Objective: Rumination is a maladaptive emotional-regulation strategy that is strongly associated with depression. Impaired executive function can lead to difficulties in disengaging from rumination, thus exacerbating depression. In this study, we inspect an electroencephalograph neurofeedback protocol that enhance the target peak alpha frequency (PAF) activation in the prefrontal region. We examine the protocol’s effects on depression and rumination. Methods: We randomly assigned 30 dysphoric participants into either the neurofeedback training group or the control group. We then evaluated their depression, rumination, and executive function at pre- and posttraining so as to examine the effects of the neurofeedback. Results: The results show that this neurofeedback protocol can specifically enhance participants’ target PAF. The participants’ executive function performances significantly improved after undergoing 20 neurofeedback sessions. Compared with those in the control group, those in the neurofeedback group had significantly fewer depressive symptoms and significantly reduced rumination. Moreover, as target PAF and executive function improved, depression and rumination both declined. Conclusion Our data are in line with those of previous studies that indicated a relationship between upper-band alpha activity and executive function. This PAF neurofeedback can effectively enhance participants’ executive function, which can reduce rumination and ameliorate depression. This neurofeedback training is based on basic cognitive neuroscience, so it sheds light on depression’s pathological factors and etiology.

Objectives: To assess the relationship of variation of blood pressure and neurological deterioration (ND) in ischemic stroke patients. Methods: We recruited patients with the fi rst-ever ischemic stroke at a teaching hospital. The National Institutes of Health Stoke Score (NIHSS) of each patient was monitored for 2 months. ND was defi ned as an increase of ≥ 2 points in NIHSS during the fi rst 7 days after stroke. Blood pressure was measured every 6 hours for fi rst 7 days. We analyzed blood pressure data in the fi rst 36 hours to study the relationship between variation of blood pressure and ND. Successive variation of systolic (svSBP) and diastolic (svDBP) blood pressure was calculated as svSBP= |SBPn+1 – SBPn | and svDBP= |DBPn+1 – DBPn | respectively. The largest svSBP in the fi rst 36 hours of hospitalization or before ND was defi ned as maximum variation of systolic blood pressure (maxvSBP). Then, the mean variation of systolic (mvSBP) and diastolic (mvDBP) blood pressure was calculated as mvSBP= svSBP/N and mvDBP= svDBP/N respectively. Results: A total of 121 patients were included in this study, and 38 of them had ND. The mvSBP was higher in the ND Group (17.9±8.4 mmHg vs. 13.7±4.4 mmHg, p=0.006) but the difference in mvDBP did not reach statistical signifi cance (9.8±3.5mmHg vs. 8.6±3.0 mmHg p=0.06). The ND Group had a larger maxvSBP (35.2±17.2 vs. 27.6±11.6 mmHg, p =0.01), which was more frequently over 30mmHg than that in the stable group (P=0.02). Conclusions: A large svSBP is associated with an increased risk for ND. The study highlights the importance of close monitoring of blood pressure in ischemic stroke patients.

OBJECTIVE: We intended to analyze the credibility judgment in written forensic psychiatric reports of child sexual abuse registered in Southern Taiwan. METHODS: Ninety-six cases of child sexual abuse between August 2010 and October 2017 encountered in two hospitals were analyzed. The results in these reports were categorized into credible and non-credible. We identified the factors that distinguished between the two groups in bivariate analyses using chi-square test. A binary logistic regression analysis was performed to determine whether the factors that significantly correlated in the bivariate analyses were independent predictors of credible judgments. RESULTS: Among 96 cases, 70 (73%) were judged as credible. Consistent testimonies of children (odds ratio=40.82) and multiple abuse events (odds ratio=6.05) were positive variables independently related to the sexual abuse allegations judged as credible. CONCLUSION The number of allegations judged as credible in this study was slightly higher than that reported in other studies. Our findings about predictors for credible cases are not in line with those reported previously. Due to the differences in resources of the cases and backgrounds of the evaluators among multiple studies, direct comparisons with previous studies must be treated with caution.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

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.

BACKGROUND: Particulate matter (PM) < 2.5 μm (PM METHODS: We obtained DNA methylation and exercise data of 496 participants (aged between 30 and 70 years) from the Taiwan Biobank (TWB) database. We also extracted PM RESULTS: DLEC1 methylation and PM CONCLUSIONS We found significant positive associations between PM
Adult ; Aged ; Air Pollutants/adverse effects* ; DNA Methylation/drug effects* ; Environmental Exposure/adverse effects* ; Exercise ; Female ; Humans ; Male ; Middle Aged ; Particulate Matter/adverse effects* ; Taiwan ; Tumor Suppressor Proteins/metabolism*