Purpose: Anorectal fistulas present a treatment challenge, with conventional surgical methods potentially resulting in complications such as fecal incontinence. To improve patient outcomes, more effective and minimally invasive therapies are critically needed. In this study, an optimal porcine model for the creation of anorectal fistulas was developed and used to evaluate the efficacy of radiofrequency ablation (RFA) therapy. Methods: Two distinct but related experiments were conducted. In the first experiment, a reliable and standardized porcine anorectal fistula model was developed. In the second, the healing process was assessed, and outcomes were compared between the RFA-treated group and the control group using the established porcine model. Results: The results indicated that a 3.5-cm fistula tract length and a 14-day evaluation period following seton removal are optimal for the porcine anorectal fistula model. In the second experiment, the RFA group tended to exhibit better outcomes regarding fistula closure, although the differences were not statistically significant. Histopathologically, no significant difference in inflammation grade was observed between groups; however, scar tissue was more predominant in the RFA group. Conclusion The findings suggest that RFA therapy may offer potential benefits in the treatment of anorectal fistulas, as demonstrated using a porcine model. To validate these results and explore the mechanisms of action underlying RFA therapy for anorectal fistulas, further research involving larger sample sizes and a more robust study design is required.

Although histone deacetylase 6 (HDAC6) is considered a therapeutic target for Alzheimer’s disease (AD), its role in cholinergic dysfunction in AD patients remains unclear. This study investigated the effects of (E)-3-(2-(4-fluorostyryl)thiazol-4-yl)-N-hydroxypropanamide (4-FHA), a new synthetic HDAC6 inhibitor, on cognitive and memory impairments in a scopolamine-induced-AD mouse model. Behaviorally, 4-FHA improved scopolamine-induced memory impairments in the Y-maze, passive avoidance, and Morris water maze tests. In addition, 4-FHA ameliorated scopolamine-induced cognitive impairments in the novel object recognition and place recognition tests. Furthermore, 4-FHA increased acetylation of α-tubulin (a major HDAC6 substrate); the expression of BDNF; and the phosphorylation of ERK 1/2, CREB, and ChAT in the hippocampus of scopolamine-treated mice. In summary, according to our data 4-FHA, an HDAC6 inhibitor, improved the cognitive and memory deficits of the AD mouse model by normalizing BDNF signaling and synaptic transmission, suggesting that 4-FHA might be a potential therapeutic candidate for AD.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Purpose: This study aimed to assess prognostic factors associated with combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and to predict 5-year survival based on these factors. Materials and Methods: Patients who underwent definitive hepatectomy from 2006 to 2022 at a single institution was retrospectively analyzed. Inclusion criteria involved a pathologically confirmed diagnosis of cHCC-CCA. Results: A total of 80 patients with diagnosed cHCC-CCA were included in the analysis. The median progression-free survival was 15.6 months, while distant metastasis-free survival (DMFS), hepatic progression-free survival, and overall survival (OS) were 50.8, 21.5, and 85.1 months, respectively. In 52 cases of recurrence, intrahepatic recurrence was the most common initial recurrence (34/52), with distant metastasis in 17 cases. Factors associated with poor DMFS included tumor necrosis, lymphovascular invasion (LVI), perineural invasion, and histologic compact type. Postoperative carbohydrate antigen 19-9, tumor necrosis, LVI, and close/positive margin were associated with poor OS. LVI emerged as a key factor affecting both DMFS and OS, with a 5-year OS of 93.3% for patients without LVI compared to 35.8% with LVI. Based on these factors, a nomogram predicting 3-year and 5-year DMFS and OS was developed, demonstrating high concordance with actual survival in the cohort (Harrell C-index 0.809 for OS, 0.801 for DMFS, respectively). Conclusion The prognosis of cHCC-CCA is notably poor when combined with LVI. Given the significant impact of adverse features, accurate outcome prediction is crucial. Moreover, consideration of adjuvant therapy may be warranted for patients exhibiting poor survival and increased risk of local recurrence or distant metastasis.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

The fundamental principles for treating ankle fractures, as with other intra-articular fractures, are anatomical reduction and stable internal fixation. Despite successful reduction, between 14% and 40% of patients continue to experience persistent pain or unsatisfactory functional outcomes. Furthermore, approximately 1% of patients progress to post-traumatic arthritis, necessitating further surgical intervention. Ankle fractures are frequently accompanied by intra-articular injuries, including osteochondral lesions, ligament tears, and syndesmosis injuries. Arthroscopy is becoming increasingly prevalent in managing acute ankle fractures by assessing intra-articular damage and facilitating accurate reduction. This review examined the role and indications for arthroscopy in ankle fractures, particularly emphasizing its benefits in diagnosing and managing associated injuries, including osteochondral lesions, syndesmosis, and deltoid ligament injuries. Furthermore, arthroscopy facilitates fracture reduction, offering a minimally invasive approach with a shorter recovery period and enhanced visualization. Its use extends to pediatric fractures and complex cases such as Maisonneuve and calcaneal fractures, potentially improving outcomes while minimizing complications. Understanding the evolving indications and benefits of arthroscopy for ankle fractures can lead to improved clinical outcomes and reduced complications.