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At least 37 records · Page 2

Imaginaries of the Pandemic in Chile: A Conceptual‐Empirical Discussion

This article aims to reconstruct the social imaginaries of Coronavirus disease 2019 (COVID‐19) in Chile. We seek to understand how families interpret their experience confronting the pandemic by identifying four main aspects: (a) the COVID‐19 pandemic, (b) working and learning, (c) health and (d) family life. Following Habermas' distinction between lifeworld and social systems, we consider these issues as constituting the social imaginary of lifeworld, different but related to the imaginaries of social systems. The qualitative empirical data was gathered through a sample of 38 families interviewed online between September 2020 and January 2021 in four Chilean cities: Iquique, Valparaíso, Santiago and Concepción. Other complementary sources of information are multimodal ethnography (digital diaries), press articles and state reports.

Vergara, Jorge Iván↗

Plant‐produced SARS ‐ CoV ‐2 antibody engineered towards enhanced potency and in vivo efficacy

Summary Prevention of severe COVID‐19 disease by SARS‐CoV‐2 in high‐risk patients, such as immuno‐compromised individuals, can be achieved by administration of antibody prophylaxis, but producing antibodies can be costly. Plant expression platforms allow substantial lower production costs compared to traditional bio‐manufacturing platforms depending on mammalian cells in bioreactors. In this study, we describe the expression, production and purification of the originally human COVA2‐15 antibody in plants. Our plant‐produced mAbs demonstrated comparable neutralizing activity with COVA2‐15 produced in mammalian cells. Furthermore, they exhibited similar capacity to prevent SARS‐CoV‐2 infection in a hamster model. To further enhance these biosimilars, we performed three glyco‐ and protein engineering techniques. First, to increase antibody half‐life, we introduced YTE‐mutation in the Fc tail; second, optimization ofN‐linked glycosylation by the addition of a C‐terminal ER‐retention motif (HDEL), and finally; production of mAb in plant production lines lacking β‐1,2‐xylosyltransferase and α‐1,3‐fucosyltransferase activities (FX‐KO). These engineered biosimilars exhibited optimized glycosylation, enhanced phagocytosis and NK cell activation capacity compared to conventional plant‐produced S15 and M15 biosimilars, in some cases outperforming mammalian cell produced COVA2‐15. These engineered antibodies hold great potential for enhancingin vivoefficacy of mAb treatment against COVID‐19 and provide a platform for the development of antibodies against other emerging viruses in a cost‐effective manner.

Biotechnology & Applied Microbiology↗

Dynamical model for social distancing in the U.S. during the COVID-19 epidemic

Social distancing has led to a “flattening of the curve” in many states across the U.S. This is part of a novel, massive, global social experiment which has served to mitigate the COVID-19 pandemic in the absence of a vaccine or effective anti-viral drugs. Hence it is important to be able to forecast hospitalizations reasonably accurately. We propose on phenomenological grounds a random walk/generalized diffusion equation which incorporates the effect of social distancing to describe the temporal evolution of the probability of having a given number of hospitalizations. The probability density function is log-normal in the number of hospitalizations, which is useful in describing pandemics where the number of hospitalizations is very high. We used this insight and data to make forecasts for states using Monte Carlo methods. Back testing validates our approach, which yields good results about a week into the future. States are beginning to reopen at the time of submission of this paper and our forecasts indicate possible precursors of increased hospitalizations. However, the trends we forecast for hospitalizations as well as infections thus far show moderate growth. Additionally we studied the reproducibility in New York (Italian strain) and California (Wuhan strain). We find that even if there is a difference in the transmission of the two strains, social distancing has been able to control the progression of COVID 19.

97 MATHEMATICS AND COMPUTING↗

Scenarios of a Sustainable Energy Transition: Perspectives from the U.S.

The energy sector has been undergoing a significant transition over the past decade, which was accelerated in 2020 during the COVD-19 pandemic. This presentation provides an overview of energy trends in the U.S., including electricity, oil and gas, coal, and renewables, the impact of the pandemic in 2020, and forecasts for recovery. Scenarios of energy use and future integrated technologies are outlined as near and mid-term approaches. The presentation concludes with potential U.S. policy priorities focused on energy and economic recovery, as well as perspectives on energy planning from the disruptions of 2020. The presentation is part of day-long series of presentations covering post-COVID-19 energy responses in Asia, Australia, Europe, and the United States.

COVID-19↗

Machine learning model to project the impact of COVID-19 on U.S. motor gasoline demand

Owing to the global lockdowns that resulted from the COVID-19 pandemic, fuel demand plummeted and the price of oil futures went negative in April 2020. Robust fuel demand projections are crucial to economic and energy planning and policy discussions. Here we incorporate pandemic projections and people's resulting travel and trip activities and fuel usage in a machine-learning-based model to project the US medium-term gasoline demand and study the impact of government intervention. We found that under the reference infection scenario, the US gasoline demand grows slowly after a quick rebound in May, and is unlikely to fully recover prior to October 2020. Under the reference and pessimistic scenario, continual lockdown (no reopening) could worsen the motor gasoline demand temporarily, but it helps the demand recover to a normal level quicker. Under the optimistic infection scenario, gasoline demand will recover close to the non-pandemic level by October 2020. The COVID 19 pandemic and consequent lockdown has had a substantial impact on mobility and therefore fuel demand and it is not clear when demand will recover. Ou et al. use a machine learning model that integrates health recovery scenarios to project the near-term future of gasoline demand.

COVID-19 pandemic↗

Testing a novel peptide drug towards a goal of reducing mortality in critically ill COVID19 patients

COVID 19 has been devastating the globe over the past year, and although our knowledge of how the disease progresses is constantly evolving, there is a significant amount we now about the mechanisms underlying COVID19. There is growing evidence that a 'cytokine storm' is a significant driver of mortality associated with COVID19, with studies showing high levels of hallmark inflammatory indicators in critically ill COVID19 patients. This essentially consists of the patient's immune system going awry and causing white blood cells to constantly release a large number of small molecules called cytokines. The result of this is further activation of the immune system, which ends up attacking not only infected but also healthy patient tissues, resulting in organ failure.

59 BASIC BIOLOGICAL SCIENCES↗

Pulmonary ACE2 expression in neonatal and adult rats

Children show a distinct presentation of COVID‐19, characterized by a lower incidence and mild phenotype, but the reason for this is still unknown. The angiotensin‐converting enzyme 2 (ACE2) functions as the primary cell entry receptor for Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and is thought to cause distinct clinical features between children and old people. The primary purpose of this study was to determine whether differences exist in the level of expression and distribution of ACE2 between neonatal and adult rat lungs. The lung tissues from rats of various ages were used to investigate the expression patterns of ACE2. Western blot, immunohistochemistry, and immunofluorescence were used to quantify or identify the localization of ACE2 in rat lungs. ACE2 was homogenously expressed in fewer alveolar type II (AT2) cells in the neonatal lung, with no polarization to the alveolar space and additional expression in pulmonary endothelium when compared to adult rat lungs. These findings suggest that the patterns of ACE2 distribution and cellular localization in rat lungs change with age.

Zhao, Depeng↗

RNA oligomers at atomic resolution containing 1‐methylpseudouridine, an essential building block of mRNA vaccines

Abstract All widely used mRNA vaccines against COVID‐19 contain in their sequence 1‐methylpseudouridine ( m1Ψ ) instead of uridine. In this publication, we report two high resolution crystal structures (at up to 1.01 and 1.32 Å, respectively) of one such double‐stranded 12‐mer RNA sequence crystallized in two crystal forms. The structures are compared with similar structures which do not contain this modification. Additionally, the X‐ray structure of 1‐methyl‐pseudouridine itself was determined.

Nievergelt, Philipp↗

Exploration of Nirmatrelvir Derivatives as Optimized SARS‐CoV‐2 Antivirals

Nirmatrelvir (NMV) is a SARS‐CoV‐2 antiviral component of the approved COVID‐19 therapeutic Paxlovid. It is a reversible covalent inhibitor of SARS‐CoV‐2 main protease (M Pro ) that is effluxed from human cells by P‐glycoprotein (P‐gp). To identify NMV analogs with improved potency and reduced P‐gp efflux, a structure–activity relationship campaign was conducted. Warheads alternative to nitrile for engaging the active site cysteine were tested showing aldehyde and dichloroacetamide with better enzyme inhibition potency. Crystal structure of MPI‐136−M Pro shows its aldehyde warhead forming a thiohemiacetal with active Cys145 of M Pro . Several S4 binders were explored revealing that an O‐to‐S shift at the N ‐terminal amide leads to better enzyme inhibition. By exploring different combinations of S2, S3, and S4 binders, two inhibitors with better enzyme inhibition potency than NMV were found. Crystal structure of MPI‐148, with ( S )‐2‐azaspiro[4,5]decane‐3‐carboxylate as an alternative S2 binder, shows extensive hydrogen‐bond networks for locking the inhibitor in active site, explaining high affinity of NMV analogs. Further characterization of cellular M Pro engagement and antiviral potency against SARS‐CoV‐2 revealed four inhibitors with greater potency than NMV in P‐gp‐expressing cells. Studies with the P‐gp inhibitor CP‐100356 showed that these compounds were less sensitive to P‐gp inhibition than NMV, consistent with reduced P‐gp‐mediated efflux.

Alugubelli, Yugendar R. [Texas A&M Drug Discovery ↗

Real‐time XFEL data analysis at SLAC and NERSC: A trial run of nascent exascale experimental data analysis

X‐ray scattering experiments using free electron lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID‐19 viral proteins). XFEL experiments are a challenge to computing in two ways: (i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; (ii) data‐collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min—sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS‐NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Completing data analysis within 10 min is a first for XFEL experiments and an important milestone if we are to keep up with data‐collection trends.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Commercialization of microcavity plasma devices and arrays: Systems for VUV photolithography and nanopatterning, disinfection of drinking water and air, and biofilm deactivation for medical therapeutics

Abstract A little more than two decades after the introduction of the first microcavity plasma devices, a growing body of commercial products based on the remarkable properties of these low‐temperature, atmospheric plasmas is now available. Following a brief review of early microplasma lamp development, this article describes microplasma‐based devices and systems currently being manufactured for applications in photolithography, photopatterning, and other nanofabrication processes, such as atomic layer deposition, spectroscopic identification and analysis of materials (including wide bandgap crystals), the disinfection of drinking water in off‐grid communities, deactivating COVID‐19 and other pathogens in air and on surfaces in public spaces, and vacuum ultraviolet lamps for driving atomic clocks. The microplasma‐based treatment of otitis media in the human ear will also be discussed.

42 ENGINEERING↗

Dual Inhibitors of SARS-CoV-2 3CL Protease and Human Cathepsin L Containing Glutamine Isosteres Are Anti-CoV-2 Agents

SARS-CoV-2 3CL protease (Main protease) and human cathepsin L are proteases that play unique roles in the infection of human cells by SARS-CoV-2, the causative agent of COVID-19. Both proteases recognize leucine and other hydrophobic amino acids at the P 2 position of a peptidomimetic inhibitor. At the P 1 position, cathepsin L accepts many amino acid side chains, with a partial preference for phenylalanine, while 3CL-PR protease has a stringent specificity for glutamine or glutamine analogues. We have designed, synthesized, and evaluated peptidomimetic aldehyde dual-target (dual-acting) inhibitors using two peptide scaffolds based on those of two Pfizer 3CL-PR inhibitors, Nirmatrelvir, and PF-835321. Our inhibitors contain glutamine isosteres at the P 1 position, including 2-pyridon-3-yl-alanine, 3-pyridinyl-alanine, and 1,3-oxazo-4-yl-alanine groups. Inhibition constants for these new inhibitors ranged from K i = 0.6–18 nM (cathepsin L) and K i = 2.6–124 nM (3CL-PR), for which inhibitors with the 2-pyridon-3-yl-alanal substituent were the most potent for 3CL-PR. The anti-CoV-2 activity of these inhibitors ranged from EC 50 = 0.47–15 μM. X-ray structures of the peptidomimetic aldehyde inhibitors of 3CL-PR with similar scaffolds all demonstrated the formation of thiohemiacetals with Cys 145 , and hydrogen-bonding interactions with the heteroatoms of the pyridon-3-yl-alanyl group, as well as the nitrogen of the N-terminal indole and its appended carbonyl group at the P 3 position. The absence of these hydrogen bonds for the inhibitors containing the 3-pyridinyl-alanyl and 1,3-oxazo-4-yl-alanyl groups was reflected in the less potent inhibition of the inhibitors with 3CL-PR. In summary, our studies demonstrate the value of a second generation of cysteine protease inhibitors that comprise a single agent that acts on both human cathepsin L and SARS-CoV-2 3CL protease. Such dual-target inhibitors will provide anti-COVID-19 drugs that remain active despite the development of resistance due to mutation of the viral protease. Such dual-target inhibitors are more likely to remain useful therapeutics despite the emergence of inactivating mutations in the viral protease because the human cathepsin L will not develop resistance. This particular dual-target approach is innovative since one of the targets is viral (3CL-PR) required for viral protein maturation and the other is human (hCatL) which enables viral infection.

60 APPLIED LIFE SCIENCES↗

Tipiracil binds to uridine site and inhibits Nsp15 endoribonuclease NendoU from SARS-CoV-2

SARS-CoV-2 Nsp15 is a uridine-specific endoribonuclease with C-terminal catalytic domain belonging to the EndoU family that is highly conserved in coronaviruses. As endoribonuclease activity seems to be responsible for the interference with the innate immune response, Nsp15 emerges as an attractive target for therapeutic intervention. Here we report the first structures with bound nucleotides and show how the enzyme specifically recognizes uridine moiety. In addition to a uridine site we present evidence for a second base binding site that can accommodate any base. The structure with a transition state analog, uridine vanadate, confirms interactions key to catalytic mechanisms. In the presence of manganese ions, the enzyme cleaves unpaired RNAs. This acquired knowledge was instrumental in identifying Tipiracil, an FDA approved drug that is used in the treatment of colorectal cancer, as a potential anti-COVID-19 drug. Using crystallography, biochemical, and whole-cell assays, we demonstrate that Tipiracil inhibits SARS-CoV-2 Nsp15 by interacting with the uridine binding pocket in the enzyme’s active site. Our findings provide new insights for the development of uracil scaffold-based drugs.

59 BASIC BIOLOGICAL SCIENCES↗

A model for selecting the best sustainable airport technology alternatives

Air transport is a continually expanding industry, a fact that has become even more evident with the recovery of the aviation industry post-COVID-19. This expansion amplified energy consumption at airports, which was already significantly high. Airport decision-makers are increasingly focusing on improving sustainability and addressing social, economic, and environmental criteria across airports worldwide. In this article, we propose a decision-making model for identifying a sustainable airport technology solution that minimizes the energy consumption of airport lighting while considering economic, emission, and life-cycle criteria. The proposed model combines data envelopment analysis and multi-criteria decision making techniques. We applied the model to the Dallas/Fort Worth International Airport (DFW) as a case study, considering eight lighting technology solutions, each with five luminous flux alternatives. Our model identified the best lighting technology solution for DFW outdoor and indoor environments based on the following criteria: luminous flux, capital costs, life-cycle costs, energy consumption, and emissions (CO2e, NOx, SO2, and PM2.5). The designed model is customizable to any airport and is applicable to a wide range of airport lighting technologies. In our analysis, Light-Emitting Diode lighting emerged as the most sustainable technology option. It ranked first in most cases due to its balance of high efficacy, long lifespan, low life-cycle cost, low capital cost, and lower emissions across all pollutants.

Tchivwila, Moise B↗

Bioinformatics and 3D Structural Analysis of the Coronavirus Main Protease Active Site Diversity

Coronaviruses (Coronaviridae) such as SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus) and MERS‐CoV (Middle East respiratory syndrome coronavirus) have been the source of recent outbreaks and global health concerns. While vaccines have been essential for controlling the SARS‐CoV‐2 (COVID‐19) pandemic, it is uncertain whether they will be effective against future coronavirus strains. Therefore, identification or design of a broad‐spectrum drug that targets highly conserved regions of the main protease of multiple coronavirus strains is essential in the long term. As part of a virtual summer research experience with the RCSB PDB, bioinformatics tools were employed to predict and construct 3D models of the coronavirus main protease (MPro) using SARS‐CoV‐2 as the template, with a focus on mutational trends and active sites. This study focused on the active sites of MPro, a cysteine protease essential for viral assembly and replication. Sequence alignments and structure modeling of MPro structures has identified conserved regions across multiple coronavirus strains. Inhibition of MPro halts coronavirus replication, making it an ideal drug target, and studies of MPro may foster and accelerate the discovery of high affinity broad‐spectrum drugs.

Wu Wu, Amy↗

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↗

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↗

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗