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The study explored whether an asynchronous short online course in mental health well-being and resilience for healthcare workers (HCWs) showed improved self-reported results among participants during the second wave of the COVID-19 pandemic.

A descriptive cross-sectional study evaluated the course outcomes using the 10-item Connor and Davison's Resilience Scale, the World Health Organization's WHO-five well-being index and self-developed questions. Data were collected via online questionnaires before and after course completion.

A total of 1 301 HCWs participated. The highest proportion of participants was from South Africa (SA) (93.7%) and females (78.7%). Analysed mean pre- and post-training scores showed increased scores in all five domains: knowledge, confidence in course outcomes, behaviour, resilience and well-being. Confidence in the course outcomes was the only common significant construct for both well-being and resilience. Mindfulness activities (β = 0.12, 95%CI [0.032, 0.213], p = 0.008) and self-care behaviours (β = 0.14, 95%CI [0.035, 0.241], p = 0.009) were significant predictors of participants' well-being. Coping mechanisms for stress (β = 0.12, 95%CI [0.036, 0.21], p = 0.006) and connecting with a social support network (β = 0.085, 95%CI [0.0007, 0.17], p = 0.048) were significant predictors of participants' resilience. Those working in the private sector, those working in clinical settings and those who were female showed significant associations with well-being and resilience.

The results are self-reported data which may be susceptible to social desirability and acquiescent effects. There are no guarantees that positive effects observed during this study are sustained over time. The study sample was selective in that it excluded those who did not consent for the use of their data and those who did not complete the course.

The research is noteworthy as literature shows that female HCWs tend to have worse mental health outcomes than males in the same field. Online learning can enable HCWs to conveniently access mental health education, accommodate their work commitments and explore topics that are potentially stigmatising.

This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.