Timely removal of oxidatively damaged proteins is critical for cells exposed to oxidative stresses; however, cellular mechanism for clearing oxidized proteins is not clear. Our study reveals a novel type of protein modification that may play a role in targeting oxidized proteins and remove them. In this process, DSS1 (deleted in split hand/split foot 1), an evolutionally conserved small protein, is conjugated to proteins induced by oxidative stresses in vitro and in vivo, implying oxidized proteins are DSS1 clients. A subsequent ubiquitination targeting DSS1-protein adducts has been observed, suggesting the client proteins are degraded through the ubiquitin-proteasome pathway. The DSS1 attachment to its clients is evidenced to be an enzymatic process modulated by an unidentified ATPase. We name this novel protein modification as DSSylation, in which DSS1 plays as a modifier, whose attachment may render target proteins a signature leading to their subsequent ubiquitination, thereby recruits proteasome to degrade them.
Free Radicals ; metabolism ; HeLa Cells ; Humans ; Oxidation-Reduction ; Oxidative Stress ; genetics ; Proteasome Endopeptidase Complex ; genetics ; metabolism ; Protein Binding ; Protein Modification, Translational ; genetics ; Ubiquitin ; metabolism ; Ubiquitination ; genetics

Osteoporosis and its associated fragility fractures are becoming a severe burden in the healthcare system globally. In the Asian-Pacific (AP) region, the rapidly increasing in aging population is the main reason accounting for the burden. Moreover, the paucity of quality care for osteoporosis continues to be an ongoing challenge. The Fracture Liaison Service (FLS) is a program promoted by International Osteoporosis Foundation (IOF) with a goal to improve quality of postfracture care and prevention of secondary fractures. In this review article, we would like to introduce the Taiwan FLS network. The first 2 programs were initiated in 2014 at the National Taiwan University Hospital and its affiliated Bei-Hu branch. Since then, the Taiwan FLS program has continued to grow exponentially. Through FLS workshops promoted by the Taiwanese Osteoporosis Association (TOA), program mentors have been able to share their valuable knowledge and clinical experience in order to promote establishments of additional programs. With 22 FLS sites including 11 successfully accredited on the best practice map, Taiwan remains as one of the highest FLS coverage countries in the AP region, and was also granted the IOF Best Secondary Fracture Prevention Promotion award in 2017. Despite challenges faced by the TOA, we strive to promote more FLS sites in Taiwan with a main goal of ameliorating further health burden in managing osteoporotic patients.
Aging ; Awards and Prizes ; Delivery of Health Care ; Education ; Financing, Organized ; Humans ; Mentors ; Osteoporosis ; Practice Guidelines as Topic ; Taiwan

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.