Gender differences and determinants of health related quality of life in coronary patients: a follow-up study

<p>Abstract</p> <p>Background</p> <p>The role of gender differences in Health Related Quality Life (HRQL) in coronary patients is controversial, so understanding the specific determinants of HRQL in men and women might be of clinical importance. The aim of this study was to know the gender differences in the evolution of HRQL at 3 and 6 months after a coronary event, and to identify the key clinical, demographic and psychological characteristics of each gender associated with these changes.</p> <p>Methods</p> <p>A follow-up study was carried out, and 175 patients (112 men and 63 women) with acute myocardial infarction (AMI) or unstable angina were studied. The SF-36v1 health questionnaire was used to assess HRQL, and the GHQ-28 (General Health Questionnaire) to measure mental health during follow-up. To study the variables related to changes in HRQL, generalized estimating equation (GEE) models were performed.</p> <p>Results</p> <p>Follow-up data were available for 55 men and 25 women at 3 months, and for 35 men and 12 women at 6 months. Observations included: a) Revascularization was performed later in women. b) The frequency of rehospitalization between months 3 and 6 of follow-up was higher in women c) Women had lower baseline scores in the SF-36. d) Men had progressed favourably in most of the physical dimensions of the SF-36 at 6 months, while at the same time women's scores had only improved for Physical Component Summary, Role Physical and Social Functioning; e) the variables determining the decrease in HRQL in men were: worse mental health and angina frequency; and in women: worse mental health, history of the disease, revascularization, and angina frequency.</p> <p>Conclusions</p> <p>There are differences in the evolution of HRQL, between men and women after a coronary attack. Mental health is the determinant most frequently associated with HRQL in both genders. However, other clinical determinants of HRQL differed with gender, emphasizing the importance of individualizing the intervention and the content of rehabilitation programs. Likewise, the recognition and treatment of mental disorders in these patients could be crucial.</p

Distinct regulation of c-myb gene expression by HoxA9, Meis1 and Pbx proteins in normal hematopoietic progenitors and transformed myeloid cells

The proto-oncogenic protein c-Myb is an essential regulator of hematopoiesis and is frequently deregulated in hematological diseases such as lymphoma and leukemia. To gain insight into the mechanisms underlying the aberrant expression of c-Myb in myeloid leukemia, we analyzed and compared c-myb gene transcriptional regulation using two cell lines modeling normal hematopoietic progenitor cells (HPCs) and transformed myelomonocytic blasts. We report that the transcription factors HoxA9, Meis1, Pbx1 and Pbx2 bind in vivo to the c-myb locus and maintain its expression through different mechanisms in HPCs and leukemic cells. Our analysis also points to a critical role for Pbx2 in deregulating c-myb expression in murine myeloid cells cotransformed by the cooperative activity of HoxA9 and Meis1. This effect is associated with an intronic positioning of epigenetic marks and RNA polymerase II binding in the orthologous region of a previously described alternative promoter for c-myb. Taken together, our results could provide a first hint to explain the abnormal expression of c-myb in leukemic cells

Altered Anatomical Network in Early Blindness Revealed by Diffusion Tensor Tractography

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. Diffusion MRI studies have revealed the efficient small-world properties and modular structure of the anatomical network in normal subjects. However, no previous study has used diffusion MRI to reveal changes in the brain anatomical network in early blindness. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 17 early blind subjects and 17 age- and gender-matched sighted controls. We established the existence of structural connections between any pair of the 90 cortical and sub-cortical regions using deterministic tractography. Compared with controls, early blind subjects showed a decreased degree of connectivity, a reduced global efficiency, and an increased characteristic path length in their brain anatomical network, especially in the visual cortex. Moreover, we revealed some regions with motor or somatosensory function have increased connections with other brain regions in the early blind, which suggested experience-dependent compensatory plasticity. This study is the first to show alterations in the topological properties of the anatomical network in early blindness. From the results, we suggest that analyzing the brain's anatomical network obtained using diffusion MRI data provides new insights into the understanding of the brain's re-organization in the specific population with early visual deprivation

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

Sampling and visualizing creases with scale-space particles.

Particle systems have gained importance as a methodology for sampling implicit surfaces and segmented objects to improve mesh generation and shape analysis. We propose that particle systems have a significantly more general role in sampling structure from unsegmented data. We describe a particle system that computes samplings of crease features (i.e. ridges and valleys, as lines or surfaces) that effectively represent many anatomical structures in scanned medical data. Because structure naturally exists at a range of sizes relative to the image resolution, computer vision has developed the theory of scale-space, which considers an n-D image as an (n+1)-D stack of images at different blurring levels. Our scale-space particles move through continuous four-dimensional scale-space according to spatial constraints imposed by the crease features, a particle-image energy that draws particles towards scales of maximal feature strength, and an inter-particle energy that controls sampling density in space and scale. To make scale-space practical for large three-dimensional data, we present a spline-based interpolation across scale from a small number of pre-computed blurrings at optimally selected scales. The configuration of the particle system is visualized with tensor glyphs that display information about the local Hessian of the image, and the scale of the particle. We use scale-space particles to sample the complex three-dimensional branching structure of airways in lung CT, and the major white matter structures in brain DTI