Gridded and direct Epoch of Reionisation bispectrum estimates using the Murchison Widefield Array

We apply two methods to estimate the 21~cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly-spaced triangles of antenna tiles, as well as an estimate based on data gridded to the $uv$-plane. The direct and gridded bispectrum estimators are applied to 21 hours of high-band (167--197~MHz; $z$=6.2--7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 hours, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21~cm bispectrum may be accessible in less time than the 21~cm power spectrum for some wave modes, with detections in hundreds of hours.Comment: 19 pages, 10 figures, accepted for publication in PAS

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

De novo mutations in SMCHD1 cause Bosma arhinia microphthalmia syndrome and abrogate nasal development

Bosma arhinia microphthalmia syndrome (BAMS) is an extremely rare and striking condition characterized by complete absence of the nose with or without ocular defects. We report here that missense mutations in the epigenetic regulator SMCHD1 mapping to the extended ATPase domain of the encoded protein cause BAMS in all 14 cases studied. All mutations were de novo where parental DNA was available. Biochemical tests and in vivo assays in Xenopus laevis embryos suggest that these mutations may behave as gain-of-function alleles. This finding is in contrast to the loss-of-function mutations in SMCHD1 that have been associated with facioscapulohumeral muscular dystrophy (FSHD) type 2. Our results establish SMCHD1 as a key player in nasal development and provide biochemical insight into its enzymatic function that may be exploited for development of therapeutics for FSHD

Robust statistics towards detection of the 21 cm signal from the Epoch of Reionization

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionization (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains different systematic biases and errors to the typical approach to estimating the fluctuation power spectrum. Extraction of histograms of visibilities allows moments analysis to be used to discriminate foregrounds from 21 cm signal and thermal noise. We use the information available in the histograms, along with the statistical dis-similarity of foregrounds from two independent observing fields, to robustly separate foregrounds from cosmological signal, while making no assumptions about the Gaussianity of the signal. Using two independent observing fields to robustly discriminate signal from foregrounds is crucial for the analysis presented in this paper. We apply the techniques to 13 h of Murchison Widefield Array EoR data over two observing fields. We compare the output to that obtained with a comparative power spectrum estimation method, and demonstrate the reduced foreground contamination using this approach. Using the second moment obtained directly from the KDE distribution functions yields a factor of 2-3 improvement in power for k < 0.3 h Mpc-1 compared with a matched delay space power estimator, while weighting data by additional statistics does not offer significant improvement beyond that available for thermal noise-only weights

Functional epigenomics approach to identify methylated candidate tumour suppressor genes in renal cell carcinoma

Promoter region hypermethylation and transcriptional silencing is a frequent cause of tumour suppressor gene (TSG) inactivation in many human cancers. Previously, to identify candidate epigenetically inactivated TSGs in renal cell carcinoma (RCC), we monitored changes in gene expression in four RCC cell lines after treatment with the demethylating agent 5-azacytidine. This enabled us to identify HAI-2/SPINT2 as a novel epigenetically inactivated candidate RCC TSG. To identify further candidate TSGs, we undertook bioinformatic and molecular genetic evaluation of a further 60 genes differentially expressed after demethylation. In addition to HAI-2/SPINT2, four genes (PLAU, CDH1, IGFB3 and MT1G) had previously been shown to undergo promoter methylation in RCC. After bioinformatic prioritisation, expression and/or methylation analysis of RCC cell lines±primary tumours was performed for 34 genes. KRT19 and CXCL16 were methylated in RCC cell lines and primary RCC; however, 22 genes were differentially expressed after demethylation but did not show primary tumour-specific methylation (methylated in normal tissue (n=1); methylated only in RCC cell lines (n=9) and not methylated in RCC cell lines (n=12)). Re-expression of CXCL16 reduced growth of an RCC cell line in vitro. In a summary, a functional epigenomic analysis of four RCC cell lines using microarrays representing 11 000 human genes yielded both known and novel candidate TSGs epigenetically inactivated in RCC, suggesting that this is valid strategy for the identification of novel TSGs and biomarkers

Cystinosin, MPDU1, SWEETs and KDELR Belong to a Well-Defined Protein Family with Putative Function of Cargo Receptors Involved in Vesicle Trafficking

Classification of proteins into families based on remote homology often helps prediction of their biological function. Here we describe prediction of protein cargo receptors involved in vesicle formation and protein trafficking. Hidden Markov model profile-to-profile searches in protein databases using endoplasmic reticulum lumen protein retaining receptors (KDEL, Erd2) as query reveal a large and diverse family of proteins with seven transmembrane helices and common topology and, most likely, similar function. Their coding genes exist in all eukaryota and in several prokaryota. Some are responsible for metabolic diseases (cystinosis, congenital disorder of glycosylation), others are candidate genes for genetic disorders (cleft lip and palate, certain forms of cancer) or solute uptake and efflux (SWEETs) and many have not yet been assigned a function. Comparison with the properties of KDEL receptors suggests that the family members could be involved in protein trafficking and serve as cargo receptors. This prediction sheds new light on a range of biologically, medically and agronomically important proteins and could open the way to discovering the function of many genes not yet annotated. Experimental testing is suggested

Paired Associative Stimulation of the Auditory System: A Proof-Of-Principle Study

Background Paired associative stimulation (PAS) consisting of repeated application of transcranial magnetic stimulation (TMS) pulses and contingent exteroceptive stimuli has been shown to induce neuroplastic effects in the motor and somatosensory system. The objective was to investigate whether the auditory system can be modulated by PAS. Methods Acoustic stimuli (4 kHz) were paired with TMS of the auditory cortex with intervals of either 45 ms (PAS(45 ms)) or 10 ms (PAS(10 ms)). Two-hundred paired stimuli were applied at 0.1 Hz and effects were compared with low frequency repetitive TMS (rTMS) at 0.1 Hz (200 stimuli) and 1 Hz (1000 stimuli) in eleven healthy students. Auditory cortex excitability was measured before and after the interventions by long latency auditory evoked potentials (AEPs) for the tone (4 kHz) used in the pairing, and a control tone (1 kHz) in a within subjects design. Results Amplitudes of the N1-P2 complex were reduced for the 4 kHz tone after both PAS(45 ms) and PAS(10 ms), but not after the 0.1 Hz and 1 Hz rTMS protocols with more pronounced effects for PAS(45 ms). Similar, but less pronounced effects were observed for the 1 kHz control tone. Conclusion These findings indicate that paired associative stimulation may induce tonotopically specific and also tone unspecific human auditory cortex plasticity