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Zhen-Hua Li,1,&ast; Jie Wang,1,&ast; Xin Cheng,1,&ast; Yi-Cheng Mao,1 Kang-Di Zhang,1 Wen-Jie Yu,1 Ying-Qing Li,1 Kai Huang,1,2 Kun Ding,1 Xiao-Jing Yang,1 Cheng-Yang Hu,3 Xiu-Jun Zhang1,4 1Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 3Department of Humanistic Medicine, School of Humanistic Medicine, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 4Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Cheng-Yang Hu; Xiu-Jun Zhang, Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, People’s Republic of China, Tel/Fax +86 551 65167031 ; +86 551 65169635, Email cy.hu@ahmu.edu.cn; zhangxiujun@ahmu.edu.cnBackground: There is growing evidence that the COVID-19 pandemic has had a dramatic impact on public mental health. However, less attention has been paid to left-behind experience college students (LBEs). This online study aimed to investigate the relationship between psychological capital (PsyCap) and anxiety among LBEs during COVID-19 pandemic, and further analyze the mediation role of self-esteem between them.Methods: A total of 9990 students were chosen using the stratified cluster sampling method. Three self-reported questionnaires were used to assess the PsyCap, self-esteem, and anxiety, respectively. All the statistical analyses were conducted using SPSS 23.0 and R, and to further investigate the mediation effect of self-esteem in the association of PsyCap with anxiety, AMOS 23.0 was used to build a structural equation model.Results: PsyCap, self-esteem, and anxiety were significantly correlated among LBEs during the COVID-19 pandemic. PsyCap affects anxiety directly (β = – 0.22, SE = 0.051, 95% CI: – 0.27, – 0.17, P < 0.05). In addition, self-esteem partially mediated the relationship between PsyCap and anxiety (mediating effect value = – 0.16, 95% CI: – 0.20, – 0.13, P < 0.05).Conclusion: During the pandemic of COVID-19, left-behind experience had a negative influence on the PsyCap and self-esteem of college students. In addition, for LBEs, self-esteem plays an important mediating role between PsyCap and anxiety. Therefore, from the perspective of PsyCap and self-esteem, schools should translate them into practical educational strategies to enhance the mental health and mitigate the anxiety levels of LBEs.Keywords: left-behind experience, COVID-19, psychology, mental health

Additional file 1: Methods. Figure S1. Study flow. HTA, Human Transcriptome Array; ICI, immune checkpoint inhibitor; NMF, non-negative matrix factorization; NPC, nasopharyngeal carcinoma; PSM, propensity score matching. Figure S2. Identification of an NMF immune factor. (A) We applied NMF (k = 5 factors or expression patterns) to analyze the gene expression profiles of nasopharyngeal carcinoma (NPC) samples in the training cohort (n = 113). One of the five factors (green bar) showed the highest ssGSEA scores in both immune enrichment score and 6-gene IFN-γ signature, as shown in the heatmap, indicating that it is an immune factor (or an immune expression pattern). High and low ssGSEA scores are represented in red and blue, respectively. (B) The top 100 exemplar immune factor genes characterized using DAVID confirmed immune-related functions. (C) NMF consensus-clustering of the training cohort using exemplar immune factor genes was refined by random forest classification. As shown in the heatmap, an immune-enriched subtype and a non-immune subtype. The ssGSEA scores of immune enrichment score and 6-gene IFN-γ signature are indicated; high and low scores are represented in red and blue, respectively. NMF, non-negative matrix factorization; NPC, nasopharyngeal carcinoma; ssGSEA, single-sample gene set enrichment analysis. Figure S3. Association of immune subtypes with tumoural genomic features and survival outcome. (A) Box plot showing similar number of non-synonymous mutations among the immune subtypes. (B) Box plot showing similar numbers of gene-level amplifications and deletions among the immune subtypes. (C) Box plot showing significantly higher cell cycling scores in non-IS. The box plot centre corresponds to the median, with the box and whiskers corresponding to the interquartile range and 1.5× interquartile range, respectively. P-values were based on the Kruskal–Wallis rank-sum test. (D) The proportion of CDKN2A deletions was significantly higher in non-IS. P-values were based on the Fisher’s exact test. (E) Kaplan–Meier curves for progression-free survival according to immune subtypes. A trend of better survival was observed for A-IS compared to E-IS and non-IS in 88 patients with available survival outcomes. P-values were calculated by log-rank test. A-IS, active immune subtype; CD4+ Tconv, conventional CD4+ T cells; CD8+ Tcyt, cytotoxic CD8+ T cells; CD8+ Tdys, dysfunctional CD8+ T cells; CD8+ Tnaï, naïve CD8+ T cells; DCs, dendritic cells; E-IS, evaded immune subtype; NK, natural killer; non-IS, non-immune subtype. Figure S4. Genetic similarity of the immune subtypes in different groups of patients from two melanoma ICI cohorts. (A) SubMap analysis of the immune subtypes in validation cohort 1 and four groups (anti-PD-1 responsive and non-responsive, and anti-CTLA-4 responsive and non-responsive) in melanoma ICI cohort 1. (B) SubMap analysis of the immune subtypes in validation cohort 1 and four groups (CR/PR/SD > 12 months, CR/PR/SD 6–12 months, CR/PR/SD 12 months for anti-PD-1 therapy (P = 0.036). A-IS, active immune subtype; CR, complete response; E-IS, evaded immune subtype; ICI, immune checkpoint inhibitor; non-IS, non-immune subtype; PD, progressive disease; PR, partial response; SD, stable disease. Table S1. Clinical cohorts used in this study. Table S2. Publicly available gene signatures used in this study. Table S7. Clinical characteristics of patients in the validation cohort 1 and validation cohort 2 (ICI).