Additional file 1: Supplementary figure 1.

Additional file 2. Figure S1: Boxplots of GSE84437 (a) and GSE62254 (b) expression profile data.

Additional file 2: Figure S2. Expression of ILPs and InR in different tissues of female adults.

Additional file 4: Figure S4. The body size of the female and male adults after feeding dsRNA.

Additional file 7: Figure S5. Identification of circPVRL3, and effects of circPVRL3 on proliferation, EMT and the activity of PI3K/AKT signaling pathway in PDAC. (A) The convergent and divergent primers were used for detecting the circular or linear form to verify that circPVRL3 was only amplified in cDNA used by RT‒qPCR and agarose gel electrophoresis. GAPDH served as a control. (B) Total RNA derived from PANC-1 cells was extracted and treated with or without RNase...

Additional file 1: Figure S1. Quantile-quantile (QQ) plot on Serum AST, ALP, LDH, HBDH, UA and TG.

Additional file 3: Figure S3. Manhattan and quantile-quantile (QQ) plot on Serum P, CHO, HDL-C, LDL-C, LP(a) and CK.

Additional file 3 : Fig. S3. Signaling Pathways Regulated by Genes Correlated with GLUT1 and JUN in Breast Cancer. a. Focal adhesion. b. ECM-receptor interaction.

Additional file 8: Figure S6. Construction of HNRNPL knockdown T24 and UMUC3 cells. A. GO analysis was conducted on the proteins pulled down by flanking introns probe. B. The results of RNAct database predictions and circFAM13B flanking introns relative mass spectrometry analysis were intersected, and HNRNPL and ADAR1 were found. C. The expression of ADAR1 and circFAM13B in T24 or UMUC3 cells were confirmed by qRT-PCR after ADAR1 siRNA transfection (**P<0.01, ***P<0.001, Student’s t-test). D....

Additional file 2: Figure S2. Study design of the current study. CNA: Copy number alteration; SNV: Single nucleotide variation; CNV: Copy number variation. PPI: Protein-protein interaction; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Oncology; MF: molecular functions; CC: cellular components; BP: biological processes; MSI: Microsatellite instability; TMB: Tumor mutational burden.

Additional file 2: Figure S2. Study design of the current study. CNA: Copy number alteration; SNV: Single nucleotide variation; CNV: Copy number variation. PPI: Protein-protein interaction; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Oncology; MF: molecular functions; CC: cellular components; BP: biological processes; MSI: Microsatellite instability; TMB: Tumor mutational burden.

Additional file 5: Figure S5. GA reduced S100A8 expression levels in PBMCs. (A) Cell clustering maps of single-cell sequencing for PBMCs of young, aged, and aged-GA mice. (B) Annotated cell clustering maps of single-cell sequencing for PBMCs in young, aged, and aged-GA mice. (C) Expression levels of S100A8 in young, aged, and aged-GA mice.

Additional file 4: Figure S4. Phylogenetic tree of BRIP1. We used a constraint-based multiple alignment online tool of NCBI to get the phylogenetic tree of BRIP1 in different species.

Additional file 5: Figure S5. The expression levels of BRIP1 in different tumors and in different tissues, blood cells, and brain tissues under the normal physiological state. We analyzed the expression of the BRIP1 gene in different tumors using antibodies of HPA005474 (a), using the consensus datasets of HPA, GTEx, and FANTOM5 to explore the expression of BRIP1 in different tissues (b) and brain tissues (d), using the consensus datasets of HPA, Monaco, and Schmieder...

Additional file 4: Figure S1. Verification of transcriptome accuracy by qRT–PCR. The x-axis represents the DETs, and the y-axis represents the relative expression of the gene. DETs above the horizontal line are upregulated and those below the horizontal line are downregulated. qRT–PCR: quantitative real-time PCR; DETs: differentially expressed transcripts.

Additional file 1: Supplementary Fig. 1. A and D. Numbers of CD8+T cells between adjacent normal tissues and tumor tissues of HCC and ICC are shown by the violin plot, respectively. B and E. Numbers of CD103+ immune cells between adjacent normal tissues and tumor tissues of HCC and ICC are shown by the violin plot, respectively. B and E. Numbers of CD103+CD8+T cells between adjacent normal tissues and tumor tissues of HCC and ICC...

Additional file 5: Figure S5. GA reduced S100A8 expression levels in PBMCs. (A) Cell clustering maps of single-cell sequencing for PBMCs of young, aged, and aged-GA mice. (B) Annotated cell clustering maps of single-cell sequencing for PBMCs in young, aged, and aged-GA mice. (C) Expression levels of S100A8 in young, aged, and aged-GA mice.

Supplementary Material 2

Supplementary Material 2

Supplementary Material 7

Supplementary Material 5

Additional file 5: Fig. S4. Correlation between CD73 expression and tumor immune cell infiltration. (A) ssGSEA analysis revealing the correlation between the CD73 mRNA level and infiltration of 28 immune cell types. Correlation analysis of CD73 and macrophage marker genes CD68 (B), M2 like macrophage marker genes CD163 (C) and CD206 (D). ssGSEA, single sample gene set enrichment analysis. *P < 0.05, ***P < 0.001, ****P < 0.0001.

Additional file 3: Fig. S2. Single-cell atlas of CD73 expression on distinct cell types in ICC. (A) t-SNE plot showing identification of single cells colored by clusters. (B) Dot plot showing the marker genes of identified cell types. (C) Spearman correlation between CD73 and KRT19 mRNA expression in FU-iCCA cohort. ICC, intrahepatic cholangiocarcinoma; tSNE, t-distributed stochastic neighbor embedding.

Additional file 4: Figure S2. The efficacy of prediction model for AKI and severe AKI with different composite inflammatory biomarkers.

Additional file 2: Figure S2. A, Blood neutrophils count and percentage among healthy control (HC) and patients with NEA and EA. B, Correlation between ILC subsets and blood neutrophils count and percentage. **** p < 0.0001, *** p < 0.001, ** p < 0.01, * p < 0.05, ns p > 0.05.