Accurate simulation of transcranial ultrasound propagation for ultrasonic neuromodulation and stimulation

Non-invasive, focal neurostimulation with ultrasound is a potentially powerful neuroscientific tool that requires effective transcranial focusing of ultrasound to develop. Time-reversal (TR) focusing using numerical simulations of transcranial ultrasound propagation can correct for the effect of the skull, but relies on accurate simulations. Here, focusing requirements for ultrasonic neurostimulation are established through a review of previously employed ultrasonic parameters, and consideration of deep brain targets. The specific limitations of finite-difference time domain (FDTD) and k-space corrected pseudospectral time domain (PSTD) schemes are tested numerically to establish the spatial points per wavelength and temporal points per period needed to achieve the desired accuracy while minimizing the computational burden. These criteria are confirmed through convergence testing of a fully simulated TR protocol using a virtual skull. The k-space PSTD scheme performed as well as, or better than, the widely used FDTD scheme across all individual error tests and in the convergence of large scale models, recommending it for use in simulated TR. Staircasing was shown to be the most serious source of error. Convergence testing indicated that higher sampling is required to achieve fine control of the pressure amplitude at the target than is needed for accurate spatial targeting

Probing cosmic dawn: Ages and star formation histories of candidate z ≥ 9 galaxies

We discuss the spectral energy distributions and physical properties of six galaxies whose photometric redshifts suggest they lie beyond a redshift z ≃ 9. Each was selected on account of a prominent excess seen in the Spitzer/IRAC 4.5 μm band which, for a redshift above z = 9.0, likely indicates the presence of a rest-frame Balmer break and a stellar component that formed earlier than a redshift z ≃ 10. In addition to constraining the earlier star formation activity on the basis of fits using stellar population models with BAGPIPES, we have undertaken the necessary, but challenging, follow-up spectroscopy for each candidate using various combinations of Keck/MOSFIRE, VLT/X-shooter, Gemini/FLAMINGOS2, and ALMA. Based on either Lyman-α or [O III] 88 μm emission, we determine a convincing redshift of z = 8.78 for GN-z-10-3 and a likely redshift of z = 9.28 for the lensed galaxy MACS0416-JD. For GN-z9-1, we conclude the case remains promising for a source beyond z ≃ 9. Together with earlier spectroscopic data for MACS1149-JD1, our analysis of this enlarged sample provides further support for a cosmic star formation history extending beyond redshifts z ≃ 10. We use our best-fitting stellar population models to reconstruct the past rest-frame UV luminosities of our sources and discuss the implications for tracing earlier progenitors of such systems with the James Webb Space Telescope

The effects of image homogenisation on simulated transcranial ultrasound propagation

Transcranial transmission of ultrasound is increasingly used in a variety of clinical and research applications, including high intensity ablation, opening the blood brain barrier, and neural stimulation. Numerical simulations of ultrasound propagation in the head are used to enable effective transcranial focusing and predict intracranial fields. Such simulations require maps of the acoustic properties of the head, which can be derived from clinical CT images. However, the spatial resolution of these images is typically coarser than the scale of heterogeneities within the skull bone, which are known to exert a major influence on ultrasound propagation. 
 
 In the present work, the impact of image related homogenisation on transcranial transmission from a single element transducer is examined using a dataset of co-registered clinical resolution CT and micro-CT images of skull sections. Reference acoustic property maps are derived from micro-CT images of cortical bone tissue. The influence of imaging resolution is examined by progressively downsampling the segmented acoustic property maps, and through comparison with maps derived from co-registered clinical CT images. The influence of different methods of segmenting the bone volume from the clinical CT images, and for resampling the clinical and micro-CT data are also examined. 
 
 Image related homogenisation is demonstrated to have a substantial effect on the transcranial transmission of ultrasound, resulting in underestimations of simulated transmission loss and time-of flight. Effects on time-of flight are due to the loss of the internal scattering microstructure of the skull, while changes in transmitted ultrasound amplitude are due to both loss of microstructure and other smoothing effects. Inflating the simulated attenuation coefficient of the skull layer reduces the error in transmitted pressure amplitude to around 40%, however this is unable to correct fully for errors in time of flight and the pressure distribution of the transmitted field.&#13

Staircase-free acoustic sources for grid-based models of wave propagation

The k-Wave MATLAB toolbox is widely used to conduct medical ultrasound simulations. It uses a Fourier collocation method to numerically solve the governing model equations, and introduces sources by adding acoustic pressure at points on an orthogonal grid. This approach introduces two errors when sources don't exactly align with the grid. These are phase errors arising from shifting source points to nearby grid nodes, and amplitude errors arising from an angular dependence in the density of source points. These two errors are collectively referred to as `staircasing'. Staircasing errors can be overcome by considering the band-limited representation of sources that arises from the use of a Fourier collocation method. To do so, sources are discretised by convolving a band-limited point source with the desired source geometry. To validate this approach, a comparison is made with current k-Wave source algorithms and with the FOCUS ultrasound simulation code. The new sources are shown to eliminate staircasing errors

The role of galaxies and AGN in reionising the IGM -- III : IGM-galaxy cross-correlations at z~6 from 8 quasar fields with DEIMOS and MUSE

We present improved results of the measurement of the correlation between galaxies and the intergalactic medium transmission at the end of reionization. We have gathered a sample of 13 spectroscopically confirmed Lyman-break galaxies (LBGs) and 21 Lyman-α emitters (LAEs) at angular separations 20 arcsec ≲ θ ≲ 10 arcmin (∼0.1–4 pMpc at z ∼ 6) from the sightlines to eight background z ≳ 6 quasars. We report for the first time the detection of an excess of Lyman-α transmission spikes at ∼10–60 cMpc from LAEs (3.2σ) and LBGs (1.9σ). We interpret the data with an improved model of the galaxy–Lyman-α transmission and two-point cross-correlations, which includes the enhanced photoionization due to clustered faint sources, enhanced gas densities around the central bright objects and spatial variations of the mean free path. The observed LAE(LBG)–Lyman-α transmission spike two-point cross-correlation function (2PCCF) constrains the luminosity-averaged escape fraction of all galaxies contributing to reionization to ⟨fesc⟩MUV−20(2σ)⁠) is necessary to reproduce the observed 2PCCF and that reionization might be driven by different sub-populations around LBGs and LAEs at z ∼ 6

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Hematoxylin and eosin stained breast histology microscopy image dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our approach utilizes several deep neural network architectures and gradient boosted trees classifier. For 4-class classification task, we report 87.2% accuracy. For 2-class classification task to detect carcinomas we report 93.8% accuracy, AUC 97.3%, and sensitivity/specificity 96.5/88.0% at the high-sensitivity operating point. To our knowledge, this approach outperforms other common methods in automated histopathological image classification. The source code for our approach is made publicly available at https://github.com/alexander-rakhlin/ICIAR2018Comment: 8 pages, 4 figure

A single low-energy, iron-poor supernova as the source of metals in the star SMSS J 031300.36-670839.3

The element abundance ratios of four low-mass stars with extremely low metallicities indicate that the gas out of which the stars formed was enriched in each case by at most a few, and potentially only one low-energy, supernova. Such supernovae yield large quantities of light elements such as carbon but very little iron. The dominance of low-energy supernovae is surprising, because it has been expected that the first stars were extremely massive, and that they disintegrated in pair-instability explosions that would rapidly enrich galaxies in iron. What has remained unclear is the yield of iron from the first supernovae, because hitherto no star is unambiguously interpreted as encapsulating the yield of a single supernova. Here we report the optical spectrum of SMSS J031300.36- 670839.3, which shows no evidence of iron (with an upper limit of 10^-7.1 times solar abundance). Based on a comparison of its abundance pattern with those of models, we conclude that the star was seeded with material from a single supernova with an original mass of ~60 Mo (and that the supernova left behind a black hole). Taken together with the previously mentioned low-metallicity stars, we conclude that low-energy supernovae were common in the early Universe, and that such supernovae yield light element enrichment with insignificant iron. Reduced stellar feedback both chemically and mechanically from low-energy supernovae would have enabled first-generation stars to form over an extended period. We speculate that such stars may perhaps have had an important role in the epoch of cosmic reionization and the chemical evolution of early galaxies.Comment: 28 pages, 6 figures, Natur

Early star-forming galaxies and the reionization of the Universe

Star forming galaxies represent a valuable tracer of cosmic history. Recent observational progress with Hubble Space Telescope has led to the discovery and study of the earliest-known galaxies corresponding to a period when the Universe was only ~800 million years old. Intense ultraviolet radiation from these early galaxies probably induced a major event in cosmic history: the reionization of intergalactic hydrogen. New techniques are being developed to understand the properties of these most distant galaxies and determine their influence on the evolution of the universe.Comment: Review article appearing in Nature. This posting reflects a submitted version of the review formatted by the authors, in accordance with Nature publication policies. For the official, published version of the review, please see http://www.nature.com/nature/archive/index.htm

Telomere disruption results in non-random formation of de novo dicentric chromosomes involving acrocentric human chromosomes

Copyright: © 2010 Stimpson et al.Genome rearrangement often produces chromosomes with two centromeres (dicentrics) that are inherently unstable because of bridge formation and breakage during cell division. However, mammalian dicentrics, and particularly those in humans, can be quite stable, usually because one centromere is functionally silenced. Molecular mechanisms of centromere inactivation are poorly understood since there are few systems to experimentally create dicentric human chromosomes. Here, we describe a human cell culture model that enriches for de novo dicentrics. We demonstrate that transient disruption of human telomere structure non-randomly produces dicentric fusions involving acrocentric chromosomes. The induced dicentrics vary in structure near fusion breakpoints and like naturally-occurring dicentrics, exhibit various inter-centromeric distances. Many functional dicentrics persist for months after formation. Even those with distantly spaced centromeres remain functionally dicentric for 20 cell generations. Other dicentrics within the population reflect centromere inactivation. In some cases, centromere inactivation occurs by an apparently epigenetic mechanism. In other dicentrics, the size of the alpha-satellite DNA array associated with CENP-A is reduced compared to the same array before dicentric formation. Extrachromosomal fragments that contained CENP-A often appear in the same cells as dicentrics. Some of these fragments are derived from the same alpha-satellite DNA array as inactivated centromeres. Our results indicate that dicentric human chromosomes undergo alternative fates after formation. Many retain two active centromeres and are stable through multiple cell divisions. Others undergo centromere inactivation. This event occurs within a broad temporal window and can involve deletion of chromatin that marks the locus as a site for CENP-A maintenance/replenishment.This work was supported by the Tumorzentrum Heidelberg/Mannheim grant (D.10026941)and by March of Dimes Research Foundation grant #1-FY06-377 and NIH R01 GM069514

Genome-Scale Validation of Deep-Sequencing Libraries

Chromatin immunoprecipitation followed by high-throughput (HTP) sequencing (ChIP-seq) is a powerful tool to establish protein-DNA interactions genome-wide. The primary limitation of its broad application at present is the often-limited access to sequencers. Here we report a protocol, Mab-seq, that generates genome-scale quality evaluations for nucleic acid libraries intended for deep-sequencing. We show how commercially available genomic microarrays can be used to maximize the efficiency of library creation and quickly generate reliable preliminary data on a chromosomal scale in advance of deep sequencing. We also exploit this technique to compare enriched regions identified using microarrays with those identified by sequencing, demonstrating that they agree on a core set of clearly identified enriched regions, while characterizing the additional enriched regions identifiable using HTP sequencing