In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Alzheimer’s disease (AD) is characterized by progressive cognitive deterioration and significant depression. However, the mechanisms linking depression to AD pathology remain unclear. Here, we investigated whether Notch2 signaling mediates depressionlike behaviors in presenilin-2 (PS2) N141I mutant mice, an early-onset AD model. PS2 wild-type (WT) and mutant (MT) mice aged 12-15 months were subjected to unpredictable chronic mild stress (UCMS) for 4 weeks, followed by sucrose preference, tail-hanging, and forced swimming tests. Behavioral assessments showed that UCMS exacerbated anhedonia and immobility only in PS2 MT mice. Molecular analysis revealed concomitant increases in plasma corticosterone, hippocampal γ-secretase activity, and Notch2 expression, and elevated total and phosphorylated glucocorticoid receptor levels in PS2 MT-UCMS mice. Gene expression profiling of human hippocampal datasets confirmed upregulation of NOTCH2 in Alzheimer’s disease and depression.Pharmacological inhibition of γ-secretase and Notch signaling with DAPT normalizes depressive behavior, reduces corticosterone release, attenuates GR phosphorylation, and inhibits Notch2 signaling in PS2 MT mice. These findings identify Notch2 as a pivotal mediator linking chronic stress to molecular changes associated with depression and AD, and suggest that targeting Notch2 signaling may provide therapeutic benefits for comorbid mood and neurodegenerative disorders.

Purpose: The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2023, with international comparisons. Materials and Methods: Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2023), with survival follow-up until December 31, 2024. Mortality data were obtained from the Ministry of Data and Statistics, while international comparisons were based on GLOBOCAN data. Results: In 2023, 288,613 newly diagnosed cancer cases (age-standardized rate [ASR], 288.6 per 100,000) and 85,271 deaths from cancer (ASR, 64.3 per 100,000) were reported. Among the incident cases, 145,452 (50.4%) were aged 65 years or older. Prostate cancer became the most common cancer among men for the first time. The proportion of localized-stage cancers increased from 45.6% in 2005 to 51.8% in 2023. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence ratios for stomach, colorectal, and breast cancer. The 5-year relative survival rate (2019-2023) was 73.7% overall and 92.7% for localized-stage cancers. Over 2.73 million prevalent cases were identified in 2023, representing 5.3% of the Korean population. Conclusion These findings indicate that Korea’s cancer control efforts have contributed to early detection and improved survival outcomes. As Korea enters a super-aged society in 2025, cancer burden will continue to increase, requiring sustained and adaptive cancer control strategies.

Background/Aims: Cardiovascular disease remains a major cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study evaluated the association between subclinical carotid atherosclerosis (SCA) and MASLD or MASLD and increased alcohol intake (MetALD) in asymptomatic individuals. Methods: This cross-sectional study included 56,889 adults undergoing health check-ups in South Korea. Hepatic steatosis was diagnosed by ultrasound, and SCA was defined by carotid plaques or increased intima-media thickness. Liver fibrosis was evaluated using the fibrosis-4 index and elastography. Results: SCA was identified in 13.5%. MASLD and MetALD were significantly associated with SCA in models adjusted for demographic and lifestyle factors (adjusted odds ratio [aOR], 1.26;95% confidence interval [CI], 1.19 to 1.33; aOR, 1.43; 95% CI, 1.30 to 1.58; respectively, p<0.001for both). However, these associations attenuated and lost statistical significance when metabolic risk factors were further adjusted. The risk of SCA increased with greater hepatic steatosis and liver fibrosis severity. In patients with MASLD, aORs were 1.70 (hepatic steatosis index >36),1.23 (fibrosis-4 index ≥1.3), and 1.78 (liver stiffness measurement ≥5.6 kPa), compared to indi-viduals without MASLD. Similar trends were observed in the MetALD group. Additionally, hyper-tension and clustering of ≥3 cardiometabolic risk factors were significantly associated with SCA inthe MASLD group, supporting the role of metabolic burden in SCA development. Conclusions MASLD and MetALD were associated with increased SCA risk, particularly in individuals with hepatic steatosis and fibrosis. These findings suggest that metabolic burden and liver disease severity jointly contribute to subclinical atherosclerosis risk.

Reference management software (RMS) represents a cornerstone of modern academic writing and publishing. For decades, programs such as EndNote, Zotero, and Mendeley have played central roles in facilitating citation organization, bibliography formatting, and collaborative scholarship. Although each platform has introduced unique innovations, persistent limitations remain, particularly with respect to usability, accessibility, and accuracy. In parallel, the rise of generative artificial intelligence has introduced an unprecedented challenge: the inadvertent inclusion of fabricated or incorrect references mistakenly incorporated into manuscripts. This phenomenon has exposed a critical limitation of traditional RMS platforms, namely their inability to verify reference authenticity. Against this backdrop, new solutions have emerged. One such example is CiteWell (https://citewell.org/), an artificial intelligence (AI)-era RMS that introduces several notable innovations, including PubMed-integrated verification, an intuitive interface for new users, customizable journal-specific styles, and multilingual accessibility. This review provides a comprehensive historical overview of RMS, evaluates the strengths and weaknesses of major platforms, and positions emerging AI-based tools as a new paradigm that combines traditional reference management with essential safeguards for contemporary academic challenges.

Purpose: This study aimed to develop and implement an antimicrobial stewardship education program for physician assistant nurses and to evaluate its effects on their knowledge and clinical performance. Methods: A quasi-experimental, single-group pre-post design was conducted with 50 physician assistant nurses at a university hospital in Seoul, Republic of Korea. The antimicrobial stewardship education program, developed using the ADDIE model, consisted of 12 sessions including lectures and case-based learning (CBL)-based discussions.Knowledge was measured before and immediately after the intervention, while performance was assessed pre-intervention and four weeks post-program. Data were analyzed using paired t-tests, Wilcoxon signed-rank tests, and analysis of covariance (ANCOVA). Results: Knowledge scores significantly improved from 44.65±7.45 to 58.50±10.11 (p<.001), and all subdomains showed significant increases (p<.001). Performance scores increased from 3.68±0.77 to 4.28±0.68 (p<.001). Knowledge gain did not differ significantly between the medical and surgical departments (p=.710). Likewise, after adjusting for pre-test scores, no significant difference in performance improvement was observed between the two departments (ANCOVA, p=.170). These results indicate that the program was effective across both departments regardless of their characteristics. Conclusion The antimicrobial stewardship education program improved both knowledge and performance among physician assistant nurses. This program may contribute to the standardization of antimicrobial stewardship education and to appropriate antimicrobial use and the reduction of antimicrobial resistance.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2022, with international comparisons. Materials and Methods: Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2022), with survival follow-up until December 31, 2023. Mortality data obtained from Statistics Korea, while international comparisons were based on GLOBOCAN data. Results: In 2022, 282,047 newly diagnosed cancer cases (age-standardized rate [ASR], 287.0 per 100,000) and 83,378 deaths from cancer (ASR, 65.7 per 100,000) were reported. The proportion of localized-stage cancers increased from 45.6% in 2005 to 50.9% in 2022. Stomach, colorectal, and breast cancer showed increased localized-stage diagnoses by 18.1, 18.5, and 9.9 percentage points, respectively. Compared to 2001-2005, the 5-year relative survival (2018-2022) increased by 20.4 percentage points for stomach cancer, 7.6 for colorectal cancer, and 5.6 for breast cancer. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence (M/I) ratios for these cancers. The 5-year relative survival (2018-2022) was 72.9%, contributing to over 2.59 million prevalent cases in 2022. Conclusion Since the launch of the National Cancer Screening Program in 2002, early detection has improved, increasing the diagnosis of localized-stage cancers and survival rates. Korea recorded the lowest M/I ratio among major comparison countries, demonstrating the effectiveness of its National Cancer Control Program.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Purpose: Thrombosis and bleeding significantly affect morbidity and mortality in myeloproliferative neoplasms (MPNs). The efficacy and safety of direct oral anticoagulants (DOACs) in MPN patients remain uncertain. Materials and Methods: We conducted a large, retrospective, nationwide cohort study using the Korean Health Insurance Review and Assessment Service database from 2010 to 2021. Results: Out of the 368 MPN patients included in the final analysis, 62.8% were treated with DOACs for atrial fibrillation (AF), and 37.2% for venous thromboembolism (VTE). The AF group was statistically older with higher CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes mellitus, prior stroke, transient ischemic attack, or thromboembolism, vascular disease, age 65-74 years, sex category [female]) scores compared to the VTE group. Antiplatelet agents were used in 51.1% of cases, and cytoreductive drugs in 79.3%, with hydroxyurea being the most common (64.9%). The median follow-up was 22.3 months, with 1-year cumulative incidence rates of thrombosis and bleeding at 11.1% and 3.7%, respectively. Multivariate analysis identified CHA2DS2-VASc scores ≥ 3 (hazard ratio [HR], 3.48), concomitant antiplatelet use (HR, 2.57), and cytoreduction (HR, 2.20) as significant thrombosis risk factors but found no significant predictors for major bleeding. Conclusion Despite the limitations of retrospective data, DOAC treatment in MPN patients seems effective and has an acceptable bleeding risk.