Comparison of manual and semi-automated delineation of regions of interest for radioligand PET imaging analysis

BACKGROUND As imaging centers produce higher resolution research scans, the number of man-hours required to process regional data has become a major concern. Comparison of automated vs. manual methodology has not been reported for functional imaging. We explored validation of using automation to delineate regions of interest on positron emission tomography (PET) scans. The purpose of this study was to ascertain improvements in image processing time and reproducibility of a semi-automated brain region extraction (SABRE) method over manual delineation of regions of interest (ROIs). METHODS We compared 2 sets of partial volume corrected serotonin 1a receptor binding potentials (BPs) resulting from manual vs. semi-automated methods. BPs were obtained from subjects meeting consensus criteria for frontotemporal degeneration and from age- and gender-matched healthy controls. Two trained raters provided each set of data to conduct comparisons of inter-rater mean image processing time, rank order of BPs for 9 PET scans, intra- and inter-rater intraclass correlation coefficients (ICC), repeatability coefficients (RC), percentages of the average parameter value (RM%), and effect sizes of either method. RESULTS SABRE saved approximately 3 hours of processing time per PET subject over manual delineation (p 0.8) for both methods. RC and RM% were lower for the manual method across all ROIs, indicating less intra-rater variance across PET subjects' BPs. CONCLUSION SABRE demonstrated significant time savings and no significant difference in reproducibility over manual methods, justifying the use of SABRE in serotonin 1a receptor radioligand PET imaging analysis. This implies that semi-automated ROI delineation is a valid methodology for future PET imaging analysis

Preparation of highly and generally enriched mammalian tissues for solid state NMR.

An appreciable level of isotope labelling is essential for future NMR structure elucidation of mammalian biomaterials, which are either poorly expressed, or unexpressable, using micro-organisms. We present a detailed protocol for high level (13)C enrichment even in slow turnover murine biomaterials (fur keratin), using a customized diet supplemented with commercial labelled algal hydrolysate and formulated as a gel to minimize wastage, which female mice consumed during pregnancy and lactation. This procedure produced approximately eightfold higher fur keratin labelling in pups, exposed in utero and throughout life to label, than in adults exposed for the same period, showing both the effectiveness, and necessity, of this approach.The authors would like to acknowledge funding from the Biotechnology and Biological Sciences Research Council for DGR and RR; Engineering and Physical Sciences Research Council for WYC and VWCW; National Institute of Health Research for RAB.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s10858-015-9977-

Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples

Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples, or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism. Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects can be applied to all studies, even those pursued with degraded samples

Radiological and clinical features of vein of Galen malformations.

BackgroundVein of Galen malformations (VOGMs) are rare and complex congenital arteriovenous fistulas. The clinical and radiological features of VOGMs and their relation to clinical outcomes are not fully characterized.ObjectiveTo examine the clinical and radiological features of VOGMs and the predictors of outcome in patients.MethodsWe retrospectively reviewed the available imaging and medical records of all patients with VOGMs treated at the University of California, San Francisco between 1986 and 2013. Radiological and clinical features were identified. We applied the modified Rankin Scale to determine functional outcome by chart review. Predictors of outcome were assessed by χ(2) analyses.ResultsForty-one cases were confirmed as VOGM. Most patients (78%) had been diagnosed with VOGM in the first year of life. Age at treatment was bimodally distributed, with predominantly urgent embolization at <10 days of age and elective embolization after 1 year of age. Patients commonly presented with hydrocephalus (65.9%) and congestive heart failure (61.0%). Mixed-type (31.7%) VOGM was more common in our cohort than purely mural (29.3%) or choroidal (26.8%) types. The most common feeding arteries were the choroidal and posterior cerebral arteries. Transarterial embolization with coils was the most common technique used to treat VOGMs at our institution. Functional outcome was normal or only mildly disabled in 50% of the cases at last follow-up (median=3 years, range=0-23 years). Younger age at first diagnosis, congestive heart failure, and seizures were predictive of adverse clinical outcome. The survival rate in our sample was 78.0% and complete thrombosis of the VOGM was achieved in 62.5% of patients.ConclusionsVOGMs continue to be challenging to treat and manage. Nonetheless, endovascular approaches to treatment are continuing to be refined and improved, with increasing success. The neurodevelopmental outcomes of affected children whose VOGMs are treated may be good in many cases

Machine Learning for the New York City Power Grid

Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce (1) feeder failure rankings, (2) cable, joint, terminator, and transformer rankings, (3) feeder Mean Time Between Failure (MTBF) estimates, and (4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or real-time, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City's electrical grid

NMR spectroscopy of native and in vitro tissues implicates polyADP ribose in biomineralization.

Nuclear magnetic resonance (NMR) spectroscopy is useful to determine molecular structure in tissues grown in vitro only if their fidelity, relative to native tissue, can be established. Here, we use multidimensional NMR spectra of animal and in vitro model tissues as fingerprints of their respective molecular structures, allowing us to compare the intact tissues at atomic length scales. To obtain spectra from animal tissues, we developed a heavy mouse enriched by about 20% in the NMR-active isotopes carbon-13 and nitrogen-15. The resulting spectra allowed us to refine an in vitro model of developing bone and to probe its detailed structure. The identification of an unexpected molecule, poly(adenosine diphosphate ribose), that may be implicated in calcification of the bone matrix, illustrates the analytical power of this approach

An emerging PB2-627 polymorphism increases the pandemic potential of avian influenza virus by breaking through ANP32 host restriction in mammalian and avian hosts

Alterations in the PB2-627 domain could substantially increase the risk of an avian influenza virus (AIV) pandemic. So far, a well-known mammalian mutation PB2-E627K has not been maintained in AIV in poultry, which limits the spread of AIVs from avian to humans. Here, we discovered a variant, PB2-627V, which combines the properties of avian-like PB2-627E and human-like PB2-627K, overcoming host restrictions and posing a risk for human pandemics. Specifically, by screening the global PB2 sequences, we discovered a new independent cluster with PB2-627V emerged in the 2010s, which is prevalent in various avian, mammalian, and human isolates of AIVs, including H9N2, H7N9, H3N8, 2.3.4.4b H5N1, and other subtypes. And, the increasing prevalence of PB2-627V in poultry is accompanied by a rise in human infection cases with this variant. Then we systematically assessed its host adaptation, fitness, and transmissibility across three subtypes of AIVs (H9N2, H7N9, and H3N8) in different host models, including avian and human cells, chickens, mice, and ferrets where infections naturally occur. We found that PB2-627V facilitates AIVs to efficiently infect and replicate in chickens and mice by utilizing both avian- and human-origin ANP32A proteins. Importantly, and like PB2-627K, PB2-627V promotes efficient transmission between ferrets through respiratory droplets. Deep sequencing in passaged chicken samples and transmitted ferret samples indicates that PB2-627V remains stable across the two distinct hosts and has a high potential for long-term prevalence in avian species. Therefore, the mutation has the ability to continue spreading among poultry and can also overcome the barrier between birds and humans, greatly enhancing the likelihood of AIVs infecting humans. Given the escalating global spread of AIVs, it is crucial to closely monitor influenza viruses carrying PB2-627V to prevent a pandemic

Genome-wide expression assay comparison across frozen and fixed postmortem brain tissue samples

<p>Abstract</p> <p>Background</p> <p>Gene expression assays have been shown to yield high quality genome-wide data from partially degraded RNA samples. However, these methods have not yet been applied to postmortem human brain tissue, despite their potential to overcome poor RNA quality and other technical limitations inherent in many assays. We compared cDNA-mediated annealing, selection, and ligation (DASL)- and <it>in vitro </it>transcription (IVT)-based genome-wide expression profiling assays on RNA samples from artificially degraded reference pools, frozen brain tissue, and formalin-fixed brain tissue.</p> <p>Results</p> <p>The DASL-based platform produced expression results of greater reliability than the IVT-based platform in artificially degraded reference brain RNA and RNA from frozen tissue-based samples. Although data associated with a small sample of formalin-fixed RNA samples were poor when obtained from both assays, the DASL-based platform exhibited greater reliability in a subset of probes and samples.</p> <p>Conclusions</p> <p>Our results suggest that the DASL-based gene expression-profiling platform may confer some advantages on mRNA assays of the brain over traditional IVT-based methods. We ultimately consider the implications of these results on investigations of neuropsychiatric disorders.</p

Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10(-10)), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10(-10)) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10(-10)) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.Swedish Research Council et al.Manuscrip

Search of the Orion spur for continuous gravitational waves using a loosely coherent algorithm on data from LIGO interferometers

We report results of a wideband search for periodic gravitational waves from isolated neutron stars within the Orion spur towards both the inner and outer regions of our Galaxy. As gravitational waves interact very weakly with matter, the search is unimpeded by dust and concentrations of stars. One search disk (A) is 6.87° in diameter and centered on 20h10m54.71s+33°33′25.29′′, and the other (B) is 7.45° in diameter and centered on 8h35m20.61s-46°49′25.151′′. We explored the frequency range of 50-1500 Hz and frequency derivative from 0 to -5×10-9 Hz/s. A multistage, loosely coherent search program allowed probing more deeply than before in these two regions, while increasing coherence length with every stage. Rigorous follow-up parameters have winnowed the initial coincidence set to only 70 candidates, to be examined manually. None of those 70 candidates proved to be consistent with an isolated gravitational-wave emitter, and 95% confidence level upper limits were placed on continuous-wave strain amplitudes. Near 169 Hz we achieve our lowest 95% C.L. upper limit on the worst-case linearly polarized strain amplitude h0 of 6.3×10-25, while at the high end of our frequency range we achieve a worst-case upper limit of 3.4×10-24 for all polarizations and sky locations. © 2016 American Physical Society