Alzheimer Disease and Oxidative Stress

Research in Alzheimer disease has recently demonstrated compelling evidence on the importance of oxidative processes in its pathogenesis. Cellular changes show that oxidative stress is an event that precedes the appearance of the hallmark pathologies of the disease, neurofibrillary tangles, and senile plaques. While it is still unclear what the initial source of the oxidative stress is in Alzheimer disease, it is likely that the process is highly dependent on redox-active transition metals such as iron and copper. Further investigation into the role that oxidative stress mechanisms seem to play in the pathogenesis of Alzheimer disease may lead to novel clinical interventions

Chandra Discovery of a 300 kpc X-ray Jet in the GPS Quasar PKS1127-145

We have discovered an X-ray jet with Chandra imaging of the z=1.187 radio-loud quasar PKS1127-145. In this paper we present the Chandra X-ray data, follow-up VLA observations, and optical imaging using the HST WFPC2. The X-ray jet contains 273+/-5 net counts in 27ksec and extends ~30 arcsec, from the quasar core, corresponding to a minimum projected linear size of ~330/h_50 kpc. The evaluation of the X-ray emission processes is complicated by the observed offsets between X-ray and radio brightness peaks. We discuss the problems posed by these observations to jet models. In addition, PKS1127-145 is a Giga-Hertz Peaked Spectrum radio source, a member of the class of radio sources suspected to be young or ``frustrated'' versions of FRI radio galaxies. However the discovery of an X-ray and radio jet extending well outside the host galaxy of PKS1127-145 suggests that activity in this and other GPS sources may be long-lived and complex.Comment: 22 pages, 11 ps figures, 1 figure in a JPG file, 3 tables. AASTEX. Accepted by The Astrophysical Journa

Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning

To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy-Richardson and variant progressive supranuclear palsy syndromes). Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy-Richardson, 52 with a progressive supranuclear palsy-cortical variant (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech/language, or progressive supranuclear palsy-corticobasal), and 17 with a progressive supranuclear palsy-subcortical variant (progressive supranuclear palsy-parkinsonism or progressive supranuclear palsy-progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation. The data supported two subtypes, each with a distinct progression of atrophy: a 'subcortical' subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a 'cortical' subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage Inference subtype with 82% of progressive supranuclear palsy-subcortical cases and 81% of progressive supranuclear palsy-Richardson cases assigned to the subcortical subtype and 82% of progressive supranuclear palsy-cortical cases assigned to the cortical subtype. The increasing stage was associated with worsening clinical scores, whilst the 'subcortical' subtype was associated with worse clinical severity scores compared to the 'cortical subtype' (progressive supranuclear palsy rating scale and Unified Parkinson's Disease Rating Scale). Validation experiments showed that subtype assignment was longitudinally stable (95% of scans were assigned to the same subtype at follow-up) and individual staging was longitudinally consistent with 90% remaining at the same stage or progressing to a later stage at follow-up. In summary, we applied Subtype and Stage Inference to structural MRI data and empirically identified two distinct subtypes of spatiotemporal atrophy in progressive supranuclear palsy. These image-based subtypes were differentially enriched for progressive supranuclear palsy clinical syndromes and showed different clinical characteristics. Being able to accurately subtype and stage progressive supranuclear palsy patients at baseline has important implications for screening patients on entry to clinical trials, as well as tracking disease progression

The role of oxidative stress in the pathogenesis of Alzheimer's disease

[ES]: La presencia de estrés oxidativo es la característica más temprana de la Enfermedad de Alzheimer (EA), lo cual proporciona un atractivo objetivo para intervenciones terapéuticas. Entre los mayores retos que se presentan actualmente están el establecimiento de la fuente de estrés oxidativo y la determinación de cómo este proceso puede influir en la etiología de la Enfermedad de Alzheimer. Este es un tema complejo, pues varios procesos, enzimáticos y no-enzimáticos, están implicados en la formación de oxígeno reactivo y otras moléculas tóxicas. En este artículo discutimos el progreso en el entendimiento de estos procesos[EN]: Oxidative stress is the earliest feature of Alzheimer disease and an attractive therapeutic target. One of the major challenges today is to establish the source of the reactive oxygen and to determine the role of oxidative stress in the etiology of Alzheimer disease. This is a complex issue since a variety of enzymatic and non-enzymatic processes are involved in the formation of reactive oxygen and other toxic molecules. In this review, we discuss progress in the understanding of these processes.Peer reviewe

Deniable Attribute Based Encryption for Branching Programs from LWE

Deniable encryption (Canetti et al. CRYPTO \u2797) is an intriguing primitive that provides a security guarantee against not only eavesdropping attacks as required by semantic security, but also stronger coercion attacks performed after the fact. The concept of deniability has later demonstrated useful and powerful in many other contexts, such as leakage resilience, adaptive security of protocols, and security against selective opening attacks. Despite its conceptual usefulness, our understanding of how to construct deniable primitives under standard assumptions is restricted. In particular from standard lattice assumptions, i.e. Learning with Errors (LWE), we have only flexibly and non-negligible advantage deniable public-key encryption schemes, whereas with the much stronger assumption of indistinguishable obfuscation, we can obtain at least fully sender-deniable PKE and computation. How to achieve deniability for other more advanced encryption schemes under standard assumptions remains an interesting open question. In this work, we construct a flexibly bi-deniable Attribute-Based Encryption (ABE) scheme for all polynomial-size Branching Programs from LWE. Our techniques involve new ways of manipulating Gaussian noise that may be of independent interest, and lead to a significantly sharper analysis of noise growth in Dual Regev type encryption schemes. We hope these ideas give insight into achieving deniability and related properties for further, advanced cryptographic systems from lattice assumptions

SNR 1E 0102.2-7219 as an X-ray calibration standard in the 0.5−1.0 keV bandpass and its application to the CCD instruments aboard Chandra , Suzaku , Swift and XMM-Newton

Context. The flight calibration of the spectral response of charge-coupled device (CCD) instruments below 1.5 keV is difficult in general because of the lack of strong lines in the on-board calibration sources typically available. This calibration is also a function of time due to the effects of radiation damage on the CCDs and/or the accumulation of a contamination layer on the filters or CCDs. Aims. We desire a simple comparison of the absolute effective areas of the current generation of CCD instruments onboard the following observatories: Chandra ACIS-S3, XMM-Newton (EPIC-MOS and EPIC-pn), Suzaku XIS, and Swift XRT and a straightforward comparison of the time-dependent response of these instruments across their respective mission lifetimes. Methods. We have been using 1E 0102.2-7219, the brightest supernova remnant in the Small Magellanic Cloud, to evaluate and modify the response models of these instruments. 1E 0102.2-7219 has strong lines of O, Ne, and Mg below 1.5 keV and little or no Fe emission to complicate the spectrum. The spectrum of 1E 0102.2-7219 has been well-characterized using the RGS gratings instrument on XMM-Newton and the HETG gratings instrument on Chandra. As part of the activities of the International Astronomical Consortium for High Energy Calibration (IACHEC), we have developed a standard spectral model for 1E 0102.2-7219 and fit this model to the spectra extracted from the CCD instruments. The model is empirical in that it includes Gaussians for the identified lines, an absorption component in the Galaxy, another absorption component in the SMC, and two thermal continuum components with different temperatures. In our fits, the model is highly constrained in that only the normalizations of the four brightest lines/line complexes (the O vii Heα triplet, O viii Lyα line, the Ne ix Heα triplet, and the Ne x Lyα line) and an overall normalization are allowed to vary, while all other components are fixed. We adopted this approach to provide a straightforward comparison of the measured line fluxes at these four energies. We have examined these measured line fluxes as a function of time for each instrument after applying the most recent calibrations that account for the time-dependent response of each instrument. Results. We performed our effective area comparison with representative, early mission data when the radiation damage and contamination layers were at a minimum, except for the XMM-Newton EPIC-pn instrument which is stable in time. We found that the measured fluxes of the O vii Heαr line, the O viii Lyα line, the Ne ix Heαr line, and the Ne x Lyα line generally agree to within ±10% for all instruments, with 38 of our 48 fitted normalizations within ± 10% of the IACHEC model value. We then fit all available observations of 1E 0102.2-7219 for the CCD instruments close to the on-axis position to characterize the time dependence in the 0.5−1.0 keV band. We present the measured line normalizations as a function of time for each CCD instrument so that the users may estimate the uncertainty in their measured line fluxes for the epoch of their observations

Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer\u27s disease

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer\u27s disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score\u27s predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials

Activity of cortical and thalamic neurons during the slow (<1 Hz) rhythm in the mouse in vivo

During NREM sleep and under certain types of anaesthesia, the mammalian brain exhibits a distinctive slow (<1 Hz) rhythm. At the cellular level, this rhythm correlates with so-called UP and DOWN membrane potential states. In the neocortex, these UP and DOWN states correspond to periods of intense network activity and widespread neuronal silence, respectively, whereas in thalamocortical (TC) neurons, UP/DOWN states take on a more stereotypical oscillatory form, with UP states commencing with a low-threshold Ca2+ potential (LTCP). Whilst these properties are now well recognised for neurons in cats and rats, whether or not they are also shared by neurons in the mouse is not fully known. To address this issue, we obtained intracellular recordings from neocortical and TC neurons during the slow (<1 Hz) rhythm in anaesthetised mice. We show that UP/DOWN states in this species are broadly similar to those observed in cats and rats, with UP states in neocortical neurons being characterised by a combination of action potential output and intense synaptic activity, whereas UP states in TC neurons always commence with an LTCP. In some neocortical and TC neurons, we observed ‘spikelets’ during UP states, supporting the possible presence of electrical coupling. Lastly, we show that, upon tonic depolarisation, UP/DOWN states in TC neurons are replaced by rhythmic high-threshold bursting at ~5 Hz, as predicted by in vitro studies. Thus, UP/DOWN state generation appears to be an elemental and conserved process in mammals that underlies the slow (<1 Hz) rhythm in several species, including humans

Human Gamma Oscillations during Slow Wave Sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30–50 Hz) and high (60–120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves (“IN-phase” pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave (“ANTI-phase” pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks