Matsuyama University

ABSTRACT This study examined whether vocalization (speaking aloud) supports the learning of multiword expressions (MWEs) in sentences, and how text presentation, vocabulary size, and working memory (WM) capacity affect outcomes. Seventy‐one Japanese university and graduate students studied 80 English MWEs (verb–noun idioms) under four within‐participant conditions combining vocalization and text presentation. In each condition, 20 MWEs were introduced and assessed through item memory, form recognition, and meaning recognition tests; an additional 20 MWEs appeared only in the tests for comparison. Participants also completed a vocabulary size test and two digit span tasks. Results showed that silent learning was more effective than vocalization, while text presentation supported learning. Vocabulary size contributed more than WM capacity. These findings suggest that vocalization does not always enhance learning and that, when learning MWEs embedded in sentences, learning without vocalization may be more effective.

Ziziphi Fructus (the fruit of Ziziphus jujuba Miller var. inermis Rehder; Japanese name "Taiso"), listed in the 18th edition of the Japanese Pharmacopoeia (JP18), is widely used in Kampo (Japanese traditional) medicine. However, a specific identification test for Ziziphi Fructus was not prescribed in JP18. Hence, in this study, we establish a TLC-based identification test for quality assurance of the crude drug Ziziphi Fructus. The HPLC experiments identified 3-O-cis-p-coumaroylalphitolic acid and 3-O-trans-p-coumaroylaliphitolic acid as suitable indicators. After developing the samples to a distance of 10 cm using ethyl acetate (EtOAc)/n-hexane/acetic acid (AcOH)/H2O (60 : 40 : 2 : 1) as the TLC-developing solvent and UV light at 254 nm, two spots with an Rf value of approximately 0.4-0.6 were detected. Additionally, based on the TLC-based experiments, alphitolic and maslinic acids emerged as potential indicator components. Treatment of samples with EtOAc/n-hexane/AcOH (60 : 40 : 1) serving as the developing solvent, followed by exposure to dilute sulfuric acid solution, heat, and UV light at 365 nm, revealed two clear spots with Rf values of approximately 0.2-0.3. These findings potentially serve as a basis for the development of an identification test to identify Ziziphi Fructus.

Introduction: The prognosis of patients with epidermal growth factor receptor mutation-positive non-small cell lung cancer has improved with the introduction of oral EGFR-tyrosine kinase inhibitor (TKI). Lower adherence to oral anticancer medications is reportedly associated with a poor prognosis. It is important to understand the causes of lower adherence to oral anticancer medications. We aimed to assess the potential risk factors associated with low adherence to EGFR-TKIs in a real-world clinical setting using administrative claims data in Japan. Methods: We identified 10,809 outpatients routinely prescribed EGFR-TKIs between December 2015 and January 2023. Adherence to EGFR-TKIs was assessed based on the medication possession ratio (MPR) during the 12-month follow-up period from the date of first outpatient EGFR-TKI prescription. Multivariable linear regression analysis was performed to identify the potential risk factors associated with lower adherence. Results: The mean (standard deviation) MPR was 94.1% (14.0). Lower adherence was associated with increasing age (per 10-year increase), female sex, dysphagia, and a higher number of concomitant oral medications (per doubling of the count). Conclusion: Adherence to EGFR-TKIs was generally high, but the findings support tailored adherence strategies, especially for older patients and for those with a higher number of concomitant oral medications, including medication review to reduce pill burden and proactive support for swallowing difficulties.

The global surge in antimicrobial resistance (AMR) highlights the critical need for the development of innovative therapies and the appropriate use of antimicrobial agents. Our research focused on preventing, managing, and mitigating the adverse effects of treatments for infection with methicillin-resistant Staphylococcus aureus. In this review, we present our investigations utilizing medical big data. The first study aimed to elucidate the relationship between renal outcome and survival following the onset of vancomycin-associated nephrotoxicity (VAN). An initial analysis using the US Food and Drug Administration Adverse Events Reporting System (FAERS) database revealed elevated mortality rates among patients with VAN compared with those without VAN, forming the basis for further investigation. A subsequent, more rigorous, retrospective analysis using electronic medical records confirmed that poor survival outcomes were significantly associated with non-recovery from VAN, particularly when progression to acute kidney injury of stage ≥2 occurred. Therefore, preventing progression to severe VAN is critical for enhancing survival outcomes. The second study investigated the relationship between statin use and daptomycin-related musculoskeletal adverse events. By employing a mixed-method approach combining meta-analysis with disproportionality analysis of the FAERS data, a significant association between statin therapy and daptomycin-related rhabdomyolysis was identified. This highlights the importance of cautious statin and daptomycin use, with careful consideration of potential safety risks. Each medical big-data database possesses unique characteristics that require careful consideration during analysis. The accurate interpretation of medical big data, coupled with its integration with complementary methodologies, will produce more robust and reliable research outcomes across diverse fields.