Screening of the antioxidant, antimicrobial and DNA damage protection potentials of the aqueous extract of Asplenium ceterach DC.

In this study, in vitro antioxidant, antimicrobial and DNA damage protection potentials of the aqueous extract of Asplenium ceterach was firstly evaluated in addition to its total phenolic and flavonoid contents. Antioxidant activity was determined by five complementary test systems named β- carotene/linoleic acid, 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging, reducing power, chelating effect and phosphomolibdenum methods. Except for chelating effect assay, the extract exhibited remarkable activity potential. Antimicrobial activity was determined by agar-well diffusion and minimum inhibitory concentration tests. In this case, Shigella dysenteriae and Staphylococcus aureus were found to be the most sensitive microorganisms. According to the electrophoretic pattern of pBR322 plasmid DNA after treatment with UV and H2O2, supercoiled DNA was successfully protected in the presence of 20 mg/ml or above concentrations of aqueous extract.Key words: Antioxidant activity, antimicrobial activity, DNA damage protection, Asplenium ceterach

Stage managing bipolar disorder.

OBJECTIVES: Clinical staging is widespread in medicine - it informs prognosis, clinical course, and treatment, and assists individualized care. Staging places an individual on a probabilistic continuum of increasing potential disease severity, ranging from clinically at-risk or latency stage through first threshold episode of illness or recurrence, and, finally, to late or end-stage disease. The aim of the present paper was to examine and update the evidence regarding staging in bipolar disorder, and how this might inform targeted and individualized intervention approaches. METHODS: We provide a narrative review of the relevant information. RESULTS: In bipolar disorder, the validity of staging is informed by a range of findings that accompany illness progression, including neuroimaging data suggesting incremental volume loss, cognitive changes, and a declining likelihood of response to pharmacological and psychosocial treatments. Staging informs the adoption of a number of approaches, including the active promotion of both indicated prevention for at-risk individuals and early intervention strategies for newly diagnosed individuals, and the tailored implementation of treatments according to the stage of illness. CONCLUSIONS: The nature of bipolar disorder implies the presence of an active process of neuroprogression that is considered to be at least partly mediated by inflammation, oxidative stress, apoptosis, and changes in neurogenesis. It further supports the concept of neuroprotection, in that a diversity of agents have putative effects against these molecular targets. Clinically, staging suggests that the at-risk state or first episode is a period that requires particularly active and broad-based treatment, consistent with the hope that the temporal trajectory of the illness can be altered. Prompt treatment may be potentially neuroprotective and attenuate the neurostructural and neurocognitive changes that emerge with chronicity. Staging highlights the need for interventions at a service delivery level and implementing treatments at the earliest stage of illness possible

Simulation of Hyperspectral Images

A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data

Optical/Near-Infrared Observations of GRO J1744-28

We present results from a series of optical (g and r-band) and near-infrared (K'-band) observations of the region of the sky including the entire XTE and ROSAT error circles for the ``Bursting Pulsar'' GRO J1744-28. These data were taken with the Astrophysical Research Consortium's 3.5-m telescope at Apache Point Observatory and with the 2.2-m telescope at the European Southern Observatory. We see no new object, nor any significant brightening of any known object, in these error circles, with the exception of an object detected in our 8 February 1996 image. This object has already been proposed as a near-infrared counterpart to GRO J1744-28. While it is seen in only two of our ten 8 February frames, there is no evidence that this is an instrumental artifact, suggesting the possibility of near-infrared flares from GRO J1744-28, similar to those that have been reported from the Rapid Burster. The distance to the ``Bursting Pulsar'' must be more than 2 kpc, and we suggest that it is more than 7 kpc.Comment: 21 pages, 5 JPEG plates, 2 postscript figures. This paper will appear in the May 1, 1997 edition of the Astrophysical Journa

Improving the Estimation of Star formation Rates and Stellar Population Ages of High-redshift Galaxies from Broadband Photometry

We explore methods to improve the estimates of star formation rates and mean stellar population ages from broadband photometry of high redshift star-forming galaxies. We use synthetic spectral templates with a variety of simple parametric star formation histories to fit broadband spectral energy distributions. These parametric models are used to infer ages, star formation rates and stellar masses for a mock data set drawn from a hierarchical semi-analytic model of galaxy evolution. Traditional parametric models generally assume an exponentially declining rate of star-formation after an initial instantaneous rise. Our results show that star formation histories with a much more gradual rise in the star formation rate are likely to be better templates, and are likely to give better overall estimates of the age distribution and star formation rate distribution of Lyman break galaxies. For B- and V-dropouts, we find the best simple parametric model to be one where the star formation rate increases linearly with time. The exponentially-declining model overpredicts the age by 100 % and 120 % for B- and V-dropouts, on average, while for a linearly-increasing model, the age is overpredicted by 9 % and 16 %, respectively. Similarly, the exponential model underpredicts star-formation rates by 56 % and 60 %, while the linearly-increasing model underpredicts by 15 % 22 %, respectively. For U-dropouts, the models where the star-formation rate has a peak (near z ~ 3) provide the best match for age -- overprediction is reduced from 110 % to 26 % -- and star-formation rate -- underprediction is reduced from 58 % to 22 %. We classify different types of star-formation histories in the semi-analytic models and show how the biases behave for the different classes. We also provide two-band calibration formulae for stellar mass and star formation rate estimations.Comment: 28 pages, 7 figures, minor changes; published in Ap

Grist: Grid-based Data Mining for Astronomy

The Grist project is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed grid services controlled by a work ow system, compliant with standards emerging from the grid computing, web services, and virtual observatory communities. This new technology is being used to find high redshift quasars, study peculiar variable objects, search for transients in real time, and fit SDSS QSO spectra to measure black hole masses. Grist services are also a component of the "hyperatlas" project to serve high-resolution multi-wavelength imagery over the Internet. In support of these science and outreach objectives, the Grist framework will provide the enabling fabric to tie together distributed grid services in the areas of data access, federation, mining, subsetting, source extraction, image mosaicking, statistics, and visualization

Protocol and rationale-the efficacy of minocycline as an adjunctive treatment for major depressive disorder: a double blind, randomised, placebo controlled trial

While current pharmacotherapies are efficacious, there remain a clear shortfall between symptom remission and functional recovery. With the explosion in our understanding of the biology of these disorders, the time is ripe for the investigation of novel therapies. Recently depression is conceptualized as an immune-inflammatory and nitro-oxidative stress related disorder. Minocycline is a tetracycline antibiotic that has anti-inflammatory, pro-oxidant, glutamatergic, neurotrophic and neuroprotective properties that make it a viable target to explore as a new therapy. This double blind, randomised, placebo controlled adjunctive trial will investigate the benefits of 200 mg/day of minocycline treatment, in addition to any usual treatment, as an adjunctive treatment for moderate-severe major depressive disorder. Sixty adults are being randomised to 12 weeks of treatment (with a 4 week follow-up post-discontinuation). The primary outcome measure for the study is mean change on the Montgomery-Asberg Depression Rating Scale (MADRS), with secondary outcomes including the Social and Occupational Functioning Assessment Scale (SOFAS), Clinical Global Impressions (CGI), Hamilton Rating Scale for Anxiety (HAM-A), Patient Global Impression (PGI), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) and Range of Impaired Functioning Tool (LIFE-RIFT). Biomarker analyses will also be conducted at baseline and week 12. The study has the potential to provide new treatment targets, both by showing efficacy with a new class of \u27antidepressant\u27 but also through the analysis of biomarkers that may further inform our understanding of the pathophysiology of unipolar depression