Smart Nanostructured Materials for SARS-CoV-2 and Variants Prevention, Biosensing and Vaccination.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has raised great concerns about human health globally. At the current stage, prevention and vaccination are still the most efficient ways to slow down the pandemic and to treat SARS-CoV-2 in various aspects. In this review, we summarize current progress and research activities in developing smart nanostructured materials for COVID-19 prevention, sensing, and vaccination. A few established concepts to prevent the spreading of SARS-CoV-2 and the variants of concerns (VOCs) are firstly reviewed, which emphasizes the importance of smart nanostructures in cutting the virus spreading chains. In the second part, we focus our discussion on the development of stimuli-responsive nanostructures for high-performance biosensing and detection of SARS-CoV-2 and VOCs. The use of nanostructures in developing effective and reliable vaccines for SARS-CoV-2 and VOCs will be introduced in the following section. In the conclusion, we summarize the current research focus on smart nanostructured materials for SARS-CoV-2 treatment. Some existing challenges are also provided, which need continuous efforts in creating smart nanostructured materials for coronavirus biosensing, treatment, and vaccination.

Common mtDNA variations at C5178a and A249d/T6392C/G10310A decrease the risk of severe COVID-19 in a Han Chinese population from Central China.

BACKGROUND: Mitochondria have been shown to play vital roles during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) development. Currently, it is unclear whether mitochondrial DNA (mtDNA) variants, which define mtDNA haplogroups and determine oxidative phosphorylation performance and reactive oxygen species production, are associated with COVID-19 risk. METHODS: A population-based case-control study was conducted to compare the distribution of mtDNA variations defining mtDNA haplogroups between healthy controls (n = 615) and COVID-19 patients (n = 536). COVID-19 patients were diagnosed based on molecular diagnostics of the viral genome by qPCR and chest X-ray or computed tomography scanning. The exclusion criteria for the healthy controls were any history of disease in the month preceding the study assessment. MtDNA variants defining mtDNA haplogroups were identified by PCR-RFLPs and HVS-I sequencing and determined based on mtDNA phylogenetic analysis using Mitomap Phylogeny. Student's t-test was used for continuous variables, and Pearson's chi-squared test or Fisher's exact test was used for categorical variables. To assess the independent effect of each mtDNA variant defining mtDNA haplogroups, multivariate logistic regression analyses were performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) with adjustments for possible confounding factors of age, sex, smoking and diseases (including cardiopulmonary diseases, diabetes, obesity and hypertension) as determined through clinical and radiographic examinations. RESULTS: Multivariate logistic regression analyses revealed that the most common investigated mtDNA variations (> 10% in the control population) at C5178a (in NADH dehydrogenase subunit 2 gene, ND2) and A249d (in the displacement loop region, D-loop)/T6392C (in cytochrome c oxidase I gene, CO1)/G10310A (in ND3) were associated with a reduced risk of severe COVID-19 (OR = 0.590, 95% CI 0.428-0.814, P = 0.001; and OR = 0.654, 95% CI 0.457-0.936, P = 0.020, respectively), while A4833G (ND2), A4715G (ND2), T3394C (ND1) and G5417A (ND2)/C16257a (D-loop)/C16261T (D-loop) were related to an increased risk of severe COVID-19 (OR = 2.336, 95% CI 1.179-4.608, P = 0.015; OR = 2.033, 95% CI 1.242-3.322, P = 0.005; OR = 3.040, 95% CI 1.522-6.061, P = 0.002; and OR = 2.890, 95% CI 1.199-6.993, P = 0.018, respectively). CONCLUSIONS: This is the first study to explore the association of mtDNA variants with individual's risk of developing severe COVID-19. Based on the case-control study, we concluded that the common mtDNA variants at C5178a and A249d/T6392C/G10310A might contribute to an individual's resistance to developing severe COVID-19, whereas A4833G, A4715G, T3394C and G5417A/C16257a/C16261T might increase an individual's risk of developing severe COVID-19.

Mesenchymal stem cell therapy for severe COVID-19.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed a global public burden on health authorities. Although the virological characteristics and pathogenesis of COVID-19 has been largely clarified, there is currently no specific therapeutic measure. In severe cases, acute SARS-CoV-2 infection leads to immune disorders and damage to both the adaptive and innate immune responses. Having roles in immune regulation and regeneration, mesenchymal stem cells (MSCs) serving as a therapeutic option may regulate the over-activated inflammatory response and promote recovery of lung damage. Since the outbreak of the COVID-19 pandemic, a series of MSC-therapy clinical trials has been conducted. The findings indicate that MSC treatment not only significantly reduces lung damage, but also improves patient recovery with safety and good immune tolerance. Herein, we summarize the recent progress in MSC therapy for COVID-19 and highlight the challenges in the field.

Characteristics and prognostic factors of disease severity in patients with COVID-19: The Beijing experience.

COVID-19 has become one of the worst infectious disease outbreaks of recent times, with over 2.1 million cases and 120,000 deaths so far. Our study investigated the demographic, clinical, laboratory and imaging features of 63 patients with COVID-19 in Beijing. Patients were classified into four groups, mild, moderate, severe and critically ill. The mean age of our patients was 47 years of age (range 3-85) and there was a slight male predominance (58.7%). Thirty percent of our patients had severe or critically ill disease, but only 20% of severe and 33% of critically ill patients had been to Wuhan. Fever was the most common presentation (84.1%), but cough was present in only slightly over half of the patients. We found that lymphocyte and eosinophils count were significantly decreased in patients with severe disease (p = 0.001 and p = 0.000, respectively). Eosinopenia was a feature of higher levels of severity. Peripheral CD4+, CD8+ T lymphocytes, and B lymphocytes were significantly decreased in severe and critically ill patients, but there was only a non-statistically significant downward trend in NK cell numbers with severity. Of note is that liver function tests including AST, ALT, GGT and LDH were elevated, and albumin was decreased. The inflammatory markers CRP, ESR and ferritin were elevated in patients with severe disease or worse. IL-6 levels were also higher, indicating that the presence of a hyperimmune inflammatory state portends higher morbidity and mortality. In a binary logistic regression model, C-reactive protein level (OR 1.073, [CI, 1.013-1.136]; p = 0.017), CD8 T lymphocyte counts (OR 0.989, [CI, 0.979-1.000]; p = 0.043), and D-dimer (OR 5.313, [CI, 0.325-86.816]; p = 0.241) were independent predictors of disease severity.