Rui Yamaguchi

Explaining hidden mechanisms: a generative model for causal graphs with nonlinear latent factors

Koji Maruhashi, H S Park, Rui Yamaguchi, Satoru Miyano

Biomedical data analysis can now recover large families of condition-specific causal graphs, yet these results are often too complex for humans to interpret mechanistically. To address this challenge, we adopt a generative perspective, we address this challenge by formulating a structural-equation-based generative …

jp, kr (code pays fourni par la source)

Correction: Machine learning model for predicting the cold–heat pattern in Kampo medicine: a multicenter prospective observational study

Ayako Maeda-Minami, Tetsuhiro Yoshino, Kotoe Katayama, Yuko Horiba et autres

[This corrects the article DOI: 10.3389/fphar.2024.1412593.].

jp, us (code pays fourni par la source)

Inhibiting KRAS with CD47 and immune checkpoint overcomes intrinsic resistance to combined KRAS and immune checkpoint inhibitor therapy

Kentaro Hirade, Noritaka Tanaka, Taisuke Kajino, Yuta Adachi et autres

Although Kirsten rat sarcoma virus (KRAS) G12C inhibitors alter the treatment strategy for patients with KRAS G12C-mutant lung cancer, their efficacy remains insufficient to eliminate tumors. Here, we identify that inhibition of mutant KRAS promotes escape from macrophage phagocytosis by upregulating the …

jp, sg (code pays fourni par la source)

The Urban Divide: Socioeconomic Status and Its Impact on Cancer in the Age of Urbanization

Yuriko N. Koyanagi, Masanori Kawaura, Keitaro Matsuo, Yukino Kawakatsu et autres

Abstract Against accelerating global urbanization, we analyzed regional cancer health disparities in Japan using nationwide cancer incidence and mortality data. This cross-sectional ecological study included 1889 Japanese municipalities, categorized as urban, suburban, and rural. Using 2015 Census data, we estimated the normalized …

jp, us (code pays fourni par la source)

RVINN: a flexible modeling for inferring dynamic transcriptional and post-transcriptional regulation using physics-informed neural networks

Osamu Muto, Zhongliang Guo, Rui Yamaguchi

SUMMARY: Dynamic gene expression is controlled by transcriptional and post-transcriptional regulation. Recent studies on transcriptional bursting and buffering have increasingly highlighted the dynamic gene regulatory mechanisms. However, direct measurement techniques still face various constraints and require complementary methodologies, which are both comprehensive …

jp (code pays fourni par la source)

Artificial intelligence for body composition assessment focusing on sarcopenia

Sachiyo Onishi, Takamichi Kuwahara, Masahiro Tajika, Tsutomu Tanaka et autres

This study aimed to address the limitations of conventional methods for measuring skeletal muscle mass for sarcopenia diagnosis by introducing an artificial intelligence (AI) system for direct computed tomography (CT) analysis. The primary focus was on enhancing simplicity, reproducibility, and convenience, and …

jp (code pays fourni par la source)

Cell of origin and expression profiles of pseudomyxoma peritonei derived from the appendix

Rei Noguchi, Kiyoshi Yamaguchi, Hideaki Yano, Yoshimasa Gohda et autres

Pseudomyxoma peritonei (PMP) is a rare disease caused by mucin-producing tumors that develop most frequently from the appendix. The disease is characterized by the accumulation of mucin in the abdominal cavity. Although frequent mutations in the KRAS and GNAS genes have been …

jp (code pays fourni par la source)

A novel mouse model of upper tract urothelial carcinoma highlights the impact of dietary intervention on gut microbiota and carcinogenesis prevention despite carcinogen exposure

Akinaru Yamamoto, Atsunari Kawashima, Toshihiro Uemura, Kosuke Nakano et autres

Animal models of N-butyl-N-(4-hydroxy butyl) nitrosamine (BBN)-induced urothelial carcinoma (UC), particularly bladder cancer (BC), have long been established. However, the rare incidence of BBN-induced upper urinary tract UC (UTUC), which originates from the same urothelium as BC, remains elusive. The scarcity of …

jp (code pays fourni par la source)

Comparative analysis of the B cell receptor repertoire during relapse and remission in patients with multiple sclerosis

Miriam Pérez-Saldívar, Yusuke Nakamura, Kazuma Kiyotani, Seiya Imoto et autres

Multiple sclerosis (MS) is a chronic, multifactorial, inflammatory and demyelinating disease of the central nervous system (CNS), which involves an autoimmune response against components of the myelin sheaths. Anti-B cell therapies have been proven to be successful in reducing relapses. Therefore, the …

mx, jp (code pays fourni par la source)

Artificial Intelligence for Body Composition Assessment Focusing on Sarcopenia

Sachiyo Onishi, Takamichi Kuwahara, Masahiro Tajika, Tsutomu Tanaka et autres

jp (code pays fourni par la source)

IMMU-03. EXPLORING CANCER-SPECIFIC T CELLS AND ANTIGENS IN GLIOBLASTOMA BASED ON SINGLE-CELL SEQUENCING OF CD8+ TILS

Takanari Okamoto, Ryo Mizuta, Ayako Demachi‐Okamura, Daisuke Muraoka et autres

Abstract BACKGROUND The effectiveness of cancer immunotherapy against glioblastoma (GBM) remains limited. This study aims to identify cancer-specific antigens to develop antigen-based cancer immunotherapies for GBM. We investigated candidate tumor antigen-specific T cells in GBM by single-cell RNA sequencing (scRNA-seq) and single-cell …

jp (code pays fourni par la source)

Machine learning model for predicting the cold–heat pattern in Kampo medicine: a multicenter prospective observational study

Ayako Maeda‐Minami, Tetsuhiro Yoshino, Kotoe Katayama, Yuko Horiba et autres

Objective: The purpose of this study was to predict the four cold-heat patterns in patients who have the subjective symptoms of the cold-heat pattern described in the International Classification of Diseases Traditional Medicine Conditions - Module 1 by applying a machine learning …

jp (code pays fourni par la source)