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Interference in cell cycle progression has been noted as one of the important properties of anticancer drugs. In this study, we developed the cell cycle prediction model using high‐content imaging data of recipient cells after drug exposure and DNA‐staining with a low‐toxic DNA dye, SiR‐DNA. For this purpose, we exploited HeLa and MCF7 cells introduced with a fluorescent ubiquitination‐based cell cycle indicator (Fucci). Fucci‐expressing cancer cells were subjected to high‐content imaging analysis using OperettaCLS after 36‐h exposure to anticancer drugs; the nuclei were segmented, and the morphological and intensity properties of each nucleus characterized by SiR‐DNA staining were calculated using imaging analysis software, Harmony. For the use of training, we classified cells into each phase of the cell cycle using the Fucci system. Training data (n = 7500) and validation data (n = 2500) were randomly sampled and the binary classification prediction models for G1, early S, and S/G2/M phases of the cell cycle were developed using four supervised machine learning algorithms. We selected random forest as the model with the best performance through 10‐fold cross‐validation; the accuracy rate was approximately 75%–87%. Regarding feature importance, variables expected to be biologically related to the cell cycle, for example, signal intensity and nuclear size, were highly ranked, suggesting the validity of the model. These results showed that the cell cycle can be predicted in cancer cells by simply exploiting the current prediction model using fluorescent images of DNA‐staining dye, and the model could be applied for the use of future ex vivo drug sensitivity diagnosis. [ABSTRACT FROM AUTHOR]

From May 1976 to June 2001, 95 porcine heart valve bioprostheses (BPs) were explanted. Among them, 85 prostheses were available for an analysis of structural valve deterioration (SVD). There were 32 Hancock (H) BPs and 53 Carpentier-Edwards (CE) BPs, with a mean implantation duration of 12 ± 3.5 and 11.0 ± 4 years, respectively. There were two extraordinary complications. One was commissural dehiscence (CD) of the CEBPs in 10/53 cases (18.9%), with a mean duration of 12.7 ± 2.7 years. This was not observed in the HBPs. The other was pannus formation in both BPs. In the mitral position, it was 25/32 (78.1%) in HBPs and 37/53 (69.8%) in CEBPs. In the aortic position, it was 4/32 (1.3%) in the HBPs and 11/53 (20.8%) in the CEBPs. We conclude that CD could not be diagnosed preoperatively and anticoagulation is therefore indicated to prevent pannus formation of such prostheses, particularly in those located in the mitral position. [ABSTRACT FROM AUTHOR]

Background: Coronary artery bypass grafting (CABG) for hemodialysis patients is high risk compared with other patient groups. The aim of this study was to analyze the potential benefits of off-pump CABG for hemodialysis patients., Methods: From April 1994 through December 2000, 26 hemodialysis patients underwent CABG. The off-pump group consisted of 15 patients operated on without a pump and the on-pump group consisted of 11 patients operated on with a pump., Results: There was no difference between the two groups with regard to mean age, mean number of diseased vessels and mean number of anastomoses per patient. No patient died in either group during hospitalization. The postoperative complication rate was low in both groups. The postoperative ventilation time was shorter in the off-pump group (8.5 vs 26.1 hours, p < 0.001, respectively [off-pump group vs on-pump group]). The length of ICU stay was shorter in the off-pump group (1.7 vs 3.5 days, p = 0.01, respectively [off-pump group vs on-pump group]). The medial cost was lower in the off-pump group (26,200.80 dollars versus 44,024.10 dollars p = 0.0001 respectively [off-pump group vs on-pump group])., Conclusions: Off-pump CABG provided excellent less-invasive cardiac surgical results for dialysis patients.