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Alternative Perspectives on Leadership: Integrating Transformational Leadership with Confucian Philosophy  [PDF]
Glenn Stone, Cynthia Conley, Yibing Luo
Open Journal of Leadership (OJL) , 2014, DOI: 10.4236/ojl.2014.32004
Abstract:

This paper presents a model for integrating elements of Transformational Leadership with Confucian Philosophy. The various concepts of each perspective are discussed with special emphasis on efforts to note similarities in the two perspectives. Examples of how leaders could apply the integration of these two perspectives are presented for those working in the social service field.

Variable Penalty Dynamic Time Warping Code for Aligning Mass Spectrometry Chromatograms in R
David Clifford,Glenn Stone
Journal of Statistical Software , 2012,
Abstract: Alignment of mass spectrometry (MS) chromatograms is sometimes required prior to sample comparison and data analysis. Without alignment, direct comparison of chromatograms would lead to inaccurate results. We demonstrate a new method for computing a high quality alignment of full length MS chromatograms using variable penalty dynamic time warping. This method aligns signals using local linear shifts without excessive warping that can alter the shape (and area) of chromatogram peaks. The software is available as the R package VPdtw on the Comprehensive R Archive Network and we highlight how one can use this package here. =
Parameter estimation for robust HMM analysis of ChIP-chip data
Peter Humburg, David Bulger, Glenn Stone
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-343
Abstract: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure.We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.High density oligonucleotide tiling arrays allow the investigation of transcriptional activity, protein-DNA interactions and chromatin structure across a whole genome. Tiling arrays have been used in a wide range of studies, including investigation of transcription factor activity [1] and of histone modifications in animals [2] and plants [3], as well as DNA methylation [4]. Analyses of these data are usually based either on a sliding window [1,5], or on hidden Markov models (HMMs) [6-8]. Other approaches have been suggested, e.g., by Huber et al. [9] and Reiss et al. [10], but are less common.Parameter estimates for sliding window approaches as well as hidden Markov models are typically ad hoc. Although there are some notable exceptions in gene expression studies [8,11], no established procedures exist to obtain good parameter estimates from tiling array data, especially in the context of chromatin immunoprecipitation (ChIP-chip) experiments. Attempts have been made to obtain parameter estimates by integrating genome annotations into the analysis [12]. While this may provide good results when investigating transcriptional activity in well studied organisms, it is limited by the quality of available annotations. For ChIP-chip studies the required annotation data is unavailable. A method for the localisat
ChIPseqR: analysis of ChIP-seq experiments
Peter Humburg, Chris A Helliwell, David Bulger, Glenn Stone
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-39
Abstract: Here we present ChIPseqR, an algorithm for the analysis of nucleosome positioning and histone modification ChIP-seq experiments. The performance of this novel method is studied on short read sequencing data of Arabidopsis thaliana mononucleosomes as well as on simulated data.ChIPseqR is shown to improve sensitivity and spatial resolution over existing methods while maintaining high specificity. Further analysis of predicted nucleosomes reveals characteristic patterns in nucleosome sequences and placement.The recent advent of high-throughput sequencing technologies has enabled genome-wide studies of DNA-binding proteins at high resolution. In such studies the protein of interest is isolated together with a fragment of bound DNA, which is then separated from the protein and sequenced. This approach has been used to investigate several different proteins including the positioning of nucleosomes [1-4]. For this type of experiment DNA is typically digested with micrococcal nuclease (MNase) before isolating nucleosome-sized DNA fragments (~150 bp) that are then sequenced. This is the application considered here. Each nucleosome is expected to produce several sequence reads of approximately 35 - 100 bp from both strands. This leads to peaks in read density on either side of the nucleosome with the extent of the peaks and the distance between the two peaks determined by the length of DNA fragments and binding site. Since the DNA fragments produced by an MNase digest of nucleosomes are selected to be similar in length to the actual binding site the resulting peaks in read counts are expected to be relatively narrow and peaks on forward and reverse strand should be separated by a region that corresponds approximately to the nucleosome bound DNA. This region is expected to be depleted of sequence reads (Figure 1). However, the distance between adjacent nucleosomes is usually short (~30 - 60 bp) and this may lead to overlap between peaks. When analysed at low resolution this ca
Visualisation in imaging mass spectrometry using the minimum noise fraction transform
Glenn Stone, David Clifford, Johan OR Gustafsson, Shaun R McColl, Peter Hoffmann
BMC Research Notes , 2012, DOI: 10.1186/1756-0500-5-419
Abstract: The MNF transform is able to extract spatially coherent information from IMS data. The MNF transform is implemented through an R-package which is available together with example data from http://sta?.scm.uws.edu.au/~glenn/?#Software webcite.In our example, the MNF transform was able to find additional images of interest. The extracted information forms a useful basis for subsequent analyses.Imaging Mass Spectrometry (IMS) provides a means to measure the spatial distribution of drug metabolite, lipid, peptide and protein features on the surface of a sectioned tissue sample (see [1] and references therein). Typically, IMS methods utilise freshly frozen sections of tissue mounted onto conductive slides. These are coated with matrix followed by MALDI-ToF/ToF spectra acquisition at anywhere from hundreds to thousands of positions across a tissue, the spatial locations of which are annotated. For example, a section of coronal murine midbrain can generate more than ~2000 spectra. Data acquisition at 0.1 GS/s over an m/z range 1000-26000 yields individual mass spectra with more than 11,000 plotted points. The resulting data set is enormous and thus difficult to process, visualise and analyse effectively.The data can be thought of in two ways, firstly a set of mass spectra acquired at a spatial array of spots, and secondly as a stack of ion intensity maps, each map being akin to a low resolution image. Software such as Biomap and flexImaging (Bruker Daltonics) view IMS data as ion intensity maps and include features such as data normalisation and noise spectra exclusion (see Figure 1). However the choice of ion intensity maps to view is largely user driven and images are noisy. Further data analysis using external software packages is possible, for example, (ClinProTools for principal component analysis (PCA), hierarchical clustering (HC) of spectra, or spectral model generation [2-5]. Other analysis techniques used on IMS data include kriging of ion intensity maps [6] and s
From transcriptome to biological function: environmental stress in an ectothermic vertebrate, the coral reef fish Pomacentrus moluccensis
Karin S Kassahn, Ross H Crozier, Alister C Ward, Glenn Stone, M Julian Caley
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-358
Abstract: We identified a series of gene functions that were involved in all stress responses examined here, suggesting some common effects of stress on biological function. These common responses were achieved by the regulation of largely independent sets of genes; the responses of individual genes varied greatly across different stress types. In response to heat exposure over five days, a total of 324 gene loci were differentially expressed. Many heat-responsive genes had functions associated with protein turnover, metabolism, and the response to oxidative stress. We were also able to identify groups of co-regulated genes, the genes within which shared similar functions.This is the first environmental genomic study to measure gene regulation in response to different environmental stressors in a natural population of a warm-adapted ectothermic vertebrate. We have shown that different types of environmental stress induce expression changes in genes with similar gene functions, but that the responses of individual genes vary between stress types. The functions of heat-responsive genes suggest that prolonged heat exposure leads to oxidative stress and protein damage, a challenge of the immune system, and the re-allocation of energy sources. This study hence offers insight into the effects of environmental stress on biological function and sheds light on the expected sensitivity of coral reef fishes to elevated temperatures in the future.Microarray technology provides a powerful tool for investigating gene regulation and its significance for biological function. However, our understanding of such relationships during environmental stress remains fragmentary, especially in vertebrates. In particular, the commonality, or otherwise, of the responses of vertebrates to different environmental stresses remain poorly understood. Recently, some understanding of responses to individual stresses, in particular those related to thermal stress in teleost fishes, has been gained. In these sp
Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data
Lauren M. Bragg ,Glenn Stone,Margaret K. Butler,Philip Hugenholtz,Gene W. Tyson
PLOS Computational Biology , 2013, DOI: 10.1371/journal.pcbi.1003031
Abstract: The Ion Torrent Personal Genome Machine (PGM) is a new sequencing platform that substantially differs from other sequencing technologies by measuring pH rather than light to detect polymerisation events. Using re-sequencing datasets, we comprehensively characterise the biases and errors introduced by the PGM at both the base and flow level, across a combination of factors, including chip density, sequencing kit, template species and machine. We found two distinct insertion/deletion (indel) error types that accounted for the majority of errors introduced by the PGM. The main error source was inaccurate flow-calls, which introduced indels at a raw rate of 2.84% (1.38% after quality clipping) using the OneTouch 200 bp kit. Inaccurate flow-calls typically resulted in over-called short-homopolymers and under-called long-homopolymers. Flow-call accuracy decreased with consecutive flow cycles, but we also found significant periodic fluctuations in the flow error-rate, corresponding to specific positions within the flow-cycle pattern. Another less common PGM error, high frequency indel (HFI) errors, are indels that occur at very high frequency in the reads relative to a given base position in the reference genome, but in the majority of instances were not replicated consistently across separate runs. HFI errors occur approximately once every thousand bases in the reference, and correspond to 0.06% of bases in reads. Currently, the PGM does not achieve the accuracy of competing light-based technologies. However, flow-call inaccuracy is systematic and the statistical models of flow-values developed here will enable PGM-specific bioinformatics approaches to be developed, which will account for these errors. HFI errors may prove more challenging to address, especially for polymorphism and amplicon applications, but may be overcome by sequencing the same DNA template across multiple chips.
Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis
Allison Sutherland, Mervyn Thomas, Roslyn A Brandon, Richard B Brandon, Jeffrey Lipman, Benjamin Tang, Anthony McLean, Ranald Pascoe, Gareth Price, Thu Nguyen, Glenn Stone, Deon Venter
Critical Care , 2011, DOI: 10.1186/cc10274
Abstract: This was a multi-centre, prospective clinical trial conducted across four tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n = 27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n = 38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n = 20). Each participant had minimally 5 ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes.Based on preliminary microarray analyses comparing HC and sepsis groups, a panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. The area under the curve (AUC) receiver operator characteristics (ROC) curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 and 92%.This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients.Systemic Inflammatory Response Syndrome (SIRS) is an overwhelming whole body reaction that may have an infectious or non-infectious aetiology and is described in associa
Genomic Responses during Acute Human Anaphylaxis Are Characterized by Upregulation of Innate Inflammatory Gene Networks
Shelley F. Stone, Anthony Bosco, Anya Jones, Claire L. Cotterell, Pauline E. van Eeden, Glenn Arendts, Daniel M. Fatovich, Simon G. A. Brown
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0101409
Abstract: Background Systemic spread of immune activation and mediator release is required for the development of anaphylaxis in humans. We hypothesized that peripheral blood leukocyte (PBL) activation plays a key role. Objective To characterize PBL genomic responses during acute anaphylaxis. Methods PBL samples were collected at three timepoints from six patients presenting to the Emergency Department (ED) with acute anaphylaxis and six healthy controls. Gene expression patterns were profiled on microarrays, differentially expressed genes were identified, and network analysis was employed to explore underlying mechanisms. Results Patients presented with moderately severe anaphylaxis after oral aspirin (2), peanut (2), bee sting (1) and unknown cause (1). Two genes were differentially expressed in patients compared to controls at ED arrival, 67 genes at 1 hour post-arrival and 2,801 genes at 3 hours post-arrival. Network analysis demonstrated that three inflammatory modules were upregulated during anaphylaxis. Notably, these modules contained multiple hub genes, which are known to play a central role in the regulation of innate inflammatory responses. Bioinformatics analyses showed that the data were enriched for LPS-like and TNF activation signatures. Conclusion PBL genomic responses during human anaphylaxis are characterized by dynamic expression of innate inflammatory modules. Upregulation of these modules was observed in patients with different reaction triggers. Our findings indicate a role for innate immune pathways in the pathogenesis of human anaphylaxis, and the hub genes identified in this study represent logical candidates for follow-up studies.
Conceptualizing an expanded role for RNs  [PDF]
Glenn Donnelly, Liz Domm
Open Journal of Nursing (OJN) , 2014, DOI: 10.4236/ojn.2014.42011
Abstract:

In our changing health care system, the role of registered nurses (RNs) has become indistinguishable from other nursing and health care providers’ roles. The purpose of this research was to explore the perspectives of nurse leaders and direct care RNs about the existing and future RN scope of practice. This research used an interpretive description analysis on data that was garnered from nurse leaders and RNs through separate focus groups. Participants identified existing threats to their roles, examined their scope of practice and proposed changes to the RN scope of practice. Specific areas that were identified included leadership, advocacy and expansion of RNs practices were dominant themes.

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