Cerebral venous sinus thrombosis(CVST)is a type of stroke associated with COVID-19 vaccine-induced immune thrombotic thrombocytopenia.The precise etiology of CVST often remains elusive due to the highly heterogeneous ...Cerebral venous sinus thrombosis(CVST)is a type of stroke associated with COVID-19 vaccine-induced immune thrombotic thrombocytopenia.The precise etiology of CVST often remains elusive due to the highly heterogeneous nature of its governing mechanisms,specifically,Virchow’s triad that involves altered blood flow,endothelial dysfunction,and hypercoagulability,which varies substantially amongst individuals.Existing diagnostic and monitoring approaches lack the capability to reflect the combination of these patient-specific thrombotic determinants.In response to this challenge,we introduce a Vein-Chip platform that recapitulates the CVST vascular anatomy from magnetic resonance venography and the associated hemodynamic flow profile using the“Chinese Movable Type-like”soft stereolithography technique.The resultant full-lumen personalized Vein-Chips,functionalized with endothelial cells,enable in-vitro thrombosis assays that can elucidate distinct thrombogenic scenarios between normal vascular conditions and those of endothelial dysfunction.The former displayed minimal platelet aggregation and negligible fibrin deposition,while the latter presented significant fibrin extrusion from platelet aggregations.The low-cost movable typing technique further enhances the potential for commercialization and broader utilization of personalized Vein-Chips in surgical labs and at-home monitoring.Future research and development in this direction will pave the way for improved management and prevention of CVST,ultimately benefiting both patients and healthcare systems.展开更多
Addressing the pressing demand for rapid and inexpensive coagulation testing in cardiovascular care,this study introduces a novel application of repurposed COVID-19 rapid antigen tests(RATs)as paper-based lateral flow...Addressing the pressing demand for rapid and inexpensive coagulation testing in cardiovascular care,this study introduces a novel application of repurposed COVID-19 rapid antigen tests(RATs)as paper-based lateral flow assays(LFAs)combined with machine learning for coagulation status evaluation.By further developing a mobile app prototype,we present a platform that enables clinicians to perform immediate and accurate anticoagulant dosing adjustments using existing post-pandemic resources.Our proof-of-concept employs a random forest machine learning classifier to interpret image feature variations on RAT NC membrane,correlating red blood cell(RBC)wicked diffusion distance in recalcified citrated whole blood with changes in coagulative viscosity,easily interpreted.Enhanced by confocal imaging studies of paper microfluidics,our approach provides insights into the mechanisms dissecting coagulation components,achieving high classification precision,recall,and F1-scores.The inverse relationship between RBC wicked diffusion distance and enoxaparin concentration paves the way for machine learning to inform real-time dose prescription adjustments,aligning with individual patient profiles to optimize therapeutic outcomes.This study not only demonstrates the potential of leveraging surplus RATs for coagulation management but also exemplifies a cost-effective,rapid,and smart strategy to enhance clinical decision-making in the post-pandemic era.展开更多
基金National Health and Medical Research Council(NHMRC)of Australia,Grant/Award Numbers:APP2003904,GNT2022247NSW Cardiovascular Capacity Building Program,Grant/Award Number:Early-Mid Career Researcher Grant+7 种基金MRFF Cardiovascular Health Mission Grants,Grant/Award Numbers:APP2016165,APP2023977Ramaciotti Foundations,Grant/Award Number:2020HIG76National Heart Foundation,Grant/Award Numbers:106979,106879Office of Global and Research Engagement,Grant/Award Number:International Sustainable Development Goal ProgramSydney Nano Research Schemes,Grant/Award Number:Grand ChallengeNational Heart Foundation Future Leader Fellow Level 2,Grant/Award Number:105863Snow Medical Research Foundation Fellow,Grant/Award Number:2022SF176New South Wales Government。
文摘Cerebral venous sinus thrombosis(CVST)is a type of stroke associated with COVID-19 vaccine-induced immune thrombotic thrombocytopenia.The precise etiology of CVST often remains elusive due to the highly heterogeneous nature of its governing mechanisms,specifically,Virchow’s triad that involves altered blood flow,endothelial dysfunction,and hypercoagulability,which varies substantially amongst individuals.Existing diagnostic and monitoring approaches lack the capability to reflect the combination of these patient-specific thrombotic determinants.In response to this challenge,we introduce a Vein-Chip platform that recapitulates the CVST vascular anatomy from magnetic resonance venography and the associated hemodynamic flow profile using the“Chinese Movable Type-like”soft stereolithography technique.The resultant full-lumen personalized Vein-Chips,functionalized with endothelial cells,enable in-vitro thrombosis assays that can elucidate distinct thrombogenic scenarios between normal vascular conditions and those of endothelial dysfunction.The former displayed minimal platelet aggregation and negligible fibrin deposition,while the latter presented significant fibrin extrusion from platelet aggregations.The low-cost movable typing technique further enhances the potential for commercialization and broader utilization of personalized Vein-Chips in surgical labs and at-home monitoring.Future research and development in this direction will pave the way for improved management and prevention of CVST,ultimately benefiting both patients and healthcare systems.
基金supported by the National Health and Medical Research Council(NHMRC)of Australia(APP2003904-L.A.J.)NSW Cardiovascular Capacity Building Program(Early-Mid Career Researcher Grant-L.A.J.,P.Q.and Z.W.)+12 种基金MRFF Cardiovascular Health Mission Grants(MRF2016165-L.A.J.)MRF2023977-L.A.J.,and MRFF Early-to-Mid Career Researchers Grant(MRF2028865-L.A.J.)NSW Government Boosting Business Innovation Program(BBIP)International Stream(L.A.J.)National Heart Foundation Vanguard Grant(106979-L.A.J.)University of Sydney External Research Collaboration Seed Fund(L.A.J.and Z.W.)Lining Arnold Ju is a Snow Medical Research Foundation Fellow(2022SF176)a National Heart Foundation Future Leader Fellow Level 2(105863)Y.C.Z.is a NHMRC PhD Scholar(GNT2022247-Y.C.Z)a National Heart Foundation PhD Scholar(106879)National Health and Medical Research Council(Australia)Investigator Emerging Leadership 1 grant(GNT2018376)Heart foundation future leader fellowship with Paul Korner Award(106780)McCusker Charitable Foundation.
文摘Addressing the pressing demand for rapid and inexpensive coagulation testing in cardiovascular care,this study introduces a novel application of repurposed COVID-19 rapid antigen tests(RATs)as paper-based lateral flow assays(LFAs)combined with machine learning for coagulation status evaluation.By further developing a mobile app prototype,we present a platform that enables clinicians to perform immediate and accurate anticoagulant dosing adjustments using existing post-pandemic resources.Our proof-of-concept employs a random forest machine learning classifier to interpret image feature variations on RAT NC membrane,correlating red blood cell(RBC)wicked diffusion distance in recalcified citrated whole blood with changes in coagulative viscosity,easily interpreted.Enhanced by confocal imaging studies of paper microfluidics,our approach provides insights into the mechanisms dissecting coagulation components,achieving high classification precision,recall,and F1-scores.The inverse relationship between RBC wicked diffusion distance and enoxaparin concentration paves the way for machine learning to inform real-time dose prescription adjustments,aligning with individual patient profiles to optimize therapeutic outcomes.This study not only demonstrates the potential of leveraging surplus RATs for coagulation management but also exemplifies a cost-effective,rapid,and smart strategy to enhance clinical decision-making in the post-pandemic era.
