Keio University · Medicine
Professor Satoko Hori's research lab focuses on translational neuroscience and pharmacovigilance, with a primary emphasis on the blood-brain barrier (BBB) and its role in drug delivery and neuroprotection. The lab investigates molecular mechanisms regulating BBB integrity, particularly the regulation of tight junction proteins like occludin and efflux transporters such as ABCG2, using in vitro models of brain endothelial, astrocyte, and pericyte cells. In parallel, the lab applies advanced artificial intelligence and natural language processing techniques to analyze patient-generated text from online communities, aiming to detect adverse drug reactions—especially hand-foot syndrome—and psychological concerns in cancer patients for early clinical intervention. This interdisciplinary approach bridges molecular neuroscience with digital health innovation.
Figures are computed from collected data and may differ slightly.
Although tight-junctions (TJs) at the blood-brain barrier (BBB) are important to prevent non-specific entry of compounds into the CNS, molecular mechanisms regulating TJ maintenance remain still unclear. The purpose of this study was therefore to identify molecules, which regulate occludin expression, derived from astrocytes and pericytes that ensheathe brain microvessels by using conditionally immortalized adult rat brain capillary endothelial (TR-BBB13), type II astrocyte (TR-AST4) and brain p
The purpose of the present study was to clarify the expression, transport properties and regulation of ATP-binding cassette G2 (ABCG2) transporter at the rat blood-brain barrier (BBB). The rat homologue of ABCG2 (rABCG2) was cloned from rat brain capillary fraction. In rABCG2-transfected HEK293 cells, rABCG2 was detected as a glycoprotein complex bridged by disulfide bonds, possibly a homodimer. The protein transported mitoxantrone and BODIPY-prazosin. In rat brain capillary fraction, rABCG2 pro
Early detection and management of adverse drug reactions (ADRs) is crucial for improving patients' quality of life. Hand-foot syndrome (HFS) is one of the most problematic ADRs for cancer patients. Recently, an increasing number of patients post their daily experiences to internet community, for example in blogs, where potential ADR signals not captured through routine clinic visits can be described. Therefore, this study aimed to identify patients with potential ADRs, focusing on HFS, from inte
This study showed that the BERT model can extract multiple worries from text generated from patients with breast cancer. This is the first application of a multilabel classifier using the BERT model to extract multiple worries from patient-generated text. The results will be helpful to identify breast cancer patients' worries and give them timely social support.
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