Publications by authors named "E Kawakami"
Microthrombus formation is associated with COVID-19 severity; however, the detailed mechanism remains unclear. In this study, we investigated mouse models with severe pneumonia caused by SARS-CoV-2 infection by using our in vivo two-photon imaging system. In the lungs of SARS-CoV-2-infected mice, increased expression of adhesion molecules in intravascular neutrophils prolonged adhesion time to the vessel wall, resulting in platelet aggregation and impaired lung perfusion.
View Article and Find Full Text PDFThis cross-sectional study investigated the prevalence and factors associated with leftover antibiotics in Japanese households through pharmacist home visits. The research, conducted in collaboration with pharmaceutical associations in Kyoto and Hirakata, included 37 cases analyzed from October 2023 to March 2024. Participants had a median age of 81 years and received a median of two antibiotic prescriptions in the past year.
View Article and Find Full Text PDFQuantification of intrahepatic covalently closed circular DNA (cccDNA) is a key for evaluating an elimination of hepatitis B virus (HBV) in infected patients. However, quantifying cccDNA requires invasive methods such as a liver biopsy, which makes it impractical to access the dynamics of cccDNA in patients. Although HBV RNA and HBV core-related antigens (HBcrAg) have been proposed as surrogate markers for evaluating cccDNA activity, they do not necessarily estimate the amount of cccDNA.
View Article and Find Full Text PDFArticle Synopsis
- This study focuses on predicting the timing of biochemical recurrence in prostate cancer patients after they undergo radical prostatectomy, highlighting the importance of early detection and intervention through accurate risk assessment.
- Researchers applied a machine learning model called Random Survival Forest, analyzing data from 548 patients to identify key factors influencing recurrence, such as Gleason score, seminal vesicle invasion, and PSA levels.
- The model showed better predictive accuracy (time-dependent AUC of 0.785) compared to traditional methods, thus providing a personalized approach for monitoring high-risk patients and improving follow-up strategies.
Background: Neutropenia can easily progress to febrile neutropenia and is a risk factor for life-threatening infections. Predicting and preventing severe neutropenia can help avoid such infections.
Aim: This study aimed to develop an optimal model using advanced statistical methods to predict neutropenia after 5-fluorouracil/cisplatin chemotherapy for esophageal cancer and to create a nomogram for clinical application.