Japan's rising research stars: Yuuki Wada

Overview

The nucleus is a membrane-bound organelle that acts as a control center in a eukaryotic cell. It contains chromosomal DNA, which controls gene expression and precisely regulates the production of proteins within the cell. In contrast, the DNA inside the mitochondria and chloroplast only carries out functions that are specific to those organelles.
Arrangement of DNA within Nucleus
The regulation of gene expression inside the nucleus is dependent on many factors, including the DNA structure. The...

The process of converting very light nuclei into heavier nuclei is also accompanied by the conversion of mass into large amounts of energy, a process called fusion. The principal source of energy in the sun is a net fusion reaction in which four hydrogen nuclei fuse and ultimately produce one helium nucleus and two positrons.
A helium nucleus has a mass that is 0.7% less than that of four hydrogen nuclei; this lost mass is converted into energy during the fusion. This reaction produces about...

Nuclear reprogramming is the process of switching gene expression of one cell type to that of another cell type, usually from a differentiated cell state to an undifferentiated cell state. Differentiation occurs during processes such as development and morphogenesis, tissue regeneration, and malignancy. Cells can also be artificially induced to reprogram their gene expression by techniques such as nuclear transfer, induced pluripotency, and cell fusion. Such techniques have many applications in...

Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...