Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods

<p>The PyGBe code solves the linearized Poisson-Boltzmann equation using a boundary-integral formulation. We use a boundary element method with a collocation approach, and solve it via a Krylov-subspace method. To do this efficiently, the matrix-vector multiplications in the Krylov iterations are accelerated with a treecode, achieving O(N log N) complexity. The code presents a Python environment for the user, while being efficient and fast. The core computational kernels are implemented in Cuda and interface with the user-visible code with PyCuda, for maximum ease-of-use combined with high performance on GPU hardware. This document provides background on the model and formulation of the numerical method, evidence of a validation exercise with well-known benchmarks---a spherical shell with a centered charge and one with an off-center charge--- and a demonstration with a realistic biological geometry (lysozyme molecule)</p> <p> </p> <p><strong>Acknowledgement</strong></p> <p>This research is made possible by support from the Office of Naval Research, Applied Computational Analysis Program. LAB also acknowledges support from NSF CAREER award OCI-1149784.</p> <p> </p

PyGBe: Python on the surface, GPUs at the heart. BEM solver for Electrostatics of Biomolecules

<p>Poster presented at the GPU Technology Conference, March 2013, San Jose, CA.</p> <p>It presents the PyGBe code (pronounced 'pig-bee'), which solves the linearized Poisson-Boltzmann equation using a boundary element method, BEM. The underlying dense systems are solved using a Krylov-subspace method, accelerated with a treecode to achieve O(N log N) complexity. </p> <p>The code presents a Python environment for the user, while computing all kernels in CUDA (interfaced with PyCuda), for maximum ease of use, combined with high performance on GPUs.</p> <p><strong>Acknowledgement</strong></p> <p>This research is made possible by a grant from the Office of Naval Research, Applied Computational Analysis Program (N00014-11-1-0356). LAB also acknowledges support from NSF CAREER award OCI-1149784.</p

Mineralization of RDX-Derived Nitrogen to N₂ via Denitrification in Coastal Marine Sediments

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is a common constituent of military explosives. Despite RDX contamination at numerous U.S. military facilities and its mobility to aquatic systems, the fate of RDX in marine systems remains largely unknown. Here, we provide RDX mineralization pathways and rates in seawater and sediments, highlighting for the first time the importance of the denitrification pathway in determining the fate of RDX-derived N. ¹⁵N nitro group labeled RDX (¹⁵N-[RDX], 50 atom %) was spiked into a mesocosm simulating shallow marine conditions of coastal Long Island Sound, and the ¹⁵N enrichment of N₂ (δ¹⁵N₂) was monitored via gas bench isotope ratio mass spectrometry (GB-IRMS) for 21 days. The ¹⁵N tracer data were used to model RDX mineralization within the context of the broader coastal marine N cycle using a multicompartment time-stepping model. Estimates of RDX mineralization rates based on the production and gas transfer of ¹⁵N₂O and ¹⁵N₂ ranged from 0.8 to 10.3 μmol d^–1. After 22 days, 11% of the added RDX had undergone mineralization, and 29% of the total removed RDX-N was identified as N₂. These results demonstrate the important consideration of sediment microbial communities in management strategies addressing cleanup of contaminated coastal sites by military explosives

Tracing the Cycling and Fate of the Explosive 2,4,6-Trinitrotoluene in Coastal Marine Systems with a Stable Isotopic Tracer, ¹⁵N‑[TNT]

2,4,6-Trinitrotoluene (TNT) has been used as a military explosive for over a hundred years. Contamination concerns have arisen as a result of manufacturing and use on a large scale; however, despite decades of work addressing TNT contamination in the environment, its fate in marine ecosystems is not fully resolved. Here we examine the cycling and fate of TNT in the coastal marine systems by spiking a marine mesocosm containing seawater, sediments, and macrobiota with isotopically labeled TNT (¹⁵N-[TNT]), simultaneously monitoring removal, transformation, mineralization, sorption, and biological uptake over a period of 16 days. TNT degradation was rapid, and we observed accumulation of reduced transformation products dissolved in the water column and in pore waters, sorbed to sediments and suspended particulate matter (SPM), and in the tissues of macrobiota. Bulk δ¹⁵N analysis of sediments, SPM, and tissues revealed large quantities of ¹⁵N beyond that accounted for in identifiable derivatives. TNT-derived N was also found in the dissolved inorganic N (DIN) pool. Using multivariate statistical analysis and a ¹⁵N mass balance approach, we identify the major transformation pathways of TNT, including the deamination of reduced TNT derivatives, potentially promoted by sorption to SPM and oxic surface sediments

Additional file 1: of Genome-wide association study of lung function and clinical implication in heavy smokers

Table S1. Association Results of the Top SNPs (P < 10− 4) with Post-bronchodilator FEV1/FVC. Table S2. Association Results of the Top SNPs (P < 10− 4) with Post-bronchodilator % Predicted FEV1.Table S3. Genotype Frequency of rs28929474 in SERPINA1 Stratified by GOLD Stages. Table S4. Prediction Models for Post-bronchodilator Lung Function Using Top 10 SNPs for Post-bronchodilator % Predicted FEV1.Figure S1. Joint analysis of the top10 SNPs for post-bronchodilator % predicted FEV1 in 1075 SPIROMICS non-Hispanic White smokers with COPD. (DOCX 141 kb

Airway tree caliber heterogeneity and airflow obstruction among older adults. Supplemental data. Journal of Applied Physiology. Accepted on February 22, 2024

Supplemental data</p