Harmonization of Multi-Center Diffusion Tensor Tractography in Neonates with Congenital Heart Disease: Optimizing Post-Processing and Application of ComBat.

Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n= 398 subjects recruited across 4 centers, with a total of n=763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.

Measurements of Atmospheric Methane Emissions from Stray Gas Migration: A Case Study from the Marcellus Shale.

Understanding emissions of methane from legacy and ongoing shale gas development requires both regional studies that assess the frequency of emissions and case studies that assess causation. We present the first direct measurements of emissions in a case study of a putatively leaking gas well in the largest shale gas play in the United States. We quantify atmospheric methane emissions in farmland >2 km from the nearest shale gas well cited for casing and cementing issues. We find that emissions are highly heterogeneous as they travel long distances in the subsurface. Emissions were measured near observed patches of dead vegetation and methane bubbling from a stream. An eddy covariance flux tower, chamber flux measurements, and a survey of enhancements of the near-surface methane mole fraction were used to quantify emissions and evaluate the spatial and temporal variability. We combined eddy covariance measurements with the survey of the methane mole fraction to estimate total emissions over the study area (2,800 m2). Estimated at ∼6 kg CH4 day-1, emissions were spatially heterogeneous but showed no temporal trends over 6 months. The isotopic signature of the atmospheric CH4 source (δ13CH4) was equal to -29‰, consistent with methane of thermogenic origin and similar to the isotopic signature of the gas reported from the nearest shale gas well. While the magnitude of emissions from the potential leak is modest compared to large emitters identified among shale gas production sites, it is large compared to estimates of emissions from single abandoned wells. Since other areas of emissions have been identified close to this putatively leaking well, our estimate of emissions likely represents only a portion of total emissions from this event. More comprehensive quantification will require more extensive spatial and temporal sampling of the locations of gas migration to the surface as well as an investigation into the mechanisms of subsurface gas migration. This work highlights an example of atmospheric methane emissions from potential stray gas migration at a location far from a well pad, and further research should explore the frequency and mechanisms behind these types of events to inform careful and strategic natural gas development.

Characterization of Dysregulated miRNA in Peripheral Blood Mononuclear Cells from Ischemic Stroke Patients.

Epigenetic modification may play an important role in pathophysiology of ischemic stroke (IS) risk. MicroRNAs (miRNAs), which constitute one of the modes of epigenetic regulation, have been shown to be associated with a number of clinical disorders including IS. The purpose of this study was to investigate the miRNA profile in the peripheral blood mononuclear cells (PBMCs) of IS patients and compare it with stroke-free controls. Blood samples were obtained from 19 healthy age-gender-race matched individuals who served as controls to 20 IS patients. miRNA microarray analysis with RNA from PBMCs was performed and significantly dysregulated miRNAs common among IS patients were identified. We identified 117 miRNAs with linear fold values of at least ±1.5, of which, 29 were significantly altered (p value <0.05). Ingenuity Pathway Analysis (IPA) indicated a role for the dysregulated miRNAs in conditions relevant to IS (e.g., organismal injury and abnormalities, hematological disease and immunological disease). Pro-inflammatory genes like STAT3, interleukin (IL) 12A, and IL12B were some of the highly predicted targets for the dysregulated miRNAs. Notably, we further identified three common and significantly upregulated miRNAs (hsa-miR-4656, -432, -503) and one downregulated miRNA (hsa-miR-874) among all IS patients. Molecular interactive network analysis revealed that the commonly dysregulated miRNAs share several targets with roles relevant to IS. Altogether, we report dysregulation of miRNAs in IS PBMCs and provide evidence for their involvement in the immune system alteration during IS pathophysiology.