Journal articles on the topic 'China. Cai zheng bu'

The contradictory role of eunuchs in ancient China has remained a long-term debate in history. Often viewed as either holy or profane, eunuchs occupied a unique space in society that defied easy categorization. This study challenges the prevailing negative perception of eunuchs in ancient dynastical China by re-examining historical records and highlighting their positive contributions to society. The historical portrayal of eunuchs as wicked and cunning individuals has been heavily influenced by Chinese literati who sought to defame their rivals in order to gain political influence. Eunuchs, who played crucial roles in the imperial court, have had a significant impact on China’s development both positively and negatively. By focusing on notable eunuchs such as Zheng He, Cai Lun, and Sima Qian, this paper demonstrates that their contributions to Chinese culture, technological advancement, and historical documentation significantly outweigh the harm caused by a few power-hungry individuals. Ultimately, the paper calls for a more nuanced understanding of eunuchs’ roles in ancient Chinese society and their impact on the country’s development.

A new species of the family Lyctocoridae, Lyctocoris ichikawai Yamada & Yasunaga sp. nov., is described from Shikoku and Kyushu, southwestern Japan. The species was found to inhabit near the sap-exuding parts on the trunk of Sawtooth Oak, Quercus acutissima Carruth. (Fagaceae). Lyctocoris ichikawai is considered to be most closely related to L. zhangi Bu & Zheng, 2001 from continental China and L. variegatus Péricart, 1969 from the Caucasus. The unique biology of the new species, including its habitat use, feeding activities, and phenology, is documented and discussed. A key is provided to distinguish among the three Japanese species of Lyctocoris.

Abstract Turkic conquest and rule of China since 386 CE for nearly two hundred years had exerted its profound and long-lasting influence on many levels of Chinese society. Turkic sinification policy had induced the Xianbei National Language (XNL), which was Turkic language with selected set of Chinese characters for phonetic spelling. XNL, being spelt in Chinese characters, managed to function in Turkic-Chinese code-mixing in the bilingual communities as evidenced in bianwen 變文. Because of the Turkic politico-socio-economical dominance, some the Turkic elements in the code-mixing eventually gained prominance and have become permanent part of the northern vernacular, predecessor of modern Mandarin. This paper discusses twelve such Turkic-rooted verbal functional expressions: (1). The causative-passive qu 取; (2). Transitive passive sha 殺, sha 煞, si 死; (3). Causative dou 鬥, dou 逗; (4). Continuative hai 還, que 卻; (5). Resultative que 卻; (6). Reflexive nə 呢 (7). Positive indirective mo shi 莫是; (8). Negative indirective bu dao 不道; (9). Future participle cai 才, cai 纔; (10). Conditional yao shi 要是, yao 要, yao bu shi 要不是; (11). INDUCE-base nong 弄; (12). The speech quote verb dao 道.

The Muslim Calendar spread into China in 1385 where it was immediately translated into Chinese by the astronomer Yuan Tong and came into use. In 1477, it was further translated by the astronomer Bei Lin and compiled into the “Qi Zheng Tui Bu”, a work more or less the same in substance with the Muslim Calendar recorded in the “Ming Shi Li Zhi”, both being works of the same source. They left for us the valuable data of the results of research of ancient Arabian astronomers.On different occasions in the Muslim Calendar, values different with one another are used for the same kind of data. In that case, which of them are used for them are accurate values surveyed and calculated by people who originally worked out the Muslim Calendar? And how are these values calculated from data now available?

Abstract Pancreatic cancer is a malignant tumor with high incidence and mortality. It is difficult to diagnose and detect in the early stage, with low surgical resection rate and high recurrence and metastasis rate after surgery. At present, the clinical therapeutic strategy is extremely limited. The first-line Standard of Care (SOC) for unresectable pancreatic cancer is chemotherapy. The preferred regimen includes gemcitabine combined with albumin paclitaxel or FOLFIRINOX (5-FU+Oxaliplatin+Irinotecan). Due to the limited long-term benefits and toxic side effects of chemotherapy, targeted therapy combined with chemotherapy has become a new therapeutic strategy. MUC1 is a highly glycosylated transmembrane mucin located on the lumen surface of epithelial cells. It can protect cells from extreme factors and plays an important role in tumor cell metabolism, apoptosis, epithelial-mesenchymal transition (EMT) and metastasis. Previous studies have confirmed that MUC1 is highly expressed in a variety of tumors, including pancreatic cancer, and is closely related to poor prognosis. DXC005 is a novel MUC1-targeting antibody-drug conjugate (ADC), generated by conjugating a Tubulysin B analogue to a recombinant humanized anti-Muc1 monoclonal antibody. DXC005 is the first MUC1-ADC IND in China, and is currently in phase I clinical trials. Preclinical studies have confirmed the efficacy of DXC005 monotherapy (2.5 mg/kg, 5 mg/kg, 10 mg/kg in one administration) in the HuPrime ® pancreatic cancer PDX model (PA1194). The tumor growth inhibition (TGI) was 42.53 %, 70.77 %, and 95.58 %, respectively. We want to further clarify whether DXC005 combined with chemotherapeutic drug Gemcitabine can ensure or even improve the efficacy while reducing the dosage of Gemcitabine. In PA1194 xenograft model, DXC005 (3 mg/kg or 6 mg/kg) in combination with Gemcitabine (10 mg/kg) showed significant anti-tumor efficacy with 58.77% and 93.17% TGIs, respectively. In contrast, the treatment with 10 mg/kg of Gemcitabine alone exhibited much less TGI. Furthermore, complete response (CR) was observed in some animals after treatment with DXC005 (6 mg/kg) plus Gemcitabine (10 mg/kg). All groups of treatment are tolerated well, no abnormal animal behavior and body weight loss were observed in the study. The above results concluded that DXC005 combined with Gemcitabine can achieve synergistic effect even with reduced dose of Gemcitabine, which will serve as a support for synergistic application in clinical studies. Citation Format: Xiaobo Cai, Min Cao, Huihui Guo, Qingliang Yang, Yongxiang Chen, Xiangfei Kong, Yong Du, Zhicang Ye, Zhixiang Guo, Lingli Zhang, Lu Bai, Junxiang Jia, Yunxia Zheng, Wei Zheng, Jun Zheng, Wenjun Li, Yuanyuan Huang, Zhongliang Fan, Binbin Chen, Yanlei Yang, Meng Dai, Robert Y. Zhao. A MUC1 antibody-conjugated with a tubulysin B analog, DXC005, demonstrates excellent synergistic effect in combination with gemcitabine for treatment of pancreatic tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1883.

Abstract Background: The etiology of lung cancer among never-smokers is unclear despite 15% of cases in men and 53% in women worldwide are not smoking-related. Metabolomics provides a snapshot of dynamic biochemical activities, including those found to be driving tumor formation and progression. This study used untargeted metabolomics with network analysis to agnostically identify network modules and independent metabolites in pre-diagnostic blood samples among never-smokers to further understand the pathogenesis of lung cancer. Methods: Within the prospective Shanghai Women’s Health Study, we conducted a nested case-control study of 395 never-smoking incident lung cancer cases and 395 never-smoking controls matched on age. We performed liquid chromatography high-resolution mass spectrometry to quantify 20,348 unique metabolic features in plasma. Because metabolic features are expected to be highly correlated and more likely to be involved in biological processes as a network of intertwined features than individually, we agnostically constructed 28 network modules using a weighted correlation network analysis approach. The associations between metabolite network modules and individual metabolites with lung cancer were assessed using conditional logistic regression models, adjusting for age, body mass index, and exposure to environmental tobacco smoke. We accounted for multiple testing using a false discovery rate (FDR) < 0.20. Results: We identified a network module of 122 metabolic features enriched in lysophosphatidylethanolamines that was associated with all lung cancer combined (p = 0.001, FDR = 0.028) and lung adenocarcinoma (p = 0.002, FDR = 0.056) and another network module of 440 metabolic features that was associated with lung adenocarcinoma (p = 0.014, FDR = 0.196). Metabolic features were enriched in pathways associated with cell growth and proliferation, including oxidative stress, bile acid biosynthesis, and metabolism of nucleic acids, carbohydrates, and amino acids, including 1-carbon compounds. Conclusions: Our prospective study suggests that untargeted plasma metabolomics in pre-diagnostic samples could provide new insights into the etiology of lung cancer in never-smokers. Replication and further characterization of these associations are warranted. Citation Format: Mohammad L. Rahman, Xiao-Ou Shu, Douglas Walker, Dean P. Jones, Wei Hu, Bu-tian Ji, Batel Blechter, Jason YY Wong, Qiuyin Cai, Gong Yang, Tu-Tang Gao, Wei Zheng, Nathaniel Rothman, Qing Lan. A nested case-control study of untargeted plasma metabolomics and lung cancer risk among never-smoking women in the prospective Shanghai Women’s Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6056.

Abstract Background: The etiology of lung cancer among never-smokers has not been adequately elucidated despite that globally15% of lung cancer cases in men and 53% in women are not smoking-related. Epigenetic modifications, including changes in DNA methylation (DNAm), have been suggested as possible underlying mechanisms. However, only a few prospective epigenome-wide association studies (EWAS) of lung cancer incidence have been conducted, all exclusively focused on DNAm in peripheral blood cells and included a minimal number of never-smokers. We aimed to investigate genome-wide DNAm associations and epigenetic age acceleration with future risk of lung cancer among never-smokers using pre-diagnostic oral rinse samples. Methods: We conducted a case-control study of 80 never-smoking incident lung cancer cases and 83 comparable never-smoking controls nested in two large prospective cohorts: the Shanghai Women’s Health Study and Shanghai Men’s Health Study. DNAm was measured using the Illumina EPIC array. The top 50 differentially methylated positions (DMPs) were identified from a discovery sample and tested for replication in a validation sample using robust linear regression models. We also conducted an EWAS in the pooled sample. We examined functional overlap enrichment across chromatin states and histone mark broadPeaks for the top 1000 DMPs using eFORGE and constructed enrichment biological pathways analyses. Results: Across discovery and pooled EWAS, we identified four DMPs associated with lung cancer at the epigenome-wide significance level of P<8.0x10-8 (cg01411366: SLC9A10, P=7.23x10-08; cg00811020: NAA30, P=3.95x10-08; cg05658193: EIF2A, SERP1, P=5.02x10-08; and cg09198866: unannotated, P=5.39x10-09). The top 1000 DMPs were significantly enriched in epithelial regulatory regions and were associated with small GTPase-mediated signal transduction pathways. Furthermore, epigenetic age acceleration, measured by the GrimAge clock was prospectively associated with an increased risk of lung cancer (OR=1.19 per year of acceleration; 95% CI: 1.06-1.34) in logistic regression models. Conclusions: To our knowledge, this is the first prospective EWAS of lung cancer among never-smokers using oral rinse samples. Our results show that DNAm in pre-diagnostic oral rinse samples can provide new insights into lung cancer etiology and risk factors. Citation Format: Mohammad L. Rahman, Charles E. Breeze, Xiao-Ou Shu, Jason YY Wong, Andres Cardenas, Xuting Wang, Bu-Tian Ji, Wei Hu, Batel Blechter, Qiuyin Cai, H Dean Hosgood, Gong Yang, Jianxin Shi, Jirong Long, Yu-Tang Gao, Douglas Bell, Wei Zheng, Qing Lan, Nathaniel Rothman. Epigenome-wide association study of lung cancer among never-smokers in two prospective cohorts in Shanghai [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3483.

Abstract Background: The majority of female lung cancer cases in Asia are never-smokers with distinct risk factor profiles. Given the high burden of disease in this population, there is an increasing need to improve the understanding of lung cancer. Current risk models for lung cancer focus on active smokers and individuals of European ancestry. Therefore, we developed statistical models by integrating genetic and environmental risk factors to estimate absolute and population attribute risk of lung cancer among never-smoking women in Asia. Methods: We built absolute risk models for lung cancer among never-smoking women using data from 71,300 women (760 incident cases) in the Shanghai Women’s Health Study (SWHS), a population-based prospective cohort study. Relative risks were estimated using a multivariable Cox regression model with questionnaire-based risk factors. To account for missing genetic data for some subjects, we simulated genotypes for 10 common single nucleotide polymorphisms (SNP) using information on minor allele frequencies (MAF) and odds ratio estimates from previous genome-wide association studies (GWAS), conditional on family history of lung cancer. We used the iCARE tool to build two models for predicting lifetime (40 years) and 6-year absolute risk of lung cancer using age-specific lung cancer incidence rates, age-specific competing mortality rates, and risk factor distribution with: 1) questionnaire-based risk factors only and 2) questionnaire and genetic data. We then used the full absolute risk model to estimate the population attributable risk (PAR) due to modifiable risk factors, namely coal use and exposure to environmental tobacco smoke (ETS). Results: The questionnaire-based only model included family history of lung cancer, coal use, exposure to ETS, and body mass index (BMI). The full model also included data on 10 lung cancer related SNPs from our previous GWAS and had a wider spread in distribution of absolute lifetime risk (median=2.41%; range=0.43-12.36) compared to the questionnaire-based only model (median=2.72%; range=1.93-4.87). We used the full model to estimate the PAR and found that 1.74% and 6.33% of lung cancer cases could be prevented if never-smoking women in Shanghai did not use coal and were not exposed to ETS, respectively. Furthermore, we found that the full model estimated that 2.5% of the study population had a 6-year absolute risk of lung cancer higher than 1.51%, which is the suggested risk threshold for screening by existing risk models. Conclusion: We built risk models for never-smoking Asian women and estimated the contribution of coal use and ETS to the burden of lung cancer in Shanghai. This initial work shows promise for expanding and validating risk models in this population with potential translational implications, such as providing insight to identifying high risk individuals that may be eligible for lung cancer screening and primary prevention efforts. Citation Format: Batel Blechter, Parichoy Pal Choudhury, Xiao-ou Shu, Wei Zheng, Qiuyin Cai, Gong Yang, Jason Y.Y. Wong, Bu-Tian Ji, Wei Hu, Anne Rositch, Nilanjan Chatterjee, Nathaniel Rothman, Qing Lan. Risk models for lung cancer in never-smoking women in Shanghai with implications for screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2254.

BackgroundThe COVID-19 pandemic continues worldwide and has had a strong impact on public health. As the pandemic evolves, efforts have been intensified to identify persistent symptoms associated with the infection once resolved have intensified.ObjectivesWe aimed to describe persistent symptoms and sequelae in patients with rheumatic and musculoskeletal diseases (RMD) after admission due to Covid-19. We also compared the role of autoimmune rheumatic diseases (ARD) with that of non–autoimmune rheumatic and musculoskeletal diseases (NARD) in persistent symptoms and sequelae.MethodsWe performed an observational study of patients with RMD who attended a rheumatology outpatient clinic in Madrid and required admission to hospital due to Covid-19 (1st March-30th May 2020) and survived. The study began at discharge and ran until 1st October 2020. The main outcomes were persistence of symptoms and sequelae related to Covid19. The independent variable was the RMD group (ARD and NARD). The covariates were sociodemographic data, clinical findings, and treatment. We ran a multivariate logistic regression model to assess the risk of the main outcomes by RMD group.ResultsWe included 105 patients, of whom 51.5% had ARD and 68.57% reported at least 1 persistent symptom. The most frequent were dyspnea, fatigue, and chest pain. Sequelae were recorded in 31 patients. These included lung damage in 10.4% of patients, lymphopenia in 10%, central retinal vein occlusion (1 patient), and optic neuritis (1 patient). Two patients died. Eleven patients required readmission owing to Covid-19 problems (16.7% ARD vs 3.9% NARD; p=0.053). No statistically significant differences were found between RMD groups in the final models.ConclusionMany RMD patients have persistent symptoms, as in other populations. Lung damage is the most frequent sequela. Compared to NARD patients, ARD patients do not seem to differ in terms of persistent symptoms or sequelae, although ARD patients might generate more readmissions due to Covid-19.References[1]Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020;81(2):e16–25[2]Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA -J Am Med Assoc. 2020;323(11):1061–9[3]Jiang F, Deng L, Zhang L, Cai Y, Cheung CW, Xia Z. Review of the Clinical Characteristics of Coronavirus Disease 2019 (COVID-19). J Gen Intern Med. 2020;35(5):1545–9.[4]Sung HK, Kim JY, Heo J, Seo H, Jang Y, Kim H, et al. Clinical Course and Outcomes of 3, 060 Patients with Coronavirus Disease 2019 in Korea, January – May 2020. 2020;35(30):1–11.[5]Freites Nuñez DD, Leon L, Mucientes A, Rodriguez-Rodriguez L, Font Urgelles J, Madrid García A, et al. Risk factors for hospital admissions related to COVID-19 in patients with autoimmune inflammatory rheumatic diseases. Ann Rheum Dis. 2020;79(11):1393–9.Disclosure of InterestsNone declared

BackgroundReports suggest that cancer patients may be more vulnerable to COVID-19, with increased disease severity and higher mortality rate.1–3 Although this is likely multifactorial, the exact pathogenesis has not been clearly elucidated. Studies have shown increased ACE2 expression in tumours as compared to normal tissues,4 5 thereby providing increased viral binding. Moreover, other mechanisms of cancer immunotherapy including treatment- and disease-related immunosuppression and functional exhaustion have been reported in patients with concomitant cancer and COVID-19; contributing to greater COVID-19 disease severity.6–8 There is still much to be revealed about the interplay between COVID-19, cancer and the immune system. These insights will give us greater understanding of the immunopathological processes underlying COVID-19 in cancer patients and their clinical relevance.MethodsA 45-year-old South Asian male diagnosed with COVID-19, with incidental discovery of stage II T3N0 caecal adenocarcinoma was consented for our study. The patient had experienced mild symptoms throughout the course of the disease, and underwent laparoscopic right hemicolectomy 10 days after recovery from COVID-19. His blood, lymph nodes, normal tissue and tumour samples were obtained for further analysis (figure 1). Multiplex immunohistochemistry was performed to understand SARS-CoV-2-associated tumour immune microenvironment. Moreover, to simulate ex vivo SARS-CoV-2 infection, dissociated cells from blood, lymph nodes, and tissue samples were stimulated with SARS-CoV-2 peptides or control for 16 hours. This was followed by 25-colour flow cytometry analysis for immune markers and cytokines. We then compared unstimulated with stimulated cells to study SARS-CoV-2-elicited immune response.ResultsMultiplex immunohistochemistry demonstrated upregulated expression of ACE2 in the tumour as compared to adjacent normal tissue, whilst SARS-CoV-2 was detected only in adjacent normal tissue but not within the tumour (figure 2). We also observed SARS-CoV-2 in other organs such as appendix and lymph nodes; and the presence of tertiary lymphoid structure, abundant T cells and NK cells within the proximity of the tumour (figure 2). Additionally, upon stimulation with SARS-CoV-2 peptides, we successfully elicited SARS-CoV-2-specific CD4+ T cells expressing immune markers such as granzyme B, TNF-α and IFN-γ (figure 3). Deep profiling of the samples is on-going with single-cell sequencing and digital spatial profiling.Abstract 475 Figure 1Study design, methodology and brief summary of the findingsBlood, lymph nodes, normal tissue and tumour samples were obtained from a 45-year-old South Asian male who was diagnosed with COVID-19 and caecal adenocarcinoma. Lymph nodes, normal tissue and tumour samples were analysed with multiplex immunohistochemistry, while dissociated cells from blood, lymph nodes and tissue samples were subjected to SARS-CoV-2 peptide stimulation and analysed with 25-colour flow cytometry. Multiplex immunohistochemistry detected SARS-CoV-2 proteins only in adjacent normal tissue but not within the tumour. Exhausted tumour-infiltrating T cells were also detected. Flow cytometry revealed CD4+ T cells expressing IFN-γ and granzyme BAbstract 475 Figure 2Multiplex immunohistochemistry of tissue samples(A) Multiplex immunohistochemistry of normal colon tissue. From left to right: SARS-CoV-2 nucleocapsid (green), CD3 (red), CD56 (cyan) and FOXP3 (white), representative of SARS-CoV-2 virus, T cells, NK cells and regulatory T cells respectively. (B) Multiplex immunohistochemistry of tertiary lymphoid structure. First row from left to right: PD-L1 (green), CD3 (orange), CD68 (red) and DAPI (blue). Second row from left to right: CD8 (magenta), cytokeratin (white), FOXP3 (cyan) and compositeAbstract 475 Figure 3Cytokine profiling with 25-colour flow cytometry panelBlood cells were incubated with SARS-CoV-2 peptides or control for 16 hours. This was followed by 25-colour flow cytometry panel with immune markers and cytokines. Both gated populations were observed to be increased after stimulation with SARS-CoV-2 peptides, suggesting that they might be SARS-CoV-2-specific T cells. Further gating on the populations showed that they were CD4+ T cells expressing granzyme B, with high (population 2) or moderate (population 1) TNF-α and IFN-γ expressionsConclusionsWe believe this is the first report of immune profiling of in situ tumour microenvironment in a cancer patient with COVID-19. Our findings showed the presence of viral proteins in several tissues despite negative swab test result, and the ability to elicit ex vivo SARS-CoV-2-specific T cell responses through peptide stimulation experiments.Ethics ApprovalThis study was approved by Centralised Institutional Review Board of SingHealth; approval number 2019/2653.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.ReferencesLiang W, Guan W, Chen R, Wang W, Li J, Xu K, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. The Lancet Oncology 2020;21(3):335–7.Cao Y, Liu X, Xiong L, Cai K. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2: A systematic review and meta-analysis. Journal of medical virology. 2020.Dai M, Liu D, Liu M, Zhou F, Li G, Chen Z, et al. Patients with cancer appear more vulnerable to SARS-COV-2: a multicenter study during the COVID-19 outbreak. Cancer discovery 2020;10(6):783–91.Bao R, Hernandez K, Huang L, Luke JJ. ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-CoV-2 COVID-19. J Immunother Cancer 2020;8(2).Winkler T, Ben-David U. Elevated expression of ACE2 in tumor-adjacent normal tissues of cancer patients. International Journal of Cancer 2020.Zheng M, Gao Y, Wang G, Song G, Liu S, Sun D, et al. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cellular & Molecular Immunology 2020;17(5):533–5.Diao B, Wang C, Tan Y, Chen X, Liu Y, Ning L, et al. Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19). Frontiers in Immunology 2020;11:827.McLane LM, Abdel-Hakeem MS, Wherry EJ. CD8 T cell exhaustion during chronic viral infection and cancer. Annual review of immunology 2019;37:457–95.

Can Gio mangrove forest (CGM) is located downstream of Ho Chi Minh City (HCMC), situated between an estuarine system of Dong Nai - Sai Gon river and a part of Vam Co river. The CGM is the largest restored mangrove forest in Vietnam and the UNESCO’s Mangrove Biosphere Reserve. The CGM has been gradually facing to numeric challenges of global climate change, environmental degradation and socio-economic development for the last decades. To evaluate sediment quality in the CGM, we collected 13 cores to analyze for sediment grain size, organic matter content, and trace element concentration of Cd, Cr, Cu, Ni, Pb, Zn. Results showed that trace element concentrations ranged from uncontaminated (Cd, Cu, and Zn) to very minor contaminated (Cr, Ni, and Pb). The concentrations were gradually influenced by suspended particle size and the mangrove plants.ReferencesAnh M.T., Chi D.H., Vinh N.N., Loan T.T., Triet L.M., Slootenb K.B.-V., Tarradellas J., 2003. Micropollutants in the sediment of Sai Gon – Dong Nai rivers: Situation and ecological risks. Chimia International Journal for Chemistry, 57, 09(0009–4293), 537–541.Baruddin N.A., Shazili N.A., Pradit S., 2017. Sequential extraction analysis of heavy metals in relation to bioaccumulation in mangroves, Rhizophora mucronata from Kelantan delta, Malaysia. AACL Bioflux, 10(2), 172-181. Retrieved from www.bioflux.com/aacl.Bravard J.-P., Goichot M., Tronchere H., 2014. An assessment of sediment transport processes in the lower Mekong river based on deposit grain size, the CM technique and flow energy data. Geomorphology, 207, 174-189.Cang L.T., Thanh N.C. 2008. Importing and exporting sediment to and from mangrove forest at Dong Trang estuary, Can Gio district, Ho Chi Minh city. Science & Technology Development, 11(04), 12-18.Carignan J., Hild P., Mevelle G., Morel J., Yeghicheyan D., 2001. Routine analyses of trace elements in geological samples using flow injection and low-pressure on-line liquid chromatography coupled to ICP-MS: A study of geochemical reference materials BR, DR-N, UB-N, AN-G and GH. The Journal of Geo standard and Geoanalysis, 187-198.Carlson P.R., Yarbro L.A., Zimmermann C.F., Montgomery J.R., 1983. Pore water chemistry of an overwash mangrove island. Academy Symposium: Future of the Indian River System, 46(3/4), 239-249. https://www.jstor.org/stable/24320336.Chatterjee M., Canário J., Sarkar S.K., Branco V., Godhantaraman N., Bhattacharya B.D., Bhattacharya A., 2012. Biogeochemistry of mercury and methylmercury in sediment cores from Sundarban mangrove wetland, India—a UNESCO World Heritage Site. Environ Monit Assess, 184, 5239–5254.Claudia R., Huy N.V., 2004. Water allocation policies for the Dong Nai river basin in Viet Nam: An integrated perspective. EPTD Discussion Paper, 127, 01-52.Folk R.L., Ward W.C., 1957. Brazos River bar: A study in the significance of grain size parameters. Journal of Sedimentary Petrology, 27(1), 3-26.Furukawaa K., Wolanski E., Mueller H., 1997. Currents and sediment transport in mangrove forests. Estuarine, Coastal and Shelf Science, 44, 301-310.Hai H.Q., Tuyen N.N., 2011. Coastal Erosion of Can Gio district Ho Chi Minh City due to the global climate change. The journal of development of technology and science, 14, 17-28.HCM SO S.O., 2015. Annual statistic data in 2015 for HCM city. Ho Chi Minh city: Statistic office of HCM city.HCMC, 2017. Decision No. 3901 on approving the areas of forest and land in HCM city in 2016. Ho Chi Minh: The people's committee of HCM city.Herut B., Sandler A., 2006. Normalization methods for pollutants in marine sediments: review and recommendations for the Mediterranean. Haifa 31080: Israel Oceanographic & Limnological Research: IOLR Report H18/2006.Hong P.N., San H.T., 1993. Mangroves of Vietnam: Chapter VI Human impacts on the mangrove ecosystem. Bangkok 10501: IUCN - The International Union for Conservation of Nature, ISBN: 2-8317-0166-x.Hubner R., Astin K.B., Herbert R.J., 2009. Comparison of sediment quality guidelines (SQGs) for the assessment of metal contamination in marine and estuarine environments. Journal of Environmental Monitoring, 11, 713–722.IAEA, 2003. Collection and preparation of bottom sediment samples for analysis of radionuclides and trace elements. Vienna, Austria: International Atomic Energy Agency, IAEA-TECDOC-1360, ISBN 92–0–109003–X.Jingchun L., Chongling Y., Ruifeng Z., Haoliang L., Guangqiu Q., 2008. Speciation changes of Cd in mangrove (Kandelia Candel L.) rhizosphere sediments. Bull Environ Contam Toxicol, 231-236. Doi:10.1007/s00128-007-9351-z.Kalaivanan R., Jayaprakash M., Nethaji S., Arya V., Giridharan L., 2017. Geochemistry of Core Sediments from Tropical Mangrove Region of Tamil Nadu: Implications on Trace Metals. Journal of Earth Science & Climatic Change, ISSN: 2157-7617., 8(1.1000385), 1-10. Doi:10.4172/2157-7617.1000385.Kathiresan K., Saravanakumar K., Mullai P., 2014. Bioaccumulation of trace elements by Avicennia marina. Journal of Coastal Life Medicine, 2(11), 888-894.Kitazawa T., Nakagawa T., Hashimoto T., Tateishi M., 2006. Stratigraphy and optically stimulated luminescence (OSL) dating of a Quaternary sequence along the Dong Nai River, southern Vietnam. Journal of Asian Earth Sciences, 27, 788–804.Lacerda L.D., 1998. Trace metals of biogeochemistry and diffuse pollution in mangrove (M. Vannucci, Ed.) Mangrove ecosystem occassional papers (ISSN: 0919-1348), 2, 1-72.Laura H., Probsta A., Probsta J.L., Ulrich E., 2003. Heavy metal distribution in some French forest soils: evidence for atmospheric contamination. The Science of Total Environment, 195-210.Li R., Li R., Chai M., Shen X., Xu H., Qiu G., 2015. Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China. Marine Pollution Bulletin, 101, 448–456.Long E., Morgan L.G., 1990. The potential for biological effects of sediment-sorted contaminants tested in the national status and trends program. Seattle, Washington: NOAA Technical Memorandum NOS OMA 52.Long E.R., Field L.J., MacDonald D.D., 1998. Predicting toxicity in marine sediments with numerical sediment quality guidelines. Environmental Toxicology and Chemistry, 17, 714–727. http://onlinelibrary.wiley.com/doi/10.1002/etc.5620170428/abstract;jsessionid=C5264A1AD0.7ACCA9B4EF9A088BE2EDE9.f04t04Long E.R., MacDonald D.D., Smith S.L., Calder F.D., 1995. Incidence of adverse biological effects within ranges of chemical concentration in marine and estuarine sediments. Environmental management, 19, 81-97.Maiti S.K., Chowdhury A., 2013. Effects of Anthropogenic Pollution on Mangrove Biodiversity: A Review. Journal of Environmental Protection, 4, 1428-1434.Marchand C., Allenbach M., Lallier-Verges E., 2011. Relation between heavy metal distribution and organic matter cycling in mangrove sediments (Conception Bay, New Caledonia). Geoderma, Elsevier, 160 (3-4), 444-456.Mohd F.N., Nor R.H., 2010. Heavy metal concentrations in an important mangrove species, Sonneratia caseolaris, in Peninsular Malaysia. Environment Asia, 3, 50-53.Muller G., 1979. Schwermetalle in den Sedimenten des Rheins - Veränderungen seit 1971. Umschau, 778-783.Nam V.N., 2007. Restoration of Can Gio mangrove forest: Its structure and function in comparison between the ecosytems of plantion and nature mangrove forest. Workshop on the thesis between Germany and Vietnam.Nickerson N.H., Thibodeau F.R., 1985. Association between pore water sulfide concentrations and the distribution of mangroves. Biogeochemistry, 1, 183-192.Ong Che R.G., 1999. Concentration of 7 Heavy Metals in Sediments and Mangrove Root Samples from Mai Po, Hong Kong. Marine Pollution Bulletin, 39, 269-279.Passega R., 1957. Texture as characteristics of clastic deposition. Publisher: American Association of Petroleum Geologists.Passega R., 1964. Grain size representation by CM patterns as a geological tool. J Sediment Petrol, 34, 830–847.Phuoc V.L., An D.T., Cang L.T., Chung B.N., Tien N.V., 2010. Study the sediment dynamics in Can Gio mangrove forest (Nang Hai site, Ho Chi Minh city). Ho Chi Minh city: The final report of National University Ho Chi Minh city, No. B2009-18-36.Pumijumnong N., Danpradit S., 2016. Heavy metal accumulation in sediments and mangrove forest stems from Surat Thani province, Thailand. The Malaysian forester, 79(1&2), 212-228.QCVN43:2012/BTNMT, 2012. QCVN43:2012/BTNMT: National technical regulation on the sediment quality, Ha Noi: Ministry of natural resources and environment of Vietnam.Qiao S., Shi X., Fang X., Liu S., Kornkanitnan N., Gao J., Yu Y., 2015. Heavy metal and clay mineral analyses in the sediments of Upper Gulf of Thailand and their implications on sedimentary provenance and dispersion pattern. Journal of Asian Earth Sciences, 114, 488–496.Rollinson H. R., 1993. Using geochemical data for evaluation, presentation and interpretation. UK: Longman Group UK Limited ISBN-0-582-06701-4.Spalding M., Blasco F., Field C., 2010. World atlas of mangrove. Cambridge: Earthscan in UK and US, ISBN: 978-1-84407-657-4.Strady E., Dang V.B., Némery J., Guédron S., Dinh Q.T., Denis H., Nguyen P.D., 2016. Baseline seasonal investigation of nutrients and trace metals in surface waters and sediments along the Saigon River basin impacted by the megacity of HCM, Viet Nam. Environ Sci Pollut Res, 1-18. doi:10.1007/s11356-016-7660-7.Tam N.F., Wong Y.S., 1996. Retention and distribution of heavy metals in mangrove soils receiving wastewater. Environment pollution, 94(5), 283-291.Thomas N., Lucas R., Bunting P., Hardy A., Rosenqvist A., Simard M., 2017. Distribution and drivers of global mangrove forest change, 1996– 2010. PLoS ONE, 12(6): e0179302, 1-14. Doi:10.1371/journal.pone.0179302.Thuy H.T., Loan T.T., Vy N.N., 2007. Study on environmental geochemistry of heavy metals in urban canal sediments of Ho Chi Minh city. Science and Technology Development, 10(01), 1-9.Toan T.T., Bay N.T., 2006. A study on the tendency of accretion and erosion in Can Gio coastal zone. Vietnam-Japan estuary workshop, 184-194.Tri N.H., Hong P.N., Cuc L.T., 2000. Can Gio Mangrove Biosphere Reserve Ho Chi Minh city, Ha Noi, Viet Nam. Ha Noi: Hanoi University Publisher.Truong T.V., 2007. Planning for water source of Dong Nai river basin. Retrieved from Water Resources Planning: http://siwrp.org.vn/tin-tuc/quy-hoach-tai-nguyen-nuoc-luu-vuc-song-dong-nai_143.html.Tuan L.D., Oanh T.T., Thanh C.V., Quy N.D., 2002. Can Gio mangrove biosphere reserve. HCM city, Vietnam: Agriculture Publisher.Tue N.T., Quy T.D., Amono A., 2012. Historical profiles of trace element concentrations in Mangrove sediments from the Ba Lat estuary, Red river, Vietnam. Water, Air & Soil Pollution, ISSN 0049-6979, 223(3), 1315-1330.Twilley R., Chen R., Hargis T., 1992. Carbon sinks in mangroves and their implications to carbon budget of tropical coastal ecosystems. Water, Air & Soil pollution, Netherland, 64, 265-288.UN Environment Program, 2006. Methods for sediment sampling and analysis. Palermo (Sicily), Italy: United Nation Environment Program.UNESCO, 2000. List of Biosphere reserves approved by MAB committee belonging to UNESCO. Retrieved from United Nations, Educational, Scientific, Cultural Organization (UNESCO): http://www.unesco.org/new/en/natural-sciences/environment/ecological-sciences/biosphere-reserves/asia-and-the-pacific.Vandenberghe N., 1975. An evaluation of CM patterns for grain size studies of fine grained sediments. Sedimentology, 22, 615-622.Vinh B.T., Ichiro D., 2012. Erosion mechanism of cohesive river bank and bed of Soai Rap river (Ho Chi Minh city). J. Sci. of the Earth, 34(2), 153-161.Wang J., Du H., Xu Y., Chen K., Liang J., Ke H., Cai M., 2016. Environmental and Ecological Risk Assessment of Trace Metal Contamination in Mangrove Ecosystems. BioMed Research International, Article ID 2167053, 1-14. Doi:10.1155/2016/2167053.Wedepohl K.H., 1995. The composition of the continental crust. Geochimica et Cosmochimica Acta, 59(7), 1217-1232.Woodroffe C., Rogers K., McKee K., Lovelock C., Mendelssohn I., Saintilan N., 2016. Mangrove sedimentation and response to relative sea level rise. The Annual Review of Marine Science, 8, 243-266.Zhang J., Liu C.L., 2002. Riverine Composition and Estuarine Geochemistry of Particulate Metals in China-Weathering Features, Anthropogenic Impact and Chemical Fluxes. Estuarine, Coastal and Shelf Science, 54(6), 1051-1070.Zhang W., Feng H., Chang J., Qu J., Xie H., Yu L., 2009. Heavy metal contamination in surface sediments of Yangtze River intertidal zone: An assessment from different indexes. Environmental Pollution, 157, 1533-1543.Zheng W.-j., Xiao-yong C., Peng L., 1997. Accumulation and biological cycling of heavy metal elements in Rhizophora stylosa mangroves in Yingluo Bay, China. Marine ecology progress series, 159, 293-301.

Treg cells serve essential roles in immunological tolerance and tissue homeostasis remodeling. However, the precise mechanism by which Treg cells specifically regulate the immune response in adipose tissue during obesity remains largely unexplored. Here we show that Foxp3, the master transcription factor of Treg cells, is negatively regulated by CREBZF, which mediates the immunosuppression of Treg cells in visceral adipose Treg cells. We found that CREBZF was dramatically induced in Treg cells from visceral adipose tissue (VAT) of obese subjects and epididymal adipose tissue (eWAT) of mice. Interestingly, palmitic acid (PA), but not insulin or lactate, promotes the expression of CREBZF in Treg cells. Treg cell-specific CREBZF deficiency significantly attenuated high-fat high sucrose (HFHS) diet-induced obesity, hyperglycemia and insulin resistance. Moreover, CREBZF deletion exhibited ameliorated inflammation and hypertrophic morphology in eWAT and enhanced systemic energy expenditure. Furthermore, obesity induced Treg cells loss, impaired Foxp3 expression and IL-10 production were reversed by CREBZF deletion in Treg cells from eWAT of mice, suggesting a key role of CREBZF in regulating the stability and immunosuppression of Treg cells. Mechanistically, single-cell transcriptomic analysis has identified a ICOShigh Treg cell subset, which is distinct from previously characterized adipose Treg cell populations and exhibited enhanced immunosuppressive function and more accumulation in CREBZF-deficient mice. Importantly, expression levels of CREBZF are negatively correlated with Foxp3 in VAT of obese human and eWAT of mice. Collectively, these studies uncover a specific adipose ICOShigh Treg subpopulation, which plays crucial roles in palmitic acid-induced immunosuppression restriction and systemic metabolic disorders. Disclosure W. Su: None. A. Cui: None. M. Huang: None. J. Lin: None. D. Ding: None. Z. Zheng: None. Y. Jiang: None. G. Cai: None. W. Li: None. S. Wei: None. J. Shen: None. X. Fang: None. J. Wen: None. Y. Huo: None. X. Wei: None. L. Li: None. Z. Liu: None. K. Qian: None. J. Zhao: None. Y. Li: None. Funding National Key R&D Program of China (2019YFA0802502), National Natural Science Foundation of China (81925008), Shanghai Science and Technology Commission (19140903300)

Glucose uptake is highly induced under cold exposure in adipose tissue, and glucose is required for generating heat during cold-induced nonshivering thermogenesis. However, the regulatory mechanism is largely unknown. Here, we uncovered a glucose sensor, a novel metabolic regulator CREBZF, that mediates the regulatory effects of glucose on browning of adipose tissue. In human white adipose tissue and inguinal white adipose tissue (iWAT) in mice, expression levels of CREBZF were remarkably induced by glucose. Glucose administration induces rectal temperature and thermogenesis in white adipose of control mice. Interestingly, these effects are further potentiated by CREBZF deficiency in adipose tissue. Consistently, during cold exposure, adipose tissue-specific CREBZF knockout mice display enhanced thermogenic gene expression, browning of iWAT and adaptive thermogenesis. Mechanistically, Lys208 acetylation modulated by transacetylase CREB-binding protein (CBP)/p300 mediates the glucose-induced reduction of proteasomal degradation and augmentation of protein stability of CREBZF. Moreover, deacetylase HDAC3 interacts with and removes the acetylation modification of CREBZF. The induced CREBZF by glucose further associates with PGC-1α and represses its transcriptional activity on thermogenic gene expression. Importantly, expression levels of CREBZF are negatively correlated with UCP1 in human adipose tissues and increased in WAT of obese ob/ob mice, which may underscore the potential role of CREBZF in the development of compromised thermogenic capability under hyperglycemic condition. Our results reveal an unknown mechanism of glucose sensing and thermogenic inactivation through reversible acetylation. Disclosure A. Cui: None. W. Su: None. J. Lin: None. D. Ding: None. Y. Jiang: None. Z. Zheng: None. M. Huang: None. G. Cai: None. S. Wei: None. W. Li: None. J. Shen: None. X. Fang: None. J. Wen: None. Y. Huo: None. X. Wei: None. L. Li: None. Z. Liu: None. K. Qian: None. J. Zhao: None. Y. Li: None. Funding National Key R&D Program of China (2019YFA0802502), National Natural Science Foundation of China (81925008), Shanghai Science and Technology Commission (19140903300)

Introduction & Objective: Ecnoglutide (XW003) is a cAMP signaling biased GLP-1 analog being developed for the treatment of type 2 diabetes mellitus (T2DM) and obesity. The primary objective of this study was to evaluate the efficacy of ecnoglutide administered for 24 weeks in adults with T2DM. Methods: We conducted a Phase 3 randomized, double-blind, placebo-controlled study of ecnoglutide, enrolling 211 adults with T2DM at 33 sites in China. Participants were randomized to receive 0.6 or 1.2 mg ecnoglutide or placebo as once weekly injections for 24 weeks, including dose escalation. All participants then received ecnoglutide (0.6 or 1.2 mg) for a total duration of 52 weeks. Change in mean HbA1c, body weight, and BMI, as well as safety and tolerability were evaluated. Results: At baseline, participants had mean HbA1c of 8.54, 8.51, and 8.51% and BMI of 27.2, 26.4, and 27.2 kg/m2, for ecnoglutide 0.6, 1.2 mg, and placebo groups, respectively. After 24 weeks, participants receiving ecnoglutide achieved significant HbA1c reductions of 1.96 to 2.43% from baseline (P≤0.0003 for both cohorts vs placebo). At 24 weeks, 76.1% of participants receiving 1.2 mg ecnoglutide achieved HbA1c ≤6.5%, 35.2% had HbA1c <5.7%, and 43.7% had body weight reductions ≥5% from baseline. Ecnoglutide was safe and well tolerated. The proportion of participants reporting any adverse event (AE) ranged from 77.5 to 78.3% for ecnoglutide groups and 60.6% for placebo. Four (2.9%) treatment-related ≥Grade 3 AEs and one (0.7%) treatment-related serious AE occurred in the ecnoglutide groups. One participant from each cohort discontinued due to an AE. The most frequently reported AEs were decreased appetite, diarrhea, and nausea, which were mostly mild to moderate and transient. Conclusion: Ecnoglutide resulted in robust HbA1c declines of up to 2.43% from baseline after 24 weeks of treatment in adults with T2DM, with up to 35.2% of participants reaching normoglycemia (HbA1c <5.7%) and 43.7% with weight reductions ≥5%. Disclosure D. Zhu: None. W. Wang: None. G. Tong: None. J. Ma: None. B. Wen: None. X. Zheng: None. B. Shi: None. S. Pang: None. S. Bing: Employee; Sciwind Biosciences, Keymed Biosciences. Q. Zheng: Employee; Sciwind Biosciences. G. Lei: None. F. Jiang: Employee; Sciwind Biosciences, PrimeGene Biosciences. X. Liu: None. Y. Bu: None. J. Ning: None. Z. Zhu: None. L. Yang: Employee; Sciwind Biosciences. M. Yang: Employee; Sciwind Biosciences. M. Fenaux: None. M.K. Junaidi: None. S. Xu: None. Funding Sciwind Biosciences

Ecnoglutide (XW003) is a novel, long-acting GLP-1 analog being developed for the treatment of type 2 diabetes and obesity. We conducted a Phase 1c randomized, double-blind, placebo-controlled study of ecnoglutide, which enrolled 60 nondiabetic adults with BMI 24-35 kg/m2. The study was conducted in China. PK, change in mean body weight and BMI, safety, and tolerability were evaluated. Participants received 1.8 or 2.4 mg ecnoglutide or placebo as once weekly injections for 14 weeks, including dose escalation. This core treatment was followed by an open-label extension of the ecnoglutide groups, for a total duration of 26 weeks. At baseline, participants had a mean body weight of 84.61 ± 10.44 kg and BMI of 29.53 ± 1.73 kg/m2. After 14 weeks of core treatment, mean weight reduction from baseline was -8.29 ± 0.52 kg in the 1.8 mg ecnoglutide group and -7.24 ± 0.56 kg in the 2.4 mg group, compared to -0.61 ± 0.82 kg for placebo (P<0.0001 vs placebo for both doses). At Week 14, the proportion of participants achieving ≥5% weight loss from baseline was 87.5% (95% CI, 67.6 to 97.3) and 70.0% (95% CI, 45.7 to 88.1) for 1.8 and 2.4 mg ecnoglutide, respectively, and 22.2% (95% CI, 2.8 to 60.0) for placebo. Continued weight reduction was observed until the end of study at Week 26, with a mean percent change from baseline of -15.0% (95%CI, -16.8 to -13.2) and -13.2% (95% CI, -15.3 to -11.1) for 1.8 and 2.4 mg ecnoglutide, respectively. At Week 26, ≥5% weight loss was observed for 94.7% (95% CI, 74.0 to 99.9) of participants in the 1.8 mg group and 100.0% (95% CI, 75.3 to 100.0) in the 2.4 mg group. At steady state, ecnoglutide showed a mean Cmax of 310 - 468 ng/mL, Tmax of 26 - 29 h, and half-life of 139 - 162 h. Overall, ecnoglutide was safe and well tolerated. The proportion of participants reporting any AE was similar between cohorts (95.2 to 100% for ecnoglutide vs 90% for placebo). The most frequent AEs were gastrointestinal, including diarrhea and vomiting. No drug-related SAE or drug-related AEs ≥Grade 3 were reported. Disclosure G. Wang: None. W. Hu: None. H.H. Qin: Employee; Sciwind Biosciences, Sichuan Anerobic Biotech. Q. Zheng: Employee; Sciwind Biosciences. J. Ning: None. G. Mengying: None. Y. Bu: Employee; Sciwind Biosciences. C. Jones: Employee; Sciwind Biosciences. M. Fenaux: Employee; Sciwind Biosciences. Stock/Shareholder; Terns Pharmaceuticals. S. Xu: Employee; Sciwind. M.K. Junaidi: None. Funding Sciwind Biosciences

The globe is engulfed by one of the most extensive public health crises as COVID-19 has become a leading cause of death worldwide. COVID-19 was first detected in Wuhan, China, in December 2019, causing the severe acute respiratory syndrome. This review discusses issues related to Covid-19 vaccines, such as vaccine development targets, vaccine types, efficacy, limitations and development prospects. Keywords: Covid-19, SARS-CoV-2, vaccine, spike protein. References [1] C. Wang, P. W. Horby, F. G. Hayden, G. F. Gao, A Novel Coronavirus Outbreak of Global Health Concern, The Lancet, Vol. 395, No. 10223, 2020, pp. 470-473, https://doi.org/10.1016/S0140-6736(20)30185-9.[2] T. Singhal, A Review of Coronavirus Disease-2019 (COVID-19), The Indian Journal of Pediatrics, Vol. 87, 2020, pp. 281-286, https://doi.org/10.1007/s12098-020-03263-6.[3] World Health Organization, WHO Coronavirus (COVID-19) Dashboard, https://covid19.who.int/, (accessed on: August 21st, 2021).[4] A. Alimolaie, A Review of Coronavirus Disease-2019 (COVID-19), Biological Science Promotion Vol. 3, No. 6, 2020, pp. 152-157.[5] J. Yang, Y. Zheng, X. Gou, K. Pu, Z. Chen, Q. Guo et al., Prevalence of Comorbidities and Its Effects in Patients Infected with SARS-Cov-2: A Systematic Review and Meta-Analysis, International Journal of Infectious Diseases, Vol. 94, 2020, pp. 91-95, https://doi.org/10.1016/j.ijid.2020.03.017.[6] H. E. Randolph, L. B. Barreiro, Herd Immunity: Understanding COVID-19, Immunity, Vol. 52, No. 5, 2020, pp. 737-741, https://doi.org/10.1016/j.immuni.2020.04.012.[7] F. Jung, V. Krieger, F. Hufert, J. H. Küpper, Herd Immunity or Suppression Strategy to Combat COVID-19, Clinical Hemorheology and Microcirculation, Vol. 75, No. 1, 2020, pp. 13-17, https://doi.org/10.3233/CH-209006.[8] O. Sharma, A. A. Sultan, H. Ding, C. R. Triggle, A Review of the Progress and Challenges of Developing a Vaccine for COVID-19, Frontiers in Immunology, Vol. 11, No. 2413, 2020, pp. 1-17, https://doi.org/10.3389/fimmu.2020.585354.[9] G. D. Sempowski, K. O. Saunders, P. Acharya, K. J. Wiehe, B. F. Haynes, Pandemic preparedness: Developing Vaccines and Therapeutic Antibodies for COVID-19, Cell, Vol. 181, No. 7, 2020, pp. 1458-1463, https://doi.org/10.1016/j.cell.2020.05. 041.[10] A. J. R. Morales, J. A. C. Ospina, E. G. Ocampo, R. V. Peña, Y. H. Rivera, J. P. E. Antezana et al., Clinical, Laboratory and Imaging Features of COVID-19: A Systematic Review and Meta-Analysis. Travel Medicine and Infectious Disease, Vol. 34, 2020, pp. 101-623, https://doi.org/10.1016/j.tmaid.2020.101623.[11] C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu et al., Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China, The Lancet, Vol. 395, No. 10223, 2020, pp. 497-506, https://doi.org/10.1016/S0140-6736(20)30183-5.[12] R. Lu, X. Zhao, J. Li, P. Niu, B. Yang, H. Wu et al., Genomic Characterisation and Epidemiology of 2019 Novel Coronavirus: Implications for Virus Origins and Receptor Binding, The Lancet, Vol. 395, No. 10224, 2020, pp. 565-574, https://doi.org/10.1016/S0140-6736(20)30251-8.[13] L. Chen, W. Liu, Q. Zhang, K. Xu, G. Ye, W. Wu et al., RNA Based mNGS Approach Identifies a Novel Human Coronavirus From Two Individual Pneumonia Cases in 2019 Wuhan Outbreak, Emerging Microbes & Infections, Vol. 9, No. 1, 2020, pp. 313-319, https://doi.org/10.1080/22221751.2020.1725399.[14] Y. Chen, Q. Liu, D. Guo, Emerging Coronaviruses: Genome Structure, Replication, and Pathogenesis, Journal of Medical Virology, Vol. 92, No. 4, 2020, pp. 418-423, https://doi.org/10.1002/jmv.25681.[15] D. R. Beniac, A. Andonov, E. Grudeski, T. F. Booth, Architecture of The SARS Coronavirus Prefusion Spike, Nature Structural & Molecular Biology, Vol. 13, No. 8, 2006, pp. 751-752, https://doi.org/10.1038/nsmb1123.[16] B. W. Neuman, G. Kiss, A. H. Kunding, D. Bhella, M. F. Baksh, S. Connelly et al., A Structural Analysis of M Protein in Coronavirus Assembly and Morphology, Journal of Structural Biology, Vol. 174, No. 1, 2011, pp. 11-22, https://doi.org/10.1016/j.jsb.2010.11.021.[17] J. L. N. Torres, M. L. DeDiego, C. V. Báguena, J. M. J. Guardeño, J. A. R. Nava, R. F. Delgado et al., Severe Acute Respiratory Syndrome Coronavirus Envelope Protein Ion Channel Activity Promotes Virus Fitness and Pathogenesis, Plos Pathogens Vol. 10, No. 5, 2014, https://doi.org/10.1371/journal.ppat.1004077.[18] A. R. Fehr, S. Perlman. Coronaviruses: An Overview of Their Replication and Pathogenesis. Coronaviruses, New York, 2015, pp. 1-23.[19] M. Letko, A. Marzi, V. Munster, Functional Assessment of Cell Entry and Receptor Usage for SARS-CoV-2 and Other Lineage B Betacoronaviruses,. Nature Microbiology, Vol. 5, No. 4, 2020, pp. 562-569, https://doi.org/10.1038/s41564-020-0688-y.[20] A. Grifoni, D. Weiskopf, S. I. Ramirez, J. Mateus, J. M. Dan, C. R. Moderbacher et al., Targets of T Cell Responses to SARS-Cov-2 Coronavirus in Humans With COVID-19 Disease and Unexposed Individuals, Cell, Vol. 181, No. 7, 2020, pp. 1489-1501, https://doi.org/10.1016/j.cell.2020.05.015.[21] M. Leslie, T Cells Found in Coronavirus Patients Bode Well for Long-Term Immunity, American Association for the Advancement of Science, Vol. 368, No. 6493, 2020, pp. 809-810, https://doi.org/10.1126/science.368.6493.809.[22] N. L. Bert, A. T. Tan, K. Kunasegaran, C. Y. Tham, M. Hafezi, A. Chia et al., SARS-CoV-2-specific T Cell Immunity in Cases of COVID-19 and SARS, and Uninfected Controls, Nature, Vol. 584, No. 7821, 2020, pp. 457-462, https://doi.org/10.1038/s41586-020-2550-z .[23] E. R. Adams, M. Ainsworth, R. Anand, M. I. Andersson, K. Auckland, J. K. Baillie et al., Antibody Testing for COVID-19: A Report from the National COVID Scientific Advisory Panel, Wellcome Open Research, Vol. 5, 2020, pp. 139-156, https://doi.org/10.12688/wellcomeopenres.15927.1.[24] N. Vabret, G. J. Britton, C. Gruber, S. Hegde, J. Kim, M. Kuksin et al., Immunology of COVID-19: current state of the science, Immunity. Vol. 52, No. 6, 2020, pp. 910-941, https://doi.org/10.1016/j.immuni.2020.05.002[25] W. Liu, A. Fontanet, P. H. Zhang, L. Zhan, Z. T. Xin, L. Baril et al., Two-Year Prospective Study of The Humoral Immune Response of Patients with Severe Acute Respiratory Syndrome, The Journal of Infectious Diseases, Vol. 193, No. 6, 2006, pp. 792-795, https://doi.org/10.1086/500469.[26] E. Callaway, Coronavirus Vaccines Leap Through Safety Trials-But Which Will Work is Anybody's Guess, Nature, Vol. 583, No. 7818, 2020, pp. 669-671, https://doi.org/10.1038/d41586-020-02174-y.[27] Y. Dong, T. Dai, Y. Wei, L. Zhang, M. Zheng, F. Zhou. A Systematic Review of SARS-Cov-2 Vaccine Candidates, Signal Transduction and Targeted Therapy, Vol. 5, No. 1, 2020, pp. 1-14, https://doi.org/10.1038/s41392-020-00352-y. [28] E. P. Regalado, Vaccines for SARS-CoV-2: Lessons from Other Coronavirus Strains. Infectious Diseases and Therapy, Vol. 9, No. 2, 2020, pp. 255-274, https://doi.org/10.1007/s40121-020-00300-x.[29] Y. Cai, J. Zhang, T. Xiao, H. Peng, S. M. Sterling, R. M. Walsh et al., Distinct Conformational States of SARS-CoV-2 Spike Protein, Science, Vol. 369, No. 6511, 2020, pp. 1586-1592, https://doi.org/10.1126/science.abd4251.[30] M. S. Suthar, M. G. Zimmerman, R. C. Kauffman, G. Mantus, S. L. Linderman, W. H. Hudson et al., Rapid Generation of Neutralizing Antibody Responses in COVID-19 Patients, Cell Reports Medicine, Vol. 1, No. 3, 2020, pp. 100040-100047, https://doi.org/10.1016/j.xcrm.2020.100040.[31] Q. Gao, L. Bao, H. Mao, L. Wang, K. Xu, M. Yang et al., Development of an Inactivated Vaccine Candidate for SARS-CoV-2, Science, Vol. 36, No. 6499, 2020, pp. 77-81, https://doi.org/10.1126/science.abc1932.[32] L. Ni, F. Ye, M. L. Cheng, Y. Feng, Y. Q. Deng, H. Zhao et al., Detection of SARS-CoV-2-specific Humoral and Cellular Immunity in COVID-19 Convalescent Individuals, Immunity, Vol. 52, No. 6, 2020, pp. 971-977, https://doi.org/10.1016/j.immuni.2020.04.023.[33] B. D. Quinlan, H. Mou, L. Zhang, Y. Guo, W. He, A. Ojha et al., The SARS-CoV-2 Receptor-binding Domain Elicits a Potent Neutralizing Response Without Antibody-dependent Enhancement, Available at SSRN, Vol. 3575134, 2020, pp. 1-24, http://dx.doi.org/10.2139/ssrn.3575134.[34] D. B. Melo, B. E. N. Payant, W. C. Liu, S. Uhl, D. Hoagland, R. Moller et al., Imbalanced Host Responseto SARS-Cov-2 Drives Development of COVID-19, Cell, Vol. 181, No. 5, 2020, pp. 1036-1045, https://doi.org/10.1016/j.cell.2020.04.026.[35] J. Hadjadj, N. Yatim, L. Barnabei, A. Corneau, J. Boussier, N. Smith et al., Impaired Type I Interferon Activity and Inflammatory Responses in Severe COVID-19 Patients, Science, Vol. 36, No. 6504, 2020, pp. 718-724, https://doi.org/10.1126/science.abc6027.[36] H. Pang, Y. Liu, X. Han, Y. Xu, F. Jiang, D. Wu et al., Protective Humoral Responses to Severe Acute Respiratory Syndrome-associated Coronavirus: Implications for the Design of an Effective Protein-based Vaccine, Journal of General Virology, Vol. 85, No. 10, 2004, pp. 3109-3113, https://doi.org/10.1099/vir.0.80111-0.[37] Y. Li, R. Tenchov, J. Smoot, C. Liu, S. Watkins, Q. Zhou, A Comprehensive Review of The Global Efforts on COVID-19 Vaccine Development, ACS Central Science , Vol. 7, No. 4, 2021, pp. 512-533, https://doi.org/10.1021/acscentsci.1c00120.[38] J. A. Wolff, R. W. Malone, P. Williams, W. Chong, G. Acsadi, A. Jani et al., Direct Gene Transfer Into Mouse Muscle in Vivo, Science, Vol. 247, No. 4949, 1990, pp. 1465-1468,. https://doi.org/10.1126/science.1690918.[39] M. Ingolotti, O. Kawalekar, D. J. Shedlock, K. Muthumani, D. B. Weiner, DNA Vaccines for Targeting Bacterial Infections, Expert Review of Vaccines, Vol. 9, No. 7, 2010, pp. 747-763, https://doi.org/10.1586/erv.10.57.[40] S. Jones, K. Evans, H. M. Johnn, M. Sharpe, J. Oxford, R. L. Williams et al., DNA Vaccination Protects Against an Influenza Challenge in A Double-Blind Randomised Placebo-Controlled Phase 1b Clinical Trial, Vaccine, Vol. 27, No. 18, 2009, pp. 2506-2512, https://doi.org/10.1016/j.vaccine.2009.02.061.[41] J. Kim, INOVIO Doses First Subject in Phase 2 Segment of its INNOVATE Phase 2/3 Clinical Trial for INO-4800, its DNA Medicine to Prevent COVID-19, Cision PR Newswire: News Distribution, Targeting and Monitoring Home, https://www.prnewswire.com/newsreleases/inovio-doses-first-subject-in-phase-2-segment-of-its-innovate-phase-23-clinical-trial-for-ino-4800-its-dna-medicine-to-prevent-covid-19-301187002.html/, 2020, (accessed on: December 7th, 2020).[42] P. Tebas, S. Yang, J. D. Boyer, E. L. Reuschel, A. Patel, A. C. Quick et al., Safety and Immunogenicity of INO-4800 DNA Vaccine Against SARS-Cov-2: A Preliminary Report of an Open-Label, Phase 1 Clinical Trial, EClinical Medicine, Vol. 31, No. 1000689, 2021, https://doi.org/10.1016/j.eclinm.2020.100689.[43] T. Schlake, A. Thess, M. F. Mleczek, K. J. Kallen. Developing mRNA-vaccine Technologies, RNA Biology, Vol. 9, No. 11, 2012, pp. 1319-1330, https://doi.org/10.4161/rna.22269.[44] K. J. Hassett, K. E. Benenato, E. Jacquinet, A. Lee, A. Woods, O. Yuzhakov et al., Optimization of lipid Nanoparticles for Intramuscular Administration of mRNA Vaccines, Molecular Therapy-Nucleic Acids, Vol. 15, 2019, pp. 1-11, https://doi.org/10.1016/j.omtn.2019.01.013.[45] A. Bashirullah, R. L. Cooperstock, H. D. Lipshitz, Spatial and Temporal Control of RNA Stability, Proceedings of the National Academy of Sciences, Vol. 98, No. 13, 2001, pp. 7025-7028. [46] K. Kariko, H. Muramatsu, J. Ludwig, D. Weissman, Generating the Optimal mRNA for Therapy: HPLC Purification Eliminates Immune Activation and Improves Translation of Nucleoside-Modified, Protein-Encoding mRNA, Nucleic Acids Research, Vol. 39, No. 21, 2011, pp. 142-152, https://doi.org/10.1093/nar/gkr695.[47] N. Pardi, M. J. Hogan, M. S. Naradikian, K. Parkhouse, D. W. Cain, L. Jones et al., Nucleoside-Modified mRNA Vaccines Induce Potent T Follicular Helper and Germinal Center B Cell Responses, Journal of Experimental Medicine, Vol. 215, No. 6, 2018, pp. 1571-1588, https://doi.org/10.1084/jem.20171450.[48] L. A. Jackson, E. J. Anderson, N. G. Rouphael, P. C. Roberts, M. Makhene, R. N. Coler et al., An mRNA Vaccine Against SARS-CoV-2-Preliminary Report, New England Journal of Medicine, Vol. 383, No. 20, 2020, pp. 1920-1931, https://doi.org/10.1056/NEJMoa2022483.[49] K. S. Corbett, D. K. Edwards, S. R. Leist, O. M. Abiona, S. B. Barnum, R. A. Gillespie et al., SARS-CoV-2 mRNA Vaccine Design Enabled by Prototype Pathogen Preparedness, Nature, Vol. 586, No. 7830, 2020, pp. 567-571, https://doi.org/10.1038/s41586-020-2622-0.[50] K. S. Corbett, B. Flynn, K. E. Foulds, J. R. Francica, S. B. Barnum, A. P. Werner et al., Evaluation of the mRNA-1273 Vaccine Against SARS-CoV-2 in Nonhuman Primates, New England Journal of Medicine, Vol. 383, No. 16, 2020, pp. 1544-1555, https://doi.org/10.1056/NEJMoa2024671.[51] E. E. Walsh, R. Frenck, A. R. Falsey, N. Kitchin, J. Absalon, A. Gurtman et al., RNA-Based COVID-19 Vaccine BNT162b2 Selected for a Pivotal Efficacy Study, Medrxiv, Vol. 2, 2020, https://doi.org/10.1101/2020.08.17.20176651.[52] M. J. Mulligan, K. E. Lyke, N. Kitchin, J. Absalon, A. Gurtman, S. Lockhart et al., Phase 1/2 Study to Describe the Safety and Immunogenicity of a COVID-19 RNA Vaccine Candidate (BNT162b1) in Adults 18 to 55 Years of Age: Interim Report, Medrxiv, Vol. 586, 2020, pp. 589-593, https://doi.org/10.1056/NEJMoa2028436.[53] E. J. Anderson, N. G. Rouphael, A. T. Widge, L. A. Jackson, P. C. Roberts, M. Makhene et al., Safety and Immunogenicity of SARS-CoV-2 mRNA-1273 Vaccine in Older Adults, New England Journal of Medicine, Vol. 383, No. 25, 2020, pp. 2427-2438, https://doi.org/10.1038/s41586-020-2639-4.[54] P. F. McKay, K. Hu, A. K. Blakney, K. Samnuan, J. C. Brown, R. Penn et al., Self-amplifying RNA SARS-CoV-2 Lipid Nanoparticle Vaccine Candidate Induces High Neutralizing Antibody Titers in Mice, Nature Communications, Vol. 11, No. 1, 2020, pp. 1-7, https://doi.org/10.1038/s41467-020-17409-9.[55] J. H. Erasmus, A. P. Khandhar, A. C. Walls, E. A. Hemann, M. A. O’Connor, P. Murapa et al., Single-dose Replicating RNA vaccine Induces Neutralizing Antibodies Against SARS-CoV-2 in Nonhuman Primates, BioRxiv, 2020, https://doi.org/10.1101/2020.05.28.121640.[56] R. D. Alwis, E. S. Gan, S. Chen, Y. S. Leong, H. C. Tan, S. L. Zhang et al., A Single Dose of Self-Transcribing and Replicating RNA-based SARS-CoV-2 Vaccine Produces Protective Adaptive Immunity in Mice, Molecular Therapy, Vol. 29, No. 6, 2021, pp. 1970-1983, https://doi.org/10.1016/j.ymthe.2021.04.001.[57] M. R. Guroff, Replicating and Non-Replicating Viral Vectors for Vaccine Development, Current Opinion in Biotechnology, Vol. 18, No. 6, 2007, pp. 546-556, https://doi.org/10.1016/j.copbio.2007.10.010.[58] K. Benihoud, P. Yeh, M. Perricaudet, Adenovirus Vectors for Gene Delivery, Current Opinion in Biotechnology, Vol. 10, No. 5,1999, pp. 440-447, https://doi.org/10.1016/s0958-1669(99)00007-5.[59] Z. Xiang, G. Gao, A. R. Sandoval, C. J. Cohen, Y. Li, J. M. Bergelson et al., Novel, Chimpanzee Serotype 68-Based Adenoviral Vaccine Carrier for Induction of Antibodies to A Transgene Product, Journal of Virology, Vol. 76, No. 6, 2002, pp. 2667-2675, https://doi.org/10.1128/JVI.76.6.2667-2675.2002.[60] F. C. Zhu, X. H. Guan, Y. H. Li, J. Y. Huang, T. Jiang, L. H. Hou et al., Immunogenicity and Safety Of A Recombinant Adenovirus Type-5-Vectored COVID-19 Vaccine in Healthy Adults Aged 18 Years or Older: A Randomised, Double-Blind, Placebo-Controlled, Phase 2 Trial, The Lancet, Vol. 396, No. 10249, 2020, pp. 479-488, https://doi.org/10.1016/S0140-6736(20)31605-6.[61] F. C. Zhu, Y. H. Li, X. H. Guan, L. H. Hou, W. J. Wang, J. X. Li et al., Safety, Tolerability, and Immunogenicity of A Recombinant Adenovirus Type-5 Vectored COVID-19 Vaccine: A Dose-Escalation, Open-Label, Non-Randomised, First-in-Human Trial, The Lancet. Vol. 395, No. 10240, 2020, pp. 1845-1854.[62] S. Wu, G. Zhong, J. Zhang, L. Shuai, Z. Zhang, Z. Wen, et al. A Single Dose of An Adenovirus-Vectored Vaccine Provides Protection Against SARS-Cov-2 Challenge, Nature Communications Vol. 1, No. 11, 2020, pp. 1-7, https://doi.org/10.1016/s41467-020-17972-1.[63] P. M. Folegatti, K. J. Ewer, P. K. Aley, B. Angus, S. Becker, S. B. Rammerstorfer et al., Safety and Immunogenicity of The Chadox1 Ncov-19 Vaccine Against SARS-Cov-2: A Preliminary Report of A Phase 1/2, Single-Blind, Randomised Controlled Trial, The Lancet, Vol. 396, No. 10249, 2020, pp. 467-478, https://doi.org/10.1016/S0140-6736(20)31604-4.[64] N. V. Doremalen, T. Lambe, A. Spencer, S. B. Rammerstorfer, J. N. Purushotham, J. R. Port et al., ChAdOx1 nCoV-19 Vaccine Prevents SARS-Cov-2 Pneumonia in Rhesus Macaques, Nature, Vol. 586, No. 7830, 2020, pp. 578-582, https://doi.org/10.1016/s41586-020-2608-y.[65] D. Y. Logunov, I. V. Dolzhikova, O. V. Zubkova, A. I. Tukhvatullin, D. V. Shcheblyakov, A. S. Dzharullaeva et al., Safety and Immunogenicity of an Rad26 And Rad5 Vector-Based Heterologous Prime-Boost COVID-19 Vaccine in Two Formulations: Two Open, Non-Randomised Phase 1/2 Studies From Russia, The Lancet, Vol. 396, No. 10255, 2020, pp. 887-897, https://doi.org/10.1016/S0140-6736(20)31866-3.[66] S. Y. Jung, K. W. Kang, E. Y. Lee, D. W. Seo, H. L. Kim, H. Kim et al., Heterologous Prime-Boost Vaccination with Adenoviral Vector and Protein Nanoparticles Induces Both Th1 and Th2 Responses Against Middle East Respiratory Syndrome Coronavirus, Vaccine, Vol. 36, No. 24, 2018, pp. 3468-3476, https://doi.org/10.1016/j.vaccine.2018.04.082.[67] S. Lu, Heterologous Prime-Boost Vaccination. Current Opinion in Immunology, Vol. 21, No. 3, 2009, pp. 346-351, https://doi.org/10.1016/j.coi.2009.05.016.[68] D. Y. Logunov, I. V. Dolzhikova, D. V. Shcheblyakov, A. I. Tukhvatulin, O. V. Zubkova, A. S. Dzharullaeva et al., Safety and Efficacy of an Rad26 and Rad5 Vector-Based Heterologous Prime-Boost COVID-19 Vaccine: an Interim Analysis of A Randomised Controlled Phase 3 Trial in Russia, The Lancet, Vol. 397, No. 10275, 2021, pp. 671-681, https://doi.org/10.1016/S0140-6736(21)00234-8.[69] T. Ura, K. Okuda, M. Shimada. Developments in Viral Vector-Based Vaccines, Vaccines, Vol. 2, No. 3, 2014, pp. 624-641, https://doi.org/10.3390/vaccines2030624.[70] B. E. Bache, M. P. Grobusch, S. T. Agnandji. Safety, Immunogenicity and Risk-Benefit Analysis of Rvsv-ΔG-ZEBOV-GP (V920) Ebola Vaccine in Phase I-III Clinical Trials Across Regions. Future Microbiology, Vol. 15, No. 2, 2020, pp. 85-106, https://doi.org/10.2217/fmb-2019-0237.[71] Ebola Vaccines, NIH: National Institute of Allergy and Infectious Diseases Logo, 2020, https://www.niaid.nih.gov/diseases-conditions/ebola-vaccines/, (accessed on: January 9th, 2020).[72] F. Krammer, SARS-CoV-2 Vaccines in Development, Nature, Vol. 586, No. 7830, 2020, pp. 516-527, https://doi.org/10.1038/s41586-020-2798-3.[73] Y. Zhang, G. Zeng, H. Pan, C. Li, Y. Hu, K. Chu et al., Safety, Tolerability, and Immunogenicity of an Inactivated SARS-CoV-2 Vaccine in Healthy Adults Aged 18-59 Years: A Randomised, Double-Blind, Placebo-Controlled, Phase 1/2 Clinical Trial, The Lancet Infectious Diseases, Vol. 21, No. 2, 2021, pp. 181-192, https://doi.org/10.1016/S1473-3099(20)30843-4.[74] Sinovac Announces Phase III Results of Its COVID-19 Vaccine, Sinovac, 2021. https://www.businessswwire.com/news/home/20210205005496/en/Sinovac-Announces-Phase-III-Results-of-Its-COVID-19-Vaccine/, 2021, (accessed on: February 5th,2021).[75] Sinovac Receives Conditional Marketing Authorization in China for its COVID-19 Vaccine. Sinovac, https://www.businessswwire.com/news/ home/20210208005305/en/Sinovac-Receives-Conditional-Marketing-Authorization-in-China-for-its-COVID-19-Vaccin/, 2021, (accessed on: February 8th, 2021).[76] L. M. Rossen, A. M. Branum, F. B. Ahmad, P. Sutton, R. N. Anderson, Excess Deaths Associated with COVID-19, by Age and Race and Ethnicity-United States, January 26-October 3, 2020, Morbidity and Mortality Weekly Report, Vol. 69, No. 42, 2020, pp. 1522-1527.[77] China Grants Conditional Market Approval for Sinopharm CNBG’s COVID-19 Vaccine. Sinopharm, http://www.sinopharm.com/en/s/1395-4173-38862.html/, 2021, (accessed on: January 2nd, 2021).[78] V. A. Fulginiti, J. J. Eller, A. W. Downie, C. H. Kempe, Altered Reactivity to Measles Virus: Atypical Measles in Children Previously Immunized with Inactivated Measles Virus Vaccines, Jama, Vol. 202, No. 12, 1967, pp. 1075-1080, https://doi.org/10.1001/jama.1967.03130250057008.[79] H. W. Kim, J. G. Canchola, C. D. Brandt, G. Pyles, R. M. Chanock, K. Jensen et al., Respiratory Syncytial Virus Disease in Infants Despite Prior Administration of Antigenic Inactivated Vaccine. American Journal of Epidemiology, Vol. 89, No. 4, 1969, pp. 422-434, https://doi.org/10.1093/oxfordjournals.aje.a120955.[80] Novavax Confirms High Levels of Efficacy Against Original and Variant COVID-19 Strains in United Kingdom and South Africa Trials, Novavax 2021, https://www.prnewswire.com/news-releases/novavax-confirms-high-levels-of-efficacy-against-original-and-variant-covid-19-strains-in-united-kingdom-and-south-africa-trials-301246019.html/, (accessed on: March 11th, 2021).[81] Our Vaccine, Covaxx, 2020, https://www.gavi.org/covax-vaccine-roll-out/, (accessed on: August 14th, 2021).[82] M. O. Mohsen, G. Augusto, M. F. Bachmann, The 3Ds in Virus‐like Particle Based‐vaccines: Design, Delivery and Dynamics, Immunological Reviews Vol. 296, No. 1, 2020, pp. 155-168, https://doi.org/10.1111/imr.12863.