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At least 1,639 records · Page 91

Identification and Characterization of Persistent Cold Pool Events from Temperature and Wind Profilers in the Columbia River Basin

Cold pool events occur when deep layers of stable, cold air remain trapped in a valley or basin for multiple days, without mixing out from daytime heating. With large impacts on air quality, freezing events, and es-pecially on wind energy production, they are often poorly forecast by modern mesoscale numerical weather prediction (NWP) models. Understanding the characteristics of cold pools is, therefore, important to provide more accurate forecasts. This study analyzes cold pool characteristics with data collected during the Second Wind Forecast Improvement Project (WFIP2), which took place in the Columbia River basin and Gorge of Oregon and Washington from fall 2015 until spring 2017. A subset of the instrumentation included three microwave radiometer pro?lers, six radar wind pro?lers with radio acoustic sounding systems, and seven sodars, which together provided seven sites with collocated vertical pro?les of temperature, humidity, wind speed, and wind direction. Using these collocated observations, we developed a set of criteria to determine if a cold pool was present based on stability, wind speed, direction, and temporal continuity, and then developed an automated algorithm based on these criteria to identify all cold pool events over the 18 months of the ?eld project. Characteristics of these events are described, including statistics of the wind speed distributions and pro?les, stability conditions, cold pool depths, and descent rates of the cold pool top. The goal of this study is a better understanding of these characteristics and their processes to ultimately lead to improved physical parameterizations in NWP models, and consequently improve forecasts of cold pool events in the study region as well at other locations that experiences similar events.

McCaffrey, Katherine L.↗

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments, and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.

54 ENVIRONMENTAL SCIENCES↗

Investigating land surface effects on the moisture transport over South America with a moisture tagging model

Land-atmosphere interactions are a critical component of precipitation processes within the Amazon and the La Plata river basins (LPRB) in South America. The possible pathways through which the land surface can affect precipitation are: 1) by changing the amount of moisture available for precipitation (moisture recycling) and 2) by changing the atmospheric thermal structure and consequently affecting circulation patterns. In this study, the Weather Research and Forecasting (WRF) model with embedded water vapor tracers (WVT) is used to disentangle these relative contributions. Using WRF-WVT we track the moisture that originates from the Amazon basin over a 10-year period. It is estimated that Amazon evapotranspiration (ET) contributes to around 30% of the total precipitation over the Amazon and around 20% over the LPRB. Analyzing moisture transport from the Amazon to the LPRB, it is found that warm (cool) surface air temperature over the northwestern Argentine is linked to low level winds and likely to induce northerly (southerly) winds that intensify (weaken) moisture transport by changing continental-scale circulation patterns.

Yang, Zhao↗

A directional microcrack damage theory for brittle solids based on continuous hyperplasticity

We present a novel microcrack-damage theory for brittle solids under compression. Instead of using internal variables like zeroth, second or fourth rank damage tensors, the state of material damage is represented by an internal function that encapsulates the information of direction, density and size of microcracks. Just like other internal variables, the evolution of this state function must obey the second law of thermodynamics for arbitrary loading paths. This is done by casting the model in the framework of continuous hyperplasticity and enforcing a non-negative dissipation rate functional. The proposed framework offers predictions on the continuous evolution of microcrack density and the induced material anisotropy along with the macroscopic stress-strain curves. The use of continuous damage function grants the model significantly enhanced resolution in characterizing the direction-dependent response of cracked solids compared to classical models that are based on damage tensors. Two scenarios are considered in developing the theory, one assumes frictionless cracks and the other incorporates friction between crack surfaces. The results highlight that inelasticity, pressure dependence, and loading-unloading hysteresis exhibited by brittle solids are natural consequences of frictional microcracks. The proposed theory offers a generic and versatile framework to upscale micromechanical processes operating at individual crack scale to explain the macroscopic behavior of cracked solids.

Materials Science↗

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Trifan, Anda↗

Investigating realistic anode off-gas combustion in SOFC/ICE hybrid systems: mini review and experimental evaluation

Solid oxide fuel cells (SOFCs) have been deployed in hybrid decentralized energy systems, in which they are directly coupled to internal combustion engines (ICEs). Prior research indicated that the anode tailgas exiting the SOFC stack should be additionally exploited due to its high energy value, with typical ICE operation favoring hybridization due to matching thermodynamic conditions during operation. Consequently, extensive research has been performed, in which engines are positioned downstream the SOFC subsystem, operating in several modes of combustion, with the most prevalent being homogeneous compression ignition (HCCI) and spark ignition (SI). Experiments were performed in a 3-cylinder ICE operating in the latter modus operandi, where the anode tailgas was assimilated by mixing syngas (H 2 : 33.9%, CO: 15.6%, CO 2 : 50.5%) with three different water vapor flowrates in the engine’s intake. While increased vapor content significantly undermined engine performance, brake thermal efficiency (BTE) surpassed 34% in the best case scenario, which outperformed the majority of engines operating under similar operating conditions, as determined from the conducted literature review. Nevertheless, the best performing application was identified operating under HCCI, in which diesel reformates assimilating SOFC anode tailgas, fueled a heavy duty ICE (17:1), and gross indicated thermal efficiency ([Formula: see text]) of 48.8% was achieved, with the same engine exhibiting identical performance when operating in reactivity-controlled compression ignition (RCCI). Overall, emissions in terms of NO x and CO were minimal, especially in SI engines, while unburned hydrocarbons (UHC) were non-existent due to the absence of hydrocarbons in the assessed reformates.

Engineering↗

Opinion: Making the Most of Colour Rendition Research

After decades of debate, new methods for characterizing color rendition have been formalized, providing an improved system of tools to aid technology developers and lighting specifiers. Solid-state lighting, previously burdened by legacy measures based on outdated science, is positioned to take advantage of these new tools to provide tailored, efficient lighting that better meets the needs of specific architectural lighting applications. This transition requires new guidance, however, presenting an opportunity for researchers. There are several key methodological considerations specific to experiments investigating color rendition that will help build a base of guidance that can be widely applied. The importance of these ideas mostly stems from new knowledge gained in the last five years, but their origins date back much further. 1.The spectral power distribution must be adequately varied to stress the measure(s) of color rendition being evaluated. Often, this means varying the gamut shape—the pattern of shift across different hues—to probe weaknesses of hue-averaged characterizations, avoiding misleading conclusions resulting from limited variation in the stimuli. 2.Evaluating the role of chromaticity on color quality evaluations requires careful accommodation of chromatic adaptation to prevent a centering bias. Asking for delayed responses may be insufficient if chromaticity changes are apparent to participants, just as side-by-side viewing of different chromaticities may not produce results that can be reliably applied in the field. It is also critical that color rendition and chromaticity conditions are varied independently. 3.The stimulus being viewed is the interaction of light and objects’ spectral reflectances. This interaction should be quantified in order to assess how derived guidelines will apply measures using standardized color sample sets. Although light source characterizations are typically used to model responses, the objects and their presentation may strongly influence evaluations. 4.Context is important. Many factors—some investigated, others hypothesized—can influence subjective evaluations of color quality, including illuminance level, type of scene, object familiarity, color composition, viewing duration, and viewer traits. Although their influence on research results is unavoidable, the effects of these contextual factors must be carefully considered in developing guidance. Appropriate experimental design can often mitigate negative consequences arising from these considerations. At a minimum, it is crucial to understand how each of these considerations can influence experimental outcomes, as well as the interpretation and application of the results in practice. Consulting other experts prior to conducting an experiment can help ensure appropriate, up-to-date research methods will be used, so that the results will be novel and useful—and not rejected during peer review. There is an interesting feedback loop: technology development provides new research tools, which allow for refined research methods and new results that lead to more technology development. It is time to make a concerted, collective effort to improve color rendition research so that the full potential of solid-state lighting and new characterization methods can be realized, ensuring that high-efficiency, high-utility, high-appeal lighting systems become standard.

Royer, Michael P.↗

Structural insights into Noonan/LEOPARD syndrome-related mutants of protein-tyrosine phosphatase SHP2 ( PTPN11 )

Background: The ubiquitous non-receptor protein tyrosine phosphatase SHP2 (encoded by PTPN11) plays a key role in RAS/ERK signaling downstream of most, if not all growth factors, cytokines and integrins, although its major substrates remain controversial. Mutations in PTPN11 lead to several distinct human diseases. Germ-line PTPN11 mutations cause about 50% of Noonan Syndrome (NS), which is among the most common autosomal dominant disorders. LEOPARD Syndrome (LS) is an acronym for its major syndromic manifestations: multiple Lentigines, Electrocardiographic abnormalities, Ocular hypertelorism, Pulmonary stenosis, Abnormalities of genitalia, Retardation of growth, and sensorineural Deafness. Frequently, LS patients have hypertrophic cardiomyopathy, and they might also have an increased risk of neuroblastoma (NS) and acute myeloid leukemia (AML). Consistent with the distinct pathogenesis of NS and LS, different types of PTPN11 mutations cause these disorders. Results: Although multiple studies have reported the biochemical and biological consequences of NS- and LS-associated PTPN11 mutations, their structural consequences have not been analyzed fully. Here we report the crystal structures of WT SHP2 and five NS/LS-associated SHP2 mutants. These findings enable direct structural comparisons of the local conformational changes caused by each mutation. Conclusions: Our structural analysis agrees with, and provides additional mechanistic insight into, the previously reported catalytic properties of these mutants. The results of our research provide new information regarding the structure-function relationship of this medically important target, and should serve as a solid foundation for structure-based drug discovery programs.

Leopard Syndrome↗

Nitrogen limitation causes a seismic shift in redox state and phosphorylation of proteins implicated in carbon flux and lipidome remodeling in Rhodotorula toruloides

Background: Oleaginous yeast are prodigious producers of oleochemicals, offering alternative and secure sources for applications in foodstuff, skincare, biofuels, and bioplastics. Nitrogen starvation is the primary strategy used to induce oil accumulation in oleaginous yeast as part of a global stress response. While research has demonstrated that post-translational modifications (PTMs), including phosphorylation and protein cysteine thiol oxidation (redox PTMs), are involved in signaling pathways that regulate stress responses in metazoa and algae, their role in oleaginous yeast remain understudied and unexplored. Results: Towards linking the yeast oleaginous phenotype to protein function, we integrated lipidomics, redox proteomics, and phosphoproteomics to investigate Rhodotorula toruloides under nitrogen-rich and starved conditions over time. Our lipidomics results unearthed interactions involving sphingolipids and cardiolipins with ER stress and mitophagy. Our redox and phosphoproteomics data highlighted the roles of the AMPK, TOR, and calcium signaling pathways in regulation of lipogenesis, autophagy, and oxidative stress response. As a first, we also demonstrated that lipogenic enzymes including fatty acid synthase are modified as a consequence of shifts in cellular redox states due to nutrient availability. Conclusions: We conclude that lipid accumulation is largely a consequence of carbon rerouting and autophagy governed by changes to PTMs, and not increases in the abundance of enzymes involved in central carbon metabolism and fatty acid biosynthesis. Our systems-level approach sets the stage for acquiring multidimensional data sets for protein structural modeling and predicting the functional relevance of PTMs using Artificial Intelligence/Machine Learning (AI/ML). Coupled to those bioinformatics approaches, the putative PTM switches that we delineate will enable advanced metabolic engineering strategies to decouple lipid accumulation from nitrogen limitation.

Lipid Signalling↗

Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake

Abstract Background Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world’s best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria. Results Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota. Conclusions We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction.

59 BASIC BIOLOGICAL SCIENCES↗

How low can they go when going with the flow? Tolerance of egg and larval fishes to rapid decompression

Egg and larval fish that drift downstream are likely to encounter river infrastructure and consequently rapid decompression, which may result in significant injury. In juvenile fish, pressure-related injury (or barotrauma) occurs when pressures fall sufficiently below the pressure at which the fish has acclimated. Because eggs and larvae are less-developed and more fragile than juveniles, there is a presumption that they may be at least as, if not more, susceptible to barotrauma injury, but studies to date report inconsistent results and none have considered the relationship between pressure change and barotrauma over a sufficiently broad range of pressure changes to enable detrimental levels to be properly determined. To address this, we exposed eggs and larvae of three physoclistic species to rapid decompression in a barometric chamber over a broad range of discrete pressure changes. Eggs, but not larvae, were unaffected by all levels of decompression tested. At exposure pressures below ~40 kPa, or ~40% of atmospheric pressure, swim bladder deflation occurred in all species and internal haemorrhage was observed in one species. None of these injuries killed the fish within 24 hours, but subsequent mortality cannot be excluded. Consequently, if larval drift is expected, it seems prudent to maintain exposure pressures at river infrastructure at 40% or more of the pressure to which a drifting larvae has acclimated.

break-point analysis↗

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗

Plant-Nitrifier Interactions in Topsoil and Subsoil

Plants can influence soil microbes through resource acquisition and interference competition, with consequences for ecosystem function such as nitrification. However, how plants alter soil conditions to influence nitrifiers and nitrification rates remains poorly understood, especially in the subsoil. Here, coupling the 15N isotopic pool dilution technique, high throughput sequencing and in situ soil O2 monitoring, we investigated how a deep-rooted perennial grass, miscanthus, versus an adjacent shallow-rooted turfgrass reference shapes nitrifier assembly and function along 1 m soil profiles. In topsoil, the suppression of ammonia (NH3) oxidizing archaea (AOA) and gross nitrification rates in miscanthus relative to the reference likely resulted from nitrifiers being outcompeted by plant roots and heterotrophic bacteria for ammonium (NH4+). The stronger tripartite competition under miscanthus may have been caused in part by the lower soil organic matter (SOM) content, which supported lower gross nitrogen (N) mineralization, the major soil process that produces NH4+. In contrast, below 10 cm soil depth, significantly greater gross nitrification rates were observed in miscanthus compared to the reference. This was likely driven by the significantly lower oxygen (O2) in miscanthus than reference subsoil, which selected against aerobic heterotrophic bacteria but in favor of AOA. Overall, we found that plants can regulate AOA community structure and function through different mechanisms in topsoil and subsoil, with suppression of nitrification in topsoil and enhancement of nitrification in subsoil.

Field Data↗

Regulatory Treatment of Low Frequency External Events under a Risk-Informed Performance-Based Licensing Pathway: Enhanced SPRA-based Margins Assessment

Recently there has been development in the field of risk-informed performance-based (RIPB) design and licensing approaches, which leverage detailed risk assessments and performance-based metrics to allow flexibility and innovation. These RIPB approaches include the probabilistic treatment of external hazards, including low frequency events that are beyond the design basis. However, there are certain challenges that have been identified to the probabilistic treatment of low frequency external events, primarily due to uncertainty in the hazard curve and the associated plant response to rare, severe events. The NRC is currently developing 10 CFR Part 53 that would establish a technology-inclusive regulatory framework for use by applicants for new commercial advanced nuclear reactors. By examining the regulatory safety criteria contained within draft 10 CFR Part 53 and associated draft RIPB seismic design guidance, potential challenges were identified in demonstrating satisfaction of the safety criteria for low frequency external events, with specific difficulties associated with demonstrating compliance with the quantitative health objectives (QHOs). Non-LWRs are expected to utilize the direct calculation of offsite consequence, rather than use surrogates, for comparison to the QHOs, which can be particularly challenging as the previously identified uncertainties are compounded by uncertainties in the response of the neighboring population. The central recommendation from this effort is that it is necessary to develop an approach for demonstrating compliance with the safety criteria in draft Part 53 that addresses the key challenges while providing flexibility to applicants. This paper summarizes key findings, establishes a series of high-level goals, and reviews a newly developed approach to address the major challenges associated with assessing compliance with QHOs, with avenues to demonstrate compliance based on either the estimated consequence or the available margin to event occurrence, while also building on existing experience of seismic margins assessments. The paper also provides examples to demonstrate the application of the approach, as well as recommendations and potential future work.

external hazards↗

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Chromoanagenesis from radiation-induced genome damage in Populus

Chromoanagenesis is a genomic catastrophe that results in chromosomal shattering and reassembly. These extreme single chromosome events were first identified in cancer, and have since been observed in other systems, but have so far only been formally documented in plants in the context of haploid induction crosses. The frequency, origins, consequences, and evolutionary impact of such major chromosomal remodeling in other situations remain obscure. Here, we demonstrate the occurrence of chromoanagenesis in poplar ( Populus sp . ) trees produced from gamma-irradiated pollen. Specifically, in this population of siblings carrying indel mutations, two individuals exhibited highly frequent copy number variation (CNV) clustered on a single chromosome, one of the hallmarks of chromoanagenesis. Using short-read sequencing, we confirmed the presence of clustered segmental rearrangement. Independently, we identified and validated novel DNA junctions and confirmed that they were clustered and corresponded to these rearrangements. Our reconstruction of the novel sequences suggests that the chromosomal segments have reorganized randomly to produce a novel rearranged chromosome but that two different mechanisms might be at play. Our results indicate that gamma irradiation can trigger chromoanagenesis, suggesting that this may also occur when natural or induced mutagens cause DNA breaks. We further demonstrate that such events can be tolerated in poplar, and even replicated clonally, providing an attractive system for more in-depth investigations of their consequences.

59 BASIC BIOLOGICAL SCIENCES↗

Coupling Genetic and Chemical Microbiome Profiling Reveals Heterogeneity of Archaeome and Bacteriome in Subsurface Biofilms That Are Dominated by the Same Archaeal Species

Earth harbors an enormous portion of subsurface microbial life, whose microbiome flux across geographical locations remains mainly unexplored due to difficult access to samples. Here, we investigated the microbiome relatedness of subsurface biofilms of two sulfidic springs in southeast Germany that have similar physical and chemical parameters and are fed by one deep groundwater current. Due to their unique hydrogeological setting these springs provide accessible windows to subsurface biofilms dominated by the same uncultivated archaeal species, called SM1 Euryarchaeon. Comparative analysis of infrared imaging spectra demonstrated great variations in archaeal membrane composition between biofilms of the two springs, suggesting different SM1 euryarchaeal strains of the same species at both aquifer outlets. This strain variation was supported by ultrastructural and metagenomic analyses of the archaeal biofilms, which included intergenic spacer region sequencing of the rRNA gene operon. At 16S rRNA gene level, PhyloChip G3 DNA microarray detected similar biofilm communities for archaea, but site-specific communities for bacteria. Both biofilms showed an enrichment of different deltaproteobacterial operational taxonomic units, whose families were, however, congruent as were their lipid spectra. Consequently, the function of the major proportion of the bacteriome appeared to be conserved across the geographic locations studied, which was confirmed by dsrB-directed quantitative PCR. Consequently, microbiome differences of these subsurface biofilms exist at subtle nuances for archaea (strain level variation) and at higher taxonomic levels for predominant bacteria without a substantial perturbation in bacteriome function. The results of this communication provide deep insight into the dynamics of subsurface microbial life and warrant its future investigation with regard to metabolic and genomic analyses.

54 ENVIRONMENTAL SCIENCES↗