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Oxidative stress is implicated in the aetiology of schizophrenia, and the antioxidant defence system (AODS) may be protective in this illness. We examined the major antioxidant glutathione (GSH) in prefrontal brain and its correlates with clinical and demographic variables in schizophrenia.
GSH levels were measured in the dorsolateral prefrontal region of 28 patients with chronic schizophrenia using a magnetic resonance spectroscopy sequence specifically adapted for GSH. We examined correlations of GSH levels with age, age at onset of illness, duration of illness, and clinical symptoms.
We found a negative correlation between GSH levels and age at onset (r = −0.46, p = 0.015), and a trend-level positive relationship between GSH and duration of illness (r = 0.34, p = 0.076).
Our findings are consistent with a possible compensatory upregulation of the AODS with longer duration of illness and suggest that the AODS may play a role in schizophrenia.
This article considers the problem of testing for an explosive bubble in financial data in the presence of time-varying volatility. We propose a sign-based variant of the Phillips, Shi, and Yu (2015, International Economic Review 56, 1043–1077) test. Unlike the original test, the sign-based test does not require bootstrap-type methods to control size in the presence of time-varying volatility. Under a locally explosive alternative, the sign-based test delivers higher power than the original test for many time-varying volatility and bubble specifications. However, since the original test can still outperform the sign-based one for some specifications, we also propose a union of rejections procedure that combines the original and sign-based tests, employing a wild bootstrap to control size. This is shown to capture most of the power available from the better performing of the two tests. We also show how a sign-based statistic can be used to date the bubble start and end points. An empirical illustration using Bitcoin price data is provided.
In the era of ALMA, we can now resolve polarization within circumstellar disks at (sub)millimeter wavelengths. While many initially hoped that these observations would map magnetic fields in disks, the observed polarization patterns indicate other possible polarization mechanisms. These alternative polarization mechanisms include Rayleigh self-scattering, grains aligning with the radiation anisotropy (k-RAT alignment), and mechanical alignment. Stephens et al. (2017) specifically showed that the polarization morphology in HL Tau changes rapidly with wavelength; the morphology is uniform at 870 μm, azimuthal at 3.1 mm, and ∼50%/50% mix of the two at 1.3 mm. Although it has been suggested that the polarized emission at 870 μm is due to scattering and at 3.1 mm is due to k-RAT alignment, both mechanisms appear to have shortcomings. Specifically, Kataoka et al. (2017) showed that scattering requires much smaller grains (10s of μm) than that suggested by other studies, while k-RAT alignment suggest a significant decrease in polarization along the minor axis, which is not seen. Studies of other disks have suggested that polarization may come from grains aligned with the magnetic fields, but these studies are inconclusive. Understanding and extracting information about the polarized emission from disks requires multi-wavelength and high resolution observations.