BiFET: sequencing Bias-free transcription factor Footprint Enrichment Test.

Transcription factor (TF) footprinting uncovers putative protein-DNA binding via combined analyses of chromatin accessibility patterns and their underlying TF sequence motifs. TF footprints are frequently used to identify TFs that regulate activities of cell/condition-specific genomic regions (target loci) in comparison to control regions (background loci) using standard enrichment tests. However, there is a strong association between the chromatin accessibility level and the GC content of a locus and the number and types of TF footprints that can be detected at this site. Traditional enrichment tests (e.g. hypergeometric) do not account for this bias and inflate false positive associations. Therefore, we developed a novel post-processing method, Bias-free Footprint Enrichment Test (BiFET), that corrects for the biases arising from the differences in chromatin accessibility levels and GC contents between target and background loci in footprint enrichment analyses. We applied BiFET on TF footprint calls obtained from EndoC-βH1 ATAC-seq samples using three different algorithms (CENTIPEDE, HINT-BC and PIQ) and showed BiFET\u27s ability to increase power and reduce false positive rate when compared to hypergeometric test. Furthermore, we used BiFET to study TF footprints from human PBMC and pancreatic islet ATAC-seq samples to show its utility to identify putative TFs associated with cell-type-specific loci

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

Physicochemical study of spiropyran-terthiophene derivatives: photochemistry and thermodynamics

The photochemistry and thermodynamics of two terthiophene (TTh) derivatives bearing benzospiropyran (BSP) moieties, 1-(3,3’’-dimethylindoline-6’-nitrobenzospiropyranyl)-2-ethyl 4,4’’-didecyloxy-2,2’:5’,2’’-terthiophene-3’-acetate (BSP-2) and 1-(3,3’’-dimethylindoline-6’-nitrobenzospiropyranyl)-2-10 ethyl 4,4’’-didecyloxy-2,2’:5’,2’’-terthiophene-3’-carboxylate (BSP-3), differing only by a single methylene spacer unit, have been studied. The kinetics of photogeneration of the equivalent merocyanine (MC) isomers (MC-2 and MC-3, respectively), the isomerisation properties of MC-2 and MC-3, and the thermodynamic parameters have been studied in cetonitrile, and compared to the parent, non-TThfunctionalised, benzospiropyran derivative, BSP-1. Despite the close structural similarity of BSP-2 and 15 BSP-3, their physicochemical properties were found to differ significantly; examples include activation energies (Ea(MC-2) = 75.05 KJ mol-1, Ea(MC-3) = 100.39 kJ mol-1) and entropies of activation (S‡ MC-2 = - 43.38 J K-1 mol-1, S‡ MC-3 = 37.78 J K-1 mol-1) for the thermal relaxation from MC to BSP, with the MC-3 value much closer to the unmodified MC-1 value (46.48 J K -1 mol-1) for this latter quantity. The thermal relaxation kinetics and solvatochromic behaviour of the derivatives in a range of solvents of 20 differing polarity (ethanol, dichloromethane, acetone, toluene and diethyl ether) are also presented. Differences in the estimated values of these thermodynamic and kinetic parameters are discussed with reference to the molecular structure of the derivatives

Simulation of Occupant Response in Space Capsule Landing Configurations With Suit Hardware

The purpose of this study was to compare the response of the total human model for safety (THUMS) human body finite element model (FEM) to experimental postmortem human subject (PMHS) test results and evaluate possible injuries caused by suit ring elements. Experimental testing evaluated the PMHS response in frontal, rear, side, falling, and spinal impacts. The THUMS was seated in a rigid seat that mirrored the sled buck used in the experimental testing. The model was then fitted with experimental combinations of neck, shoulder, humerus and thigh rings with a five-point restraint system. Experimental seat acceleration data was used as the input for the simulations. The simulation results were analyzed and compared to PMHS measurements to evaluate the response of the THUMS in these loading conditions. The metrics selected to compare the THUMS simulation to PMHS tests were the chest acceleration, seat acceleration and belt forces with additional metrics implemented in THUMS. The chest acceleration of the simulations and the experimental data was closely matched except in the Z-axis (superior/inferior) loading scenarios based on signal analysis. The belt force data of the model better correlated to the experimental results in loading scenarios where the THUMS interacted primarily with the restraint system compared to load cases where the primary interaction was between the seat and the occupant (rear, spinal and lateral impacts). The simulation output demonstrated low injury metric values for the occupant in these loading conditions. In the experimental testing, rib fractures were recorded for the frontal and left lateral impact scenarios. Fractures were not seen in the simulations, most likely due to variations between the simulation and the PMHS initial configuration. The placement of the rings on the THUMS was optimal with symmetric placement about the centerline of the model. The experimental placement of the rings had more experimental variation. Even with this discrepancy, the THUMS can still be considered a valuable predictive tool for occupant injury because it can compare results across many simulations. The THUMS also has the ability to assess a wider variety of other injury information, compared to anthropomorphic test devices (ATDs), that can be used to compare simulation results

AMULET: a novel read count-based method for effective multiplet detection from single nucleus ATAC-seq data.

Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies

Head Impact Exposure in Youth and Collegiate American Football

The relationship between head impact and subsequent brain injury for American football players is not well defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multiseason study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9–14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95th percentile PLA practice: 42.6 vs 58.8; 95th percentile peak rotational acceleration (PRA, rad∙s–2) competition: 2262 vs 4422; 95th percentile PRA practice: 2081 vs 4052; 95th percentile HITsp competition: 25.4 vs 32.8; 95th percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management

Variation in histone configurations correlates with gene expression across nine inbred strains of mice.

The diversity outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression, and as such are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), and DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represented a distinct combination of the four histone modifications. We found that the epigenetic landscape was highly variable across the DO founders and was associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179