Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID-19: A single-center prospective longitudinal study

Background: Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. Methods: We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(−) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher\u27s linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts. Results: Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels. Conclusions: Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19

Parasite Burden and CD36-Mediated Sequestration Are Determinants of Acute Lung Injury in an Experimental Malaria Model

Although acute lung injury (ALI) is a common complication of severe malaria, little is known about the underlying molecular basis of lung dysfunction. Animal models have provided powerful insights into the pathogenesis of severe malaria syndromes such as cerebral malaria (CM); however, no model of malaria-induced lung injury has been definitively established. This study used bronchoalveolar lavage (BAL), histopathology and gene expression analysis to examine the development of ALI in mice infected with Plasmodium berghei ANKA (PbA). BAL fluid of PbA-infected C57BL/6 mice revealed a significant increase in IgM and total protein prior to the development of CM, indicating disruption of the alveolar–capillary membrane barrier—the physiological hallmark of ALI. In contrast to sepsis-induced ALI, BAL fluid cell counts remained constant with no infiltration of neutrophils. Histopathology showed septal inflammation without cellular transmigration into the alveolar spaces. Microarray analysis of lung tissue from PbA-infected mice identified a significant up-regulation of expressed genes associated with the gene ontology categories of defense and immune response. Severity of malaria-induced ALI varied in a panel of inbred mouse strains, and development of ALI correlated with peripheral parasite burden but not CM susceptibility. Cd36−/− mice, which have decreased parasite lung sequestration, were relatively protected from ALI. In summary, parasite burden and CD36-mediated sequestration in the lung are primary determinants of ALI in experimental murine malaria. Furthermore, differential susceptibility of mouse strains to malaria-induced ALI and CM suggests that distinct genetic determinants may regulate susceptibility to these two important causes of malaria-associated morbidity and mortality

Design of Conventional and Detonation-Driven Hypervelocity Expansion Tubes

Freestream disturbances can have a significant impact on studies of boundary layer transition in ground tests, including experiments in high-enthalpy hypersonic facilities such as an expansion tube. Freest ream noise reduction in expansion tubes can be achieved by increasing the driver-to-driven pressure ratio p_4/p_1, so we seek .methods to increase this ratio in Caltech's HET facility. Towards this end, an in-house modular parametric code has been developed using Python to explore possible modifications to the HET. The effect of increasing the pressure in a passive driver on potential noise reduction is investigated. Optimization of acceleration section length is also explored for conventional drivers. The performance of detonation drivers using H_2 and C_2H_2 fuels with He, Ar, and CO_2 diluents is examined