Whole-genome sequencing analysis of Klebsiella aerogenes among men who have sex with men in Guangzhou, China.

Klebsiella aerogenes is a common infectious bacterium that poses a threat to human health. Nevertheless, there are limited data on the population structure, genetic diversity, and pathogenicity of K. aerogenes, especially among men who have sex with men (MSM). The present study aimed to clarify the sequence types (STs), clonal complexes (CCs), resistance genes, and virulence factors of popular strains. Multilocus sequence typing was used to describe the population structure of K. aerogenes. The Virulence Factor Database and Comprehensive Antibiotic Resistance Database were used to assess the virulence and resistance profiles. In this study, next-generation sequencing was performed on nasal swabs specimens collected in an HIV Voluntary Counseling Testing outpatient department in Guangzhou, China, from April to August 2019. The identification results showed that a total of 258 K. aerogenes isolates were collected from 911 participants. We found that the isolates were most resistant to furantoin (89.53%, 231/258) and ampicillin (89.15%, 230/258), followed by imipenem (24.81%, 64/258) and cefotaxime (18.22%, 47/258). The most common STs in carbapenem-resistant K. aerogenes were ST4, ST93, and ST14. The population has at least 14 CCs, including several novel ones identified in this study (CC11-CC16). The main mechanism of drug resistance genes was antibiotic efflux. Based on the presence of the iron carrier production genes irp and ybt, we identified two clusters according to virulence profiles. In cluster A, CC3 and CC4 carry the clb operator encoding the toxin. Increased monitoring is needed for the three main ST type strains carried by MSM. The main clone group CC4 has a large number of toxin genes, and it spreads among MSM. Caution is needed to prevent further spread of this clone group in this population. In sum, our results may provide a foundation for the development of new therapeutic and surveillance strategies for treating MSM.

Spatiotemporal analysis of the morbidity of global Omicron from November 2021 to February 2022.

The Omicron variant was first reported to the World Health Organization (WHO) from South Africa on November 24, 2021; this variant is spreading rapidly worldwide. No study has conducted a spatiotemporal analysis of the morbidity of Omicron infection at the country level; hence, to explore the spatial transmission of the Omicron variant among the 220 countries worldwide, we aimed to the analyze its spatial autocorrelation and to conduct a multiple linear regression to investigate the underlying factors associated with the pandemic. This study was an ecological study. Data on the number of confirmed cases were extracted from the WHO website. The spatiotemporal characteristic was described in a thematic map. The Global Moran Index (Moran's I) was used to detect the spatial autocorrelation, while the local indicators of spatial association (LISA) were used to analyze the local spatial correlation characteristics. The joinpoint regression model was used to explore the change in the trend of the Omicron incidence over time. The association between the morbidity of Omicron and influencing factors were analyzed using multiple linear regression. This study was an ecological study. Data on the number of confirmed cases were extracted from the WHO website. The spatiotemporal characteristic was described in a thematic map. The Global Moran Index (Moran's I) was used to detect the spatial autocorrelation, while the LISA were used to analyze the local spatial correlation characteristics. The joinpoint regression model was used to explore the change in the trend of the Omicron incidence over time. The association between the morbidity of Omicron and influencing factors were analyzed using multiple linear regression. The value of Moran's I was positive (Moran's I = 0.061, Z-score = 3.772, p = 0.007), indicating a spatial correlation of the morbidity of Omicron at the country level. From November 26, 2021 to February 26, 2022; the morbidity showed obvious spatial clustering. Hotspot clustering was observed mostly in Europe (locations in High-High category: 24). Coldspot clustering was observed mostly in Africa and Asia (locations in Low-Low category: 32). The result of joinpoint regression showed an increasing trend from December 21, 2021 to January 26, 2022. Results of the multiple linear regression analysis demonstrated that the morbidity of Omicron was strongly positively correlated with income support (coefficient = 1.905, 95% confidence interval [CI]: 1.354-2.456, p < 0.001) and strongly negatively correlated with close public transport (coefficient = -1.591, 95% CI: -2.461 to -0.721, p = 0.001). Omicron outbreaks exhibited spatial clustering at the country level worldwide; the countries with higher disease morbidity could impact the other countries that are surrounded by and close to it. The locations with High-High clustering category, which referred to the countries with higher disease morbidity, were mainly observed in Europe, and its adjoining country also showed high spatial clustering. The morbidity of Omicron increased from December 21, 2021 to January 26, 2022. The higher morbidity of Omicron was associated with the economic and policy interventions implemented; hence, to deal with the epidemic, the prevention and control measures should be strengthened in all aspects.

Dose-Response Effects of Low-Dose Ionizing Radiation on Blood Parameters in Industrial Irradiation Workers.

While previous studies have focused on the health effects of occupational exposure of radiations on medical radiation workers, few have analyzed the dose-response relationship between low radiation doses and changes in blood parameters. Even fewer studies have been conducted on industrial worker populations. Using a prospective cohort study design, this study collected health examination reports and personal dose monitoring data from 705 industrial irradiation workers who underwent regular physical examinations at Dongguan Sixth People's Hospital. The dose-response effects of low-dose ionizing radiation on blood parameters were assessed using a generalized linear model and restricted cubic spline model. Red blood cell counts decreased then increased, before decreasing again with increasing ionizing radiation. This was in contrast to the curve of the total platelet count after irradiation. Additionally, a radiation dose of 2.904 mSv was the turning point for the nonlinear curve of hemoglobin count changes. In conclusion, long-term, low-dose ionizing radiation affects blood cell levels in industrial irradiation workers. There is a nonlinear dose-response relationship between red blood cell, platelet, and hemoglobin counts and the cumulative radiation dose. These findings should alert radiation workers to seek preventive medical treatment before the occurrence of any serious hematopoietic disease.