Growth Analysis of Single-Walled Carbon Nanotubes Based on Interatomic Potentials by Molecular Dynamics Simulation

Molecular dynamics simulation was performed to understand the growth mechanism of single-walled carbon nanotubes (SWNTs) by using the Brenner–Tersoff potential as the interaction among carbon atoms (C–C) and the Tersoff-type potential as the interaction between carbon and metal (C–M) and between metal and metal atoms (M–M). The potential functions for C–M and M–M bonds were established from the results of ab initio calculations. The growth of high-quality SWNTs was simulated at a suitable temperature and supply ratio of carbon atoms. The potential energy of carbon atoms was strongly dependent on the number of C–C and C–M bonds. The dependence explains the growth process, including cap formation, its lift-off, and the continuous SWNT growth

Sample collection diagram.

<p>All samples were collected prospectively. Samples were collected from the following three groups; Surgery, Endoscopy, and Healthy Volunteers. Surgery and Endoscopy groups contain Pre (pre-operative plasma), PBMCs, Tumor, and Post (post-operative plasma) samples. Samples from patients showing Stage IV disease, insufficient sample size, or insufficient extracted DNA amount were excluded from the study (detailed information in text). The color of each box indicates which procedures were used for analysis each type of sample.</p

Dynamics of MMs and CEA in pre- and post-operation.

<p>a, MMs monitored with the mutation allele frequency using an Ion PGM. Three, one, and three MMs were used for monitoring cases 1, 2, and 3, respectively. The corresponding serum levels of CEA are shown. b, MMs monitored with the mutation allele frequency by ddPCR. One or two MMs were used for monitoring in the represented cases. The horizontal dotted line shows the upper limit of the normal range of CEA serum levels (3.4 ng/ml). Each number adjacent to each data point is the allele frequency for genes; and serum values for CEA. ^aStop codon, ^bSplice site.</p

Mutation characteristics of colorectal tumors.

<p>a, Mutation types. Six types of mutations were detected with CHPv2. b, Tumor-unique mutation profile according to allele frequency. Each column denotes a tumor-unique mutation of an individual tumor. Each row denotes cancer-associated genes in CHPv2. The color indicates the variant allele frequency indicated in the color bar.</p

Hierarchical clustering of three different matrices and results of immunohistochemical examinations of candidate markers.

<p>(A) Based on a chemosensitivity assay of a cancer cell line panel, the A (activity) × C (cells)  =  AC matrix was created. (B) Quantitative protein expression data of each cell line determined by “reverse-phase” lysate microarray generates the C×P (protein)  =  CP matrix. (C) A heatmap with hierarchical clustering representation of the AP matrix, which is generated from AC and CP matrices. (D) Immunohistochemical stainings of candidate markers for 5-FU treatment.</p

Induction of biomarkers by 5-FU treatment.

<p>(A) Baseline protein expression of NF-κB and JNK in five gastric cancer cell lines. Tublin was used as a loading control. (B) Induction of candidate biomarkers in response to 5-FU treatment in different concentrations in MKN45 and KE39. (C) Examination of protein localization by fluorescent immunocytochemistry using MKN45. (D) Increased inhibitory growth effect by anticancer agents in gastric cancer cell lines after transfection of siRNA for NF-κB p65 and JNK transcripts. Control samples are the corresponding cell lines transfected with the indicated siRNAs without anticancer agents. Abbreviations are: CIS, cisplatinum; DTX, docetaxel; and PXL, paclitaxel; and 5FU, 5-fluorouracil. *<i>p</i><0.05, Student <i>t</i>-test.</p

Time-to-relapse (TTR) rates on the basis of NF-κB and JNK protein expression in gastric and colon carcinomas.

<p>Time-to-relapse (TTR) rates on the basis of NF-κB and JNK protein expression in gastric and colon carcinomas.</p