Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Objective: Involuntary admission to psychiatric inpatient care can protect both patients with severe mental illnesses and individuals around them. This study analyzed annual healthcare costs per person for involuntary psychiatric admission and examined categories of mental disorders and other factors associated with mortality. Methods: This retrospective cohort study collected 1 million randomly sampled beneficiaries from the National Health Insurance Database for 2002–2013. It identified and matched 181 patients with involuntary psychiatric admissions (research group) with 724 patients with voluntary psychiatric admissions (control group) through 1:4 propensity-score matching for sex, age, comorbidities, mental disorder category, and index year of diagnosis. Results: Mean life expectancy of patients with involuntary psychiatric admissions was 33.13 years less than the general population. Average annual healthcare costs per person for involuntary psychiatric admissions were 3.94 times higher compared with voluntary admissions. The general linear model demonstrated that average annual medical costs per person per compulsory hospitalization were 5.8 times that of voluntary hospitalization. Survival analysis using the Cox proportional hazards model found no significant association between type of psychiatric admission (involuntary or voluntary) and death. Conclusion This study revealed no significant difference in mortality between involuntary and voluntary psychiatric admissions, indicating involuntary treatment’s effectiveness.

Purpose: The aim of the study was to determine the effectiveness of dignity therapy for end-of-life patients with cancer. Methods: This study used a quasi-experimental study design with a nonrandomized controlled trial.Dignity therapy was used as an intervention in the experimental group, and general visit was used in the control group. Thirty end-of-life patients with cancer were recruited, with 16 in the experimental group and 14 in the control group. Outcome variables were the participants' dignity, demoralization, and depression. Measurements were taken at the following time points: pre-test (before intervention), posttest 1 (the 7th day), and post-test 2 (the 14th day). The effectiveness of the intervention in the two groups was analyzed using the generalized estimating equation, with the p value set to be less than .05. Results: After dignity therapy, the end-of-life patients with cancer reflected increased dignity signifi-cantly [β= -37.08, standard error (SE) = 7.43, Wald x2= 24.94, p < .001], whereas demoralization (β= -39.55, SE = 6.42, Wald x2= 37.95, p < .001) and depression (β= -12.01, SE = 2.17, x2= 30.71, p< 001) were both reduced significantly. Conclusion Clinical nurses could be adopting dignity therapy to relieve psychological distress and improve spiritual need in end-of-life patients with cancer. Future studies might be expanded to looking at patients vis-a -vis end-of-life patients without cancer to improve their psychological distress. These results provide reference data for the care of end-of-life patients with cancer for nursing professionals.

Purpose: The aim of the study was to determine the effectiveness of dignity therapy for end-of-life patients with cancer. Methods: This study used a quasi-experimental study design with a nonrandomized controlled trial.Dignity therapy was used as an intervention in the experimental group, and general visit was used in the control group. Thirty end-of-life patients with cancer were recruited, with 16 in the experimental group and 14 in the control group. Outcome variables were the participants' dignity, demoralization, and depression. Measurements were taken at the following time points: pre-test (before intervention), posttest 1 (the 7th day), and post-test 2 (the 14th day). The effectiveness of the intervention in the two groups was analyzed using the generalized estimating equation, with the p value set to be less than .05. Results: After dignity therapy, the end-of-life patients with cancer reflected increased dignity signifi-cantly [β= -37.08, standard error (SE) = 7.43, Wald x2= 24.94, p < .001], whereas demoralization (β= -39.55, SE = 6.42, Wald x2= 37.95, p < .001) and depression (β= -12.01, SE = 2.17, x2= 30.71, p< 001) were both reduced significantly. Conclusion Clinical nurses could be adopting dignity therapy to relieve psychological distress and improve spiritual need in end-of-life patients with cancer. Future studies might be expanded to looking at patients vis-a -vis end-of-life patients without cancer to improve their psychological distress. These results provide reference data for the care of end-of-life patients with cancer for nursing professionals.

Cis-3-O-p-hydroxycinnamoyl ursolic acid (HCUA), a triterpenoid compound, was purified from Elaeagnus oldhamii Maxim. This traditional medicinal plant has been used for treating rheumatoid arthritis and lung disorders as well as for its anti-inflammation and anticancer activities. This study aimed to investigate the anti-proliferative and apoptotic-inducing activities of HCUA in oral cancer cells. HCUA exhibited anti-proliferative activity in oral cancer cell lines (Ca9-22 and SAS cells), but not in normal oral fibroblasts. The inhibitory concentration of HCUA that resulted in 50% viability was 24.0 µM and 17.8 µM for Ca9-22 and SAS cells, respectively. Moreover, HCUA increased the number of cells in the sub-G1 arrest phase and apoptosis in a concentration-dependent manner in both oral cancer cell lines, but not in normal oral fibroblasts. Importantly, HCUA induced p53-mediated transcriptional regulation of pro-apoptotic proteins (Bax, Bak, Bim, Noxa, and PUMA), which are associated with mitochondrial apoptosis in oral cancer cells via the loss of mitochondrial membrane potential. HCUA triggered the production of intracellular reactive oxygen species (ROS) that was ascertained to be involved in HCUA-induced apoptosis by the ROS inhibitors YCG063 and N-acetyl-L-cysteine. As a result, HCUA had potential antitumor activity to oral cancer cells through eliciting ROS-dependent and p53-mediated mitochondrial apoptosis. Overall, HCUA could be applicable for the development of anticancer agents against human oral cancer.
Acetylcysteine ; Antineoplastic Agents ; Apoptosis Regulatory Proteins ; Apoptosis* ; Arthritis, Rheumatoid ; Cell Line ; Elaeagnaceae ; Fibroblasts ; Humans ; Lung ; Membrane Potential, Mitochondrial ; Mouth Neoplasms* ; Plants, Medicinal ; Reactive Oxygen Species

BACKGROUND AND PURPOSE: It is essential to develop a reliable predictive serum biomarker for Parkinson's disease (PD). The accumulation of alpha-synuclein (αSyn) and up-regulated expression of Rab35 participate in the etiology of PD. The purpose of this investigation was to determine whether the combined assessment of serum αSyn and Rab35 is a useful predictive biomarker for PD. METHODS: Serum levels of αSyn or Rab35 were determined in serum samples from 59 sporadic PD patients, 19 progressive supranuclear palsy (PSP) patients, 20 multiple system atrophy (MSA) patients, and 60 normal controls (NC). Receiver operating characteristics (ROC) curves were calculated to determine the diagnostic accuracy of αSyn or/and Rab35 in discriminating PD patients from NC or atypical parkinsonian patients. RESULTS: The levels of αSyn and Rab35 were increased in PD patients. The serum level of Rab35 was positively correlated with that of αSyn in PD patients. Compared to analyzing αSyn or Rab35 alone, the combined analysis of αSyn and Rab35 produced a larger area under the ROC curve and performed better in discriminating PD patients from NC, MSA patients, or PSP patients. When age was dichotomized at 55, 60, 65, or 70 years, the combined assessment of αSyn and Rab35 for classifying PD was better in the group below the cutoff age than in the group above the cutoff age. CONCLUSIONS: Combined assessment of serum αSyn and Rab35 is a better biomarker for discriminating PD patients from NC or atypical parkinsonian patients, and is a useful predictive biomarker for younger sporadic PD patients.
alpha-Synuclein ; Humans ; Multiple System Atrophy ; Parkinson Disease ; ROC Curve ; Supranuclear Palsy, Progressive