these mouse brain models, with ARG2 protein levels directly increased by Mn exposure. ARG2 protein is not Teduced in the prodromal stage, though enzyme activity is reduced, indicating that altered Mn bioavailability as a cofactor leads to the deficient enzymatic activity. These data support a hypothesis that mutant HIT leads to a selective deficiency of neuronal Mn at an early disease stage, contributing to HD striatal urea-cycle pathophysiology through an effect on arginase activity. (C) 2017 The Author(s). Published by Elsevier B.V.

Open Access at Sciencedirect

Thursday, July 13, 2017

"Web app for population viability and harvesting analyses." Co-authored by Rich Salter

New publication from Professor Emeritus Richard Salter:
Official Journal of the Resource Modeling Association

Getz WM, Muellerklein OC, Salter RM, Carlson CJ, Lyons AJ, Seidel DP. 2017. A web app for population viability and harvesting analyses. Natural Resource Modeling 30(2):e12120

Population viability analysis (PVA) is used to assess the probability that a biological population will persist for a specified period of time. Such models are typically cast as Markov processes that may include age, stage, sex and metapopulation structures, density-dependence and ecological interaction processes. They may also include harvesting, stocking, and thresholds that trigger interventions. Here we present a PVA web app that includes extensible user-selected options. Specifically, this PVA web app allows for the specification of one to ten age classes, one or two sexes, single population or metapopulation configurations with 2 or 3 subpopulations, as well as density-dependent settings for inducing region-specific carrying capacities. Movement among subpopulations can be influenced by age, metapopulation connectivity, and attractivity of regions based on the relative fitness of the youngest age classes in each region. Simulations can be carried out deterministically or stochastically, with a user-specified combination of demographic and environmental processes. This PVA web app is freely available at http://www.numerusinc.com/webapps/pva for running directly on any browser and device. It is easily modified by users familiar with the NovaModeler Software Platform.

Subscriber access on Wiley Online Library.

Friday, July 07, 2017

Oxidative stress and neurotoxicity in Huntington's disease: publication by G. Kwakye

About NeuroToxicology
New publication from Assistant Professor of Neuroscience Gunnar Kwakye and students in the Kwakye lab:

"Acute exposure to chlorpyrifos caused NADPH oxidase mediated oxidative stress and neurotoxicity in a striatal cell model of Huntington's disease."
Gifty A. Dominah, OC'15.; Rachel A. McMinimy, OC'17; Sallay Kallon, OC'17; Gunnar F. Kwakye.
NeuroToxicology, vol. 60, pp 54-69;  MAY 2017

Subscriber Access on ScienceDirect
Abstract and indexing on PubMed
About NeuroToxicology

Wednesday, June 07, 2017

Plant systematics & evolution of Potentilleae and Sibbalidia: new publication from Mike Moore

A new publication by Michael Moore, Associate Professor of Botany, and collaborators in China.

Feng T, Moore, Michael J, Yan M, Sun Y, Zhang H, Meng A, Li X, Jian S, Li J, Wang H. 2017. Phylogenetic study of the tribe Potentilleae (Rosaceae), with further insight into the disintegration of Sibbaldia. Journal of Systematics and Evolution 55(3):177-91.

Sibbaldia procumbens (5066467208)
Potentilleae, one of 10 tribes of the Rosaceae, are mainly distributed in alpine regions of the Northern Hemisphere. The taxonomy of Potentilleae has been challenging due to extensive hybridization, polyploidization, and/or apomixis characterizing several genera of Potentilleae, such as Alchemilla, Argentina, and Potentilla. To help clarify relationships within Potentilleae, a phylogenetic analysis of the tribe with an emphasis on the polyphyletic genus Sibbaldia was carried out using nuclear ribosomal internal and external transcribed spacer regions and the plastid trnL-F and trnS-G spacer regions. In agreement with previous phylogenetic analyses, three major clades were identified in the present study: the subtribe Fragariinae, the genera Argentina, and Potentilla. The 15 species of Sibbaldia were recovered in five distinct clades: three in subtribe Fragariinae, one in Argentina, and the last in Potentilla. The recently established genus Chamaecallis, comprising a single species formerly treated in Sibbaldia that has intermediate floral character states with respect to Fragariinae and Potentilla, was recovered as sister to Drymocallis. Morphological character state reconstruction indicated that a reduction in the number of stamens (10) is a derived character state that has arisen multiple times in Potentilleae. Molecular dating analyses agreed with previously published estimates and suggested that crown group Potentilleae arose in the Middle to Late Eocene, with most generic-level divergences occurring in the Oligocene and Miocene.  (from the publisher's website)

Thursday, May 25, 2017

Environmental Dashboard and Ground-state rotational constants examined: two very different areas of study by Oberlin researchers

Recent publications from faculty and staff (Oberlin affiliated authors are in bold font):


Clark, Shane; Petersen, John E; Frantz, Cindy M; Roose, Deborah; Ginn, Joel; Daneri DR. 2017. Teaching systems thinking to 4th and 5th graders using environmental dashboard display technology. Plos One 12(4):e0176322
Tackling complex environmental challenges requires the capacity to understand how relationships and interactions between parts result in dynamic behavior of whole systems. There has been convincing research that these "systems thinking" skills can be learned. However, there is little research on methods for teaching these skills to children or assessing their impact. The Environmental Dashboard is a technology that uses "sociotechnical" feedback-information feedback designed to affect thought and behavior. Environmental Dashboard (ED) combines real-time information on community resource use with images and words that reflect pro-environmental actions of community members. Prior research indicates that ED supports the development of systems thinking in adults. To assess its impact on children, the technology was installed in a primary school and children were passively exposed to ED displays. This resulted in no measurable impact on systems thinking skills. The next stage of this research examined the impact of actively integrating ED into lessons on electricity in 4th and 5th grade. This active integration enhanced both content-related systems thinking skills and content retention.

Demaison J, Craig Norman C, Gurusinghe R, Tubergen MJ, Rudolph HD, Coudert LH, Szalay PG, Csaszar AG. 2017. Fourier transform microwave spectrum of propene-3-d(1) (CH2=CHCH2D), quadrupole coupling constants of deuterium, and a semiexperimental equilibrium structure of propene. Journal of Physical Chemistry A 121(16):3155-66
The ground-state rotational spectrum of propene-3-d(1), CH2=CHCH2D, was measured by Fourier transform microwave spectroscopy. Transitions were assigned for the two conformers, one with the D atom in the symmetry plane (S) and the other with the D atom out of the plane (A). The energy difference between the two conformers was calculated to be 6.5 cm(-1), the S conformer having lower energy. The quadrupole hyperfine structure due to deuterium was resolved and analyzed for both conformers. The experimental quadrupole coupling and the centrifugal distortion constants compared favorably to their ab initio counterparts. Ground-state rotational constants, for the S conformer are 40582.157(9), 9067.024(1), and 7766.0165(12) MHz. Ground-state rotational constants for the A Conformer are 43403.75(3), 8658.961(2), and 7718.247(2) MHz. For the A conformer, a small tunneling splitting (19 MHz) due to internal rotation was observed and analyzed. Using the new rotational constants of this work as well as those previously determined for the C-13 species and for some deuterium-substituted species from the literature, a new semiexperimental equilibrium structure was determined and its high accuracy was confirmed. The difficulty in obtaining accurate coordinates for the out-of-plane hydrogen atom is discussed.

Tuesday, April 25, 2017

Deep learning discussed on the TED Radio Hour

Deep Learning / Ian Goodfellow, Joshua Bengio and
Aaron Courville.  MIT Press, 2016.
The TED Radio Hour on Friday, April 21, 2017 was titled The Digital Industrial Revolution, followed by the question, "As machine learning surpasses human intelligence, where does that leave us?"

During the session, TED speakers explored "ideas about the exciting — and terrifying — future of human-robot collaboration."

One of the speakers referenced deep learning, which immediately brought to mind this book on our new book shelf.  It defines deep learning as a "form of machine learning that enables computers to learn from experience and understand the work in terms of a hierarchy of concepts."  Seemingly benign, and the book's cover is soothing at first glance, with its profusion of blossoms.  On close examination, the cover art work has multiple layers of meaning, and it is this multiplicity of issues surrounding deep learning and neural networks that the TED Radio Hour speakers address.  It makes for fascinating listening!  The four talks are linked here:

Monday, April 17, 2017

Hormones at the hippocampus, caffeine cocrystals, lateral roots, and transcirptome: new publications

Four recent publications from Oberlin College science faculty (names indicated in bold). Student or alumni co-authors in the list below include Veronica Burnham, Christopher Sunday, Abigail Laman-Magarg, and Nicolas Vigilante.

As indexed in Web of Science
Burnham, Veronica, Christopher Sundby, Abigail Laman-Maharg, and Janice Thornton. 2017. Luteinizing hormone acts at the hippocampus to dampen spatial memory. Hormones and Behavior 89, : 55-63. Download: OhioLINK Electronic Journal Center

Laskowski, Marta and Kirsten H. ten Tusscher. 2017. Periodic lateral root priming: What makes it tick? Plant Cell 29, no. 3: 432-444. Download, open access, at Plant Cell

Vigilante, Nicolas J. and Manish A. Mehta. 2017. A C-13 solid-state NMR investigation of four cocrystals of caffeine and theophylline. Acta Crystallographica Section C-Structural Chemistry 73, : 234-243. Read the abstract online at publisher's site

Yang, Ya, Michael J. Moore, Samuel F. Brockington, Alfonso Timoneda, Tao Feng, Hannah E. Marx, Joseph F. Walker, and Stephen A. Smith. 2017. An efficient field and laboratory workflow for plant phylotranscriptomic projects. Applications in Plant Sciences 5, no. 3: 1600128. Download: BioOne