Sera Metabolomics Characterization of Patients at Different Stages in Wuhan Identifies Critical Biomarkers of COVID-19.

We have witnessed the 2-year-long global rampage of COVID-19 caused by the wide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, knowledge about biomarkers of the entire COVID-19 process is limited. Identification of the systemic features of COVID-19 will lead to critical biomarkers and therapeutic targets for early intervention and clinical disease course prediction. Here, we performed a comprehensive analysis of clinical measurements and serum metabolomics in 199 patients with different stages of COVID-19. In particular, our study is the first serum metabolomic analysis of critical rehabilitation patients and critical death patients. We found many differential metabolites in the comparison of metabolomic results between ordinary, severe, and critical patients and uninfected patients. Through the metabolomic results of COVID-19 patients in various stages, and critical rehabilitation patients and critical death patients, we identified a series of differential metabolites as biomarkers, a separate queue and precise distinction, and predicted COVID-19 verification. These differentially expressed metabolites, included 1,2-di-(9Z,12Z-octadecadienoyl)-sn-glycero-3-phosphate, propylparaben, 20-hydroxyeicosatetraenoic acid, triethanolamine, chavicol, disialosyl galactosyl globoside, 1-arachidonoylglycerophosphoinositol, and alpha-methylstyrene, all of which have been identified for the first time as biomarkers in COVID-19 progression. These biomarkers are involved in many pathological and physiological pathways of COVID-19, for example, immune responses, platelet degranulation, and metabolism which might result in pathogenesis. Our results showed valuable information about metabolites obviously altered in COVID-19 patients with different stages, which could shed light on the pathogenesis as well as serve as potential therapeutic agents of COVID-19.

Molecular Engineering of Laser-Induced Graphene for Potential-Driven Broad-Spectrum Antimicrobial and Antiviral Applications.

Worldwide, countless deaths have been caused by the coronavirus disease 2019. In addition to the virus variants, an increasing number of fatal fungal infections have been reported, which further exacerbates the scenario. Therefore, the development of porous surfaces with both antiviral and antimicrobial capacities is of urgent need. Here, a cost-effective, nontoxic, and metal-free strategy is reported for the surface engineering of laser-induced graphene (LIG). The authors covalently engineer the surface potential of the LIG from -14 to ≈+35 mV (LIG+ ), enabling both high-efficiency antimicrobial and antiviral performance under mild conditions. Specifically, several candidate microorganisms of different types, including Escherichia coli, Streptomyces tenebrarius, and Candida albicans, are almost completely inactivated after 10-min solar irradiation. LIG+ also exhibits a strong antiviral effect against human coronaviruses: 99% HCoV-OC43 and 100% HCoV-229E inactivation are achieved after 20-min treatment. Such enhancement may also be observed against other types of pathogens that are heat-sensitive and oppositely charged. Besides, the covalent modification strategy alleviates the leaching problem, and the low cytotoxicity of LIG+ makes it advantageous. This study highlights the synergy of surface potential and photothermal effect in the inactivation of pathogens and it provides a direction for designing porous materials for airborne disease removal and water disinfection.

Development and validation of a simplified nomogram predicting individual critical illness of risk in COVID-19: A retrospective study.

This study aims to screen useful predictors of critical cases among coronavirus disease 2019 (COVID-19) patients and to develop a simple-to-use nomogram for clinical utility. A retrospective study was conducted that consisted of a primary cohort with 315 COVID-19 patients and two validation cohorts with 69 and 123 patients, respectively. Logistic regression analyses were used to identify the independent risks of progression to critical. An individualized prediction model was developed, and calibration, decision curve, and clinical impact curves were used to assess the performance of the model. External validations for the predictive nomogram were also provided. The variables of age, comorbid diseases, neutrophil-to-lymphocyte ratio, d-dimer, C-reactive protein, and platelet count were estimated to be independent predictors of progression to critical, which were incorporated to establish a model of the nomogram. It demonstrated good discrimination (with a C-index of 0.923) and calibration. Good discrimination (C-index, 0.882 and 0.906) and calibration were also noted on applying the nomogram in two validation cohorts. The clinical relevance of the nomogram was justified by the decision curve and clinical impact curve analysis. This study presents an individualized prediction nomogram incorporating six clinical characteristics, which can be conveniently applied to assess an individual's risk of progressing to critical COVID-19.

Cytokines and their relationship with the severity and prognosis of coronavirus disease 2019 (COVID-19): a retrospective cohort study.

OBJECTIVE: To delineate the characteristics and clinical significance of plasma inflammatory cytokines altered in COVID-19. DESIGN: Retrospective, single-centre cohort study. SETTING: Tongji Hospital in Wuhan, China. PARTICIPANTS: Among a cohort of 308 patients with a diagnosis of COVID-19, 138 patients died while 170 patients recovered and were discharged from the hospital. The data were collected until 27 February 2020. PRIMARY AND SECONDARY OUTCOME MEASURES: Clinical characteristics and laboratory findings were obtained from electronic medical records using data collection forms. RESULTS: The percentage of patients with elevated interleukin 2 receptor (IL-2R), IL-6, IL-8, IL-10 and tumour necrosis factor (TNF) increased with severity of disease (p<0.0001 for all). IL-2R (p<0.0001), IL-6 (p<0.0001), IL-8 (p=0.0001), IL-10 (p<0.0001) and TNF (p<0.0001) were also twofold to 20-fold higher in patients who died compared with those who recovered. Also, IL-6 and IL-10 increased in both the progressive patient groups: moderate (p=0.0026) and severe (p<0.0001). In multivariate analysis, higher levels of IL-2R (OR 1.001, 95% CI 1.000 to 1.002, p=0.031) and IL-6 (OR 1.013, 95% CI 1.003 to 1.024, p=0.015) on admission were associated with increasing odds of in-hospital death, independent of other covariates, including severity of disease and lymphocyte count. CONCLUSION: Increased proinflammatory and anti-inflammatory cytokines, including IL-2R, IL-6, IL-8, TNF and IL-10, showed an obvious association with both COVID-19 severity and in-hospital mortality. Thus, our study indicates that cytokines are valuable in predicting the severity of COVID-19 and helps in distinguishing critically ill patients from the less affected ones.

Clinical characteristics study of elderly patients aged 75 or older with COVID-19 pneumonia in China (preprint)

Background: Coronavirus disease 2019 (COVID-19), a newly emerged respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become pandemic. Clinical observation indicated that elderly patients had high incidence of severe pneumonia and poor treatment efficacy. Therefore, this study was to clarify the characteristics of elderly patients aged 75 or older with COVID-19 pneumonia in order to guide rational treatment for elderly patients. Methods: we enrolled 331 elderly patients aged 75 or older with confirmed COVID-19 in Huoshenshan hospital of Wuhan from February 3rd to March 31st. The cases were divided into general, serious and critical groups according to severity after hospitalization, and the difference among groups were compared by R package statistics software. Results: Compared with general group, serious and critical groups had more underlying comorbidities and higher incidence of cough, breath shortness and anorexia. Moreover, there existed obviously differences in many of laboratory indexes and CT images among them. serious and critical elderly patients were more likely to receive oxygen, mechanical ventilation, expectorant, corticosteroid, abidor, cephaloprin, imipenem, human serum albumin (HSA), nutrition support, anti SARS-CoV-2 positive plasma and actemra. Multivariate analysis of factors showed that male sex, hypertension, diabetes, renal diseases, breath shortness, neutrophil, platelet, creatinine, lactate dehydrogenase were the risk factor for serious and critical illness. While blood cell (WBC) was the protective factor. Conclusion: elderly patients have high incidence of severe pneumonia and poor treatment efficacy. The reasons might be that many of the elderly patients with COVID-19 pneumonia have certain chronic disease, poor immune function and a meager response to the virus. the pathogenic mechanism of SARS-CoV-2 might be involved in the cell-mediated immunity and cytokine storms by acting on lymphocytes.

Diagnostic performance of initial blood urea nitrogen combined with D-dimer levels for predicting in-hospital mortality in COVID-19 patients.

The crude mortality rate in critical pneumonia cases with coronavirus disease 2019 (COVID-19) reaches 49%. This study aimed to test whether levels of blood urea nitrogen (BUN) in combination with D-dimer were predictors of in-hospital mortality in COVID-19 patients. The clinical characteristics of 305 COVID-19 patients were analysed and were compared between the survivor and non-survivor groups. Of the 305 patients, 85 (27.9%) died and 220 (72.1%) were discharged from hospital. Compared with discharged cases, non-survivor cases were older and their BUN and D-dimer levels were significantly higher (P < 0.0001). Least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses identified BUN and D-dimer levels as independent risk factors for poor prognosis. Kaplan-Meier analysis showed that elevated levels of BUN and D-dimer were associated with increased mortality (log-rank, P < 0.0001). The area under the curve for BUN combined with D-dimer was 0.94 (95% CI 0.90-0.97), with a sensitivity of 85% and specificity of 91%. Based on BUN and D-dimer levels on admission, a nomogram model was developed that showed good discrimination, with a concordance index of 0.94. Together, initial BUN and D-dimer levels were associated with mortality in COVID-19 patients. The combination of BUN ≥ 4.6 mmol/L and D-dimer ≥ 0.845 µg/mL appears to identify patients at high risk of in-hospital mortality, therefore it may prove to be a powerful risk assessment tool for severe COVID-19 patients.