Despite decades of intensive research, the development of a diagnostic test for major depressive disorder (MDD) had proven to be a formidable and elusive task, with all individual marker-based approaches yielding insufficient sensitivity and specificity for clinical use. In the present work, we examined the diagnostic performance of a multi-assay, serum-based test in two independent samples of patients with MDD. Serum levels of nine biomarkers (alpha1 antitrypsin, apolipoprotein CIII, brain-derived neurotrophic factor, cortisol, epidermal growth factor, myeloperoxidase, prolactin, resistin and soluble tumor necrosis factor alpha receptor type II) in peripheral blood were measured in two samples of MDD patients, and one of the non-depressed control subjects. Biomarkers measured were agreed upon a priori, and were selected on the basis of previous exploratory analyses in separate patient/control samples. Individual assay values were combined mathematically to yield an MDDScore. A 'positive' test, (consistent with the presence of MDD) was defined as an MDDScore of 50 or greater. For the Pilot Study, 36 MDD patients were recruited along with 43 non-depressed subjects. In this sample, the test demonstrated a sensitivity and specificity of 91.7% and 81.3%, respectively, in differentiating between the two groups. The Replication Study involved 34 MDD subjects, and yielded nearly identical sensitivity and specificity (91.1% and 81%, respectively). The results of the present study suggest that this test can differentiate MDD subjects from non-depressed controls with adequate sensitivity and specificity. Further research is needed to confirm the performance of the test across various age and ethnic groups, and in different clinical settings.

A two-dimensional, J-resolved magnetic resonance spectroscopic extraction approach was developed employing GAMMA-simulated, LCModel basis-sets. In this approach, a two-dimensional J-resolved (2D-JPRESS) dataset was resolved into a series of one-dimensional spectra where each spectrum was modeled and fitted with its theoretically customized LCModel template. Metabolite levels were derived from the total integral across the J-series of spectra for each metabolite. Phantoms containing physiologic concentrations of the major brain chemicals were used for validation. Varying concentrations of glutamate and glutamine were evaluated at and around their accepted in vivo concentrations in order to compare the accuracy and precision of our method with 30 ms PRESS. We also assessed 2D-JPRESS and 30 ms PRESS in vivo, in a single voxel within the parieto-occipital cortex by scanning ten healthy volunteers once and a single healthy volunteer over nine repeated measures. Phantom studies demonstrated that serial fitting of 2D-JPRESS spectra with simulated LCModel basis sets provided accurate concentration estimates for common metabolites including glutamate and glutamine. Our in vivo results using 2D-JPRESS suggested superior reproducibility in measuring glutamine and glutamate relative to 30 ms PRESS. These novel methods have clear implications for clinical and research studies seeking to understand neurochemical dysfunction.

This paper investigates whether government support can act to increase exporting activity. We use a uniquely rich data set on Irish manufacturing plants and employ an empirical strategy that combines a non-parametric matching procedure with a difference-in-differences estimator in order to deal with the potential selection problem inherent in the analysis. Our results suggest that if grants are large enough they can encourage already exporting firms to compete more effectively on the international market. However, there is little evidence that grants encourage non-exporters to start exporting. Keywords: exporting, subsidies, matching, difference-in-differences JEL classification: L2, H2, F2, O3 * The authors are grateful to Forfás for the provision of the data and to an anonymous referee and participants at ETSG 2005 in Dublin for helpful comments. Financial support through the Leverhulme Trust (Grant No. F114/BF) and the ESRC (Grant No. RES-000-22-0468) is gratefully acknowledged. Section I: IntroductionMost governments seem to take a positive view on exporting, so that the more firms in the economy export, the better. In this regard it is not surprising that many governments have taken some initiative in encouraging firms to export.Despite the potential importance of using explicit policies to promote exporting activity, there are, however, few empirical studies that have investigated this issue. One exception is the recent study by Bernard and Jensen (2004) on the determinants of exporting activity in the US which, amongst other things, investigates whether export promotion expenditures at the state level influence the decision of US plants to export or not. Their findings suggest little evidence that such policies encourage participation in the global market by US manufacturers.Arguably, export promotion expenditures on their own may not have a significant effect on exporting. Firstly, expenditure on export promotion measured at the state level may be masking firm specific differences in their ability to access information on foreign markets and, hence, heterogeneity in the ability to export. Secondly, information on foreign markets per se may not be sufficient to ensure that firms can successfully compete on the international markets. Even more important may be that firms are productive enough to do so.As the recent theoretical and empirical literature on firm level export activity argues, selling abroad involves sunk costs and it is only the "better" firms, i.e. those that are more efficient or productive, that are able to overcome these entry barriers and export successfully (Clerides et al., 1998;Bernard and Jensen, 1999;Melitz, 2003). These findings perhaps highlight the fact that other types of 1 government support specifically targeted at improving productivity related aspects of the firms' operations, to assist them in overcoming barriers to exporting, could prove more effective. Examples of such relevant support programmes include arguably subsidies, such as for R&D and training, amongst oth...

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The National Institute of Mental Health (Bethesda, MD) reports that approximately 5.2 million Americans experience post-traumatic stress disorder (PTSD) each year. PTSD can be severely debilitating and diminish quality of life for patients and those who care for them. Studies have indicated that propranolol, a beta-blocker, reduces consolidation of emotional memory. When administered immediately after a psychic trauma, it is efficacious as a prophylactic for PTSD. Use of such memory-altering drugs raises important ethical concerns, including some futuristic dystopias put forth by the President's Council on Bioethics. We think that adequate informed consent should facilitate ethical research using propranolol and, if it proves efficacious, routine treatment. Clinical evidence from studies should certainly continue to evaluate realistic concerns about possible ill effects of diminishing memory. If memory-attenuating drugs prove effective, we believe that the most immediate social concern is the over-medicalization of bad memories, and its subsequent exploitation by the pharmaceutical industry.

Proton magnetic resonance spectroscopy has the potential to provide valuable information about alterations in gamma-aminobutyric acid (GABA), glutamate (Glu), and glutamine (Gln) in psychiatric and neurological disorders. In order to use this technique effectively, it is important to establish the accuracy and reproducibility of the methodology. In this study, phantoms with known metabolite concentrations were used to compare the accuracy of 2D J-resolved MRS, single-echo 30 ms PRESS, and GABA-edited MEGA-PRESS for measuring all three aforementioned neurochemicals simultaneously. The phantoms included metabolite concentrations above and below the physiological range and scans were performed at baseline, 1 week, and 1 month time-points. For GABA measurement, MEGA-PRESS proved optimal with a measured-to-target correlation of R2 = 0.999, with J-resolved providing R2 = 0.973 for GABA. All three methods proved effective in measuring Glu with R2 = 0.987 (30 ms PRESS), R2 = 0.996 (J-resolved) and R2 = 0.910 (MEGA-PRESS). J-resolved and MEGA-PRESS yielded good results for Gln measures with respective R2 = 0.855 (J-resolved) and R2 = 0.815 (MEGA-PRESS). The 30 ms PRESS method proved ineffective in measuring GABA and Gln. When measurement stability at in vivo concentration was assessed as a function of varying spectral quality, J-resolved proved the most stable and immune to signal-to-noise and linewidth fluctuation compared to MEGA-PRESS and 30 ms PRESS.

We have used Monte Carlo simulations for a two-layered diffusive medium to investigate the effect of a superficial layer on the measurement of absorption variations from optical diffuse reflectance data processed by using: (a) a multidistance, frequency-domain method based on diffusion theory for a semi-infinite homogeneous medium; (b) a differential-pathlength-factor method based on a modified Lambert-Beer law for a homogeneous medium and (c) a two-distance, partial-pathlength method based on a modified Lambert-Beer law for a two-layered medium. Methods (a) and (b) lead to a single value for the absorption variation, whereas method (c) yields absorption variations for each layer. In the simulations, the optical coefficients of the medium were representative of those of biological tissue in the near-infrared. The thickness of the first layer was in the range 0.3-1.4 cm, and the source-detector distances were in the range 1-5 cm, which is typical of near-infrared diffuse reflectance measurements in tissue. The simulations have shown that (1) method (a) is mostly sensitive to absorption changes in the underlying layer, provided that the thickness of the superficial layer is approximately 0.6 cm or less; (2) method (b) is significantly affected by absorption changes in the superficial layer and (3) method (c) yields the absorption changes for both layers with a relatively good accuracy of approximately 4% for the superficial layer and approximately 10% for the underlying layer (provided that the absorption changes are less than 20-30% of the baseline value). We have applied all three methods of data analysis to near-infrared data collected on the forehead of a human subject during electroconvulsive therapy. Our results suggest that the multidistance method (a) and the two-distance partial-pathlength method (c) may better decouple the contributions to the optical signals that originate in deeper tissue (brain) from those that originate in more superficial tissue layers.

Racemic fluoxetine consists of R-and S-fluoxetine, which are metabolized to R-and S-norfluoxetine, respectively. This study was designed to compare brain levels achieved with R-fluoxetine to those achieved with racemic fluoxetine in healthy subjects using fluorine-19 (19-F) magnetic resonance spectroscopy (MRS). In all, 13 healthy volunteers received study drug for 5 weeks using a dosing schedule designed to achieve steady state for 20 mg/day racemic fluoxetine, 80 mg/day R-fluoxetine, or 120 mg/day R-fluoxetine. The resulting brain drug levels were measured using 19-F MRS. At 5 weeks, the racemate, 80 and 120 mg/day R-fluoxetine groups had mean brain levels of 25.5, 34.9, and 41.4 mM, respectively. In the serum, R-norfluoxetine, which is thought to be an inactive metabolite, accounted for 17, 71, and 63% of the fluoxetine/norfluoxetine concentration, respectively. When the relative proportion of active to total species in serum are taken into account, the data suggest that doses of R-fluoxetine greater than 120 mg/day would be needed to achieve brain levels of active drug comparable to 20 mg/day of racemate. The 120 mg/day R-fluoxetine group experienced a mean increase in QTc interval of 44 ms, with one individual having an increase of 89 ms, which suggests that higher doses may not be tolerable. While these data support the use of MRS to aid in defining the therapeutic dose range for drug development, they also highlight the need for additional studies with concurrent animal models to establish the validity of using serum drug/metabolite ratios to interpret MRS determined brain drug levels.