Background: Hearing loss (HL) is one of the most common sensory disorders, affecting over 5-8% of the world's population. Approximately half of HL cases are attributed to genetic factors. In hereditary deafness, about 75-80% is inherited through autosomal recessive inheritance, and common pathogenic genes include GJB2 and SLC26A4. Pathogenic variants in the SLC26A4gene are the leading cause of hereditary hearing loss in humans, second only to the GJB2 gene. Variants in the SLC26A4gene cause hearing loss, which can be non-syndromic autosomal recessive deafness (DFNB4, OMIM #600791) associated with enlarged vestibular aqueduct (EVA) or Pendred syndrome (Pendred, OMIM #605646). DFNB4 is characterized by sensorineural hearing loss combined with EVA or less common cochlear malformation defect. Pendred syndrome is characterized by bilateral sensorineural hearing loss with EVA and an iodine defect that can lead to thyroid goiter. Currently, it is known that EVA is associated with variants in the SLC26A4 gene and is a penetrant feature of SLC26A4-related HL. Predominant mutations in these genes differ significantly across populations. For instance, predominant SLC26A4 mutations differ among populations, including p.T416P and c.1001G>A in Caucasians, p.H723R in Japanese and Koreans, and c.919-2A>G in Han Taiwanese and Han Chinese. On the other hand, there has been no study of hearing loss related to SLC26A4 gene variants among Mongolians, which is the basis of our research. Aim: We aimed to identify the characteristics of the SLC26A4 gene variants in Mongolian people with Enlarged vestibular aqueduct and Mondini malformation. Materials and Methods: In 2022-2024, We included 13 people with hearing loss and enlarged vestibular aqueduct, incomplete cochlea (1.5 turns of the cochlea with cystic apex- incomplete partition type II- Mondini malformation) were examined by CT scan of the temporal bone in our study. WES (Whole exome sequencing) analysis was performed in the Genetics genetic-laboratory of the National Taiwan University Hospital. Results: Genetic analysis revealed 26 confirmed pathogenic variants of bi-allelic SLC26A4 gene of 8 different types in 13 cases, and c.919-2A>G variant was dominant with 46% (12/26) in allele frequency, and c.2027T>A (p.L676Q) variant 19% (5/26), c.1318A>T(p.K440X) variant 11% (3/26), c.1229C>T (p.T410M) variant 8% (2/26) ) , c.716T>A (p.V239D), c.281C>T (p.T94I), c.1546dupC, and c.1975G>C (p.V659L) variants were each 4% (1/26)- revealed. Two male children, 11 years old (SLC26A4: c.919-2A>G) and 7 years old (SLC26A4: c.919-2A>G:, SLC26A4: c.2027T>A (p.L676Q))had history of born normal hearing and progressive hearing loss. Conclusions 1. 26 variants of bi-allelic SLC26A4 gene mutation were detected in Mongolian people with EVA and Mondini malformation, and c.919-2A>G was the most dominant allele variant, and rare variants such as c.1546dupC, c.716T>A (p.V239D) were detected. 2. Our study shows that whole-exome sequencing (WES) can identify gene mutations that are not detected by polymerase chain reaction (PCR) or NGS analysis.

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.

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.

Objectives: This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach. Methods: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches. Results: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment. Conclusions This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.

Even though the combined use of ultrasound (US) and alpha-fetoprotein (AFP) is recommended for the surveillance of hepatocellular carcinoma (HCC), the utilization of AFP has its challenges, including accuracy dependent on its cut-off levels, degree of liver necroinflammation, and etiology of liver disease. Though various studies have demonstrated the utility of protein induced by vitamin K absence II (PIVKA-II) in surveillance, treatment monitoring, and predicting recurrence, it is still not recommended as a routine biomarker test. A panel of 17 experts from Asia-Pacific, gathered to discuss and reach a consensus on the clinical usefulness and value of PIVKA-II for the surveillance and treatment monitoring of HCC, based on six predetermined statements. The experts agreed that PIVKA-II was valuable in the detection of HCC in AFP-negative patients, and could potentially benefit detection of early HCC in combination with AFP. PIVKA-II is clinically useful for monitoring curative and intra-arterial locoregional treatments, outcomes, and recurrence, and could potentially predict microvascular invasion risk and facilitate patient selection for liver transplant. However, combining PIVKA-II with US and AFP for HCC surveillance, including small HCC, still requires more evidence, whilst its role in detecting AFP-negative HCC will potentially increase as more patients are treated for hepatitis-related HCC. PIVKA-II in combination with AFP and US has a clinical role in the Asia-Pacific region for surveillance. However, implementation of PIVKA-II in the region will have some challenges, such as requiring standardization of cut-off values, its cost-effectiveness and improving awareness among healthcare providers.

Background: Feline mammary carcinoma (FMC) is one of the most prevalent malignancies of female cats. FMC is highly metastatic and thus leads to poor disease outcomes. Among all metastases, liver metastasis occurs in about 25% of FMC patients. However, the mechanism underlying hepatic metastasis of FMC remains largely uncharacterized. Results: Herein, we demonstrate that FMC-derived extracellular vesicles (FMC-EVs) promotes the liver metastasis of FMC by activating hepatic stellate cells (HSCs) to prime a hepatic premetastatic niche (PMN). Moreover, we provide evidence that sphingosine kinase 1 (SK1) delivered by FMC-EV was pivotal for the activation of HSC and the formation of hepatic PMN. Depletion of SK1 impaired cargo sorting in FMC-EV and the EV-potentiated HSC activation, and abol‑ ished hepatic colonization of FMC cells. Conclusions Taken together, our findings uncover a previously uncharacterized mechanism underlying liver-metas‑ tasis of FMC and provide new insights into prognosis and treatment of this feline malignancy.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is closely associated with diabetes. The cumulative impact of both diseases synergistically increases risk of adverse events. However, present population analysis is predominantly conducted with reference to non-NAFLD individuals and has not yet examined the impact of prediabetes. Hence, we sought to conduct a retrospective analysis on the impact of diabetic status in NAFLD patients, referencing non-diabetic NAFLD individuals. Methods: Data from the National Health and Nutrition Examination Survey 1999–2018 was used. Hepatic steatosis was defined with United States Fatty Liver Index (US-FLI) and FLI at a cut-off of 30 and 60 respectively, in absence of substantial alcohol use. A multivariate generalized linear model was used for risk ratios of binary outcomes while survival analysis was conducted with Cox regression and Fine Gray model for competing risk. Results: Of 32,234 patients, 28.92% were identified to have NAFLD. 36.04%, 38.32% and 25.63% were non-diabetic, prediabetic and diabetic respectively. Diabetic NAFLD significantly increased risk of cardiovascular disease (CVD), stroke, chronic kidney disease, all-cause and CVD mortality compared to non-diabetic NAFLD. However, prediabetic NAFLD only significantly increased the risk of CVD and did not result in a higher risk of mortality. Conclusions Given the increased risk of adverse outcomes, this study highlights the importance of regular diabetes screening in NAFLD and adoption of prompt lifestyle modifications to reduce disease progression. Facing high cardiovascular burden, prediabetic and diabetic NAFLD individuals can benefit from early cardiovascular referrals to reduce risk of CVD events and mortality.

Background: The risk and benefit of tissue plasminogen activator (tPA) for aged>80 years with acute ischemic stroke (AIS) are controversial. In this study, we investigated the safety and efficacy of tPA in this population and utilized the artificial neural network (ANN) to established outcome predictive models. Methods: We retrospectively reviewed the stroke registry data of patients with AIS, aged >80 years who arrived at the hospital within 3 hours from the onset of symptoms. The characteristics and the outcomes, presented as modified Rankin Scale (mRS), and mortality rate at 3 months between the tPA-treated and non-tPA groups were analyzed. An ANN algorithm was applied to establish predictive models. Results: A total of 80 patients aged>80 years with AIS were identified, and 49 of them received tPA. After adequate training, our ANN models accurately predicted the outcomes with the area under the receiver operating characteristic curves of 0.974, and a low error to predict the mRS score at 3 months. After applying our prediction model to those in the non-tPA group, we demonstrated the potential benefits in those patients if they had undergone tPA therapy. Conclusions: Our results show that ANN can be a potentially useful tool for predicting the treatment outcomes of tPA. Such novel machine learning-based models may help with therapeutic decision making in clinical settings.

Recombinant tissue plasminogen activator (rt-PA) is the most effective treatment for acute ischemic stroke and the exclusion criteria of rt-PA has been revised to extend its application. However, in Taiwan, National Health Insurance (NHI) did not follow the latest international consensus due to safety concerns. The present study investigated whether extending the application of rt-PA in Taiwan was safe and effective. The medical records from the Shuang Ho hospital stroke registry between August 2009 and December 2016 were retrospectively reviewed. Post rt-PA intracranial hemorrhage (ICH) and modified Rankin Scale (mRS) score at 3-month after stroke were the primary and secondary outcomes, respectively. Differences were analyzed through Fisher’s exact test and Student’s t test. A p-value of <0.05 was considered statistically significant. Overall, there were 243 patients categorized into two groups: NHI exclusion criteria adherence (n = 160) and non-adherence (n = 83). There was no significant difference in the risk of post rt-PA ICH (12.50% in adherence group, 4.82% in non-adherence group, p=0.07). Among the non-adherence group, 10 patients breached the latest international exclusion criteria and none of them experienced post rt-PA ICH. However, among patients with moderately severe stroke, the odds of mRS < 2 at 3-month were significantly lower in non-adherence group. This study demonstrated that extending administration of rt-PA in Taiwan was safe but the functional outcome after moderate stroke was not as favorable as adherence group. Old age, long onset-to-treatment time and less efficacy of lower dose of rt-PA were the possible factors for the difference in outcome.