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At least 937 records · Page 52

Enhanced Hanford Low-Activity Waste Glass Property Data Development: Phase 1

This report summarizes and analyzes data collected on a first test matrix of 36 low-activity waste (LAW) glass compositions intended to expand the LAW glass composition region over which glass property models are valid. The 36 LAW glass compositions were selected using statistical layered experimental design to explore a new glass composition region that overlaps and expands beyond the previously explored LAW glass composition region. The layered design of 36 LAW glasses consisted of 18 outer-layer glasses, 13 inner-layer glasses, a center glass (two replicates), and a glass previously tested at another laboratory (three replicates). The outer-layer glass compositions include extrema of the glass compositions that extend across and slightly beyond the compositions that are expected to be targeted for production. The analyses performed on these glasses include chemical composition (for target compositional verification), density, viscosity, electrical conductivity, crystal fraction, Canister Centerline Cooling with crystal identification, Product Consistency Test response, sulfur solubility, iron redox, and Vapor Hydration Test response. This report documents and discusses the results obtained from this testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of Laboratory Testbeds Simulating Real-World Greenhouse Gas Emissions

Climate change leads to drastic variations in the environment that can threaten food security. To protect the security and prosperity of the environment, new agricultural practices that mitigate greenhouse gas emissions need to be developed. Agriculture plays a large role in the emissions of greenhouse gases, thus a need for new practices. At present, testing landscape management practices for carbon sequestration and reduction of greenhouse gas emissions are expensive because such tests often require intricate field experiments. Laboratory tests on landscape management practices often fail to simulate and accurately represent the natural systems researchers intend to study. There are methods that can be used to make these laboratory tests more closely replicate natural systems for the improvement of agricultural lands used in biofuel and food production. The goal of this project is to develop a laboratory testbed replicating field conditions that will mimic field greenhouse gas emissions. To achieve this goal, we used soil cores taken from agricultural and marginal lands, then attached fiberglass wicks to improve the drainage system in the soil core to simulate a more natural hydraulic system. The soil cores with the wicks were used to compared to greenhouse gas emissions observed in the field. Our preliminary results suggest that the soil carbon dioxide and nitrous oxide flux from the agricultural land site were comparable to the soil cores equipped with the drainage wicks. The data suggests that laboratory testbeds can be used to mimic field greenhouse gas emissions if parameters, such as soil water content were in a set range. The laboratory testbed produces similar greenhouse gas emissions to the agricultural site when the soil water content was between 15-25%.

54 ENVIRONMENTAL SCIENCES↗

Leveraging State Clean Water Revolving Funds to Expand Clean Energy Financing

To meet clean energy goals, states will need significant capital. Federal funding from the Inflation Reduction Act and the Infrastructure Investment and Jobs Act will help, including by capitalizing clean energy state revolving loan funds (RLFs). States can leverage state clean water revolving funds to finance even more clean energy improvements. New York and Pennsylvania have used this innovative mechanism to extend the impact of their clean energy loan programs. For states looking to extend the reach of their clean energy financing programs, the brief: -Explains how each state leveraged their state revolving funds, -Identifies critical success factors for doing so, and -Offers key elements for replicating this model In New York, New York State Energy Research and Development Authority structured a sale of bonds secured by the repayments from a portfolio of residential energy efficiency loans from its Green Jobs – Green New York Program, with the additional support of a guarantee from the state’s clean water revolving fund. The Pennsylvania Treasury Department received a direct investment of funds from Pennsylvania’s clean water revolving fund to support the relaunch of the Keystone Home Energy Loan Program (HELP), which had previously been shuttered due to lack of support funding. From our review of these two case studies, when facilitating state clean water revolving fund transactions to support clean energy lending, the following critical success factors emerged: -Reference to preventing atmospheric deposition resulting from the combustion of fossil fuels in the state’s Clean Water Act Section 319 Nonpoint Source Pollution Management Plan, which sets out that state’s strategy for reducing pollution into state waterways. -Strong relationships and trust between the clean water revolving fund administrator and the state agency administering the clean energy loan program. -Limited funding exposure for the clean water revolving funds—which are generally large and well capitalized—to ensure that any losses experienced by clean water revolving funds would have a negligible impact on the fund’s ability to support core water and wastewater projects. -Willingness, on the part of the clean water revolving fund administrator, to innovate and engage in careful analysis to support transaction structuring, and support from state energy partner organizations. The brief provides case studies of these states’ experiences, critical success factors, and key elements for replicating the model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Discerning Deception: An Empirically-Driven Agent-Based Model of Expert Evaluation of Scientific Content

Both human subject experiments and computational, modeling and simulations have been used to study detection of deception. This work aims to combine these two methods by integrating empirically-derived information (from human subject experiments) into agent-based models to generate novel insights into the complex problems of detection of disinformation content. Computational experiments are used to simulate across multiple scenarios for evaluation and decision-making regarding the validity of potentially deceptive scientific documents. Factors influencing the human agent behaviors in the model were identified through a human subject experiment that was conducted to evaluate and characterize decision making related to disinformation discernment. Correlation and regression analyses were used to translate insights from the human subjects experiment to inform the parameterization of agent features and scenario development. Three scenarios were evaluated with the agent-based models to help evaluate the replicability of the simulations (validation analysis) and assess the influence of human agent and document features (sensitivity analyses). A replication of the human participant experiment demonstrated that the agent-based simulations compare favorably to empirical findings. The agent-based modeling was then used to conduct sensitivity analysis on the accuracy of deception detection as a function of document proportions and human agent features. Results indicate that precision values are adversely impacted when the proportion of deceptive documents is lower in the overall sample, whereas recall values are more sensitive to changes in human agent features. These findings indicate important nuances in accuracy evaluations that should be further considered (including consideration of potential alternate metrics) in future agent-based models of disinformation. Additional areas for future exploration include extension of simulations to consider other ways to align the agent-based model design with psychological theory and inclusion of agent-agent interactions, especially as it pertains to sharing of scientific information within an organizational context.

99 GENERAL AND MISCELLANEOUS↗

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗

Verifying LLM generative agents reflect human behavior in contested information environments to effectively simulate disinformation campaigns (Proteus)

Disinformation poses a significant and evolving threat to today’s online environment. Individuals encounter challenges in detecting disinformation, subsequently influencing their behavior and decision-making processes. Our research examines the potential use of large language model (LLM) generative agents (LGAs) to replicate human behavior to better understand how disinformation is spread in online environments. Using human subjects research, we first investigate how personality traits, individual differences, and demographic factors relate to decision-making in simulated online disinformation environments. Then, we examine whether LGAs can effectively replicate human responses in the same simulated online environments when assigned personality traits, demographic characteristics and behavioral attributes. Our findings indicate that LGAs can align with human decisions in these scenarios; however, alignment is contingent upon scenario context, persona settings and LLM selection. Results provide valuable insights for methodology refinement in future research and in utilizing LGAs to model complex national security challenges such as disinformation campaigns.

97 MATHEMATICS AND COMPUTING↗

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗

Comparison of Infiltration Test Methods for Soil Health Assessment

Infiltration rate (IR) has been commonly used as a metric to evaluate soil quality and health. For the USDA Soil Quality Test Kit, a 15-cm (6-in) diameter (ID) cylinder is used to measure IR with 444 cm 3 (equivalent to 2.54 cm or 1 in) of water while other standard IR procedures require substantially larger volumes of water. The general objective of this study was to compare different methods for IR measurement. Using three replications, IR measurements were conducted along a 9-m (27-ft) long transect in two different soil types by the double-ring infiltrometer (DRI) using 25- and 50-cm (10-and 20-in, respectively) cylinders, single-ring infiltrometer (SRI) using 25- and 50-cm cylinders, Cornell sprinkle infiltrometer (CSI) using a 24.1-cm (9.5-in) cylinder, the USDA recommended procedure using a 15-cm diameter cylinder (hereafter referred to as USDA-15 method), and a modified USDA method using a 24.1-cm diameter cylinder. Although the USDA-15 method is simple and requires a small amount of water, based on high variability among replications and significant reduction in IR during early stages of water entry into the soil, the procedure does not offer an accurate estimate of the soil infiltration potential. The CSI procedure was reproducible, but it is more cumbersome to perform than other methods. The DRI, SRI, and CSI methods required a much greater volume of water than the USDA-15 method but produced results that are more consistent. The most consistent results were obtained by the CSI and DRI methods. The modified USDA method results were similar to the SRI method and were an improvement over the original USDA-15 method. For assessing soil health, additional investigations should be conducted to evaluate a modified version of the USDA procedure using a larger cylinder.

54 ENVIRONMENTAL SCIENCES↗

IA-TmG.2.0

Soil samples were collected in triplicate in the Fall of 2017 across three grassland locations having differences in historical annual precipitation. For each of the three field site soil collections, one deeply sequenced composite metagenome (> 1 terabase) was obtained and individually sequenced in replicate to provide three additional terabase metagenomes for replicate statistical comparison in addition to screening for viral soil contigs for assessing the impact of historical annual precipitation. This data package provides new knowledge of viral types, abundances, diversity, and auxiliary metabolic genes (AMGs) in grassland soils for predicting viral response to changes in their environment.

59 BASIC BIOLOGICAL SCIENCES↗

KS-TmG.2.0

Soil samples were collected in triplicate in the Fall of 2017 across three grassland locations having differences in historical annual precipitation. For each of the three field site soil collections, one deeply sequenced composite metagenome (> 1 terabase) was obtained and individually sequenced in replicate to provide three additional terabase metagenomes for replicate statistical comparison in addition to screening for viral soil contigs for assessing the impact of historical annual precipitation. This data package provides new knowledge of viral types, abundances, diversity, and auxiliary metabolic genes (AMGs) in grassland soils for predicting viral response to changes in their environment.

59 BASIC BIOLOGICAL SCIENCES↗

WA-TmG.2.0

Soil samples were collected in triplicate in the Fall of 2017 across three grassland locations having differences in historical annual precipitation. For each of the three field site soil collections, one deeply sequenced composite metagenome (> 1 terabase) was obtained and individually sequenced in replicate to provide three additional terabase metagenomes for replicate statistical comparison in addition to screening for viral soil contigs for assessing the impact of historical annual precipitation. This data package provides new knowledge of viral types, abundances, diversity, and auxiliary metabolic genes (AMGs) in grassland soils for predicting viral response to changes in their environment.

59 BASIC BIOLOGICAL SCIENCES↗

SPRUCE Deep Peat Microbial Diversity, CO2 and CH4 Production in Response to Nutrient, Temperature, and pH Treatments during Incubation Studies

This dataset contains the results of a microcosm incubation study on deep peat collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA in September 2014. Microcosms were monitored for carbon dioxide (CO2) and methane (CH4) production, and microbial community dynamics were assessed using quantitative polymerase chain reaction (qPCR) and amplicon sequencing. The experiment was designed with a full factorial design with elevated temperature, nitrogen (N), (P), and pH treatments was used with samples from each transect serving replicates. In all, 96 microcosms were constructed to account for the 16 treatment combinations (Nitrogen x Phosphorous x pH x temperature), 2 time points, and 3 replicates. Temperature treatments were 6 degrees C, to mimic the SPRUCE ambient plot temperatures, and 15 degrees C to mimic the SPRUCE +9 degrees C treatment. These data show that one year of deep peat warming, microbial community structure and abundance of bacterial, archaeal, fungal, and methanogenic populations showed strong vertical stratification across the peat depth profile yet no clear response to the temperature treatments (Kluber et al, 2020). In an effort to identify factors that may be limiting decomposition and microbial community change in deep peat, we conducted an anerobic microcosm incubation of deep peat (150-200 cm depth). This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

Clostridium autoethanogenum isopropanol production via native plasmid pCA replicon

Clostridium autoethanogenum is a model gas-fermenting acetogen for commercial ethanol production. It is also a platform organism being developed for the carbon-negative production of acetone and isopropanol by gas fermentation. We have assembled a 5.5 kb pCA plasmid for type strain DSM10061 (JA1-1) using three genome sequence datasets. pCA is predicted to encode seven open-reading frames and estimated to be a low-copy number plasmid present at approximately 12 copies per chromosome. RNA-seq analyses indicate that pCA genes are transcribed at low levels and two proteins, CAETHG_05090 (putative replication protein) and CAETHG_05115 (hypothetical, a possible Mob protein), were detected at low levels during batch gas fermentations. Thiolase (thlA), CoA-transferase (ctfAB), and acetoacetate decarboxylase (adc) genes were introduced into a vector for isopropanol production in C. autoethanogenum using the native plasmid origin of replication. The availability of the pCA sequence will facilitate studies into its physiological role and could form the basis for genetic tool optimization.

09 BIOMASS FUELS↗

Age and the means of bypassing stasis influence the intrinsic subtype of immortalized human mammary epithelial cells

Based on molecular features, breast cancers are grouped into intrinsic subtypes that have different prognoses and therapeutic response profiles. With increasing age, breast cancer incidence increases, with hormone receptor-positive and other luminal-like subtype tumors comprising a majority of cases. It is not known at what stage of tumor progression subtype specification occurs, nor how the process of aging affects the intrinsic subtype. We examined subtype markers in immortalized human mammary epithelial cell lines established following exposure of primary cultured cell strains to a two-step immortalization protocol that targets the two main barriers to immortality: stasis (stress-associated senescence) and replicative senescence. Cell lines derived from epithelial cells obtained from non-tumorous pre- and post-menopausal breast surgery tissues were compared. Additionally, comparisons were made between lines generated using two different genetic interventions to bypass stasis: transduction of either an shRNA that down-regulated p16INK4A, or overexpressed constitutive active cyclin D1/CDK2. In all cases, the replicative senescence barrier was bypassed by transduction of c-Myc. Cells from all resulting immortal lines exhibited normal karyotypes. Immunofluorescence, flow cytometry, and gene expression analyses of lineage-specific markers were used to categorize the intrinsic subtypes of the immortalized lines. Bypassing stasis with p16 shRNA in young strains generated cell lines that were invariably basal-like, but the lines examined from older strains exhibited some luminal features such as keratin 19 and estrogen receptor expression. Overexpression of cyclin D1/CDK2 resulted in keratin 19 positive, luminal-like cell lines from both young and old strains, and the lines examined from older strains exhibited estrogen receptor expression. Thus age and the method of bypassing stasis independently influence the subtype of immortalized human mammary epithelial cells.

59 BASIC BIOLOGICAL SCIENCES↗

Francisella novicida Two-Component System Response Regulator BfpR Modulates iglC Gene Expression, Antimicrobial Peptide Resistance, and Biofilm Production

Response regulators are a critical part of the two-component system of gene expression regulation in bacteria, transferring a signal from a sensor kinase into DNA binding activity resulting in alteration of gene expression. In this study, we investigated a previously uncharacterized response regulator in Francisella novicida, FTN_1452 that we have named BfpR (Biofilm-regulating Francisella protein Regulator, FTN_1452). In contrast to another Francisella response regulator, QseB/PmrA, BfpR appears to be a negative regulator of biofilm production, and also a positive regulator of antimicrobial peptide resistance in this bacterium. The protein was crystallized and X-ray crystallography studies produced a 1.8 Å structure of the BfpR N-terminal receiver domain revealing interesting insight into its potential interaction with the sensor kinase. Structural analysis of BfpR places it in the OmpR/PhoP family of bacterial response regulators along with WalR and ResD. Proteomic and transcriptomic analyses suggest that BfpR overexpression affects expression of the critical Francisella virulence factor iglC, as well as other proteins in the bacterium. We demonstrate that mutation of bfpR is associated with an antimicrobial peptide resistance phenotype, a phenotype also associated with other response regulators, for the human cathelicidin peptide LL-37 and a sheep antimicrobial peptide SMAP-29. F. novicida with mutated bfpR replicated better than WT in intracellular infection assays in human-derived macrophages suggesting that the down-regulation of iglC expression in bfpR mutant may enable this intracellular replication to occur. Response regulators have been shown to play important roles in the regulation of bacterial biofilm production. We demonstrate that F. novicida biofilm formation was highly increased in the bfpR mutant, corresponding to altered glycogen synthesis. Waxworm infection experiments suggest a role of BfpR as a negative modulator of iglC expression with de-repression by Mg 2+ . In this study, we find that the response regulator BfpR may be a negative regulator of biofilm formation, and a positive regulator of antimicrobial peptide resistance in F. novicida.

59 BASIC BIOLOGICAL SCIENCES↗

Meta gene set enrichment analyses link miR-137-regulated pathways with schizophrenia risk

Background: A single nucleotide polymorphism (SNP) within MIR137, the host gene for miR-137, has been identified repeatedly as a risk factor for schizophrenia. Previous genetic pathway analyses suggest that potential targets of this microRNA (miRNA) are also highly enriched in schizophrenia-relevant biological pathways, including those involved in nervous system development and function. Methods: In this study, we evaluated the schizophrenia risk of miR-137 target genes within these pathways. Gene set enrichment analysis of pathway-specific miR-137 targets was performed using the stage 1 (21,856 subjects) schizophrenia genome wide association study data from the Psychiatric Genomics Consortium and a small independent replication cohort (244 subjects) from the Mind Clinical Imaging Consortium and Northwestern University. Results: Gene sets of potential miR-137 targets were enriched with variants associated with schizophrenia risk, including target sets involved in axonal guidance signaling, Ephrin receptor signaling, long-term potentiation, PKA signaling, and Sertoli cell junction signaling. The schizophrenia-risk association of SNPs in PKA signaling targets was replicated in the second independent cohort. Conclusions: These results suggest that these biological pathways may be involved in the mechanisms by which this MIR137 variant enhances schizophrenia risk. SNPs in targets and the miRNA host gene may collectively lead to dysregulation of target expression and aberrant functioning of such implicated pathways. Pathway-guided gene set enrichment analyses should be useful in evaluating the impact of other miRNAs and target genes in different diseases.

Genetics & Heredity↗

Deep Sequencing of MHC-Adapted Viral Lines Reveals Complex Recombinational Exchanges With Endogenous Retroviruses Leading to High-Frequency Variants

Experimental evolution (serial passage) of Friend virus complex (FVC) in mice demonstrates phenotypic adaptation to specific host major histocompatibility complex (MHC) genotypes. These evolved viral lines show increased fitness and virulence in their host-genotype-of-passage, but display fitness and virulence tradeoffs when infecting unfamiliar host MHC genotypes. Here, we deep sequence these viral lines in an attempt to discover the genetic basis of FVC adaptation. The principal prediction for genotype-specific adaptation is that unique mutations would rise to high frequency in viral lines adapted to each host MHC genotype. This prediction was not supported by our sequencing data as most observed high-frequency variants were present in each of our independently evolved viral lines. However, using a multi-variate approach to measure divergence between viral populations, we show that populations of replicate evolved viral lines from the same MHC congenic mouse strain were more similar to one another than to lines derived from different MHC congenic mouse strains, suggesting that MHC genotype does predictably act on viral evolution in our model. Sequence analysis also revealed rampant recombination with endogenous murine leukemia virus sequences (EnMuLVs) that are encoded within the BALB/c mouse genome. The highest frequency variants in all six lines contained a 12 bp insertion from a recombinant EnMuLV source, suggesting such recombinants were either being favored by selection or were contained in a recombinational hotspot. Interestingly, they did not reach fixation, as if they are low fitness. The amount of background mutations linked to FVC/EnMuLV variable sites indicated that FVC/EnMuLV recombinants had not reached mutation selection equilibrium and thus, that EnMuLV sequences are likely continuously introgressing into the replicating viral population. These discoveries raise the question: is the expression of EnMuLV sequences in mouse splenocytes that permit recombination with exogenous FVC a pathogen or host adaptation?

59 BASIC BIOLOGICAL SCIENCES↗