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At least 19 records

Tiny Device Mimics Human Lung Function

Scientists at Los Alamos National Laboratory are developing a miniature, tissue-engineered artificial lung that mimics the response of the human lung to drugs, toxins and other agents. “We breathe in and out thousands of times every day. And while we have control over what we eat or drink, we don’t always have control over what we breathe in,” said Jennifer Harris of Biosecurity and Public Health at Los Alamos, "and so we’re making this miniature lung to be able to test on actual human cells whether something in the environment, or a drug, is toxic or harmful to us." Nicknamed “PuLMo” for Pulmonary Lung Model (Pulmo is also the Latin word for "lung")the device consists of two major parts, the bronchiolar unit and the alveolar unit—just like the human lung. The units are primarily made from various polymers and are connected by a microfluidic “circuit board” that manages fluid and air flow. “When we build our lung, we not only take into account the aspects of different cell types, the tissues that are involved, we also take into account that a lung is supposed to breathe, so PuLMo actually breathes,” said Pulak Nath of Applied Modern Physics, who leads engineering efforts for the project. The most exciting application of PuLMo is a potentially revolutionary improvement in the reliability of drug-toxicity assessments and the prediction of new pharmaceutical success in humans, according to Harris. The PuLMo may also be designed to mimic lung disease conditions, such as Chronic Obstructive Pulmonary Disease (COPD) and asthma, and may be used to study lung air-flow dynamics to better understand the mechanisms of toxins and drug delivery and the effects of smoking, particularly the less-understood effects of e-cigarettes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Pulmo (V.2.0): Miniaturized Artificial, Configurable Human Lung System of Systems for Accelerated Toxicological Studies

The Pulmonary Lung Model (PuLMo) Version 2.0 is a miniaturized, engineered human artificial lung organ, designed to mimic the responses of human lungs to pharmaceuticals, toxins, and other agents. It can be customized in a system of systems implementation to reduce the life-cycle time and cost of pulmonary toxicological studies.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

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.↗

Acute shortage ventilator

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.

Breur, Sander↗

SU-F-P-54: Guidelines to Check Image Registration QA of a Clinical Deformation Registration Software: A Single Institution Preliminary Study

Purpose: The objective of this study is to verify and analyze the accuracy of a clinical deformable image registration (DIR) software. Methods: To test clinical DIR software qualitatively and quantitatively, we focused on lung radiotherapy and analyzed a single (Lung) patient CT scan. Artificial anatomical changes were applied to account for daily variations during the course of treatment including the planning target volume (PTV) and organs at risk (OAR). The primary CT (pCT) and the structure set (pST) was deformed with commercial tool (ImSimQA-Oncology Systems Limited) and after artificial deformation (dCT and dST) sent to another commercial tool (VelocityAI-Varian Medical Systems). In Velocity, the deformed CT and structures (dCT and dST) were inversely deformed back to original primary CT (dbpCT and dbpST). We compared the dbpST and pST structure sets using similarity metrics. Furthermore, a binary deformation field vector (BDF) was created and sent to ImSimQA software for comparison with known “ground truth” deformation vector fields (DVF). Results: An image similarity comparison was made by using “ground truth” DVF and “deformed output” BDF with an output of normalized “cross correlation (CC)” and “mutual information (MI)” in ImSimQA software. Results for the lung case were MI=0.66 and CC=0.99. The artificial structure deformation in both pST and dbpST was analyzed using DICE coefficient, mean distance to conformity (MDC) and deformation field error volume histogram (DFEVH) by comparing them before and after inverse deformation. We have noticed inadequate structure match for CTV, ITV and PTV due to close proximity of heart and overall affected by lung expansion. Conclusion: We have seen similarity between pCT and dbpCT but not so well between pST and dbpST, because of inadequate structure deformation in clinical DIR system. This system based quality assurance test will prepare us for adopting the guidelines of upcoming AAPM task group 132 protocol.

60 APPLIED LIFE SCIENCES↗

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↗

Comparison of Dose Distributions With TG-43 and Collapsed Cone Convolution Algorithms Applied to Accelerated Partial Breast Irradiation Patient Plans

Purpose: To compare the treatment plans for accelerated partial breast irradiation calculated by the new commercially available collapsed cone convolution (CCC) and current standard TG-43–based algorithms for 50 patients treated at our institution with either a Strut-Adjusted Volume Implant (SAVI) or Contura device. Methods and Materials: We recalculated target coverage, volume of highly dosed normal tissue, and dose to organs at risk (ribs, skin, and lung) with each algorithm. For 1 case an artificial air pocket was added to simulate 10% nonconformance. We performed a Wilcoxon signed rank test to determine the median differences in the clinical indices V90, V95, V100, V150, V200, and highest-dosed 0.1 cm{sup 3} and 1.0 cm{sup 3} of rib, skin, and lung between the two algorithms. Results: The CCC algorithm calculated lower values on average for all dose-volume histogram parameters. Across the entire patient cohort, the median difference in the clinical indices calculated by the 2 algorithms was <10% for dose to organs at risk, <5% for target volume coverage (V90, V95, and V100), and <4 cm{sup 3} for dose to normal breast tissue (V150 and V200). No discernable difference was seen in the nonconformance case. Conclusions: We found that on average over our patient population CCC calculated (<10%) lower doses than TG-43. These results should inform clinicians as they prepare for the transition to heterogeneous dose calculation algorithms and determine whether clinical tolerance limits warrant modification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Metal(loid) bioaccessibility and inhalation risk assessment: A comparison between an urban and an industrial area

Highlights: • Metal(loid) bioaccessibility of PM{sub 10} was evaluated with simulated lung fluids. • Most studied metal(loids) were highly bioaccessible in artificial lysosomal fluid. • Metal(loid)s from the industrial site had the highest bioaccessibility. • Elevated non-carcinogenic risk associated with Mn was found at the studied area. • Carcinogenic risk was slightly exceeded for Cd exposure at the industrial location. The content of metal(loid)s in particulate matter (PM) is of special concern due to their contribution to overall (PM) toxicity. In this study, the bioaccessibility and human health risk of potentially toxic metal(loid)s associated with PM{sub 10} were investigated in two areas of the Cantabrian region (northern Spain) with different levels of exposure: an industrial area mainly influenced by a ferromanganese alloy plant; and an urban area consisting mainly of residential and commercial activities, but also affected, albeit to a lesser extent by the ferroalloy plant. Total content and bioaccessible fractions in simulated lung fluids (SLFs) of Fe, Mn, Zn, Ni, Cu, Sb, Mo, Cd and Pb were determined by ICP-MS. Gamble's solution and artificial lysosomal fluid (ALF) were used to mimic different conditions inside the human respiratory system. A health risk assessment was performed based on the United States Environmental Protection Agency's (USEPA) methodology. Most metal(loid)s showed moderate and high bioaccessibility in Gamble's solution and ALF, respectively. Despite the high variability between the samples, metal(loid) bioaccessibility was found to be higher on average at the industrial site, suggesting a greater hazard to human health in the proximity of the main metal(loid) sources. Based on the results of the risk assessment, the non-carcinogenic risk associated with Mn exposure was above the safe limit (HQ> 1) under all the studied scenarios at the industrial site and under some specific scenarios at the urban location. The estimated carcinogenic inhalation risk for Cd exposure at the industrial site was found to be within the range between 1.0 × 10{sup −6} to 1.0 × 10{sup −4} (uncertainty range) under some scenarios. The results obtained in this study indicate that Mn and Cd inhalation exposure occurring in the vicinities of the studied areas may pose a human health risk.

54 ENVIRONMENTAL SCIENCES↗

Incorporating Physical Priors into Weakly Supervised Anomaly Detection

We propose a new machine-learning-based anomaly detection strategy for comparing data with a background-only reference (a form of weak supervision). The sensitivity of previous strategies degrades significantly when the signal is too rare or there are many unhelpful features. Our prior-assisted weak supervision (PAWS) method incorporates information from a class of signal models to significantly enhance the search sensitivity of weakly supervised approaches. As long as the true signal is in the prespecified class, PAWS matches the sensitivity of a dedicated, fully supervised method without specifying the exact parameters ahead of time. On the benchmark LHC Olympics anomaly detection dataset, our mix of semisupervised and weakly supervised learning is able to extend the sensitivity over previous methods by a factor of 10 in cross section. Furthermore, if we add irrelevant (noise) dimensions to the inputs, classical methods degrade by another factor of 10 in cross section while PAWS remains insensitive to noise. This new approach could be applied in a number of scenarios and pushes the frontier of sensitivity between completely model-agnostic approaches and fully model-specific searches.

artificial neural networks↗

Resin Assisted Capture Coupled with Isobaric Tandem Mass Tag Labeling for Multiplexed Quantification of Protein Thiol Oxidation

Reversible oxidative modifications on protein thiols have recently emerged as important mediators of cellular function. Herein we describe the detailed procedure of a quantitative redox proteomics method that utilizes resin-assisted capture (RAC) in combination with tandem mass tag (TMT) isobaric labeling and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to allow multiplexed stochiometric quantification of oxidized protein thiols at the proteome level. The site-specific quantitative information on oxidized cysteine residues provides additional insight into the functional impacts of such modifications. The workflow is adaptable across many sample types including cultured cells (e.g. mammalian, prokaryotic) and whole tissues (e.g. heart, lung, muscle) which are initially lysed/homogenized with free thiols being alkylated to prevent artificial oxidation. The oxidized protein thiols are then reduced and captured by a thiol affinity resin which streamlines and simplifies the workflow steps by allowing the proceeding digestion, labeling, and washing procedures to be performed without additional transfer of proteins/peptides. Finally, labeled peptides are eluted and analyzed by LC-MS/MS to reveal comprehensive stoichiometric changes related to thiol oxidation across the entire proteome. This method greatly improves our understanding of the role of redox dependent regulation under physiological and pathophysiological states related to protein thiol oxidation.

RAC, TMT, thiol redox proteomics, cysteine, PTM st↗

Loss of PTEN causes SHP2 activation, making lung cancer cells unresponsive to IFN-γ

Src homology-2 domain-containing phosphatase (SHP) 2, an oncogenic phosphatase, inhibits type II immune interferon (IFN)-γ signaling by subverting signal transducers and activators of transcription 1 tyrosine phosphorylation and activation. For cancer immunoediting, this study aimed to investigate the decrease of phosphatase and tensin homolog deleted on chromosome 10 (PTEN), a tumor suppressor protein, leading to cellular impairment of IFN-γ signaling. In comparison with human lung adenocarcinoma A549 cells, the natural PTEN loss in another human lung adenocarcinoma line, PC14PE6/AS2 cells, presents reduced responsiveness in IFN-γ-induced IFN regulatory factor 1 activation and CD54 expression. Artificially silencing PTEN expression in A549 cells also caused cells to be unresponsive to IFN-γ without affecting IFN-γ receptor expression. IFN-γ-induced inhibition of cell proliferation and cytotoxicity were demonstrated in A549 cells but were defective in PC14PE6/AS2 cells and in PTEN-deficient A549 cells. Aberrant activation of SHP2 by ROS was specifically shown in PC14PE6/AS2 cells and PTEN-deficient A549 cells. Inhibiting ROS and SHP2 rescued cellular responses to IFN-γ-induced cytotoxicity and inhibition of cell proliferation in PC14PE6/AS2 cells. These results demonstrate that a decrease in PTEN facilitates ROS/SHP2 signaling, causing lung cancer cells to become unresponsive to IFN-γ. - Highlights: • This study demonstrates that PTEN decrease causes cellular unresponsive to IFN-γ. • Lung cancer cells with PTEN deficiency show unresponsive to IFN-γ signaling. • PTEN decrease inhibits IFN-γ-induced CD54, cell proliferation inhibition, and cytotoxicity. • ROS-mediated SHP2 activation makes PTEN-deficient cells unresponsive to IFN-γ.

60 APPLIED LIFE SCIENCES↗

Selecting registration schemes in case of interstitial lung disease follow-up in CT

Purpose: Primary goal of this study is to select optimal registration schemes in the framework of interstitial lung disease (ILD) follow-up analysis in CT. Methods: A set of 128 multiresolution schemes composed of multiresolution nonrigid and combinations of rigid and nonrigid registration schemes are evaluated, utilizing ten artificially warped ILD follow-up volumes, originating from ten clinical volumetric CT scans of ILD affected patients, to select candidate optimal schemes. Specifically, all combinations of four transformation models (three rigid: rigid, similarity, affine and one nonrigid: third order B-spline), four cost functions (sum-of-square distances, normalized correlation coefficient, mutual information, and normalized mutual information), four gradient descent optimizers (standard, regular step, adaptive stochastic, and finite difference), and two types of pyramids (recursive and Gaussian-smoothing) were considered. The selection process involves two stages. The first stage involves identification of schemes with deformation field singularities, according to the determinant of the Jacobian matrix. In the second stage, evaluation methodology is based on distance between corresponding landmark points in both normal lung parenchyma (NLP) and ILD affected regions. Statistical analysis was performed in order to select near optimal registration schemes per evaluation metric. Performance of the candidate registration schemes was verified on a case sample of ten clinical follow-up CT scans to obtain the selected registration schemes. Results: By considering near optimal schemes common to all ranking lists, 16 out of 128 registration schemes were initially selected. These schemes obtained submillimeter registration accuracies in terms of average distance errors 0.18 ± 0.01 mm for NLP and 0.20 ± 0.01 mm for ILD, in case of artificially generated follow-up data. Registration accuracy in terms of average distance error in clinical follow-up data was in the range of 1.985–2.156 mm and 1.966–2.234 mm, for NLP and ILD affected regions, respectively, excluding schemes with statistically significant lower performance (Wilcoxon signed-ranks test, p < 0.05), resulting in 13 finally selected registration schemes. Conclusions: Selected registration schemes in case of ILD CT follow-up analysis indicate the significance of adaptive stochastic gradient descent optimizer, as well as the importance of combined rigid and nonrigid schemes providing high accuracy and time efficiency. The selected optimal deformable registration schemes are equivalent in terms of their accuracy and thus compatible in terms of their clinical outcome.

60 APPLIED LIFE SCIENCES↗

Tetranuclear Polypyridylruthenium(II) Complexes as Selective Nucleic Acid Stains for Flow Cytometric Analysis of Monocytic and Epithelial Lung Carcinoma Large Extracellular Vesicles

Selective staining of extracellular vesicles (EVs) is a major challenge for diagnostic and therapeutic applications. Herein, the EV labeling properties of a new class of tetranuclear polypyridylruthenium(II) complexes, Rubb7-TNL and Rubb7-TL, as phosphorescent stains are described. These new stains have many advantages over standard stains to detect and characterize EVs, including: high specificity for EV staining versus cell staining; high phosphorescence yields; photostability; and a lack of leaching from EVs until incorporation with target cells. As an example of their utility, large EVs released from control (basal) or lipopolysaccharide (LPS)-stimulated THP-1 monocytic leukemia cells were studied as a model of immune system EVs released during bacterial infection. Key findings from EV staining combined with flow cytometry were as follows: (i) LPS-stimulated THP-1 cells generated significantly larger and more numerous large EVs, as compared with those from unstimulated cells; (ii) EVs retained native EV physical properties after staining; and (iii) the new stains selectively differentiated intact large EVs from artificial liposomes, which are models of cell membrane fragments or other lipid-containing debris, as well as distinguished two distinct subpopulations of monocytic EVs within the same experiment, as a result of biochemical differences between unstimulated and LPS-stimulated monocytes. Comparatively, the staining patterns of A549 epithelial lung carcinoma-derived EVs closely resembled those of THP-1 cell line-derived EVs, which highlighted similarities in their selective staining despite their distinct cellular origins. This is consistent with the hypothesis that these new phosphorescent stains target RNA within the EVs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Indistinguishable photons from an artificial atom in silicon photonics

Silicon is the ideal material for building electronic and photonic circuits at scale. Integrated photonic quantum technologies in silicon offer a promising path to scaling by leveraging advanced semiconductor manufacturing and integration capabilities. However, the lack of deterministic quantum light sources and strong photon-photon interactions in silicon poses a challenge to scalability. In this work, we demonstrate an indistinguishable photon source in silicon photonics based on an artificial atom. We show that a G center in a silicon waveguide can generate high-purity telecom-band single photons. We perform high-resolution spectroscopy and time-delayed two-photon interference to demonstrate the indistinguishability of single photons emitted from a G center in a silicon waveguide. Our results show that artificial atoms in silicon photonics can source single photons suitable for photonic quantum networks and processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Objective assessment in digital images of skin erythema caused by radiotherapy

Purpose: Skin toxicity caused by radiotherapy has been visually classified into discrete grades. The present study proposes an objective and continuous assessment method of skin erythema in digital images taken under arbitrary lighting conditions, which is the case for most clinical environments. The purpose of this paper is to show the feasibility of the proposed method. Methods: Clinical data were gathered from six patients who received carbon beam therapy for lung cancer. Skin condition was recorded using an ordinary compact digital camera under unfixed lighting conditions; a laser Doppler flowmeter was used to measure blood flow in the skin. The photos and measurements were taken at 3 h, 30, and 90 days after irradiation. Images were decomposed into hemoglobin and melanin colors using independent component analysis. Pixel values in hemoglobin color images were compared with skin dose and skin blood flow. The uncertainty of the practical photographic method was also studied in nonclinical experiments. Results: The clinical data showed good linearity between skin dose, skin blood flow, and pixel value in the hemoglobin color images; their correlation coefficients were larger than 0.7. It was deduced from the nonclinical that the uncertainty due to the proposed method with photography was 15%; such an uncertainty was not critical for assessment of skin erythema in practical use. Conclusions: Feasibility of the proposed method for assessment of skin erythema using digital images was demonstrated. The numerical relationship obtained helped to predict skin erythema by artificial processing of skin images. Although the proposed method using photographs taken under unfixed lighting conditions increased the uncertainty of skin information in the images, it was shown to be powerful for the assessment of skin conditions because of its flexibility and adaptability.

60 APPLIED LIFE SCIENCES↗

Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Boice, Emily N. (ORCID:0000000171802842)↗

A vision of immuno-oncology: the Siena think tank of the Italian Network for Tumor Biotherapy (NIBIT) foundation

The yearly Think Tank Meeting of the Italian Network for Tumor Biotherapy (NIBIT) Foundation, brings together in Siena, Tuscany (Italy), experts in immuno-oncology to review the learnings from current immunotherapy treatments, and to propose new pre-clinical and clinical investigations in selected research areas. While immunotherapies in non-small cell lung cancer and melanoma led to practice changing therapies, the same therapies had only modest benefit for patients with other malignancies, such as mesothelioma and glioblastoma. One way to improve on current immunotherapies is to alter the sequence of each combination agent. Matching the immunotherapy to the host’s immune response may thus improve the activity of the current treatments. A second approach is to combine current immunotherapies with novel agents targeting complementary mechanisms. Identifying the appropriate novel agents may require different approaches than the traditional laboratory-based discovery work. For example, artificial intelligence-based research may help focusing the search for innovative and most promising combination partners. Novel immunotherapies are needed in cancer patients with resistance to or relapse after current immunotherapeutic drugs. Such new treatments may include targeted agents or monoclonal antibodies to overcome the immune-suppressive tumor microenvironment. The mode of combining the novel treatments, including vaccines, needs to be matched to the patient’s immune status for achieving the maximum benefit. In this scenario, specific attention should be also paid nowadays to the immune intersection between COVID-19 and cancer.

60 APPLIED LIFE SCIENCES↗

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↗