Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “LUNGS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications. Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. Additionally, the four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated. The air-kerma strength was (9.772 ± 0.001) × 10 -8 U Bq -1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h -1 U -1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data. TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Seaweed-derived fucoidans and rhamnan sulfates serve as potent anti-SARS-CoV-2 agents with potential for prophylaxis

Seaweeds represent a rich source of sulfated polysaccharides with similarity to heparan sulfate, a facilitator of myriad virus host cell attachment. For this reason, attention has been drawn to their antiviral activity, including the potential for anti-SARS-CoV-2 activity. We have identified and structurally characterized several fucoidan extracts, including those from different species of brown macroalga, and a rhamnan sulfate from a green macroalga species. A high molecular weight fucoidan extracted from Saccharina japonica (FSjRPI-27), and a rhamnan sulfate extracted from Monostroma nitidum (RSMn), showed potent competitive inhibition of spike glycoprotein receptor binding to a heparin-coated SPR chip. This inhibition was also observed in cell-based assays using hACE2 HEK-293 T cells infected by pseudotyped SARS-CoV-2 virus with IC50 values <1 μg/mL. Effectiveness was demonstrated in vivo using hACE2–transgenic mice. Intranasal administration of FSjRPI-27 showed protection when dosed 6 h prior to and at infection, and then every 2 days post-infection, with 100 % survival and no toxicity at 104 plaque-forming units per mouse vs. buffer control. At 5-fold higher virus dose, FSjRPI-27 reduced mortality and yielded reduced viral titers in bronchioalveolar fluid and lung homogenates vs. buffer control. Furthermore, these findings suggest the potential application of seaweed-based sulfated polysaccharides as promising anti-SARS-CoV-2 prophylactics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1–2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. In conclusion, this platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Thirdhand tobacco smoke exposure increases the genetic background-dependent risk of pan-tumor development in Collaborative Cross mice

Increasing evidence has shown that thirdhand smoke (THS) exposure is likely to induce adverse health effects. An important knowledge gap remains in our understanding of THS exposure related to cancer risk in the human population. Population-based animal models are useful and powerful in investigating the interplay between host genetics and THS exposure on cancer risk. Here, we used the Collaborative Cross (CC) mouse population-based model system, which recapitulates the genetic and phenotypic diversity observed in the human population, to assess cancer risk after a short period of exposure, between 4 and 9 weeks of age. Eight CC strains (CC001, CC019, CC026, CC036, CC037, CC041, CC042 and CC051) were included in our study. We quantified pan-tumor incidence, tumor burden per mouse, organ tumor spectrum and tumor-free survival until 18 months of age. At the population level, we observed a significantly increased pan-tumor incidence and tumor burden per mouse in THS-treated mice as compared to the control (p = 3.04E-06). Lung and liver tissues exhibited the largest risk of undergoing tumorigenesis after THS exposure. Tumor-free survival was significantly reduced in THS-treated mice compared to control (p = 0.044). At the individual strain level, we observed a large variation in tumor incidence across the 8 CC strains. CC036 and CC041 exhibited a significant increase in pan-tumor incidence (p = 0.0084 and p = 0.000066, respectively) after THS exposure compared to control. We conclude that early-life THS exposure increases tumor development in CC mice and that host genetic background plays an important role in individual susceptibility to THS-induced tumorigenesis. Genetic background is an important factor that should be taken into account when determining human cancer risk of THS exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Bio-distribution and deposition of wildfire smoke chemicals into olfactory bulb and brain of rats after intranasal instillation

Epidemiological and experimental studies suggest wildfire smoke is a potential contributor to neurological dysfunction and associated with neuroinflammation. Using doses comparable to those encountered during intense wildfire events (200-300 μg/m 3 ), we explore the absorption, distribution, metabolism, and elimination (ADME) and pharmacokinetics of representative members of major chemical classes (acid, phenol, PAH, aldehyde) in inhaled wood smoke condensates. Male Sprague Dawley rats were intranasally instilled with smoldering eucalyptus woodsmoke extract (WSE) reconstituted in saline spiked with 14 C-labeled palmitic acid (PA), benzo[a]pyrene (B[a]P), catechol (CAT) or benzaldehyde (BZ). Serum was collected from 5 min to 2 weeks after exposure and tissues were collected at 0.5, 2, 4, 24 h and 2 weeks after exposure. Urine was collected over the 24 h exposure. Tissues were collected, rinsed in PBS and analyzed by accelerator mass spectrometry (AMS) for 14C-labeled chemicals. PA and B[a]P entered circulation slowly, reached maximum concentration (C max ) near 15 ng/mL at 2 h, and had circulating concentrations near 1/3 C max 24 h after exposure. CAT and BZ rapidly entered circulation and were mostly cleared at 2 h. Excess 14 C from all four chemicals was detected in olfactory bulb and brain over the first 24 h but only PA (or its metabolites) was retained in olfactory bulb, brain and kidney at 2 weeks post exposure. All excess 14 C was cleared from the lung at 2 weeks. Metabolite analysis of urine (CAT, BZ and B(a)P) dosed samples did not detect any parent compound. CAT and BZ were rapidly cleared. The slower uptake and clearance of PA or B[a]P or their reactive metabolites when dosed with WSE in brain and olfactory bulb potentially provide greater opportunity for inflammatory response. This study suggests that wildfire smoke chemicals can enter the brain directly from the nasal cavity to the olfactory bulb and via systemic circulation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Translating nanoparticle dosimetry from conventional in vitro systems to occupational inhalation exposures

As encouraged by Toxicity Testing in the 21st Century, researchers increasingly apply high-throughput in vitro approaches to identify and characterize nanoparticle hazards, including conventional aqueous cell culture systems to assess respiratory hazards. Translating nanoparticle dose from conventional toxicity testing systems to relevant human exposures remains a major challenge for assessing occupational risk of nanoparticle exposures. Here, we explored existing computational tools and data available to translate nanoparticle dose metrics from cellular test systems to inhalation exposures of silver nanoparticles in humans. We used the Multiple-Path Particle Dosimetry (MPPD) Model to predict deposition of humans exposed to 20 and 110 nm silver nanoparticles at 0.9 µg/m3 over an 8 hr period, the proposed a National Institute of Occupational Safety and Health (NIOSH) recommended exposure limit (REL). MPPD predicts 1.88 and 0.98 µg of silver deposited in an 8 hr period for 20 and 110 nm nanoparticles, respectively, with 20 nm particles displaying nearly 11-fold higher total surface area deposited. Peak nanoparticle concentrations occurred more proximal in the pulmonary tract compared to mass deposition patterns (generation 5 vs. generations 20-21, respectively) due to regional differences in lung lining fluid volumes. Assuming 0.4% nanoparticle dissolution by mass as previously measured, we predict peak concentrations of silver ions in cells of 0.24 and 0.17 µg/mL for 20 and 110 nm particles, respectively. Both predicted concentrations are below the measured toxic threshold of 1.7 µg/mL of silver ions in cells from in vitro assessments. Assuming 4% dissolution by mass, we predict 10-fold higher silver concentrations in tissues, peaking at 2.4 and 1.7 µg/mL, for 20 and 110 nm nanoparticles respectively, exceeding the observed in vitro toxic threshold and highlighting the importance and sensitivity of dissolution rates. Overall, this approach offers a framework for extrapolating nanotoxicity results from in vitro cell culture systems to human exposures. Aligning appropriate dose metrics from in vitro and in vivo hazard characterizations and human pulmonary doses from occupational exposures are critical components for successful nanoparticle risk assessment and worker protection and provide guidance for designing future in vitro studies aimed at relevant human exposures.

Smith, Jordan N.↗
DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Structural Insights into the Mechanisms and Pharmacology of K 2P Potassium Channels

Leak currents, defined as voltage and time independent flows of ions across cell membranes, are central to cellular electrical excitability control. The K 2P (KCNK) potassium channel class comprises an ion channel family that produces potassium leak currents that oppose excitation and stabilize the resting membrane potential in cells in the brain, cardiovascular system, immune system, and sensory organs. Due to their widespread tissue distribution, K 2P s contribute to many physiological and pathophysiological processes including anesthesia, pain, arrythmias, ischemia, hypertension, migraine, intraocular pressure regulation, and lung injury responses. Structural studies of six homomeric K 2P s have established the basic architecture of this channel family, revealed key moving parts involved in K 2P function, uncovered the importance of asymmetric pinching and dilation motions in the K 2P selectivity filter (SF) C-type gate, and defined two K 2P structural classes based on the absence or presence of an intracellular gate. Further, a series of structures characterizing K 2P :modulator interactions have revealed a striking polysite pharmacology housed within a relatively modestly sized (~70 kDa) channel. Binding sites for small molecules or lipids that control channel function are found at every layer of the channel structure, starting from its extracellular side through the portion that interacts with the membrane bilayer inner leaflet. This framework provides the basis for understanding how gating cues sensed by different channel parts control function and how small molecules and lipids modulate K 2P activity. Such knowledge should catalyze development of new K 2P modulators to probe function and treat a wide range of disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mucin 4 is a cellular biomarker of necrotizing bronchiolitis in influenza A virus infection

Influenza A virus (IAV) in the human and swine host infects epithelial cells lining the respiratory tract causing a necrotizing bronchitis and bronchiolitis. These epithelial surfaces are protected by large glycoproteins called mucins. Mucin 4 (MUC4) is a transmembrane mucin that consists of an alpha subunit responsible for surface protection and intracellular beta subunit involved in signal transduction which repress apoptosis and stimulate epithelial proliferation. This study was designed to determine the expression and potential role of MUC4 during IAV infection. We used immunohistochemistry in combination with machine learning image analysis to quantify differential protein expression of MUC4 subunits in IAV-infected and uninfected lung in a porcine model. MUC4 protein basal expression in control animals varied significantly by litter. MUC4 protein expression was significantly increased in bronchioles with necrotizing bronchiolitis compared to histologically normal bronchioles, likely representing a regenerative response to restore mucosal integrity of conducting airways. Understanding the impact of differential MUC4 expression among healthy individuals and during IAV infection will facilitate control strategies by elucidating mechanisms associated with susceptibility to IAV that can be therapeutically or genetically regulated and may be extended to other respiratory diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Rapid Automated Annotation and Analysis of N-Glycan Mass Spectrometry Imaging Data Sets Using NGlycDB in METASPACE

Imaging N-glycan spatial distribution in tissues using mass spectrometry imaging (MSI) is emerging as a promising tool in biological and clinical applications. However, there is currently no high throughput tool for visualization and molecular annotation of N-glycans in MSI data, which significantly slows down data processing and hampers the applicability of this approach. In this work, we present how METASPACE, an open-source cloud engine for molecular annotation of MSI data, can be used to automatically annotate, visualize, analyze, and interpret high-resolution mass spectrometry-based spatial N-glycomics data. METASPACE is an emerging tool in spatial metabolomics, but the lack of compatible glycan databases has limited its application for comprehensive N-glycan annotations from MSI datasets. We created NGlycDB, a public database of N-glycans, by adapting available glycan databases. We demonstrate the applicability of NGlycDB in METASPACE by analyzing MALDI-MSI data from formalin-fixed paraffin-embedded (FFPE) human kidney and mouse lung tissue sections. We added NGlycDB to METASPACE for public use, thus facilitating applications of MSI in glycobiology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Discovery of Macrocyclic Myeloid Cell Leukemia 1 (Mcl-1)Inhibitors that Demonstrate Potent Cellular Efficacy and In Vivo Activity in a Mouse Solid Tumor Xenograft Model

Abstract The B cell lymphoma 2 (Bcl-2) family of proteins are key regulators of intrinsic apoptosis. The antiapoptotic protein myeloid cell leukemia 1 (Mcl-1), which is associated with high tumor grade, poor survival, and resistance to treatment, has emerged as a promising candidate for treating hematological and solid cancers. Herein, we report the structure-guided design of small molecule macrocyclic Mcl-1 inhibitors based on the (R)-methyl-dihydropyrazinoindolone scaffold our group has previously disclosed. The macrocyclic inhibitors bind Mcl-1 with subnanomolar affinity and offer improved potency in cell culture growth inhibition assays. Inhibitor 13 achieved tumor regression in a lung cancer-derived tumor xenograft model in mice as a monotherapy. The improved potency of the macrocyclic series allowed replacement of heretofore conserved indole carboxylic acid moiety, resulting in neutral inhibitors. Amide inhibitor 25 displayed a >10-fold increase in oral bioavailability as compared to acid-containing macrocyclic or acyclic inhibitors.

Pharmacology & Pharmacy↗
DOE OSTI2025

Human Coronavirus-229E Hijacks Key Host-Cell RNA-Processing Complexes for Replication

The recent rise in zoonotic coronavirus outbreaks underscores the urgency to understand virus-host interactions and develop potent antiviral therapeutics. Systems biology approaches, particularly proteomics have been invaluable in providing a global overview of such interactions. However, these conventional approaches rely on measuring protein abundance changes which don’t reflect functional shifts. In this study, we employed a high-throughput structural proteomics approach called limited proteolysis-based mass spectrometry (LiP-MS) to capture conformational changes, which we demonstrate are better proxies for functional alterations. We applied this tool to both immortalized and primary human lung cells following human coronavirus 229E (HCoV-229E) infection. We identified significant infection-induced structural changes within RNA processing complexes such as the spliceosome-C and NOP56-associated complex. These observations emphasize that HCoV-229E infection propagates a multi-pronged effort to obstruct the house keeping RNA processing functions in the host. Finally, we show that HCoV-229E replication can be attenuated by the targeted disruption of these complexes, indicating that the identified cellular factories are viable targets to prevent coronavirus infection.

coronavirus↗
DOE OSTI2020

Facile Fabrication of Hierarchical MOF–Metal Nanoparticle Tandem Catalysts for the Synthesis of Bioactive Molecules

Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Finally, our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Chemoproteomic Elucidation of β-Lactam Drug Targets in Mycobacterium abscessus

The pathogen Mycobacterium abscessus (Mab) can cause severe and difficult-to-treat chronic lung infections. Despite the rising incidence and clinical concern of Mab infections, treatment options are limited and often ineffective. Treatment is complicated by Mab’s ability to persist in a nonreplicating, drug-resistant state. Several β-lactam antibiotics are potently bactericidal against Mab but are underutilized because their molecular mechanisms of action against Mab are incompletely understood. In the current study, we used β-lactam-derived activity-based probes and chemoproteomics to report the first comprehensive list of Mab enzymes targeted by β-lactams. We compared β-lactam targets across two Mab subspecies in actively replicating and nonreplicating cultures, using a new carbon starvation model of persistence. We identified 17 targets that were active in every condition tested, seven of which were previously unknown to bind β-lactams. Lastly, we characterized the β-lactamase activity and β-lactam inhibition profiles of nine Mab enzymes, demonstrating that imipenem inhibits these targets more effectively than cefoxitin. These findings demonstrate β-lactam target engagement in persistent Mab and provide clarity on the mechanisms of action of clinically relevant β-lactams in Mab, crucial steps toward fully realizing their potential for treating infections caused by this opportunistic pathogen.

Mycobacterium abscessus↗
DOE OSTI2023

Functional Impact of a Cancer-Related Variant in Human Δ 1 -Pyrroline-5-Carboxylate Reductase 1

Pyrroline-5-carboxylate reductase (PYCR) is a proline biosynthetic enzyme that catalyzes the NAD(P)H-dependent reduction of Δ 1 -pyrroline-5-carboxylate (P5C) to proline. Humans have three PYCR isoforms, with PYCR1 often upregulated in different types of cancers. Here, we studied the biochemical and structural properties of the Thr171Met variant of PYCR1, which is found in patients with malignant melanoma and lung adenocarcinoma. Although PYCR1 is strongly associated with cancer progression, characterization of a PYCR1 variant in cancer patients has not yet been reported. Thr171 is conserved in all three PYCR isozymes and is located near the P5C substrate binding site. We found that the amino acid replacement does not affect thermostability but has a profound effect on PYCR1 catalytic activity. The k cat of the PYCR1 variant T171M is 100- to 200-fold lower than wild-type PYCR1 when P5C is the variable substrate, and 10- to 25-fold lower when NAD(P)H is varied. A 1.84 Å resolution X-ray crystal structure of T171M reveals that the Met side chain invades the P5C substrate binding site, suggesting that the catalytic defect is due to steric clash preventing P5C from achieving the optimal pose for hydride transfer from NAD(P)H. These results suggest that any impact on PYCR1 function associated with T171M in cancer does not derive from increased catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Epigraph hemagglutinin vaccine induces broad cross-reactive immunity against swine H3 influenza virus

Influenza A virus infection in swine impacts the agricultural industry in addition to its zoonotic potential. Here, we utilize epigraph, a computational algorithm, to design a universal swine H3 influenza vaccine. The epigraph hemagglutinin proteins are delivered using an Adenovirus type 5 vector and are compared to a wild type hemagglutinin and the commercial inactivated vaccine, FluSure. In mice, epigraph vaccination leads to significant cross-reactive antibody and T-cell responses against a diverse panel of swH3 isolates. Epigraph vaccination also reduces weight loss and lung viral titers in mice after challenge with three divergent swH3 viruses. Vaccination studies in swine, the target species for this vaccine, show stronger levels of cross-reactive antibodies and T-cell responses after immunization with the epigraph vaccine compared to the wild type and FluSure vaccines. In both murine and swine models, epigraph vaccination shows superior cross-reactive immunity that should be further investigated as a universal swH3 vaccine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structural basis for SARS-CoV-2 envelope protein recognition of human cell junction protein PALS1

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has created global health and economic emergencies. SARS-CoV-2 viruses promote their own spread and virulence by hijacking human proteins, which occurs through viral protein recognition of human targets. To understand the structural basis for SARS-CoV-2 viral-host protein recognition, here we use cryo-electron microscopy (cryo-EM) to determine a complex structure of the human cell junction protein PALS1 and SARS-CoV-2 viral envelope (E) protein. Our reported structure shows that the E protein C-terminal DLLV motif recognizes a pocket formed exclusively by hydrophobic residues from the PDZ and SH3 domains of PALS1. Our structural analysis provides an explanation for the observation that the viral E protein recruits PALS1 from lung epithelial cell junctions. In addition, our structure provides novel targets for peptide- and small-molecule inhibitors that could block the PALS1-E interactions to reduce E-mediated virulence.

59 BASIC BIOLOGICAL SCIENCES↗