Objective: Bipolar disorder (BD) is characterized by the poor sleep quality. Whether the striatal dopamine transporter (DAT) availability is related to sleep quality among patients with BD is unclear. Methods: Fifty-three euthymic patients with BD (24 BD-I and 29 BD-II) and sixty-eight healthy controls were enrolled. The Chinese Version of the Pittsburgh Sleep Quality Index (PSQI) was used, and the availability of DAT was assessed by single-photon emission computed tomography (SPECT) using [99mTc] TRODAT-1. Results: The sleep disturbance component of the PSQI was significantly associated with the level of DAT availability among patients with BD. Conclusion The striatal dopaminergic activity that contributes to resilience to adversity was associated with sleep pattern among patients with BD.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

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.

To expand the single-dose duration over which noninvasive clinical and preclinical cancer imaging can be conducted with high sensitivity, and well-defined spatial and temporal resolutions, a facile strategy to prepare ultrasmall nanoparticulate X-ray contrast media (nano-XRCM) as dual-modality imaging agents for positron emission tomography (PET) and computed tomography (CT) has been established. Synthesized from controlled copolymerization of triiodobenzoyl ethyl acrylate and oligo(ethylene oxide) acrylate monomers, the amphiphilic statistical iodocopolymers (ICPs) could directly dissolve in water to afford thermodynamically stable solutions with high aqueous iodine concentrations (>140 mg iodine/mL water) and comparable viscosities to conventional small molecule XRCM. The formation of ultrasmall iodinated nanoparticles with hydrodynamic diameters of ca. 10 nm in water was confirmed by dynamic and static light scattering techniques. In a breast cancer mouse model, in vivo biodistribution studies revealed that the ⁶⁴Cu-chelator-functionalized iodinated nano-XRCM exhibited extended blood residency and higher tumor accumulation compared to typical small molecule imaging agents. PET/CT imaging of tumor over 3 days showed good correlation between PET and CT signals, while CT imaging allowed continuous observation of tumor retention even after 10 days post-injection, enabling longitudinal monitoring of tumor retention for imaging or potentially therapeutic effect after a single administration of nano-XRCM.