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At least 1,045 records · Page 58

Generative AI for Power Grid Operations

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, and some studies have performed system-level analysis, few have been able to provide a network-based model of the TRN that also provides the relative shifts in transcriptional regulator activity triggered by changing environments. Here, we compiled a compendium of nearly 650 publicly available, high quality M. tuberculosis RNA-sequencing data sets and applied an unsupervised machine learning method to obtain a quantitative, top-down TRN. It consists of 80 independently modulated gene sets known as “iModulons,” 41 of which correspond to known regulons. These iModulons explain 61% of the variance in the organism’s transcriptional response. We show that iModulons (i) reveal the function of poorly characterized regulons, (ii) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and infection events, and (iii) identify intrinsic clusters of regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

59 BASIC BIOLOGICAL SCIENCES↗

Language evolution and human-computer interaction

Many of the issues that confront designers of interactive computer systems also appear in natural language evolution. Natural languages and human-computer interfaces share as their primary mission the support of extended 'dialogues' between responsive entities. Because in each case one participant is a human being, some of the pressures operating on natural languages, causing them to evolve in order to better support such dialogue, also operate on human-computer 'languages' or interfaces. This does not necessarily push interfaces in the direction of natural language - since one entity in this dialogue is not a human, this is not to be expected. Nonetheless, by discerning where the pressures that guide natural language evolution also appear in human-computer interaction, we can contribute to the design of computer systems and obtain a new perspective on natural languages.

Grudin, Jonathan↗

Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments

‘Cell Painting’ is an imaging-based high-throughput phenotypic profiling (HTPP) method in which cultured cells are fluorescently labeled to visualize subcellular structures (i.e., nucleus, nucleoli, endoplasmic reticulum, cytoskeleton, Golgi apparatus / plasma membrane and mitochondria) and to quantify morphological changes in response to chemicals or other perturbagens. HTPP is a high-throughput and cost-effective bioactivity screening method that detects effects associated with many different molecular mechanisms in an untargeted manner, enabling rapid in vitro hazard assessment for thousands of chemicals. Here, 1201 chemicals from the ToxCast library were screened in concentration-response up to ~100 μM in human U-2 OS cells using HTPP. A phenotype altering concentration (PAC) was estimated for chemicals active in the tested range. PACs tended to be higher than lower bound potency values estimated from a broad collection of targeted high-throughput assays, but lower than the threshold for cytotoxicity. In vitro to in vivo extrapolation (IVIVE) was used to estimate administered equivalent doses (AEDs) based on PACs for comparison to human exposure predictions. AEDs for 18/412 chemicals overlapped with predicted human exposures. Phenotypic profile information was also leveraged to identify putative mechanisms of action and group chemicals. Of 58 known nuclear receptor modulators, only glucocorticoids and retinoids produced characteristic profiles; and both receptor types are expressed in U-2 OS cells. Thirteen chemicals with profile similarity to glucocorticoids were tested in a secondary screen and one chemical, pyrene, was confirmed by an orthogonal gene expression assay as a novel putative GR modulating chemical. Most active chemicals demonstrated profiles not associated with a known mechanism-of-action. However, many structurally related chemicals produced similar profiles, with exceptions such as diniconazole, whose profile differed from other active conazoles. Overall, the present study demonstrates how HTPP can be applied in screening-level chemical assessments through a series of examples and brief case studies.

60 APPLIED LIFE SCIENCES↗

Omics-Lethal Human Viruses, Influenza A Experiment ICL104

The purpose of this experiment was to evaluate the host response to Influenza A pandemic wild-type H1N1 (A/California/04/2009), natural isolate virus. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) with wild-type H1N1 virus (A/California/04/2009) and processed for mRNA, miRNA, proteomics, metabolomics, and lipidomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Biologically-Inspired Concepts for Autonomic Self-Protection in Multiagent Systems

Biologically-inspired autonomous and autonomic systems (AAS) are essentially concerned with creating self-directed and self-managing systems based on metaphors &om nature and the human body, such as the autonomic nervous system. Agent technologies have been identified as a key enabler for engineering autonomy and autonomicity in systems, both in terms of retrofitting into legacy systems and in designing new systems. Handing over responsibility to systems themselves raises concerns for humans with regard to safety and security. This paper reports on the continued investigation into a strand of research on how to engineer self-protection mechanisms into systems to assist in encouraging confidence regarding security when utilizing autonomy and autonomicity. This includes utilizing the apoptosis and quiescence metaphors to potentially provide a self-destruct or self-sleep signal between autonomic agents when needed, and an ALice signal to facilitate self-identification and self-certification between anonymous autonomous agents and systems.

Sterritt, Roy↗

Load compensating reactions to perturbations at wrist joint in normal man

The electromyographic responses to step torque loads were studied in flexors and extensors at the human wrist. Based on temporal bursting patterns and functional behavior, the response was divided into four temporal components. Two early components, the myotatic (30-60 ms) late myotatic (60-120 ms) appears to be reflex response. The third postmyotatic component (120-200 ms) appear to be a triggered reaction, preceeding the fourth, stabilizing component (200-400 ms). A comparison of response at the wrist with similar data at the ankle provides the basis for a generalized classification of the response in various muscles to torque step perturbations.

Jaeger, R. J.↗

Neurovascular Outcomes of Ionizing Radiation in Human Blood-Brain Barrier Models

One of the main health risks in human deep space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neurodegeneration and neuroinflammation associated with cognitive and behavioral dysfunction. The extent of CNS damage is partially mediated by the blood-brain barrier (BBB), which regulates the interaction between CNS and systemic responses to stressors in the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, neuroinflammation and oxidative stress. However, studies on BBB and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we developed a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments caused by deep space radiation. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5Gy 250MeV/n 4He and 0.3-0.8Gy 600MeV/n 56Fe; as well as to 0.5-1Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by damage to endothelial cells and tight junctions, altered cytokine expression including TNFalpha upregulation, and increased oxidative stress. In particular, 600MeV/n 56Fe particle irradiation selectively induced astrocyte damage and blood-brain barrier permeability only in models that contained astrocytes in addition to endothelial cells, indicating astrocytes as a particularly radiosensitive component of the CNS that could therefore be a suitable a target for neuroprotection. Future studies will compare human and mouse CNS model responses to simulated GCRs and evaluate the induction of an anti-inflammatory phenotype in astrocytes as a potential countermeasure. Ultimately, we aim to expand upon these results to uncover novel cellular and mechanistic targets for countermeasure development to mitigate human CNS damage in deep space exploration.

space radiation↗

Neurovascular Outcomes of Space Radiation in Human Blood-Brain Barrier Models

One of the main health risks in human deep space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neurodegeneration and neuroinflammation associated with cognitive and behavioral dysfunction. The extent of CNS damage is partially mediated by the blood-brain barrier (BBB), which regulates the interaction between CNS and systemic responses to stressors in the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, neuroinflammation and oxidative stress. However, studies on BBB and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we developed a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments caused by deep space radiation. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5Gy 250MeV/n 4He and 0.3-0.8Gy 600MeV/n 56Fe; as well as to 0.5-1Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by damage to endothelial cells and tight junctions, altered cytokine expression including TNFalpha upregulation, and increased oxidative stress. In particular, 600MeV/n 56Fe particle irradiation selectively induced astrocyte damage and increased blood-brain barrier permeability only in models that contained astrocytes in addition to endothelial cells, indicating astrocytes as a particularly radiosensitive component of the CNS that could therefore be a suitable a target for neuroprotection. Future studies will compare human and mouse CNS model responses to simulated GCRs and evaluate the induction of an anti-inflammatory phenotype in astrocytes as a potential countermeasure. Ultimately, we aim to expand upon these results to uncover novel cellular and mechanistic targets for countermeasure development to mitigate human CNS damage in deep space exploration.

centrat nervous system↗

Neurovascular Outcomes of Ionizing Radiation in Human Blood-Brain Barrier Models

One of the main health risks in human deep space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neurodegeneration and neuroinflammation associated with cognitive and behavioral dysfunction. The extent of CNS damage is partially mediated by the blood-brain barrier (BBB), which regulates the interaction between CNS and systemic responses to stressors in the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, neuroinflammation and oxidative stress. However, studies on BBB and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we developed a high throughput 3D human neurovascular system model, based on commercially available Mimetas OrganoPlates seeded by primary human cells, to investigate the neurovascular responses to simulated deep space radiation. Using this system, we have demonstrated that 600MeV/n 56Fe irradiation leads to cellular damage and increased blood-brain barrier permeability via dysfunction of brain cells called astrocytes, which appear to be the weakest link and therefore a highly suitable countermeasure target to reduce the impact of space radiation on the blood-brain barrier. We anticipate that our results form merely the first step in ongoing development of organ models, including their adaptation for personalized risk assessment, high throughput approaches to countermeasure screening and validation, and eventual payload adaptation.

organ-on-a-chip↗

Discovery and characterization of a selective IKZF2 glue degrader for cancer immunotherapy

Malignant tumors can evade destruction by the immune system by attracting immune-suppressive regulatory T cells (Treg) cells. The IKZF2 (Helios) transcription factor plays a crucial role in maintaining function and stability of Treg cells, and IKZF2 deficiency reduces tumor growth in mice. Here we report the discovery of NVP-DKY709, a selective molecular glue degrader of IKZF2 that spares IKZF1/3. We describe the recruitment-guided medicinal chemistry campaign leading to NVP-DKY709 that redirected the degradation selectivity of cereblon (CRBN) binders from IKZF1 toward IKZF2. Selectivity of NVP-DKY709 for IKZF2 was rationalized by analyzing the DDB1:CRBN:NVP-DKY709:IKZF2(ZF2 or ZF2-3) ternary complex X-ray structures. Exposure to NVP-DKY709 reduced the suppressive activity of human Treg cells and rescued cytokine production in exhausted T-effector cells. In vivo, treatment with NVP-DKY709 delayed tumor growth in mice with a humanized immune system and enhanced immunization responses in cynomolgus monkeys. NVP-DKY709 is being investigated in the clinic as an immune-enhancing agent for cancer immunotherapy.

59 BASIC BIOLOGICAL SCIENCES↗

Network analysis uncovers the communication structure of SARS-CoV-2 spike protein identifying sites for immunogen design

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has triggered myriad efforts to understand the structure and dynamics of this complex pathogen. The spike glycoprotein of SARS-CoV-2 is a significant target for immunogens as it is the means by which the virus enters human cells, while simultaneously sporting mutations responsible for immune escape. These functional and escape processes are regulated by complex molecular-level interactions. Our study presents quantitative insights on domain and residue contributions to allosteric communication, immune evasion, and local- and global-level control of functions through the derivation of a weighted graph representation from all-atom MD simulations. Focusing on the ancestral form and the D614G-variant, we provide evidence of the utility of our approach by guiding the selection of a mutation that alters the spike’s stability. Taken together, the network approach serves as a valuable tool to evaluate communication “hot-spots” in proteins to guide design of stable immunogens.

60 APPLIED LIFE SCIENCES↗

Expression, purification and characterization of human proton-coupled oligopeptide transporter 1 hPEPT1

The human peptide transporter hPEPT1 (SLC15A1) is responsible for uptake of dietary di- and tripeptides and a number of drugs from the small intestine by utilizing the proton electrochemical gradient, and hence an important target for peptide-like drug design and drug delivery. hPEPT1 belongs to the ubiquitous major facilitator superfamily that all contain a 12TM core structure, with global conformational changes occurring during the transport cycle. Several bacterial homologues of these transporters have been characterized, providing valuable insight into the transport mechanism of this family. Here we report the overexpression and purification of recombinant hPEPT1 in a detergent-solubilized state. Thermostability profiling of hPEPT1 at different pH values revealed that hPEPT1 is more stable at pH 6 as compared to pH 7 and 8. Micro-scale thermophoresis (MST) confirmed that the purified hPEPT1 was able to bind di- and tripeptides respectively. To assess the in-solution oligomeric state of hPEPT1, negative stain electron microscopy was performed, demonstrating a predominantly monomeric state.

59 BASIC BIOLOGICAL SCIENCES↗

Demand Response Analysis for Different Residential Personas in a Comfort-Driven Behavioral Context

Low demand response (DR) participation and high program drop-out rates continue to impede DR goals that could save up to $13 billion in annual grid expansion and electricity demand costs. Yet, the literature lacks a thorough understanding of how different residential customer segments enrolled in DR programs respond to utility signals in view of occupant comfort considerations. The objective of this study is to gain a clear understanding of the effects of four different customer personas on residential DR. Given current data limitations, this work developed an array of hypothetical personas with varied priorities, activity levels, and comfort thresholds based on demographic variables that have been found in previous studies to influence energy consumption. A BEopt DR model for a reference residential single-family building located in Colorado was built to isolate the effect of differences in buildings or climate. The results provide useful evidence on how persona-comfort differences lead to significant deviations in DR goals (especially peak demand reduction), ranging from 0.1% to 20%. This work presents a novel framework representing comfort preferences in DR models. The data generated, albeit synthetic, and the results could inform DR program design considerations of how different people respond to different comfort priorities.

BEopt↗

CRISPR-prime editing, a versatile genetic tool to create specific mutations with a single nucleotide resolution in Leptospira

ABSTRACT Leptospirosis, caused by pathogenic bacteria from the genusLeptospira, is a global zoonosis responsible for more than one million human cases and 60,000 deaths annually. The disease also affects many domestic animal species. Historically, genetic manipulation ofLeptospirahas been difficult to perform, resulting in limited knowledge on pathogenic mechanisms of disease and the identification of virulence factors. The application of CRISPR/Cas9 and its variations have helped fill these gaps but the generation of knockout mutants remains challenging because double-strand breaks (DSBs) inflicted by Cas9 nuclease are lethal toLeptospiracells. The novel CRISPR prime editing (PE) strategy is the first precise genome-editing technology that allows deletions, insertions, and base substitutions without introducing DSBs. This revolutionary technique utilizes a nickase Cas9 that cleaves a single strand of DNA, coupled with an engineered reverse transcriptase and a modified single-guide RNA (termed prime editing guide RNA) containing an extended 3′ end with the desired edits. We demonstrate the application of CRISPR-PE in both saprophytic and pathogenicLeptospirafrom multiple species and serovars by introducing deletions or insertions into target DNA with a remarkable precision of just one nucleotide. Additionally, we demonstrate the ability to genetically manipulateLeptospira borgpetersenii, a prevalent pathogenic species of humans, domestic cattle, and wildlife animals. Rapid plasmid loss by mutated strains in liquid culture allows for the generation of knockout strains without selective markers, which can be readily used to elucidate virulence factors and develop optimized bacterin and/or live vaccines against leptospirosis. IMPORTANCE Leptospirosis is a geographically widespread bacterial zoonosis. Genetic manipulation of pathogenicLeptospiraspp. has been laborious and difficult to perform, limiting our ability to understand how leptospires cause disease. The application of the CRISPR/Cas9 system toLeptospiraenhanced our ability to generate knockdown and knockout mutants; however, the latter remains challenging. Here, we demonstrate the application of the CRISPR prime editing technique inLeptospira, allowing the generation of knockout mutants in several pathogenic species, with mutations comprising just a single nucleotide resolution. Notably, we generated a mutant in theLeptospira borgpeterseniibackground, a prevalent pathogenic species of humans and cattle. Our application of this method opens new avenues for studying pathogenic mechanisms ofLeptospiraand the identification of virulence factors across multiple species. These methods can also be used to facilitate the generation of marker-less knockout strains for updated and improved bacterin and/or live vaccines.

Microbiology↗

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗

PILOT REACTION TO HIGH SPEED ROTATION

Ten pilots subjected to high speed rotation to determine their susceptibility to motion sickness, vestibular nystagmus and performance of complex functions

ROTATING VEHICLE↗