Additional file 2: Fig. S1. A Schematic diagram of the genomic locus of CEBPA-DT (www.ncbi.nlm.nih.gov/). B The protein-coding potential of CEBPA-DT predicted by Open reading frame (ORF) Finder software prediction ( https://www.ncbi.nlm.nih.gov/orffinder/ ). C The protein-coding potential of CEBPA-DT predicted by Coding-Potential Assessment Tool ( wlcb.oit.uci.edu/cpat/ ).

Additional file 6: Fig. S5. A-B The expression levels of DDR2 were measured by western blot and RT-qPCR in indicated HCCLM9 and SNU-449 cells transfected with negative control siRNA or siRNAs targeting DDR2. C-D Cell migration capacity of indicated HCCLM9 and SNU-449 cells were measured by scratch wound-healing assays. Scale bar, 100μm. E-F Cell migration and invasion capacity of indicated HCCLM9 and SNU-449 cells were measured by transwell migration and matrigel invasion assays. Scale bar,...

Additional file 7: Fig. S6. A-B Scratch wound-healing assays showed cell migration capacity of indicated Hep3B and Huh7 cells stably transfected with lentivirus of shDDR2 vectors and control/ CEBPA-DT overexpressing vectors. Scale bar, 100μm. C-D Transwell migration and matrigel invasion assays showed cell migration and invasion capacity of indicated Hep3B and Huh7 cells stably transfected with lentivirus of shDDR2 vectors and control/ CEBPA-DT overexpressing vectors. Scale bar, 100μm. E Representative images (fluorescence) of lung metastatic...

Additional file 1: Fig. S1 The distributions of variant allele frequencies (VAFs) of ARID1A, ARID1B, ARID2, PBRM1, SMARCA4, and SMARCB1. The median VAFs of the above genes were 16.1%, 13.4%, 13.3%, 17.2%, 15.2%, and 16.7%, respectively. Red solid line, median; black dotted line, quartiles.

Additional file 3: Fig. S3 The signaling pathway enrichment of the variated genes in the SWI/SNF-mutant tumors by GO analysis. The GO analysis was performed on all the mutated genes in 1001 SWI/SNF-mutant samples.

The fitted trees for evolutionary analyses using MEME, SLAC, FUBAR method

Supplementary figures 1-4

Supplemental material, sj-jpg-1-inq-10.1177_00469580231153274 for Criminal Litigation of Workplace Violence in Chinese Hospitals and Legal Effort to Deescalate Crimes by Heng Li, Dajun Gao, Yanjie Guan and Chang Xu in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental material, sj-jpg-1-inq-10.1177_00469580231153274 for Criminal Litigation of Workplace Violence in Chinese Hospitals and Legal Effort to Deescalate Crimes by Heng Li, Dajun Gao, Yanjie Guan and Chang Xu in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental material, sj-jpg-2-inq-10.1177_00469580231153274 for Criminal Litigation of Workplace Violence in Chinese Hospitals and Legal Effort to Deescalate Crimes by Heng Li, Dajun Gao, Yanjie Guan and Chang Xu in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental material, sj-jpg-2-inq-10.1177_00469580231153274 for Criminal Litigation of Workplace Violence in Chinese Hospitals and Legal Effort to Deescalate Crimes by Heng Li, Dajun Gao, Yanjie Guan and Chang Xu in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Head and neck squamous cell carcinoma (HNSCC) remains a dreadful malignancy bearing poor clinical efficacy, with emerging evidences indicating RNA-binding proteins’ (RBPs’) relevance to the evolution of the disease. Categorized as RBPs, the K-homology domain-containing 1 (KHDC1) family is proved to be closely related to cell survival and death. As a novel KHDC1 member, only one study is currently available in osteoarthritis synovial cells to unveil KHDC1L’s function of promoting proliferation. Nevertheless, to the best...

Glioma is a common intracranial tumor originated from neuroglia cell. Chrysophanol is an anthraquinone derivative proved to exert anticancer effects in various cancers. This paper investigated the effect and mechanism of chrysophanol in glioma. Glioma cell lines U251 and SHG-44 were adopted in the experiments. The cells were treated with chrysophanol at different concentrations (0, 10, 20 50, 100 and 200 μM) for 48 h in the study, and then processed with MitoTempo. Mitochondria and...

Cutaneous melanoma (CM) is a malignant and aggressive skin cancer that is the leading cause of skin cancer-related deaths. Increasing evidence shows that immunity plays a vital role in the prognosis of CM. In this study, we developed an immune-related gene pair (IRGP) signature to predict the clinical prognosis of patients with CM. Immune-related genes from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected to construct the IRGPs, and...

Owing to the complexity of chemical ingredients in traditional Chinese medicine (TCM), it is difficult to maintain quality and efficacy by relying only on chemical markers. Lianhua Qingwen capsule (LHQW) was selected as an example to discuss the feasibility of a bioassay for quality control. Network pharmacology was used to screen potential targets in LHQW with respect to its anti-inflammatory effects. An in vitro cell model was used to validate the prediction. An anti-inflammatory bioassay...

Owing to the complexity of chemical ingredients in traditional Chinese medicine (TCM), it is difficult to maintain quality and efficacy by relying only on chemical markers. Lianhua Qingwen capsule (LHQW) was selected as an example to discuss the feasibility of a bioassay for quality control. Network pharmacology was used to screen potential targets in LHQW with respect to its anti-inflammatory effects. An in vitro cell model was used to validate the prediction. An anti-inflammatory bioassay...

Coagulation factors participates in the inflammatory cascade, known to play a crucial role in the development of acute kidney injury (AKI). Thus, it’s likely that some factors may be associated with AKI. Among them, low levels of fibrinogen and antithrombin III (ATIII) activity have been proved to increase mortality in patients with sepsis. Moreover, they are also reported to be associated with higher incidence of AKI. However, the association between coagulation parameters, especially fibrinogen and...

The files include supplementary tables and detailed methods used in the manuscript, such as human acetabular cartilage dissociation and nuclei isolation and library construction, and 4 supplementary figures.

To verify the applicability and accuracy of the permeability model in natural and laboratory samples.

Additional file 4: Fig. S4. Effects of cilostazol treatment on complete blood counts after CLP. a, b The level of platelets (a), WBC (b), NEUT (c), MONO (d) and LYMPH (e) (n = 5). WBC, white blood cells; NEUT, neutrophil; MONO, monocyte; LYMPH, lymphocyte. The data are presented as the mean ± SEM, *P < 0.05, ***P < 0.001, and ns indicates no significant difference.

Additional file 5: Fig. S5. Association between DNA methylation and gene expression levels. (A-B) Scatter plots showing correlation between gene expression level and promoter methylation level (A) and first exon (B). (C) Box plot showing promoter methylation level of genes grouped by expression levels. (D-F) Scatterplots and fitting curves of DNA methylation and relative gene expression of gene body methylation (D), exon methylation (E) and intron methylation (F). (G-I) MetGDE genes selected based on the...

Additional file 5: Supplementary Figure S5. The ROC curves for the risk model in the four GCs. A-C The ROC curves of CESC for training (A), validation (B), and total (C) sets. D-F The ROC curves of OV for training (D), valida©n (E), and total (F) sets. G-I The ROC curves of UCEC for training (G), validation (H), and total (I) sets. J-L The ROC curves of UCS for training (J), validation (K), and total...

Additional file 7: Supplementary Figure S7. Clinical value of risk score by independent prognostic analysis. A-H The Univariate Cox regression analysis and Multivariate Cox regression analysis for CESC (A-B), OV (C-D), UCEC (E-F), and UCS G-H.

Additional file 8: Supplementary Figure S8. The Nomogram model based on risk model and clinical features for GCs. A-B The Nomogram (A) and calibration curve (B) for CESC. C-D The Nomogram (C) and calibration curve (D) for OV. (E-F) The Nomo©m (E) and calibration curve (F) for UCEC. G-H The Nomogram (G) and calibration curve (H) for UCS.

Additional file 7: Fig. S7. Effect of LPS and CD40L on TRAFs proteins in EGCs. a Representative western blot images of TRAFs proteins expression in EGCs. b-g Western blot analysis of TRAF1 (b), TRAF2 (c), TRAF3 (d), TRAF4 (e), TRAF5 (f) and TRAF6 (g) expression in different groups of EGCs (n = 6). The data are presented as the mean ± SEM, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.