Highlights COVID -19 cases now confirmed in multiple countries. assessed the prevalence of comorbidities in infected patients.  comorbidities are risk factors for severe patients compare with Non-severe.J o u r n a l P r e -p r o o f 2  help the health sector guide vulnerable populations and assess the risk of deterioration.Background: An outbreak of Novel Coronavirus in Wuhan, China, the epidemic is more widespread than initially estimated, with cases now confirmed in multiple countries. Aims:The aim of the meta-analysis was to assess the prevalence of comorbidities in the COVID-19 infection patients and the risk of underlying diseases in severe patients compared to non-severe patients. Methods:A literature search was conducted using the databases PubMed, EMBASE, and Web of sciences until February 25, 2020. Risk ratio (OR) and 95% confidence intervals (CIs) were pooled using random-effects models.Results: Eight studies were included in the meta-analysis, including 46248 infected patients. The result showed the most prevalent clinical symptom was fever ( 91±3, 95% CI 86-97% ), followed by cough (67±7, 95% CI 59-76%), fatigue ( 51±0, 95% CI 34-68% ) and dyspnea ( 30±4, 95% CI 21-40%). The most prevalent comorbidity were hypertension (17±7, 95% CI 14-22%) and diabetes ( 8±6, 95% CI 6-11% ), followed by cardiovascular diseases ( 5±4, 95% CI 4-7% ) and respiratory system disease( 2±0, 95% CI 1-3% ). Compared with the Non-severe patient, the pooled odds ratio of hypertension, respiratory system disease, cardiovascular disease in severe patients were (OR 2.36, 95% CI: 1.46-3.83) ,(OR 2.46, 95% CI: 1.76-3.44) and (OR 3.42, 95% CI: 1.88-6.22)respectively. Conclusion:We assessed the prevalence of comorbidities in the COVID-19 infection patients and found underlying disease, including hypertension, respiratory system disease and cardiovascular, may be a risk factor for severe patients compared with Non-severe patients.

is a major health threat. Vaccination and passive immunization are considered as alternative therapeutic strategies for managing infections. Lipopolysaccharide O antigens are attractive candidates because of the relatively small range of known O-antigen polysaccharide structures, but immunotherapeutic applications require a complete understanding of the structures found in clinical settings. Currently, the precise number of O antigens is unknown because available serological tests have limited resolution, and their association with defined chemical structures is sometimes uncertain. Molecular serotyping methods can evaluate clinical prevalence of O serotypes but require a full understanding of the genetic determinants for each O-antigen structure. This is problematic with because genes outside the main (O-antigen biosynthesis) locus can have profound effects on the final structure. Here, we report two new loci encoding enzymes that modify a conserved polysaccharide backbone comprising disaccharide repeat units [→3)-α-d-Gal-(1→3)-β-d-Gal-(1→] (O2a antigen). We identified in serotype O2aeh a three-component system that modifies completed O2a glycan in the periplasm by adding 1,2-linked α-Gal side-group residues. In serotype O2ac, a polysaccharide comprising disaccharide repeat units [→5)-β-d-Gal-(1→3)-β-d-GlcNAc-(1→] (O2c antigen) is attached to the non-reducing termini of O2a-antigen chains. O2c-polysaccharide synthesis is dependent on a locus encoding three glycosyltransferase enzymes. The authentic O2aeh and O2c antigens were recapitulated in recombinant hosts to establish the essential gene set for their synthesis. These findings now provide a complete understanding of the molecular genetic basis for the known variations in O-antigen carbohydrate structures based on the O2a backbone.

Objectives To evaluate the prevalence of Helicobacter pylori infection and risk factors and to serotype the strains in Wuwei, located in north‐western China, which has a high incidence of gastric cancer. Methods Helicobacter pylori infection was analysed in 21 291 adults by 14C‐urea breath test, and H. pylori antibody were detected in 9183 serum samples by latex immunoturbidimetric method. The correlation of H. pylori infection with demographic–economic, lifestyle factors and medical history among the participants was determined by questionnaire. The antibodies against H. pylori urease, VacA and CagA in serum were determined by dot immunobinding assay. Results The infection rate of H. pylori was 53.0%, and 90.1% of strains were type I strains. The H. pylori infection rate was higher among farmers (OR = 1.34, 95% CI: 1.19–1.50) and individuals who had a junior high school or higher education level (OR = 1.10, 95% CI: 1.06–1.15), and was lower in older individuals (OR = 0.86, 95% CI: 0.83–0.90), individuals with high income (OR = 0.93, 95% CI: 0.90–0.95), individuals with a habit of eating quickly (OR = 0.93, 95% CI: 0.87–0.99) and individuals who consumed more fruit and vegetables (OR = 0.90, 95% CI: 0.85–0.95). Individuals with history of cholecystitis/cholecystolithiasis, hypertension and asthma were negatively correlated with H. pylori infection (P < 0.05). Conclusion The prevalence of H. pylori infection is high in Wuwei. The major prevalent strain is type I strain. Age, education, occupation, household income, consumption of fruit and vegetables, and habit of eating quickly are independent risk factors for H. pylori infection, which is also associated with individuals with a history of extragastric diseases.

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