A Deep Learning Model for Accurate Segmentation of the Brain from Micro-CT Imaging.

Unlabelled: The use of microcomputed tomography (Micro-CT) for imaging biological samples has burgeoned in the past decade, due to increased access to scanning platforms, ease of operation, isotropic three-dimensional image information, and the ability to derive accurate quantitative data. However, manual data analysis of Micro-CT images can be laborious and time intensive. Deep learning offers the ability to streamline this process, but historically has included caveats-namely, the need for a large amount of training data, which is often limited in many Micro-CT studies.

Small variant benchmark from a complete assembly of X and Y chromosomes.

The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research and clinical laboratories to evaluate variant detection on male sex chromosomes X and Y, we create a small variant benchmark set with 111,725 variants for the Genome in a Bottle HG002 reference material. We develop an active evaluation approach to demonstrate the benchmark set reliably identifies errors in challenging genomic regions and across short and long read callsets.

A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.

Somatic mosaicism is an important cause of disease, but mosaic and somatic variants are often challenging to detect because they exist in only a fraction of cells. To address the need for benchmarking subclonal variants in normal cell populations, we developed a benchmark containing mosaic variants in the Genome in a Bottle Consortium (GIAB) HG002 reference material DNA from a large batch of a normal lymphoblastoid cell line. First, we used a somatic variant caller with high coverage (300x) Illumina whole genome sequencing data from the Ashkenazi Jewish trio to detect variants in HG002 not detected in at least 5% of cells from the combined parental data.

Structural Properties of [N1888][TFSI] Ionic Liquid: A Small Angle Neutron Scattering and Polarizable Molecular Dynamics Study.

In this study, we investigate the quaternary ammonium-based ionic liquid (QAIL), methyltrioctylammonium bis(trifluoromethylsulfonyl)imide, [N][TFSI], utilizing small angle neutron scattering (SANS) measurements and polarizable molecular dynamics (MD) simulations to characterize the short- and long-range liquid structure. Scattering structure factors show signatures of three length scales in reciprocal space indicative of alternating polarity ( ∼ 0.44 Å), charge ( ∼ 0.