PURPOSE: The purpose of this study was to investigate the casual relationship between nurses' mentoring and turnover intention and to verify the goodness of fit between a hypothetical model and actual data in order to suggest an adequate model. METHODS: The survey was conducted with 434 nurses working in general hospitals in Seoul. Data were collected during February 2013, and analyzed with SPSS Windows 18.0 and AMOS 7.0. RESULTS: Mentoring was found to have a direct effect on decrease in role stress. Role stress had a direct effect on increase in burnout and mentoring, with role stress as a mediator, there was an indirect effect on burnout. Burnout had a direct effect on increase in turnover intention, and role stress, with burnout as a mediator, and mentoring, through role stress and burnout, an indirect effect was found on increase in turnover intention. CONCLUSION: The results of this study indicate that nursing managers should put effort into reducing role stress and burnout, while seeking to establish a more efficient mentoring system so that for nurses, there will be a lowering of turnover intention.
Adult ; Attitude of Health Personnel ; *Burnout, Professional ; Female ; Hospitals, General ; Humans ; Job Satisfaction ; Marriage ; Models, Theoretical ; Nursing Staff, Hospital/*psychology ; Personnel Turnover ; *Stress, Psychological

Background: There are limited data on the accuracy of cloud-based speech recognition (SR) open application programming interfaces (APIs) for medical terminology. This study aimed to evaluate the medical term recognition accuracy of current available cloud-based SR open APIs in Korean. Methods: We analyzed the SR accuracy of currently available cloud-based SR open APIs using real doctor–patient conversation recordings collected from an outpatient clinic at a large tertiary medical center in Korea. For each original and SR transcription, we analyzed the accuracy rate of each cloud-based SR open API (i.e., the number of medical terms in the SR transcription per number of medical terms in the original transcription). Results: A total of 112 doctor–patient conversation recordings were converted with three cloud-based SR open APIs (Naver Clova SR from Naver Corporation; Google Speech-toText from Alphabet Inc.; and Amazon Transcribe from Amazon), and each transcription was compared. Naver Clova SR (75.1%) showed the highest accuracy with the recognition of medical terms compared to the other open APIs (Google Speech-to-Text, 50.9%, P < 0.001; Amazon Transcribe, 57.9%, P < 0.001), and Amazon Transcribe demonstrated higher recognition accuracy compared to Google Speech-to-Text (P< 0.001). In the sub-analysis, Naver Clova SR showed the highest accuracy in all areas according to word classes, but the accuracy of words longer than five characters showed no statistical differences (Naver Clova SR, 52.6%; Google Speech-to-Text, 56.3%; Amazon Transcribe, 36.6%). Conclusion Among three current cloud-based SR open APIs, Naver Clova SR which manufactured by Korean company showed highest accuracy of medical terms in Korean, compared to Google Speech-to-Text and Amazon Transcribe. Although limitations are existing in the recognition of medical terminology, there is a lot of rooms for improvement of this promising technology by combining strengths of each SR engines.

Amelogenesis imperfecta (AI) occurs either in isolation or in association with other dental abnormalities and systemic disorder. A rare syndrome associating AI with nephrocalcinosis was named as Enamel Renal Syndrome (ERS; OMIM #204690). This syndrome is characterized by severe enamel hypoplasia, failed tooth eruption, intra pulpal calcifications, enlarged gingiva, and nephrocalcinosis. Nephrocalcinosis is a condition where calcium salts are deposited in renal tissue, and this may lead to critical kidney complications. This rare syndrome shows pathognomonic oral characteristics that are easily detectable at an early age, which proceeds the onset of renal involvement. Pediatric dentists are the first oral health practitioners whom ERS patients will meet at early age. The role of pediatric dentists is critically important for early diagnosis and referral of patients to both nephrologists for renal assessment and geneticists for identification of causative mutation and diagnosis. Early detection of renal involvement may provide chances to prevent further undesired renal complications.

PURPOSE: Growth inhibitory effects of lipid soluble components of the Korean red ginseng and the antineoplastic mechanism against human melanoma cell lines were investigated. To examine molecular mechanism of growth inhibitory effects of GX-PE, we analyzed the effect of GX-PE on cell cycle progression and expression of cell cycle regulatory factors such as retinoblastoma gene product (Rb), p27 (Kip1), p21 (WAF1), cdk2, cdk4 and cyclin D1 which are known to regulate cell cycle progression. MATERIALS AND METHODS: Petroleum ether extract of the Korean red ginseng (GX-PE) was added to cultures of three human melanoma cell lines, SK-MEL-1, SK-MEL-2, and SK-MEL-5. Proliferation was measured by 3H-thymidine incorporation assay. Cell cycle and expression of cell cycle regulatory factors were analyzed by flow cytometry and Western blotting, respectively. RESULTS: Growth of melanoma cells was inhibited by GX-PE in proportion to the concentration. GX-PE significantly inhibited cell cycle progression at G1 phase. GX-PE increased expression of negative cell cycle regulators, i.e., p27 (Kip1) in SK-MEL-2 and p21 (WAF1) and Rb in SK-MEL-1. CONCLUSION: These results suggest that GX-PE inhibits proliferation of melanoma cells at a G1-S transition point of the cell cycle. The effect of GX-PE is most likely due to induction of negative cell cycle regulatory factors.
Blotting, Western ; Cell Cycle* ; Cell Line* ; Cyclin D1 ; Ether ; Flow Cytometry ; G1 Phase ; Genes, Retinoblastoma ; Humans* ; Melanoma* ; Panax* ; Petroleum

OBJECTIVES: While parents who foster children with epilepsy would have considerable parenting difficulties, the parenting stress and sense of competence have not been investigated. We investigated maternal parenting stress, parenting satisfaction and sense of parenting competence in children with seizure disorders, and the associations with seizure-related variables. METHODS: Mothers of 79 children with seizure disorders (41 boys, 38 girls; mean age, 9.9+/-2.3 years) and 79 healthy comparison subjects matched for age and sex were recruited for this study. The Korean version of the Parenting Stress Index (K-PSI-SF) and the Parenting Sense of Competence (K-PSOC) were used to assess parenting stress, parenting satisfaction and parenting efficacy. RESULTS: Mothers of children with seizure disorders showed higher scores on stress related to difficult child and child learning and parenting anxiety compared to mothers of healthy children. In addition, scores on stress related to parental-child interaction and child learning were significantly associated with parental economic status. Scores on stress from parental-child interaction was also correlated with seizure severity, and stress from child learning was correlated with seizure type. Sense of parenting competence and anxiety scores were correlated with paternal educational status, respectively. CONCLUSION: These findings suggest that mothers of children with epilepsy have greater parenting stress and anxiety and social and seizure-associated factors may affect the parenting stress and anxiety.
Anxiety ; Child* ; Educational Status ; Epilepsy* ; Female ; Humans ; Learning ; Mental Competency* ; Mothers ; Parenting* ; Parents* ; Seizures*

15-deoxy-delta12,14-PGJ2(15d-PGJ2) is a natural ligand that activates the peroxisome proliferators-activated receptor (PPAR) gamma, a member of nuclear receptor family implicated in regulation of lipid metabolism and adipocyte differentiation. Recent studies have shown that 15d-PGJ2 is the potent anti-inflammatory agent functioning via PPARgamma-dependent and -independent mechanisms. Most postulated mechanisms for anti-inflammatory action of PPARgamma agonists are involved in inhibiting NF-kappaB signaling pathway. We examined the possibility that IL-6 signaling via the Jak-Stat pathway is modulated by 15d-PGJ2 in lymphocytes and also examined whether the inhibition of IL-6 signaling is dependent of PPARgamma. 15d-PGJ2 blocked IL-6 induced Stat1 and Stat3 activation in primary human lymphocytes, Jurkat cells and immortalized rheumatoid arthritis B cells. Inhibition of IL-6 signaling was induced rapidly within 15 min after treatment of 15d-PGJ2. Other PPARgamma-agonists, such as troglitazone and ciglitazone, did not inhibit IL-6 signaling, indicating that 15d-PGJ2 affect the IL-6-induced Jak-Stat signaling pathway via PPARgamma-independent mechanism. Although cycloheximide reversed 15d-PGJ2-mediated inhibition of Stat3 activation, actinomycin D had no effect on 15d-PGJ2-mediated inhibition of IL-6 signaling, indicating that inhibition of IL-6 signaling occur independent of de novo gene expression. These results show that 15d-PGJ2 specifically inhibit Jak-Stat signaling pathway in lymphocytes, and suggest that 15d-PGJ2 may regulate inflammatory reactions through the modulation of different signaling pathway other than NF-kappaB in lymphocytes.
Arthritis, Rheumatoid/metabolism/pathology ; Chromans/pharmacology ; Cycloheximide/pharmacology ; DNA-Binding Proteins/*metabolism ; Dactinomycin/pharmacology ; Gene Expression Regulation ; Humans ; Hypoglycemic Agents/pharmacology ; Interleukin-6/*pharmacology ; Jurkat Cells/metabolism/pathology ; Lymphocytes/cytology/*drug effects/*metabolism ; NF-kappa B/metabolism ; PPAR gamma/metabolism ; Phosphorylation ; Prostaglandin D2/*analogs & derivatives/pharmacology ; Protein Synthesis Inhibitors/pharmacology ; Research Support, Non-U.S. Gov't ; *Signal Transduction ; Thiazolidinediones/pharmacology ; Trans-Activators/*metabolism

Background: /Aim: Cancer-associated fibroblasts (CAFs) play an immunosuppressive role in the tumor microenvironment (TME) of human cancers; however, their characteristics and role in hepatocellular carcinoma (HCC) remain to be elucidated. Methods: Nine tumor and surrounding liver tissue samples from patients with HCC who underwent surgery were used to isolate patient-derived CAFs. Cell morphology was observed using an optical microscope after culture, and cell phenotypes were evaluated using flow cytometry and immunoblotting. Cytokines secreted by CAFs into culture medium were quantified using a multiplex cytokine assay. Results: CAFs were abundant in the TME of HCC and were adjacent to immune cells. After culture, the CAFs and non-tumor fibroblasts exhibited spindle shapes. We observed a robust expression of alpha-smooth muscle actin and fibroblast activation protein in CAFs, whereas alpha-fetoprotein, epithelial cell adhesion molecule, platelet/endothelial cell adhesion molecule-1, and E-cadherin were not expressed in CAFs. Furthermore, CAFs showed high secretion of various cytokines, namely C-X-C motif chemokine ligand 12, interleukin (IL)-6, IL-8, and C-C motif chemokine ligand 2. Conclusions CAFs are abundant in the TME of HCC and play a crucial role in tumor progression. These fibroblasts secrete cytokines that promote tumor growth and metastasis.

Receptor-interacting serine/threonine-protein kinase (RIPK) 3 is a member of the TNF receptor-I signaling complex and mediates necroptosis, an inflammatory cell death. Ulcerative colitis (UC) is an excessive inflammatory disease caused by uncontrolled T cell activation. The current study is aimed to determine whether RIPK3 inhibitor attenuates UC development inhibiting inflammation and necroptosis using experimental colitis mice model. Dextran sulfate sodium-induced colitis mice were administered RIPK3 inhibitor (3 mg/ml) 3 times and their tissues were analyzed by immunohistochemistry. RIPK3, mixed lineage kinase domain-like (MLKL), phosphorylated MLKL, IL-17, and CD4 in colitis patient colon tissues were detected using confocal microscopy. Protein levels were measured using immunohistochemistry and ELISA. The differentiation of Th17 cells was evaluated using flow cytometry. The expression of proinflammatory cytokines and necroptosis in peripheral blood mononuclear cells from UC patients was decreased markedly by RIPK3 inhibitor treatment. We also observed that the injection of RIPK3 inhibitor improves colitis severity and protects intestinal destruction. RIPK3 inhibitor reduced necroptosis factors and proinflammatory cytokines in the colon and consequently protected colon devastation. The expression of inflammatory mediators in experimental colitis mice splenocytes was decreased significantly by RIPK3 inhibitor treatment. These results suggest that RIPK3 inhibitor ameliorates severity of experimental colitis and reduces inflammation through the inhibition of inflammatory response and necroptosis and support RIPK3-targeting substances for treatment of UC.

The protein encoded by the Gene Associated with Retinoid-Interferon-Induced Mortality-19 (GRIM-19) is located in the mitochondrial inner membrane and is homologous to the NADH dehydrogenase 1-alpha subcomplex subunit 13 of the electron transport chain.Multiple sclerosis (MS) is a demyelinating disease that damages the brain and spinal cord.Although both the cause and mechanism of MS progression remain unclear, it is accepted that an immune disorder is involved. We explored whether GRIM-19 ameliorated MS by increasing the levels of inflammatory cytokines and immune cells; we used a mouse model of experimental autoimmune encephalomyelitis (EAE) to this end. Six-to-eight-week-old male C57BL/6, IFNγ-knockout (KO), and GRIM-19 transgenic mice were used; EAE was induced in all strains. A GRIM-19 overexpression vector (GRIM19 OVN) was electrophoretically injected intravenously. The levels of Th1 and Th17 cells were measured via flow cytometry, immunofluorescence, and immunohistochemical analysis. IL-17A and IFNγ expression levels were assessed via ELISA and quantitative PCR. IL-17A expression decreased and IFNγ expression increased in EAE mice that received injections of the GRIM19 OVN. GRIM-19 transgenic mice expressed more IFNγ than did wild-type mice; this inhibited EAE development. However, the effect of GRIM-19 overexpression on the EAE of IFNγ-KO mice did not differ from that of the empty vector. GRIM-19 expression was therapeutic for EAE mice, elevating the IFNγ level. GRIM-19 regulated the Th17/Treg cell balance.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.