Käyttäytymisterapian vaikuttavuus hoitomuotona nuorten ADHD-oireisiin

Tiivistelmä. Tässä kandidaatin tutkielmassa tarkasteltiin kognitiivisen käyttäytymisterapian vaikuttavuutta nuorten ADHD-oireisiin. Tutkielma toteutettiin kuvailevana kirjallisuuskatsauksena tutustumalla aiheesta tehtyihin keskeisimpiin tutkimuksiin. Kiinnostus tutkimuskentällä tutkielman aiheeseen on herännyt vasta lähivuosien aikana. Tuoreiden tutkimusten valossa tutkielman tavoitteena oli selvittää, onko kognitiivisella käyttäytymisterapialla vaikutusta nuorten ADHD-oireisiin. Tarkoituksena oli samalla lisätä ymmärrystä ADHD:sta ja sen psykososiaalisista hoitokeinoista. ADHD eli aktiivisuuden ja tarkkaavuuden häiriö on kehityksellinen oireyhtymä, jonka ydinoireisiin kuuluvat tarkkaamattomuus, ylivilkkaus ja impulsiivisuus. ADHD heikentää toimintakykyä ja sen oireet ovat pitkäkestoisia. Kognitiivinen käyttäytymisterapia toimii yleiskäsitteenä kaikille psykoterapeuttisille menetelmille, joiden tavoitteena on kognitiivisia prosesseja muokkaamalla vähentää psyykkistä kärsimystä ja haitallista käyttäytymistä. Nuorten ADHD-oireiden hoitoon kuuluvassa kognitiivisessa käyttäytymisterapiassa työstettäviä kohteita ovat itsesäätely, sosiaalisten tilanteiden ongelmanratkaisu ja sosiaaliset taidot, oman toiminnan arviointi ja säätely sekä ADHD:n ydinoireiden hallinta. Tutkielmaan valikoituneiden tutkimusten tulosten perusteella voidaan päätellä, että kognitiivisesta käyttäytymisterapiasta voi olla joidenkin ADHD-oireisten nuorten hoidossa hyötyä. Tutkimuksissa todettiin kognitiivisen käyttäytymisterapian madaltavan nuorten tarvetta ADHD-lääkitykselle, parantavan heidän suoriutumistansa koulussa sekä vähentävän heidän kokemiaan ahdistus- ja masennusoireita. Erityisesti nuorten vanhemmat ja opettajat, mutta myös nuoret itse ilmoittivat tarkkaamattomuusoireiden vähentyneen. Kaikissa tutkimuksissa kognitiivisella käyttäytymisterapialla ei kuitenkaan todettu tilastollisesti merkittävää vaikutusta oireistoon

Neurite imaging reveals microstructural variations in human cerebral cortical gray matter

We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture

Developing a Global Healthcare Innovation Index

Our understanding of medicine is being revolutionised by the pace of science. But not all the potential innovations in life sciences and medical technology are taken up into everyday practice in healthcare, even when they are shown to be beneficial. For the poorest people in the world, many innovations are not accessible because they are either unaffordable or unsuitable for their health systems. Tackling this gap requires the development of appropriate and affordable health technologies and novel business models. In the more advanced health systems there is a disconnection between the effort on research and development (R&D) and how much of this makes it into mainstream healthcare practice. Even the most evidence-based and affordable innovations can fail or are only taken up patchily, whether we compare across countries, or between localities or health organisations within countries. And technological innovation can be a problem for those responsible for paying for health systems. New technologies often increase costs because they allow us to treat more people for a longer part of their lives. Yet the general view amongst politicians, managers and others involved in healthcare is that health systems across the world need new thinking. They are increasingly facing escalating demand from an ageing population and the growing incidence of chronic disease. Healthcare is consuming an ever-increasing share of gross domestic product (GDP). The search is on for ways of providing the best quality healthcare as affordably as possible. The health technology industries – pharmaceutical and biotechnology, medical devices, information technology and the built environment (design, engineering and construction) – drive much of the innovation that takes place in healthcare. They are very big business. Collectively these companies have global revenues in the order of USD 2 trillion a year, about a quarter of overall global spending on healthcare. But they too are experiencing a changing landscape – an evolving market for their products, a changing balance of power across health systems as governments and payers seek to control costs, hence pressure on their business models. Innovation is regarded by economists and politicians as one of the main drivers of economic growth. It helps to explain why some companies, regions and countries perform better than others in terms of higher productivity and income. For companies involved in the health technology sector, and governments in countries where they are located, there is concern to ensure that their business models are sustainable and continue to successfully deliver new products to the market

A Pyrolysis Pilot Unit Integrated to a Circulating Fluidized Bed Boiler - Experiences from a Pilot Project

A novel integrated pyrolysis pilot plant has been built in Tampere, Finland by Metso, in co-operation with UPM, Fortum and VTT. A 7 tons of bio-oil per day (2 MWfuel input) fast pyrolysis unit has been integrated with Metso’s 4 MWth CFB pilot boiler. Test runs of bio-oil production have been carried out during 2009-2010. More than 80 tons of bio-oil has been produced and utilization tests have been started in district heating burner applications

Diffusion tensor model links to neurite orientation dispersion and density imaging at high b-value in cerebral cortical gray matter

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture

Approximation of the critical buckling factor for composite panels

This article is concerned with the approximation of the critical buckling factor for thin composite plates. A new method to improve the approximation of this critical factor is applied based on its behavior with respect to lamination parameters and loading conditions. This method allows accurate approximation of the critical buckling factor for non-orthotropic laminates under complex combined loadings (including shear loading). The influence of the stacking sequence and loading conditions is extensively studied as well as properties of the critical buckling factor behavior (e.g concavity over tensor D or out-of-plane lamination parameters). Moreover, the critical buckling factor is numerically shown to be piecewise linear for orthotropic laminates under combined loading whenever shear remains low and it is also shown to be piecewise continuous in the general case. Based on the numerically observed behavior, a new scheme for the approximation is applied that separates each buckling mode and builds linear, polynomial or rational regressions for each mode. Results of this approach and applications to structural optimization are presented

A Strategy For Identifying Putative Causes Of Gene Expression Variation In Human Cancer

There is often a need to predict the impact of alterations in one variable on another variable. This is especially the case in cancer research, where much effort has been made to carry out large-scale gene expression screening by microarray techniques. However, the causes of this variability from one cancer to another and from one gene to another often remain unknown. In this study we present a systematic procedure for finding genes whose expression is altered by an intrinsic or extrinsic explanatory phenomenon. The procedure has three stages: preprocessing, data integration and statistical analysis. We tested and verified the utility of this approach in a study, where expression and copy number of 13,824 genes were determined in 14 breast cancer samples. The expression of 270 genes could be explained by the variability of gene copy number. These genes may represent an important set of primary, genetically "damaged" genes that drive cancer progression

Towards HCP-style macaque connectomes: 24-channel 3T multi-array coil, MRI sequences and preprocessing

Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain