Dynamics of SARS-CoV-2 Antibody Responses up to 9 Months Post-Vaccination in Individuals with Previous SARS-CoV-2 Infection Receiving Inactivated Vaccines.

Humoral immunity confers protection against COVID-19. The longevity of antibody responses after receiving an inactivated vaccine in individuals with previous SARS-CoV-2 infection is unclear. Plasma samples were collected from 58 individuals with previous SARS-CoV-2 infection and 25 healthy donors (HDs) who had been vaccinated with an inactivated vaccine. The neutralizing antibodies (NAbs) and S1 domain-specific antibodies against the SARS-CoV-2 wild-type and Omicron strains and nucleoside protein (NP)-specific antibodies were measured using a chemiluminescent immunoassay. Statistical analysis was performed using clinical variables and antibodies at different timepoints after SARS-CoV-2 vaccination. NAbs targeting the wild-type or Omicron strain were detected in individuals with previous SARS-CoV-2 infection at 12 months after infection (wild-type: 81%, geometric mean (GM): 20.3 AU/mL; Omicron: 44%, GM: 9.4 AU/mL), and vaccination provided further enhancement of these antibody levels (wild-type: 98%, GM: 53.3 AU/mL; Omicron: 75%, GM: 27.8 AU/mL, at 3 months after vaccination), which were significantly higher than those in HDs receiving a third dose of inactivated vaccine (wild-type: 85%, GM: 33.6 AU/mL; Omicron: 45%, GM: 11.5 AU/mL). The level of NAbs in individuals with previous infection plateaued 6 months after vaccination, but the NAb levels in HDs declined continuously. NAb levels in individuals with previous infection at 3 months post-vaccination were strongly correlated with those at 6 months post-vaccination, and weakly correlated with those before vaccination. NAb levels declined substantially in most individuals, and the rate of antibody decay was negatively correlated with the neutrophil-to-lymphocyte ratio in the blood at discharge. These results suggest that the inactivated vaccine induced robust and durable NAb responses in individuals with previous infection up to 9 months after vaccination.

Bring the life stages into the domain of basic and clinical pharmacology.

Completely distinct physiological conditions and immune responses exist among different human life stages. Age is not always consistent with the life stage. We proposed to incorporate the concept of the life stages into basic and clinical pharmacology, including clinical trials, drug labels, and drug usage in clinical practice. Life-stage-based medical treatment is the application of medicine according to life stages such as prepuberty, reproductive, and aging. A large number of diseases are life-stage-dependent. Many medications and therapy have shown various age effects but not been recognized as life-stage-dependent. The same dosage and drug applications used in different life stages lead to divergent outcomes. Incorporating life stages in medicine and drug usage will enhance the efficacy and precision of the medication in disease treatment.

Association between population density and infection rate suggests the importance of social distancing and travel restriction in reducing the COVID-19 pandemic.

Currently, 2019-nCoV has spread to most countries of the world. Understanding the environmental factors that affect the spread of the disease COVID-19 infection is critical to stop the spread of the disease. The purpose of this study is to investigate whether population density is associated with the infection rate of the COVID-19. We collected data from official webpages of cities in China and in the USA. The data were organized on Excel spreadsheets for statistical analyses. We calculated the morbidity and population density of cities and regions in these two countries. We then examined the relationship between morbidity and other factors. Our analysis indicated that the population density in cities in Hubei province where the COVID-19 was severe was associated with a higher percentage of morbidity, with an r value of 0.62. Similarly, in the USA, the density of 51 states and territories is also associated with morbidity from COVID-19 with an r value of 0.55. In contrast, as a control group, there is no association between the morbidity and population density in 33 other regions of China, where the COVID-19 epidemic is well under control. Interestingly, our study also indicated that these associations were not influenced by the first case of COVID-19. The rate of morbidity and the number of days from the first case in the USA have no association, with an r value of - 0.1288. Population density is positively associated with the percentage of patients with COVID-19 infection in the population. Our data support the importance of such as social distancing and travel restriction in the prevention of COVID-19 spread.

Mortality in Four Waves of COVID-19 Is Differently Associated with Healthcare Capacities Affected by Economic Disparities.

BACKGROUND: The greatest challenges are imposed on the overall capacity of disease management when the cases reach the maximum in each wave of the pandemic. METHODS: The cases and deaths for the four waves of COVID-19 in 119 countries and regions (CRs) were collected. We compared the mortality across CRs where populations experience different economic and healthcare disparities. FINDINGS: Among 119 CRs, 117, 112, 111, and 55 have experienced 1, 2, 3, and 4 waves of COVID-19 disease, respectively. The average mortality rates at the disease turning point were 0.036, 0.019. 0.017, and 0.015 for the waves 1, 2, 3, and 4, respectively. Among 49 potential factors, income level, gross national income (GNI) per capita, and school enrollment are positively correlated with the mortality rates in the first wave, but negatively correlated with the rates of the rest of the waves. Their values for the first wave are 0.253, 0.346 and 0.385, respectively. The r value for waves 2, 3, and 4 are -0.310, -0.293, -0.234; -0.263, -0.284, -0.282; and -0.330, -0.394, -0.048, respectively. In high-income CRs, the mortality rates in waves 2 and 3 were 29% and 28% of that in wave 1; while in upper-middle-income CRs, the rates for waves 2 and 3 were 76% and 79% of that in wave 1. The rates in waves 2 and 3 for lower-middle-income countries were 88% and 89% of that in wave 1, and for low-income countries were 135% and 135%. Furthermore, comparison among the largest case numbers through all waves indicated that the mortalities in upper- and lower-middle-income countries is 65% more than that of the high-income countries. INTERPRETATION: Conclusions from the first wave of the COVID-19 pandemic do not apply to the following waves. The clinical outcomes in developing countries become worse along with the expansion of the pandemic.

Acidic preconditioning reduces lipopolysaccharide-induced acute lung injury by upregulating the expression of angiotensin-converting enzyme 2.

Acid preconditioning (APC) through carbon dioxide inhalation can exert protective effects during acute lung injury (ALI) triggered by ischemia-reperfusion. Angiotensin-converting enzyme 2 (ACE2) has been identified as a receptor for severe acute respiratory syndrome coronavirus and the novel coronavirus disease-19. Downregulation of ACE2 plays an important role in the pathogenesis of severe lung failure after viral or bacterial infections. The aim of the present study was to examine the anti-inflammatory mechanism through which APC alleviates lipopolysaccharide (LPS)-induced ALI in vivo and in vitro. The present results demonstrated that LPS significantly downregulated the expression of ACE2, while APC significantly reduced LPS-induced ALI and provided beneficial effects. In addition, bioinformatics analysis indicated that microRNA (miR)-200c-3p directly targeted the 3'untranslated region of ACE2 and regulated the expression of ACE2 protein. LPS exposure inhibited the expression of ACE2 protein in A549 cells by upregulating the levels of miR-200c-3p. However, APC inhibited the upregulation of miR-200c-3p induced by LPS, as well as the downregulation of ACE2 protein, through the NF-κB pathway. In conclusion, although LPS can inhibit the expression of ACE2 by upregulating the levels of miR-200c-3p through the NF-κB pathway, APC inhibited this effect, thus reducing inflammation during LPS-induced ALI.

Capacity of transportation and spread of COVID-19-an ironical fact for developed countries.

The widespread epidemic of the COVID-19 in developed countries such as Europe and the USA has sparked many speculations. What factors caused the rapid early pandemic of the COVID-19 in developed countries is the main goal of this study. We collected the main disease indicators and various environmental and economic factors in 61 countries around the world. Our results show that the number of cases is positively correlated with the country's GDP. We further analyzed the factors related to the spread of the disease. They indicate a strong positive correlation between the total patient numbers and the number of airline passengers, with an r value of 0.80. There is also a positive correlation between the number of car ownership and the total patient, with an r value of 0.35. Both the flight passengers and car ownership contribute 66% to the number of total patients. The total death numbers and the number of airline passengers are positively correlated, with an r value of 0.71. A positive correlation between the number of car ownership and the total deaths is with an r value of 0.42. The total contribution of both the flight passengers and car ownership to the number of total deaths is 57%. Our conclusion is that the main cause of the coronavirus pandemic in developed countries is related to the transportation. In other words, the number of travelers determined the early coronavirus pandemic. Therefore, it is necessary to strengthen restrictions and screening of passengers at airports, especially international airports.

A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy.

The most effective measure to prevent or stop the spread of infectious diseases is the early identification and isolation of infected individuals through comprehensive screening. At present, in the COVID-19 pandemic, such screening is often limited to isolated regions as determined by local governments. Screening of potentially infectious individuals should be conducted through coordinated national or global unified actions. Our current research focuses on using resources to conduct comprehensive national and regional regular testing with a risk rate based, algorithmic guided, multiple-level, pooled testing strategy. Here, combining methodologies with mathematical logistic models, we present an analytic procedure of an overall plan for coordinating state, national, or global testing. The proposed plan includes three parts 1) organization, resource allocation, and distribution; 2) screening based on different risk levels and business types; and 3) algorithm guided, multiple level, continuously screening the entire population in a region. This strategy will overcome the false positive and negative results in the polymerase chain reaction (PCR) test and missing samples during initial tests. Based on our proposed protocol, the population screening of 300,000,000 in the US can be done weekly with between 15,000,000 and 6,000,000 test kits. The strategy can be used for population screening for current COVID-19 and any future severe infectious disease when drugs or vaccines are not available.