Publications by authors named "K Fukuzawa"
[3. Hokkaido Branch, Tohoku Branch, Kanto Branch, Tokyo Branch].
Nihon Hoshasen Gijutsu Gakkai Zasshi
January 2024
Background: Several studies found that early pancreatic atrophy detected by computed tomography (CT) within 6 months was associated with a high incidence of diabetes in patients with type-1 autoimmune pancreatitis (AIP) receiving steroid therapy; however, no long-term follow-up studies have been performed.
Aim: To investigate pancreatic volume (PV) changes using three dimensional (3D)-CT volumetry and their relationship with IgG4 and diabetes in patients with AIP.
Methods: This retrospective study included 33 patients with type-1 AIP receiving steroid therapy.
Atrial fibrillation (AF) is strongly associated with strokes, heart failure, and increased mortality. This study aims to identify the monocyte-macrophage heterogeneity and interactions of these cells with non-immune cells, and to identify functional biomarkers in patients with AF. Therefore, we assess the single cell landscape of left atria (LA), using a combination of single cell and nucleus RNA-seq.
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- - The frozen domain (FD) approximation using the fragment molecular orbital (FMO) method allows for efficient partial geometry optimization of large biomolecular systems, including protein-ligand complexes.
- - A new variation called the frozen domain and partial dimer (FDPD) method was developed, which significantly reduces computational time for geometry optimization compared to conventional methods, achieving notable improvements in systems such as the β-adrenergic receptor and estrogen receptor.
- - The FDPD method enhanced the understanding of structure-activity relationships in drug design, as it improved the correlation between ligand binding energy and biological activity by optimizing structures more effectively.
Article Synopsis
- * The research utilizes the fragment molecular orbital (FMO) method on a dataset comprising over 5,000 protein structures from the SCOP2 database, resulting in more than 200 million inter-fragment interaction energies.
- * Multiple basis sets were applied to improve accuracy in energy calculations, and the total dataset size is approximately 6.7 GB, which can aid in functional analyses and machine learning applications related to protein properties.