ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to major public health crises worldwide. Several studies have reported the comprehensive mRNA expression analysis of immune-related genes in patients with COVID-19, using blood samples, to understand its pathogenesis; however, the characteristics of RNA expression in COVID-19 and bacterial sepsis have not been compared. The current study aimed to address this gap. METHODS: RNA-sequencing and bioinformatics analyses were used to compare the transcriptome expression of whole blood samples from patients with COVID-19 and patients with sepsis who were admitted to the intensive care unit of Osaka University Graduate School of Medicine. RESULTS: The COVID-19 and sepsis cohorts showed upregulation of mitochondrial- and neutrophil-related transcripts, respectively. Compared with that in the control cohort, neutrophil-related transcripts were upregulated in both the COVID-19 and sepsis cohorts. In contrast, mitochondrial-related transcripts were upregulated in the COVID-19 cohort and downregulated in the sepsis cohort, compared to those in the control cohort. Moreover, transcript levels of the pro-apoptotic genes BAK1, CYCS, BBC3, CASP7, and CASP8 were upregulated in the COVID-19 cohort, whereas those of anti-apoptotic genes, such as BCL2L11 and BCL2L1, were upregulated in the sepsis cohort. CONCLUSIONS: This study clarified the differential expression of transcripts related to neutrophils and mitochondria in sepsis and COVID-19 conditions. Mitochondrial-related transcripts were downregulated in sepsis than in COVID-19 conditions, and our results indicated suboptimal intrinsic apoptotic features in sepsis samples compared with that in COVID-19 samples. This study is expected to contribute to the development of specific treatments for COVID-19.
Subject(s)
COVID-19 , Sepsis , Humans , COVID-19/genetics , Sepsis/genetics , SARS-CoV-2 , Intensive Care Units , RNAABSTRACT
We derive feedback control laws for isolation, contact regulation, and vaccination for infectious diseases, using a strict Lyapunov function. We use an SIQR epidemic model describing transmission, isolation via quarantine, and vaccination for diseases to which immunity is long-lasting. Assuming that mass vaccination is not available to completely eliminate the disease in a time horizon of interest, we provide feedback control laws that drive the disease to an endemic equilibrium. We prove the input-to-state stability (or ISS) robustness property on the entire state space, when the immigration perturbation is viewed as the uncertainty. We use an ISS Lyapunov function to derive the feedback control laws. A key ingredient in our analysis is that all compartment variables are present not only in the Lyapunov function, but also in a negative definite upper bound on its time derivative. We illustrate the efficacy of our method through simulations, and we discuss the usefulness of parameters in the controls. Since the control laws are feedback, their values are updated based on data acquired in real time. We also discuss the degradation caused by the delayed data acquisition occurring in practical implementations, and we derive bounds on the delays under which the ISS property is ensured when delays are present.
ABSTRACT
This article pursues a new approach to the design of feedback control laws mitigating the spread of human infectious diseases. The control inputs of vaccination, isolation, and outing/gathering regulation are derived as the gradient of a positive definite function of all the population variables of the SIQR model. Lyapunov functions in which susceptible and infected populations are decoupled are known to be non‐self‐sufficient for proving stability of the SIQR model as well as other variants of the SIR model. This fact has been hampering Lyapunov‐based control design of infectious disease models. This article demonstrates that a popular decoupled function can still serve as a control Lyapunov function as long as isolation is made state‐dependent. Techniques realizing this novel idea are presented and shown to allow the Lyapunov function to establish a robustness guarantee in terms of input‐to‐state stability with respect to immigration and newborn perturbation on an arbitrarily large domain. The effectiveness of the proposed simultaneous controller is illustrated through numerical simulations performed with a parameter set of COVID‐19. [ FROM AUTHOR] Copyright of International Journal of Robust & Nonlinear Control is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Bovine lactoferrin (bLF) is a naturally occurring glycoprotein with antibacterial and antiviral activities. We evaluated whether bLF can prevent viral infections in the human intestinal epithelial cell line Caco-2. To assess antiviral responses, we measured the levels of interferon (IFN) expression, IFN-stimulated gene expression, and infection with a pseudotyped virus bearing either severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein or vesicular stomatitis virus (VSV)-G protein after treatment of cells with both bLF and polyinosinic-polycytidylic acid, an analog of double-stranded RNA that mimics viral infection. Combination treatment of cells with both bLF and polyinosinic-polycytidylic acid increased mRNA and protein expression of several IFN genes (IFNB, IFNL1, and IFNL2) and IFN-stimulated genes (ISG15, MX1, IFITM1, and IFITM3) in Caco-2 cells. However, treatment with bLF alone did not induce an antiviral response. Furthermore, combination treatment suppressed infection of the SARS-CoV-2 pseudotyped virus more efficiently than did bLF treatment alone, even though combination treatment increased the expression of mRNA encoding ACE2. These results indicate that bLF increases the antiviral response associated with the double-stranded RNA-stimulated signaling pathway. Our results also suggest that bLF and double-stranded RNA analogs can be used to treat viral infections, including those caused by SARS-CoV-2.