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At least 703 records · Page 39

Helical dynamo growth and saturation at modest versus extreme magnetic Reynolds numbers

Understanding magnetic field growth in astrophysical objects is a persistent challenge. In stars and galaxies, turbulent flows with net kinetic helicity are believed to be responsible for driving large-scale magnetic fields. However, numerical simulations have demonstrated that such helical dynamos in closed volumes saturate at lower magnetic field strengths when increasing the magnetic Reynolds number Rm . This would imply that helical large-scale dynamos cannot be efficient in astrophysical bodies without the help of helicity outflows such as stellar winds. But do these implications actually apply for very large Rm ? Here we tackle the long-standing question of how much helical large-scale dynamo growth occurs independent of Rm in a closed volume. We analyze data from numerical simulations with a new method that tracks resistive versus nonresistive drivers of helical field growth. We identify a presaturation regime when the large-scale field grows at a rate independent of Rm , but to an Rm -dependent magnitude. The latter Rm dependence is due to a dominant resistive contribution, but whose fractional contribution to the large-scale magnetic energy decreases with increasing Rm . We argue that the resistive contribution would become negligible at large Rm and an Rm -independent dynamical contribution would dominate if the current helicity spectrum in the inertial range is steeper than k 0 . As such helicity spectra are plausible, this renews optimism for the relevance of closed dynamos. Our work pinpoints how modest Rm simulations can cause misapprehension of the Rm → ∞ behavior. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of Salmonella enterica Isolated from a Mixed-Use Watershed in Georgia, USA: Antimicrobial Resistance, Serotype Diversity, and Genetic Relatedness to Human Isolates

As the cases of Salmonella enterica infections associated with contaminated water are increasing, this study was conducted to address the role of surface water as a reservoir of S. enterica serotypes. We sampled rivers and streams (n = 688) over a 3-year period (2015 to 2017) in a mixed-use watershed in Georgia, USA, and 70.2% of the total stream samples tested positive for Salmonella. A total of 1,190 isolates were recovered and characterized by serotyping, antimicrobial susceptibility testing, and pulsed-field gel electrophoresis (PFGE). A wide range of serotypes was identified, including those commonly associated with humans and animals, with S. enterica serotype Muenchen being predominant (22.7%) and each serotype exhibiting a high degree of strain diversity by PFGE. About half (46.1%) of the isolates had PFGE patterns indistinguishable from those of human clinical isolates in the CDC PulseNet database. A total of 52 isolates (4.4%) were resistant to antimicrobials, out of which 43 isolates were multidrug resistant (MDR; resistance to two or more classes of antimicrobials). These 52 resistant Salmonella isolates were screened for the presence of antimicrobial resistance genes, plasmid replicons, and class 1 integrons, out of which four representative MDR isolates were selected for whole-genome sequencing analysis. The results showed that 28 MDR isolates resistant to 10 antimicrobials had blacmy-2 on an A/C plasmid. Persistent contamination of surface water with a high diversity of Salmonella strains, some of which are drug resistant and genetically indistinguishable from human isolates, supports a role of environmental surface water as a reservoir for and transmission route of this pathogen.

59 BASIC BIOLOGICAL SCIENCES↗

Protein-based forensic identification using genetically variant peptides in human bone

Bone tissue contains organic material that is useful for forensic investigations and may contain preserved endogenous protein that can persist in the environment for extended periods of time over a range of conditions. Single amino acid polymorphisms in these proteins reflect genetic information since they result from non-synonymous single nucleotide polymorphisms (SNPs) in DNA. Detection of genetically variant peptides (GVPs) — those peptides that contain amino acid polymorphisms — in digests of bone proteins allows for the corresponding SNP alleles to be inferred. Resulting genetic profiles can be used to calculate statistical measures of association between a bone sample and an individual. In this study proteomic analysis on rib cortical bone samples from 10 recently deceased individuals demonstrates this concept. A straight-forward acidic demineralization protocol yielded proteins that were digested with trypsin. Tryptic digests were analyzed by liquid chromatography mass spectrometry. A total of 1736 different proteins were identified across all resulting datasets. On average, individual samples contained 454 ± 121 ($\bar{x}$ ± σ) proteins. Thirty-five genetically variant peptides were identified from 15 observed proteins. Overall, 134 SNP inferences were made based on proteomically detected GVPs, which were confirmed by sequencing of subject DNA. Inferred individual SNP genetic profiles ranged in random match probability (RMP) from 1/6 to 1/42,472 when calculated with European population frequencies in the 1000 Genomes Project, Phase 3. Similarly, RMPs based on African population frequencies were calculated for each SNP genetic profile and likelihood ratios (LR) were obtained by dividing each European RMP by the corresponding African RMP. In conclusion, resulting LR values ranged from 1.4 to 825 with a median value of 16. GVP markers offer a basis for the identification of compromised skeletal remains independent of the presence of DNA template.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time sequence gamma-spectrometry of irradiated salt

Persisted Memory Mapping File (MMF) techniques have developed for the processing and analysis of time-stamped list (TLIST) mode data collected from an irradiated salt sample. This is a new technique that is unique to this research and enables additional information to be obtained from a conventional pulse height analysis (PHA) gamma-spectrometry acquisition. A salt sample was irradiated using a DT neutron generator and immediately measured using TLIST acquisition for 1 month to generate a 22 GB data file. MMF techniques were used to process the file without size restrictions at a rate of 388.5 MB minute-1, with instant access to any position within the file, separating the file into a series of time sequenced spectra suitable for PHA analysis. This enabled 14 activation products to be identified at different time intervals (41Ar, 80Br, 80mBr, 47Ca, 34mCl, 38Cl, 42K, 43K, 56Mn, 22Na, 24Na, 85Sr, 87mSr and 69mZn), and 6 radionuclides (80Br, 47Ca, 34mCl, 56Mn, 24Na and 87mSr) to be definitively confirmed based upon their measured half-life. Using this technique, the detection of 47Ca, and in-growth of its 47Sc progeny, was demonstrated as useful for calculating the time since irradiation.

Burnett, Jonathan L.↗

Environmental contaminants activate human and polar bear (Ursus maritimus) pregnane X receptors (PXR, NR1I2) differently

Background: Many persistent organic pollutants (POPs) accumulate readily in polar bears because of their position as apex predators in Arctic food webs. The pregnane X receptor (PXR, formally NR1I2, here proposed to be named promiscuous xenobiotic receptor) is a xenobiotic sensor that is directly involved in metabolizing pathways of a wide range of environmental contaminants. Objectives: In the present study, we comparably assess the ability of 51 selected pharmaceuticals, pesticides and emerging contaminants to activate PXRs from polar bears and humans using an in vitro luciferase reporter gene assay. Results: We found that polar bear PXR is activated by a wide range of our test compounds (68%) but has a slightly more narrow ligand specificity than human PXR that was activated by 86% of the 51 test compounds. The majority of the agonists identified (70%) produces a stronger induction of the reporter gene via human PXR than via polar bear PXR, however with some notable and environmentally relevant exceptions. Conclusions: Due to the observed differences in activation of polar bear and human PXRs, exposure of each species to environmental agents is likely to induce biotransformation differently in the two species. Bioinformatics analyses and structural modeling studies suggest that amino acids that are not part of the ligand-binding domain and do not interact with the ligand can modulate receptor activation. - Highlights: • Comparative study of ligand activation of human and polar bear PXRs. • Polar bear PXR is a promiscuous ligand-activated nuclear receptor but less so than human PXR. • Environmental contaminants activate human and polar bear PXRs differently. • Expression and ligand promiscuity indicate that PXR is a xenosensor in polar bears.

60 APPLIED LIFE SCIENCES↗

Meteorological Drivers and Large-Scale Climate Forcing of West Antarctic Surface Melt

Understanding the drivers of surface melting in West Antarctica is crucial for understanding future ice loss and global sea level rise. This study identifies atmospheric drivers of surface melt on West Antarctic ice shelves and ice sheet margins and relationships with tropical Pacific and high-latitude climate forcing using multidecadal reanalysis and satellite datasets. Physical drivers of ice melt are diagnosed by comparing satellite-observed melt patterns to anomalies of reanalysis near-surface air temperature, winds, and satellite-derived cloud cover, radiative fluxes, and sea ice concentration based on an Antarctic summer synoptic climatology spanning 1979–2017. Summer warming in West Antarctica is favored by Amundsen Sea (AS) blocking activity and a negative phase of the southern annular mode (SAM), which both correlate with El Niño conditions in the tropical Pacific Ocean. Extensive melt events on the Ross–Amundsen sector of the West Antarctic Ice Sheet (WAIS) are linked to persistent, intense AS blocking anticyclones, which force intrusions of marine air over the ice sheet. Surface melting is primarily driven by enhanced downwelling longwave radiation from clouds and a warm, moist atmosphere and by turbulent mixing of sensible heat to the surface by föhn winds. Since the late 1990s, concurrent with ocean-driven WAIS mass loss, summer surface melt occurrence has increased from the Amundsen Sea Embayment to the eastern Ross Ice Shelf. We link this change to increasing anticyclonic advection of marine air into West Antarctica, amplified by increasing air–sea fluxes associated with declining sea ice concentration in the coastal Ross–Amundsen Seas.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗

Dense Non Aqueous Phase Liquid Source Area Delineation Using Membrane Interface Probe and Hydraulic Profile Tool Technology at Space Launch Complex 16, Cape Canaveral Air Force Station, Florida - 16352

The historical use and disposal of chlorinated solvents throughout Department of Defense and Department of Energy sites has resulted in subsurface contamination by dense non-aqueous phase liquids (DNAPL). The nature and environmental persistence of DNAPLs makes delineation and remediation of these compounds challenging and costly. This paper examines the utilization of data from a membrane interface probe (MIP) and hydraulic profile tool (HPT) to reduce a typical 18 to 24 month field investigation to 3 months; thereby, significantly reducing costs and resulting in a three-dimensional (3D) imagery of a deep DNAPL plume in order to support an aggressive remedial design for Space Launch Complex 16 (SLC16) at Cape Canaveral Air Force Station, Florida. During the early stages of the U.S. space program, chlorinated solvents were routinely used at space complexes. Spent solvents were discharged to surface impoundments where they migrated into the subsurface. Over time, these chlorinated solvents reached concentrations high enough to form a DNAPL plume. Recent investigations near SLC16 identified a previously unknown DNAPL plume co-mingled with dissolved-phase chlorinated compounds. The DNAPL source area (concentrations of trichloroethene [TCE] as high as 1,000,000 micrograms per liter [μg/L]) was discovered approximately 1,200 feet (ft) west of the existing monitoring network area. The U.S. Air Force, along with the U.S. Army Corps of Engineers, developed data quality objectives (DQO) to delineate the extent of the DNAPL and the dissolved-phase contaminant plume. A multi-phase investigation approach was developed by HydroGeoLogic, Inc. (HGL) emphasizing the use of MIP and HPT sampling technologies, conventional direct push technology (DPT), and monitoring well sampling methods. This approach allowed the collection of real-time data that supported the project DQOs and significantly reduced overall project costs and the field implementation schedule. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comparative analysis of TCDD-induced AhR-mediated gene expression in human, mouse and rat primary B cells

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental pollutant that activates the aryl hydrocarbon receptor (AhR) resulting in altered gene expression. In vivo, in vitro, and ex vivo studies have demonstrated that B cells are directly impaired by TCDD, and are a sensitive target as evidenced by suppression of antibody responses. The window of sensitivity to TCDD-induced suppression of IgM secretion among mouse, rat and human B cells is similar. Specifically, TCDD must be present within the initial 12 h post B cell stimulation, indicating that TCDD disrupts early signaling network(s) necessary for B lymphocyte activation and differentiation. Therefore, we hypothesized that TCDD treatment across three different species (mouse, rat and human) triggers a conserved, B cell-specific mechanism that is involved in TCDD-induced immunosuppression. RNA sequencing (RNA-Seq) was used to identify B cell-specific orthologous genes that are differentially expressed in response to TCDD in primary mouse, rat and human B cells. Time course studies identified TCDD-elicited differential expression of 515 human, 2371 mouse and 712 rat orthologous genes over the 24-h period. 28 orthologs were differentially expressed in response to TCDD in all three species. Overrepresented pathways enriched in all three species included cytokine-cytokine receptor interaction, ECM-receptor interaction, focal adhesion, regulation of actin cytoskeleton and pathways in cancer. Differentially expressed genes functionally associated with cell-cell signaling in humans, immune response in mice, and oxidation reduction in rats. Overall, these results suggest that despite the conservation of the AhR and its signaling mechanism, TCDD elicits species-specific gene expression changes. - Highlights: • Kovalova TAAP Highlights Nov. 2016 • RNA-Seq identified TCDD-induced gene expression in PWM-activated primary B cells. • TCDD elicited differential expression of 515 human, 2371 mouse and 712 rat orthologs. • 28 orthologs were differentially expressed in response to TCDD in all three species. • TCDD elicits mostly species-specific gene expression changes in activated B cells.

60 APPLIED LIFE SCIENCES↗

Insights into the physiological and genomic characterization of three bacterial isolates from a highly alkaline, terrestrial serpentinizing system

The terrestrial serpentinite-hosted ecosystem known as “The Cedars” is home to a diverse microbial community persisting under highly alkaline (pH ~ 12) and reducing (Eh < -550 mV) conditions. This extreme environment presents particular difficulties for microbial life, and efforts to isolate microorganisms from The Cedars over the past decade have remained challenging. Herein, we report the initial physiological assessment and/or full genomic characterization of three isolates: Paenibacillus sp. Cedars (‘Paeni-Cedars’), Alishewanella sp. BS5-314 (‘Ali-BS5-314’), and Anaerobacillus sp. CMMVII (‘Anaero-CMMVII’). Paeni-Cedars is a Gram-positive, rod-shaped, mesophilic facultative anaerobe that grows between pH 7–10 (minimum pH tested was 7), temperatures 20–40°C, and 0–3% NaCl concentration. The addition of 10–20 mM CaCl 2 enhanced growth, and iron reduction was observed in the following order, 2-line ferrihydrite > magnetite > serpentinite ~ chromite ~ hematite. Genome analysis identified genes for flavin-mediated iron reduction and synthesis of a bacillibactin-like, catechol-type siderophore. Ali-BS5-314 is a Gram-negative, rod-shaped, mesophilic, facultative anaerobic alkaliphile that grows between pH 10–12 and temperatures 10–40°C, with limited growth observed 1–5% NaCl. Nitrate is used as a terminal electron acceptor under anaerobic conditions, which was corroborated by genome analysis. The Ali-BS5-314 genome also includes genes for benzoate-like compound metabolism. Anaero-CMMVII remained difficult to cultivate for physiological studies; however, growth was observed between pH 9–12, with the addition of 0.01–1% yeast extract. Anaero-CMMVII is a probable oxygen-tolerant anaerobic alkaliphile with hydrogenotrophic respiration coupled with nitrate reduction, as determined by genome analysis. Based on single-copy genes, ANI, AAI and dDDH analyses, Paeni-Cedars and Ali-BS5-314 are related to other species (P. glucanolyticus and A. aestuarii, respectively), and Anaero-CMMVII represents a new species. The characterization of these three isolates demonstrate the range of ecophysiological adaptations and metabolisms present in serpentinite-hosted ecosystems, including mineral reduction, alkaliphily, and siderophore production.

59 BASIC BIOLOGICAL SCIENCES↗

A data analytical approach for assessing the efficacy of Operational Technology active defenses against insider threats

In recent years, the need for Operational Technology (OT) defenses has been recognized, serving as an additional line of defense when Information Technology (IT) defenses are bypassed. This is no longer considered an uncommon possibility when dealing with advanced persistent threat (APT) actors expected to be state-sponsored and receiving insider assistance. In these extreme adversarial situations, OT defenses aim to provide another layer of defense for the system, introduced directly at the physical process level, as described by the sensors data, the system model, and control actions. Just like IT defenses, two schools of thought, i.e., passive and active defenses, have emerged to address this challenge. In active defenses, representing the focus of this paper, known signatures, synthesized based on the system's unique characteristics, are inserted into the system. In contradistinction, passive methods rely solely on observing system behavior in search of patterns of normal behavior with deviations thereof representing abnormal behavior. In their most sophisticated implementations, both passive and active defenses rely on the use of data analytics to identify the patterns and synthesize the observed and/or inserted signatures. Past research has shown that passive defenses may be bypassed by APT actors relying on data analytics and their intimate knowledge of the system to evade detection by respecting the patterns identified by the defenders. Here this manuscript explores the use of active defenses under the assumption that the attacker has privileged access to the system, including access to the system's model and sensors data. Specifically, this manuscript assesses the ability of active defenses to remain invisible to the attackers, and discusses the associated challenges that must be addressed to ensure their resiliency against APT actors.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Opportunities for nonvolatile memory systems in extreme-scale high-performance computing

For extreme-scale high-performance computing systems, system-wide power consumption has been identified as one of the key constraints moving forward, where DRAM main memory systems account for about 30 to 50 percent of a node's overall power consumption. As the benefits of device scaling for DRAM memory slow, it will become increasingly difficult to keep memory capacities balanced with increasing computational rates offered by next-generation processors. However, several emerging memory technologies related to nonvolatile memory (NVM) devices are being investigated as an alternative for DRAM. Moving forward, NVM devices could offer solutions for HPC architectures. Researchers are investigating how to integrate these emerging technologies into future extreme-scale HPC systems and how to expose these capabilities in the software stack and applications. In addition, current results show several of these strategies could offer high-bandwidth I/O, larger main memory capacities, persistent data structures, and new approaches for application resilience and output postprocessing, such as transaction-based incremental checkpointing and in situ visualization, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Limited effects of tannin supplementation on the dairy cattle fecal microbiome with modulation of metabolites

Tannins are plant secondary metabolites that bind organic carbon (C) and nitrogen (N), potentially altering substrate bioavailability for enteric fermentation in ruminants. This interaction may reduce greenhouse gas (GHG) emissions and influence nitrogen partitioning. Given tannins' resistance to ruminal degradation and persistence through the gastrointestinal tract, this study investigated the effects of a tannin-based feed additive on fecal microbial diversity, fecal chemical composition, and GHG emissions. Twenty-four early- to mid-lactation dairy cows were randomized to receive either a tannin-based feed additive (TRT; containing condensed and hydrolyzable tannins from Schinopsis quebracho-colorado [Schltdl.]) or a control diet (CON) for 64 days. Cows were blocked by parity, dry matter intake, milk yield, body weight, and days in milk. Fecal samples were collected on days 0, 16, 32, and 64 and analyzed using 16S rRNA gene amplicon sequencing. Fecal C, N, and indole-3-lactate were measured, and GHG emissions (N2O, CH4, CO2) were assessed via 14-day laboratory incubation. A total of 1,538 amplicon sequence variants were identified, with Firmicutes as the dominant phylum. Fecal phylogenetic diversity showed a significant treatment × day interaction (p < 0.01), with TRT cows exhibiting reduced microbial diversity from day 16 to 64. Fecal C and N concentrations were significantly lower (p < 0.01) in TRT cows on day 16, while indole-3-lactate levels were higher on day 64 (p = 0.02). GHG emissions did not differ significantly between treatments. The tannin-based feed additive influenced fecal microbial community structure and select chemical parameters but did not significantly affect GHG emissions from feces. These findings suggest that dietary tannins may modulate gut microbial ecology with minimal impact on downstream manure-related emissions.

Klein, Matthew L↗

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗

A Complex Interplay between Nitric Oxide, Quorum Sensing, and the Unique Secondary Metabolite Tundrenone Constitutes the Hypoxia Response in Methylobacter

Methylobacter species, members of the Methylococcales, have recently emerged as some of the globally widespread, cosmopolitan species that play a key role in the environmental consumption of methane across gradients of dioxygen tensions. In this work, we approached the question of howMethylobacter copes with hypoxia, via laboratory manipulation. Through comparative transcriptomics of cultures grown under high dioxygen partial pressure versus cultures exposed to hypoxia, we identified a gene cluster encoding a hybrid cluster protein along with sensing and regulatory functions. Through mutant analysis, we demonstrated that this gene cluster is involved in the hypoxia stress response. Through additional transcriptomic analyses, we uncovered a complex interconnection between the NO-mediated stress response, quorum sensing, the secondary metabolite tundrenone, and methanol dehydrogenase functions. This novel and complex hypoxia stress response system is so far unique to Methylobacter species, and it may play a role in the environmental fitness of these organisms and in their cosmopolitan environmental distribution.Here, we describe a novel and complex hypoxia response system in a methanotrophic bacterium that involves modules of central carbon metabolism, denitrification, quorum sensing, and a secondary metabolite, tundrenone. This intricate stress response system, so far unique to Methylobacter species, may be responsible for the persistence and activity of these species across gradients of dioxygen tensions and for the cosmopolitan distribution of these organisms in freshwater and soil environments in the Northern Hemisphere, including the fast-melting permafrosts.

59 BASIC BIOLOGICAL SCIENCES↗

Key Metabolites and Mechanistic Changes for Salt Tolerance in an Experimentally Evolved Sulfate-Reducing Bacterium, Desulfovibrio vulgaris

ABSTRACT. Rapid genetic and phenotypic adaptation of the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough to salt stress was observed during experimental evolution. In order to identify key metabolites important for salt tolerance, a clone, ES10-5, which was isolated from population ES10 and allowed to experimentally evolve under salt stress for 5,000 generations, was analyzed and compared to clone ES9-11, which was isolated from population ES9 and had evolved under the same conditions for 1,200 generations. These two clones were chosen because they represented the best-adapted clones among six independently evolved populations. ES10-5 acquired new mutations in genes potentially involved in salt tolerance, in addition to the preexisting mutations and different mutations in the same genes as in ES9-11. Most basal abundance changes of metabolites and phospholipid fatty acids (PLFAs) were lower in ES10-5 than ES9-11, but an increase of glutamate and branched PLFA i17:1ω9c under high-salinity conditions was persistent. ES9-11 had decreased cell motility compared to the ancestor; in contrast, ES10-5 showed higher cell motility under both nonstress and high-salinity conditions. Both genotypes displayed better growth energy efficiencies than the ancestor under nonstress or high-salinity conditions. Consistently, ES10-5 did not display most of the basal transcriptional changes observed in ES9-11, but it showed increased expression of genes involved in glutamate biosynthesis, cation efflux, and energy metabolism under high salinity. These results demonstrated the role of glutamate as a key osmolyte and i17:1ω9c as the major PLFA for salt tolerance in D. vulgaris . The mechanistic changes in evolved genotypes suggested that growth energy efficiency might be a key factor for selection. IMPORTANCE. High salinity (e.g., elevated NaCl) is a stressor that affects many organisms. Salt tolerance, a complex trait involving multiple cellular pathways, is attractive for experimental evolutionary studies. Desulfovibrio vulgaris Hildenborough is a model sulfate-reducing bacterium (SRB) that is important in biogeochemical cycling of sulfur, carbon, and nitrogen, potentially for bio-corrosion, and for bioremediation of toxic heavy metals and radionuclides. The coexistence of SRB and high salinity in natural habitats and heavy metal-contaminated field sites laid the foundation for the study of salt adaptation of D. vulgaris Hildenborough with experimental evolution. Here in this paper, we analyzed a clone that evolved under salt stress for 5,000 generations and compared it to a clone evolved under the same condition for 1,200 generations. The results indicated the key roles of glutamate for osmoprotection and of i17:1ω9c for increasing membrane fluidity during salt adaptation. The findings provide valuable insights about the salt adaptation mechanism changes during long-term experimental evolution.

59 BASIC BIOLOGICAL SCIENCES↗

A systematic literature review on residential demand response with a focus on opportunities for low-income communities

Demand Response improves efficiency and grid stability, reducing peak load and total system costs. It can potentially contribute to other societal aspects, including mitigating climate change and improving air quality, health, stress levels, and comfort. This paper reviewed the literature on residential demand response programs in the United States, through the lens of the five energy justice principles, identifying and categorizing a set of 165 papers from 1960 to 2024. As a result, we observe significant progress in distributive justice, however, mostly focused on increasing participation rather than attending specific needs of historically marginalized communities. Concordantly, recognition and procedural justice dimensions are lagging, while cosmopolitan justice studies are scarce, underscoring a need to improve the measurement of impacts resulting from the implementation of demand response programs. Future research opportunities include the consolidation of standardized definitions and metrics, to better understand burdens and needs of diverse residential users. In terms of policy, collection and transparent access to standardized data is required as a condition to the design of flexible, customizable, transparent, and easy to navigate demand response programs. As a result, a better understanding of and engagement with customers has the potential to increase adoption rates, persistence in the program, and overall impacts for the system, households, and society.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Simultaneous thermoelectric and optoelectronic characterization of individual nanowires

Semiconducting nanowires have been explored for a number of applications in optoelectronics such as photodetectors and solar cells. Currently, there is ample interest in identifying the mechanisms that lead to photoresponse in nanowires in order to improve and optimize performance. However, distinguishing among the different mechanisms, including photovoltaic, photothermoelectric, photoemission, bolometric, and photoconductive, is often difficult using purely optoelectronic measurements. In this work, we present an approach for performing combined and simultaneous thermoelectric and optoelectronic measurements on the same individual nanowire. We apply the approach to GaN/AlGaN core/shell and GaN/AlGaN/GaN core/shell/shell nanowires and demonstrate the photothermoelectric nature of the photocurrent observed at the electrical contacts at zero bias, for above- and below-bandgap illumination. Furthermore, the approach allows for the experimental determination of the temperature rise due to laser illumination, which is often obtained indirectly through modeling. We also show that under bias, both above- and below-bandgap illumination leads to a photoresponse in the channel with signatures of persistent photoconductivity due to photogating. Finally, we reveal the concomitant presence of photothermoelectric and photogating phenomena at the contacts in scanning photocurrent microscopy under bias by using their different temporal response. Furthermore, our approach is applicable to a broad range of nanomaterials to elucidate their fundamental optoelectronic and thermoelectric properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗