Chikuma Hamada

Learn More
The recent development of DNA microarray technology allows us to measure simultaneously the expression levels of thousands of genes and to identify truly correlated genes with anticancer drug response (differentially expressed genes) from many candidate genes. Significance Analysis of Microarray (SAM) is often used to estimate the false discovery rate(More)
Mining of gene expression data to identify genes associated with patient survival is an ongoing problem in cancer prognostic studies using microarrays in order to use such genes to achieve more accurate prognoses. The least absolute shrinkage and selection operator (lasso) is often used for gene selection and parameter estimation in high-dimensional(More)
Choosing an appropriate statistic and precisely evaluating the false discovery rate (FDR) are both essential for devising an effective method for identifying differentially expressed genes in microarray data. The t-type score proposed by Pan et al. (2003) succeeded in suppressing false positives by controlling the underestimation of variance but left the(More)
Our objective was to confirm the efficacy and safety of edaravone in amyotrophic lateral sclerosis (ALS) patients. We conducted a 36-week confirmatory study, consisting of 12-week pre-observation period followed by 24-week treatment period. Patients received placebo or edaravone i.v. infusion over 60 min for the first 14 days in cycle 1, and for 10 of the(More)
In the past decade, researchers in oncology have sought to develop survival prediction models using gene expression data. The least absolute shrinkage and selection operator (lasso) has been widely used to select genes that truly correlated with a patient's survival. The lasso selects genes for prediction by shrinking a large number of coefficients of the(More)
Powerful array-based single-nucleotide polymorphism-typing platforms have recently heralded a new era in which genome-wide studies are conducted with increasing frequency. A genetic polymorphism associated with population pharmacokinetics (PK) is typically analyzed using nonlinear mixed-effect models (NLMM). Applying NLMM to large-scale data, such as those(More)
PURPOSE Continuous treatment with FOLFOX therapy is associated with peripheral nerve toxicity, and to improve this inconvenient side effect various methods of administration are being investigated. A regimen of intermittent oxaliplatin administration by continuous infusion therapy, i.e., modified FOLFOX7 (mFOLFOX7) + bevacizumab, was designed with the goal(More)
INTRODUCTION Coronary computed-tomography angiography (CCTA) has high diagnostic performance, but it sometimes does not allow evaluation because of artifacts. Currently, the use of a β-blocker is recommended to prevent motion artifacts, but the β-blocker (metoprolol, propranolol, etc.) commonly used has a slow onset and long duration of action. Landiolol(More)
When identifying the differentially expressed genes (DEGs) in microarray data, we often observe heteroscedasticity between groups and dependence among genes. Incorporating these factors is necessary for sample size calculation in microarray experiments. A penalized t-statistic is widely used to improve the identifiability of DEGs. We develop a formula to(More)