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At least 955 records · Page 53

Ultrafast Optomechanical Strain in Layered GeS

Strong coupling between light and mechanical strain forms the foundation for next-generation optical micro- and nano-electromechanical systems. Such optomechanical responses in two-dimensional materials present novel types of functionalities arising from the weak van der Waals bond between atomic layers. In this paper, by using structure-sensitive megaelectronvolt ultrafast electron diffraction, we report the experimental observation of optically driven ultrafast in-plane strain in the layered group IV monochalcogenide germanium sulfide (GeS). Surprisingly, the photoinduced structural deformation exhibits strain amplitudes of order 0.1% with a 10 ps fast response time and a significant in-plane anisotropy between zigzag and armchair crystallographic directions. Rather than arising due to heating, experimental and theoretical investigations suggest deformation potentials caused by electronic density redistribution and converse piezoelectric effects generated by photoinduced electric fields are the dominant contributors to the observed dynamic anisotropic strains. Our observations define new avenues for ultrafast optomechanical control and strain engineering within functional devices.

2D materials↗

Surface-Functionalized Cellulose Nanocrystals as Nanofillers for Crosslinking Processes: Implications for Thermosetting Resins

Understanding the response of fillers in the epoxy resin crosslinking process and characterizing polymer–filler dynamics are the key features that guide the engineering of new thermosetting resin composites. Here, in this work, X-ray photon correlation spectroscopy (XPCS) is used as a thermal analysis tool to track the microscopic changes occurring during the cure of a functionalized cellulose nanocrystal (mCNC)–epoxy composite. In contrast, traditional methods such as differential scanning calorimetry (DSC) and curing rheology are used to understand the kinetics and properties on macroscopic length scales. Of interest is the influence of the mCNC on the curing kinetics and properties of the thermosetting resin. Two levels of modification (increasing hydrophobicity) were chosen to observe the effect of functionalization. Before cure, the highly functionalized CNC (mCNC3) shows a 44% increase in complex viscosity (η*), while the less functionalized CNC (mCNC2) shows a η* value similar to that of the neat resin. As the cure cycle progresses, results from DSC, rheology, and XPCS further show the enhancement in dispersion for mCNC3. The results show a clear difference in the maximum drift velocity, maximum heat flow, and complex viscosity during the ramp to the isothermal cure temperature (T cure ). Such results suggest that mCNC3 contains a well-dispersed network of particles due to the higher level of functionalization. During T cure , a transition in elastic modulus (G') occurs only for the highly functionalized CNC particle system. We believe that heat-induced aggregation occurs, and the crosslinked resin ultimately dominates the macroscopic properties of the final cured system for all samples. The results from the three techniques are in good agreement and showcase XPCS as a beneficial experimental tool for characterizing the microscopic dynamics of particulate-filled thermosetting resins. Hence, we envision this to be a fundamental curing study for the design of thermosetting resin composites.

36 MATERIALS SCIENCE↗

Severe and mild drought cause distinct phylogenetically linked shifts in the blue grama (Bouteloua gracilis) rhizobiome

Plants rely on a diverse rhizobiome to regulate nutrient acquisition and plant health. With increasing severity and frequency of droughts worldwide due to climate change, untangling the relationships between plants and their rhizobiomes is vital to maintaining agricultural productivity and protecting ecosystem diversity. While some plant physiological responses to drought are generally conserved, patterns of root exudation (release of small metabolites shown to influence microbes) and the consequential effects on the plant rhizobiome can differ widely across plant species under drought. To address this knowledge gap, we conducted a greenhouse study using blue grama ( Bouteloua gracilis ), a drought-tolerant C4 grass native to shortgrass prairie across North American plains, as a model organism to study the effect of increasing drought severity (ambient, mild drought, severe drought) on root exudation and the rhizobiome. Our previous results demonstrated physiological effects of increasing drought severity including an increase in belowground carbon allocation through root exudation and shifts in root exudate composition concurrent with the gradient of drought severity. This work is focused on the rhizobiome community structure using targeted sequencing and found that mild and severe drought resulted in unique shifts in the bacterial + archaeal and fungal communities relative to ambient, non-droughted controls. Specifically, using the change in relative abundance between ambient and drought conditions for each ZOTU as a surrogate for population-scale drought tolerance (e.g., as a response trait), we found that rhizobiome response to drought was non-randomly distributed across the phylogenies of both communities, suggesting that Planctomycetota , Thermoproteota (formerly Thaumarchaeota ), and the Glomeromycota were the primary clades driving these changes. Correlation analyses indicated weak correlations between droughted community composition and a select few root exudate compounds previously implicated in plant drought responses including pyruvic acid, D-glucose, and myoinositol. This study demonstrates the variable impacts of drought severity on the composition of the blue grama rhizobiome and provides a platform for hypothesis generation for targeted functional studies of specific taxa involved in plant-microbe drought responses.

Goemann, Hannah M.↗

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗

Field experiments show no consistent reductions in soil microbial carbon in response to warming

Soil microbes play an essential role in maintaining soil functions and services, but the dynamics of soil microbial biomass carbon (MBC) under global climate change remain unclear. Recently, Patoine et al. combined a global MBC data set with Random Forest modeling and reported that global MBC decreased over 1992–2013, mainly driven by increasing temperatures. Contrarily, using MBC field observations from soil warming manipulation experiments and in-situ long-term measurements across the globe, we found that MBC showed no significant changes under soil warming. Our findings indicate that soil MBC is unlikely to have decreased significantly due to the global warming of 0.28 °C during 1992–2013, and that further mechanistic studies are needed to understand potential changes in MBC under climate change.

54 ENVIRONMENTAL SCIENCES↗

EEPD1 evolved a unique DNA clamping dimer protecting reversed replication forks

Exonuclease/endonuclease/phosphatase (EEP)-fold hydrolases are canonically monomeric phosphodiesterases exemplified by APE1, DNase I, and TDP2 nucleases. While EEP family domain containing protein 1 (EEPD1) acts in DNA stress responses, its proposed nuclease activities are enigmatic. Here, we integrate hybrid structural methods, evolution, biochemistry, cancer genomics, plus molecular and cell biology to define EEPD1 structure, assembly, and function at stalled DNA replication forks. Results imply EEPD1 surprisingly requires both unique EEP domain dimer and distinctive tandem Helix-hairpin-Helix [(HhH) 2 ] domains to clamp double-stranded (ds) DNA at reversed DNA replication forks for fork protection. Small-angle X-ray Scattering (SAXS), crystal, and cryo-EM structures unveil an unprecedented tryptophan handshake dimer, conserved interface di-Trp-Pro pocket, and adjustable “wrist” enabling an open-closed conformational switch. EEPD1 dimer cooperatively binds complex dsDNA replication fork intermediates but alone lacks nuclease activity due to loss of key EEP catalytic residues during Metazoan evolution and atmospheric oxygen buildup. Instead, EEPD1 prevents nucleolytic degradation of reversed replication forks by MRE11. Furthermore, cancer bioinformatics support oxidative damage-dependent EEPD1 association as a significant modulator of overall patient survival. Collective findings uncover unexpected EEP dimer and fork protection function in clamping, not cleaving, reversed replication forks for metazoan oxidative stress responses controlling genome stability and cancer outcomes.

Shen, Runze [Univ. of Texas, Houston, TX (United S↗

Verification Testing For Solid-Element Material Models 11-19 in DYNA3D/ParaDyn

This technical report documents the creation and implementation of verification tests for solid-element material models 11 through 19 available in DYNA3D/ParaDyn. The verification tests covered all aspects of each material model, except for the Weibull distribution functionality in material models 15 and 19. General test cases were created to verify the elastic and plastic behavior of the material models. Other additional tests were developed to examine the intricacies of each material model. Each test involved the use a kinematic load case and specification of material parameters necessary to activate corresponding features of the material model. The load cases prescribed the full time history of the kinematic motion for the solid elements, and these loads are independent of the material model or element formulation. When possible, closed form solutions were then derived for each verification test in a continuum setting. The DYNA3D simulations for each test were carried out over a unit time interval, t ϵ [0, 1], and the as implemented DYNA3D response was compared to the closed form solutions evaluated at discrete points in time. A relative error measure was determined for each test to justify the proper implementation of the material model. The relative errors comparing the DYNA3D solution to the analytical solution were, in general, on the order of machine precision except where noted. This signifies the proper implementation of solid-element material models 11-19. In the development of these verification tests, six bugs were found and fixed in the source code. Additionally, this work generated eighteen DYNA3D input decks and answer extraction scripts in the DYNA3D/ParaDyn Software Quality Assurance test suite, which are comprised of a total of 285 solid-element tests. Testing for each material model utilizes two input decks and answer extraction scripts, where one focuses on the linear elastic response and the other examines the inelastic and remaining functionalities of the material model. In total, this work added 285 individual verification test problems in the DYNA3D/ParaDyn test suite.

42 ENGINEERING↗

Evaluation of the Radioactive Material Released in the Harborview Research and Training Building and Some Implications for Emergency Response

On 2 May 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a mobile hot cell on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%, was released from the mobile hot cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy’s Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. Furthermore, the implications for emergency response are relevant to data quality and management. A Data Quality Objective guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and archiving of samples.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Phase Switching as the Origin of Large Piezoelectric Response in Organic-Inorganic Perovskites: A First-Principles Study

Piezoelectrics are critical functional components of many practical applications such as sensors, ultrasonic transducers, actuators, medical imaging, telecommunications. So far, the best performing piezoelectrics are ferroelectric ceramics, many of which are toxic, heavy, hard, and cost-ineffective. Recently, a groundbreaking discovery of extraordinarily large piezoelectric coefficients in the family of organic-inorganic perovskites gave a hope for a cheaper, environmentally friendly, inexpensive, light-weight and flexible alternative. However, the origin of such response in organic-inorganic ferroelectrics whose spontaneous polarization is an order of magnitude smaller than for inorganic counterparts remains unclear. In this study we employ first-principles simulations to predict that the mechanism associated with large piezoelectric constants is of extrinsic origin and associated with switching between the stable phase and previously overlooked energetically competitive metastable phase that can be stabilized by the external stress. Here, the phase switching changes the polarization direction and, therefore, gives origin to large piezoelectric response, similar to PbZr$_{1-x}$Ti$_x$O$_3$ near morphotropic phase boundary. Existence of such metastable phases is likely to manifest as the dynamical molecular disorder above the Curie temperature and, therefore, could be intrinsic to the entire family of organic-inorganic ferroelectrics with such disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Non-volatile electric-field control of inversion symmetry

Competition between ground states at phase boundaries can lead to significant changes in properties under stimuli, particularly when these ground states have different crystal symmetries. A key challenge is to stabilize and control the coexistence of symmetry-distinct phases. Using BiFeO 3 layers confined between layers of dielectric TbScO 3 as a model system, we stabilize the mixed-phase coexistence of centrosymmetric and non-centrosymmetric BiFeO 3 phases at room temperature with antipolar, insulating and polar semiconducting behaviour, respectively. Application of orthogonal in-plane electric (polar) fields results in reversible non-volatile interconversion between the two phases, hence removing and introducing centrosymmetry. Counterintuitively, we find that an electric field 'erases' polarization, resulting from the anisotropy in octahedral tilts introduced by the interweaving TbScO 3 layers. Consequently, this interconversion between centrosymmetric and non-centrosymmetric phases generates changes in the non-linear optical response of over three orders of magnitude, resistivity of over five orders of magnitude and control of microscopic polar order. Here our work establishes a platform for cross-functional devices that take advantage of changes in optical, electrical and ferroic responses, and demonstrates octahedral tilts as an important order parameter in materials interface design.

36 MATERIALS SCIENCE↗

Towards Quantum-Chemical Level Calculations of SARS-CoV-2 Spike Protein Variants of Concern by First Principles Density Functional Theory

The spike protein (S-protein) is a crucial part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with its many domains responsible for binding, fusion, and host cell entry. In this review we use the density functional theory (DFT) calculations to analyze the atomic-scale interactions and investigate the consequences of mutations in S-protein domains. We specifically describe the key amino acids and functions of each domain, which are essential for structural stability as well as recognition and fusion processes with the host cell; in addition, we speculate on how mutations affect these properties. Such unprecedented large-scale ab initio calculations, with up to 5000 atoms in the system, are based on the novel concept of amino acid–amino acid-bond pair unit (AABPU) that allows for an alternative description of proteins, providing valuable information on partial charge, interatomic bonding and hydrogen bond (HB) formation. In general, our results show that the S-protein mutations for different variants foster an increased positive partial charge, alter the interatomic interactions, and disrupt the HB networks. We conclude by outlining a roadmap for future computational research of biomolecular virus-related systems.

60 APPLIED LIFE SCIENCES↗

TARP Identifying Critical Thresholds for Acute Response of Plants and Ecosystems to Water Stress at Walker Branch Watershed, 2002-2005

This dataset contains data from a manipulative field study aimed at identifying critical thresholds for acute response of plants and ecosystems to water stress (TARP) that took place at Walker Branch Watershed in Oak Ridge, Tennessee from 2002-2005 (2002-06-20 to 2005-12-16). The study used understory tents for the removal of 100% of the growing-season throughfall and stem flow, to provide data on the impact of acute drought on mechanisms responsible for growth and mortality of deciduous forest canopy trees representative of common plant functional types (Liriodendron and Quercus). Through three years of manipulation (2003, 2004 and 2005; pretreatment measurements in 2002) various measures of tree response to surface moisture deficits were recorded including root and leaf traits, plant nonstructural carbohydrates status, hourly sapflow, basal area, and periodic observations of foliar photosynthesis and conductance. Additionally, environmental data such as air and soil temperature, soil water content, and soil matric potential were recorded. This dataset contains data 16 files in comma-separate (*.csv) format. Additional metadata are provided: 16 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

basal area↗

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗

Direct Functionalization of Established 3D-Printed Aza-Michael Liquid Crystal Elastomers with Donor–Acceptor Stenhouse Adducts

Extrusion 3D printing has advanced the manufacturing of complex liquid crystal elastomer (LCE) architectures. In parallel, donor–acceptor Stenhouse adducts (DASAs), a class of white-light-responsive photoswitches, have enabled both photochemical and photothermal LCE actuation. However, DASA–LCEs have yet to be extruded and 3D-printed. Two key challenges exist: DASA’s inherent sensitivity to heat and radicals can lead to degradation during ink preparation and printing, and small changes in the concentration of the added DASA component impact the properties of the extrudable ink, requiring reoptimization of well-established 3D-printing protocols. To overcome these challenges, we present a post-printing functionalization strategy that circumvents these limitations. Residual secondary amines, inherent to inks synthesized via standard aza-Michael addition, serve as active sites for covalent attachment of DASA photoresponsive groups following printing and cross-linking. Our method means that DASAs can be directly grafted onto 3D-printed aza-Michael LCEs without modifying the ink formulation or processing. The resulting DASA–LCEs exhibit wavelength tunability within the visible range and a variety of photothermal and photochemical responses. The post-functionalization can occur within 2 min and enables spatial control of the DASA concentration, producing films with tunable color gradients and locally varied photothermal and photochemical responses under visible light. In conclusion, this approach enables the rapid fabrication of DASA-based light-responsive LCEs using established ink formulations with the potential for the design of complex 3D architectures.

3D printing↗

Elevated temperature alters microbial communities, but not decomposition rates, during 3 years of in situ peat decomposition

ABSTRACT Peatlands are large carbon sinks with primary production outpacing decomposition of organic matter. Results from the S pruce and P eatland R esponses U nder C hanging E nvironments (SPRUCE) study show net losses of organic matter and increased greenhouse gas production from peatlands in response to whole-ecosystem warming. Here, we investigated how warming and elevated CO 2 impact peat microbial communities and peat soil decomposition rates and characterized microbial communities through amplicon sequencing and compositional changes across four depth increments. Microbial diversity and community composition were significantly impacted by soil depth, temperature, and CO 2 treatment. Bacterial/archaeal α-diversity increased significantly with increasing temperature, and fungal α-diversity was lower under elevated CO 2 treatments. Trans domain microbial networks showed higher complexity of microbial communities in decomposition ladder depths from the warmed enclosures, and the number of highly connected hub taxa within the networks was positively correlated with temperature. Methanogenic hubs were identified in the networks constructed from the warmest enclosures, indicating increased importance of methanogenesis in response to warming. Microbial community responses were not however reflected in measures of peat soil decomposition, as warming and elevated CO 2 had no significant short-term effects on soil mass loss or composition. Regardless of treatment, on average only 4.5% of the original soil mass was lost after 3 years and variation between replicates was high, potentially masking treatment effects. Previous results at the SPRUCE experiment have shown warming is accelerating organic-matter decomposition and CO 2 and CH 4 production, and our results suggest these changes may be driven by warming-induced shifts in microbial communities. IMPORTANCE Microbial community changes in response to climate change drivers have the potential to alter the trajectory of important ecosystem functions. In this paper, we show that while microbial communities in peatland systems responded to manipulations of temperature and CO 2 concentrations, these changes were not associated with similar responses in peat decomposition rates over 3 years. It is unclear however from our current studies whether this functional resiliency over 3 years will continue over the longer time scales relevant to peatland ecosystem functions.

54 ENVIRONMENTAL SCIENCES↗

Circadian immunometabolic states impart a temporal response to SARS-CoV-2 spike proteins in mammalian macrophages

Circadian rhythms, the 24-hour cycles that tune organismal physiology to the daily rhythms of light and dark, optimally organize cellular processes such as metabolism and mitochondrial function. In mammals, macrophage functions are regulated by these 24-hour circadian rhythms such that the immunometabolic response is coordinated across the day, consolidating macrophage physiology into temporally distinct phases to time the cellular immune response. However, while it is known that there are time-of-day specific responses to stress in a macrophage, little has been done to determine if circadian regulation coordinates the response of a macrophage to real-world pathogens. Importantly, key proteins in the response to viral infection have been found to be under circadian control, and time of day of application is known to affect the efficacy of vaccinations, including in the case of the COVID-19 virus. Therefore, to investigate if the circadian regulation of macrophage physiology imparted a time-of-day response to viral exposure, we exposed primary mouse and human macrophages to the SARS-CoV-1 and CoV-2 spike proteins at different times over the circadian day. To establish a time-of-day effect, we performed a multi-omics analysis and in vitro tissue culture assays examining macrophage responses over circadian time. We found that, conserved across the species, the timing of spike protein exposure dictated two distinct temporal responses which were characterized by hallmarks of immunometabolic suppression and modest inflammatory activation. However, these responses were primarily influenced by central metabolic and mitochondrial changes and not by classical immune activation.

Circadian Biology↗