COVID-19-associated pulmonary aspergillosis (CAPA): identification of Aspergillus species and determination of antifungal susceptibility profiles.

Among the co-infectious agents in COVID-19 patients, Aspergillus species cause invasive pulmonary aspergillosis (IPA). IPA is difficult to diagnose and is associated with high morbidity and mortality. This study is aimed at identifying Aspergillus spp. from sputum and tracheal aspirate (TA) samples of COVID-19 patients and at determining their antifungal susceptibility profiles. A total of 50 patients with COVID-19 hospitalized in their intensive care units (ICU) were included in the study. Identification of Aspergillus isolates was performed by phenotypic and molecular methods. ECMM/ISHAM consensus criteria were used for IPA case definitions. The antifungal susceptibility profiles of isolates were determined by the microdilution method. Aspergillus spp. was detected in 35 (70%) of the clinical samples. Among the Aspergillus spp., 20 (57.1%) A. fumigatus, six (17.1%) A. flavus, four (11.4%) A. niger, three (8.6%) A. terreus, and two (5.7%) A. welwitschiae were identified. In general, Aspergillus isolates were susceptible to the tested antifungal agents. In the study, nine patients were diagnosed with possible IPA, 11 patients were diagnosed with probable IPA, and 15 patients were diagnosed with Aspergillus colonization according to the used algorithms. Serum galactomannan antigen positivity was found in 11 of the patients diagnosed with IPA. Our results provide data on the incidence of IPA, identification of Aspergillus spp., and its susceptibility profiles in critically ill COVID-19 patients. Prospective studies are needed for a faster diagnosis or antifungal prophylaxis to manage the poor prognosis of IPA and reduce the risk of mortality.

Evaluation of the Relationship Between Aquaporin-1, Hepcidin, Zinc, Copper, and Iron Levels and Oxidative Stress in the Serum of Critically Ill Patients with COVID-19.

Our study aims to determine the relationship between hepcidin, aquaporin (AQP-1), copper (Cu), zinc (Zn), iron (Fe) levels, and oxidative stress in the sera of seriously ill COVID-19 patients with invasive mechanical ventilation. Ninety persons with and without COVID-19 were taken up and separated into two groups. The first group included seriously COVID-19 inpatients having endotracheal intubation in the intensive care unit (n = 45). The second group included individuals who had negative PCR tests and had no chronic disease (the healthy control group n = 45). AQP-1, hepcidin, Zn, Cu, Fe, total antioxidant status (TAS), and total oxidant status (TOS) were studied in the sera of both groups, and the relations of these levels with oxidative stress were determined. When the COVID-19 patient and the control groups were compared, all studied parameters were found to be statistically significant (p < 0.01). Total oxidant status (TOS), oxidative stress index (OSI), and AQP-1, hepcidin, and Cu levels were increased in patients with COVID-19 compared to healthy people. Serum TAC, Zn, and Fe levels were found to be lower in the patient group than in the control group. Significant correlations were detected between the studied parameters in COVID-19 patients. Results indicated that oxidative stress may play an important role in viral infection due to SARS-CoV-2. We think that oxidative stress parameters as well as some trace elements at the onset of COVID-19 disease will provide a better triage in terms of disease severity.

Evaluation of amino acid profile in serum of patients with Covid-19 for providing a new treatment strategy.

Background: Amino acids have an important role in metabolism and may affect COVID-19-related outcomes. In our study, the amino acid serum level of hospitalized COVID19 patients was evaluated to determine a new treatment strategy. Methods: The amino acid profile covering 43 amino acids in 68 subjects, comprising 30 (14 men and 16 women) controls and 38 (16 men and 22 women) COVID-19 patients, were examined. The amino acid profiles of the participants were screened by LC-MS/MS. Results: Compared with the control group, serum levels of 27 amino acids increased in the patient group. Alpha-aminopimelic acid, sarcosine, and hydroxyproline amino acids were considerably higher in the control group than in the patient group (p<0.0001). There was no notable difference among control group and the case group for 13 amino acids (p≥0.05). A significant positive correlation was seen among the control and the patient groups in the mean amino acid values (r=0.937; p<0.0001). Conclusions: These results postulated a clear picture on the serum levels of amino acid in the COVID-19 patients. Serum amino acids measured in hospitalized COVID-19 patients can explain the patient's metabolic status during the disease.

Structure and Hierarchy of SARS-CoV-2 Infection Dynamics Models Revealed by Reaction Network Analysis.

This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy.

Structure and Hierarchy of SARS-CoV-2 Infection Dynamics Models Revealed by Reaction Network Analysis

This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy.

The International Virus Bioinformatics Meeting 2020.

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8-9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.