The Effectiveness and Safety of the Short-Course Therapy in Liver Transplant Recipients With Uncomplicated Gram-Negative Bacteremia: A Retrospective Study.

Introduction: The appropriate duration of therapy for uncomplicated gram-negative bloodstream infection (GN-BSI) in liver transplant (LTx) recipients remains unknown. This study aims to explore the effectiveness of a short-course antimicrobial therapy.

Methods: This retrospective study was performed in a single LTx center in Japan.

Epidemiology and risk factors for mortality in clostridial bacteremia in Japan: A retrospective multicenter observational study.

Objectives: Clostridium species are ubiquitous in nature and commonly cause infections, including bacteremia. C. perfringens is often the causative species, while the epidemiology of other clostridial species remains unclear.

Acceleration of Reaction Space Projector Analysis Using Combinatorial Optimization: Application to Organic Chemical Reactions.

In recent years, automated reaction path search methods have established the concept of a reaction route network. The Reaction Space Projector (ReSPer) visualizes the potential energy hypersurface into a lower-dimensional subspace using principal coordinates. The main time-consuming process in ReSPer is calculating the structural distance matrix, making it impractical for complex organic reaction route networks.

Fast score is associated with patient-reported outcomes in patients with metabolic dysfunction-associated steatotic liver disease.

Backgrounds: People with metabolic dysfunction-associated steatotic liver disease (MASLD) frequently report fatigue. This symptom is associated with hepatic inflammation and fibrosis. FibroScan-aspartate aminotransferase (FAST) score is a noninvasive measurement tool that can be used to assess the severity of MASLD.

Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.

Purpose: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.

Methods: We retrospectively analyzed scan data of adult patients who underwent body CT during two periods relative to DLR implementation at our facility: a 12-month pre-DLR phase (n = 5553) using hybrid iterative reconstruction and a 12-month post-DLR phase (n = 5494) with routine CT reconstruction transitioning to DLR. To ensure comparability between two groups, we employed propensity score matching 1:1 based on age, sex, and body mass index.