Additional file 2: Fig. S1. Mutation profiles of newly diagnosed DLBCL patients based on (A) plasma ctDNA (N = 52) and (B) tumor gDNA (N = 43) in this cohort. Fig. S2. Correlation between pretreatment ctDNA levels and 1) known prognostic factors, including baseline LDH (A), IPI score (B), B symptoms (C), Ann Arbor stage (D), 2) the response to the first-line treatment (E). Undetectable ctDNA was assigned the value of 0 Log hGE/mL. Fig....

Additional file 1: Figure S1. Pan-cancer analysis of ACE2 expression in tumor and para-tumor tissues in the TCGA database. Significance was calculated with Student’s t-test. ns-P>0.05, *P<0.05, **P<0.01, ***P<0.001, ****P < 0.0001. Figure S2. Pan-cancer analysis of the correlations between ACE2 and immunological features. (A) Correlations between ACE2 and 122 immunomodulators (chemokines, receptors, MHC and immunostimulators). The color reveals the correlation coefficient. The asterisks reveal statistical differences assessed by Pearson analysis. (B) Correlations between ACE2...

Additional file 2: Figure S2. Articles uploaded to the WeChat officialaccount.

Additional file 3: Figure S3. Screenshots of parents and doctorscommunicating with each other in the WeChat group.

Additional file 6: Table S3. Acceptance of WeChat among intervention group and control group.

Additional file 2: Table S2. RNA oligos used in the study.

Additional file 1. Supplementary materials for the prediction and prognosis of adverse maternal and foetal/neonatal outcomes in pulmonary hypertension.

Additional file2. Fig S2: Association analysis of ten cuproptosis-related genes (CRGs), and DEGs screening of Cluster 3 and Cluster 1. (A) Protein interaction relationships of the ten CRGs (the larger the area of the circle, the stronger the association with other genes). (B) The correlations plot of the ten CRGs. (C) The volcano map of differentially expressed genes (DEGs) between Cluster 1 and Cluster 2. (D) Changes in the trajectory of each independent variable of...

Additional file 1. Supplement figures (Figs. S1–S15), materials and methods.

Additional file 21: Supplementary Table 10. The average sequencing depth and standard deviation for each dataset in this study.

Additional file 22: Supplementary Table 11. Spiked recoveries and relative standard deviations of short chain fatty acids in plasma and feces.

Additional file 23: Supplementary Figure 12. SCFAs for external standard curves and control environmental acetate contamination. (a), (b) and (c) External standard curves of short-chain fatty acids (acetic acid, propionate, butyrate) standards in plasma samples. (d), (e) and (f) External standard curves of short-chain fatty acids (acetic acid, propionate, butyrate) standards in faecal samples. (g) Peak time of acetonitrile. (h) Peak time of acetic acid.

Additional file 25: Supplementary Table 13. Univariate and multivariate regression analysis of risk factors for vascular calcification in the participants with faecal samples.

Additional file 7: Supplementary Figure 3. Attenuation of macrophage infiltration and expression of TNF-α in calcified vessel walls by oral propionate administration. (a) Immunofluorescence staining for macrophages and TNF-α in calcified vessel walls (original magnification ×100). (b) Quantitative analysis of the CD68-positive area. (c) Quantitative analysis of the TNF-α-positive area. Data are presented as the mean ± standard deviation (SD). Statistical significance was determined using one-way ANOVA (Tukey’s post hoc test). ***P< 0.001, ****P< 0.0001.

Additional file 9: Supplementary Figure 5. Amelioration of intestinal microbiota imbalance in rats by rectal propionate administration. (a) Principal coordinate analysis (PCoA) diagram showing the β-diversity of the intestinal microbiota among the three groups. (b) and (c) α-diversity of the intestinal microbiota. (d) Relative abundance of intestinal microbiota constituents at the phylum level. (e) Analysis of the differences in the intestinal microbiota by LEfSe. (f) Spearman’s correlation analysis of the relationship of the intestinal microbiota...

Additional file 1: Table S1. Baseline demographics of MSA. Table S2. The comparison of frequency of each NMSS domain at baseline and 1- and 2-year follow-up.

Hematological indices assist in predicting clinical outcomes. To explore changes of hematological indices on oropharynx squamous cell carcinoma (OPSCC) patients received radiotherapy and their association with survival. The white blood cell count (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), hemoglobin (Hb), platelet (Plt), albumin (Alb), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at baseline, 1-, 3-, 6- and 12-months follow-up were retrospectively collected. The trajectory of indices was described. A linear model with...

Additional file 2. Supplementary tables.

Additional file 6.

Additional file 6.

Additional file 7.

Additional file 2: Supplementary Table 1. Independent sample test of age.

Additional file 1.

Additional file 2: Fig. S2. The biopanning results of the IL-5-specific Nbs library.

Additional file 3: Fig. S3. Original, full-length gel images.