Salmonella enterica serovar Typhimurium (S. Typhimurium) is a major cause of salmonellosis, and the emergence of multidrug-resistant pathovariants has become a growing concern. Here, we investigate a distinct rough colony variant exhibiting a strong biofilm-forming ability isolated in China. Whole-genome sequencing on 2,212 Chinese isolates and 1,739 publicly available genomes reveals the population structure and evolutionary history of the rough colony variants. Characterized by macro, red, dry, and rough (mrdar) colonies, these variants demonstrate enhanced biofilm formation at 28 °C and 37 °C compared to typical rdar colonies. The mrdar variants exhibit extensive multidrug resistance, with significantly higher resistance to at least five classes of antimicrobial agents compared to non-mrdar variants. This resistance is primarily conferred by an IncHI2 plasmid harboring 19 antimicrobial resistance genes. Phylogenomic analysis divides the global collections into six lineages. The majority of mrdar variants belong to sublineage L6.5, which originated from Chinese smooth colony strains and possibly emerged circa 1977. Among the mrdar variants, upregulation of the csgDEFG operons is observed, probably due to a distinct point mutation (−44G > T) in the csgD gene promoter. Pangenome and genome-wide association analyses identify 87 specific accessory genes and 72 distinct single nucleotide polymorphisms associated with the mrdar morphotype.

Antimicrobial resistance of Shigella sonnei has become a global concern. Here, we report a phylogenetic group of S. sonnei with extensive drug resistance, including a combination of multidrug resistance, coresistance to ceftriaxone and azithromycin (cef^Razi^R), reduced susceptibility to fluoroquinolones, and even colistin resistance (col^R). This distinct clone caused six waterborne shigellosis outbreaks in China from 2015 to 2020. We collect 155 outbreak isolates and 152 sporadic isolates. The cef^Razi^R isolates, including outbreak strains, are mainly distributed in a distinct clade located in global Lineage III. The outbreak strains form a recently derived monophyletic group that may have emerged circa 2010. The cef^Razi^R and col^R phenotypes are attributed to the acquisition of different plasmids, particularly the IncB/O/K/Z plasmid coharboring the bla_CTX-M-14, mphA, aac(3)-IId, dfrA17, aadA5, and sul1 genes and the IncI2 plasmid with an mcr-1 gene. Genetic analyses identify 92 accessory genes and 60 single-nucleotide polymorphisms associated with the cef^Razi^R phenotype. Surveillance of this clone is required to determine its dissemination and threat to global public health.

Parental coercive and structured feeding practices are linked with children’s weight gain. Thus, identifying their predictors will assist in childhood obesity prevention. We explored how parents’ concerns and perceptions of children’s weight, parenting stress, parenting competence, parents’ family roles, and only child status (of both parent and child) predict the use of restriction, pressure to eat, and monitoring practices among parents of preschoolers. Parent–child dyads (n = 2990) were recruited in Beijing in 2019. Parenting competence, parents’ weight perceptions and feeding practices were assessed using the Chinese version of Parenting Sense of Competence Scale and Child Feeding Questionnaire (CFQ), respectively. Parenting stress and other variables were collected through self-administered questionnaires. Multivariate linear associations between parents’ weight perceptions and feeding practices were significant among normal-weight children. Parents’ concerns about children being overweight were positively associated with restriction and monitoring, and negatively associated with pressure to eat. Higher levels of parenting stress and parenting competence significantly improved the adoption of restriction and pressure to eat. Parents’ only child status and that of children had an impact on parents’ feeding practices. The fathers’ feeding preferences were substantially different from what mothers preferred. In conclusion, such parenting and family characteristics significantly influenced feeding practices of preschoolers’ parents. These were long neglected in China.

The excessive consumption of sugar-sweetened beverages (SSBs) has been proven to be critical for obesity among preschoolers. This study aimed to describe the SSB consumption rates among preschoolers in the Dongcheng District of Beijing, China, and to explore the association between obesogenic environmental determinants and consumption. We applied a stratified cluster sampling method and recruited 3057 primary caregivers of preschoolers in June 2019 to participate in the survey. The caregivers reported their children’s consumption rates of six categories of SSBs and their exposure rates to SSB-related obesogenic environments. The associations between them were tested using multivariate logistic regression models. The mean (SD) age of the children was 5.6 (0.6) years and nearly half (48.3%) were girls. About 84.5% of the children had consumed SSBs over the past three months, and sugar-sweetened milk beverages had the highest consumption rate. Higher exposure to advertisements for the corresponding SSB categories in children, higher frequency rates of consuming SSBs and of taking children to fast-food restaurants in caregivers, and lower frequency rates of reading the Nutrition Facts Panels by caregivers were associated with higher SSB consumption rates among children (p < 0.05 in all of the SSB categories investigated, except for the Nutrition Facts Panel reading behaviors for the sports and energy beverages). SSB consumption among preschoolers is of concern, and comprehensive policy actions and education are urgently needed.

ObjectiveTo determine which early-stage variables best predicted the deterioration of coronavirus disease 2019 (COVID-19) among community-isolated people infected with severe acute respiratory syndrome coronavirus 2 and to test the performance of prediction using only inexpensive-to-measure variables. MethodsMedical records of 3145 people isolated in two Fangcang shelter hospitals (large-scale community isolation centers) from February to March 2020 were accessed. Two complementary methods-machine learning algorithms and competing risk survival analyses-were used to test potential predictors, including age, gender, severity upon admission, symptoms (general symptoms, respiratory symptoms, and gastrointestinal symptoms), computed tomography (CT) signs, and comorbid chronic diseases. All variables were measured upon (or shortly after) admission. The outcome was deterioration versus recovery of COVID-19. ResultsMore than a quarter of the 3145 people did not present any symptoms, while one-third ended isolation due to deterioration. Machine learning models identified moderate severity upon admission, old age, and CT ground-glass opacity as the most important predictors of deterioration. Removing CT signs did not degrade the performance of models. Competing risk models identified age >= 35 years, male gender, moderate severity upon admission, cough, expectoration, CT patchy opacity, CT consolidation, comorbid diabetes, and comorbid cardiovascular or cerebrovascular diseases as significant predictors of deterioration, while a stuffy or runny nose as a predictor of recovery. ConclusionsEarly-stage prediction of COVID-19 deterioration can be made with inexpensive-to-measure variables, such as demographic characteristics, severity upon admission, observable symptoms, and self-reported comorbid diseases, among asymptomatic people and mildly to moderately symptomatic patients.