Coronary artery-left ventricular fistula

Cardiology683167-179CAGY

Synthesis of Ti(C, N, O) coatings by unbalanced magnetron sputtering

Several TiCNO coatings were deposited using an unbalanced magnetron sputtering system. The composition of C, N, 0 was first studied using GDOS (glow discharge optical spectrometer). The coating properties as a function of oxygen/nitrogen flow ratio were then studied by using SEM, scratch testing and nano-indentation measurement. The tribological. properties of the coatings were then investigated using a ball-on-disk setup with alumina balls. The sliding speeds were set at 10, 20, and 30 cm/min. The results show that coating properties and performance are greatly affected by the flow rate of oxygen. With oxygen flow rate set at 4 seem during deposition, the TiCNO coating shows the lowest wear rate and friction coefficient among all. Further increase in oxygen flow rate caused a decrease of wear resistance with the increase of friction coefficient. The wear debris were analyzed using Raman spectroscopy. The tribological behavior of the selected TiCNO coating was also compared with other Ti-based hard coatings. (C) 2003 Elsevier B.V All rights reserved

Erratum: An intrinsic mechanism controls reactivation of neural stem cells by spindle matrix proteins

10.1038/s41467-017-01017-1Nature communications81129

The medical, functional and social challenges faced by older adults with intellectual disability

Annals of the Academy of Medicine Singapore427338-349AAMS

Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial

Objective To date, there are no predictive biomarkers to guide selection of patients with gastric cancer (GC) who benefit from paclitaxel. Stomach cancer Adjuvant Multi-Institutional group Trial (SAMIT) was a 2x2 factorial randomised phase III study in which patients with GC were randomised to Pac-S-1 (paclitaxel +S-1), Pac-UFT (paclitaxel +UFT), S-1 alone or UFT alone after curative surgery. Design The primary objective of this study was to identify a gene signature that predicts survival benefit from paclitaxel chemotherapy in GC patients. SAMIT GC samples were profiled using a customised 476 gene NanoString panel. A random forest machine-learning model was applied on the NanoString profiles to develop a gene signature. An independent cohort of metastatic patients with GC treated with paclitaxel and ramucirumab (Pac-Ram) served as an external validation cohort. Results From the SAMIT trial 499 samples were analysed in this study. From the Pac-S-1 training cohort, the random forest model generated a 19-gene signature assigning patients to two groups: Pac-Sensitive and Pac-Resistant. In the Pac-UFT validation cohort, Pac-Sensitive patients exhibited a significant improvement in disease free survival (DFS): 3-year DFS 66% vs 40% (HR 0.44, p=0.0029). There was no survival difference between Pac-Sensitive and Pac-Resistant in the UFT or S-1 alone arms, test of interaction p<0.001. In the external Pac-Ram validation cohort, the signature predicted benefit for Pac-Sensitive (median PFS 147 days vs 112 days, HR 0.48, p=0.022). Conclusion Using machine-learning techniques on one of the largest GC trials (SAMIT), we identify a gene signature representing the first predictive biomarker for paclitaxel benefit

Genomic and Epigenomic Profiling of High-Risk Intestinal Metaplasia Reveals Molecular Determinants of Progression to Gastric Cancer

10.1016/j.ccell.2017.11.018Cancer Cell331137-150 e5CCAE

Thermal cycles, interface chemistry and optical performance of Mg/SiC multilayers

68.65.Ac Multilayers, 61.05.cm X-ray reflectometry (surfaces, interfaces, films), 78.70.En X-ray emission spectra and fluorescence, 73.90.+f Other topics in electronic structure and electrical properties of surfaces, interfaces, thin films, and low-dimensional structures, 66.30.Ny Chemical interdiffusion; diffusion barriers, 68.35.Fx Diffusion; interface formation,