Vaccination increased host antiviral gene expression and reduced COVID-19 severity during the Omicron variant outbreak in Fuyang City, China.

BACKGROUND: The differences in host antiviral gene expression and disease severity between vaccinated and non-vaccinated coronavirus disease 2019 (COVID-19) patients are not well characterized. We sought to compare the clinical characteristics and host antiviral gene expression patterns of vaccinated and non-vaccinated cohorts at the Second People's Hospital of Fuyang City. METHODS: In this case-control study, we retrospectively analyzed 113 vaccinated patients with a COVID-19 Omicron variant infection, 46 non-vaccinated COVID-19 patients, and 24 healthy subjects (no history of COVID-19) recruited from the Second People's Hospital of Fuyang City. Blood samples were collected from each study participant for RNA extraction and PCR. We compared host antiviral gene expression profiles between healthy controls and COVID-19 patients who were either vaccinated or non-vaccinated at the time of infection. RESULTS: In the vaccinated group, most patients were asymptomatic, with only 42.9 % of patients developing fever. Notably, no patients had extrapulmonary organ damage. In contrast, 21.4 % of patients in the non-vaccinated group developed severe/critical (SC) disease and 78.6 % had mild/moderate (MM) disease, with fever occurring in 74.2 % patients. We found that Omicron infection in COVID-19 vaccinated patients was associated with significantly increased expression of several important host antiviral genes including IL12B, IL13, CXCL11, CXCL9, IFNA2, IFNA1, IFNγ, and TNFα. CONCLUSION: Vaccinated patients infected with the Omicron variant were mostly asymptomatic. In contrast, non-vaccinated patients frequently developed SC or MM disease. Older patients with SC COVID-19 also had a higher occurrence of mild liver dysfunction. Omicron infection in COVID-19 vaccinated patients was associated with the activation of key host antiviral genes and thus may play a role in reducing disease severity.

A Review on Current Nanofiber Technologies: Electrospinning, Centrifugal Spinning, and Electro‐Centrifugal Spinning

Nanofiber‐based products are widely used in the fields of public health, air/water filtration, energy storage, etc. The demand for nonwoven products is rapidly increasing especially after COVID‐19 pandemic. Electrospinning is the most popular technology to produce nanofiber‐based products from various kinds of materials in bench and commercial scales. While centrifugal spinning and electro‐centrifugal spinning are considered to be the other two well‐known technologies to fabricate nanofibers. However, their developments are restricted mainly due to the unnormalized spinning devices and spinning principles. High solution concentration and high production efficiency are the two main strengths of centrifugal spinning, but beaded fibers can be formed easily due to air perturbation or device vibration. Electro‐centrifugal spinning is formed by introducing a high voltage electrostatic field into the centrifugal spinning system, which suppresses the formation of beaded fibers and results in producing elegant nanofibers. It is believed that electrospinning can be replaced by electro‐centrifugal spinning in some specific application areas. This article gives an overview on the existing devices and the crucial processing parameters of these nanofiber technologies, also constructive suggestions are proposed to facilitate the development of centrifugal and electro‐centrifugal spinning.

Effect of polymorphism in Rhinolophus affinis ACE2 on entry of SARS-CoV-2 related bat coronaviruses.

Bat coronavirus RaTG13 shares about 96.2% nucleotide sequence identity with that of SARS-CoV-2 and uses human and Rhinolophus affinis (Ra) angiotensin-converting enzyme 2 (ACE2) as entry receptors. Whether there are bat species other than R. affinis susceptible to RaTG13 infection remains elusive. Here, we show that, among 18 different bat ACE2s tested, only RaACE2 is highly susceptible to transduction by RaTG13 S pseudovirions, indicating that the bat species harboring RaTG13 might be very limited. RaACE2 has seven polymorphic variants, RA-01 to RA-07, and they show different susceptibilities to RaTG13 S pseudovirions transduction. Sequence and mutagenesis analyses reveal that residues 34, 38, and 83 in RaACE2 might play critical roles in interaction with the RaTG13 S protein. Of note, RaACE2 polymorphisms have minimal effect on S proteins of SARS-CoV-2 and several SARS-CoV-2 related CoVs (SC2r-CoVs) including BANAL-20-52 and BANAL-20-236 in terms of binding, membrane fusion, and pseudovirus entry. Further mutagenesis analyses identify residues 501 and 505 in S proteins critical for the recognition of different RaACE2 variants and pangolin ACE2 (pACE2), indicating that RaTG13 might have not been well adapted to R. affinis bats. While single D501N and H505Y changes in RaTG13 S protein significantly enhance the infectivity and minimize the difference in susceptibility among different RaACE2 variants, an N501D substitution in SARS-CoV-2 S protein displays marked disparity in transduction efficiencies among RaACE2 variants with a significant reduction in infectivity on several RaACE2 variants. Finally, a T372A substitution in RaTG13 S protein not only significantly increases infectivity on all RaACE2 variants, but also markedly enhances entry on several bat ACE2s including R. sinicus YN, R. pearsonii, and R. ferrumeiqunum. However, the T372A mutant is about 4-fold more sensitive to neutralizing sera from mice immunized with BANAL-20-52 S, suggesting that the better immune evasion ability of T372 over A372 might contribute to the natural selective advantage of T372 over A372 among bat CoVs. Together, our study aids a better understanding of coronavirus entry, vaccine design, and evolution.

A Review on Current Nanofiber Technologies: Electrospinning, Centrifugal Spinning, and Electro‐Centrifugal Spinning

Nanofiber‐based products are widely used in the fields of public health, air/water filtration, energy storage, etc. The demand for nonwoven products is rapidly increasing especially after COVID‐19 pandemic. Electrospinning is the most popular technology to produce nanofiber‐based products from various kinds of materials in bench and commercial scales. While centrifugal spinning and electro‐centrifugal spinning are considered to be the other two well‐known technologies to fabricate nanofibers. However, their developments are restricted mainly due to the unnormalized spinning devices and spinning principles. High solution concentration and high production efficiency are the two main strengths of centrifugal spinning, but beaded fibers can be formed easily due to air perturbation or device vibration. Electro‐centrifugal spinning is formed by introducing a high voltage electrostatic field into the centrifugal spinning system, which suppresses the formation of beaded fibers and results in producing elegant nanofibers. It is believed that electrospinning can be replaced by electro‐centrifugal spinning in some specific application areas. This article gives an overview on the existing devices and the crucial processing parameters of these nanofiber technologies, also constructive suggestions are proposed to facilitate the development of centrifugal and electro‐centrifugal spinning. [ FROM AUTHOR]

Differentially expressed immune response genes in COVID-19 patients based on disease severity.

BACKGROUND: Dysregulated immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are thought to underlie the progression of coronavirus disease 2019 (COVID-19). We sought to further characterize host antiviral and cytokine gene expression in COVID-19 patients based on illness severity. METHODS: In this case-control study, we retrospectively analyzed 46 recovered COVID-19 patients and 24 healthy subjects (no history of COVID-19) recruited from the Second People's Hospital of Fuyang City. Blood samples were collected from each study participant for RNA extraction and PCR. We assessed changes in antiviral gene expression between healthy controls and patients with mild/moderate (MM) and severe/critical (SC) disease. RESULTS: We found that type I interferon signaling (IFNA2, TLR8, IFNA1, IFNAR1, TLR9, IRF7, ISG15, APOBEC3G, and MX1) and genes encoding proinflammatory cytokines (IL12B, IL15, IL6, IL12A and IL1B) and chemokines (CXCL9, CXCL11 and CXCL10) were upregulated in patients with MM and SC disease. Moreover, we found that IFNA1, apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G (APOBEC3G), and Fas-associated protein with death domain (FADD) were significantly downregulated (P < 0.05) in the SC group compared to the MM group. We also observed that microRNA (miR)-155 and miR-130a levels were markedly higher in the MM group compared to the SC group. CONCLUSION: COVID-19 is associated with the activation of host antiviral genes. Induction of the IFN system appears to be particularly important in controlling SARS-CoV-2 infection, as decreased expression of IFNA1, APOBEC3G and FADD genes in SC patients, relative to MM patients, may be associated with disease progression.

COVID-19 induced liver function abnormality associates with age.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a novel infectious disease that may cause fever, dry cough, fatigue and shortness of breath. The impact of COVID-19 on liver function is not well described. RESULTS: We found that the overall frequency of LFT abnormality was 17.6%. Frequency of LFT abnormality was significantly greater in patients with severe/critical (SC) COVID-19 compared to those with mild/moderate (MM) COVID-19 (32.4% vs 11.6%, p=0.011). Among patients with LFT abnormality, the median age was significantly higher in the SC group compared to the MM group (52 vs 39 years, p=0.021). CONCLUSION: COVID-19 is frequently associated with mild liver function abnormality, particularly in individuals with severe/critical COVID-19 who were older. Liver function should be monitored carefully during infection, with judicious use of hepatotoxic agents where possible and avoidance of prolonged hypotension to minimize liver injury in older patients. METHODS: The No. 2 People's Hospital of Fuyang City in China has admitted a total of 159 patients with confirmed COVID-19 since the outbreak from January 2020 to March 2020. We analyzed the incidence of liver function test (LFT) abnormality in these patients with confirmed COVID-19 infection.

Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score.

BACKGROUND: We aimed to clarify high-risk factors for coronavirus disease 2019 (COVID-19) with multivariate analysis and establish a predictive model of disease progression to help clinicians better choose a therapeutic strategy. METHODS: All consecutive patients with COVID-19 admitted to Fuyang Second People's Hospital or the Fifth Medical Center of Chinese PLA General Hospital between 20 January and 22 February 2020 were enrolled and their clinical data were retrospectively collected. Multivariate Cox regression was used to identify risk factors associated with progression, which were then were incorporated into a nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the model. RESULTS: Overall, 208 patients were divided into a stable group (n = 168, 80.8%) and a progressive group (n = 40,19.2%) based on whether their conditions worsened during hospitalization. Univariate and multivariate analyses showed that comorbidity, older age, lower lymphocyte count, and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of .86 (95% confidence interval [CI], .81-.91) and well-fitted calibration curves. A novel scoring model, named as CALL, was established; its area under the ROC was .91 (95% CI, .86-.94). Using a cutoff of 6 points, the positive and negative predictive values were 50.7% (38.9-62.4%) and 98.5% (94.7-99.8%), respectively. CONCLUSIONS: Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources.