Mapping Multiple Literacies: An Introduction to Deleuzian Literacy Studies

Mapping Multiple Literacies brings together the latest theory and research in the fields of literacy study and European philosophy, Multiple Literacies Theory (MLT) and the philosophical work of Gilles Deleuze. It frames the process of becoming literate as a fluid process involving multiple modes of presentation, and explains these processes in terms of making maps of our social lives and ways of doing things together. For Deleuze, language acquisition is a social activity of which we are a part, but only one part amongst many others. Masny and Cole draw on Deleuze's thinking to expand the repertoires of literacy research and understanding. They outline how we can understand literacy as a social activity and map the ways in which becoming literate may take hold and transform communities. The chapters in this book weave together theory, data and practice to open up a creative new area of literacy studies and to provoke vigorous debate about the sociology of literacy.

Multiple Literacies Theory: Discourse, sensation, resonance and becoming

This thematic issue on education and the politics of becoming focuses on how a Multiple Literacies Theory (MLT) plugs into practice in education. MLT does this by creating an assemblage between discourse, text, resonance and sensations. What does this produce? Becoming AND how one might live are the product of an assemblage (May, 2005; Semetsky, 2003). In this paper, MLT is the approach that explores the connection between educational theory and practice through the lens of an empirical study of multilingual children acquiring multiple writing systems simultaneously. The introduction explicates discourse, text, resonance, sensation and becoming. The second section introduces certain Deleuzian concepts that plug into MLT. The third section serves as an introduction to MLT. The fourth section is devoted to the study by way of a rhizoanalysis. Finally, drawing on the concept of the rhizome, this article exits with potential lines of flight opened by MLT. These are becomings which highlight the significance of this work in terms of transforming not only how literacies are conceptualized, especially in minority language contexts, but also how one might live.

Social enterprises in rural community development

Social enterprises are hybrid organizational forms that combine characteristics of for-profit businesses and community sector organizations. This article explores how rural communities may use social enterprises to progress local development agendas across both economic and social domains. Drawing on qualitative case studies of three social enterprises in rural North West Tasmania, this article explores the role of social enterprises in local development processes. The case study social enterprises, despite differences in size, structure, mission and age, are strongly embedded in their local places and local communities. As deeply contextualized development actors, these social enterprises mobilize multiple resources and assets to achieve a range of local development outcomes, including but not limited to social capital

Achieving high reliability for ambiguity resolutions with multiple GNSS constellations

Global Navigation Satellite Systems (GNSS)-based observation systems can provide high precision positioning and navigation solutions in real time, in the order of subcentimetre if we make use of carrier phase measurements in the differential mode and deal with all the bias and noise terms well. However, these carrier phase measurements are ambiguous due to unknown, integer numbers of cycles. One key challenge in the differential carrier phase mode is to fix the integer ambiguities correctly. On the other hand, in the safety of life or liability-critical applications, such as for vehicle safety positioning and aviation, not only is high accuracy required, but also the reliability requirement is important. This PhD research studies to achieve high reliability for ambiguity resolution (AR) in a multi-GNSS environment. GNSS ambiguity estimation and validation problems are the focus of the research effort. Particularly, we study the case of multiple constellations that include initial to full operations of foreseeable Galileo, GLONASS and Compass and QZSS navigation systems from next few years to the end of the decade. Since real observation data is only available from GPS and GLONASS systems, the simulation method named Virtual Galileo Constellation (VGC) is applied to generate observational data from another constellation in the data analysis. In addition, both full ambiguity resolution (FAR) and partial ambiguity resolution (PAR) algorithms are used in processing single and dual constellation data. Firstly, a brief overview of related work on AR methods and reliability theory is given. Next, a modified inverse integer Cholesky decorrelation method and its performance on AR are presented. Subsequently, a new measure of decorrelation performance called orthogonality defect is introduced and compared with other measures. Furthermore, a new AR scheme considering the ambiguity validation requirement in the control of the search space size is proposed to improve the search efficiency. With respect to the reliability of AR, we also discuss the computation of the ambiguity success rate (ASR) and confirm that the success rate computed with the integer bootstrapping method is quite a sharp approximation to the actual integer least-squares (ILS) method success rate. The advantages of multi-GNSS constellations are examined in terms of the PAR technique involving the predefined ASR. Finally, a novel satellite selection algorithm for reliable ambiguity resolution called SARA is developed. In summary, the study demonstrats that when the ASR is close to one, the reliability of AR can be guaranteed and the ambiguity validation is effective. The work then focuses on new strategies to improve the ASR, including a partial ambiguity resolution procedure with a predefined success rate and a novel satellite selection strategy with a high success rate. The proposed strategies bring significant benefits of multi-GNSS signals to real-time high precision and high reliability positioning services.

The individual and interactive relationship between long chain omega-3 polyunsaturated fatty acids and physical activity as predictors of cognition in cognitively impaired and non-impaired older adults

Alterations in cognitive function are characteristic of the aging process in humans and other animals. However, the nature of these age related changes in cognition is complex and is likely to be influenced by interactions between genetic predispositions and environmental factors resulting in dynamic fluctuations within and between individuals. These inter and intra-individual fluctuations are evident in both so-called normal cognitive aging and at the onset of cognitive pathology. Mild Cognitive Impairment (MCI), thought to be a prodromal phase of dementia, represents perhaps the final opportunity to mitigate cognitive declines that may lead to terminal conditions such as dementia. The prognosis for people with MCI is mixed with the evidence suggesting that many will remain stable within 10-years of diagnosis, many will improve, and many will transition to dementia. If the characteristics of people who do not progress to dementia from MCI can be identified and replicated in others it may be possible to reduce or delay dementia onset, thus reducing a growing personal and public health burden. Furthermore, if MCI onset can be prevented or delayed, the burden of cognitive decline in aging populations worldwide may be reduced. A cognitive domain that is sensitive to the effects of advancing age, and declines in which have been shown to presage the onset of dementia in MCI patients, is executive function. Moreover, environmental factors such as diet and physical activity have been shown to affect performance on tests of executive function. For example, improvements in executive function have been demonstrated as a result of increased aerobic and anaerobic physical activity and, although the evidence is not as strong, findings from dietary interventions suggest certain nutrients may preserve or improve executive functions in old age. These encouraging findings have been demonstrated in older adults with MCI and their non-impaired peers. However, there are some gaps in the literature that need to be addressed. For example, little is known about the effect on cognition of an interaction between diet and physical activity. Both are important contributors to health and wellbeing, and a growing body of evidence attests to their importance in mental and cognitive health in aging individuals. Yet physical activity and diet are rarely considered together in the context of cognitive function. There is also little known about potential underlying biological mechanisms that might explain the physical activity/diet/cognition relationship. The first aim of this program of research was to examine the individual and interactive role of physical activity and diet, specifically long chain polyunsaturated fatty acid consumption(LCn3) as predictors of MCI status. The second aim is to examine executive function in MCI in the context of the individual and interactive effects of physical activity and LCn3.. A third aim was to explore the role of immune and endocrine system biomarkers as possible mediators in the relationship between LCn3, physical activity and cognition. Study 1a was a cross-sectional analysis of MCI status as a function of erythrocyte proportions of an interaction between physical activity and LCn3. The marine based LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have both received support in the literature as having cognitive benefits, although comparisons of the relative benefits of EPA or DHA, particularly in relation to the aetiology of MCI, are rare. Furthermore, a limited amount of research has examined the cognitive benefits of physical activity in terms of MCI onset. No studies have examined the potential interactive benefits of physical activity and either EPA or DHA. Eighty-four male and female adults aged 65 to 87 years, 50 with MCI and 34 without, participated in Study 1a. A logistic binary regression was conducted with MCI status as a dependent variable, and the individual and interactive relationships between physical activity and either EPA or DHA as predictors. Physical activity was measured using a questionnaire and specific physical activity categories were weighted according to the metabolic equivalents (METs) of each activity to create a physical activity intensity index (PAI). A significant relationship was identified between MCI outcome and the interaction between the PAI and EPA; participants with a higher PAI and higher erythrocyte proportions of EPA were more likely to be classified as non-MCI than their less active peers with less EPA. Study 1b was a randomised control trial using the participants from Study 1a who were identified with MCI. Given the importance of executive function as a determinant of progression to more severe forms of cognitive impairment and dementia, Study 1b aimed to examine the individual and interactive effect of physical activity and supplementation with either EPA or DHA on executive function in a sample of older adults with MCI. Fifty male and female participants were randomly allocated to supplementation groups to receive 6-months of supplementation with EPA, or DHA, or linoleic acid (LA), a long chain polyunsaturated omega-6 fatty acid not known for its cognitive enhancing properties. Physical activity was measured using the PAI from Study 1a at baseline and follow-up. Executive function was measured using five tests thought to measure different executive function domains. Erythrocyte proportions of EPA and DHA were higher at follow-up; however, PAI was not significantly different. There was also a significant improvement in three of the five executive function tests at follow-up. However, regression analyses revealed that none of the variance in executive function at follow-up was predicted by EPA, DHA, PAI, the EPA by PAI interaction, or the DHA by PAI interaction. The absence of an effect may be due to a small sample resulting in limited power to find an effect, the lack of change in physical activity over time in terms of volume and/or intensity, or a combination of both reduced power and no change in physical activity. Study 2a was a cross-sectional study using cognitively unimpaired older adults to examine the individual and interactive effects of LCn3 and PAI on executive function. Several possible explanations for the absence of an effect were identified. From this consideration of alternative explanations it was hypothesised that post-onset interventions with LCn3 either alone or in interation with self-reported physical activity may not be beneficial in MCI. Thus executive function responses to the individual and interactive effects of physical activity and LCn3 were examined in a sample of older male and female adults without cognitive impairment (n = 50). A further aim of study 2a was to operationalise executive function using principal components analysis (PCA) of several executive function tests. This approach was used firstly as a data reduction technique to overcome the task impurity problem, and secondly to examine the executive function structure of the sample for evidence of de-differentiation. Two executive function components were identified as a result of the PCA (EF 1 and EF 2). However, EPA, DHA, the PAI, or the EPA by PAI or DHA by PAI interactions did not account for any variance in the executive function components in subsequent hierarchical multiple regressions. Study 2b was an exploratory correlational study designed to explore the possibility that immune and endocrine system biomarkers may act as mediators of the relationship between LCn3, PAI, the interaction between LCn3 and PAI, and executive functions. Insulin-like growth factor-1 (IGF-1), an endocrine system growth hormone, and interleukin-6 (IL-6) an immune system cytokine involved in the acute inflammatory response, have both been shown to affect cognition including executive functions. Moreover, IGF-1 and IL-6 have been shown to be antithetical in so far as chronically increased IL-6 has been associated with reduced IGF-1 levels, a relationship that has been linked to age related morbidity. Further, physical activity and LCn3 have been shown to modulate levels of both IGF-1 and IL-6. Thus, it is possible that the cognitive enhancing effects of LCn3, physical activity or their interaction are mediated by changes in the balance between IL-6 and IGF-1. Partial and non-parametric correlations were conducted in a subsample of participants from Study 2a (n = 13) to explore these relationships. Correlations of interest did not reach significance; however, the coefficients were quite large for several relationships suggesting studies with larger samples may be warranted. In summary, the current program of research found some evidence supporting an interaction between EPA, not DHA, and higher energy expenditure via physical activity in differentiating between older adults with and without MCI. However, a RCT examining executive function in older adults with MCI found no support for increasing EPA or DHA while maintaining current levels of energy expenditure. Furthermore, a cross-sectional study examining executive function in older adults without MCI found no support for better executive function performance as a function of increased EPA or DHA consumption, greater energy expenditure via physical activity or an interaction between physical activity and either EPA or DHA. Finally, an examination of endocrine and immune system biomarkers revealed promising relationships in terms of executive function in non-MCI older adults particularly with respect to LCn3 and physical activity. Taken together, these findings demonstrate a potential benefit of increasing physical activity and LCn3 consumption, particularly EPA, in mitigating the risk of developing MCI. In contrast, no support was found for a benefit to executive function as a result of increased physical activity, LCn3 consumption or an interaction between physical activity and LCn3, in participants with and without MCI. These results are discussed with reference to previous findings in the literature including possible limitations and opportunities for future research.

Multiple scattering in deep inelastic neutron scattering : Monte Carlo simulations and experiments at the ISIS eVS inverse geometry spectrometer

A procedure for the evaluation of multiple scattering contributions is described, for deep inelastic neutron scattering (DINS) studies using an inverse geometry time-of-flight spectrometer. The accuracy of a Monte Carlo code DINSMS, used to calculate the multiple scattering, is tested by comparison with analytic expressions and with experimental data collected from polythene, polycrystalline graphite and tin samples. It is shown that the Monte Carlo code gives an accurate representation of the measured data and can therefore be used to reliably correct DINS data.

Quality Assessment Matrix : A Collaborative Evaluation Using Multiple Lines of Evidence

Welcome to the Quality assessment matrix. This matrix is designed for highly qualified discipline experts to evaluate their course, major or unit in a systematic manner. The primary purpose of the Quality assessment matrix is to provide a tool that a group of academic staff at universities can collaboratively review the assessment within a course, major or unit annually. The annual review will result in you being read for an external curricula review at any point in time. This tool is designed for use in a workshop format with one, two or more academic staff, and will lead to an action plan for implementation.

Cell migration and proliferation on homogeneous and non-homogeneous domains : modelling on the scale of individuals and populations

Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

Fractional models for the migration of biological cells in complex spatial domains

Travelling wave phenomena are observed in many biological applications. Mathematical theory of standard reaction-diffusion problems shows that simple partial differential equations exhibit travelling wave solutions with constant wavespeed and such models are used to describe, for example, waves of chemical concentrations, electrical signals, cell migration, waves of epidemics and population dynamics. However, as in the study of cell motion in complex spatial geometries, experimental data are often not consistent with constant wavespeed. Non-local spatial models have successfully been used to model anomalous diffusion and spatial heterogeneity in different physical contexts. In this paper, we develop a fractional model based on the Fisher-Kolmogoroff equation and analyse it for its wavespeed properties, attempting to relate the numerical results obtained from our simulations to experimental data describing enteric neural crest-derived cells migrating along the intact gut of mouse embryos. The model proposed essentially combines fractional and standard diffusion in different regions of the spatial domain and qualitatively reproduces the behaviour of neural crest-derived cells observed in the caecum and the hindgut of mouse embryos during in vivo experiments.

Pseudo-marginal algorithms with multiple CPUs

The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

Ingenuity pathways analysis of urine metabonomics phenotypes toxicity of gentamicin in multiple organs

We introduce the use of Ingenuity Pathway Analysis to analyzing global metabonomics in order to characterize phenotypically biochemical perturbations and the potential mechanisms of the gentamicin-induced toxicity in multiple organs. A single dose of gentamicin was administered to Sprague Dawley rats (200 mg/kg, n = 6) and urine samples were collected at -24-0 h pre-dosage, 0-24, 24-48, 48-72 and 72-96 h post-dosage of gentamicin. The urine metabonomics analysis was performed by UPLC/MS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition analyses (Heatmap, PCA and PLS-DA), revealing a time-dependency of the biochemical perturbations induced by gentamicin toxicity. As result, the holistic metabolome change induced by gentamicin toxicity in the animal's organisms was characterized. Several metabolites involved in amino acid metabolism were identified in urine, and it was confirmed that gentamicin biochemical perturbations can be foreseen from these biomarkers. Notoriously, it was found that gentamicin induced toxicity in multiple organs system in the laboratory rats. The proof-of-knowledge based Ingenuity Pathway Analysis revealed gentamicin induced liver and heart toxicity, along with the previously known toxicity in kidney. The metabolites creatine, nicotinic acid, prostaglandin E2, and cholic acid were identified and validated as phenotypic biomarkers of gentamicin induced toxicity. Altogether, the significance of the use of metabonomics analyses in the assessment of drug toxicity is highlighted once more; furthermore, this work demonstrated the powerful predictive potential of the Ingenuity Pathway Analysis to study of drug toxicity and its valuable complementation for metabonomics based assessment of the drug toxicity.

Social support promotes psychological well-being following a natural disaster

Receiving emotional support has consistently been demonstrated as an important factor associated with mental health but sparse research has investigated giving support in addition to receiving it or the types of support that predict well-being. In this paper the relationship between giving and receiving instrumental and emotional social support and psychological well-being during and following a natural disaster is investigated. A survey administered between four and six months after fatal floods was conducted with 200 community members consisting of men (n = 68) and women (n = 132) aged between 17 and 87 years. Social support experiences were assessed using the 2-Way Social Support Scale (2-Way SSS; Shakespeare-Finch & Obst, 2011) and eudemonic well-being was measured using the Psychological Well-Being Scale (PWBS; Ryff & Keyes, 1995). Hierarchical multiple regression analyses were used to examine expected relationships and to explore the differential effects of the four factors of the 2-Way SSS. Results indicated that social support shared significant positive associations with domains of psychological well-being, especially with regards to interpersonal relationships. Receiving and giving emotional support were respectively the strongest unique predictors of psychological well-being. However, receiving instrumental support predicted less autonomy. Results highlight the importance of measuring social support as a multidimensional construct and affirm that disaster response policy and practice should focus on emotional as well as instrumental needs in order to promote individual and community psychosocial health following a flooding crisis.

Resequencing and fine-mapping of the chromosome 12q13-14 locus associated with multiple sclerosis refines the number of implicated genes

Multiple sclerosis (MS) is a common chronic inflammatory disease of the central nervous system. Susceptibility to the disease is affected by both environmental and genetic factors. Genetic factors include haplotypes in the histocompatibility complex (MHC) and over 50 non-MHC loci reported by genome-wide association studies. Amongst these, we previously reported polymorphisms in chromosome 12q13-14 with a protective effect in individuals of European descent. This locus spans 288 kb and contains 17 genes, including several candidate genes which have potentially significant pathogenic and therapeutic implications. In this study, we aimed to fine-map this locus. We have implemented a two-phase study: a variant discovery phase where we have used next-generation sequencing and two target-enrichment strategies [long-range polymerase chain reaction (PCR) and Nimblegen's solution phase hybridization capture] in pools of 25 samples; and a genotyping phase where we genotyped 712 variants in 3577 healthy controls and 3269 MS patients. This study confirmed the association (rs2069502, P = 9.9 × 10−11, OR = 0.787) and narrowed down the locus of association to an 86.5 kb region. Although the study was unable to pinpoint the key-associated variant, we have identified a 42 (genotyped and imputed) single-nucleotide polymorphism haplotype block likely to harbour the causal variant. No evidence of association at previously reported low-frequency variants in CYP27B1 was observed. As part of the study we compared variant discovery performance using two target-enrichment strategies. We concluded that our pools enriched with Nimblegen's solution phase hybridization capture had better sensitivity to detect true variants than the pools enriched with long-range PCR, whilst specificity was better in the long-range PCR-enriched pools compared with solution phase hybridization capture enriched pools; this result has important implications for the design of future fine-mapping studies.

The evolution and biogeography of the austral horse fly tribe Scionini (Diptera: Tabanidae: Pangoniinae) inferred from multiple mitochondrial and nuclear genes

Phylogenetic relationships within the Tabanidae are largely unknown, despite their considerable medical and ecological importance. The first robust phylogenetic hypothesis for the horse fly tribe Scionini is provided, completing the systematic placement of all tribes in the subfamily Pangoniinae. The Scionini consists of seven mostly southern hemisphere genera distributed in Australia, New Guinea, New Zealand and South America. A 5757. bp alignment of 6 genes, including mitochondrial (COI and COII), ribosomal (28S) and nuclear (AATS and CAD regions 1, 3 and 4) genes, was analysed for 176 taxa using both Bayesian and maximum likelihood approaches. Results indicate the Scionini are strongly monophyletic, with the exclusion of the only northern hemisphere genus Goniops. The South American genera Fidena, Pityocera and Scione were strongly monophyletic, corresponding to current morphology-based classification schemes. The most widespread genus Scaptia was paraphyletic and formed nine strongly supported monophyletic clades, each corresponding to either the current subgenera or several previously synonymised genera that should be formally resurrected. Molecular results also reveal a newly recognised genus endemic to New Zealand, formerly placed within Scaptia. Divergence time estimation was employed to assess the global biogeographical patterns in the Pangoniinae. These analyses demonstrated that the Scionini are a typical Gondwanan group whose diversification was influenced by the fragmentation of that ancient land mass. Furthermore, results indicate that the Scionini most likely originated in Australia and subsequently radiated to New Zealand and South American by both long distance dispersal and vicariance. The phylogenetic framework of the Scionini provided herein will be valuable for taxonomic revisions of the Tabanidae.

Circulating microRNAs involved in multiple sclerosis

Multiple sclerosis (MS) is an immune-mediated, demyelinating and neurodegenerative disease of the central nervous system. After traumatic brain injury, it is the leading cause of neurology disability in young adults. Considerable advances have been made in identifying genes involved in MS but the genetic and phenotypic complexity associated with this disease significantly hinders any progress. A novel class of small RNA molecules, microRNAs (miRNAs) has acquired much attention because they regulate the expression of up to 30% of protein-coding genes and may play a pivotal role in the development of many, if not all, complex diseases. Seven published studies investigated miRNAs from peripheral blood mononuclear cells, CD4+, CD8+ T cell, B lymphocytes, peripheral blood leukocytes, whole blood and brain astrocytes with MS risk. The absence of MS studies investigating plasma miRNA prompted the current investigation of identifying a circulating miRNA signature in MS. We conducted a microarray analysis of over 900 known miRNA transcripts from plasma samples collected from four MS individuals and four sex-aged and ethnicity matched healthy controls. We identified six plasma miRNA (miR-614, miR-572, miR-648, miR-1826, miR-422a and miR-22) that were significantly up-regulated and one plasma miRNA (miR-1979) that was significantly down-regulated in MS individuals. Both miR-422a and miR-22 have previously been implicated in MS. The present study is the first to show a circulating miRNA signature involved in MS that could serve as a potential prognostic and diagnostic biomarker for MS.