317 research outputs found

    Live Imaging at the Onset of Cortical Neurogenesis Reveals Differential Appearance of the Neuronal Phenotype in Apical versus Basal Progenitor Progeny

    Get PDF
    The neurons of the mammalian brain are generated by progenitors dividing either at the apical surface of the ventricular zone (neuroepithelial and radial glial cells, collectively referred to as apical progenitors) or at its basal side (basal progenitors, also called intermediate progenitors). For apical progenitors, the orientation of the cleavage plane relative to their apical-basal axis is thought to be of critical importance for the fate of the daughter cells. For basal progenitors, the relationship between cell polarity, cleavage plane orientation and the fate of daughter cells is unknown. Here, we have investigated these issues at the very onset of cortical neurogenesis. To directly observe the generation of neurons from apical and basal progenitors, we established a novel transgenic mouse line in which membrane GFP is expressed from the beta-III-tubulin promoter, an early pan-neuronal marker, and crossed this line with a previously described knock-in line in which nuclear GFP is expressed from the Tis21 promoter, a pan-neurogenic progenitor marker. Mitotic Tis21-positive basal progenitors nearly always divided symmetrically, generating two neurons, but, in contrast to symmetrically dividing apical progenitors, lacked apical-basal polarity and showed a nearly randomized cleavage plane orientation. Moreover, the appearance of beta-III-tubulin–driven GFP fluorescence in basal progenitor-derived neurons, in contrast to that in apical progenitor-derived neurons, was so rapid that it suggested the initiation of the neuronal phenotype already in the progenitor. Our observations imply that (i) the loss of apical-basal polarity restricts neuronal progenitors to the symmetric mode of cell division, and that (ii) basal progenitors initiate the expression of neuronal phenotype already before mitosis, in contrast to apical progenitors

    The role of glucocorticoids in the induction of zinc-α2-glycoprotein expression in adipose tissue in cancer cachexia

    Get PDF
    Loss of adipose tissue in cancer cachexia in mice bearing the MAC16 tumour arises from an increased lipid mobilisation through increased expression of zinc-α2-glycoprotein (ZAG) in white (WAT) and brown (BAT) adipose tissue. Glucocorticoids have been suggested to increase ZAG expression, and this study examines their role in cachexia and the mechanisms involved. In mice bearing the MAC16 tumour, serum cortisol concentrations increased in parallel with weight loss, and the glucocorticoid receptor antagonist RU38486 (25 mg kg−1) attenuated both the loss of body weight and ZAG expression in WAT. Dexamethasone (66 μg kg−1) administration to normal mice produced a six-fold increase in ZAG expression in both WAT and BAT, which was also attenuated by RU38486. In vitro studies using 3T3-L1 adipocytes showed dexamethasone (1.68 μM) to stimulate lipolysis and increase ZAG expression, and both were attenuated by RU38486 (10 μM), anti-ZAG antibody (1 μgml−1), and the β3-adrenoreceptor (β3-AR) antagonist SR59230A (10 μM). Zinc-α2-glycoprotein also increased its own expression and this was attenuated by SR59230A, suggesting that it was mediated through the β3-AR. This suggests that glucocorticoids stimulate lipolysis through an increase in ZAG expression, and that they are responsible for the increase in ZAG expression seen in adipose tissue of cachectic mice

    HAMSTER: visualizing microarray experiments as a set of minimum spanning trees

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Visualization tools allow researchers to obtain a global view of the interrelationships between the probes or experiments of a gene expression (<it>e.g. microarray</it>) data set. Some existing methods include hierarchical clustering and k-means. In recent years, others have proposed applying minimum spanning trees (MST) for microarray clustering. Although MST-based clustering is formally equivalent to the dendrograms produced by hierarchical clustering under certain conditions; visually they can be quite different.</p> <p>Methods</p> <p>HAMSTER (Helpful Abstraction using Minimum Spanning Trees for Expression Relations) is an open source system for generating a <b>set </b>of MSTs from the experiments of a microarray data set. While previous works have generated a single MST from a data set for data clustering, we recursively merge experiments and repeat this process to obtain a set of MSTs for data visualization. Depending on the parameters chosen, each tree is analogous to a snapshot of one step of the hierarchical clustering process. We scored and ranked these trees using one of three proposed schemes. HAMSTER is implemented in C++ and makes use of Graphviz for laying out each MST.</p> <p>Results</p> <p>We report on the running time of HAMSTER and demonstrate using data sets from the NCBI Gene Expression Omnibus (GEO) that the images created by HAMSTER offer insights that differ from the dendrograms of hierarchical clustering. In addition to the C++ program which is available as open source, we also provided a web-based version (HAMSTER<sup>+</sup>) which allows users to apply our system through a web browser without any computer programming knowledge.</p> <p>Conclusion</p> <p>Researchers may find it helpful to include HAMSTER in their microarray analysis workflow as it can offer insights that differ from hierarchical clustering. We believe that HAMSTER would be useful for certain types of gradient data sets (e.g time-series data) and data that indicate relationships between cells/tissues. Both the source and the web server variant of HAMSTER are available from <url>http://hamster.cbrc.jp/</url>.</p

    Disease surveillance using a hidden Markov model

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

    MyD88 Dependent Signaling Contributes to Protective Host Defense against Burkholderia pseudomallei

    Get PDF
    Background: Toll-like receptors (TLRs) have a central role in the recognition of pathogens and the initiation of the innate immune response. Myeloid differentiation primary-response gene 88 (MyD88) and TIR-domain-containing adaptor protein inducing IFNb (TRIF) are regarded as the key signaling adaptor proteins for TLRs. Melioidosis, which is endemic in SE-Asia, is a severe infection caused by the gram-negative bacterium Burkholderia pseudomallei. We here aimed to characterize the role of MyD88 and TRIF in host defense against melioidosis. Methodology and Principal Findings: First, we found that MyD88, but not TRIF, deficient whole blood leukocytes released less TNFa upon stimulation with B. pseudomallei compared to wild-type (WT) cells. Thereafter we inoculated MyD88 knockout (KO), TRIF mutant and WT mice intranasally with B. pseudomallei and found that MyD88 KO, but not TRIF mutant mice demonstrated a strongly accelerated lethality, which was accompanied by significantly increased bacterial loads in lungs, liver and blood, and grossly enhanced liver damage compared to WT mice. The decreased bacterial clearance capacity of MyD88 KO mice was accompanied by a markedly reduced early pulmonary neutrophil recruitment and a diminished activation of neutrophils after infection with B. pseudomallei. MyD88 KO leukocytes displayed an unaltered capacity to phagocytose and kill B. pseudomallei in vitro. Conclusions: MyD88 dependent signaling, but not TRIF dependent signaling, contributes to a protective host respons

    Active learning and optimal climate policy

    Get PDF
    This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

    MALDI-TOF MS Enables the Rapid Identification of the Major Molecular Types within the Cryptococcus neoformans/C. gattii Species Complex

    Get PDF
    BACKGROUND: The Cryptococcus neoformans/C. gattii species complex comprises two sibling species that are divided into eight major molecular types, C. neoformans VNI to VNIV and C. gattii VGI to VGIV. These genotypes differ in host range, epidemiology, virulence, antifungal susceptibility and geographic distribution. The currently used phenotypic and molecular identification methods for the species/molecular types are time consuming and expensive. As Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) offers an effective alternative for the rapid identification of microorganisms, the objective of this study was to examine its potential for the identification of C. neoformans and C. gattii strains at the intra- and inter-species level. METHODOLOGY: Protein extracts obtained via the formic acid extraction method of 164 C. neoformans/C. gattii isolates, including four inter-species hybrids, were studied. RESULTS: The obtained mass spectra correctly identified 100% of all studied isolates, grouped each isolate according to the currently recognized species, C. neoformans and C. gattii, and detected potential hybrids. In addition, all isolates were clearly separated according to their major molecular type, generating greater spectral differences among the C. neoformans molecular types than the C. gattii molecular types, most likely reflecting a closer phylogenetic relationship between the latter. The number of colonies used and the incubation length did not affect the results. No spectra were obtained from intact yeast cells. An extended validated spectral library containing spectra of all eight major molecular types was established. CONCLUSIONS: MALDI-TOF MS is a rapid identification tool for the correct recognition of the two currently recognized human pathogenic Cryptococcus species and offers a simple method for the separation of the eight major molecular types and the detection of hybrid strains within this species complex in the clinical laboratory. The obtained mass spectra provide further evidence that the major molecular types warrant variety or even species status
    corecore