Sod1 deficiency reduces incubation time in mouse models of prion disease.

Prion infections, causing neurodegenerative conditions such as Creutzfeldt-Jakob disease and kuru in humans, scrapie in sheep and BSE in cattle are characterised by prolonged and variable incubation periods that are faithfully reproduced in mouse models. Incubation time is partly determined by genetic factors including polymorphisms in the prion protein gene. Quantitative trait loci studies in mice and human genome-wide association studies have confirmed that multiple genes are involved. Candidate gene approaches have also been used and identified App, Il1-r1 and Sod1 as affecting incubation times. In this study we looked for an association between App, Il1-r1 and Sod1 representative SNPs and prion disease incubation time in the Northport heterogeneous stock of mice inoculated with the Chandler/RML prion strain. No association was seen with App, however, significant associations were seen with Il1-r1 (P = 0.02) and Sod1 (P<0.0001) suggesting that polymorphisms at these loci contribute to the natural variation observed in incubation time. Furthermore, following challenge with Chandler/RML, ME7 and MRC2 prion strains, Sod1 deficient mice showed highly significant reductions in incubation time of 20, 13 and 24%, respectively. No differences were detected in Sod1 expression or activity. Our data confirm the protective role of endogenous Sod1 in prion disease

Increased mRNA expression of CDKN2A is a transcriptomic marker of clinically aggressive meningiomas

Homozygous deletion of CDKN2A/B was recently incorporated into the World Health Organization classification for grade 3 meningiomas. While this marker is overall rare in meningiomas, its relationship to other CDKN2A alterations on a transcriptomic, epigenomic, and copy number level has not yet been determined. We therefore utilized multidimensional molecular data of 1577 meningioma samples from 6 independent cohorts enriched for clinically aggressive meningiomas to comprehensively interrogate the spectrum of CDKN2A alterations through DNA methylation, copy number variation, transcriptomics, and proteomics using an integrated molecular approach. Homozygous CDKN2A/B deletions were identified in only 7.1% of cases but were associated with significantly poorer outcomes compared to tumors without these deletions. Heterozygous CDKN2A/B deletions were identified in 2.6% of cases and had similarly poor outcomes as those with homozygous deletions. Among tumors with intact CDKN2A/B (without a homozygous or heterozygous deletion), we found a distinct difference in outcome based on mRNA expression of CDKN2A, with meningiomas that had elevated mRNA expression (CDKN2Ahigh) having a significantly shorter time to recurrence. The expression of CDKN2A was independently prognostic after accounting for copy number loss and consistently increased with WHO grade and more aggressive molecular and methylation groups irrespective of cohort. Despite the discordant and mutually exclusive status of the CDKN2A gene in these groups, both CDKN2Ahigh meningiomas and meningiomas with CDKN2A deletions were enriched for similar cell cycle pathways but at different checkpoints. High mRNA expression of CDKN2A was also associated with gene hypermethylation, Rb-deficiency, and lack of response to CDK inhibition. p16 immunohistochemistry could not reliably differentiate between meningiomas with and without CDKN2A deletions but appeared to correlate better with mRNA expression. These findings support the role of CDKN2A mRNA expression as a biomarker of clinically aggressive meningiomas with potential therapeutic implications

Modern optical astronomy: technology and impact of interferometry

The present `state of the art' and the path to future progress in high spatial resolution imaging interferometry is reviewed. The review begins with a treatment of the fundamentals of stellar optical interferometry, the origin, properties, optical effects of turbulence in the Earth's atmosphere, the passive methods that are applied on a single telescope to overcome atmospheric image degradation such as speckle interferometry, and various other techniques. These topics include differential speckle interferometry, speckle spectroscopy and polarimetry, phase diversity, wavefront shearing interferometry, phase-closure methods, dark speckle imaging, as well as the limitations imposed by the detectors on the performance of speckle imaging. A brief account is given of the technological innovation of adaptive-optics (AO) to compensate such atmospheric effects on the image in real time. A major advancement involves the transition from single-aperture to the dilute-aperture interferometry using multiple telescopes. Therefore, the review deals with recent developments involving ground-based, and space-based optical arrays. Emphasis is placed on the problems specific to delay-lines, beam recombination, polarization, dispersion, fringe-tracking, bootstrapping, coherencing and cophasing, and recovery of the visibility functions. The role of AO in enhancing visibilities is also discussed. The applications of interferometry, such as imaging, astrometry, and nulling are described. The mathematical intricacies of the various `post-detection' image-processing techniques are examined critically. The review concludes with a discussion of the astrophysical importance and the perspectives of interferometry.Comment: 65 pages LaTeX file including 23 figures. Reviews of Modern Physics, 2002, to appear in April issu

Glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA): a molecularly distinct brain tumor type with recurrent NTRK gene fusions

Glioneuronal tumors are a heterogenous group of CNS neoplasms that can be challenging to accurately diagnose. Molecular methods are highly useful in classifying these tumors-distinguishing precise classes from their histological mimics and identifying previously unrecognized types of tumors. Using an unsupervised visualization approach of DNA methylation data, we identified a novel group of tumors (n = 20) that formed a cluster separate from all established CNS tumor types. Molecular analyses revealed ATRX alterations (in 16/16 cases by DNA sequencing and/or immunohistochemistry) as well as potentially targetable gene fusions involving receptor tyrosine-kinases (RTK; mostly NTRK1-3) in all of these tumors (16/16; 100%). In addition, copy number profiling showed homozygous deletions of CDKN2A/B in 55% of cases. Histological and immunohistochemical investigations revealed glioneuronal tumors with isomorphic, round and often condensed nuclei, perinuclear clearing, high mitotic activity and microvascular proliferation. Tumors were mainly located supratentorially (84%) and occurred in patients with a median age of 19 years. Survival data were limited (n = 18) but point towards a more aggressive biology as compared to other glioneuronal tumors (median progression-free survival 12.5 months). Given their molecular characteristics in addition to anaplastic features, we suggest the term glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA) to describe these tumors. In summary, our findings highlight a novel type of glioneuronal tumor driven by different RTK fusions accompanied by recurrent alterations in ATRX and homozygous deletions of CDKN2A/B. Targeted approaches such as NTRK inhibition might represent a therapeutic option for patients suffering from these tumors

The Boston criteria version 2.0 for cerebral amyloid angiopathy:a multicentre, retrospective, MRI–neuropathology diagnostic accuracy study

BACKGROUND: Cerebral amyloid angiopathy (CAA) is an age-related small vessel disease, characterised pathologically by progressive deposition of amyloid β in the cerebrovascular wall. The Boston criteria are used worldwide for the in-vivo diagnosis of CAA but have not been updated since 2010, before the emergence of additional MRI markers. We report an international collaborative study aiming to update and externally validate the Boston diagnostic criteria across the full spectrum of clinical CAA presentations. METHODS: In this multicentre, hospital-based, retrospective, MRI and neuropathology diagnostic accuracy study, we did a retrospective analysis of clinical, radiological, and histopathological data available to sites participating in the International CAA Association to formulate updated Boston criteria and establish their diagnostic accuracy across different populations and clinical presentations. Ten North American and European academic medical centres identified patients aged 50 years and older with potential CAA-related clinical presentations (ie, spontaneous intracerebral haemorrhage, cognitive impairment, or transient focal neurological episodes), available brain MRI, and histopathological assessment for CAA diagnosis. MRI scans were centrally rated at Massachusetts General Hospital (Boston, MA, USA) for haemorrhagic and non-haemorrhagic CAA markers, and brain tissue samples were rated by neuropathologists at the contributing sites. We derived the Boston criteria version 2.0 (v2.0) by selecting MRI features to optimise diagnostic specificity and sensitivity in a prespecified derivation cohort (Boston cases 1994-2012, n=159), then externally validated the criteria in a prespecified temporal validation cohort (Boston cases 2012-18, n=59) and a geographical validation cohort (non-Boston cases 2004-18; n=123), comparing accuracy of the new criteria to the currently used modified Boston criteria with histopathological assessment of CAA as the diagnostic standard. We also assessed performance of the v2.0 criteria in patients across all cohorts who had the diagnostic gold standard of brain autopsy. FINDINGS: The study protocol was finalised on Jan 15, 2017, patient identification was completed on Dec 31, 2018, and imaging analyses were completed on Sept 30, 2019. Of 401 potentially eligible patients presenting to Massachusetts General Hospital, 218 were eligible to be included in the analysis; of 160 patient datasets from other centres, 123 were included. Using the derivation cohort, we derived provisional criteria for probable CAA requiring the presence of at least two strictly lobar haemorrhagic lesions (ie, intracerebral haemorrhages, cerebral microbleeds, or foci of cortical superficial siderosis) or at least one strictly lobar haemorrhagic lesion and at least one white matter characteristic (ie, severe visible perivascular spaces in centrum semiovale or white matter hyperintensities in a multispot pattern). The sensitivity and specificity of these criteria were 74·8% (95% CI 65·4-82·7) and 84·6% (71·9-93·1) in the derivation cohort, 92·5% (79·6-98·4) and 89·5% (66·9-98·7) in the temporal validation cohort, 80·2% (70·8-87·6) and 81·5% (61·9-93·7) in the geographical validation cohort, and 74·5% (65·4-82·4) and 95·0% (83·1-99·4) in all patients who had autopsy as the diagnostic standard. The area under the receiver operating characteristic curve (AUC) was 0·797 (0·732-0·861) in the derivation cohort, 0·910 (0·828-0·992) in the temporal validation cohort, 0·808 (0·724-0·893) in the geographical validation cohort, and 0·848 (0·794-0·901) in patients who had autopsy as the diagnostic standard. The v2.0 Boston criteria for probable CAA had superior accuracy to the current Boston criteria (sensitivity 64·5% [54·9-73·4]; specificity 95·0% [83·1-99·4]; AUC 0·798 [0·741-0854]; p=0·0005 for comparison of AUC) across all individuals who had autopsy as the diagnostic standard. INTERPRETATION: The Boston criteria v2.0 incorporate emerging MRI markers of CAA to enhance sensitivity without compromising their specificity in our cohorts of patients aged 50 years and older presenting with spontaneous intracerebral haemorrhage, cognitive impairment, or transient focal neurological episodes. Future studies will be needed to determine generalisability of the v.2.0 criteria across the full range of patients and clinical presentations. FUNDING: US National Institutes of Health (R01 AG26484)

Ionized gas diagnostics from protoplanetary discs in the Orion Nebula and the abundance discrepancy problem

We present results from integral field spectroscopy with PMAS. The observed field contains: five protoplanetary discs (also known as proplyds), the high-velocity jet HH 514 and a bowshock. Spatial distribution maps are obtained for different emission line fluxes, the c(H{\beta}) coefficient, electron densities and temperatures, ionic abundances of different ions from collisionally excited lines (CELs), C2+ and O2+ abundances from recombination lines (RLs) and the abundance discrepancy factor of O2+, ADF(O2+). We find that collisional de-excitation has a major influence on the line fluxes in the proplyds. If this is not properly accounted for then physical conditions deduced from commonly used line ratios will be in error, leading to unreliable chemical abundances for these objects. We obtain the intrinsic emission of the proplyds 177-341, 170-337 and 170-334 by a direct subtraction of the background emission, though the last two present some background contamination due to their small sizes. A detailed analysis of 177-341 spectra reveals the presence of high-density gas (3.8\times10^5 cm^-3) in contrast to the typical values observed in the background gas of the nebula (3800 cm^-3). We also explore how the background subtraction could be affected by the possible opacity of the proplyd. We construct a physical model for the proplyd 177-341 finding a good agreement between the predicted and observed line ratios. Finally, we find that the use of reliable physical conditions returns an ADF(O2+) about zero for the intrinsic spectra of 177-341, while the background emission presents the typical ADF(O2+) observed in the Orion Nebula. We conclude that the presence of high-density ionized gas is severely affecting the abundances determined from CELs and, therefore, those from RLs should be considered as a better approximation to the true abundances.Comment: 22 pages, 11 figures. Accepted for publication in MNRA

The relation between the most-massive star and its parental star cluster mass

We present a thorough literature study of the most-massive star, m_max, in several young star clusters in order to assess whether or not star clusters are populated from the stellar initial mass function (IMF) by random sampling over the mass range 0.01 < m < 150 M_sol without being constrained by the cluster mass, M_ecl. The data reveal a partition of the sample into lowest mass objects (M_ecl < 10^2 M_sol), moderate mass clusters (10^2 M_sol < M_ecl < 10^3 M_sol) and rich clusters above 10^3 M_sol. Additionally, there is a plateau of a constant maximal star mass (m_max ~ 25 M_sol) for clusters with masses between 10^3 M_sol and 4 10^3 M_sol. Statistical tests of this data set reveal that the hypothesis of random sampling from the IMF between 0.01 and 150 M_sol is highly unlikely for star clusters more massive than 10^2 M_sol with a probability of p ~ 2 10^-7 for the objects with M_ecl between 10^2 M_sol and 10^3 M_sol and p ~ 3 10^-9 for the more massive star clusters. Also, the spread of m_max values at a given M_ecl is smaller than expected from random sampling. We suggest that the basic physical process able to explain this dependence of stellar inventory of a star cluster on its mass may be the interplay between stellar feedback and the binding energy of the cluster-forming molecular cloud core. Given these results, it would follow that an integrated galactic initial mass function (IGIMF) sampled from such clusters would automatically be steeper in comparison to the IMF within individual star clusters.Comment: 26 pages, 13 figures, 3 tables, accepted for publication in MNRA

Sarcoma classification by DNA methylation profiling

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications