Avocado oil is prized for its high nutritional value due to the substantial amounts of triglycerides (TGs) and unsaturated fatty acids (FAs) present. While avocado oil is traditionally extracted from mature fruit flesh, alternative sources such as avocado seed oil have recently increased in popularity. Unfortunately, sufficient evidence is not available to support the claimed health benefit and safe use of such oils. To address potential quality issues and identify possible adulteration, authenticated avocado oils extracted from the fruit peel, pulp and seed by supercritical fluid extraction (SFE), as well as commercial avocado pulp and seed oils sold in US market were analyzed for TGs and FAs in the present study. Characterization and quantification of TGs were conducted using UHPLC/ESI-MS. Thirteen TGs containing saturated and unsaturated fatty acids in avocado oils were unambiguously identified. Compared to traditional analytical methods, which are based only on the relative areas of chromatographic peaks neglecting the differences in the relative response of individual TG, our method improved the quantification of TGs by using the reference standards whenever possible or the reference standards with the same equivalent carbon number (ECN). To verify the precision and accuracy of the UHPLC/ESI-MS method, the hydrolysis and transesterification products of avocado oil were analyzed for fatty acid methyl esters using a GC/MS method. The concentrations of individual FA were calculated, and the results agreed with the UHPLC/ESI-MS method. Although chemical profiles of avocado oils from pulp and peel are very similar, a significant difference was observed for the seed oil. Principal component analysis (PCA) based on TG and FA compositional data allowed correct identification of individual avocado oil and detection of possible adulteration.Background This retrospective study was conducted to investigate the independent risk factors of hypotensive and bradycardic events (HBEs) in shoulder arthroscopic surgery under interscalene blocks (ISB) in the sitting position. Methods A total of 2549 patients who underwent shoulder arthroscopic surgery under ISB and had complete clinical data were included in the study. https://www.selleckchem.com/products/gsk3326595-epz015938.html The 357 patients who developed HBEs were included in the HBEs group, and the remaining 2192 in the non-HBEs group. The potential risk factors for HBEs, such as age, sex, past medical history, anesthetic characteristics, and intraoperative medications were collected and compared between groups. Statistically significant variables were included in a logistic regression model to further evaluate the independent risk factors for HBEs in shoulder arthroscopic surgery under ISB. Results The incidence of HBEs was 14.0% (357/2549). Logistic regression analysis revealed that the intraoperative use of hydralazine (OR 4.2; 95% CI 2.9-6.3), propofol (OR 2.1; 95% CI 1.3-3.6) and dexmedetomidine (OR 3.9; 95% CI 1.9-7.8) before HBEs were independent risk factors for HBEs in patients who received shoulder arthroscopic surgery under ISB. Conclusions The intraoperative use of antihypertensives such as hydralazine and sedatives such as propofol or dexmedetomidine leads to increased risk of HBEs during shoulder arthroscopic surgery under ISB in the sitting position.OBJECTIVE Suicidal ideation (SI) precedes actual suicidal event. Thus, it is important for the prevention of suicide to screen the individuals with SI. This study aimed to identify the factors associated with SI and to build prediction models in Korean adults using machine learning methods. METHODS The 2010-2013 dataset of the Korea National Health and Nutritional Examination Survey was used as the training dataset (n=16,437), and the subset collected in 2015 was used as the testing dataset (n=3,788). Various machine learning algorithms were applied and compared to the conventional logistic regression (LR)-based model. RESULTS Common risk factors for SI included stress awareness, experience of continuous depressive mood, EQ-5D score, depressive disorder, household income, educational status, alcohol abuse, and unmet medical service needs. The prediction performances of the machine learning models, as measured by the area under receiver-operating curve, ranged from 0.794 to 0.877, some of which were better than that of the conventional LR model (0.867). The Bayesian network, LogitBoost with LR, and ANN models outperformed the conventional LR model. CONCLUSION A machine learning-based approach could provide better SI prediction performance compared to a conventional LR-based model. These may help primary care physicians to identify patients at risk of SI and will facilitate the early prevention of suicide.OBJECTIVE Limited data exist on non-suicidal self-injury (NSSI) and suicide attempts among psychiatric patients in Korea. In this study, we investigated the clinical characteristics of patients who engaged in NSSI and/or suicide attempts. METHODS We performed a retrospective medical chart review of patients with NSSI and/or suicide attempts at the psychiatric department of a university medical center in Seoul between 2017 and 2019. According to their history, patients were allocated to one of three groups NSSI only, suicide attempts only and NSSI and suicide attempts group. Groups were compared based on sociodemographic characteristics and psychological assessments. RESULTS Overall, 80 patients with NSSI and/or suicide attempts were evaluated. Patients with NSSI and suicide attempts were more likely to be female than the other two groups. Patients with NSSI and suicide attempts were more likely to suffer from Cluster B personality disorder than the other groups. And patients with NSSI and suicide attempts scored significantly higher on novelty-seeking in TCI and RC8, RC9 in MMPI-2. CONCLUSION Patients with NSSI and/or suicide attempts were more likely to be female, younger, and showed higher levels of psychological disturbances. These findings highlight the importance of early detection and intervention for patients with NSSI.OBJECTIVE The aim of study is to investigate the relationship between serum vitamin D, c-reactive protein (CRP) levels, and anxiety symptoms. METHODS Serum vitamin D and CRP levels of 51,003 Korean adult participants were collected retrospectively. Anxiety symptoms were assessed using the Korean version of Beck Anxiety Inventory. Logistic regression was used to estimate the odds ratio (ORs) of anxiety symptoms by serum vitamin D and CRP levels. The regression was adjusted for covariates, and each model was adjusted mutually for vitamin D and CRP levels. RESULTS Compared with sufficient vitamin D levels (≥20 ng/mL), insufficient (10-19.99 ng/mL) and deficient ( less then 10 ng/mL) vitamin D levels were significantly associated with risk of anxiety symptoms. Also, continuous vitamin D levels were negatively associated with the risk of anxiety symptoms. CRP levels did not affect the relationship between vitamin D levels and risk of anxiety symptoms. CONCLUSION Insufficient (10-19.99 ng/mL) and deficient ( less then 10 ng/mL) vitamin D levels were significantly associated with risk of anxiety symptoms.