Strain-deformation Reconstruction of Carbon Fiber Composite Laminates Based on BP Neural Network

The Carbon Fiber Reinforced Polymer (CFRP) laminate structural components used in the aerospace and military domains require high precision and strong stability. Usually the deformation of these structural components is difficult to be measured directly during operation, but the deformation of the CFRP laminate structure can be reconstructed with strain information. The CFRP laminate structure can be designed to adapt to the requirements of different applications through layering of variable thickness. In this paper, aiming at the discontinuous stiffness and strength of the variable laminations within the CFRP laminate structure, the BP neural network is proposed to be applied to the deformation reconstruction of CFRP laminates. With strain as input and deformation as output, based on a large amount of experimental data, the BP neural network model between strain and deformation is obtained through training. In this paper, CFRP test piecs with equal thickness and variable thickness were designed, and the corresponding strain-deformation reconstruction experimental system was constructed. The strain on the surface of CFRP test piece was measured by the fiber grating sensor, and the deformation of the test piece was measured by the laser displacement sensor. The comparative analysis between the predicted deflection obtained by neural network reconstruction and the actual measured deflection shows that BP neural network can reconstruct the structural deformation of CFRP laminates within certain error range.</div

Data for: Dynamic Design and Vibration Testing of CFRP Drive-line System Used in Heavy-duty Machine Tool

The data provide the vibration testing results, data matrix of transfer matrix method and the FEA. The vibration testing results include the acceleration, frequency response and vibration displacement of both CFRP and metal driveline in each testing speed

MOESM1 of IFN-γ down-regulates the PD-1 expression and assist nivolumab in PD-1-blockade effect on CD8+ T-lymphocytes in pancreatic cancer

Additional file 1: Figure S1. The average tumor sizes of 0.1 μg/ml mAb-IFN-γ, IFN-γ, 0.1 μg/ml mAb and Ctrl groups on 31 days after the injection of BxPC-3 cells

Additional file 1 of A pyroptosis-related gene signature predicts prognosis and immune microenvironment in hepatocellular carcinoma

Additional file 1: Figure S1. Consensus clusters by PRGs in TCGA cohort. Figure S2. DEGs and TMB scores of the clusters 1 and 2. Figure S3. Screening of four PRGs signature genes. Figure S4. The expressions of four prognostic PRGs in high- and low-risk groups. Table S1. Names of 30 pyroptosis-related genes

Additional file 3 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 3: Table S2. Protein kinase like domain associated genes

Additional file 4 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 4: Table S3. Levels of transcriptome and protein phosphorylation of genes in HIF-1 signaling

Additional file 2 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 2: Table S1. Proteins identified by proteomic

Additional file 1 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 1: Figure S1. a Representative flow cytometry plots for CD44 and CD24 expression in human pancreatic cancer HPC-Y5 cells with DMSO or fisetin treatment. Cells were treated with fisetin (100 µM) for 48 h. b Statistical plot of ratio of CD44 + /CD24 + positive and CD44-/CD24- negative cells in control or fisetin treatment HPC-Y5 cells. Data are presented as mean ± SD (n = 3); *P  1.5). d Heat map of Biological Process in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S2. Heat map of Cellular Component in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S3. Heat map of Molecular Function in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S4. a Heat map of KEGG pathway enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Enrichment pathways of Q1 and Q2 indicated proteins in important pathways including PI3K–Akt signaling, pathways in cancer, metabolism pathways and ECM-receptor interaction were declined in PANC-1 cells with fisetin treatment. b Heat map of protein domain enrichment analysis of differentially expressed proteins in each Q subset. Enrichment protein domain of Q1 and Q2 indicated proteins with EGF-like domain and Laminin EGF domain were reduced by fisetin treatment. c Protein domain enrichment analysis of whole differentially expressed proteins quantified by proteomics analysis. Figure S5. a Summary of acetylated sites and proteins quantified by acetyl-proteomics analysis. b Summary of differentially expressed acetylated sites and proteins quantified by acetyl-proteomics analysis. 368 sites were changed over 1.2-folds (P < 0.05) including 307 up-regulated and 61 down-regulated in 264 proteins. c Go enrichment analysis of differentially expressed acetylated proteins. d Immunoprecipitation and western blot determined that EP300 was acetyl-transferase of CDK1. Figure S6. Protein motif analysis was performed by statistical analysis of the patterns of amino acid sequences before and after all acetylated sites in samples. 19 types of conserved motifs were identified by motif analysis. Figure S7. a Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in adherent PANC-1 cells or spheres generated from PANC-1 cells. Adhe, adherent cells. b Inhibition of CD44 and Sox2 by CDK1 silencing can be rescued by over-expressing STAT3. Expression of CD44, Sox2, CDK1, STAT3, p-CDK1 and p-STAT3 were examined by western blot analysis. c Inhibition of CDK1-STAT3 signaling by fisetin in purified pancreatic cancer stem cell spheres. Expression of CD44, Sox2, CDK1, STAT3, p-CDK1 and p-STAT3 were performed by western blot analysis. d-e Direct suppression of purified pancreatic oncospheres by fisetin. Second generation of PANC-1 and HPC-Y5 cells from oncospheres were subjected to the tumor sphere-formation assay in ultra-low cluster plates. After the cultivation process to initial point, these tumor spheres were treated with or without fisetin (100 μM) for 48 h. Scale bars, 100 μm. Data are presented as mean ± SD (n = 3),*P < 0.05; ns, no significance. Figure S8. a HDAC3 silencing reduced levels of p-CDK1, p-STAT3, CD44 and Sox2. Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in HDAC3 silencing PANC-1 cells. b-c Lack of HDAC3 weakened tumor sphere formatting capacity in PDAC cells. Scale bars, 100 μm. Data are presented as mean ± SD (n = 4); *P < 0.05. d HDAC3 over-expression increased levels of p-CDK1, p-STAT3, CD44 and Sox2. Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in HDAC3 over-expression PANC-1 cells. e–f Over-expressing HDAC3 enhanced the sphere formatting capacity both in PANC-1 and HPC-Y5 cells. Scale bars, 100 μm. Data are presented as mean ± SD (n = 4); *P < 0.05, **P < 0.01. g Fisetin reduced expression of HDAC3 both in PANC-1 and HPC-Y5 cells. Figure S9. a Fraction-affected (Fa) and CI are explored after 48-h incubation with fisetin and gemcitabine combination, CI < 1 represents synergy. b Representative section of magnetic resonance imaging (MRI) for spontaneous pancreatic ductal adenocarcinoma in KPC mice. Figure S10. a Western blot analysis was used to determine expression of CDK1 in stable CDK1 knockout PANC-1 cells. CDK1-KO: CDK1-knockout. b Quantification of relative phosphorylation of CDK1 was performed by analyzing western blot results with image J software. The relative phosphorylation of CDK1 was significant reduced in PANC-1 and HPC-Y5 cells with fisetin (100 μM) treatment. Fis, fisetin; *P < 0.05; ns, no significance. c qRT-PCR showed that mRNA expression of CDK1 was not influenced by fisetin treatment in pancreatic cancer cells. Data are presented as mean ± SD (n = 3). ns, no significance. d Proteasome inhibitor MG132 restore the expression of CDK1 in PDAC cells with fisetin treatment. PANC-1 and HPC-Y5 ells were cultured with or without fisetin (100 μM) treatment for 48 h. Before the collection of cells, MG132 (10 μM) were added to culture medium for 0, 6 and 12 h. h, hours. e Immunoprecipitation and western blot determined that fisetin induced prominent ubiquitination of CDK1 in pancreatic cancer cells. IP, immunoprecipitation. Ub, ubiquitin. Figure S11. a Western blot analysis was used to determine phosphorylation of CDK1 at Thr14 and Thr161 residues in pancreatic cancer PANC-1 and HPC-Y5 cells. p-CDK1(T161): phosphorylation of CDK1 at Thr161; p-CDK1(T14): phosphorylation of CDK1 at Thr14

Additional file 5 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 5: Table S4. Levels of transcriptome and protein phosphorylation of genes in JAK–STAT signaling