Publications by Colleges and Departments (MSU - Bozeman)

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    An Alternative to the Carnegie Classifications: Identifying Similar Institutions with Structural Equation Models and Clustering
    (2019-01) Harmon, Paul; McKnight, Sarah; Hildreth, Laura; Godwin, Ian; Greenwood, Mark C.
    The Carnegie Classification of Institutions of Higher Education is a commonly used framework for institutional classification that classifies doctoral-granting schools into three groups based on research productivity. Despite its wide use, the Carnegie methodology involves several shortcomings, including a lack of thorough documentation, subjectively placed thresholds between institutions, and a methodology that is not completely reproducible. We describe the methodology of the 2015 and 2018 updates to the classification and propose an alternative method of classification using the same data that relies on structural equation modeling (SEM) of latent factors rather than principal component-based indices of productivity. In contrast to the Carnegie methodology, we use SEM to obtain a single factor score for each school based on latent metrics of research productivity. Classifications are then made using a univariate model-based clustering algorithm as opposed to subjective thresholding, as is done in the Carnegie methodology. Finally, we present a Shiny web application that demonstrates sensitivity of both the Carnegie Classification and SEM-based classification of a selected university and generates a table of peer institutions in line with the stated goals of the Carnegie Classification.
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    Characterization of synovial fluid metabolomic phenotypes of cartilage morphological changes associated with osteoarthritis
    (2019-08) Carlson, Alyssa K.; Rawle, Rachel A.; Wallace, Cameron W.; Brooks, Ellen G.; Adams, Erik; Greenwood, Mark C.; Olmer, Merissa; Lotz, Martin K.; Bothner, Brian; June, Ronald K.
    "Objective Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolomic phenotypes from human synovial fluid. Design: Post mortem synovial fluids (n = 75) were analyzed by high performance-liquid chromatography mass spectrometry (LC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression. Results: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Synovial fluid metabolomic phenotypes exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid. Conclusion: These results revealed distinct metabolic phenotypes in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers, and can move toward developing personalized interventions for subgroups of OA patients.
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    NeurEx: digitalized neurological examination offers a novel high-resolution disability scale
    (2018-10) Kosa, Peter; Barbour, Christopher; Wichman, Alison; Sandford, Mary; Greenwood, Mark C.; Bielekova, Bibiana
    Objective To develop a sensitive neurological disability scale for broad utilization in clinical practice. Methods We employed advances of mobile computing to develop an iPad-based App for convenient documentation of the neurological examination into a secure, cloud-linked database. We included features present in four traditional neuroimmunological disability scales and codified their automatic computation. By combining spatial distribution of the neurological deficit with quantitative or semiquantitative rating of its severity we developed a new summary score (called NeurEx; ranging from 0 to 1349 with minimal measurable change of 0.25) and compared its performance with clinician- and App-computed traditional clinical scales. Results In the cross-sectional comparison of 906 neurological examinations, the variance between App-computed and clinician-scored disability scales was comparable to the variance between rating of the identical neurological examination by multiple sclerosis (MS)-trained clinicians. By eliminating rating ambiguity, App-computed scales achieved greater accuracy in measuring disability progression over time (n = 191 patients studied over 880.6 patient-years). The NeurEx score had no apparent ceiling effect and more than 200-fold higher sensitivity for detecting a measurable yearly disability progression (i.e., median progression slope of 8.13 relative to minimum detectable change of 0.25) than Expanded Disability Status Scale (EDSS) with a median yearly progression slope of 0.071 that is lower than the minimal measurable change on EDSS of 0.5. Interpretation NeurEx can be used as a highly sensitive outcome measure in neuroimmunology. The App can be easily modified for use in other areas of neurology and it can bridge private practice practitioners to academic centers in multicenter research studies.
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    Statistical methods for detecting groups of patterns in daily step count activity profiles
    (2016) Meyer, Elijah S.; Tran, Tan; Greenwood, Mark C.
    The growth of wearable technology is apparent. A total of 2.7 million wearable bands were shipped worldwide in the first quarter of 2014 (Sullivan, 2014). Of this number, Fitbit, a company focused on developing and manufacturing compact, wireless wearable technology devices accounted for half of the shipments alone. A Fitbit device can track steps, distance, calories burned, floors climbed, active minutes, and sleep patterns and provides regular users with daily totals or totals over 15-minute intervals throughout the day. The motivation of staying fit coupled with the convenience of collecting the data through a simple wrist band is fueling this industry. The utility of activity tracking for improved health outcomes is left for other researchers. Here we focus on whether the focus on daily summaries is making dissimilar days look similar, and whether we can group days in such a way that balances total activity as well as timing of that activity.
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    Prokaryotes in the WAIS Divide ice core reflect source and transport changes between Last Glacial Maximum and the early Holocene
    (2018-05) Santibanez, Pamela A.; Maselli, Olivia J.; Greenwood, Mark C.; Grieman, Mackenzie M.; Saltzman, Eric S.; McConnell, Joseph R.; Priscu, John C.
    We present the first long-term, highly resolved prokaryotic cell concentration record obtained from a polar ice core. This record, obtained from the West Antarctic Ice Sheet (WAIS) Divide (WD) ice core, spanned from the Last Glacial Maximum (LGM) to the early Holocene (EH) and showed distinct fluctuations in prokaryotic cell concentration coincident with major climatic states. The time series also revealed a ~1,500-year periodicity with greater amplitude during the Last Deglaciation (LDG). Higher prokaryotic cell concentration and lower variability occurred during the LGM and EH than during the LDG. A seven-fold decrease in prokaryotic cell concentration coincided with the LGM/LDG transition and the global 19 ka meltwater pulse. Statistical models revealed significant relationships between the prokaryotic cell record and tracers of both marine (sea-salt sodium [ssNa]) and burning emissions (black carbon [BC]). Collectively, these models, together with visual observations and methanosulfidic acid (MSA) measurements, indicated that the temporal variability in concentration of airborne prokaryotic cells reflected changes in marine/sea-ice regional environments of the WAIS. Our data revealed that variations in source and transport were the most likely processes producing the significant temporal variations in WD prokaryotic cell concentrations. This record provided strong evidence that airborne prokaryotic cell deposition differed during the LGM, LDG and EH, and that these changes in cell densities could be explained by different environmental conditions during each of these climatic periods. Our observations provide the first ice core time-series evidence for a prokaryotic response to long-term climatic and environmental processes.
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    Meta-analysis of the Age-Dependent Efficacy of Multiple Sclerosis Treatments
    (2017-11) Weideman, Ann Marie; Tapia-Maltos, Marco Aurelio; Johnson, Kory; Greenwood, Mark C.; Bielekova, Bibiana
    Objective: To perform a meta-analysis of randomized, blinded, multiple sclerosis (MS) clinical trials, to test the hypothesis that efficacy of immunomodulatory disease-modifying therapies (DMTs) on MS disability progression is strongly dependent on age. Methods: We performed a literature search with pre-defined criteria and extracted relevant features from 38 clinical trials that assessed efficacy of DMTs on disability progression. We fit a linear regression, weighted for trial sample size, and duration, to examine the hypothesis that age has a defining effect on the therapeutic efficacy of immunomodulatory DMTs. Results: More than 28,000 MS subjects participating in trials of 13 categories of immunomodulatory drugs are included in the meta-analysis. The efficacy of immunomodulatory DMTs on MS disability strongly decreased with advancing age (R-2= 0.6757, p = 6.39e-09). Inclusion of baseline EDSS did not significantly improve the model. The regression predicts zero efficacy beyond approximately age 53 years. The comparative efficacy rank derived from the regression residuals differentiates high-and low-efficacy drugs. High-efficacy drugs outperform low-efficacy drugs in inhibiting MS disability only for patients younger than 40.5 years. Conclusion: The meta-analysis supports the notion that progressive MS is simply a later stage of the MS disease process and that age is an essential modifier of a drug efficacy. Higher efficacy treatments exert their benefit over lower efficacy treatments only during early stages of MS, and, after age 53, the model suggests that there is no predicted benefit to receiving immunomodulatory DMTs for the average MS patient.
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    New Multiple Sclerosis Disease Severity Scale Predicts Future Accumulation of Disability
    (2017-11) Weideman, Ann Marie; Barbour, Christopher; Tapia-Maltos, Marco Aurelio; Tran, Tan; Jackson, Kayla; Kosa, Peter; Komori, Mika; Wichman, Alison; Johnson, Kory; Greenwood, Mark C.; Bielekova, Bibiana
    The search for the genetic foundation of multiple sclerosis (MS) severity remains elusive. It is, in fact, controversial whether MS severity is a stable feature that predicts future disability progression. If MS severity is not stable, it is unlikely that genotype decisively determines disability progression. An alternative explanation tested here is that the apparent instability of MS severity is caused by inaccuracies of its current measurement. We applied statistical learning techniques to a 902 patient-years longitudinal cohort of MS patients, divided into training (n = 133) and validation (n = 68) sub-cohorts, to test four hypotheses: (1) there is intra-individual stability in the rate of accumulation of MS-related disability, which is also influenced by extrinsic factors. (2) Previous results from observational studies are negatively affected by the insensitive nature of the Expanded Disability Status Scale (EDSS). The EDSS-based MS Severity Score (MSSS) is further disadvantaged by the inability to reliably measure MS onset and, consequently, disease duration (DD). (3) Replacing EDSS with a sensitive scale, i.e., Combinatorial Weight-Adjusted Disability Score (CombiWISE), and substituting age for DD will significantly improve predictions of future accumulation of disability. (4) Adjusting measured disability for the efficacy of administered therapies and other relevant external features will further strengthen predictions of future MS course. The result is a MS disease severity scale (MS-DSS) derived by conceptual advancements of MSSS and a statistical learning method called gradient boosting machines (GBM). MS-DSS greatly outperforms MSSS and the recently developed Age Related MS Severity Score in predicting future disability progression. In an independent validation cohort, MS-DSS measured at the first clinic visit correlated significantly with subsequent therapy-adjusted progression slopes (r = 0.5448, p = 1.56e-06) measured by CombiWISE. To facilitate widespread use of MS-DSS, we developed a free, interactive web application that calculates all aspects of MS-DSS and its contributing scales from user-provided raw data. MS-DSS represents a much-needed tool for genotype-phenotype correlations, for identifying biological processes that underlie MS progression, and for aiding therapeutic decisions.
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    Bioenergy and Breast Cancer: A report on tumor growth and metastasis
    (2016) Running, Alice; Greenwood, Mark C.; Hildreth, Laura; Schmidt, Jade
    As many as 80% of the 296,000 women and 2,240 men diagnosed with breast cancer in the United States will seek out complementary and alternative medicine (CAM) treatments. One such therapy is Healing Touch (HT), recognized by the National Center for Complementary and Integrative Health (NCCIH) as a treatment modality. Using a multiple experimental groups design, fifty-six six- to eight-week-old Balb/c mice were injected with 4T1 breast cancer tumor cells and randomly divided into intervention and positive control groups. Five days after tumor cell injection, mice in the intervention groups received HT either daily or every other day for 10 minutes by one HT practitioner. At 15 days after tumor cell injection, tumor size was measured, and metastasis was evaluated by a medical pathologist after necropsy. Tumor size did not differ significantly among the groups (F(3,52) = 0.75, p value = 0.53). The presence of metastasis did not differ across groups (chi-square(3) = 3.902, p = 0.272) or when compared within an organ (liver: chi-square(3) = 2.507, p = 0.474; lungs: chi-square(3) = 3.804, ; spleen: chi-square(3) = 0.595, p = 0.898). However, these results did indicate a moderate, though insignificant, positive impact of HT and highlight the need for continued research into dose, length of treatment, and measurable outcomes (tumor size, metastasis) to provide evidence to suggest application for nursing care.
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    When a habitat freezes solid: Microorganisms over-winter within the ice column of a coastal Antarctic lake
    (2011-03) Foreman, Christine M.; Dieser, Markus; Greenwood, Mark C.; Cory, R. M.; Laybourn-Parry, Johanna; Lisle, John T.; Jaros, C.; Miller, P. L.; Chin, Yu-Ping; McKnight, Diane M.
    A major impediment to understanding the biology of microorganisms inhabiting Antarctic environments is the logistical constraint of conducting field work primarily during the summer season. However, organisms that persist throughout the year encounter severe environmental changes between seasons. In an attempt to bridge this gap, we collected ice core samples from Pony Lake in early November 2004 when the lake was frozen solid to its base, providing an archive for the biological and chemical processes that occurred during winter freezeup. The ice contained bacteria and virus-like particles, while flagellated algae and ciliates over-wintered in the form of inactive cysts and spores. Both bacteria and algae were metabolically active in the ice core melt water. Bacterial production ranged from 1.8 to 37.9 μg C L−1 day−1. Upon encountering favorable growth conditions in the melt water, primary production ranged from 51 to 931 μg C L−1 day−1. Because of the strong H2S odor and the presence of closely related anaerobic organisms assigned to Pony Lake bacterial 16S rRNA gene clones, we hypothesize that the microbial assemblage was strongly affected by oxygen gradients, which ultimately restricted the majority of phylotypes to distinct strata within the ice column. This study provides evidence that the microbial community over-winters in the ice column of Pony Lake and returns to a highly active metabolic state when spring melt is initiated.
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    Physicochemical and biological dynamics in a coastal Antarctic lake as it transitions from frozen to open water
    (2013-03) Dieser, Markus; Foreman, Christine M.; Jaros, C.; Lisle, John T.; Greenwood, Mark C.; Laybourn-Parry, Johanna; Miller, P. L.; Chin, Yu-Ping; McKnight, Diane M.
    Pony Lake, at Cape Royds, Antarctica, is a shallow, eutrophic, coastal lake that freezes solid in the winter. Changes in Pony Lake's physicochemical parameters and microbial community were studied during the transition from ice to open water. Due to rising water temperatures, the progressive melt of the ice column and the gradual mixing of basal brines into the remaining water column, Pony Lake evolved physically and chemically over the course of the summer, thereby affecting the microbial community composition. Temperature, pH, conductivity, nutrients and major ion concentrations reached their maximum in January. Pony Lake was colonized by bacteria, viruses, phytoflagellates, ciliates, and a small number of rotifers. Primary and bacterial production were highest in mid-December (2.66 mg C 1-1 d-1 and 30.5 µg C 1-1 d-1, respectively). A 16S rRNA gene analysis of the bacterioplankton revealed 34 unique sequences dominated by members of the ß- and y-proteobacteria lineages. Cluster analyses on denaturing gradient gel electrophoresis (DGGE) banding patterns and community structure indicated a shift in the dominant members of the microbial community during the transition from winter ice, to early, and late summer lakewater. Our data demonstrate that temporal changes in physicochemical parameters during the summer months determine community dynamics and mediate changes in microbial species composition.
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