Purpose: This meta-analysis was conducted to determine the effect size of anxiety and psychological outcomes of virtual reality interventions in patients with anxiety disorders. Methods: A total of 835 studies were initially identified, of which six were found to be suitable according to the PICO (P: Patients with social phobia, I: VR technology, C: non VR technology, O: Variables related to mental health). criteria. Results: An analysis of the effect size of these studies confirmed that virtual reality interventions were not statistically significantly effective for generalized anxiety disorder (standardized mean difference [SMD]=0.16, 95% confidence interval [CI]=-0.84 to 1.15), but exhibited statistically significant effects for social anxiety (SMD=-0.56, 95% CI=-0.87 to -0.25) disorder and relational anxiety disorder (SMD -0.83, 95% CI=-1.49 to -0.16). Although these interventions were not statistically significantly effective for depression (SMD=-0.40, 95% CI=-0.84 to 0.04), they were effective in reducing negative emotions (SMD=-0.75, 95% CI=-1.20 to -0.31). Conclusion Virtual reality interventions based on the desensitization effect may be considered a viable option for reducing anxiety disorders.

Purpose: This meta-analysis was conducted to determine the effect size of anxiety and psychological outcomes of virtual reality interventions in patients with anxiety disorders. Methods: A total of 835 studies were initially identified, of which six were found to be suitable according to the PICO (P: Patients with social phobia, I: VR technology, C: non VR technology, O: Variables related to mental health). criteria. Results: An analysis of the effect size of these studies confirmed that virtual reality interventions were not statistically significantly effective for generalized anxiety disorder (standardized mean difference [SMD]=0.16, 95% confidence interval [CI]=-0.84 to 1.15), but exhibited statistically significant effects for social anxiety (SMD=-0.56, 95% CI=-0.87 to -0.25) disorder and relational anxiety disorder (SMD -0.83, 95% CI=-1.49 to -0.16). Although these interventions were not statistically significantly effective for depression (SMD=-0.40, 95% CI=-0.84 to 0.04), they were effective in reducing negative emotions (SMD=-0.75, 95% CI=-1.20 to -0.31). Conclusion Virtual reality interventions based on the desensitization effect may be considered a viable option for reducing anxiety disorders.

Purpose: This meta-analysis was conducted to determine the effect size of anxiety and psychological outcomes of virtual reality interventions in patients with anxiety disorders. Methods: A total of 835 studies were initially identified, of which six were found to be suitable according to the PICO (P: Patients with social phobia, I: VR technology, C: non VR technology, O: Variables related to mental health). criteria. Results: An analysis of the effect size of these studies confirmed that virtual reality interventions were not statistically significantly effective for generalized anxiety disorder (standardized mean difference [SMD]=0.16, 95% confidence interval [CI]=-0.84 to 1.15), but exhibited statistically significant effects for social anxiety (SMD=-0.56, 95% CI=-0.87 to -0.25) disorder and relational anxiety disorder (SMD -0.83, 95% CI=-1.49 to -0.16). Although these interventions were not statistically significantly effective for depression (SMD=-0.40, 95% CI=-0.84 to 0.04), they were effective in reducing negative emotions (SMD=-0.75, 95% CI=-1.20 to -0.31). Conclusion Virtual reality interventions based on the desensitization effect may be considered a viable option for reducing anxiety disorders.

Purpose: Circulating cell-free DNA (cfDNA) has great potential in clinical oncology. The prognostic and predictive values of cfDNA in non–small cell lung cancer (NSCLC) have been reported, with epidermal growth factor receptor (EGFR), KRAS, and BRAF mutations in tumor-derived cfDNAs acting as biomarkers during the early stages of tumor progression and recurrence. However, extremely low tumor-derived DNA rates hinder cfDNA application. We developed an ultra-high-sensitivity lung version 1 (ULV1) panel targeting BRAF, KRAS, and EGFR hotspot mutations using small amounts of cfDNA, allowing for semi-quantitative analysis with excellent limit-of-detection (0.05%). Materials and Methods: Mutation analysis was performed on cfDNAs extracted from the plasma of 104 patients with NSCLC by using the ULV1 panel and targeted next-generation sequencing (CT-ULTRA), followed by comparison analysis of mutation patterns previously screened using matched tumor tissue DNA. Results: The ULV1 panel demonstrated robust selective amplification of mutant alleles, enabling the detection of mutations with a high degree of analytical sensitivity (limit-of-detection, 0.025%-0.1%) and specificity (87.9%-100%). Applying ULV1 to NSCLC cfDNA revealed 51.1% (23/45) samples with EGFR mutations, increasing with tumor stage: 8.33% (stage I) to 78.26% (stage IV). Semi-quantitative analysis proved effective for low-mutation-fraction clinical samples. Comparative analysis with PANAMutyper EGFR exhibited substantial concordance (κ=0.84). Conclusion Good detection sensitivity (~80%) was observed despite the limited volume (1 mL) and long-term storage (12-50 months) of plasma used and is expected to increase with high cfDNA inputs. Thus, the ULV1 panel is a fast and cost-effective method for early diagnosis, treatment selection, and clinical follow-up of patients with NSCLC.

Background: Diacylglycerol O-acyltransferase 2 (DGAT2) synthesizes triacylglycerol (TG) from diacylglycerol; therefore, DGAT2 is considered as a therapeutic target for steatosis. However, the consequence of inhibiting DGAT2 is not fully investigated due to side effects including lethality and lipotoxicity. In this article, we observed the role of DGAT2 in hepatocarcinoma. Methods: The role of DGAT2 is analyzed via loss-of-function assay. DGAT2 knockdown (KD) and inhibitor treatment on HepG2 cell line was analyzed. Cumulative analysis of cell metabolism with bioinformatic data were assessed, and further compared with different cohorts of liver cancer patients and non-alcoholic fatty liver disease (NAFLD) patients to elucidate how DGAT2 is regulating cancer metabolism. Results: Mitochondrial function is suppressed in DGAT2 KD HepG2 cell along with the decreased lipid droplets. In the aspect of the cancer, DGAT2 KD upregulates cell proliferation. Analyzing transcriptome of NAFLD and hepatocellular carcinoma (HCC) patients highlights negatively correlating expression patterns of 73 lipid-associated genes including DGAT2. Cancer patients with the lower DGAT2 expression face lower survival rate. DGAT2 KD cell and patients’ transcriptome show downregulation in estrogen- related receptor alpha (ESRRA) via integrated system for motif activity response analysis (ISMARA), with increased dimerization with corepressor prospero homeobox 1 (PROX1). Conclusion DGAT2 sustains the stability of mitochondria in hepatoma via suppressing ESRRA-PROX1 transcriptional network and hinders HCC from shifting towards glycolytic metabolism, which lowers cell proliferation.

Background: Preeclampsia (PE) is a hypertensive pregnancy disorder linked to placental dysfunction, often involving pathological lesions like acute atherosis, decidual vasculopathy, accelerated villous maturation, and fibrinoid deposition. However, there is no gold standard for the pathological diagnosis of PE and this limits the ability of clinicians to distinguish between PE and non-PE pregnancies. Recent advances in computational pathology have provided the opportunity to automate pathological analysis for diagnosis, classification, prediction, and prediction of disease progression. In this study, we assessed whether computational pathology could be used to identify PE placentas. Methods: A total of 168 placental whole-slide images (WSIs) of patients from Seoul National University Hospital (comprising 84 PE cases and 84 normal controls) were used for model development and internal validation. For external validation of the model, 76 placental slides (including 38 PE cases and 38 normal controls) were obtained from the Boramae Medical Center (BMC). To establish standard criteria for diagnosing PE and distinguishing it from controls using placental WSIs, patch characteristics and quantification of terminal and intermediate villi were employed. In unsupervised learning, K-means clustering was conducted as a feature obtained through an Auto Encoder to extract the ratio of each cluster for each WSI. For supervised learning, quantitative assessments of the villi were obtained using a U-Net-based segmentation algorithm. The prediction model was developed using an ensemble method and was compared with a clinical feature model developed by using placental size features. Results: Using ensemble modeling, we developed a model to identify PE placentas.The model showed good performance (area under the precision-recall curve [AUPRC], 0.771; 95% confidence interval [CI], 0.752–0.790), with 77.3% of sensitivity and 71.1% of specificity, whereas the clinical feature model showed an AUPRC 0.713 (95% CI, 0.694–0.732) with 55.6% sensitivity and 86.8% specificity. External validation of the predictive model employing the BMC-derived set of placental slides also showed good discrimination (AUPRC, 0.725; 95% CI, 0.720–0.730). Conclusion The proposed computational pathology model demonstrated a strong ability to identify preeclamptic placentas. Computational pathology has the potential to improve the identification of PE placentas.

Objectives: We conducted a meta-analysis of randomized controlled trials to investigate the therapeutic effects of mindfulnessbased interventions on depressive symptoms in patients with major depressive disorder. Methods: In February 2021, we searched Embase, MEDLINE, Cochrane Library, PsycINFO, CINAHL, and AMED. Under the guidance of the corresponding author, two evaluators independently reviewed and selected articles based on predetermined selection criteria. Results: Based on the selection criteria, we systematically screened and included a total of 12 randomized controlled trials comprising 720 cases for the final analysis. Utilizing a random-effects model for data analysis, we determined the Hedges’ g value to be 0.787, indicating a medium-sized effect according to Cohen’s interpretation. The 95% confidence interval for the effect size ranged from 0.414 to 1.160 (p-value < 0.0001). Conclusions This study reveals the potential effectiveness of mindfulness-based interventions in treating depressive symptoms among patients with major depressive disorder.

Purpose: Robotic single-site plus one-port myomectomy (RSOM) was designed to reduce the number of incision sites for greater cosmetic satisfaction of patients while retaining the benefits of conventional robotic multi-site myomectomy (CRM). Robotic single-site plus two-port myomectomy (RSTM) eliminated one port relative to conventional CRM, and RSOM achieved the same advantage with respect to RSTM. This study aimed to compare RSOM with RSTM in terms of their respective methodologies and surgical outcomes. Materials and Methods: The medical records of 230 patients who had undergone RSOM and 146 patients who had undergone RSTM were reviewed. The groups’ surgical outcomes were compared using propensity score matching (PSM) analysis. Results: In the total data, RSOM had a shorter operative time (135.1±57.4 min vs. 149.9±46.2 min, p=0.009) and a shorter hospital stay (5.2±0.5 days vs. 5.4±0.7 days, p=0.033) relative to RSTM. The PSM analysis showed that there were no statistically significant intergroup differences in the patients’ baseline characteristics. Regarding the surgical outcomes, the RSOM group showed shorter operative time (129.2±49.3 min vs. 148.7±46.3 min, p=0.001) compared to the RSTM group. Conclusion Compared with RSTM, RSOM was associated with shorter operative time. Additionally, more detailed comparative and prospective studies are needed to evaluate RSOM relative to RSTM.

Purpose: The aims of this study were to evaluate the cumulative recurrence, reoperation, and pregnancy rates after ovarian endometrioma surgery at a single institution for more than a 5-year follow-up period. Materials and Methods: This study was conducted as a retrospective chart review of patients with ovarian endometrioma who underwent surgery between January 2008 and March 2016. Study subjects included premenopausal women with at least 5 years of follow-up. Exclusion criteria were patients with stage I or II ovarian endometrioma, those who underwent hysterectomy or bilateral oophorectomy, and presence of residual ovarian lesions on the first postoperative ultrasonography at 3–6 months. Recurrence was defined as a cystic mass by ultrasonography. Results: A total of 756 patients were recruited. The median follow-up duration was 85.5 months (interquartile range, 71–107 months). Recurrent endometrioma was detected in 27.9% patients, and reoperation was performed in 8.3% patients. Cumulative rates at 24, 36, 60, and 120 months were 5.8%, 8.7%, 15.5% and 37.6%, respectively, for recurrence and 0.1%, 0.5%, 2.9%, and 15.1%, respectively, for reoperation. After multivariable analysis, age ≤31 years [hazard ratio (HR)=2.108; 95% confidence interval (CI)=1.522–2.921; p<0.001], no subsequent pregnancy (HR=1.851; 95% CI=1.309–2.617; p<0.001), and postoperative hormonal treatment ≤15 months (HR=2.869; 95% CI=2.088–3.941; p<0.001) were significant risk factors for recurrent endometrioma. Among 315 patients who desired pregnancy, 54.0% were able to have a successful pregnancy and delivery. Conclusion Considering that longer postoperative hormonal treatment is the sole modifiable factor for recurrent endometrioma, we recommend long-term hormonal treatment until subsequent pregnancy, especially in younger women.

Purpose: Biliary tract cancers (BTCs) are rare and show a dismal prognosis with limited treatment options. To improve our understanding of these heterogeneous tumors and develop effective therapeutic agents, suitable preclinical models reflecting diverse tumor characteristics are needed. We established and characterized new patient-derived cancer cell cultures and patient-derived xenograft (PDX) models using malignant ascites from five patients with BTC. Materials and Methods: Five patient-derived cancer cell cultures and three PDX models derived from malignant ascites of five patients with BTC, AMCBTC-01, -02, -03, -04, and -05, were established. To characterize the models histogenetically and confirm whether characteristics of the primary tumor were maintained, targeted sequencing and histopathological comparison between primary tissue and xenograft tumors were performed. Results: From malignant ascites of five BTC patients, five patient-derived cancer cell cultures (100% success rate), and three PDXs (60% success rate) were established. The morphological characteristics of three primary xenograft tumors were compared with those of matched primary tumors, and they displayed a similar morphology. The mutated genes in samples (models, primary tumor tissue, or both) from more than one patient were TP53 (n=2), KRAS (n=2), and STK11 (n=2). Overall, the pattern of commonly mutated genes in BTC cell cultures was different from that in commercially available BTC cell lines. Conclusion We successfully established the patient-derived cancer cell cultures and xenograft models derived from malignant ascites in BTC patients. These models accompanied by different genetic characteristics from commercially available models will help better understand BTC biology.