Bilateral internal thoracic artery grafting: current state of the art

The purpose of this article is to review the key literature and assess the current status of bilateral internal thoracic artery grafting. Numerous retrospective studies have demonstrated a benefit of bilateral internal thoracic artery grafting over single internal thoracic artery grafting in terms of the long-term risk of all-cause death, cardiac-related death, and cardiac events. The survival benefit of bilateral internal thoracic artery grafting manifests relatively early after operation for high-risk patients. The skeletonization technique reduces the risk of sternal wound complications in all patients and particularly in those with diabetes. Both the left and right internal thoracic arteries have better patency when grated to the left coronary territory than saphenous vein. However, the right internal thoracic artery does not always have good patency when grafted to the right coronary artery. Bilateral internal thoracic artery grafting using the skeletonization technique is recommended for revascularization of the left coronary territory.     

In vitro biocompatibility of dextrin: the addition of a low concentration of dextrin in the medium promotes the cell activity of L929 mouse fibroblasts

To develop a bone substitute with shape-generating properties, we focused our attention on dextrin, which has a low viscosity. After considering methods of evaluation for research and development, we started by using cells that are widely used for safe biological evaluations in the field of dentistry and conducted in vitro evaluations. In this experiment, we variously added concentrations of 0.1, 1.0 and 10 mmol/l of dextrin to a culture medium in order to examine the effects on L929 mouse fibroblasts in vitro. As a result, the proliferative activity of the L929 cells was promoted during the culture period as the concentration of added dextrin became lower, and in particular, the 0.1 and 1 mmol/l addition group showed higher values than those of the control group. From the above results, it was revealed that the addition of a low concentration of dextrin in a medium promotes the cell proliferative activity.     

Software for systems biology: from tools to integrated platforms

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.     

Probabilistic alignments with quality scores: an application to short-read mapping toward accurate SNP/indel detection

MOTIVATION: Recent studies have revealed the importance of considering quality scores of reads generated by next-generation sequence (NGS) platforms in various downstream analyses. It is also known that probabilistic alignments based on marginal probabilities (e.g. aligned-column and/or gap probabilities) provide more accurate alignment than conventional maximum score-based alignment. There exists, however, no study about probabilistic alignment that considers quality scores explicitly, although the method is expected to be useful in SNP/indel callers and bisulfite mapping, because accurate estimation of aligned columns or gaps is important in those analyses. RESULTS: In this study, we propose methods of probabilistic alignment that consider quality scores of (one of) the sequences as well as a usual score matrix. The method is based on posterior decoding techniques in which various marginal probabilities are computed from a probabilistic model of alignments with quality scores, and can arbitrarily trade-off sensitivity and positive predictive value (PPV) of prediction (aligned columns and gaps). The method is directly applicable to read mapping (alignment) toward accurate detection of SNPs and indels. Several computational experiments indicated that probabilistic alignments can estimate aligned columns and gaps accurately, compared with other mapping algorithms e.g. SHRiMP2, Stampy, BWA and Novoalign. The study also suggested that our approach yields favorable precision for SNP/indel calling.