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1.
Clin Transl Sci ; 15(5): 1291-1303, 2022 05.
Article in English | MEDLINE | ID: covidwho-1673035

ABSTRACT

The RD-X19 is an investigational, handheld medical device precisely engineered to emit blue light through the oral cavity to target the oropharynx and surrounding tissues. At doses shown to be noncytotoxic in an in vitro three-dimensional human epithelial tissue model, the monochromatic visible light delivered by RD-X19 results in light-initiated expression of immune stimulating cytokines IL-1α and IL-1ß, with corresponding inhibition of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) replication. A single exposure of 425 nm blue light at 60 J/cm2 led to greater than 99% reductions against all SARS-CoV-2 strains tested in vitro, including the more transmissible (Alpha) and immune evasive (Beta) variants. These preclinical findings along with other studies led to a randomized, double-blind, sham-controlled early feasibility study using the investigational device as a treatment for outpatients with mild to moderate coronavirus disease 2019 (COVID-19). The study enrolled 31 subjects with a positive SARS-CoV-2 antigen test and at least two moderate COVID-19 signs and symptoms at baseline. Subjects were randomized 2:1 (RD-X19: sham) and treated twice daily for 4 days. Efficacy outcome measures included assessments of SARS-CoV-2 saliva viral load and clinical assessments of COVID-19. There were no local application site reactions and no device-related adverse events. At the end of the study (day 8), the mean change in log10 viral load was -3.29 for RD-X19 and -1.81 for sham, demonstrating a treatment benefit of -1.48 logs (95% confidence internal, -2.88 to -0.071, nominal p = 0.040). Among the clinical outcome measures, differences between RD-X19 and sham were also observed, with a 57-h reduction of median time to sustained resolution of COVID-19 signs and symptoms (log rank test, nominal p = 0.044).


Subject(s)
COVID-19 , Feasibility Studies , Humans , Outpatients , SARS-CoV-2 , Treatment Outcome , Viral Load
2.
Sci Rep ; 11(1): 20595, 2021 10 18.
Article in English | MEDLINE | ID: covidwho-1475487

ABSTRACT

The delivery of safe, visible wavelengths of light can be an effective, pathogen-agnostic, countermeasure that would expand the current portfolio of SARS-CoV-2 intervention strategies beyond the conventional approaches of vaccine, antibody, and antiviral therapeutics. Employing custom biological light units, that incorporate optically engineered light-emitting diode (LED) arrays, we harnessed monochromatic wavelengths of light for uniform delivery across biological surfaces. We demonstrated that primary 3D human tracheal/bronchial-derived epithelial tissues tolerated high doses of a narrow spectral band of visible light centered at a peak wavelength of 425 nm. We extended these studies to Vero E6 cells to understand how light may influence the viability of a mammalian cell line conventionally used for assaying SARS-CoV-2. The exposure of single-cell monolayers of Vero E6 cells to similar doses of 425 nm blue light resulted in viabilities that were dependent on dose and cell density. Doses of 425 nm blue light that are well-tolerated by Vero E6 cells also inhibited infection and replication of cell-associated SARS-CoV-2 by > 99% 24 h post-infection after a single five-minute light exposure. Moreover, the 425 nm blue light inactivated cell-free betacoronaviruses including SARS-CoV-1, MERS-CoV, and SARS-CoV-2 up to 99.99% in a dose-dependent manner. Importantly, clinically applicable doses of 425 nm blue light dramatically inhibited SARS-CoV-2 infection and replication in primary human 3D tracheal/bronchial tissue. Safe doses of visible light should be considered part of the strategic portfolio for the development of SARS-CoV-2 therapeutic countermeasures to mitigate coronavirus disease 2019 (COVID-19).


Subject(s)
COVID-19/drug therapy , COVID-19/prevention & control , Light , SARS-CoV-2 , Trachea/radiation effects , Virus Replication/radiation effects , Adult , Animals , Antiviral Agents/pharmacology , Bronchi , Calibration , Cell-Free System , Chlorocebus aethiops , Epithelium/pathology , Female , Humans , Respiratory Mucosa/radiation effects , Trachea/virology , Vero Cells
3.
Methods Mol Biol ; 2099: 137-159, 2020.
Article in English | MEDLINE | ID: covidwho-1292550

ABSTRACT

Since 2012, monthly cases of Middle East respiratory syndrome coronavirus (MERS-CoV) continue to cause severe respiratory disease that is fatal in ~35% of diagnosed individuals. The ongoing threat to global public health and the need for novel therapeutic countermeasures have driven the development of animal models that can reproducibly replicate the pathology associated with MERS-CoV in human infections. The inability of MERS-CoV to replicate in the respiratory tracts of mice, hamsters, and ferrets stymied initial attempts to generate small animal models. Identification of human dipeptidyl peptidase IV (hDPP4) as the receptor for MERS-CoV infection opened the door for genetic engineering of mice. Precise molecular engineering of mouse DPP4 (mDPP4) with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology maintained inherent expression profiles, and limited MERS-CoV susceptibility to tissues that naturally express mDPP4, notably the lower respiratory tract wherein MERS-CoV elicits severe pulmonary pathology. Here, we describe the generation of the 288-330+/+ MERS-CoV mouse model in which mice were made susceptible to MERS-CoV by modifying two amino acids on mDPP4 (A288 and T330), and the use of adaptive evolution to generate novel MERS-CoV isolates that cause fatal respiratory disease. The 288-330+/+ mice are currently being used to evaluate novel drug, antibody, and vaccine therapeutic countermeasures for MERS-CoV. The chapter starts with a historical perspective on the emergence of MERS-CoV and animal models evaluated for MERS-CoV pathogenesis, and then outlines the development of the 288-330+/+ mouse model, assays for assessing a MERS-CoV pulmonary infection in a mouse model, and describes some of the challenges associated with using genetically engineered mice.


Subject(s)
Coronavirus Infections/virology , Dipeptidyl Peptidase 4/genetics , Disease Models, Animal , Mice/genetics , Middle East Respiratory Syndrome Coronavirus/physiology , Respiratory Distress Syndrome/virology , Animals , CRISPR-Cas Systems , Coronavirus Infections/pathology , Dipeptidyl Peptidase 4/metabolism , Disease Susceptibility , Female , Genetic Engineering , Humans , Lung/virology , Male , Mice, Inbred C57BL , Respiratory Distress Syndrome/pathology
4.
BMC Bioinformatics ; 22(1): 287, 2021 May 29.
Article in English | MEDLINE | ID: covidwho-1257920

ABSTRACT

BACKGROUND: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. RESULTS: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. CONCLUSIONS: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.


Subject(s)
Algorithms , Models, Biological , Genomics , Proteins
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