Benzimidazoles have shown significant promise for repurposing as a cancer therapy. The aims of this review are to investigate the possibilities and limitations of the anti-cancer effects of benzimidazole anthelmintics and to suggest ways to overcome these limitations. This review included studies on the anti-cancer effects of 11 benzimidazoles. Largely divided into three parts, i.e., preclinical anti-cancer effects, clinical anti-cancer effects, and pharmacokinetic properties, we examine the characteristics of each benzimidazole and attempt to elucidate its key properties. Although many studies have demonstrated the anti-cancer effects of benzimidazoles, there is limited evidence regarding their effects in clinical settings. This might be because the clinical trials conducted using benzimidazoles failed to restrict their participants with specific criteria including cancer entities, cancer stages, and genetic characteristics of the participants. In addition, these drugs have limitations including low bioavailability, which results in insufficient plasma concentration levels. Additional studies on whole anti-cancer pathways and development strategies, including formulations, could result significant enhancements of the anti-cancer effects of benzimidazoles in clinical situations.

South Korea is promoting digital healthcare services in the public sector. One notable initiative is the “artificial intelligence and the internet of things (AI–IoT)-based healthcare project for senior citizens”, which was implemented by the Korea Health Promotion Institute (KHPI). This project utilized an IoT-based digital healthcare service that integrates information technology and screen-based AI speaker functions. Services through this project are intended for senior citizens aged 65 years (or older) who face challenges in visiting public healthcare institutions owing to limitations on outdoor activities, especially in the post-coronavirus 2019 era. This article shares the recent outcomes of this project and outlines the mid-to-long-term development strategies for this style of South Korean digital healthcare initiatives.

The disease control rate is very low (at less than 30%) for diabetes. The use of digital healthcare technology is increasing recently for continuous management in daily life. In this study, a meta-analysis was conducted to evaluate the clinical effects of digital healthcare technology for patients with type 2 diabetes management. For a review of the literature, databases such as PubMed, Embase, and Cochrane Library were searched using Medical Subject Heading (MeSH) terms published up to 9 August 2021. As a result, 2354 articles were identified, and 12 randomized controlled trial articles were finally included. Digital healthcare technology combined management for type 2 diabetes significantly decreased HbA1c (p < 0.00001, standardized mean difference (SMD) = −0.49) and marginally decreased triglyceride, compared with usual care (p = 0.06, SMD = −0.18). However, it did not significantly affect BMI (p = 0.20, SMD = −0.47), total cholesterol (p = 0.13, SMD = −0.19), HLD-C (p = 0.89, SMD = −0.01), LDL-C (p = 0.95, SMD = −0.01), systolic BP (p = 0.83, SMD = 0.03), or diastolic BP (p = 0.23, SMD = 0.65), compared with usual care. These results indicate that digital healthcare technology can improve HbA1c and triglyceride levels of type 2 diabetes patients. Further well-designed randomized controlled clinical trials are needed to confirm the clinical effect of digital healthcare technology.

Background: Mobile health technologies show promise in addressing metabolic syndrome, but their comparative effectiveness in large-scale public health interventions remains unclear. Objective: This study aims to compare the effectiveness of wearable devices (wearable activity trackers) and mobile app–based activity trackers (built-in step counters) in promoting walking practice, improving health behaviors, and reducing metabolic syndrome risk within a national mobile health care program operated by the Korea Health Promotion Institute. Methods: This retrospective cohort study analyzed data from 46,579 participants in South Korea’s national mobile health care program (2020‐2022). Participants used wearable devices for 12 weeks, after which some switched to built-in step counters. The study collected data on demographics, health behaviors, and metabolic syndrome risk factors at baseline, 12 weeks, and 24 weeks. Outcomes included changes in walking practice, health behaviors, and metabolic syndrome risk factors. Metabolic syndrome risk was assessed based on 5 factors: blood pressure, fasting glucose, waist circumference, triglycerides, and high-density lipoprotein cholesterol. Health behaviors included low-sodium diet preference, nutrition label reading, regular breakfast consumption, aerobic physical activity, and regular walking. To address potential selection bias, propensity score matching was performed, balancing the 2 groups on baseline characteristics including age, gender, education level, occupation, insurance type, smoking status, and alcohol consumption. Results: Both wearable activity tracker and built-in step counter groups exhibited significant improvements across all evaluated outcomes. The improvement rates for regular walking practice, health behavior changes, and metabolic syndrome risk reduction were high in both groups, with percentages ranging from 45.2% to 60.8%. After propensity score matching, both device types showed substantial improvements across all indicators. The built-in step counter group demonstrated greater reductions in metabolic syndrome risk compared to the wearable device group (odds ratio [OR] 1.20, 95% CI 1.05‐1.36). No significant differences were found in overall health behavior improvements (OR 0.95, 95% CI 0.83‐1.09) or walking practice (OR 0.84, 95% CI 0.70‐1.01) between the 2 groups. Age-specific subgroup analyses revealed that the association between built-in step counters and metabolic syndrome risk reduction was more pronounced in young adults aged 19‐39 years (OR 1.35, 95% CI 1.09‐1.68). Among Android use subgroups, built-in step counters were associated with a higher reduction in health risk factors (OR 1.20, 95% CI 1.03‐1.39). Conclusions: Both wearable devices and built-in step counters effectively reduced metabolic syndrome risk in a large-scale public health intervention, with built-in step counters showing a slight advantage. The findings suggest that personalized device recommendations based on individual characteristics, such as age and specific health risk factors, may enhance the effectiveness of mobile health interventions. Future research should explore the mechanisms behind these differences and their long-term impacts on health outcomes.

Objective: We sought to evaluate the differential effects of wearable device-based interventions on weight-related and metabolic health outcomes among adults and youth with overweight or obesity. Methods: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) published up to November 2025, identified through PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov. Eligible studies compared wearable device interventions to control conditions and reported outcomes such as weight, body mass index (BMI), waist circumference, blood pressure, lipid levels, and hemoglobin A1c (HbA1c). Data were pooled using random-effects models, and subgroup analysis was performed by age group. Results: Eighteen RCTs were included. Wearable device interventions significantly reduced BMI overall (mean difference [MD], −0.63 kg/m ² ; 95% confidence interval [CI], −1.01 to −0.25; P = 0.001), with a greater effect in children and adolescents (MD, −0.91 kg/m ² ; 95% CI, −1.26 to −0.56; P < 0.00001). In adults, waist circumference decreased significantly (MD, −5.22 cm; 95% CI, −9.03 to −1.40; P = 0.007), and HbA1c also improved (MD, −0.24%; 95% CI, −0.30 to −0.18%; P < 0.00001). No significant differences were observed for overall weight change, blood pressure, or lipid profiles in adults. Pediatric participants showed more consistent improvements across multiple indicators. Conclusion: Wearable device-based interventions led to modest but significant improvements in metabolic health, particularly in children and adolescents. These findings underscore the potential of wearable technologies as supportive tools for obesity management and highlight the importance of age-specific strategies in intervention design.

Background: Although metformin is the first-line medicine for type 2 diabetes (T2D), its safety profile in adolescents remains poorly understood. This study seeks to investigate the adverse events linked to metformin use in adolescents diagnosed with T2D. Methods: Data from the Food and Drug Administration Adverse Event Reporting System (FAERS), spanning Q1 2004 to Q2 2024, were retrospectively analyzed in this study. Adverse reactions were standardized using the Medical Dictionary for Regulatory Activities, then significant adverse drug reaction signals were identified through disproportionality analysis employing reporting odds ratio (ROR) and information component (IC) methods. Results: Of 17,956,653 FAERS reports, 80,187 involved metformin, including 973 in adolescents (10–19 years), with 174 cases were identified with a T2D indication. Analysis at the system organ class level revealed that congenital, familial, and genetic disorders [ROR: 8.8 (4.0, 19.3); IC: 2.2 (1.1, 2.9)] and pregnancy conditions [ROR: 4.9 (2.5, 9.5); IC: 1.8 (0.8, 2.5)] showed the most significant signals. At the preferred term (PT) level, three signals were identified across all sexes and subgroups: treatment noncompliance [ROR: overall 4.14 (2.44, 7.02), male 4.27 (2.00, 9.12), and female 4.65 (2.22, 9.74); IC: overall 1.67 (0.88, 2.22), male 1.60 (0.46, 2.36), and female 1.74 (0.60, 2.50)], lactic acidosis [IC: overall 2.99 (1.91, 3.72), male 2.53 (0.76, 3.61), and female 2.76 (1.34, 3.67)], and gastrointestinal disorder [ROR: overall 13.09 (4.73, 36.23), male 54.33 (6.05, 487.96), female 5.34 (1.10, 25.84)]. Neurological disorders were observed only in males, while pregnancy-related adverse effects and renal disorders occurred exclusively in females. Additionally, the study identified potential new signals not documented in metformin labeling, including areflexia, muscle weakness, ataxia, decreased vibratory sense, rhabdomyolysis, substance use, and axillary pain. Conclusion: The study reveals a complex safety profile of metformin in adolescents with T2D, warranting further research to confirm risks.