Two Distinct Mechanisms for Actin Capping Protein Regulation—Steric and Allosteric Inhibition

A crystallographic study reveals the structural basis for regulation by two different inhibitors of the actin capping protein, a critical factor controlling actin-driven cell motility

Acute hepatitis E in a renal transplantation recipient: a case report

Mitsutoshi Shindo,1 Hiroaki Takemae,2 Takafumi Kubo,2 Masatsugu Soeno,2 Tetsuo Ando,2 Yoshiyuki Morishita1 1Division of Nephrology, First Department of Integrated Medicine, Saitama Medical Center, Jichi Medical University, Saitama, Japan; 2Department of Dialysis and Transplant Surgery, Hidaka Hospital, Gunma, Japan Abstract: Hepatitis E is caused by infection with the hepatitis E virus (HEV). HEV is transmitted orally via HEV-contaminated food or drink. Hepatitis E usually shows mild symptoms and is self-limiting in the general population; however, it may progress to chronic hepatitis in immunosuppressed patients such as recipients of organ transplantation. However, a few cases of acute hepatitis E have been reported in organ transplantation recipients. We herein report a case of acute hepatitis E in a 31-year-old male renal transplant recipient. The patient underwent renal transplantation 2 years ago, and his postoperative course was uneventful without rejection. After complaining of general fatigue and low-grade fever for 1 week, he was referred to and admitted to our hospital. Careful interview revealed that he ate undercooked pork 10 weeks prior. Blood analysis revealed liver dysfunction but was serologically negative for hepatitis A, B and C virus, cytomegalovirus infection and collagen diseases. Immunoglobulin A antibody against hepatitis E virus (HEV-IgA) was also negative at that point. After 2 weeks of admission, HEV-IgA and HEV-RNA were measured again as hepatitis E could not be ruled out due to history of ingestion of undercooked meat that may have been contaminated with HEV. At that time, HEV-IgA and HEV-RNA (genotype 3) were positive. Thus, an acute hepatitis E was diagnosed. His liver function gradually improved to within the normal range, and HEV-IgA and HEV-RNA were negative at 11 weeks after admission. In conclusion, we describe here a case of acute hepatitis E in a renal transplant recipient. Careful interview regarding the possibility of ingestion of HEV-contaminated food and repeated measurements of HEV-IgA were helpful in finalizing a diagnosis. Keywords: hepatitis E virus, anti-HEV IgA, recipient, renal transplantation, zoonosi

Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

Background: Despite the increasing availability of clinical decision support systems (CDSSs) and rising expectation for CDSSs based on artificial intelligence (AI), little is known about the acceptance of AI-based CDSS by physicians and its barriers and facilitators in emergency care settings. Objective: We aimed to evaluate the acceptance, barriers, and facilitators to implementing AI-based CDSSs in the emergency care setting through the opinions of physicians on our newly developed, real-time AI-based CDSS, which alerts ED physicians by predicting aortic dissection based on numeric and text information from medical charts, by using the Unified Theory of Acceptance and Use of Technology (UTAUT; for quantitative evaluation) and the Consolidated Framework for Implementation Research (CFIR; for qualitative evaluation) frameworks. Methods: This mixed methods study was performed from March to April 2021. Transitional year residents (n=6), emergency medicine residents (n=5), and emergency physicians (n=3) from two community, tertiary care hospitals in Japan were included. We first developed a real-time CDSS for predicting aortic dissection based on numeric and text information from medical charts (eg, chief complaints, medical history, vital signs) with natural language processing. This system was deployed on the internet, and the participants used the system with clinical vignettes of model cases. Participants were then involved in a mixed methods evaluation consisting of a UTAUT-based questionnaire with a 5-point Likert scale (quantitative) and a CFIR-based semistructured interview (qualitative). Cronbach α was calculated as a reliability estimate for UTAUT subconstructs. Interviews were sampled, transcribed, and analyzed using the MaxQDA software. The framework analysis approach was used during the study to determine the relevance of the CFIR constructs. Results: All 14 participants completed the questionnaires and interviews. Quantitative analysis revealed generally positive responses for user acceptance with all scores above the neutral score of 3.0. In addition, the mixed methods analysis identified two significant barriers (System Performance, Compatibility) and two major facilitators (Evidence Strength, Design Quality) for implementation of AI-based CDSSs in emergency care settings. Conclusions: Our mixed methods evaluation based on theoretically grounded frameworks revealed the acceptance, barriers, and facilitators of implementation of AI-based CDSS. Although the concern of system failure and overtrusting of the system could be barriers to implementation, the locality of the system and designing an intuitive user interface could likely facilitate the use of optimal AI-based CDSS. Alleviating and resolving these factors should be key to achieving good user acceptance of AI-based CDSS. © Ryo Fujimori, Keibun Liu, Shoko Soeno, Hiromu Naraba, Kentaro Ogura, Konan Hara, Tomohiro Sonoo, Takayuki Ogura, Kensuke Nakamura, Tadahiro Goto. OriginallyOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]