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Identification, characterization, and engineering of glycosylation in thrombolyticsa
Biotechnol Adv. 2023 May 12:108174. doi: 10.1016/j.biotechadv.2023.108174. Online ahead of print.ABSTRACTCardiovascular diseases, such as myocardial infarction, ischemic stroke, and pulmonary embolism, are the most common causes of disability and death worldwide. Blood clot hydrolysis by thrombolytic enzymes and thrombectomy are key clinical interventions. The most widely used thrombolytic enzyme is alteplase, which has been used in clinical practice since 1986. Another clinically used thrombolytic protein is tenecteplase, which has modified epitopes and engineered glycosylation sites, suggesting that carbohydrate modifica...
Source: Adv Data - May 14, 2023 Category: Epidemiology Authors: Martin Toul Veronika Slonkova Jan Mican Adam Urminsky Maria Tomkova Erik Sedlak David Bednar Jiri Damborsky Lenka Hernychova Zbynek Prokop Source Type: research

Diagnosis of Coronary Artery Disease based on Machine Learning algorithms Support Vector Machine, Artificial Neural Network, and Random Forest
CONCLUSION: In this study, it was shown that machine learning algorithms can be used with high accuracy to detect CAD. Thus, it allows physicians to perform timely preventive treatment in patients with CAD.PMID:37057235 | PMC:PMC10086656 | DOI:10.4103/abr.abr_383_21
Source: Adv Data - April 14, 2023 Category: Epidemiology Authors: Saeed Saeedbakhsh Mohammad Sattari Maryam Mohammadi Jamshid Najafian Farzaneh Mohammadi Source Type: research

Machine learning prediction of symptomatic intracerebral hemorrhage after stroke thrombolysis: a cross-cultural validation in Caucasian and Han Chinese cohort
CONCLUSION: The established SVM model is feasible for predicting the risk of sICH after thrombolysis quickly and efficiently in both Caucasian and Han Chinese cohort.PMID:36225969 | PMC:PMC9549180 | DOI:10.1177/17562864221129380
Source: Adv Data - October 13, 2022 Category: Epidemiology Authors: Junfeng Liu Xinyue Chen Xiaonan Guo Renjie Xu Yanan Wang Ming Liu Source Type: research

Accuracy of machine learning algorithms for the assessment of upper-limb motor impairments in patients with post-stroke hemiparesis: A systematic review and meta-analysis
CONCLUSION: Automated systems using machine learning algorithms could support therapists in assessing upper extremity motor function in post-stroke patients. However, to draw more robust conclusions, methodological designs that minimize the risk of bias and increase the quality of the methodology of future studies are required.PMID:36047897 | DOI:10.17219/acem/152596
Source: Adv Data - September 1, 2022 Category: Epidemiology Authors: Jorge Fernando Ambros-Antemate Adriana Reyes-Flores Liliana Argueta-Figueroa Rafael Ram írez-Ramírez Marciano Vargas-Trevi ño Jaime Guti érrez-Gutiérrez Eduardo P érez-Campos Mayoral Eduardo P érez-Campos Luis Angel Flores-Mej ía Rafael Torres-Ros Source Type: research

Radiomics-based prediction of hemorrhage expansion among patients with thrombolysis/thrombectomy related-hemorrhagic transformation using machine learning
CONCLUSIONS: The currently established NECT-based radiomic score is valuable in predicting hemorrhage expansion after HT among patients treated with reperfusion treatment after ischemic stroke, which may aid clinicians in determining patients with HT who are most likely to benefit from anti-expansion treatment.PMID:35173809 | PMC:PMC8842178 | DOI:10.1177/17562864211060029
Source: Adv Data - February 17, 2022 Category: Epidemiology Authors: Junfeng Liu Wendan Tao Zhetao Wang Xinyue Chen Bo Wu Ming Liu Source Type: research

DEG/ENaC Ion Channels in the Function of the Nervous System: From Worm to Man
Adv Exp Med Biol. 2021;1349:165-192. doi: 10.1007/978-981-16-4254-8_9.ABSTRACTDEG/ENaC channels are voltage-independent Na+/Ca2+ channels that are conserved across species and are expressed in many different cell types and tissues, where they contribute to a wide array of physiological functions from transepithelial Na+ transport, to sensory perception, and learning and memory. In this chapter, we focus on the members of this family that are expressed in the nervous system, grouping them based on their function. Structurally, DEG/ENaC channels are trimers formed by either identical or homologous subunits, each one protrudi...
Source: Adv Data - February 9, 2022 Category: Epidemiology Authors: Laura Bianchi Source Type: research

Predicting the Risk of Ischemic Stroke in Patients Treated with Novel Oral Anticoagulants: A Machine Learning Approach
Conclusions: The stroke risk in AF patients treated with NOAC could be predicted based on comorbidities like ischemic heart diseases, urinary tract infections, and dementia additionally to age and male sex. Knowing and addressing these factors may help reduce the risk of stroke in this patient population.Neuroepidemiology
Source: Neuroepidemiology - July 21, 2021 Category: Epidemiology Source Type: research