Potent immunogenicity and broad-spectrum protection potential of microneedle array patch-based COVID-19 DNA vaccine candidates encoding dimeric RBD chimera of SARS-CoV and SARS-CoV-2 variants.

Breakthrough infections by SARS-CoV-2 variants pose a global challenge to COVID-19 pandemic control, and the development of more effective vaccines of broad-spectrum protection is needed. In this study, we constructed pVAX1-based plasmids encoding receptor-binding domain (RBD) chimera of SARS-CoV-1 and SARS-CoV-2 variants, including pAD1002 (encoding RBDSARS/BA1), pAD1003 (encoding RBDSARS/Beta) and pAD131 (encoding RBDBA1/Beta). Plasmids pAD1002 and pAD131 were far more immunogenic than pAD1003 in terms of eliciting RBD-specific IgG when intramuscularly administered without electroporation. Furthermore, dissolvable microneedle array patches (MAP) greatly enhanced the immunogenicity of these DNA constructs in mice and rabbits. MAP laden with pAD1002 (MAP-1002) significantly outperformed inactivated SARS-CoV-2 virus vaccine in inducing RBD-specific IFN-γ+ effector and memory T cells, and generated T lymphocytes of different homing patterns compared to that induced by electroporated DNA in mice. In consistence with the high titer neutralization results of MAP-1002 antisera against SARS-CoV-2 pseudoviruses, MAP-1002 protected human ACE2-transgenic mice from Omicron BA.1 challenge. Collectively, MAP-based DNA constructs encoding chimeric RBDs of SARS-CoV-1 and SARS-CoV-2 variants, as represented by MAP-1002, are potential COVID-19 vaccine candidates worthy further translational study.

A COVID-19 DNA Vaccine Candidate Elicits Broadly Neutralizing Antibodies against Multiple SARS-CoV-2 Variants including the Currently Circulating Omicron BA.5, BF.7, BQ.1 and XBB.

Waves of breakthrough infections by SARS-CoV-2 Omicron subvariants currently pose a global challenge to the control of the COVID-19 pandemic. We previously reported a pVAX1-based DNA vaccine candidate, pAD1002, that encodes a receptor-binding domain (RBD) chimera of SARS-CoV-1 and Omicron BA.1. In mouse and rabbit models, pAD1002 plasmid induced cross-neutralizing Abs against heterologous sarbecoviruses, including SARS-CoV-1 and SARS-CoV-2 wildtype, Delta and Omicron variants. However, these antisera failed to block the recent emerging Omicron subvariants BF.7 and BQ.1. To solve this problem, we replaced the BA.1 RBD-encoding DNA sequence in pAD1002 with that of BA.4/5. The resulting construct, namely pAD1016, elicited SARS-CoV-1 and SARS-CoV-2 RBD-specific IFN-γ+ cellular responses in BALB/c and C57BL/6 mice. More importantly, pAD1016 vaccination in mice, rabbits and pigs generated serum Abs capable of neutralizing pseudoviruses representing multiple SARS-CoV-2 Omicron subvariants including BA.2, BA.4/5, BF.7, BQ.1 and XBB. As a booster vaccine for inactivated SARS-CoV-2 virus preimmunization in mice, pAD1016 broadened the serum Ab neutralization spectrum to cover the Omicron BA.4/5, BF7 and BQ.1 subvariants. These preliminary data highlight the potential benefit of pAD1016 in eliciting neutralizing Abs against broad-spectrum Omicron subvariants in individuals previously vaccinated with inactivated prototype SARS-CoV-2 virus and suggests that pAD1016 is worthy of further translational study as a COVID-19 vaccine candidate.

Effects of COVID-19 Control Measures on the Concentration and Composition of PM2.5-Bound Polycyclic Aromatic Hydrocarbons in Shanghai

In order to explore the effects of COVID-19 control measures on the concentration and composition of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs), and to better understand the sources of PM2.5-bound PAHs, PM2.5, samples were collected at two sites in urban and suburban areas of Shanghai before the lockdown, during the lockdown, after the lockdown in 2020, and during the same periods in 2019. The mass concentrations of 21 individual PAHs were determined via GC-MS analysis. While the COVID-19 control measures significantly reduced the absolute concentration of PM2.5-bound PAHs, they had no significant effect on their relative abundances, indicating that the significantly reduced traffic emission may not originally be the major source of PAHs in Shanghai. The differences in the composition of PM2.5-bound PAHs at three different lockdown-related periods may be caused by the gas-particle distribution of semi-volatile PAHs. The similarity in the composition of PM2.5-bound PAHs in different functional areas and different periods brings more uncertainties to the identification of PAH sources using the diagnostic ratios. During the lockdown period, the toxic equivalent concentration of PM2.5-bound PAHs in Shanghai was estimated to decrease by about 1/4, which still exhibits substantial carcinogenic risk upon exposure via inhalation.

Investigation of the Impacts of COVID-19 on the Electricity Consumption of a University Dormitory Using Weather Normalization (preprint)

This study investigated the impacts of the COVID-19 pandemic on the electricity consumption of a university dormitory building in the southern U.S. The historical electricity consumption data of this university dormitory building and weather data of an on-campus weather station, which were collected from January 1st, 2017 to July 31st, 2020, were used for analysis. Four inverse data-driven prediction models, i.e., Artificial Neural Network, Long Short-Term Memory Recurrent Neural Network, eXtreme Gradient Boosting, and Light Gradient Boosting Machine, were exploited to account for the influence of the weather conditions. The results suggested that the total electricity consumption of the objective building decreased by nearly 41% (about 276,000 kWh (942 MMBtu)) compared with the prediction value during the campus shutdown due to the COVID-19. Besides, the daily load ratio (DLR) varied significantly as well. In general, the DLR decreased gradually from 80% to nearly 40% in the second half of March 2020, maintained on a relatively stable level between 30% to 60% in April, May, and June 2020, and then slowly recovered to 80% of the normal capacity in July 2020.

Immune phenotyping based on neutrophil-to-lymphocyte ratio and IgG predicts disease severity and outcome for patients with COVID-19 (preprint)

Background: A recently emerging respiratory disease named coronavirus disease 2019 (COVID-19) has quickly spread across the world. This disease is initiated by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and uncontrolled cytokine storm, but it remains unknown as to whether a robust antibody response is related to clinical deterioration and poor outcome in laboratory-confirmed COVID-19 patients. Methods: Anti-SARS-CoV-2 IgG and IgM antibodies were determined by chemiluminescence analysis (CLIA) in COVID-19 patients from a single center in Wuhan. Median IgG and IgM levels in acute and convalescent-phase sera (within 35 days) for all included patients were calculated and compared among severe and nonsevere patients. Immune response phenotyping based on late IgG levels and neutrophil-to-lymphocyte ratio (NLR) was characterized to stratify patients with different disease severities and outcome. Laboratory parameters in patients with different immune response phenotypes and disease severities were analyzed. Findings: A total of 222 patients were included in this study. IgG was first detected on day 4 of illness, and its peak levels occurred in the fourth week. Severe cases were more frequently found in patients with high IgG levels, compared to those who with low IgG levels (51.8% versus 32.3%; p=0.008). Severity rates for patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 72.3%, 48.5%, 33.3%, and 15.6%, respectively (p<0.0001). Furthermore, severe patients with NLRhiIgGhi, NLRhiIgGlo had higher proinflammatory cytokines levels including IL-2, IL-6 and IL-10, and decreased CD4+ T cell count compared to those with NLRloIgGlo phenotype (p<0.05). Recovery rate for severe patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 58.8% (20/34), 68.8% (11/16), 80.0% (4/5), and 100% (12/12), respectively (p=0.0592). Dead cases only occurred in NLRhiIgGhi and NLRhiIgGlo phenotypes. Interpretation: COVID-19 severity is associated with increased IgG response, and an immune response phenotyping based on late IgG response and NLR could act as a simple complementary tool to discriminate between severe and nonsevere COVID-19 patients, and further predict their clinical outcome.

Clinical characteristics of 82 death cases with COVID-19 (preprint)

Background A recently developing pneumonia caused by SARS-CoV-2 was originated in Wuhan, China, and has quickly spread across the world. We reported the clinical characteristics of 82 death cases with COVID-19 in a single center. Methods Clinical data on 82 death cases laboratory-confirmed as SARS-CoV-2 infection were obtained from a Wuhan local hospital's electronic medical records according to previously designed standardized data collection forms. Findings All patients were local residents of Wuhan, and the great proportion of them were diagnosed as severe illness when admitted. Most of the death cases were male (65.9%). More than half of dead patients were older than 60 years (80.5%) and the median age was 72.5 years. The bulk of death cases had comorbidity (76.8%), including hypertension (56.1%), heart disease (20.7%), diabetes (18.3%), cerebrovascular disease (12.2%), and cancer (7.3%). Respiratory failure remained the leading cause of death (69.5%), following by sepsis syndrome/MOF (28.0%), cardiac failure (14.6%), hemorrhage (6.1%), and renal failure (3.7%). Furthermore, respiratory, cardiac, hemorrhage, hepatic, and renal damage were found in 100%, 89%, 80.5%, 78.0%, and 31.7% of patients, respectively. On the admission, lymphopenia (89.2%), neutrophilia (74.3%), and thrombocytopenia (24.3%) were usually observed. Most patients had a high neutrophil-to-lymphocyte ratio of >5 (94.5%), high systemic immune-inflammation index of >500 (89.2%), increased C-reactive protein level (100%), lactate dehydrogenase (93.2%), and D-dimer (97.1%). A high level of IL-6 (>10 pg/ml) was observed in all detected patients. Median time from initial symptom to death was 15 days (IQR 11-20), and a significant association between aspartate aminotransferase (p=0.002), alanine aminotransferase (p=0.037) and time from initial symptom to death were interestingly observed. Conclusion Older males with comorbidities are more likely to develop severe disease, even die from SARS-CoV-2 infection. Respiratory failure is the main cause of COVID-19, but either virus itself or cytokine release storm mediated damage to other organ including cardiac, renal, hepatic, and hemorrhage should be taken seriously as well.