Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Purpose: In this study, we investigated the effect of bisphenol-A (BPA) and its major analogs, bisphenol-F (BPF), and bisphenol-S (BPS), on spermatogonial stem cells (SSCs) populations using in vitro SSC culture and in vivo transplantation models. Materials and Methods: SSCs enriched from 6- to 8-day-old C57BL/6-eGFP+ male mice testes were treated with varying concentrations of bisphenols for 7 days to examine bisphenol-derived cytotoxicity and changes in SSC characteristics. We utilized flow cytometry, immunocytochemistry, real-time quantitative reverse transcription-PCR, and western blot analysis. The functional alteration of SSCs was further investigated by examining donor SSC-derived spermatogenesis evaluation through in vivo transplantation and subsequent testis analysis. Results: BPF exhibited a similar inhibitory effect on SSCs as BPA, demonstrating a significant decrease in SSC survival, inhibition of proliferation, and induction of apoptosis. On the other hand, while BPS was comparatively weaker than BPA and BPF, it still showed significant SSC cytotoxicity. Importantly, SSCs exposed to BPA, BPF, and BPS exhibited a significant reduction in donor SSC-derived germ cell colonies per total number of cultured cells, indicating that, like BPA, BPF, and BPS can induce a comparable reduction in functional SSCs in the recipient animals. However, the progress of spermatogenesis, as evidenced by histochemistry and the expressions of PCNA and SSC specific markers, collectively indicates that BPA, BPF, and BPS may not adversely affect the spermatogenesis. Conclusions Our findings indicate that the major BPA substitutes, BPF and BPS, have significant cytotoxic effects on SSCs, similar to BPA. These effects may lead to a reduction in the functional self-renewal stem cell population and potential impacts on male fertility.

Purpose: In this study, we investigated the effect of bisphenol-A (BPA) and its major analogs, bisphenol-F (BPF), and bisphenol-S (BPS), on spermatogonial stem cells (SSCs) populations using in vitro SSC culture and in vivo transplantation models. Materials and Methods: SSCs enriched from 6- to 8-day-old C57BL/6-eGFP+ male mice testes were treated with varying concentrations of bisphenols for 7 days to examine bisphenol-derived cytotoxicity and changes in SSC characteristics. We utilized flow cytometry, immunocytochemistry, real-time quantitative reverse transcription-PCR, and western blot analysis. The functional alteration of SSCs was further investigated by examining donor SSC-derived spermatogenesis evaluation through in vivo transplantation and subsequent testis analysis. Results: BPF exhibited a similar inhibitory effect on SSCs as BPA, demonstrating a significant decrease in SSC survival, inhibition of proliferation, and induction of apoptosis. On the other hand, while BPS was comparatively weaker than BPA and BPF, it still showed significant SSC cytotoxicity. Importantly, SSCs exposed to BPA, BPF, and BPS exhibited a significant reduction in donor SSC-derived germ cell colonies per total number of cultured cells, indicating that, like BPA, BPF, and BPS can induce a comparable reduction in functional SSCs in the recipient animals. However, the progress of spermatogenesis, as evidenced by histochemistry and the expressions of PCNA and SSC specific markers, collectively indicates that BPA, BPF, and BPS may not adversely affect the spermatogenesis. Conclusions Our findings indicate that the major BPA substitutes, BPF and BPS, have significant cytotoxic effects on SSCs, similar to BPA. These effects may lead to a reduction in the functional self-renewal stem cell population and potential impacts on male fertility.

Purpose: In this study, we investigated the effect of bisphenol-A (BPA) and its major analogs, bisphenol-F (BPF), and bisphenol-S (BPS), on spermatogonial stem cells (SSCs) populations using in vitro SSC culture and in vivo transplantation models. Materials and Methods: SSCs enriched from 6- to 8-day-old C57BL/6-eGFP+ male mice testes were treated with varying concentrations of bisphenols for 7 days to examine bisphenol-derived cytotoxicity and changes in SSC characteristics. We utilized flow cytometry, immunocytochemistry, real-time quantitative reverse transcription-PCR, and western blot analysis. The functional alteration of SSCs was further investigated by examining donor SSC-derived spermatogenesis evaluation through in vivo transplantation and subsequent testis analysis. Results: BPF exhibited a similar inhibitory effect on SSCs as BPA, demonstrating a significant decrease in SSC survival, inhibition of proliferation, and induction of apoptosis. On the other hand, while BPS was comparatively weaker than BPA and BPF, it still showed significant SSC cytotoxicity. Importantly, SSCs exposed to BPA, BPF, and BPS exhibited a significant reduction in donor SSC-derived germ cell colonies per total number of cultured cells, indicating that, like BPA, BPF, and BPS can induce a comparable reduction in functional SSCs in the recipient animals. However, the progress of spermatogenesis, as evidenced by histochemistry and the expressions of PCNA and SSC specific markers, collectively indicates that BPA, BPF, and BPS may not adversely affect the spermatogenesis. Conclusions Our findings indicate that the major BPA substitutes, BPF and BPS, have significant cytotoxic effects on SSCs, similar to BPA. These effects may lead to a reduction in the functional self-renewal stem cell population and potential impacts on male fertility.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.