Kappa-RBD produced by glycoengineered Pichia pastoris elicited high neutralizing antibody titers against pseudoviruses of SARS-CoV-2 variants.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) kappa (B.1.617.1) variant represented the main variant of concern (VOC) for the epidemic in India in May 2021. We have previously established a technology platform for rapidly preparing SARS-CoV-2 receptor-binding domain (RBD) candidate vaccines based on glycoengineered Pichia pastoris. Our previous study revealed that the wild-type RBD (WT-RBD) formulated with aluminum hydroxide and CpG 2006 adjuvant effectively induces neutralizing antibodies in BALB/c mice. In the present study, a glycoengineered P. pastoris expression system was used to prepare recombinant kappa-RBD candidate vaccine. Kappa-RBD formulated with CpG and alum induced BALB/c mice to produce a potent antigen-specific antibody response and neutralizing antibody titers against pseudoviruses of SARS-CoV-2 kappa, delta, lambda, beta, and omicron variants and WT. Therefore, the recombinant kappa-RBD vaccine has sufficient potency to be a promising COVID-19 vaccine candidate.

Distribution, Progression, and Associated Factors of Refractive Status of Children in Lhasa, Tibet, after COVID-19 Quarantine.

INTRODUCTION: Uncorrected refractive error is one of the major causes of visual impairment in children and adolescents worldwide. During the COVID-19 epidemic, home isolation is considered a boost to the progression of children's myopia. Under geographical conditions of high altitude and strong sunshine, the Tibetan plateau is the main residence of the Tibetan population, where little information is available about the refractive status and developmental trajectory. Therefore, this article aimed to evaluate the distribution, progression, and associated factors of the refractive status in second-grade children in Lhasa after COVID-19 quarantine. MATERIALS AND METHODS: Students from 7 elementary schools completed comprehensive ocular examinations in the Lhasa Childhood Eye Study. Data regarding cycloplegic refraction and corneal biometry parameters, including axial length (AL), corneal power, anterior chamber depth (ACD), and other demographic factors, were analyzed. RESULTS: A total of 1,819 students were included, with a mean age of 7.9 ± 0.5 years, of which 961 were boys (52.8%), and 95.1% were Tibetan. The prevalence of myopia, emmetropia, mild hyperopia, and hyperopia was 10.94%, 24.02%, 60.80%, and 4.24%, respectively. Besides, the average cycloplegic spherical equivalent refraction (SER) was +1.07 ± 0.92 diopter (D) before the COVID-19 quarantine and +0.59 ± 1.08D after the quarantine (p < 0.05), with a growth rate of 7%. Moreover, the prevalence of hyperopia in girls was significantly higher than that of boys (p < 0.001). Nonetheless, the proportion of myopia and emmetropia was similar (p = 0.75). Meanwhile, children in suburban schools had a significantly lower proportion of myopia (p < 0.001). The average AL, ACD, lens power (LP), and AL-to-corneal radius (AL/CR) ratio were 22.79 ± 0.78 mm, 3.54 ± 0.21 mm, 25.12 ± 1.48D, and 2.93 ± 0.08, respectively. The results of AL, ACD, and AL/CR for girls were significantly lower than for boys, while the result of LP is the opposite (p < 0.001). Finally, multivariate regression analysis revealed that SER was negatively correlated with AL, LP, and AL/CR ratio, while positively correlated with CR and ACD (p < 0.001). CONCLUSION: This study found that after the COVID-19 confinement, myopia progressed faster in Lhasa children but was still significantly lower than that of plain cities in China. Compared to short-term confinement, this acceleration was more likely related to the growth and general trend of myopia in children. Collectively, these findings help to explore the differences in ocular growth and development among children of different ethnic groups.

Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models.

In December 2019, the novel coronavirus pneumonia (COVID-19) occurred in Wuhan, Hubei Province, China. The epidemic quickly broke out and spread throughout the country. Now it becomes a pandemic that affects the whole world. In this study, three models were used to fit and predict the epidemic situation in China: a modified SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) dynamic model, a neural network method LSTM (Long Short-Term Memory), and a GWR (Geographically Weighted Regression) model reflecting spatial heterogeneity. Overall, all the three models performed well with great accuracy. The dynamic SEIRD prediction APE (absolute percent error) of China had been ≤ 1.0% since Mid-February. The LSTM model showed comparable accuracy. The GWR model took into account the influence of geographical differences, with R2 = 99.98% in fitting and 97.95% in prediction. Wilcoxon test showed that none of the three models outperformed the other two at the significance level of 0.05. The parametric analysis of the infectious rate and recovery rate demonstrated that China's national policies had effectively slowed down the spread of the epidemic. Furthermore, the models in this study provided a wide range of implications for other countries to predict the short-term and long-term trend of COVID-19, and to evaluate the intensity and effect of their interventions.