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DOE OSTI2021

New Approach Methodology for Assessing Inhalation Risks of a Contact Respiratory Cytotoxicant: Computational Fluid Dynamics-Based Aerosol Dosimetry Modeling for Cross-Species and In Vitro Comparisons

Regulatory agencies are considering alternative approaches to assessing inhalation toxicity that utilizes in vitro studies with human cells and in silico modeling in lieu of additional animal studies. In support of this goal, computational fluid-particle dynamics models were developed to estimate site-specific deposition of inhaled aerosols containing the fungicide, chlorothalonil, in the rat and human for comparisons to prior rat inhalation studies and new human in vitro studies. Under bioassay conditions, the deposition was predicted to be greatest at the front of the rat nose followed by the anterior transitional epithelium and larynx corresponding to regions most sensitive to local contact irritation and cytotoxicity. For humans, simulations of aerosol deposition covering potential occupational or residential exposures (1–50 µm diameter) were conducted using nasal and oral breathing. Aerosols in the 1–5 µm range readily penetrated the deep region of the human lung following both oral and nasal breathing. Under actual use conditions (aerosol formulations >10 µm), the majority of deposited doses were in the upper conducting airways. Beyond the nose or mouth, the greatest deposition in the pharynx, larynx, trachea, and bronchi was predicted for aerosols in the 10–20 µm size range. Only small amounts of aerosols >20 µm penetrated past the pharyngeal region. Using the ICRP clearance model, local retained tissue dose metrics including maximal concentrations and areas under the curve were calculated for each airway region following repeated occupational exposures. These results are directly comparable with benchmark doses from in vitro toxicity studies in human cells leading to estimated human equivalent concentrations that reduce the reliance on animals for risk assessments.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2024

Modeling Plutonium Decorporation in a Female Nuclear Worker Treated with Ca-DTPA after Inhalation Intake

The present work models plutonium (Pu) biokinetics in a female former nuclear worker. Her bioassay measurements are available at the US Transuranium and Uranium Registries. The worker was internally exposed to a plutonium-americium mixture via acute inhalation at a nuclear weapons facility. She was medically treated with injections of 1 g Ca-DTPA on days 0, 5, and 14 after the intake. Between days 0 and 20, fecal and urine samples were collected and analyzed for 239 Pu and 241 Am. Subsequently, she was followed up for bioassay monitoring over 14 y, with additional post-treatment urine samples collected and analyzed for 239 Pu. The uniqueness of this dataset is due to the availability of: (1) both early and long-term bioassay data from a female with plutonium intake; (2) data on chelation therapy for a female; and (3) fecal measurement results. Chelation therapy with Ca- and/or Zn-salts of DTPA is known to aid in reducing the internal radiation dose by enhancing the excretion of plutonium and americium from the body. Such enhancement affects plutonium biokinetics in the human body, posing a challenge to the internal dose assessment. The current radiation dose assessment practice is to exclude the data affected by Ca-DTPA from the analysis. The present analysis is the first to explicitly model the chelation-affected bioassay data in a female by using a newly developed chelation model. Thus, the bioassay data collected during and after the Ca-DTPA administrations were used for biokinetic modeling and dose assessment. The Markov Chain Monte Carlo method was used to investigate model parameter uncertainty, based on the bioassay data and assumed prior probability distributions. A χ 2 /nData (number of data points) ≈ 1 was observed in this study, which indicates self-consistency of the data with the model. Results of this study show that the worker’s 239 Pu intake was 12 Bq, with a committed effective dose to the whole-body of 1.2 mSv and a committed equivalent dose to the bone surfaces, liver, and lungs of 37.8, 9.1, and 0.8 mSv, respectively. This study also discusses the worker’s dose reduction due to chelation treatment.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

International Commission on Radiological Protectio↗

DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients in Consequence Management: Propagated Dose Uncertainty in ICRP 66 Human Respiratory Tract Model

Reference inhalation dose models rely on deterministic biokinetics and reference computational phantoms, limiting their applicability to the variability present in population-specific exposures encountered in emergency response scenarios. Here, this study introduces REDCAL, a Python-based computational framework developed to propagate uncertainty in inhalation dose coefficients using the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model. REDCAL integrates ICRP deposition and clearance models, systemic biokinetics, and governing physics principles, and leverages Sandia National Laboratories’ Dakota toolkit for uncertainty quantification via Latin Hypercube Sampling. REDCAL was validated against DCAL, with biokinetic retention results differing by less than 1% and effective dose coefficients by less than 2% across all tested radionuclides. Stochastic sampling introduced variability in dose coefficients, with geometric standard deviations (GSD) in committed effective dose coefficients (CEDC) ranging from 1.0 to 1.5, based on lognormal distribution fits. Analysis demonstrated that variations in the activity median aerodynamic diameter (AMAD) notably influenced the computed CEDC values. Smaller particles (<1 µm) increased doses by 20–30% due to deeper lung deposition and prolonged retention for alpha emitting radionuclides, such as 241 Am and 239 Pu. Radionuclides with fast clearance, such as 133 I, demonstrated a dose reduction exceeding 50%, as AMAD increased beyond 5 µm due to upper airway deposition and rapid mucociliary clearance. The greatest GSD among the radionuclides reported in this study was for 241 Am. In most cases, the largest GSDs in the CEDC were associated with larger particle sizes, an expected outcome, as ICRP Publication 66 defines GSD in particle size as a function of AMAD, resulting in an extended tail of the lognormal distribution. The findings support improved inhalation dose assessments and enhance consequence management strategies for the U.S. Federal Radiological Monitoring and Assessment Center by quantifying uncertainty in dose coefficients and strengthening decision-making for emergency response scenarios.

Biokinetic Modeling↗

DOE OSTI2020

Acute Shortage Ventilator

Abstract We have implemented an “Acute Shortage Ventilator” (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.

Akerib, D. S.↗

DOE OSTI2021

Topologically Associating Domain Boundaries are Commonly Required for Normal Genome Function

Topologically associating domain (TAD) boundaries are thought to partition the genome into distinct regulatory territories. Anecdotal evidence suggests that their disruption may interfere with normal gene expression and cause disease phenotype, but the overall extent to which this occurs remains unknown. Here we show that TAD boundary deletions commonly disrupt normal genome function in vivo . We used CRISPR genome editing in mice to individually delete eight TAD boundaries (11-80kb in size) from the genome in mice. All deletions examined resulted in at least one detectable molecular or organismal phenotype, which included altered chromatin interactions or gene expression, reduced viability, and anatomical phenotypes. For 5 of 8 (62%) loci examined, boundary deletions were associated with increased embryonic lethality or other developmental phenotypes. For example, a TAD boundary deletion near Smad3/Smad6 caused complete embryonic lethality, while a deletion near Tbx5/Lhx5 resulted in a severe lung malformation. Our findings demonstrate the importance of TAD boundary sequences for in vivo genome function and suggest that noncoding deletions affecting TAD boundaries should be carefully considered for potential pathogenicity in clinical genetics screening.

Rajderkar, Sudha↗

DOE OSTI2025

Frequency shifts in the electron paramagnetic resonance spectrum of 39 K due to spin-exchange collisions with polarized 3 He and precise 3 He polarimetry

The Zeeman splittings and electron paramagnetic resonance frequencies of alkali-metal atoms are shifted in the presence of a polarized noble gas. For a spherical geometry, the shift is enhanced over what is expected classically by a dimensionless atomic parameter 𝜅 0 that is unique to each alkali-metal-atom–noble-gas pair. Here, we present a precise measurement of 𝜅 0 for the 39 K − 3 He system with a relative accuracy of better than 1%. A critical component of achieving subpercent accuracy involved characterizing the shape of our samples using both MRI and CT medical-imaging techniques. The parameter 𝜅 0 plays an important role in establishing the absolute polarization of 3 He in a variety of contexts, including polarized targets for electron-scattering experiments and MRI of the gas space of the lungs. Our measurement more than doubles the accuracy possible when using 𝜅 0 for polarimetry purposes. Just as important, the work presented here represents a direct measurement of 𝜅 0 for the 39 K − 3 He system; previous values for 𝜅 0 in the 39 K − 3 He system relied on a chain of measurements that were benchmarked by previous measurements of 𝜅 0 in the Rb- 3 He system.

Zeeman effect↗

DOE OSTI2021

Understanding protein-complex assembly through grand canonical maximum entropy modeling

Inside a cell, heterotypic proteins assemble in inhomogeneous, crowded systems where the abundance of these proteins vary with cell types. While some protein complexes form putative structures that can be visualized with imaging, there are far more protein complexes that are yet to be solved because of their dynamic associations with one another. Nevertheless, it is possible to infer these protein complexes through a physical model. However, it is often not clear to physicists what kind of data from biology is necessary for such a modeling endeavor. Here, we aim to model these clusters of coarse-grained protein assemblies from multiple subunits through the constraints of interactions among the subunits and the chemical potential of each subunit. We obtained the constraints on the interactions among subunits from the known protein structures. We inferred the chemical potential that dictates the particle number distribution of each protein subunit from the knowledge of protein abundance from experimental data. Guided by the maximum entropy principle, we formulated an inverse statistical mechanical method to infer the distribution of particle numbers from the data of protein abundance as chemical potentials for a grand canonical multicomponent mixture. Using grand canonical Monte Carlo simulations, we captured a distribution of high-order clusters in a protein complex of succinate dehydrogenase with four known subunits. The complexity of hierarchical clusters varies with the relative protein abundance of each subunit in distinctive cell types such as lung, heart, and brain. When the crowding content increases, we observed that crowding stabilizes emergent clusters that do not exist in dilute conditions. We, therefore, proposed a testable hypothesis that the hierarchical complexity of protein clusters on a molecular scale is a plausible biomarker of predicting the phenotypes of a cell.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The reactivity of experimentally reduced lunar regolith simulants: Health implications for future crewed missions to the lunar surface

Crewed missions to the Moon may resume as early as 2026 with NASA's Artemis III mission, and lunar dust exposure/inhalation is a potentially serious health hazard that requires detailed study. Current dust exposure limits are based on Apollo-era samples that spent decades in long-term storage on Earth; their diminished reactivity may lead to underestimation of potential harm that could be caused by lunar dust exposure. In particular, lunar dust contains nanophase metallic iron grains, produced by “space weathering”; the reactivity of this unique component of lunar dust is not well understood. Herein, we employ a chemical reduction technique that exposes lunar simulants to heat and hydrogen gas to produce metallic iron particles on grain surfaces. We assess the capacity of these reduced lunar simulants to generate hydroxyl radical (OH*) when immersed in deionized (DI) water, simulated lung fluid (SLF), and artificial lysosomal fluid (ALF). Lunar simulant reduction produces surface-adhered metallic iron “blebs” that resemble nanophase metallic iron particles found in lunar dust grains. Reduced samples generate ~5–100× greater concentrations of the oxidative OH* in DI water versus non-reduced simulants, which we attribute to metallic iron. SLF and ALF appear to reduce measured OH*. The increase in observed OH* generation for reduced simulants implies high oxidative damage upon exposure to lunar dust. Low levels of OH* measured in SLF and ALF imply potential damage to proteins or quenching of OH* generation, respectively. Reduction of lunar dust simulants provides a quick cost-effective approach to study dusty materials analogous to authentic lunar dust.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

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↗

DOE OSTI2022

A human antibody reveals a conserved site on beta-coronavirus spike proteins and confers protection against SARS-CoV-2 infection

Broadly neutralizing antibodies (bnAbs) to coronaviruses (CoVs) are valuable in their own right as prophylactic and therapeutic reagents to treat diverse CoVs and as templates for rational pan-CoV vaccine design. We recently described a bnAb, CC40.8, from a CoV disease 2019 (COVID-19) convalescent donor that exhibits broad reactivity with human β-CoVs. Here, we showed that CC40.8 targets the conserved S2 stem helix region of the CoV spike fusion machinery. We determined a crystal structure of CC40.8 Fab with a SARS-CoV-2 S2 stem peptide at 1.6-Å resolution and found that the peptide adopted a mainly helical structure. Conserved residues in β-CoVs interacted with CC40.8 antibody, thereby providing a molecular basis for its broad reactivity. CC40.8 exhibited in vivo protective efficacy against SARS-CoV-2 challenge in two animal models. In both models, CC40.8-treated animals exhibited less weight loss and reduced lung viral titers compared to controls. Furthermore, we noted that CC40.8-like bnAbs are relatively rare in human COVID-19 infection, and therefore, their elicitation may require rational structure-based vaccine design strategies. Overall, our study describes a target on β-CoV spike proteins for protective antibodies that may facilitate the development of pan–β-CoV vaccines.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort

The drivers of critical coronavirus disease 2019 (COVID-19) remain unknown. Given major confounding factors such as age and comorbidities, true mediators of this condition have remained elusive. We used a multi-omics analysis combined with artificial intelligence in a young patient cohort where major comorbidities were excluded at the onset. The cohort included 47 “critical” (in the intensive care unit under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) patients with COVID-19 and 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cell proteomics, cytokine profiling, and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing, and structural causal modeling were used. Patients with critical COVID-19 were characterized by exacerbated inflammation, perturbed lymphoid and myeloid compartments, increased coagulation, and viral cell biology. Among differentially expressed genes, we observed up-regulation of the metalloprotease ADAM9. This gene signature was validated in a second independent cohort of 81 critical and 73 recovered patients with COVID-19 and was further confirmed at the transcriptional and protein level and by proteolytic activity. Ex vivo ADAM9 inhibition decreased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, cohort of individuals with COVID-19, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. We further identified ADAM9 as a driver of disease severity and a candidate therapeutic target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Applying a polysaccharide lyase from Stenotrophomonas maltophilia to disrupt alginate exopolysaccharide produced by Pseudomonas aeruginosa clinical isolates

Pseudomonas aeruginosa is considered one of the most challenging, drug-resistant, opportunistic pathogens partly due to its ability to synthesize robust biofilms. Biofilm is a mixture of extracellular polymeric substances (EPS) that encapsulates microbial cells, leading to immune evasion, antibiotic resistance, and thus higher risk of infection. In the cystic fibrosis lung environment, P. aeruginosa undergoes a mucoid transition, defined by overproduction of the exopolysaccharide alginate. Alginate encapsulation results in bacterial resistance to antibiotics and the host immune system. Given its role in airway inflammation and chronic infection, alginate is an obvious target to improve treatment for P. aeruginosa infection. Previously, we demonstrated polysaccharide lyase Smlt1473 from Stenotrophomonas maltophilia strain k279a can catalyze the degradation of multiple polyuronides in vitro, including D-mannuronic acid (poly-ManA). Poly-ManA is a major constituent of P. aeruginosa alginate, suggesting that Smlt1473 could have potential application against multidrug-resistant P. aeruginosa and perhaps other microbes with related biofilm composition. In this study, we demonstrate that Smlt1473 can inhibit and degrade alginate from P. aeruginosa. Additionally, we show that tested P. aeruginosa strains are dominant in acetylated alginate and that all but one have similar M-to-G ratios. These results indicate that variation in enzyme efficacy among the isolates is not primarily due to differences in total EPS or alginate chemical composition. Overall, these results demonstrate Smlt1473 can inhibit and degrade P. aeruginosa alginate and suggest that other factors including rate of EPS production, alginate sequence/chain length, or non-EPS components may explain differences in enzyme efficacy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Molecular Modeling Predicts Novel Antibody Escape Mutations in the Respiratory Syncytial Virus Fusion Glycoprotein

Respiratory syncytial virus (RSV) causes severe disease in young infants, particularly those with heart or lung diseases or born prematurely. Because no vaccine is currently available, monoclonal antibodies are used to prevent severe RSV disease in high-risk infants. While it is known that RSV evolves to avoid recognition by antibodies, screening tools that can predict which changes to the virus may lead to antibody resistance are greatly needed.

molecular modeling↗

DOE OSTI2022

Vaccine-Associated Enhanced Respiratory Disease following Influenza Virus Infection in Ferrets Recapitulates the Model in Pigs

Influenza A virus (IAV) causes respiratory disease in swine and humans. Vaccines are used to prevent influenza illness in both populations but must be frequently updated due to rapidly evolving strains. Mismatch between the circulating strains and the strains contained in vaccines may cause loss of efficacy. Whole inactivated virus (WIV) vaccines with adjuvant, utilized by the swine industry, are effective against antigenically similar viruses; however, vaccine-associated enhanced respiratory disease (VAERD) may happen when the WIV is antigenically mismatched with the infecting virus. VAERD is a repeatable model in pigs, but had yet to be experimentally demonstrated in other mammalian species. We recapitulated VAERD in ferrets, a standard benchmark animal model for studying human influenza infection, in a direct comparison to VAERD in pigs. Both species were vaccinated with WIV with oil-in-water adjuvant containing a d -1 H1N2 (1B.2.2) derived from the pre-2009 human seasonal lineage, then challenged with a 2009 pandemic H1N1 (H1N1pdm09, 1A.3.3.2) 5 weeks after vaccination. Nonvaccinated and challenged groups showed typical signs of influenza disease, but the mismatched vaccinated and challenged pigs and ferrets showed elevated clinical signs, despite similar viral loads. VAERD-affected pigs exhibited a 2-fold increase in lung lesions, while VAERDaffected ferrets showed a 4-fold increase. Similar to pigs, antibodies from VAERD-affected ferrets preferentially bound to the HA2 domain of the H1N1pdm09 challenge strain. These results indicate that VAERD is not limited to pigs, as demonstrated here in ferrets, and the need to consider VAERD when evaluating new vaccine platforms and strategies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Sac1 links phosphoinositide turnover to cryptococcal virulence

Cryptococcus neoformans is an environmentally acquired fungal pathogen that causes over 140,000 deaths per year. Cryptococcal infection occurs when infectious particles are deposited into the lung, where they encounter host phagocytic cells. C. neoformans may be engulfed by these phagocytes, an important step of infection that leads to outcomes ranging from termination of infection to cryptococcal dissemination. To study this critical process, we screened approximately 4,700 cryptococcal gene deletion mutants for altered uptake, using primary mouse and human phagocytic cells. Among the hits of these two screens, we identified 93 mutants with perturbed uptake in both systems, as well as others with differences in uptake by only one cell type. We further screened the hits for changes in thickness of the capsule, a protective polysaccharide layer around the cell which is an important cryptococcal virulence factor. The combination of our three screens yielded 45 mutants, including one lacking the phosphatidylinositol-4-phosphate phosphatase Sac1. In this work, we implicate Sac1 in both host cell uptake and capsule production. We found that sac1 mutants exhibit lipid trafficking defects, reductions in secretory system function, and changes in capsule size and composition. Many of these changes occur specifically in tissue culture media, highlighting the role of Sac1 phosphatase activity in responding to the stress of host-like conditions. Overall, these findings show how genome-scale screening can identify cellular factors that contribute to our understanding of cryptococcal biology and demonstrate the role of Sac1 in determining fungal virulence.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Cryptococcus neoformans Secretes Small Molecules That Inhibit IL-1 β Inflammasome-Dependent Secretion

Cryptococcus neoformans is an encapsulated yeast that causes disease mainly in immunosuppressed hosts. It is considered a facultative intracellular pathogen because of its capacity to survive and replicate inside phagocytes, especially macrophages. This ability is heavily dependent on various virulence factors, particularly the glucuronoxylomannan (GXM) component of the polysaccharide capsule. Inflammasome activation in phagocytes is usually protective against fungal infections, including cryptococcosis. Nevertheless, recognition of C. neoformans by inflammasome receptors requires specific changes in morphology or the opsonization of the yeast, impairing proper inflammasome function. In this context, we analyzed the impact of molecules secreted by C. neoformans B3501 strain and its acapsular mutant Δcap67 in inflammasome activation in an in vitro model. Our results showed that conditioned media derived from B3501 was capable of inhibiting inflammasome-dependent events (i.e., IL-1β secretion and LDH release via pyroptosis) more strongly than conditioned media from Δcap67, regardless of GXM presence. We also demonstrated that macrophages treated with conditioned media were less responsive against infection with the virulent strain H99, exhibiting lower rates of phagocytosis, increased fungal burdens, and enhanced vomocytosis. Moreover, we showed that the aromatic metabolite DL-Indole-3-lactic acid (ILA) and DL-p-Hydroxyphenyllactic acid (HPLA) were present in B3501’s conditioned media and that ILA alone or with HPLA is involved in the regulation of inflammasome activation by C. neoformans. These results were confirmed by in vivo experiments, where exposure to conditioned media led to higher fungal burdens in Acanthamoeba castellanii culture as well as in higher fungal loads in the lungs of infected mice. Overall, the results presented show that conditioned media from a wild-type strain can inhibit a vital recognition pathway and subsequent fungicidal functions of macrophages, contributing to fungal survival in vitro and in vivo and suggesting that secretion of aromatic metabolites, such as ILA, during cryptococcal infections fundamentally impacts pathogenesis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

ROI Hide and Seek Protocol v1

1. Segmentation We provide scripts for the model definition of the U-net architecture adapted from: https://github.com/jvanvugt/pytorch-unet/blob/master/unet.py We developed scripts for preparing the lung segmentation data set. We developed scripts for training the U-Net architecture. We developed scripts for applying the trained U-Net model to perform the ROI Hide and Seek protocol on the classification dataset to create the modified dataset. 2. Classification We provide scripts for the training of the COVID-Net models provided by Linda Wang, this code is adapted from her github repository: https://github.com/lindawangg/COVID-Net/tree/d7b36831d854f57de5bc7557217f5439e86e016f. These scripts were modified to save training log information as well as to load the provided models in their github repo. We developed scripts for training standard Neural Network Models (resnet 50, vgg 11, Alexnet) on the COVID datsets along with the ROI Hide and Seek altered datasets.

Sadre, Robbie↗