Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Although gemcitabine-based regimens are widely used as an effective treatment for pancreatic cancer, acquired resistance to gemcitabine has become an increasingly common problem. Therefore, a novel therapeutic strategy to treat gemcitabine-resistant pancreatic cancer is urgently required. Piceamycin has been reported to exhibit antiproliferative activity against various cancer cells; however, its underlying molecular mechanism for anticancer activity in pancreatic cancer cells remains unexplored. Therefore, the present study evaluated the antiproliferation activity of piceamycin in a gemcitabine-resistant pancreatic cancer cell line and patient-derived pancreatic cancer organoids. Piceamycin effectively inhibited the proliferation and suppressed the expression of alpha-actinin-4, a gene that plays a pivotal role in tumorigenesis and metastasis of various cancers, in gemcitabine-resistant cells. Long-term exposure to piceamycin induced cell cycle arrest at the G0/G1 phase and caused apoptosis. Piceamycin alsoinhibited the invasion and migration of gemcitabine-resistant cells by modulating focal adhesion and epithelial-mesenchymal transition biomarkers. Moreover, the combination of piceamycin and gemcitabine exhibited a synergistic antiproliferative activity in gemcitabine-resistant cells. Piceamycin also effectively inhibited patient-derived pancreatic cancer organoid growth and induced apoptosis in the organoids. Taken together, these findings demonstrate that piceamycin may be an effective agent for overcoming gemcitabine resistance in pancreatic cancer.

Previous studies suggested effectiveness of psilocybin in the field of mental health. FDA designated psilocybin as a “breakthrough therapy” for the treatment of treatment-resistant depression (TRD) in 2018. This paper provided a review of psilocybin’s potential role in treatment of depression by focusing on published clinical trials. Studies showed that psilocybin, an agonist on 5-HT2A receptors, manifests antidepressant and anxiolytic effects by increasing glutamate transmission, reducing brain inflammation, decreasing default mode network activity. In terms of clinical trials, eleven studies (six open-label and five double blinded randomized clinical trials, DB-RCTs) trials exploring psilocybin’s impact on depression were found. Among open-label studies, a pilot study on TRD patients demonstrated significant reductions in depressive symptoms after two psilocybin sessions. Psilocybin also improved cognitive bias associated with depression. Extension studies confirmed sustained improvements and high remission rates. Among five DB-RCTs, two showed that psilocybin led to significant reductions in anxiety and depression in cancer patients, and the improvements sustained for over 6 months. In MDD, psilocybin showed rapid reductions in depression, with higher remission rates compared to escitalopram in a DB-RCT. Another DB-RCT showed that psilocybin induced higher decrease in depression around 6 hours after their administrations than placebo. The last DB-RCT showed that in patients with TRD, a single dose of psilocybin 25 mg, but not psilocybin 10 mg, resulted in superior antidepressant effect than psilocybin 1 mg. Overall, psilocybin showed promise in treating depression and anxiety, with notable safety profiles. Further research should explore optimal dosages and long-term effects.

Background: The risk of device thrombosis and device-oriented clinical outcomes with bioresorbable vascular scaffold (BVS) was reported to be significantly higher than with contemporary drug-eluting stents (DESs). However, optimal device implantation may improve clinical outcomes in patients receiving BVS. The current study evaluated mid-term safety and efficacy of Absorb BVS with meticulous device optimization under intravascular imaging guidance. Methods: The SMART-REWARD and PERSPECTIVE-PCI registries in Korea prospectively enrolled 390 patients with BVS and 675 patients with DES, respectively. The primary endpoint was target vessel failure (TVF) at 2 years and the secondary major endpoint was patientoriented composite outcome (POCO) at 2 years. Results: Patient-level pooled analysis evaluated 1,003 patients (377 patients with BVS and 626 patients with DES). Mean scaffold diameter per lesion was 3.24 ± 0.30 mm in BVS group.Most BVSs were implanted with pre-dilatation (90.9%), intravascular imaging guidance (74.9%), and post-dilatation (73.1%) at proximal to mid segment (81.9%) in target vessel.Patients treated with BVS showed comparable risks of 2-year TVF (2.9% vs. 3.7%, adjusted hazard ratio [HR], 1.283, 95% confidence interval [CI], 0.487–3.378, P = 0.615) and 2-year POCO (4.5% vs. 5.9%, adjusted HR, 1.413, 95% CI, 0.663–3.012,P = 0.370) than those with DES. The rate of 2-year definite or probable device thrombosis (0.3% vs. 0.5%, P = 0.424) was also similar. The sensitivity analyses consistently showed comparable risk of TVF and POCO between the 2 groups. Conclusion With meticulous device optimization under imaging guidance and avoidance of implantation in small vessels, BVS showed comparable risks of 2-year TVF and device thrombosis with DES.

It is unclear whether young adults with chronic obstructive pulmonary disease (COPD) are at an increased risk of rapid lung function decline. A total of 2,934 Korean adults aged 40–49 years who had consecutive lung function measurements were included. COPD was defined as pre-bronchodilator forced expiratory volume in 1 second (FEV 1 )/forced vital capacity < lower limit of normal. The risk of rapid decline in FEV 1 , defined as ≥ 60 mL/year, was assessed using multivariable logistic regression analysis. In the multivariable model, a significantly higher risk of rapid decline in FEV 1 was observed for the COPD group compared with the non-COPD group (adjusted odds ratio, 1.89; 95% confidence interval, 1.18–2.95), which was especially significant in subjects with FEV 1 less than the median value (< 110%pred) (P interaction = 0.017) and inactive physical activity (P interaction = 0.039). In conclusion, the risk of rapid FEV 1 decline was higher in young adults with COPD than in those without COPD, especially in those with FEV 1 less than the median value and inactive physical activity.

Background and Objectives: Although the shortage of donor is a common problem worldwide, a significant portion of unutilized hearts are classified as marginal donor (MD) hearts. However, research on the correlation between the MD and the prognosis of heart transplantation (HTx) is lacking. This study was conducted to investigate the clinical impact of MD in HTx. Methods: Consecutive 73 HTxs during 2014 and 2021 in a tertiary hospital were analyzed.MD was defined as follows; a donor age >55 years, left ventricular ejection fraction <50%, cold ischemic time >240 minutes, or significant cardiac structural problems. Preoperative characteristics and postoperative hemodynamic data, primary graft dysfunction (PGD), and the survival rate were analyzed. Risk stratification by Index for Mortality Prediction after Cardiac Transplantation (IMPACT) score was performed to examine the outcomes according to the recipient state. Each group was sub-divided into 2 risk groups according to the IMPACT score (low <10 vs. high ≥10). Results: A total of 32 (43.8%) patients received an organ from MDs. Extracorporeal membrane oxygenation was more frequent in the non-MD group (34.4% vs. 70.7, p=0.007) There was no significant difference in PGD, 30-day mortality and long-term survival between groups. In the subgroup analysis, early outcomes did not differ between low- and high-risk groups. However, the long-term survival was better in the low-risk group (p=0.01). Conclusions The outcomes of MD group were not significantly different from non-MD group. Particularly, in low-risk recipient, the MD group showed excellent early and longterm outcomes. These results suggest the usability of selected MD hearts without increasing adverse events.

Purpose: To compare the short-term clinical and radiologic outcomes of combined posterior cruciate ligament (PCL) and posterolateral complex (PLC) reconstruction to those of isolated PCL reconstruction (PCLR) for patients with posterolateral knee laxity less than grade III. Materials and Methods: We retrospectively reviewed 49 patients (51 knees) who underwent PCLR between January 2008 and December 2015. Patients with a minimum follow-up of 24 months were included and divided into two groups (group A, isolated PCLR; group B, combined PCL and PLC reconstruction). Clinical outcomes were evaluated as the International Knee Documentation Committee (IKDC) subjective, Lysholm, and Tegner activity scale scores. Radiologic outcomes were also assessed using the side-to-side differences in posterior tibial translation via stress radiographs. Results: A total of 30 cases were analyzed. There were no significant differences in the Lysholm and Tegner activity scale scores between the two groups preoperatively and at the final follow-up. However, group B showed a higher IKDC subjective score compared to group A at the final follow-up (group A, 72.8±8.9; group B, 77.7±10.1; p<0.05). Regarding the radiologic outcomes, group B also showed a significantly less side-to-side difference in posterior tibial translation compared to group A at the final follow-up (group A, 4.8±2.3 mm; group B, 3.8±2.1 mm; p<0.05). Conclusion Combined PCL and PLC reconstruction resulted in improved clinical and radiologic outcomes than isolated PCLR in patients who have less than grade III posterolateral laxity of the knee. In cases of PCL rupture with ambiguous PLC injury, combined PCL and PLC reconstruction may help to improve posterior residual laxity of the knee.

Coronavirus disease 2019 (COVID-19) has multiple negative impacts on the psychiatric health of both those previously infected and not infected with severe acute respiratory syndrome coronavirus 2. Moreover, the negative impacts of COVID-19 are closely associated with geographical region, culture, medical system, and ethnic background. We summarized the evidence of the impact of COVID-19 on the psychiatric health of the Korean population. This narrative review included thirteen research articles, which investigated the impact of COVID-19 on the psychiatric health of Koreans. COVID-19 survivors were reported to have a 2.4 times greater risk of developing psychiatric disorders compared to members of a control group, and anxiety and stress-related disorders were the most common newly diagnosed psychiatric illnesses. Studies also reported that COVID-19 survivors had a 3.33-fold higher prevalence of insomnia, a 2.72-fold higher prevalence of mild cognitive impairment, and a 3.09-fold higher prevalence of dementia compared to the control group. In addition, more than four studies have highlighted that the medical staff members, including nurses and medical students, exhibit a greater negative psychiatric impact of COVID-19. However, none of the articles investigated the biological pathophysiology or mechanism linking COVID-19 and the risk of diverse psychiatric disorders. Moreover, none of the studies were actual prospective studies. Thus, longitudinal studies are needed to more clearly elucidate the effect of COVID-19 on the psychiatric health of the Korean population. Lastly, studies focusing on preventing and treating COVID-19–associated psychiatric problems are needed to provide a benefit in real clinical settings.