Additional file 1 of Whole-brain dopamine transporter binding pattern predicts survival in multiple system atrophy

Additional file 1: Supplementary Methods. Figure S1. The schematic flow of the study design. Table S1. Clinical diagnosis of the training cohort. Table S2. The demographic characteristics of the training cohort and MSA patients. Table S3. Binding ratios for each striatal regions in clusters. Table S4. Clinical and image-based characteristics of clusters. Table S5. Results of survival analysis using clinical and PET imaging factors

MOESM1 of Comprehensive gene expression analysis for exploring the association between glucose metabolism and differentiation of thyroid cancer

Additional file 1 Figure S1. Plots for GLUT and glycolysis signatures in PTC with different cell types. (A) Box and whiskers plot of GLUT signature in PTC according to cell type (Classical cell type 20.13 ± 1.32 vs. Follicular cell type 18.42 ± 1.20, t = 11.55, p < 0.001) (B) Box and whiskers plot of glycolysis signature in PTC according to cell type (Classical cell type − 0.13 ± 0.94 vs. Follicular cell type 0.52 ± 1.12, t = − 5.65, p < 0.001) (C) Scatter plot of TDS versus glucose metabolism signature in classical cell type PTC (r = − 0.47, p < 0.001 for GLUT; r = 0.23, p < 0.001 for glycolysis) (D) Scatter plot of TDS versus glucose metabolism signature in follicular cell type PTC (r = 0.43, p < 0.001 for GLUT; r = 0.34, p = 0.001 for glycolysis

MOESM2 of Comprehensive gene expression analysis for exploring the association between glucose metabolism and differentiation of thyroid cancer

Additional file 2 Figure S2. Box and whisker plot of glycolysis signatures by N-stage or M-stage in PTC. The line across each box represent the median, and the top edge, and the bottom edge represents the first quartile, and the third quartile, respectively. Student’s t-test showed significant difference of signatures of glycolysis between N positive and N negative groups (N negative group 0.13 ± 1.03 vs. N positive group − 0.24 ± 0.89, t = 3.86, p = 0.0001). No significant difference of signatures of glycolysis were found between M positive and M negative groups (M negative group − 0.08 ± 1.03 vs. M positive group − 0.16 ± 0.89, t = 0.22, p = 0.82). (*** = p < 0.001

Additional file 2 of The role of 99mTc-DPD bone SPECT/CT in the management of growth disturbance of the long bones in pediatric patients: a retrospective observational study

Supplementary Material

Additional file 1 of The role of 99mTc-DPD bone SPECT/CT in the management of growth disturbance of the long bones in pediatric patients: a retrospective observational study

Supplementary Material

Characterization and Cancer Cell Specific Binding Properties of Anti-EGFR Antibody Conjugated Quantum Dots

Synthesis of biologically active antibody conjugated quantum dots (QDs) has been of great importance in cellular imaging and diagnostics. Cetuximab (or Erbitux) is the first monoclonal antibody drug which targets the epidermal growth factor receptor (EGFR) overexpressed in most cancer cells. In the present work, we investigated three different conjugation strategies to obtain the biologically functional QD−cetuximab conjugates for the tumor-specific imaging. Successful conjugation of cetuximab to QDs was achieved using PEG conjugated polymer-coated QDs and two long-chain heterobifunctional linkers, sulfo-LC-SPDP and sulfo-SMCC. The dissociation constant of the QD−cetuximab conjugates to EGFR was determined to be 0.61 ± 0.28 nM. The cancer cell-specific binding ability of the QD−cetuximab conjugates was evaluated in vitro, and the cellular internalization of the QD−cetuximab conjugates was clearly demonstrated in live cells by confocal microscopy. The cellular imaging experiments using the QD−cetuximab conjugates showed a clear endocytosis pathway, which was evidenced by the colocalization of the QD−cetuximab conjugates with dye-labeled transferrin. These results suggest that the QD−cetuximab conjugates as an imaging modality for tumor EGFR overexpression can be expected to provide important information on the expression levels of EGFR on the cancer cells

Patient characteristics.

Patient characteristics.</p

Univariate and multivariate analyses for determining SUV_max.

Univariate and multivariate analyses for determining SUVmax.</p

Univariate and multivariate analyses for determining SUV_max using ≥ 10% for AR positivity.

AR: androgen receptor. (DOCX)</p

Correlations of AR with expression of FA β-oxidation-associated genes and GLUT1.

AR expression show positive correlation with FA oxidation (A) and negative correlation with GLUT1 expression (B). AR, expression level of androgen receptor gene; FA, fatty acid; FA oxidation, gene set enrichment score of FA β-oxidation-associated genes; GLUT1, expression level of GLUT1 (SLC2A1) gene.</p