White matter lesions characterise brain involvement in moderate to severe chronic obstructive pulmonary disease, but cerebral atrophy does not.

BACKGROUND: Brain pathology is relatively unexplored in chronic obstructive pulmonary disease (COPD). This study is a comprehensive investigation of grey matter (GM) and white matter (WM) changes and how these relate to disease severity and cognitive function. METHODS: T1-weighted and fluid-attenuated inversion recovery images were acquired for 31 stable COPD patients (FEV1 52.1% pred., PaO2 10.1 kPa) and 24 age, gender-matched controls. T1-weighted images were segmented into GM, WM and cerebrospinal fluid (CSF) tissue classes using a semi-automated procedure optimised for use with this cohort. This procedure allows, cohort-specific anatomical features to be captured, white matter lesions (WMLs) to be identified and includes a tissue repair step to correct for misclassification caused by WMLs. Tissue volumes and cortical thickness were calculated from the resulting segmentations. Additionally, a fully-automated pipeline was used to calculate localised cortical surface and gyrification. WM and GM tissue volumes, the tissue volume ratio (indicator of atrophy), average cortical thickness, and the number, size, and volume of white matter lesions (WMLs) were analysed across the whole-brain and regionally - for each anatomical lobe and the deep-GM. The hippocampus was investigated as a region-of-interest. Localised (voxel-wise and vertex-wise) variations in cortical gyrification, GM density and cortical thickness, were also investigated. Statistical models controlling for age and gender were used to test for between-group differences and within-group correlations. Robust statistical approaches ensured the family-wise error rate was controlled in regional and local analyses. RESULTS: There were no significant differences in global, regional, or local measures of GM between patients and controls, however, patients had an increased volume (p = 0.02) and size (p = 0.04) of WMLs. In patients, greater normalised hippocampal volume positively correlated with exacerbation frequency (p = 0.04), and greater WML volume was associated with worse episodic memory (p = 0.05). A negative relationship between WML and FEV1 % pred. approached significance (p = 0.06). CONCLUSIONS: There was no evidence of cerebral atrophy within this cohort of stable COPD patients, with moderate airflow obstruction. However, there were indications of WM damage consistent with an ischaemic pathology. It cannot be concluded whether this represents a specific COPD, or smoking-related, effect

Active Learning Techniques to Build Problem Solving Skills in Chemistry Students

Through the introduction of Team-Based Learning problem classes and a ‘Purple Pens’ feedback intervention in which students write their own feedback on a mixed formative and summative class test we have been able to observe a significant increase in exam performance in Foundation Year students. Both Science and Health students improved their exam performance by 13% and 11% respectively and both interventions were positively received by students

Disruption of white matter connectivity in chronic obstructive pulmonary disease.

BACKGROUND: Mild cognitive impairment is a common systemic manifestation of chronic obstructive pulmonary disease (COPD). However, its pathophysiological origins are not understood. Since, cognitive function relies on efficient communication between distributed cortical and subcortical regions, we investigated whether people with COPD have disruption in white matter connectivity. METHODS: Structural networks were constructed for 30 COPD patients (aged 54-84 years, 57% male, FEV1 52.5% pred.) and 23 controls (aged 51-81 years, 48% Male). Networks comprised 90 grey matter regions (nodes) interconnected by white mater fibre tracts traced using deterministic tractography (edges). Edges were weighted by the number of streamlines adjusted for a) streamline length and b) end-node volume. White matter connectivity was quantified using global and nodal graph metrics which characterised the networks connection density, connection strength, segregation, integration, nodal influence and small-worldness. Between-group differences in white matter connectivity and within-group associations with cognitive function and disease severity were tested. RESULTS: COPD patients' brain networks had significantly lower global connection strength (p = 0.03) and connection density (p = 0.04). There was a trend towards COPD patients having a reduction in nodal connection density and connection strength across the majority of network nodes but this only reached significance for connection density in the right superior temporal gyrus (p = 0.02) and did not survive correction for end-node volume. There were no other significant global or nodal network differences or within-group associations with disease severity or cognitive function. CONCLUSION: COPD brain networks show evidence of damage compared to controls with a reduced number and strength of connections. This loss of connectivity was not sufficient to disrupt the overall efficiency of network organisation, suggesting that it has redundant capacity that makes it resilient to damage, which may explain why cognitive dysfunction is not severe. This might also explain why no direct relationships could be found with cognitive measures. Smoking and hypertension are known to have deleterious effects on the brain. These confounding effects could not be excluded

Quasi-diffusion magnetic resonance imaging (QDI): A fast, high b-value diffusion imaging technique.

To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1-4 min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps. QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s-1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value. We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena

An indigenous approach to explore health-related experiences among Māori parents: the Pukapuka Hauora asthma study.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tBACKGROUND: The prevalence of asthma for Indigenous New Zealand Māori is amongst the highest in the world. Recent evidence shows ethnic differences in asthma symptom prevalence in New Zealand have widened, with asthma symptoms and hospitalisation rates consistently higher for Māori across all age-groups, especially children and adolescents. This paper: outlines our qualitative, longitudinal research exploring the practical issues Māori children and their families face trying to achieve optimum asthma outcomes; details the research methods used within this study; and discusses the process evaluation findings of the features that made this approach successful in engaging and retaining participants in the study. METHODS: Thirty-two Māori families were recruited using a Kaupapa Māori (Māori way) Research approach. Each participated in a series of four in-depth interviews that were carried out at seasonal intervals over the course of one year. Families also took part in an interviewer-administered questionnaire and participated in a Photovoice exercise. All interviews were digitally recorded, transcribed verbatim and independently coded by two researchers. The research team then conducted the analysis and theme development. The questionnaires were analysed separately, with explanations for findings explored within the qualitative data. RESULTS: The methodology produced a 100 percent retention rate of the participating families over the course of the follow-up. This was attributed to the research collaboration, the respectful research relationships established with families, and the families' judgement that the methods used enabled them to tell their stories. The acceptability of the methodology will add to the validity and trustworthiness of the findings. CONCLUSION: Given the extent and persistence of ethnic disparities in childhood asthma management, it is imperative that an indigenous approach be taken to understanding the core issues facing Māori families. By conducting community-partnership research underpinned by an indigenous methodology, and employing a range of appropriate methods, we have successfully recruited and retained a cohort of Māori families with experiences of childhood asthma. We aim to make their voices heard in order to develop a series of culturally relevant interventions aimed at remediating these disparities.Health Research Council of New ZealandNIH

Using art for public engagement: reflections on the Dementia and Imagination project

Creative outputs engage the public and can be used to share research. This paper reports on public engagement activities that were part of the research project Dementia and Imagination (D&I). We found that artwork and creative activities effectively engaged a range of audiences and challenged negative ideas about dementia. For the project team, public engagement developed relationships with collaborators and connected the research to different community settings, influencing future programmes of work. Further work could explore public engagement in diverse settings to assess which approaches are effective in maximising research value and wider community benefit

Does Training on Broad Band Tactile Stimulation Promote the Generalization of Perceptual Learning?

Given the clear role of sensory feedback in successful motor control, there is a growing interest in integrating substitutionary tactile feedback into robotic limb devices. To enhance the utility of such feedback, here we investigate how to best improve the limited generalization of tactile learning across body parts and stimulus properties. Specifically, we sought to understand how perceptual learning with different types of tactile stimuli may give rise to different patterns of learning generalization. To address this, we utilized vibro-tactile effectors to present patterns of stimulation in a match-to-sample paradigm. One group of participants trained on narrow-band stimulation consisting of simple sinusoidal vibrations, and the other on broad-band stimulation generated from music. We hypothesized that training on broad-band tactile stimulation would promote greater generalization of learning outcomes. We found training with broad-band stimuli generalized to underlying stimulus features of frequency discrimination but showed weaker generalization to un-trained digits. This study provides a first step towards devising perceptual learning paradigms that will generalize broadly to the untrained perceptual contexts

Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique.

BACKGROUND: There is an increasing demand for noninvasive brain tumor biomarkers to guide surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor imaging (DTI) segmentation (D-SEG) to delineate tumor volumes of interest (VOIs) for subsequent classification of tumor type. D-SEG uses isotropic (p) and anisotropic (q) components of the diffusion tensor to segment regions with similar diffusion characteristics. METHODS: DTI scans were acquired from 95 patients with low- and high-grade glioma, metastases, and meningioma and from 29 healthy subjects. D-SEG uses k-means clustering of the 2D (p,q) space to generate segments with different isotropic and anisotropic diffusion characteristics. RESULTS: Our results are visualized using a novel RGB color scheme incorporating p, q and T2-weighted information within each segment. The volumetric contribution of each segment to gray matter, white matter, and cerebrospinal fluid spaces was used to generate healthy tissue D-SEG spectra. Tumor VOIs were extracted using a semiautomated flood-filling technique and D-SEG spectra were computed within the VOI. Classification of tumor type using D-SEG spectra was performed using support vector machines. D-SEG was computationally fast and stable and delineated regions of healthy tissue from tumor and edema. D-SEG spectra were consistent for each tumor type, with constituent diffusion characteristics potentially reflecting regional differences in tissue microstructure. Support vector machines classified tumor type with an overall accuracy of 94.7%, providing better classification than previously reported. CONCLUSIONS: D-SEG presents a user-friendly, semiautomated biomarker that may provide a valuable adjunct in noninvasive brain tumor diagnosis and treatment planning

The vegetation history of an Amazonian domed peatland

The peatland pole forests of the Pastaza-Marañón Foreland Basin (PMFB), Peru, are the most carbon-dense ecosystems known in Amazonia once below ground carbon stores are taken into account. Here we present the first multiproxy palaeoenvironmental record including pollen data from one of these peatlands, San Jorge in northern Peru, supported by an age model based on radiocarbon and 210Pb dating. The pollen data indicate that vegetation changes during the early phases of peat initiation resulted from autogenic succession in combination with fluvial influence. The overall pattern of vegetation change is not straightforward: the record does not reflect a process of unidirectional, progressive terrestrialization, but includes a reversal in the succession and vegetation transitions, which omit predicted successional phases. This complexity is similar to that seen in the only other existing pollen record from a PMFB peatland, at Quistococha, but contrasts with peat records from Panama and Southeast Asia where successional patterning appears more predictable. Our dating results provide the first evidence from a PMFB peatland that peat accumulation may have been discontinuous, with evidence for reduced rates of peat accumulation, or a possible hiatus, around 1300–400 cal yr BP. An ecological shift from open lake to palm swamp occurs at this time, possibly driven by climatic change. The pollen data indicate that the present pole forest vegetation at San Jorge began to assemble c. 200–150 cal yr BP. Given this young age, it is likely that the pole forest at this site remains in a state of transition