Background: Preclinical studies have reported anticancer properties of sodium-glucose cotransporter 2 inhibitors (SGLT2is). We aimed to elucidate the association between the use of SGLT2is and the risk of prostate cancer among male patients with type 2 diabetes mellitus (T2DM). Methods: An active-comparator, new-user cohort design using a nationwide database between September 2014 and June 2020 was conducted on 45,601 new SGLT2i users and 205,395 new users of other glucose-lowering medications (oGLMs). In the following 1:1 propensity score matched (PSM) analysis, 35,371 SGLT2i users matched with an equivalent number of oGLM users were assessed. The hazard ratios (HRs) and 95% confidence intervals (CIs) for prostate cancer were calculated. Results: Among the cohort, prostate cancer was diagnosed in 210 out of 45,601 SGLT2i users, corresponding to a cumulative incidence of 1.0%, in contrast to 1,880 cases among 205,395 users of oGLMs, with a cumulative incidence of 1.5%. The use of SGLT2is was significantly correlated with a reduced risk of prostate cancer based on a multivariable-adjusted HR of 0.83 (95% CI, 0.71 to 0.98). PSM analysis affirmed 18% reduction in prostate cancer risk associated with SGLT2i use (HR, 0.82; 95% CI, 0.67 to 0.99). Subgroup analyses revealed that body mass index (BMI) significantly influenced the effect of SGLT2i on prostate cancer risk, with a more pronounced reduction in the subgroup with a BMI <25 kg/m2 (P=0.037). Conclusion The use of SGLT2is in Korean male patients with T2DM is associated with a lower risk of prostate cancer.

Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.

Background: Cough is a prominent symptom of chronic respiratory diseases, including asthma, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), and bronchiectasis (BE). Some patients develop chronic cough (CC), defined as lasting more than 8 weeks, yet its characteristics remain poorly understood. This study aimed to characterize CC across various chronic respiratory diseases using validated cough assessment tools. Methods: The Cough Assessment in Chronic Respiratory Diseases (COASESS) study, a multicenter, prospective cross-sectional study, was conducted at 10 university hospitals. CC was evaluated in terms of intensity (numeric rating scale [NRS]), frequency (cough symptom score [CSS]), and quality of life (using the cough assessment test [COAT] and Leicester cough questionnaire [LCQ]). Cough hypersensitivity was assessed with the cough hypersensitivity questionnaire (CHQ). Data on age, sex, and smoking status were also collected. Results: Among the 303 enrolled patients, 266 with chronic respiratory diseases were included in the analysis. Patients with asthma were younger, predominantly female, and non-smokers, whereas those with COPD and IPF were older males who had previously smoked (p<0.001). Scores for COAT, LCQ, NRS, and CSS showed significant differences across the diseases, with asthma and IPF patients experiencing a greater symptom burden and lower quality of life compared to those with COPD or BE (p<0.001). Although CHQ total scores were similar across groups, asthma patients more frequently reported triggers such as talking and post-nasal drip. Conclusion This study revealed distinct characteristics of CC across different chronic respiratory diseases. Asthma and IPF were associated with a higher symptom burden, and cough hypersensitivity varied depending on the underlying condition. These findings highlight the necessity for disease-specific assessments and management strategies for CC.

The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

The brain-derived neurotrophic factor (BDNF) plays a crucial role in neuroprotection, and we have previously demonstrated BDNF-mediated neuroprotective effects in mesenchymal stromal cells (MSCs). The present study aimed to investigate whether BDNF-overexpressing MSCs enhance the therapeutic efficacy of naïve MSCs in a preclinical model of severe neonatal intraventricular hemorrhage (IVH). We exposed primary rat neuronal cells to 40 U of thrombin overnight in vitro. Subsequently, the neuronal cells were co-cultured with either naïve MSCs or BDNF-overexpressing MSCs (1×105 cells in 1 mL media) for 24 hours. Next, 300 μL of maternal blood was injected into bilateral ventricles on postnatal day (P)4 to induce severe IVH in newborn Sprague-Dawley male rats. At P6, either naïve MSCs or BDNF-overexpressing MSCs (1×105 cells in 10 μL saline) were transplanted intraventricularly. Behavioral function tests, including passive avoidance, followed by endpoint analyses of brain tissue and cerebrospinal fluid were performed at P35. BDNF-overexpressing MSCs enhanced the effects of naïve MSCs against cell death, cytotoxicity, and oxidative stress in vitro. Notably, naïve and BDNF-overexpressing MSCs did not attenuate post-hemorrhagic ventricular dilatation, neuronal cell death, or gliosis. However, BDNF-overexpressing MSCs attenuated microglial activation.Furthermore, inflammatory cytokine (interleukin [IL]-1α, IL-1β, IL-6, and tumor necrosis factor-α) levels and memory function assessed using a passive avoidance test significantly improved in the BDNF-overexpressing MSC transplanted group compared with the naïve MSC transplanted group. Our data suggest that BDNF-overexpressing MSCs may offer superior protective effects to naïve MSCs in a neonatal IVH model.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Objective: Disasters such as pandemics and natural catastrophes cause significant psychological distress, increasing the risk of depression, anxiety, and post-traumatic stress disorder (PTSD). This review aimed to evaluate the effectiveness of remote mental health interventions, such as telepsychiatry, online cognitive behavioral therapy (CBT), mobile applications, and artificial intelligence (AI)-based tools, during disasters. Methods: A comprehensive literature search was conducted using international databases (PubMed, EMBASE, PsycINFO, Web of Science, Scopus, CINAHL) and Korean domestic databases (KISS, RISS, DBpia, KMbase, KoreaMed). Studies published between January 2010 and February 2025 were screened following the PRISMA 2020 guidelines. Two board-certified psychiatrists independently reviewed titles, abstracts, and full texts. Peer-reviewed articles and relevant grey literature, including government manuals and expert guidelines, were included. Results: A total of 147 studies were synthesized, including randomized controlled trials, meta-analyses, observational studies, and policy documents. Evidence showed that remote interventions effectively reduced symptoms of depression, anxiety, and PTSD. Online CBT was beneficial for mild to moderate distress; mobile apps facilitated psychoeducation and symptom tracking; and telepsychiatry ensured care continuity, especially in underserved areas. AI tools showed promise in screening and triage but require better clinical integration. Effectiveness was highest when interventions were implemented early, integrated within stepped-care models, and guided by trained professionals. Conclusion Remote mental health interventions are practical and effective tools for bridging mental health care gaps during disasters. To ensure sustainability, these interventions should be integrated into national disaster mental health frameworks, accompanied by adequate funding, clinician training, legal safeguards, and cultural adaptation.