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IntroductionThe mental health of populations is usually affected after a disaster event. However, it is not known what the level of mental health of Chinese population 1 year after COVID-19, nor what factors influence it.AimThis study aimed to examine the mental health status of general population in Chengdu 1 year after COVID-19, and then analyse influencing factors.MethodThis study is a cross-sectional survey based on the SCL-90 questionnaire. Continuous data were described as M and SD, and counting data were described as frequencies(n) and percentages (%). Chi-square test or Fisher’s exact test were used for statistical inference, and significance variables were included in the binary logistic regression equation for multivariate analysis.ResultsThere were 172 participants with positive screening results. Age, marital status, number of kids, self-perceived health and the presence of chronic disease had an effect on screening results. Logistic regression analysis showed that age and self-perceived health were the main influencing factors.DiscussionYoung people aged 18–19 and those who consider themselves not very healthy were at higher risk of poor mental health 1 year after the COVID-19 outbreak.Impact statementCommunity institutions and community workers should focus on the mental health status of people 1 year after COVID-19, with a focus on people with poor self-perceived health and younger age groups, and take early preventive measures.

Abstract Medicinal plants represent a huge reservoir of secondary metabolites (SMs), substances with significant pharmaceutical and industrial potential. However, obtaining secondary metabolites remains a challenge due to their low-yield accumulation in medicinal plants; moreover, these secondary metabolites are produced through tightly coordinated pathways involving many spatiotemporally and environmentally regulated steps. The first regulatory layer involves a complex network of transcription factors; a second, more recently discovered layer of complexity in the regulation of SMs is epigenetic modification, such as DNA methylation, histone modification and small RNA-based mechanisms, which can jointly or separately influence secondary metabolites by regulating gene expression. Here, we summarize the findings in the fields of genetic and epigenetic regulation with a special emphasis on SMs in medicinal plants, providing a new perspective on the multiple layers of regulation of gene expression. Graphical Abstract

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Background: Anti–N-methyl-D-aspartate receptor (NMDAR) encephalitis showing severe neuropsychiatric symptoms is the most common type of autoimmune encephalitis. However, the corresponding standard clinical magnetic resonance imaging (MRI) presents normal or atypical in the majority of patients with anti-NMDAR encephalitis. Here, this study aimed to investigate the alterations in brain functional activity in patients with anti-NMDAR encephalitis and whether these alterations contributed to cognition and mood disorders. Methods: Seventeen patients with anti-NMDAR encephalitis and eighteen gender, age and education-matched healthy controls were recruited. All participants underwent neuropsychological tests (including Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD24)) and resting-state functional MRI. MRI data was firstly analyzed by amplitude of low-frequency fluctuation (ALFF), and brain regions with altered ALFF between groups were selected as regions of interest for the further functional connectivity (FC) analysis. Correlation analyses were performed to investigate the associations between brain dysfunction and neuropsychological performance. Results: Relative to the healthy controls, patients with anti-NMDAR encephalitis performed inferiorly in the MoCA score, and showed anxiety and depression disorders with higher HAMA and HAMD24 scores (all p

The mechanism of maternal in vivo haploid induction is not fully understood. In this study, the young embryos were identified by morphology, cytology and simple sequence repeat (SSR) markers at different developmental stages in the cross HZ514 (sweet corn) × HZI1 (inducer). The results indicated that the low seed setting rate was determined by the inducer pollen during the process of fertilization. The mosaic endosperm kernels and the different percentages of aneuploidy, mixploidy, lagged chromosome, micronuclei, chromosomal bridge and ring chromosome were found in the cross; 7.37% of the haploid embryos carried chromosome segments from HZI1. About 1% twin seedlings resulted from the cross and were analyzed by cytology and SSR markers. Four pairs of twin seedlings had different chromosome numbers (2n = 20 and 2n = 10–20) and there were some chromosome fragments from HZI1. Aneuploidy, mixploidy and the abnormal chromosomes occurred in the in vivo haploid induction by HZI1, which is the cytological basis for haploid induction and indicates that the inducer's chromosomes are prone to be lost during mitotic and meiotic divisions. Morphological, cellular and molecular evidences reveal that complete or partial chromosome elimination from inducer HZI1 controls the maize in vivo haploid induction. DATA: The link refers to the raw data from: Morphological, cellular and molecular evidences of chromosome random elimination in vivo upon haploid induction in maize. Current Plant Biology. Raw data for phenotype, maker sequence and cytology could be directly downloaded by the link: http://dx.doi.org/10.5061/dryad.bt963