Calcification of intervertebral discs in the dachshund: a radiographic and histopathologic study of 20 dogs

<p>Abstract</p> <p>Background</p> <p>The purpose of the study was to compare radiographic and histopathologic findings with regard to number and extent of calcified discs in the dachshund.</p> <p>Methods</p> <p>The intervertebral discs of 20 dachshunds were subjected to a radiographic and histopathologic examination. The dogs were selected randomly from clinical cases euthanased for reasons unrelated to research at the Norwegian School of Veterinary Science. Lateral radiographs were taken of the vertebral columns after removing them from the carcasses. The histopathologic examination included 5 μm thick sections in the transverse plane, stained with hematoxylin-eosin and von Kossa. Radiographs and histological sections were evaluated independently.</p> <p>Results</p> <p>A total of 148 (28.5%) calcified discs were identified at the radiographic and 230 (45.7%) at the histopathologic examination. Of 92 discs found to be calcified by histopathology, but not by radiography, the degree of calcification was evaluated as 'slight' in 84 (91.3%). All the intervertebral discs (n = 138) that were found to be calcified by radiography were also found to be calcified by histopathology.</p> <p>Conclusion</p> <p>A sensitivity of 0.6 and specificity of 1.0 for radiography was calculated when using histopathology as the gold standard.</p

Neutrophils Promote Mycobacterial Trehalose Dimycolate-Induced Lung Inflammation via the Mincle Pathway

Trehalose 6,6′-dimycolate (TDM), a cord factor of Mycobacterium tuberculosis (Mtb), is an important regulator of immune responses during Mtb infections. Macrophages recognize TDM through the Mincle receptor and initiate TDM-induced inflammatory responses, leading to lung granuloma formation. Although various immune cells are recruited to lung granulomas, the roles of other immune cells, especially during the initial process of TDM-induced inflammation, are not clear. In this study, Mincle signaling on neutrophils played an important role in TDM-induced lung inflammation by promoting adhesion and innate immune responses. Neutrophils were recruited during the early stage of lung inflammation following TDM-induced granuloma formation. Mincle expression on neutrophils was required for infiltration of TDM-challenged sites in a granuloma model induced by TDM-coated-beads. TDM-induced Mincle signaling on neutrophils increased cell adherence by enhancing F-actin polymerization and CD11b/CD18 surface expression. The TDM-induced effects were dependent on Src, Syk, and MAPK/ERK kinases (MEK). Moreover, coactivation of the Mincle and TLR2 pathways by TDM and Pam3CSK4 treatment synergistically induced CD11b/CD18 surface expression, reactive oxygen species, and TNFα production by neutrophils. These synergistically-enhanced immune responses correlated with the degree of Mincle expression on neutrophil surfaces. The physiological relevance of the Mincle-mediated anti-TDM immune response was confirmed by defective immune responses in Mincle−/− mice upon aerosol infections with Mtb. Mincle-mutant mice had higher inflammation levels and mycobacterial loads than WT mice. Neutrophil depletion with anti-Ly6G antibody caused a reduction in IL-6 and monocyte chemotactic protein-1 expression upon TDM treatment, and reduced levels of immune cell recruitment during the initial stage of infection. These findings suggest a new role of Mincle signaling on neutrophils during anti-mycobacterial responses

Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT

Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment

Merged consensus clustering to assess and improve class discovery with microarray data

<p>Abstract</p> <p>Background</p> <p>One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced.</p> <p>Results</p> <p>Here we describe an R package containing methods to analyse the consistency of clustering results from any number of different clustering methods using resampling statistics. These methods allow the identification of the the best supported clusters and additionally rank cluster members by their fidelity within the cluster. These metrics allow us to compare the performance of different clustering algorithms under different experimental conditions and to select those that produce the most reliable clustering structures. We show the application of this method to simulated data, canonical gene expression experiments and our own novel analysis of genes involved in the specification of the peripheral nervous system in the fruitfly, <it>Drosophila melanogaster</it>.</p> <p>Conclusions</p> <p>Our package enables users to apply the merged consensus clustering methodology conveniently within the R programming environment, providing both analysis and graphical display functions for exploring clustering approaches. It extends the basic principle of consensus clustering by allowing the merging of results between different methods to provide an averaged clustering robustness. We show that this extension is useful in correcting for the tendency of clustering algorithms to treat outliers differently within datasets. The R package, <it>clusterCons</it>, is freely available at CRAN and sourceforge under the GNU public licence.</p

TCR signal strength controls thymic differentiation of discrete proinflammatory gamma delta T cell subsets

The mouse thymus produces discrete gd T cell subsets that make either interferon-g (IFN-g) or interleukin 17 (IL-17), but the role of the T cell antigen receptor (TCR) in this developmental process remains controversial. Here we show that Cd3g+/− Cd3d+/− (CD3 double-haploinsufficient (CD3DH)) mice have reduced TCR expression and signaling strength on gd T cells. CD3DH mice had normal numbers and phenotypes of ab thymocyte subsets, but impaired differentiation of fetal Vg6+ (but not Vg4+) IL-17- producing gd T cells and a marked depletion of IFN-g-producing CD122+ NK1.1+ gd T cells throughout ontogeny. Adult CD3DH mice showed reduced peripheral IFN-g+ gd T cells and were resistant to experimental cerebral malaria. Thus, TCR signal strength within specific thymic developmental windows is a major determinant of the generation of proinflammatory gd T cell subsets and their impact on pathophysiology

Roadless and Low-Traffic Areas as Conservation Targets in Europe

With increasing road encroachment, habitat fragmentation by transport infrastructures has been a serious threat for European biodiversity. Areas with no roads or little traffic (“roadless and low-traffic areas”) represent relatively undisturbed natural habitats and functioning ecosystems. They provide many benefits for biodiversity and human societies (e.g., landscape connectivity, barrier against pests and invasions, ecosystem services). Roadless and low-traffic areas, with a lower level of anthropogenic disturbances, are of special relevance in Europe because of their rarity and, in the context of climate change, because of their contribution to higher resilience and buffering capacity within landscape ecosystems. An analysis of European legal instruments illustrates that, although most laws aimed at protecting targets which are inherent to fragmentation, like connectivity, ecosystem processes or integrity, roadless areas are widely neglected as a legal target. A case study in Germany underlines this finding. Although the Natura 2000 network covers a significant proportion of the country (16%), Natura 2000 sites are highly fragmented and most low-traffic areas (75%) lie unprotected outside this network. This proportion is even higher for the old Federal States (western Germany), where only 20% of the low-traffic areas are protected. We propose that the few remaining roadless and low-traffic areas in Europe should be an important focus of conservation efforts; they should be urgently inventoried, included more explicitly in the law and accounted for in transport and urban planning. Considering them as complementary conservation targets would represent a concrete step towards the strengthening and adaptation of the Natura 2000 network to climate change

A 1-Year Study of Endurance Runners: Training, Laboratory Tests, and Field Tests

Purpose: To compare critical speed (CS) measured from a single-visit field test of the distance–time relationship with the “traditional” treadmill time-to-exhaustion multivisit protocol. Methods: Ten male distance runners completed treadmill and field tests to calculate CS and the maximum distance performed above CS (D′). The field test involved 3 runs on a single visit to an outdoor athletics track over 3600, 2400, and 1200 m. Two field-test protocols were evaluated using either a 30-min recovery or a 60-min recovery between runs. The treadmill test involved runs to exhaustion at 100%, 105%, and 110% of velocity at VO2max, with 24 h recovery between runs. Results: There was no difference in CS measured with the treadmill and 30-min- and 60-minrecovery field tests (P .05). A typical error of the estimate of 0.14 m/s (95% confidence limits 0.09–0.26 m/s) was seen for CS and 88 m (95% confidence limits 60–169 m) for D′. A coefficient of variation of 0.4% (95% confidence limits: 0.3–0.8%) was found for repeat tests of CS and 13% (95% confidence limits 10–27%) for D′. Conclusion: The single-visit method provides a useful alternative for assessing CS in the field