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At least 1,387 records · Page 77

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology

Open database for GPD analyses

This article summarizes the main ideas behind creating an open database proposed for use in the exploration of generalized parton distributions (GPDs). This lightweight database is well suited for GPD phenomenology and is designed to store both experimental and lattice-QCD data. It can also aid in benchmarking GPD-related developments, such as GPD models. The database utilizes a new data format based on the YAML serialization language, enabling the storage of essential information for modern analyses, such as replica values. It includes interfaces for both Python and C++, allowing straightforward integration with analysis codes.

Burkert, V. D. [Thomas Jefferson National Accelera

Molecular 9 Be + $p$ fusion reaction

Here, we study (nuclear) fusion reactions in beryllium. We argue that some are nuclear long-distance molecular processes of interest for low-energy nuclear reactions. For these, we develop a novel reaction model. We note a chain of reactions that can naturally arise in beryllium target created by nonequilibrium proton reactions.

Rafelski, Johann [Univ. of Arizona, Tucson, AZ (Un

Ion Transport in Concentrated Crosslinked Solid Polymer Electrolytes

Crosslinking polymers is a common approach to create mechanically stable solid materials such as polymer electrolytes for lithium batteries. In conventional liquid electrolytes, the solvent molecules move freely to accommodate the field-induced motion of ions. However, in crosslinked polymer electrolytes, the rearrangement of polymer segments is constrained by the deformation limits of the network. Herein, we develop a new transport model that accounts for both the formation of concentration gradients and the elasticity of the electrolyte. The elasticity is incorporated by adding an additional term related to the entropy of crosslinked strands to the electrochemical potential of the salt. The resulting Crosslink Model contains two adjustable parameters: $\mathcal{N}$, the average number of monomers in a strand, and λ crit , the maximum strain the network can sustain. These solid-like constraints produce singularities in the governing transport equations, fundamentally altering the concentration profiles. Plateaus in salt concentrations emerge near the electrodes, and network elasticity introduces a strain overpotential. When compared to a Baseline Model ($\mathcal{N}$ → ∞, equivalent to concentrated solution theory), which predicts steepest gradients near the electrodes, both models yield similar current–voltage relationships. Model predictions are compared to electrochemical data for a poly(ethylene oxide)-based crosslinked polymer electrolyte.

Patel, Vivaan [University of California, Berkeley,

DualSPHysics-INL

Funded by the DOE's Bioenergy Technology Office through the Feedstock-Conversion Interface Consortium, INL researchers developed this code to model biomass freestock flow in various handling equipment, such as hoppers and augers. Built on top of an existing open-source code DualSPHysics (https://dual.sphysics.org/) , the enrichment includes modification of the mass conservation equation that switching tracking density to void ratio, adding a hypoplastic constitutive law to better capture the flow physics of this type of material and implementing a novel boundary condition that can handle the dynamic contact between material and equipment. All implementation were realized via Nvidia CUDA, so GPU accelaration can be leveraged to signifiantly speed up the computational process.

Jin, Wencheng [Idaho National Laboratory (INL), Id

building-physics/refrigeration-system

The existing refrigeration system for OpenStudio was originally designed for a prototype supermarket model. To support the development of new modular space types, it is crucial to refactor the system. This process includes refining the design by utilizing the manufacturer's existing data, along with incorporating the latest data from manufacturers, to enhance the system’s adaptability and functionality. This repository currently contains the refrigeration system database and Python-based automation for generating OpenStudio-compatible refrigeration JSON files.

Bae, Yeonjin [Oak Ridge National Laboratory (ORNL)

An improved dataset for predicting mammal infecting viruses from genetic sequence information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alternative data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 ± 0.070 to 0.784 ± 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 ± 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no better than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 ± 0.08) or not (ROC AUC 0.50 ± 0.04).

59 BASIC BIOLOGICAL SCIENCES

The 1990 San Francisco Bay Area Metropolitan Transportation Commission Household Survey

The San Francisco Bay Area's Metropolitan Transportation Commission (MTC) and the regional transportation planning agency for the nine-county Bay Area conducted the survey. The basic purpose for the survey was for the development of travel demand models to simulate the various components of travel behavior: auto ownership, trip frequency (trip generation), and the distribution of trips between origins and destinations by travel mode. Planners at MTC envisioned the 1990 survey as the first wave of a multi-wave household panel survey designed to capture both short- and long-term changes in regional travel behavior. The 1990 survey collected single-weekday travel data from nearly 9,900 Bay Area households and multiple-weekday travel data from nearly 1,500 households. The 1990 survey effort also included a separate sub-project, funded by the Bay Area Rapid Transit (BART) District, to collect multiple-weekday travel data from 1,000 BART-using households. The BART survey and the MTC multiple-weekday survey were completed in the spring of 1990; the MTC single-weekday survey was continued and completed during the autumn of 1990.

1Hz data

1994 Household Travel Survey

The Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board (COG/TPB) periodically conducts regional household travel surveys to monitor changes in daily travel and to gather information on the demographic, socioeconomic, and trip-making characteristics of Washington, D.C.-area residents. Information collected in the 1994 Household Travel Survey was an important component in the development of regional travel demand forecasting models used to predict changes in daily travel in response to current development trends and changes in regional transportation policies and programs. In two waves during the spring and fall of 1994, consultants for COG/TPB conducted a survey of daily travel by persons living in area households. The survey file contains travel information associated with 4,863 households residing in 13 jurisdictions comprising the greater Washington, D.C., region (approximately a 1-in-300 sample). The survey file contains 39,800 internal trip records with respect to the expanded cordon.

1Hz data

1968 Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board Home Interview Survey

The Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board periodically conducts regional household travel surveys to monitor changes in daily travel and to gather information on the demographic, socioeconomic, and trip-making characteristics of Washington, D.C.-area residents. Information collected in the 1968 Home Interview Survey was an important component in the development of regional travel demand forecasting models used to predict changes in daily travel in response to current development trends and changes in regional transportation policies and programs. The survey sampled 26,000 households residing in six jurisdictions comprising the greater Washington, D.C. region (an approximately 1-in-20 sample).

1Hz data

1987/88 Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board Home Interview Survey

The Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board periodically conducts regional household travel surveys to monitor changes in daily travel and to gather information on the demographic, socioeconomic, and trip-making characteristics of Washington, D.C.-area residents. Information collected in the 1987/88 Home Interview Survey was an important component in the development of regional travel demand forecasting models used to predict changes in daily travel in response to current development trends and changes in regional transportation policies and programs. The survey sampled 8,000 households residing in eight jurisdictions comprising the greater Washington, D.C. region (an approximately 1-in-166 sample).

1Hz data

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES

Development of a Two-Dimensional CASTLE Transmission-Line Model for all Levels of Saturn

This report describes a two-dimensional model of Saturn based on the CASTLE transmission line code. Building on previous modeling efforts, 2D circuit models based on the “chain-link fence” geometry are constructed for pre-ReCap Saturn and post-ReCap Saturn. The 2D model results are in better agreement with data from Shot 4550 measurements of load currents and doses then the previous 1D model. Lower doses (9%) predicted by the new model can be compensated by increasing the load A-K gap.

43 PARTICLE ACCELERATORS

Optimal CO2 Transport and Storage Cost Screening: Application Example

Poster on “Optimal CO2 Transport and Storage Cost Screening: Application Example” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. A major challenge to commercial scale CCS deployment from the perspective of coal and natural gas-fired power plants is understanding cost-optimal CO2 transport and viable geologic storage options. This study demonstrates unique workflows, using NETL-developed, publicly-available models and tools, to efficiently estimate optimal CO2 transport and storage (T&S) costs for each of the CO2 sources in NETL’s Carbon Capture Retrofit Databases (CCRD) for Electricity Generating Units. The results demonstrate the impact of cost-drivers on optimal T&S, and trends in optimal T&S data, based on real point sources that could be retrofitted with CO2 source technologies.

application example

Estimates of the Economic Impacts of Long-Duration, Widespread Power Disruptions in Puerto Rico

A typical electricity customer in Puerto Rico experienced nearly 27 hours of power interruptions in 2023–with many customers experiencing extremely long duration outages during a single event (i.e., greater than one month). This project involved conducting state-of-the-art surveying to assess the direct costs of power outages occurring across Puerto Rico, developing customer-specific models to estimate future costs over varying outage durations, and comparing these estimates to FEMA’s Value of Unit Service for Electricity. We estimate that a territory-wide power outage may cost customers $\$1$, $\$5$ and $\$29$ billion during one-, 14-, and 30-day interruptions, respectively. However, these are lower-bound estimates because our study focused on direct economic costs and, by necessity, did not fully incorporate (1) indirect impacts to the economy; (2) costs to repair or replace damaged utility infrastructure; and (3) the broader societal consequences including increased morbidity- and mortality-related costs. The information contained in this study can be used to estimate the direct economic value of past or proposed investments in power system resilience. We conclude with a discussion of this study’s limitations and suggest additional research to improve stakeholder understanding of the impacts of power outages across Puerto Rico.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Towards Exascale Astrophysics of Mergers and Supernovae (TEAMS)

The TEAMS project brought together cutting-edge simulations, theoretical insights, and collaborative efforts to deepen our understanding of some of the universe’s most extreme phenomena—supernovae, neutron star mergers, and the powerful signals they emit. Using one of the largest suites of 3D supernova simulations ever conducted, researchers uncovered new insights into how massive stars explode, how those explosions vary by stellar mass, and what conditions lead to the birth of neutron stars or black holes. They also studied the radiation and gravitational wave signals emitted during these events, revealing how future observations can be used to uncover what happens deep inside collapsing stars. The team developed improved tools for modeling how light and neutrinos behave in such explosive environments, enabling more accurate predictions of what astronomers might observe. Work also explored how the chemical composition and geometry of kilonovae—the visible explosions that follow neutron star mergers—influence their signals and can reveal the origins of heavy elements like gold. These efforts not only advanced scientific knowledge, but also trained a new generation of researchers at the intersection of astrophysics, computational science, and nuclear theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Corrosion Testing of Refractory in Contact with Molten Glasses Designed for Waste Vitrification - APPS1 Matrix Glasses

It is known that the predictive life of the refractory ceramic liner of nuclear waste glass melters is conservative, as demonstrated by performance of these materials such as in the Defense Waste Processing Facility (DWPF). The motivation for this task is to maximize the useful life of the melters that will be operated at the Waste Treatment and Immobilization Plant (WTP), which will in turn minimize procurement and disposal costs and melter outage times, as well as to identify maximum loadings in the waste glass of those species that corrode melter components. This task was initiated jointly with Pacific Northwest National Laboratory (PNNL) with the objective to develop a methodology and model to enable more accurate prediction of refractory service life under prototypic conditions from laboratory-scale material corrosion tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Corrosion Testing of Refractory in Contact with Molten Glasses Designed for Waste Vitrification - HAL24 M1 Matrix Glasses

It is known that the predictive life of the refractory ceramic liner of nuclear waste glass melters is conservative, as demonstrated by performance of these materials such as in the Defense Waste Processing Facility (DWPF). The motivation for this task is to maximize the useful life of the melters that will be operated at the Waste Treatment and Immobilization Plant (WTP), which will in turn minimize procurement and disposal costs and melter outage times, as well as to identify maximum loadings in the waste glass of those species that corrode melter components. This task was initiated jointly with Pacific Northwest National Laboratory (PNNL) with the objective to develop a methodology and model to enable more accurate prediction of refractory service life under prototypic conditions from laboratory-scale material corrosion tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W