Background: In the era of nucleoside analogs (NA), we investigated the safety of using hepatitis B surface antigen (HBsAg)-positive grafts in liver transplantation (LT) using nationwide KOTRY data. Methods: Among 4,265 adult LTs in the KOTRY registry (April 2014–January 2020), 20 (0.5%) used HBsAg(+) grafts. The S(+) group was compared with HBsAg-nega-tive groups, both HBcAb(+) (C[+]) and HBcAb(−) (SC[−]), using 1:1 propensity scorematching. Patient and graft survival were evaluated using Kaplan–Meier analysis.Cox regression was used to identify prognostic factors. Results: No significant differences were observed in patient or graft survival be-tween S(+) and C(+) or SC(−) groups. Key prognostic factors for patient survivalincluded age, HCC, MELD score, ascites, and encephalopathy. For graft survival, HCC, preoperative HCC treatment, MELD score, ascites, and encephalopathy were significant. HBV recurrence occurred in the S(+) group, but did not compromise outcomes. Conclusion In HBV-endemic regions, HBsAg(+) liver grafts can be safely used to expand the donor pool without compromising LT outcomes when combined with appropriate prophylaxis.

Purpose: The present study aimed to develop 2 deep learning (DL) systems incorporating detection functions for the diagnosis of carotid artery calcifications (CACs) on panoramic radiographs and to compare their diagnostic performances using CAC-based, side-based, and patient-based evaluations. Materials and Methods: Panoramic radiographs from 290 patients with CACs and 290 control patients without CACs were used to develop 2 detection models: one designed to detect individual CACs across the entire radiograph (System 1) and another designed to detect CACs within the limited bilateral cervical areas (System 2). CAC-based performance was evaluated using recall, precision, and F1-score. Side-based and patient-based performances were assessed usingsensitivity, specificity, positive predictive value, negative predictive value, accuracy, and the area under the receiveroperating characteristic curve (AUC). Results: For System 1, CAC-based recall, precision, and F1-score were 0.81, 0.68, and 0.74, respectively. For System 2,the corresponding values were 0.90, 0.67, and 0.77. Side-based sensitivity, specificity, and AUC were 0.87, 0.80, and 0.83 for System 1, and 0.93, 0.84, and 0.89 for System 2. Patient-based sensitivity, specificity, and AUC were 0.93, 0.73,and 0.83 for System 1, and 0.95, 0.70, and 0.83 for System 2. Although a relatively large number of false positives were observed in CAC-based assessments, side-based and patient-based performances showed improvement. Conclusion Side-based and patient-based performances were sufficient when calculated on the basis of CAC-basedevaluations for diagnosing CACs on panoramic radiographs. When conducting studies of this type, performance assessments should include side-based and patient-based evaluations in addition to CAC-based analyses.

Purpose: In this study, we aimed to classify an implant system by comparing the types of implant thread shapes shown on radiographs using various Convolutional Neural Networks (CNNs), particularly Xception, InceptionV3, ResNet50V2, and ResNet101V2. The accuracy of the CNN based on the implant site was compared. Materials and Methods: A total of 1000 radiographic images, consisting of eight types of implants, were preprocessed by resizing and CLAHE filtering, and then augmented. CNNs were trained and validated for implant thread shape prediction. Grad-CAM was used to visualize class activation maps (CAM) on the implant threads shown within the radiographic image. Results: Averaged over 10 validation folds, each model achieved an AUC of over 0.96: AUC of 0.961 (95% CI 0.952–0.970) with Xception, 0.973 (95% CI 0.966-0.980) with InceptionV3, 0.980 (95% CI 0.974-0.988) with ResNet50V2, and 0.983 (95% CI 0.975-0.992) with ResNet101V2. Accuracy was higher in the posterior region than in the anterior area in all four models. Most CAMs highlighted the implant surface where the threads were present; however, some showed responses in other areas. Conclusion The CNN models accurately classified implants in all areas of the oral cavity according to the thread shape, using radiographic images.

Purpose: In this study, we aimed to classify an implant system by comparing the types of implant thread shapes shown on radiographs using various Convolutional Neural Networks (CNNs), particularly Xception, InceptionV3, ResNet50V2, and ResNet101V2. The accuracy of the CNN based on the implant site was compared. Materials and Methods: A total of 1000 radiographic images, consisting of eight types of implants, were preprocessed by resizing and CLAHE filtering, and then augmented. CNNs were trained and validated for implant thread shape prediction. Grad-CAM was used to visualize class activation maps (CAM) on the implant threads shown within the radiographic image. Results: Averaged over 10 validation folds, each model achieved an AUC of over 0.96: AUC of 0.961 (95% CI 0.952–0.970) with Xception, 0.973 (95% CI 0.966-0.980) with InceptionV3, 0.980 (95% CI 0.974-0.988) with ResNet50V2, and 0.983 (95% CI 0.975-0.992) with ResNet101V2. Accuracy was higher in the posterior region than in the anterior area in all four models. Most CAMs highlighted the implant surface where the threads were present; however, some showed responses in other areas. Conclusion The CNN models accurately classified implants in all areas of the oral cavity according to the thread shape, using radiographic images.

Purpose: In this study, we aimed to classify an implant system by comparing the types of implant thread shapes shown on radiographs using various Convolutional Neural Networks (CNNs), particularly Xception, InceptionV3, ResNet50V2, and ResNet101V2. The accuracy of the CNN based on the implant site was compared. Materials and Methods: A total of 1000 radiographic images, consisting of eight types of implants, were preprocessed by resizing and CLAHE filtering, and then augmented. CNNs were trained and validated for implant thread shape prediction. Grad-CAM was used to visualize class activation maps (CAM) on the implant threads shown within the radiographic image. Results: Averaged over 10 validation folds, each model achieved an AUC of over 0.96: AUC of 0.961 (95% CI 0.952–0.970) with Xception, 0.973 (95% CI 0.966-0.980) with InceptionV3, 0.980 (95% CI 0.974-0.988) with ResNet50V2, and 0.983 (95% CI 0.975-0.992) with ResNet101V2. Accuracy was higher in the posterior region than in the anterior area in all four models. Most CAMs highlighted the implant surface where the threads were present; however, some showed responses in other areas. Conclusion The CNN models accurately classified implants in all areas of the oral cavity according to the thread shape, using radiographic images.

Background: Purse-string suture is a simple technique to reduce wound size and to achieve complete or partial closure of skin defects. Objective: To classify situations in which purse-string sutures can be utilized and to assess the long-term size reduction and cosmetic outcome of the final scar. Methods: Patients (93 from Severance hospital and 12 from Gangnam Severance hospital) in whom purse-string sutures were used between January 2015 and December 2019 were retrospectively reviewed. Wound site, final reconstruction method, repair duration, final wound size, and Vancouver scar scale were assessed. Results: A total of 105 patients were reviewed. Lesions were located on the trunk (48 [45.7%]), limbs (32 [30.5%]), and face (25 [23.8%]). Mean ratio of wound length/primary defect length was 0.79±0.30. Multilayered purse-string suture showed the shortest duration from excision to final repair (p<0.001) and most effectively minimized the scar size (scar to defect size ratio 0.67±0.23, p=0.002). The average Vancouver scar scale measured at the latest followup visit at least 6 months postoperatively was 1.62, and the risk of hypertrophic scarring was 8.6%. There was no significant difference in the Vancouver scar scale and the risk of hypertrophic scarring between the different surgical method groups. Conclusion Purse-string sutures can be utilized in many stages of reconstruction to effectively reduce scar size without compromising the final cosmetic outcome.

Background: Dental evaluation and protection are important for preventing traumatic dental injuries when patients are under general anesthesia. The objective of the present study was to develop a questionnaire based on dentition-related risk factors that could serve as a valuable tool for dental evaluation and documentation. Methods: We developed a questionnaire for dental evaluation before administration of general anesthesia, investigated the association between patient-and-dentist responses and mouthguard fabrication, and assessed response agreement between 100 patients. Results: Protective mouthguards were fabricated for 27 patients who were identified as having a high risk of dental injury. There was a strong association between dentists’ responses and mouthguard fabrication, depending on the general oral health status, use of ceramic prosthesis, presence of masticatory pain related to periodontal diseases, gingival edema, and implants (P < 0.05). Response agreement between patients and dentists for items related to dental pain, loss of dental pulp vitality, root canal therapy, dental trauma, aesthetic prosthesis, tooth mobility, and implant prosthesis was high (Cohen’s kappa coefficient κ ≥ 0.6). Conclusions A high agreement was observed between patient-dentist responses and a strong association with mouthguard fabrication for items pertaining to ceramic prosthesis, masticatory pain, and dental implants. Patients with a “yes” response to these items are recommended to undergo a dental evaluation and use a dental protective device while under general anesthesia.

Background: Pathological gambling is associated with several adverse outcomes, including depression, suicide, divorce, loss of employment, and debt. However, studies on the prevalence of pathological gambling are limited in South Korea. We assessed the prevalence of pathological gambling and its related factors. Methods: Data were obtained from 500 community-dwelling adults aged 20–59 years living in Jeju, Korea. This study assessed pathological/problem gambling using the Korean version of the Diagnostic Interview Schedule. We used the Patient Health Questionnaire-9 to obtain information about depression. Results: Lifetime prevalence rates of pathological gambling and problem gambling were 1.2% and 7.2%, respectively. The association between pathological/problem gambling and depression was highly significant (p<0.001). Multivariate analysis revealed significant relationships between men gender (odds ratio [OR], 2.62; 95% confidence interval [CI], 1.18–5.84; p=0.018) and depression (OR, 2.84; 95% CI, 1.42–5.68; p<0.001) and pathological/problem gambling. Conclusion Pathological/problem gambling is highly associated with depression, indicating that clinicians should carefully evaluate and treat depression among gamblers.

Abstinence from prolonged psychostimulant use prompts stimulant withdrawal syndrome. Molecular adaptations within the dorsal striatum have been considered the main hallmark of stimulant abstinence. Here we explored striatal miRNA-target interaction and its impact on circulating miRNA marker as well as behavioral dysfunctions in methamphetamine (MA) abstinence. We conducted miRNA sequencing and profiling in the nonhuman primate model of MA abstinence, followed by miRNA qPCR, LC-MS/MS proteomics, immunoassays, and behavior tests in mice. In nonhuman primates, MA abstinence triggered a lasting upregulation of miR-137 in the dorsal striatum but a simultaneous downregulation of circulating miR-137. In mice, aberrant increase in striatal miR-137-dependent inhibition of SYNCRIP essentially mediated the MA abstinence-induced reduction of circulating miR-137. Pathway modeling through experimental deduction illustrated that the MA abstinence-mediated downregulation of circulating miR-137 was caused by reduction of SYNCRIP-dependent miRNA sorting into the exosomes in the dorsal striatum. Furthermore, diminished SYNCRIP in the dorsal striatum was necessary for MA abstinence-induced behavioral bias towards egocentric spatial learning. Taken together, our data revealed circulating miR-137 as a potential blood-based marker that could reflect MA abstinence-dependent changes in striatal miR-137/SYNCRIP axis, and striatal SYNCRIP as a potential therapeutic target for striatum-associated cognitive dysfunction by MA withdrawal syndrome.