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DOE OSTI2019

A Hybrid Reinforcement Learning and Cellular Automata Model for Crowd Simulation on the GPU

We present a GPU-based hybrid model for crowd simulations. The model uses reinforcement learning to guide groups of pedestrians towards a goal while adapting to environmental dynamics, and a cellular automaton to describe individual pedestrians’ interactions. In contrast to traditional multi-agent reinforcement learning methods, our model encodes the learned navigation policy into a navigation map, which is used by the cellular automaton’s update rule to calculate the next simulation step. As a result, reinforcement learning is independent of the number of agents, allowing the simulation of large crowds. Implementation of this model on the GPU allows interactive simulations of several hundreds of pedestrians.

Ruiz, Sergio↗

DOE OSTI2020

Cellular and extracellular C contributions to respiration after wetting dry soil

Wetting of dry soil triggers a pulse of microbial respiration that has been attributed to two broad mechanisms: (1) recycling of microbial cellular carbon (C), and (2) consumption of extracellular organic C made available to microbes by wetting. We evaluated these two mechanisms by measuring cumulative CO 2 release, changes in the size and chemical composition of microbial biomass, and water-extractable organic carbon (WEOC) concentrations following artificial wetting of soil sampled from two depths at each of seven sites across California spanning a range of geologic parent materials. In samples collected from surface soil (0–10 cm depth), we found that cumulative CO 2 release after wetting in the laboratory was most strongly correlated with microbial biomass. In these samples, the relative abundance of trehalose—a putative microbial osmolyte—decreased from 25% (SD = 12) to 16% (SD = 7) of the chloroform-labile fraction of the microbial biomass after wetting. This suggested a role for osmolyte consumption in generating the respiration pulse. In subsoil (40–50 cm depth, or sampled at contact with rock), however, the cumulative CO2 release after wetting was unrelated to microbial biomass and more strongly related to WEOC. The concentrations of selected microbial biomass constituents (e.g. trehalose and amino acids) in WEOC were negligible (< 1%), suggesting that cell lysis was not important in generating WEOC in this study. The amount of WEOC relative to total organic C was greatest in subsoil, and negatively related to ammonium oxalate-extractable Fe (Pearson’s R = 0.42, p < 0.01), suggesting a role for soil mineralogical properties in controlling WEOC release. Together, these findings suggest that microbial cellular C and extracellular C jointly contribute to the respiration pulse, and that their relative contribution depends on depth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Interrelations of Apoptotic and Cellular Senescence Genes Methylation in Inflammatory Bowel Disease Subtypes and Colorectal Carcinoma in Egyptians Patients

Ras-related domain family member 1 transcript variant A (RASSF1A) controls apoptosis and cell proliferation while p14/ARF gene has a regulatory role in cellular senescence. Failure of apoptosis and cellular senescence occurs during inflammatory bowel disease (IBD) and colorectal cancer (CRC). To reveal the role of peripheral leukocyte promoter methylation of RASSF1A and p14/ARF in the pathogenesis of IBD subtypes and CRC we investigated the methylation state of the two genes by methylation-specific polymerase chain reaction (MSP-PCR) in 60 CRC patients, 60 patients with IBD; 27 with ulcerative colitis and 33 had Crohn’s disease and also in 30 healthy subjects. Methylated RASSF1A and p14/ARF genes were detected in 55% and 60% of CRC, while the frequency of the methylated RASSF1A and p14/ARF genes was 23.3% and 43.3% in IBD patients and 3.3% and 13.3% in the control group (P = 0.000 each). Also, the frequency of methylated RASSF1A gene was significantly higher in ulcerative colitis than in Crohn’s disease, while a non-significant frequency of methylated p14/ARF was detected between ulcerative colitis and Crohn’s disease. Furthermore, methylated RASSF1A and p14/ARF were associated with the grade of CRC but not associated with the age of patients, family history, or tumor location. Results suggest that methylated RASSF1A and p14/ARF are related to CRC and IBD pathogenesis and may be used as molecular biomarkers for early detection of CRC and IBD.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Dynamic and Programmable Cellular-Scale Granules Enable Tissue-like Materials

Living tissues are an integrated, multiscale architecture consisting of dense cellular ensembles and extracellular matrices (ECMs). The cells and ECMs cooperate to enable specialized mechanical properties and dynamic responsiveness. However, the mechanical properties of living tissues are difficult to replicate. A particular challenge is identification of a cell-like synthetic component, which is tightly integrated with its matrix and also responsive to external stimuli. Here, we demonstrate that cellular-scale hydrated starch granules, an underexplored component in materials science, can turn conventional hydrogels into tissue-like materials when composites are formed. By using several synchrotron-based X-ray techniques, we reveal the mechanically induced organization and training dynamics of the starch granules in the hydrogel matrix. These dynamic behaviors enable multiple tissue-like properties such as programmability, anisotropy, strain-stiffening, mechanochemistry, and self-healability.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Cellular metabolic stress responses via organelles

Metabolite fluctuations following nutrient metabolism or environmental stresses impact various intracellular signaling networks and stress responses to maintain cellular and organismal homeostasis. It has been shown that subcellular organelles, such as the endoplasmic reticulum, the Golgi apparatus, lysosomes and mitochondria serve as crucial hubs linking alterations in metabolite levels to cellular responses. This role is coordinated by molecular machineries that are associated with the lipid membranes of organelles, which sense the fluctuations in specific metabolites and activate the appropriate signaling and effector molecules. Moreover, recent studies have demonstrated that membraneless organelles, such as the nucleolus and stress granules, are involved in the metabolic stress response. Metabolite-induced post-translational modifications appear to play an important role in this process. Here, we review the molecular mechanisms of metabolite sensing and metabolite-mediated stress responses through membrane-bound and membraneless organelles in mammalian cells.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Tailoring Biomimetic Phosphorylcholine-Containing Block Copolymers as Membrane-Targeting Cellular Rescue Agents

Some synthetic polymers can block cell death when applied following an injury that would otherwise kill the cell. This cellular rescue occurs through interactions of the polymers with cell membranes. However, general principles for designing synthetic polymers to ensure strong, but nondisruptive, cell membrane targeting are not fully elucidated. Here, we tailored biomimetic phosphorylcholine-containing block copolymers to interact with cell membranes and determined their efficacy in blocking neuronal death following oxygen-glucose deprivation. By adjusting the hydrophilicity and membrane affinity of poly(2-methacryloyloxyethyl phosphorylcholine) (polyMPC)-based triblock copolymers, the surface active regime in which the copolymers function effectively as membrane-targeting cellular rescue agents was determined. We identified nonintrusive interactions between the polymer and the cell membrane that alter the collective dynamics of the membrane by inducing rigidification without disrupting lipid packing or membrane thickness. Furthermore, our results open new avenues for biological applications of polyMPC-based polymers and provide an approach to designing membrane-targeting agents to block cell death after injury.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging

Metabolic trade-offs between growth and productivity are key constraints in metabolic engineering and adaptive evolution; however, how cellular noise impacts these trade offs and drives the emergence of subpopulations with distinct resource allocation strategies, remains largely unknown. Here, we introduce a single-cell strategy for quantifying the trade-offs between triacylglycerol production and growth in the oleaginous microorganism Yarrowia lipolytica. The strategy relies on high-throughput quantitative-phase imaging and, enabled by nanoscale secondary ion mass spectrometry analyses and dedicated image processing, allows us to image how resources are partitioned between growth and productivity. Enhanced precision over population-averaging biotechnologies and conventional microscopy demonstrates how cellular noise impacts growth and productivity differently. As such, subpopulations with distinct metabolic trade-offs emerge, with notable impacts on strain performance and robustness. By quantifying autophagic catabolic fluxes under nutrient-limiting conditions, we discover an underlying cell-to-cell heterogeneity in protein and fatty-acid recycling, unmasking a potential bet-hedging survival strategy under starvation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Multimodal interference-based imaging of nanoscale structure and macromolecular motion uncovers UV induced cellular paroxysm

Understanding the relationship between intracellular motion and macromolecular structure remains a challenge in biology. Macromolecular structures are assembled from numerous molecules, some of which cannot be labeled. Most techniques to study motion require potentially cytotoxic dyes or transfection, which can alter cellular behavior and are susceptible to photobleaching. Here in this paper, we present a multimodal label-free imaging platform for measuring intracellular structure and macromolecular dynamics in living cells with a sensitivity to macromolecular structure as small as 20 nm and millisecond temporal resolution. We develop and validate a theory for temporal measurements of light interference. In vitro, we study how higher-order chromatin structure and dynamics change during cell differentiation and ultraviolet (UV) light irradiation. Finally, we discover cellular paroxysms, a near-instantaneous burst of macromolecular motion that occurs during UV induced cell death. With nanoscale sensitive, millisecond resolved capabilities, this platform could address critical questions about macromolecular behavior in live cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Collective motion conceals fitness differences in crowded cellular populations

Many cellular populations are tightly packed, such as microbial colonies and biofilms, or tissues and tumours in multicellular organisms. The movement of one cell in these crowded assemblages requires motion of others, so that cell displacements are correlated over many cell diameters. Whenever movement is important for survival or growth, these correlated rearrangements could couple the evolutionary fate of different lineages. However, little is known about the interplay between mechanical forces and evolution in dense cellular populations. Here, by tracking slower-growing clones at the expanding edge of yeast colonies, we show that the collective motion of cells prevents costly mutations from being weeded out rapidly. Joint pushing by neighbouring cells generates correlated movements that suppress the differential displacements required for selection to act. This mechanical screening of fitness differences allows slower-growing mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue. Our work suggests that, in crowded populations, cells cooperate with surrounding neighbours through inevitable mechanical interactions. This effect has to be considered when predicting evolutionary outcomes, such as the emergence of drug resistance or cancer evolution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Cellular, molecular, and therapeutic characterization of pilocarpine-induced temporal lobe epilepsy

Animal models have expanded our understanding of temporal lobe epilepsy (TLE). However, translating these to cell-specific druggable hypotheses is not explored. Herein, we conducted an integrative insilico-analysis of an available transcriptomics dataset obtained from animals with pilocarpine-induced-TLE. A set of 119 genes with subtle-to-moderate impact predicted most forms of epilepsy with ~ 97% accuracy and characteristically mapped to upregulated homeostatic and downregulated synaptic pathways. The deconvolution of cellular proportions revealed opposing changes in diverse cell types. The proportion of nonneuronal cells increased whereas that of interneurons, except for those expressing vasoactive intestinal peptide (Vip), decreased, and pyramidal neurons of the cornu-ammonis (CA) subfields showed the highest variation in proportion. A probabilistic Bayesian-network demonstrated an aberrant and oscillating physiological interaction between nonneuronal cells involved in the blood–brain-barrier and Vip interneurons in driving seizures, and their role was evaluated insilico using transcriptomic changes induced by valproic-acid, which showed opposing effects in the two cell-types. Additionally, we revealed novel epileptic and antiepileptic mechanisms and predicted drugs using causal inference, outperforming the present drug repurposing approaches. These well-powered findings not only expand the understanding of TLE and seizure oscillation, but also provide predictive biomarkers of epilepsy, cellular and causal micro-circuitry changes associated with it, and a drug-discovery method focusing on these events.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Spatial Proteomics towards cellular Resolution

Introduction: Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level. Areas covered: This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution. Expert opinion: The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. In conclusion, achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Response of solidification cellular structures in additively manufactured 316 stainless steel to heavy ion irradiation: an in situ study

In-core or cladding structural materials exposed to heavy ion irradiation often suffer serious irradiation-induced damages. Introducing defect sinks can effectively mitigate irradiation-induced degradation in materials. Here, we investigated the radiation response of additively manufactured 316 austenitic stainless steel with high-density solidification cellular structures via in situ Kr ++ irradiation at 400°C to 5dpa. The study shows that the trapped dislocations along with the cellular walls can serve as effective defect sinks, thus reduce dislocation loop density compared with the conventional coarse-grained counterparts. This study provides a positive step for the potential applications of radiation-resistant, additively manufactured steels in advanced nuclear reactors.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Time-resolved cryogenic electron tomography for the study of transient cellular processes

Cryogenic electron tomography (cryo-ET) is the highest resolution imaging technique applicable to the life sciences, enabling sub-nanometer visualization of specimens preserved in their near native states. The rapid plunge freezing process used to prepare samples lends itself to time-resolved studies, which researchers have pursued for in vitro samples for decades. Here, we focus on developing a freezing apparatus for time-resolved studies in situ. The device mixes cellular samples with solution-phase stimulants before spraying them directly onto an electron microscopy grid that is transiting into cryogenic liquid ethane. By varying the flow rates of cell and stimulant solutions within the device, we can control the reaction time from tens of milliseconds to over a second prior to freezing. In a proof-of-principle demonstration, the freezing method is applied to a model bacterium, Caulobacter crescentus, mixed with an acidic buffer. Through cryo-ET we resolved structural changes throughout the cell, including surface-layer protein dissolution, outer membrane deformation, and cytosolic rearrangement, all within 1.5 seconds of reaction time. This new approach, Time-Resolved cryo-ET (TR-cryo-ET), enhances the capabilities of cryo-ET by incorporating a sub-second temporal axis and enables the visualization of induced structural changes at the molecular, organelle, or cellular level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗

DOE OSTI2026

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗

DOE OSTI2024

Staircase resiliency in a fluctuating cellular array

Inhomogeneous mixing by stationary convective cells set in a fixed array is a particularly simple route to layering. Layered profile structures, or staircases, have been observed in many systems, including drift-wave turbulence in magnetic confinement devices. The simplest type of staircase occurs in passive-scalar advection, due to the existence and interplay of two disparate timescales, the cell turn-over (τ H ), and the cell diffusion (τ D ) time. In this simple system, we study the resiliency of the staircase structure in the presence of global transverse shear and weak vortex scattering. The fixed cellular array is then generalized to a fluctuating vortex array in a series of numerical experiments. The focus is on regimes of low-modest effective Reynolds numbers, as found in magnetic fusion devices. By systematically perturbing the elements of the vortex array, we learn that staircases form and are resilient (although steps become less regular, due to cell mergers) over a broad range of Reynolds numbers. The criteria for resiliency are (a) τ D >>τ H and (b) a sufficiently high profile curvature (κ ≥ 1.5). We learn that scalar concentration travels along regions of shear, thus staircase barriers form first, and scalar concentration "homogenizes" in vortices later. The scattering of vortices induces a lower effective speed of scalar concentration front propagation. The paths are those of the least time. We observe that if background diffusion is kept fixed, the cell geometric properties can be used to derive an approximation for the effective diffusivity of the scalar. Furthermore, the effective diffusivity of the fluctuating vortex array does not deviate significantly from that of the fixed cellular array.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Biomechanical Feedback Strengthens Jammed Cellular Packings

Growth in confined spaces can drive cellular populations through a jamming transition from a fluidlike state to a solidlike state. Experiments have found that jammed budding yeast populations can build up extreme compressive pressures (over 1 MPa), which in turn feed back onto cellular physiology by slowing or even stalling cell growth. Using numerical simulations, we investigate how this feedback impacts the mechanical properties of model jammed cell populations. In this work, we find that feedback directs growth toward poorly coordinated regions, resulting in an excess number of cell-cell contacts that rigidify cell packings. Cell packings possess anomalously large shear and bulk moduli that depend sensitively on the strength of feedback. These results demonstrate that mechanical feedback on the single-cell level is a simple mechanism by which living systems may tune their population-level mechanical properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Nonlocal Finite-Depth Circuits for Constructing Symmetry-Protected Topological States and Quantum Cellular Automata

Whether a given target state can be prepared by starting with a simple product state and acting with a finite-depth quantum circuit is a key question in condensed matter physics and quantum information science. It underpins classifications of topological phases, as well as the understanding of topological quantum codes, and has obvious relevance for device implementations. Traditionally, this question assumes that the quantum circuit is made up of unitary gates that are . Inspired by the advent of noisy intermediate-scale quantum devices, we reconsider this question with k - gates, i.e., gates that act on no more than k degrees of freedom but are not restricted to be geometrically local. First, we construct explicit finite-depth circuits of symmetric k -local gates that create symmetry-protected topological (SPT) states from an initial product state. Our construction applies to SPT states protected by global symmetries or subsystem symmetries but not to those with higher-form symmetries, which we conjecture remain nontrivial. Next, we show how to implement arbitrary translationally invariant quantum cellular automata in any dimension using finite-depth circuits of k -local gates. These results imply that the topological classifications of SPT phases and quantum cellular automata both collapse to a single trivial phase in the presence of k -local interactions. We furthermore argue that SPT phases are fragile to k -local symmetric perturbations. We conclude by discussing the implications for other phases, such as fracton phases, and surveying future directions. Our analysis opens a new experimentally motivated conceptual direction examining the stability of phases and the feasibility of state preparation without the assumption of geometric locality. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗