BACKGROUND: Exogenous Cushing’s syndrome, which results from prolonged glucocorticoid treatment, is associated with metabolic abnormalities. Previously, we reported the inhibitory effect of tonsil-derived mesenchymal stem cell conditioned medium (T-MSC CM) on glucocorticoid signal transduction. In this study, we investigated the therapeutic efficacy of T-MSCs in a mouse model of exogenous Cushing’s syndrome. METHODS: Exogenous Cushing’s syndrome model mice was generated by corticosterone administration in the drinking water for 5 weeks, and T-MSCs were injected intraperitoneally twice during the third week. Serum lipid profiles were measured using a chemistry analyzer. HepG2 cells were treated with dexamethasone and co-cultured with T-MSCs.Expression levels of genes involved in cholesterol metabolism were examined using real-time PCR. Low-density lipoprotein receptor (LDLR) protein levels were determined using western blotting and immunohistochemistry. Liver RNA extracted from the CORT and CORT ? MSC mouse groups was used for transcriptome sequencing analysis and protein– protein interaction analysis. RESULTS: Weight reduction and improvements in dyslipidemia by T-MSC administration were observed only in female mice. T-MSCs reduce circulating LDL cholesterol levels by downregulating liver X receptor a (LXRa) and inducible degrader of LDLR (IDOL) expression, thereby stabilizing LDLRs in the liver. Transcriptome analysis of liver tissue revealed pathways that are regulated by T-MSCs administration. CONCLUSION Administration of MSCs to female mice receiving chronic corticosterone treatment reduced the circulating LDL cholesterol level by downregulating the LXRa–IDOL axis in hepatocytes. These results suggest that T-MSCs may offer a novel therapeutic strategy for managing exogenous Cushing’s syndrome by regulating cholesterol metabolism.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Purpose: This study aims to evaluate the treatment approaches and locoregional patterns for adenoid cystic carcinoma (ACC) in the breast, which is an uncommon malignant tumor with limited clinical data. Materials and Methods: A total of 93 patients diagnosed with primary ACC in the breast between 1992 and 2022 were collected from multi-institutions. All patients underwent surgical resection, including breast-conserving surgery (BCS) or total mastectomy (TM). Recurrence patterns and locoregional recurrence-free survival (LRFS) were assessed. Results: Seventy-five patients (80.7%) underwent BCS, and 71 of them (94.7%) received post-operative radiation therapy (PORT). Eighteen patients (19.3%) underwent TM, with five of them (27.8%) also receiving PORT. With a median follow-up of 50 months, the LRFS rate was 84.2% at 5 years. Local recurrence (LR) was observed in five patients (5.4%) and four cases (80%) of the LR occurred in the tumor bed. Three of LR (3/75, 4.0%) had a history of BCS and PORT, meanwhile, two of LR (2/18, 11.1%) had a history of mastectomy. Regional recurrence occurred in two patients (2.2%), and both cases had a history of PORT with (n=1) and without (n=1) irradiation of the regional lymph nodes. Partial breast irradiation (p=0.35), BCS (p=0.96) and PORT in BCS group (p=0.33) had no significant association with LRFS. Conclusion BCS followed by PORT was the predominant treatment approach for ACC of the breast and LR mostly occurred in the tumor bed. The findings of this study suggest that partial breast irradiation might be considered for PORT in primary breast ACC.

Objective: Several miRNAs have been identified as differentially expressed in patients with poor ovarian response (POR) compared to those with normal responses. This study aims to assess the potential of serum miR-329-3p as a biomarker for diagnosing POR. Methods: We conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to confirm the target genes of miR-329-3p. KGN cells were transfected with both miR-329-3p mimic and inhibitor to assess the differential expression of these target genes. In accordance with the Bologna criteria, we enrolled 16 control patients and 16 patients with POR. We collected patient samples, including serum from day 2 and the human chorionic gonadotropin (hCG) day, as well as granulosa and cumulus cells, to validate the expression of miR-329-3p using quantitative real-time polymerase chain reaction. Results: KEGG pathway analysis revealed that miR-329-3p targeted adenylyl cyclase 9 (ADCY9) and protein kinase A subunit beta (PRKACB), both of which are involved in ovarian steroidogenesis. In KGN cells treated with a miR-329-3p mimic, ADCY9 and PRKACB expression levels were significantly reduced (p<0.05). Elevated levels of miR-329-3p suppressed aromatase expression and 17β-estradiol production by modulating ADCY9 and PRKACB in KGN cells. These effects were also observed in POR patients. Follicle-stimulating hormone receptor (FSHR) expression was diminished in the granulosa cells of POR patients. On day 2, on hCG day, and in granulosa cells, miR-329-3p exhibited high expression levels in the serum of POR patients. Conclusion miR-329-3p exhibited increased expression in granulosa cells and in the sera of POR patients. Consequently, we propose that miR-329-3p may be a potential biomarker for the diagnosis of POR.

Background: Dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, reduces hyperglycemia and obesity by inhibiting renal glucose reabsorption. This post hoc study evaluated clinical factors influencing patient response to dapagliflozin. Methods: The analysis focused on patients treated with dapagliflozin (10 mg/day for 52 weeks) within the randomized, double-blind, parallel-group BEYOND trial. Adequate glycemic control (GC) was defined as a reduction in glycated hemoglobin (HbA1c) of ≥ 1.0% or the achievement of an HbA1c level <7.0% at week 52. Significant weight loss (WL) referred to a reduction in body weight of ≥3.0% at week 52. Participants were classified into four groups based on their GC and WL responses: GC+/WL+, GC+/WL−, GC−/WL+, and GC−/WL−. Results: Among dapagliflozin recipients (n=56), at 52 weeks, HbA1c had decreased by 1.0%±0.8% from baseline, while body weight had declined by 2.4±3.1 kg. Overall, 69.6% of participants achieved GC+, and 57.1% achieved WL+. Male sex and shorter diabetes duration were significantly associated with achieving GC+. Conversely, higher estimated glomerular filtration rate was significantly linked to WL+. The only factor significantly associated with both GC+ and WL+ was shorter diabetes duration (odds ratio, 0.81; 95% confidence interval, 0.68 to 0.97; P=0.023). The GC+ and WL+ groups exhibited favorable responses beginning soon after dapagliflozin therapy was initiated. Furthermore, HbA1c decline was more strongly associated with reduction in visceral fat than with WL. Conclusion A short duration of diabetes and early response to treatment appear to represent key factors in maximizing the benefits of dapagliflozin for blood glucose and weight management.

Objective: As the demand for community mental health services continues to grow, the need for well-equipped and organized services has become apparent. This study aimed to optimize the roles and infrastructure of mental health services, by establishing, among other initiatives, standardized operating models. Methods: The study was conducted in multiple phases from May 12, 2021, to December 29, 2021. Stakeholders within South Korea and metropolitan mental health welfare centers were targeted, but addiction management support centers, including officials, patients, and their families, were integrated as well. A literature review and survey, focus group interviews, a Delphi survey, and expert consultation contributed to comprehensive revisions and improvements of the mental health service model. Results: The proposed model for community mental health welfare centers emphasizes the expansion of personnel and infrastructure, with a focus on severe mental illnesses and suicide prevention. The model for metropolitan mental health welfare centers delineates essential tasks in areas such as project planning and establishment, community research, and education about severe mental illnesses. The establishment of a 24-hour emergency intervention center was a crucial feature. In the integrated addiction support center model, the need to promote addiction management is defined as an essential task and the establishment of national governance for addiction policies is recommended. Conclusion This study proposed standard operating models for three types of mental health service centers. To meet the increasing need for community care, robust mental health service delivery systems are of primary importance.

BACKGROUND: Exogenous Cushing’s syndrome, which results from prolonged glucocorticoid treatment, is associated with metabolic abnormalities. Previously, we reported the inhibitory effect of tonsil-derived mesenchymal stem cell conditioned medium (T-MSC CM) on glucocorticoid signal transduction. In this study, we investigated the therapeutic efficacy of T-MSCs in a mouse model of exogenous Cushing’s syndrome. METHODS: Exogenous Cushing’s syndrome model mice was generated by corticosterone administration in the drinking water for 5 weeks, and T-MSCs were injected intraperitoneally twice during the third week. Serum lipid profiles were measured using a chemistry analyzer. HepG2 cells were treated with dexamethasone and co-cultured with T-MSCs.Expression levels of genes involved in cholesterol metabolism were examined using real-time PCR. Low-density lipoprotein receptor (LDLR) protein levels were determined using western blotting and immunohistochemistry. Liver RNA extracted from the CORT and CORT ? MSC mouse groups was used for transcriptome sequencing analysis and protein– protein interaction analysis. RESULTS: Weight reduction and improvements in dyslipidemia by T-MSC administration were observed only in female mice. T-MSCs reduce circulating LDL cholesterol levels by downregulating liver X receptor a (LXRa) and inducible degrader of LDLR (IDOL) expression, thereby stabilizing LDLRs in the liver. Transcriptome analysis of liver tissue revealed pathways that are regulated by T-MSCs administration. CONCLUSION Administration of MSCs to female mice receiving chronic corticosterone treatment reduced the circulating LDL cholesterol level by downregulating the LXRa–IDOL axis in hepatocytes. These results suggest that T-MSCs may offer a novel therapeutic strategy for managing exogenous Cushing’s syndrome by regulating cholesterol metabolism.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Objective: Pain is a significant and debilitating symptom of rheumatoid arthritis (RA) that significantly affects the quality of life and functional ability of patients. In the present study, we examined the association between pain variables and disease activity markers in patients with RA. Methods: We enrolled 133 patients with RA and assessed their clinical characteristics, socioeconomic and psychological factors, and pain measures. The psychological factors assessed included depressive symptoms and pain catastrophizing. Results: The study cohort comprised predominantly female patients with RA with an average age of 55.5±10.1 years. Depressive symptoms had a mean score of 5.83±4.71, while pain catastrophizing had an average score of 14.36±10.70. The mean scores for pain intensity, and pain interference, were 2.98±1.75 and 19.54±16.17, respectively, with significant positive correlations observed with depressive symptoms. Hemoglobin and hematocrit levels were negatively correlated with pain intensity. Multivariable linear regression analysis revealed significant associations between depressive symptoms and pain intensity, catastrophizing, and interference. Other factors associated with pain intensity included tender joint count. Pain catastrophizing was associated with education and economic status. Pain interference was associated with sex and economic status. Conclusion This study shows the influence of disease-related indicators and psychological factors on pain in patients with RA, with depressive symptoms playing a crucial role in predicting pain experience. Effective pain management strategies for RA should include the management of depressive symptoms, in addition to addressing disease-related indicators.