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At least 757 records · Page 42

Localized energy burden, concentrated disadvantage, and the feminization of energy poverty

Energy burden directly influences households' health and safety. Amid a growing literature on energy, poverty and gender remains relatively understudied. We evaluate socioeconomic, geographic, and health factors as multidimensions of concentrated disadvantage that magnify energy burden in the United States over time. We show that the energy burden is more pronounced in disadvantaged counties with larger elderly, impoverished, disabled people, and racialized populations where people do not have health insurance. Neighborhoods with households headed by women of color (especially Black women) are more likely to face a high energy burden, which worsened during the COVID-19 pandemic. Although energy costs are often regarded as an individual responsibility, these findings illustrate the feminization of energy poverty and indicate the need for an intersectional and interdisciplinary framework in devising energy policy directed to households with the most severe energy burden.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗

Agnostic capture of pathogens for the detection and diagnostics of emerging threats

The continued emergence of pathogens, whether novel, re-emerging, or engineered, poses a persistent global biosecurity and public health challenge. Recent outbreaks, including COVID-19, Lassa fever, Marburg virus, mpox, and avian influenza, underscore the urgent need for robust systems that enable rapid surveillance, early diagnosis, and timely countermeasures before widespread human transmission occurs. In this article, we focus on early detection technologies and systematically evaluate current diagnostic and sensing modalities. We highlight sequencing and spectroscopy as two complementary approaches capable of providing broad, agnostic detection and rich biological insight. Our analysis emphasizes that scientific innovation alone is insufficient: effective preparedness also requires improved data curation, integration, and sharing to build AI-ready resources that accelerate future responses. We argue for coordinated advances in both technological capabilities and supporting infrastructure to enable the rapid identification and characterization of emerging pathogens and to fully leverage modern science against evolving infectious threats.

Environmental health↗

Structural insights into protection against a SARS-CoV-2 spike variant by T cell receptor diversity

T cells play a crucial role in combatting SARS-CoV-2 and forming long-term memory responses to this coronavirus. The emergence of SARS-CoV-2 variants that can evade T cell immunity has raised concerns about vaccine efficacy and the risk of reinfection. Some SARS-CoV-2 T cell epitopes elicit clonally restricted CD8 + T cell responses characterized by T cell receptors (TCRs) that lack structural diversity. Mutations in such epitopes can lead to loss of recognition by most T cells specific for that epitope, facilitating viral escape. Here, we studied an HLA-A2–restricted spike protein epitope (RLQ) that elicits CD8 + T cell responses in COVID-19 convalescent patients characterized by highly diverse TCRs. We previously reported the structure of an RLQ-specific TCR (RLQ3) with greatly reduced recognition of the most common natural variant of the RLQ epitope (T1006I). Opposite to RLQ3, TCR RLQ7 recognizes T1006I with even higher functional avidity than the WT epitope. To explain the ability of RLQ7, but not RLQ3, to tolerate the T1006I mutation, we determined structures of RLQ7 bound to RLQ–HLA-A2 and T1006I–HLA-A2. These complexes show that there are multiple structural solutions to recognizing RLQ and thereby generating a clonally diverse T cell response to this epitope that assures protection against viral escape and T cell clonal loss.

60 APPLIED LIFE SCIENCES↗

Morphological and Phenotypic Characteristics of the Bovine Nasopharyngeal Mucosa and Associated Lymphoid Tissue

The mammalian nasopharynx is an anatomically complex region of the upper respiratory tract that directly communicates with the nasal cavity, laryngopharynx, oesophagus and trachea. The nasopharyngeal mucosa contains moderate quantities of mucosa-associated lymphoid tissue (MALT) that is appropriately located for immunological sampling but also creates vulnerability to pathogens. In recent years, the nasopharynx has been inculpated in the pathogenesis of important diseases of cattle (foot-and-mouth disease) and humans (COVID-19), yet the tissue has never been described in detail in any species. In order to characterize the morphology and cellular composition of the bovine nasopharynx, samples of mucosa were collected from the nasopharynx of five 8–13-month-old steers and examined using light microscopy, immunohistochemistry and multichannel immunofluorescence. Morphologically, the nasopharyngeal epithelium was highly heterogeneous, with a continuum ranging from stratified squamous epithelium to highly attenuated, follicle-associated epithelium (FAE). Distribution of MALT was similarly regionally variable ranging from absent to clusters of multiple lymphoid follicles. Phenotypic characterization demonstrated dense distributions of dendritic cells and T lymphocytes surrounding lymphoid follicles, which comprised mostly B lymphocytes. The FAE overlaying the lymphoid follicles also contained higher numbers of dendritic cells and lymphocytes compared with the adjacent non-lymphoid epithelium, although cytotoxic T cells were notably scarce in the FAE. The bovine nasopharyngeal lymphoid tissue had comparable elements to other MALTs with specific differences that may help to elucidate the pathogenesis of infectious agents that have specific tropism for this tissue.

59 BASIC BIOLOGICAL SCIENCES↗

Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding

The paper considers testing and signal identification for covariance matrices from two populations of marginally sub-Gaussian distributed. A multi-level thresholding procedure is proposed for testing the equality of two high-dimensional covariance matrices, which is designed to detect sparse and faint differences between the covariances. A novel -statistic composition is developed to establish the asymptotic distribution of the thresholding statistics in conjunction with the matrix blocking and the coupling techniques. It is shown that the proposed test is more powerful than the existing tests in detecting sparse and weak signals in covariances. Multiple testing procedures are constructed to discover different covariances and the sub-groups of variables with different covariance structures between the two populations. The proposed procedures are based on the multi-level thresholding test, which are able to control the false discovery proportion () with high power. Simulation experiments and a case study on the returns of the S&P 500 stocks before and after the COVID-19 pandemic are conducted to demonstrate and compare the utilities of the proposed methods.

97 MATHEMATICS AND COMPUTING↗

Potential impact of work from home jobs on residential energy bills: A case study in phoenix, AZ, USA

Nearly one-third of U.S. households face challenges paying energy bills. During the day, many residents have routine access to cooled environments provided by others—employers, shopping centers, and other public buildings. The COVID-19 pandemic, however, has significantly shifted the cost burden of air conditioning in hot cities. Specifically, during the pandemic, many companies either laid off employees or put them in work-from-home (WFH) assignments. Large tech companies are already promoting WFH as a long-term option for their employees, even after the pandemic. This change in the nature of the workforce might reduce daily travel expenses for workers, but could also significantly increase residential energy bills, particularly during summer in very hot climates. Here, this study uses building energy simulations to quantify the potential residential energy bill penalties resulting from WFH for typical residences in Phoenix. Four building archetypes are used in this study to represent variations in building vintage, occupancy, and characteristics. The results show that, for some single-family residences in Phoenix, WFH can increase annual energy bills by more than $1100 (up to a 70% increase). The study also demonstrates that building performance enhancement retrofit measures have the potential to reduce this WFH energy bill penalty for the existing buildings substantially.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Realizing "Net-Zero-Carbon" Sustainable Aviation Fuel

The aviation industry needs renewable and fungible jet fuel - commonly referred to as sustainable aviation fuel (SAF) - to minimize emissions and increase efficiencies. SAF can displace the same, if not more, CO2 equivalent emissions (CO2eq), reduce contrail formation, and increase engine-aircraft efficiencies. Flight represents ~10% of transportation greenhouse gas emissions, with the global consumption of ~400 billion liters of fossil jet fuel in 2019 releasing over 900 million tons of CO2eq. Even with impacts from the COVID-19 global pandemic, the aviation sector is projected to grow with passenger miles expected to double by 2050, relative to 2010. As such, there is an urgent need to produce drop-in aviation fuel from renewables with a dramatically lower carbon footprint.

biojet↗

Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid

Structural biologists and the open-access Protein Data Bank (PDB) played decisive roles in combating the COVID-19 pandemic. Global biostructure data were turned into global knowledge, allowing scientists and engineers to understand the inner workings of coronaviruses and develop effective countermeasures. Two mRNA vaccines, initially designed with guidance from PDB structures of the SARS-CoV-1 and MERS-CoV spike proteins, prevented infections entirely or reduced the likelihood of morbidity and mortality for more than five billion individual recipients worldwide. Structure-guided drug discovery by Pfizer, Inc (facilitated by PDB structures), initiated in the 2000s in response to SARS-CoV-1 and resumed in 2020, yielded nirmatrelvir (the active ingredient of Paxlovid) -- a potent, orally-bioavailable inhibitor of the SARS-CoV-2 main protease. You've got to love the Protein Data Bank!

Burley, Stephen K.↗

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. Finally, a synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation

60 APPLIED LIFE SCIENCES↗

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗

Using Facebook to Recruit Urban Participants for Smartphone-Based Travel Surveys

Social media has become an integral part of everyday life for many individuals, serving as a platform to express opinions, share memories and lifestyles, follow news, and adapt to social trends and norms. The wealth of user information and analytics on these platforms has facilitated the development and sale of tailored products and services, benefiting advertisers and researchers seeking survey participants. Social media advertising has demonstrated its effectiveness in reaching hard-to-reach populations. However, transport researchers have yet to capitalise on this potential fully. This paper presents our experience using social media to recruit participants for two smartphone travel surveys conducted in Australia. We demonstrate that social media recruitment and smartphone-based travel surveys are highly effective, adaptable, and can be rapidly deployed in response to research opportunities, such as during the early phase of the COVID-19 pandemic when traditional methods may be less suitable. This approach also holds great potential for travel surveys targeting the general population. This paper shares several lessons from this experiment, including our administrative approach and detailed technical instructions to utilise open-source software tools for conducting smartphone travel surveys like ours. This approach significantly reduces study costs compared to most commercial solutions.

97 MATHEMATICS AND COMPUTING↗

Defending Weapons Inspections from the Effects of Disinformation

The intentional spread of disinformation is not a new challenge for the scientific world. We have seen it perpetuate the idea of a flat earth, convince communities that vaccines are more dangerous than helpful, and even suggest a connection between the “5G” communication infrastructure and COVID-19. Nor is disinformation a new phenomenon in the weapons inspection arena. Weapons inspectors themselves are often forced to sift through alternative narratives of events and inconsistent reporting, and they regularly see their credibility and conclusions questioned in the face of government politics or public biases. But certain recent disinformation campaigns have become so overwhelmingly comprehensive and effective that they constitute a new kind of threat. By preventing accountability for clear violations of international law, these campaigns have created a challenge to the survival of arms control treaties themselves. If weapons inspectors cannot regain the trust of the international community in the face of this challenge, it will be increasingly difficult to ensure compliance with arms control and disarmament treaties going forward. In this essay, I will briefly discuss one of the most comprehensive disinformation efforts of the past decade: the disinformation campaign used to prevent accountability for Syria's repeated use of chemical weapons. After this discussion, I will propose one possible approach to help protect the credibility of disarmament experts and weapons inspectors in the face of pervasive disinformation. This approach will require a concerted effort to connect and support compliance experts and to understand and explain their expertise across cultural, political, national, economic, and religious divides.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

10 New Insights in Climate Science 2020 - a Horizon Scan

We summarize some of the past year’s most important findings within climate change-related research. New research has improved our understanding of Earth’s sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Zirconium-Based Metal–Organic Frameworks as Reusable Antibacterial Peroxide Carriers for Protective Textiles

Countries around the world have sought efficient protective coverings, including masks, gowns, and fabrics, for air purification to protect people against infectious diseases. However, the demand for significant quantities of disposable protective textiles poses a global challenge, especially when the production of protective gear is suspended due to COVID-19 outbreaks in factories and along supply lines. Therefore, the development of reusable, self-decontaminating protective masks and coverings loaded with disinfectants, such as antibacterial peroxide species, presents an attractive strategy to fight against bacteria risks. In this work, we incorporated persulfate ions, which serve as stable active peroxide precursors, into two porous zirconium-based metal–organic frameworks (Zr-MOFs), enabling these materials to act as regenerable reservoirs for the slow release of biocidal hydrogen peroxide upon hydrolysis by contact with humid air. Single-crystal X-ray diffraction studies reveal the two different coordination motifs for the persulfate ions, which can either bridge between two adjacent nodes or coordinate to a single node depending on both the node connectivity and the distances between open metal sites. The active peroxide precursors within the porous Zr-MOF carriers are stable during storage and easily regenerated once consumed. Importantly, these persulfate-loaded Zr-MOFs can be integrated onto textiles using a facile aqueous in-situ growth procedure, and these composites demonstrate potent and reusable biocidal activity against both Gram-negative bacteria and Gram-positive bacteria. Altogether, this approach presents a viable strategy to develop robust protective textiles capable of rapidly deactivating pathogens.

36 MATERIALS SCIENCE↗

Impact of Remdesivir Incorporation along the Primer Strand on SARS-CoV-2 RNA-Dependent RNA Polymerase

Remdesivir was the first antiviral drug that received emergency use authorization from the United States Food and Drug Administration and is now formally approved to treat COVID-19. Remdesivir is a nucleotide analogue that targets the RNA-dependent RNA polymerase (RdRp) of coronaviruses, including SARS-CoV-2. The solution of multiple RdRp structures has been one of the main axes of research in the race against the SARS-CoV-2 virus. Several hypotheses of the mechanism of inhibition of RdRp by remdesivir have been proposed, although open questions remain. This work uses molecular dynamics simulations to explore the impact of remdesivir and two analogues as incoming nucleotides and of up to four incorporations of remdesivir along the primer strand on RdRp. The simulation results suggest that the overall structure and the dynamical behavior of RdRp are destabilized by remdesivir and the two analogues in the incoming position. The incorporation of remdesivir along the primer strand impacts specific non-bonded interactions between the nascent RNA and the polymerase subunit, as well as the overall dynamical networks on RdRp. The strongest impact on the structure and dynamics are observed after three incorporations, when remdesivir is located at position -A3, in agreement with previously reported experimental and computational results. Our results provide atomic-level details of the role played by remdesivir on the disruption of RNA synthesis by RdRp and the main drivers of these disruptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2

Direct-acting antivirals for the treatment of the COVID-19 pandemic caused by the SARS-CoV-2 virus are needed to complement vaccination efforts. Given the ongoing emergence of new variants, automated experimentation, and active learning based fast workflows for antiviral lead discovery remain critical to our ability to address the pandemic’s evolution in a timely manner. While several such pipelines have been introduced to discover candidates with noncovalent interactions with the main protease (M pro ), here we developed a closed-loop artificial intelligence pipeline to design electrophilic warhead-based covalent candidates. Here, this work introduces a deep learning-assisted automated computational workflow to introduce linkers and an electrophilic “warhead” to design covalent candidates and incorporates cutting-edge experimental techniques for validation. Using this process, promising candidates in the library were screened, and several potential hits were identified and tested experimentally using native mass spectrometry and fluorescence resonance energy transfer (FRET)-based screening assays. We identified four chloroacetamide-based covalent inhibitors of M pro with micromolar affinities (K I of 5.27 μM) using our pipeline. Experimentally resolved binding modes for each compound were determined using room-temperature X-ray crystallography, which is consistent with the predicted poses. The induced conformational changes based on molecular dynamics simulations further suggest that the dynamics may be an important factor to further improve selectivity, thereby effectively lowering KI and reducing toxicity. These results demonstrate the utility of our modular and data-driven approach for potent and selective covalent inhibitor discovery and provide a platform to apply it to other emerging targets.

60 APPLIED LIFE SCIENCES↗

Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease

Creating small-molecule antivirals specific for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins is crucial to battle coronavirus disease 2019 (COVID-19). SARS-CoV-2 main protease (Mpro) is an established drug target for the design of protease inhibitors. We performed a structure–activity relationship (SAR) study of noncovalent compounds that bind in the enzyme’s substrate-binding subsites S1 and S2, revealing structural, electronic, and electrostatic determinants of these sites. The study was guided by the X-ray/neutron structure of Mpro complexed with Mcule-5948770040 (compound 1), in which protonation states were directly visualized. Virtual reality-assisted structure analysis and small-molecule building were employed to generate analogues of 1. In vitro enzyme inhibition assays and room-temperature X-ray structures demonstrated the effect of chemical modifications on Mpro inhibition, showing that (1) maintaining correct geometry of an inhibitor’s P1 group is essential to preserve the hydrogen bond with the protonated His163; (2) a positively charged linker is preferred; and (3) subsite S2 prefers nonbulky modestly electronegative groups.

60 APPLIED LIFE SCIENCES↗