The nano delivery systems and applications of mRNA.

The current COVID-19 epidemic has greatly accelerated the application of mRNA technology to our real world, and during this battle mRNA has proven it's unique advantages compared to traditional biopharmaceutical and vaccine technology. In order to overcome mRNA instability in human physiological environments, mRNA chemical modifications and nano delivery systems are two key factors for their in vivo applications. In this review, we would like to summarize the challenges for clinical translation of mRNA-based therapeutics, with an emphasis on recent advances in innovative materials and delivery strategies. The nano delivery systems include lipid delivery systems (lipid nanoparticles and liposomes), polymer complexes, micelles, cationic peptides and so on. The similarities and differences of lipid nanoparticles and liposomes are also discussed. In addition, this review also present the applications of mRNA to other areas than COVID-19 vaccine, such as infectious diseases, tumors, and cardiovascular disease, for which a variety of candidate vaccines or drugs have entered clinical trials. Furthermore, mRNA was found that it might be used to treat some genetic disease, overcome the immaturity of the immune system due to the small fetal size in utero, treat some neurological diseases that are difficult to be treated surgically, even be used in advancing the translation of iPSC technology et al. In short, mRNA has a wide range of applications, and its era has just begun.

Spatio-temporal distribution characteristics of COVID-19 in China: a city-level modeling study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China. OBJECTIVE: To analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China. METHODS: A spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space-time scan statistic were conducted. RESULTS: The high incidence stage of China's COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran's I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China. CONCLUSIONS: Spatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.

Dynamic landscape mapping of humoral immunity to SARS-CoV-2 identifies non-structural protein antibodies associated with the survival of critical COVID-19 patients.

A comprehensive analysis of the humoral immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential in understanding COVID-19 pathogenesis and developing antibody-based diagnostics and therapy. In this work, we performed a longitudinal analysis of antibody responses to SARS-CoV-2 proteins in 104 serum samples from 49 critical COVID-19 patients using a peptide-based SARS-CoV-2 proteome microarray. Our data show that the binding epitopes of IgM and IgG antibodies differ across SARS-CoV-2 proteins and even within the same protein. Moreover, most IgM and IgG epitopes are located within nonstructural proteins (nsps), which are critical in inactivating the host's innate immune response and enabling SARS-CoV-2 replication, transcription, and polyprotein processing. IgM antibodies are associated with a good prognosis and target nsp3 and nsp5 proteases, whereas IgG antibodies are associated with high mortality and target structural proteins (Nucleocapsid, Spike, ORF3a). The epitopes targeted by antibodies in patients with a high mortality rate were further validated using an independent serum cohort (n = 56) and using global correlation mapping analysis with the clinical variables that are associated with COVID-19 severity. Our data provide fundamental insight into humoral immunity during SARS-CoV-2 infection. SARS-CoV-2 immunogenic epitopes identified in this work could also help direct antibody-based COVID-19 treatment and triage patients.

Detection of SARS-CoV-2 in fecal samples with different pretreatment methods and PCR kits.

BACKGROUND: Gastrointestinal symptoms are common in COVID-19 patients and SARS-CoV-2 RNA has been detected in the patients' feces, which could lead to fecal-oral transmission. Therefore, fecal sample testing with real-time RT-PCR is highly recommended as a routine test for SARS-CoV-2 infection. However, varying rates of detection in fecal sample have been reported. The aim of this study was to provide insights into the detection rates of SARS-CoV-2 in COVID-19 patients' fecal sample by using four real-time RT-PCR kits and two pretreatment methods (inactive and non-inactive). RESULTS: The detection rate of Trizol pretreatment group was slightly higher than that of Phosphate Buffered Saline (PBS) groups, showing that pretreatment and inactivation by Trizol had no influence to SARS-CoV-2 nucleic acid test (NAT) results. 39.29% detection rate in fecal sample by DAAN was obtained, while Bio-germ was 40.48%, Sansure 34.52%, and GeneoDx 33.33%. The former three kits had no significant difference. The DAAN kit detection rates of ORF1ab and N gene were nearly equal and Ct value distribution was more scattered, while the Bio-germ kit distribution was more clustered. The positive rate of SARS-COV-2 in fecal samples correlated with the severity of the disease, specifically, severe cases were less likely to be identified than asymptomatic infection in the DAAN group (adjusted OR 0.05, 95%CI = 0.00 ~ 0.91). CONCLUSIONS: Trizol should be of choice as a valid and safe method for pretreatment of fecal samples of SARS-CoV-2. All real-time RT-PCR kits assessed in this study can be used for routine detection of SARS-CoV-2 in fecal samples. While DAAN, with high NAT positive rate, could be the best out of the 4 kits used in this study. SARS-CoV-2 positive rate in fecal sample was related to the severity of illness.

Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China.

COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54-0.84) and 0.25 (95% CI: 0.13-0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors.

[Biological Product Development Strategies for Prevention and Treatment of Coronavirus Disease 2019].

Coronavirus disease 2019 (COVID-19) caused by the novel coronavirus, also known as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), has become a Public Health Emergency of International Concern. Due to the large infection population, broad transmissibility and high mortality, it is urgent to find out the efficient and specific methods to prevent and treat COVID-19. As biological products have broadly applied in the prevention and treatment of severe epidemic diseases, they are promising in blocking novel coronavirus infection. According to the research advances of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), we reviewed the potential application of biological products such as interferon, convalescent plasma, intestinal micro-ecological regulators, vaccines and therapeutic antibodies, etc. , on prevention and treatment of COVID-19. May this review be helpful for conquering COVID-19 in the near future.