Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: This study aimed to evaluate and optimize microbial DNA extraction methods from urine, a non-invasive sample source, to enhance DNA quality, purity, and reliability for urinary microbiome research and biomarker discovery in bladder cancer. Materials and Methods: A total of 302 individuals (258 with genitourinary cancers and 44 with benign urologic diseases) participated in this study. Urine samples were collected via sterile catheterization, resulting in 445 vials for microbial analysis. DNA extraction was performed using three protocols: the standard protocol (SP), water dilution protocol (WDP), and chelation-assisted protocol (CAP). DNA quality (concentration, purity, and contamination levels) was assessed using NanoDrop spectrophotometry.Microbial analysis was conducted on 138 samples (108 cancerous and 30 benign) using 16S rRNA sequencing. Prior to sequencing on the Illumina MiSeq platform, Victor 3 fluorometry was used for validation. Results: WDP outperformed other methods, achieving significantly higher 260/280 and 260/230 ratios, indicating superior DNA purity and reduced contamination, while maintaining reliable DNA yields. CAP was excluded due to poor performance across all metrics. Microbial abundance was significantly higher in WDP-extracted samples (p<0.0001), whereas SP demonstrated higher alpha diversity indices (p<0.01), likely due to improved detection of low-abundance taxa. Beta diversity analysis showed no significant compositional differences between SP and WDP (p=1.0), supporting the reliability of WDP for microbiome research. Conclusions WDP is a highly effective and reliable method for microbial DNA extraction from urine, ensuring high-quality and reproducible results. Future research should address sample variability and crystal precipitation to further refine microbiome-based diagnostics and therapeutics.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: T1 high grade (T1HG) bladder cancer (BC) is a type of non-muscle invasive BC (NMIBC) that is recognized as an aggressive subtype with a heightened propensity for progression. Current risk stratification methods for NMIBC rely on clinicopathological indicators; however, these approaches do not adequately capture the aggressive nature of T1HG BC. Thus, new, more accurate biomarkers for T1HG risk stratification are needed. Here, we enrolled three different patient cohorts and investigated expression of collagen type VI alpha 1 (COL6A1), a key component of the extracellular matrix, at different stages and grades of BC, with a specific focus on T1HG BC. Materials and Methods: Samples from 298 BC patients were subjected to RNA sequencing and real-time polymerase chain reaction. Results: We found that T1HG BC and muscle invasive BC (MIBC) exhibited comparable expression of COL6A1, which was significantly higher than that by other NMIBC subtypes. In particular, T1HG patients who later progressed to MIBC had considerably higher expression of COL6A1 than Ta, T1 low grade patients, and patients that did not progress, highlighting the aggressive nature and higher risk of progression associated with T1HG BC. Moreover, Cox and Kaplan–Meier survival analyses revealed a significant association between elevated expression of COL6A1 and poor progression-free survival of T1HG BC patients (multivariate Cox hazard ratio, 16.812; 95% confidence interval, 3.283–86.095; p=0.001 and p=0.0002 [log-rank test]). Conclusions These findings suggest that COL6A1 may be a promising biomarker for risk stratification of T1HG BC, offering valuable insight into disease prognosis and guidance of personalized treatment decisions.

Background: and Purpose Migraine is a condition that is often observed to run in families, but its complex genetic background remains unclear. This study aimed to identify the genetic factors influencing migraines and their potential association with the family medical history. Methods: We performed a comprehensive genome-wide association study of a cohort of 1,561 outpatients with migraine and 473 individuals without migraine in Taiwan, including Han Chinese individuals with or without a family history of migraine. By analyzing the detailed headache history of the patients and their relatives we aimed to isolate potential genetic markers associated with migraine while considering factors such as sex, episodic vs. chronic migraine, and the presence of aura. Results: We revealed novel genetic risk loci, including rs2287637 in DEAD-Box helicase 1 and long intergenic non-protein coding RNA 1804 and rs12055943 in engulfment and cell motility 1, that were correlated with the family history of migraine. We also found a genetic location downstream of mesoderm posterior BHLH transcription factor 2 associated with episodic migraine, whereas loci within the ubiquitin-specific peptidase 26 exonic region, dual specificity phosphatase 9 and pregnancy-upregulated non-ubiquitous CaM kinase intergenic regions, and poly (ADP-ribose) polymerase 1 and STUM were linked to chronic migraine. We additionally identified genetic regionsassociated with the presence or absence of aura. A locus between LINC02561 and urocortin 3 was predominantly observed in female patients. Moreover, three different single-nucleotide polymorphisms were associated with the family history of migraine in the control group. Conclusions This study has identified new genetic locations associated with migraine and its family history in a Han Chinese population, reinforcing the genetic background of migraine. The findings point to potential candidate genes that should be investigated further.

Background: The PLASMIC score is a convenient tool for predicting ADAMTS13 activity of ＜10%.Lactate dehydrogenase (LDH) is widely used as a marker of haemolysis in thrombotic thrombocytopenic purpura (TTP) monitoring, and could be used as a replacement marker for lysis. We aimed to validate the PLASMIC score in a multi-centre Asia Pacific region, and to explore whether LDH could be used as a replacement marker for lysis. Methods: Records of patients with thrombotic microangiopathy (TMA) were reviewed. Patients’ ADAMTS13 activity levels were obtained, along with clinical/laboratory findings relevant to the PLASMIC score. Both PLASMIC scores and PLASMIC-LDH scores, in which LDH replaced traditional lysis markers, were calculated. We generated a receiver operator characteristics (ROC) curve and compared the area under the curve values (AUC) to determine the predictive ability of each score. Results: 46 patients fulfilled the inclusion criteria, of which 34 had ADAMTS13 activity levels of ＜10%. When the patients were divided into intermediate-to-high risk (scores 5‒7) and low risk (scores 0‒4), the PLASMIC score showed a sensitivity of 97.1% and specificity of 58.3%, with a positive predictive value (PPV) of 86.8% and negative predictive value (NPV) of 87.5%. The PLASMIC-LDH score had a sensitivity of 97.1% and specificity of 33.3%, with a PPV of 80.5% and NPV of 80.0%. Conclusion Our study validated the utility of the PLASMIC score, and demonstrated PLASMIC-LDH as a reasonable alternative in the absence of traditional lysis markers, to help identify high-risk patients for treatment via plasma exchange.