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.

Background: This study aimed to identify the effect of histamine-2 receptor antagonist (H2RA) and proton pump inhibitor (PPI) use on the positivity rate and clinical outcomes of coronavirus disease 2019 (COVID-19). Methods: We performed a nationwide cohort study with propensity score matching using medical claims data and general health examination results from the Korean National Health Insurance Service. Individuals aged ≥ 20 years who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between 1 January and 4 June 2020 were included.Patients who were prescribed H2RA or PPI within 1 year of the test date were defined as H2RA and PPI users, respectively. The primary outcome was SARS-CoV-2 test positivity, and the secondary outcome was the instance of severe clinical outcomes of COVID-19, including death, intensive care unit admission, and mechanical ventilation administration. Results: Among 59,094 patients tested for SARS-CoV-2, 21,711 were H2RA users, 12,426 were PPI users, and 24,957 were non-users. After propensity score matching, risk of SARS-CoV-2 infection was significantly lower in H2RA users (odds ratio [OR], 0.85; 95% confidence interval [CI], 0.74–0.98) and PPI users (OR, 0.62; 95% CI, 0.52–0.74) compared to non-users. In patients with comorbidities including diabetes, dyslipidemia, and hypertension, the effect of H2RA and PPI against SARS-CoV-2 infection was not significant, whereas the protective effect was maintained in patients without such comorbidities. Risk of severe clinical outcomes in COVID-19 patients showed no difference between users and non-users after propensity score matching either in H2RA users (OR, 0.89; 95% CI, 0.52–1.54) or PPI users (OR, 1.22; 95% CI, 0.60–2.51). Conclusion H2RA and PPI use is associated with a decreased risk for SARS-CoV-2 infection but does not affect clinical outcome. Comorbidities including diabetes, hypertension, and dyslipidemia seem to offset the protective effect of H2RA and PPI.

This review aims to define the 4 types of the metaverse and to explain the potential and limitations of its educational applications. The metaverse roadmap categorizes the metaverse into 4 types: augmented reality, lifelogging, mirror world, and virtual reality. An example of the application of augmented reality in medical education would be an augmented reality T-shirt that allows students to examine the inside of the human body as an anatomy lab. Furthermore, a research team in a hospital in Seoul developed a spinal surgery platform that applied augmented reality technology. The potential of the metaverse as a new educational environment is suggested to be as follows: a space for new social communication; a higher degree of freedom to create and share; and the provision of new experiences and high immersion through virtualization. Some of its limitations may be weaker social connections and the possibility of privacy impingement; the commission of various crimes due to the virtual space and anonymity of the metaverse; and maladaptation to the real world for students whose identity has not been established. The metaverse is predicted to change our daily life and economy beyond the realm of games and entertainment. The metaverse has infinite potential as a new social communication space. The following future tasks are suggested for the educational use of the metaverse: first, teachers should carefully analyze how students understand the metaverse; second, teachers should design classes for students to solve problems or perform projects cooperatively and creatively; third, educational metaverse platforms should be developed that prevent misuse of student data.

Changes in the expression profiles of specific proteins leads to serious human diseases, including colitis. The proteomic changes related to colitis and the differential expression between tuberculous (TC) and ulcerative colitis (UC) in colon tissue from colitis patients has not been defined. We therefore performed a proteomic analysis of human TC and UC mucosal tissue. Total protein was obtained from the colon mucosal tissue of normal, TC, and UC patients, and resolved by 2-dimensional electrophoresis (2-DE). The results were analyzed with PDQuest using silver staining. We used matrix-assisted laser desorption ionization time-of-flight/time-of-flight spectrometry (MALDI TOF/TOF) to identify proteins differentially expressed in TC and UC. Of the over 1,000 proteins isolated, three in TC tissue and two in UC tissue displayed altered expression when compared to normal tissue. Moreover, two proteins were differentially expressed in a comparative analysis between TC and UC. These were identified as mutant beta-actin, alpha-enolase and Charcot-Leyden crystal protein. In particular, the expression of alpha-enolase was significantly greater in TC compared with normal tissue, but decreased in comparison to UC, implying that alpha-enolase may represent a biomarker for differential diagnosis of TC and UC. This study therefore provides a valuable resource for the molecular and diagnostic analysis of human colitis.
Actins ; Colitis ; Colitis, Ulcerative ; Colon ; Diagnosis, Differential ; Electrophoresis ; Glycoproteins ; Humans ; Lysophospholipase ; Mucous Membrane ; Phosphopyruvate Hydratase ; Proteins ; Proteomics ; Silver Staining ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ; Spectrum Analysis ; Ulcer

HoxB4, a homeodomain-containing transcription factor, is involved in the expansion of hematopoietic stem cells and progenitor cells in vivo and in vitro, and plays a key role in regulating the balance between hematopoietic stem cell renewal and cell differentiation. However, the biological activity of HoxB4 in other cells has not been reported. In this study, we investigated the effect of overexpressed HoxB4 on cell survival under various conditions that induce death, using the Ba/F3 cell line. Analysis of phenotypical characteristics showed that HoxB4 overexpression in Ba/F3 cells reduced cell size, death, and proliferation rate. Moreover, the progression from early to late apoptotic stages was inhibited in Ba/F3 cells subjected to HoxB4 overexpression under removal of interleukin-3-mediated signal, leading to the induction of cell cycle arrest at the G2/M phase and attenuated cell death by Fas protein stimulation in vitro. Furthermore, apoptotic cell death induced by doxorubicin-treated G2/M phase cell-cycle arrest also decreased with HoxB4 overexpression in Ba/F3 cells. From these data, we suggest that HoxB4 may play an important role in the regulation of pro-B cell survival under various apoptotic death environments.
Apoptosis ; Cell Cycle Checkpoints ; Cell Death ; Cell Differentiation ; Cell Line ; Cell Proliferation ; Cell Size ; Cell Survival ; Hematopoietic Stem Cells ; Precursor Cells, B-Lymphoid ; Stem Cells ; Transcription Factors

PURPOSE: Mucopolysaccharidosis (MPS) is a lysosomal storage disease that causes tissue distortion and dysfunction due to the infiltration of mucopolysaccharide in connective tissue. The purpose of this study was to evaluate the characteristic findings of abdominal CT and plain chest radiography in patients with MPS. MATERIALS AND METHODS: Sixty-two children with MPS diagnosed by urine analysis were involved in this study; 24 of these underwent abdominal CT and the findings were reviewed by two radiologists, who reached a consensus. Organomegaly was classified as severe, moderate or mild. On chest PA radiographs of 42 of the children, the transverse diameter of the trachea was measured and compared with that of 42 normal controls. Student's t test was used for statistical analysis. RESUTLS: At abdominal CT, hepatomegaly was observed in 22 patients (92%; 2 severe, 15 moderate and 5 mild); and splenomegaly was present in 18 (75%; 2 severe, 4 moderate and 12 mild). Among eight patients (33%) with pancreatic enlargement, one had a severly enlarged pancreas, while in the remaining seven, enlargement was mild. Also present were inguinal hernia (n=15), umbilical hernia (n=12), undulation with thickening of the diaphragmatic crura (n=10), abnormalities related to the male genitalia (n=5) and vascular anomaly (n=3). In MPS patients, the mid-point diameter of the trachea (range, 5.6-9 mm; mean, 6.9 mm) was significantly less than in normal controls (range, 8-14 mm; mean, 10.8 mm) (p<0.001). CONCLUSION: An awareness of the characteristic abnormalities observed at abdominal CT and chest PA radiography can lead to a better understanding of MPS in children.
Abdomen* ; Child ; Connective Tissue ; Consensus ; Genitalia, Male ; Hepatomegaly ; Hernia, Inguinal ; Hernia, Umbilical ; Humans ; Lysosomal Storage Diseases ; Male ; Mucopolysaccharidoses* ; Musculoskeletal System* ; Pancreas ; Radiography ; Splenomegaly ; Thorax* ; Tomography, X-Ray Computed ; Trachea

PURPOSE: High frequency oscillatory ventilation (HFOV) is used to support infants with severe respiratory failure unresponsive to conventional ventilation (CV). We reviewed chest radiographs before and after HFOV with clinical correlation in infants with respiratory distress syndrome (RDS). METHODS: Eighteen very low birth weight infants with RDS who had HFOV were included in this study. All patients were diagnosed as having RDS clinically and radiologically. Mean gestational age of infants was 27 weeks (range : 24-31 weeks). The mean duration of HFOV was 3 days (range : 14 hours-9 days). The chest radiographs of these infants within 3 hours before and after application of HFOV were retrospectively reviewed. Radiological findings based on aeration and parenchymal densities were classified into improved, no change, and progressed. Medical records were reviewed for FiO2 levels, clinical outcomes, complications, and causes of death. RESULTS: In 15 of 18 infants, aeration and parenchymal densities were improved and FiO2 levels were also improved after HFOV. Four of these 15 infants who showed improvement of radiological findings developed pneumothorax, sepsis, pulmonary or intestinal bleeding, and subsequently died. In remaining 3 infants in whom chest radiographs after HFOV showed no interval change or progression, oxygenation was also worsened and all died. CONCLUSION: Chest radiographs of HFOV-treated, very low birth weight infants showed improvement of aeration and parenchymal densities in most cases. Clinical outcome was good in infants who showed improvement on chest radiographs compared to those of progression group as far as there was no associated complication. Knowledge of radiological changes after HFOV will help in interpretation of chest radiographs in those HFOV-treated infants.
Cause of Death ; Gestational Age ; Hemorrhage ; Humans ; Infant* ; Infant, Very Low Birth Weight* ; Medical Records ; Oxygen ; Pneumothorax ; Radiography, Thoracic ; Respiratory Insufficiency ; Retrospective Studies ; Sepsis ; Ventilation*

Mucinous cystic neoplasms of the pancreas are uncommon and known to occur mainly in middle-aged women. Wepresent a case of pancreatic mucinous cystadeno-carcinoma in an 11-year-old girl who had a past history of bluntabdominal trauma. The tumor was initially mistaken for a traumatic pseudocyst. US and CT revealed a multiloculatedcystic mass in the pancreatic tail. The mass showed good transmission on ultrasonography (US) and had anattenuation value of 10 HU on CT. Metastatic lesions in the liver were also shown on follow-up study.
Child* ; Cystadenocarcinoma, Mucinous* ; Female* ; Follow-Up Studies ; Humans ; Liver ; Mucins* ; Pancreas ; Ultrasonography