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At least 505 records · Page 28

Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms

Rapidly changing computer architectures, such as those found at high-performance computing (HPC) facilities, present the need for mini-applications (miniapps) that capture essential algorithms used in large applications to test program performance and portability, aiding transitions to new systems. The COVID-19 pandemic has fueled a flurry of activity in computational drug discovery, including the use of supercomputers and GPU acceleration for massive virtual screens for therapeutics. Recent work targeting COVID-19 at the Oak Ridge Leadership Computing Facility (OLCF) used the GPU-accelerated program AutoDock-GPU to screen billions of compounds on the Summit supercomputer. In this paper we present the development of a new miniapp, miniAutoDock-GPU, that can be used to evaluate the performance and portability of GPU-accelerated protein-ligand docking programs on different computer architectures. These tests are especially relevant as facilities transition from petascale systems and prepare for upcoming exascale systems that will use a variety of GPU vendors. The key calculations, namely, the Lamarckian genetic algorithm combined with a local search using a Solis-Wets based random optimization algorithm, are implemented. We developed versions of the miniapp using several different programming models for GPU acceleration, including a version using the CUDA runtime API for NVIDIA GPUs, and the Kokkos middle-ware API which is facilitated by C++ template libraries. A third version, currently in progress, uses the HIP programming model. These efforts will help facilitate the transition to exascale systems for this important emerging HPC application, as well as its use on a wide range of heterogeneous platforms.

Thavappiragasam, Mathialakan↗

Robust Deep Gaussian Process-Based Probabilistic Electrical Load Forecasting Against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This article proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining the excellent performance of capturing the forecasting uncertainties.

anomalous events↗

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗

The Potential of Low Molecular Weight Heparin to Mitigate Cytokine Storm in Severe COVID‐19 Patients: A Retrospective Cohort Study

On March 11, 2020, the World Health Organization declared its assessment of coronavirus disease 2019 (COVID‐19) as a global pandemic. However, specific anti‐severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) drugs are still under development, and patients are managed by multiple complementary treatments. We performed a retrospective analysis to compare and evaluate the effect of low molecular weight heparin (LMWH) treatment on disease progression. For this purpose, the clinical records and laboratory indicators were extracted from electronic medical records of 42 patients with COVID‐19 (21 of whom were treated with LMWH, and 21 without LMWH) hospitalized (Union Hospital of Huazhong University of Science and Technology) from February 1 to March 15, 2020. Changes in the percentage of lymphocytes before and after LMWH treatment were significantly different from those in the control group ( P = 0.011). Likewise, changes in the levels of D‐dimer and fibrinogen degradation products in the LMWH group before and after treatment were significantly different from those in the control group ( P = 0.035). Remarkably, IL‐6 levels were significantly reduced after LMWH treatment ( P = 0.006), indicating that, besides other beneficial properties, LMWH may exert an anti‐inflammatory effect and attenuate in part the “cytokine storm” induced by the virus. Our results support the use of LMWH as a potential therapeutic drug for the treatment of COVID‐19, paving the way for a subsequent well‐controlled clinical study.

Shi, Chen↗

Structure and epitope of a neutralizing monoclonal antibody that targets the stem helix of β coronaviruses

Monoclonal antibodies that retain neutralizing activity against multiple coronavirus (CoV) lineages and variants of concern (VoC) must be developed to protect against future pandemics. These broadly neutralizing MAbs (BNMAbs) may be used as therapeutics and/or to assist in the rational design of vaccines that induce BNMAbs. 1249A8 is a BNMAb that targets the stem helix (SH) region of CoV spike (S) protein and neutralizes Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) original strain, delta, and omicron VoC, Severe Acute Respiratory Syndrome CoV (SARS-CoV), and Middle East Respiratory Syndrome CoV (MERS-CoV). To understand its mechanism of action, the crystal structure of 1249A8 bound to a MERS-CoV SH peptide was determined at 2.1 Å resolution. BNMAb 1249A8 mimics the SARS-CoV-2 S loop residues 743–749, which interacts with the N-terminal end of the SH helix in the S post-fusion conformation. The conformation of 1249A8-bound SH is distinct from the SH conformation observed in the post-fusion SARS-CoV-2 S structure, suggesting 1249A8 disrupts the secondary structure and refolding events required for CoV post-fusion S to initiate membrane fusion and ultimately infection. This study provides novel insights into the neutralization mechanisms of SH-targeting CoV BNMAbs that may inform vaccine development and the design of optimal BNMAb therapeutics.

60 APPLIED LIFE SCIENCES↗

Nitrogen Deposition Weakens Soil Carbon Control of Nitrogen Dynamics Across the Contiguous United States

ABSTRACT Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta‐glucosidase (BG) and N ‐acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID‐19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

Nieland, Matthew A. [Stockbridge School of Agricul↗

Nonclassical autophagy activation pathways are essential for production of infectious Influenza A virus in vitro

Autophagy is a critical mechanism deployed by eukaryotic cells in response to stress, including viral infection, to boost the innate antimicrobial responses. However, an increasing number of pathogens hijack the autophagic machinery to facilitate their own replication. Influenza A virus (IAV), responsible for several global pandemics, has an intricate dependence on autophagy for successful replication in mammalian cells. To elucidate key chokepoints in the host stress responses facilitating IAV replication, we constructed a meta-transcriptome of IAV and host gene expression dynamics during early (1–3 hpi), mid (4–6 hpi), and late (8–12 hpi) stages of the viral replication cycle at two multiplicities of infection (MOI): 1 and 5. We supplemented the global transcriptome study with phosphoproteomic analysis of stress-activated protein kinase (SAPK/JNK) signaling in lung carcinoma (predominantly used as an in vitro model of IAV replication) and normal human bronchial epithelial cells. We report significant differences in the activation profiles of autophagy regulating genes upon IAV infection at the two MOI as well as divergent dependence on ULK1 signaling within the normal and cancer cells. Regardless of the cell model, JNK-Thr187 signaling was crucial for the production of infectious viral particles.

59 BASIC BIOLOGICAL SCIENCES↗

Direction of impact for explainable risk assessment modeling

Abstract Several graphical indicators have been recently introduced to help analysts visualize the marginal effects of inputs in complex models. The insights derived from such tools may help decision‐makers and risk analysts in designing interventions. However, we know little about the adequacy and consistency of different indicators. This work investigates popular marginal effect indicators to understand whether they yield indications consistent with the properties of the quantitative model under inspection. Specifically, we examine the notions of monotonicity, Lipschitz, and concavity consistency. Surprisingly, only PD functions satisfy all these notions of consistency. However, when selecting the indicators, in addition to consistency, analysts need to consider the risk of model extrapolation. For situations where such risk is under control, we utilize individual conditional expectations together with PD plots. Two applications, on a NASA space risk assessment model and a susceptible exposed infected recovered (SEIR) model for the COVID‐19 pandemic illustrate the insights obtained from these indicators.

Mathematical Methods In Social Sciences↗

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. In conclusion, identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

60 APPLIED LIFE SCIENCES↗

Multi-species outbreak of SARS-CoV-2 Delta variant in a zoological institution, with the detection in two new families of carnivores

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a worldwide distribution in humans and many other mammalian species. In late September 2021, 12 animals maintained by the Chicago Zoological Society's Brookfield Zoo were observed with variable clinical signs. The Delta variant of SARS-CoV-2 was detected in faeces and nasal swabs by qRT-PCR, including the first detection in animals from the families Procyonidae and Viverridae. Test positivity rate was 12.5% for 35 animals tested. All animals had been vaccinated with at least one dose of a recombinant vaccine designed for animals and all recovered with variable supportive treatment. Sequence analysis showed that six zoo animal strains were closely correlated with 18 human SARS-CoV-2 strains, suggestive of potential human-to-animal transmission events. This report documents the expanding host range of COVID-19 during the ongoing pandemic.

59 BASIC BIOLOGICAL SCIENCES↗

Emergence of SARS-CoV-2 through recombination and strong purifying selection

COVID-19 has become a global pandemic caused by the novel coronavirus SARS-CoV-2. Understanding the origins of SARS-CoV-2 is critical for deterring future zoonosis, discovering new drugs, and developing a vaccine. We show evidence of strong purifying selection around the receptor binding motif (RBM) in the spike and other genes among bat, pangolin, and human coronaviruses, suggesting similar evolutionary constraints in different host species. We also demonstrate that SARS-CoV-2’s entire RBM was introduced through recombination with coronaviruses from pangolins, possibly a critical step in the evolution of SARS-CoV-2’s ability to infect humans. Similar purifying selection in different host species, together with frequent recombination among coronaviruses, suggests a common evolutionary mechanism that could lead to new emerging human coronaviruses.

60 APPLIED LIFE SCIENCES↗

ChAdOx1 interacts with CAR and PF4 with implications for thrombosis with thrombocytopenia syndrome

Vaccines derived from chimpanzee adenovirus Y25 (ChAdOx1), human adenovirus type 26 (HAdV-D26), and human adenovirus type 5 (HAdV-C5) are critical in combatting the severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic. As part of the largest vaccination campaign in history, ultrarare side effects not seen in phase 3 trials, including thrombosis with thrombocytopenia syndrome (TTS), a rare condition resembling heparin-induced thrombocytopenia (HIT), have been observed. This study demonstrates that all three adenoviruses deployed as vaccination vectors versus SARS-CoV-2 bind to platelet factor 4 (PF4), a protein implicated in the pathogenesis of HIT. We have determined the structure of the ChAdOx1 viral vector and used it in state-of-the-art computational simulations to demonstrate an electrostatic interaction mechanism with PF4, which was confirmed experimentally by surface plasmon resonance. These data confirm that PF4 is capable of forming stable complexes with clinically relevant adenoviruses, an important step in unraveling the mechanisms underlying TTS.

60 APPLIED LIFE SCIENCES↗

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and x-ray diffraction at room temperature

The nonstructural protein 3 (NSP3) macrodomain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Mac1) removes adenosine diphosphate (ADP) ribosylation posttranslational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the coronavirus disease 2019 pandemic. Here, we determined neutron and x-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose–bound states. We characterize extensive solvation in the Mac1 active site and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase the potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a reevaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

60 APPLIED LIFE SCIENCES↗

Biochemical and structural insights into SARS-CoV-2 polyprotein processing by Mpro

SARS-CoV-2, a human coronavirus, is the causative agent of the COVID-19 pandemic. Its genome is translated into two large polyproteins subsequently cleaved by viral papain-like protease and main protease (Mpro). Polyprotein processing is essential yet incompletely understood. We studied Mpro-mediated processing of the nsp7-11 polyprotein, whose mature products include cofactors of the viral replicase, and identified the order of cleavages. Integrative modeling based on mass spectrometry (including hydrogen-deuterium exchange and cross-linking) and x-ray scattering yielded a nsp7-11 structural ensemble, demonstrating shared secondary structural elements with individual nsps. The pattern of cross-links and HDX footprint of the C145A Mpro and nsp7-11 complex demonstrate preferential binding of the enzyme active site to the polyprotein junction sites and additional transient contacts to help orient the enzyme on its substrate for cleavage. Last, proteolysis assays were used to characterize the effect of inhibitors/binders on Mpro processing/inhibition using the nsp7-11 polyprotein as substrate.

60 APPLIED LIFE SCIENCES↗

Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally, with >365,000 cases in California as of 17 July 2020. We investigated the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning nine counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least seven different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington state, with lack of a predominant lineage and limited transmission among communities. Lineages associated with outbreak clusters in two counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain the spread of SARS-CoV-2 in California and other states.

59 BASIC BIOLOGICAL SCIENCES↗

Structural and functional ramifications of antigenic drift in recent SARS-CoV-2 variants

Defenses against SARS-CoV-2 variants Our key defense against the COVID-19 pandemic is neutralizing antibodies against the SARS-CoV-2 virus elicited by natural infection or vaccination. Recent emerging viral variants have raised concern because of their potential to escape antibody neutralization. Wang et al . identified four antibodies from early-outbreak convalescent donors that are potent against 23 variants, including variants of concern, and characterized their binding to the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Yuan et al . examined the impact of emerging mutations in the receptor-binding domain of the spike protein on binding to the host receptor ACE2 and to a range of antibodies. These studies may be helpful for developing more broadly effective vaccines and therapeutic antibodies. —VV

59 BASIC BIOLOGICAL SCIENCES↗

Leverage demand-side policies for energy security

Energy security is a top priority for governments, companies, and households because energy systems and the critical functions that they support are threatened by disruptions from wars, pandemics, climate change, and other shocks (1). More often than not, governments rely on policies focused on energy supply to enhance energy security while generally ignoring demand-side possibilities. Further, the indicators traditionally used to measure energy security are also tilted toward the supply side; this fails to capture the full spectrum of vulnerability to energy crises. Energy security assessments need to reflect the wider benefits of security related interventions more accurately. To that end, we develop a systematic approach to measuring the energy security impacts of policy interventions that explicitly considers energy demand (buildings, transport, and industry). Here, we determine that demand-side actions outperform conventional supply-side approaches at making countries more resilient. Energy demand links more directly than supply to the satisfaction of critical social functions and human well-being that are at the core of energy security. Yet, demand-side perspectives tend to be neglected or underrepresented in analysis and policy debates on energy security. Factors that contribute to this supply-side bias include the traditional sectoral organization of industries and policy institutions along fuels (coal, oil, and gas) and energy forms (electric utilities) as well as the decentralized and multivaried activities characteristic of energy demand (from vehicles to household appliances to manufacturing and more), which leads to a multitude of actors and institutional fragmentation. The basic fundamentals of energy systems and markets, where demand and supply are intricately linked, have also not yet risen from vague awareness to a central organizing principle among policy-makers for structuring the energy security discourse.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗