Predicting outcome in acute stroke with large vessel occlusion:application and validation of MR PREDICTS in the ESCAPE-NA1 population

Background: Predicting outcome after endovascular treatment for acute ischemic stroke is challenging. We aim to investigate differences between predicted and observed outcomes in patients with acute ischemic stroke treated with endovascular treatment and to evaluate the performance of a validated outcome prediction score. Patients and methods: MR PREDICTS is an outcome prediction tool based on a logistic regression model designed to predict the treatment benefit of endovascular treatment based on the MR CLEAN and HERMES populations. ESCAPE-NA1 is a randomized trial of nerinetide vs. placebo in patients with acute stroke and large vessel occlusion. We applied MR PREDICTS to patients in the control arm of ESCAPE-NA1. Model performance was assessed by calculating its discriminative ability and calibration. Results: Overall, 556/1105 patients (50.3%) in the ESCAPE-NA1-trial were randomized to the control arm, 435/556 (78.2%) were treated within 6 h of symptom onset. Good outcome (modified Rankin scale 0–2) at 3 months was achieved in 275/435 patients (63.2%), the predicted probability of good outcome was 52.5%. Baseline characteristics were similar in the study and model derivation cohort except for age (ESCAPE-NA1: mean: 70 y vs. HERMES: 66 y), hypertension (72% vs. 57%), and collaterals (good collaterals, 15% vs. 44%). Compared to HERMES we observed higher rates of successful reperfusion (TICI 2b-3, ESCAPE-NA1: 87% vs. HERMES: 71%) and faster times from symptom onset to reperfusion (median: 201 min vs. 286 min). Model performance was good, indicated by a c-statistic of 0.76 (95%confidence interval: 0.71–0.81). Conclusion: Outcome-prediction using models created from HERMES data, based on information available in the emergency department underestimated the actual outcome in patients with acute ischemic stroke and large vessel occlusion receiving endovascular treatment despite overall good model performance, which might be explained by differences in quality of and time to reperfusion. These findings underline the importance of timely and successful reperfusion for functional outcomes in acute stroke patients.</p

Imaging, Intervention, and Workflow in Acute Ischemic Stroke: The Calgary Approach

ABSTRACT SUMMARY: Five recently published clinical trials showed dramatically higher rates of favorable functional outcome and a satisfying safety profile of endovascular treatment compared with the previous standard of care in acute ischemic stroke with proximal anterior circulation artery occlusion. Eligibility criteria within these trials varied by age, stroke severity, imaging, treatment-time window, and endovascular treatment devices. This focused review provides an overview of the trial results and explores the heterogeneity in imaging techniques, workflow, and endovascular techniques used in these trials and the consequent impact on practice. Using evidence from these trials and following a case from start to finish, this review recommends strategies that will help the appropriate patient undergo a fast, focused clinical evaluation, imaging, and intervention. ABBREVIATIONS: MR CLEAN ϭ Multicenter Randomized Clinical trial of Endovascular treatment for Acute ischemic stroke in the Netherlands; EMS ϭ Emergenc

Predicting outcome in acute stroke with large vessel occlusion:application and validation of MR PREDICTS in the ESCAPE-NA1 population

Background: Predicting outcome after endovascular treatment for acute ischemic stroke is challenging. We aim to investigate differences between predicted and observed outcomes in patients with acute ischemic stroke treated with endovascular treatment and to evaluate the performance of a validated outcome prediction score. Patients and methods: MR PREDICTS is an outcome prediction tool based on a logistic regression model designed to predict the treatment benefit of endovascular treatment based on the MR CLEAN and HERMES populations. ESCAPE-NA1 is a randomized trial of nerinetide vs. placebo in patients with acute stroke and large vessel occlusion. We applied MR PREDICTS to patients in the control arm of ESCAPE-NA1. Model performance was assessed by calculating its discriminative ability and calibration. Results: Overall, 556/1105 patients (50.3%) in the ESCAPE-NA1-trial were randomized to the control arm, 435/556 (78.2%) were treated within 6 h of symptom onset. Good outcome (modified Rankin scale 0–2) at 3 months was achieved in 275/435 patients (63.2%), the predicted probability of good outcome was 52.5%. Baseline characteristics were similar in the study and model derivation cohort except for age (ESCAPE-NA1: mean: 70 y vs. HERMES: 66 y), hypertension (72% vs. 57%), and collaterals (good collaterals, 15% vs. 44%). Compared to HERMES we observed higher rates of successful reperfusion (TICI 2b-3, ESCAPE-NA1: 87% vs. HERMES: 71%) and faster times from symptom onset to reperfusion (median: 201 min vs. 286 min). Model performance was good, indicated by a c-statistic of 0.76 (95%confidence interval: 0.71–0.81). Conclusion: Outcome-prediction using models created from HERMES data, based on information available in the emergency department underestimated the actual outcome in patients with acute ischemic stroke and large vessel occlusion receiving endovascular treatment despite overall good model performance, which might be explained by differences in quality of and time to reperfusion. These findings underline the importance of timely and successful reperfusion for functional outcomes in acute stroke patients.</p

The key features of SARS-CoV-2 leader and NSP1 required for viral escape of NSP1-mediated repression

SARS-CoV-2, responsible for the ongoing global pandemic, must overcome a conundrum faced by all viruses. To achieve its own replication and spread, it simultaneously depends on and subverts cellular mechanisms. At the early stage of infection, SARS-CoV-2 expresses the viral nonstructural protein 1 (NSP1), which inhibits host translation by blocking the mRNA entry tunnel on the ribosome; this interferes with the binding of cellular mRNAs to the ribosome. Viral mRNAs, on the other hand, overcome this blockade. We show that NSP1 enhances expression of mRNAs containing the SARS-CoV-2 leader. The first stem-loop (SL1) in viral leader is both necessary and sufficient for this enhancement mechanism. Our analysis pinpoints specific residues within SL1 (three cytosine residues at the positions 15, 19 and 20) and another within NSP1 (R124) which are required for viral evasion, and thus might present promising drug targets. We target SL1 with the anti-sense oligo (ASO) to efficiently and specifically downregulate SARS-CoV-2 mRNA. Additionally, we carried out analysis of a functional interactome of NSP1 using BioID and identified components of anti-viral defense pathways. Our analysis therefore suggests a mechanism by which NSP1 inhibits the expression of host genes while enhancing that of viral RNA. This analysis helps reconcile conflicting reports in the literature regarding the mechanisms by which the virus avoids NSP1 silencing

mRNA stability and m(6)A are major determinants of subcellular mRNA localization in neurons

For cells to perform their biological functions, they need to adopt specific shapes and form functionally distinct subcellular compartments. This is achieved in part via an asymmetric distribution of mRNAs within cells. Currently, the main model of mRNA localization involves specific sequences called "zipcodes" that direct mRNAs to their proper locations. However, while thousands of mRNAs localize within cells, only a few zipcodes have been identified, suggesting that additional mechanisms contribute to localization. Here, we assess the role of mRNA stability in localization by combining the isolation of the soma and neurites of mouse primary cortical and mESC-derived neurons, SLAM-seq, m(6)A-RIP-seq, the perturbation of mRNA destabilization mechanisms, and the analysis of multiple mRNA localization datasets. We show that depletion of mRNA destabilization elements, such as m(6)A, AU-rich elements, and suboptimal codons, functions as a mechanism that mediates the localization of mRNAs associated with housekeeping functions to neurites in several types of neurons

Massively parallel identification of mRNA localization elements in primary cortical neurons

Cells adopt highly polarized shapes and form distinct subcellular compartments in many cases due to the localization of many mRNAs to specific areas, where they are translated into proteins with local functions. This mRNA localization is mediated by specific cis-regulatory elements in mRNAs, commonly called ‘zipcodes’. Although there are hundreds of localized mRNAs, only a few zipcodes have been characterized. Here we describe a novel neuronal zipcode identification protocol (N-zip) that can identify zipcodes across hundreds of 3′ untranslated regions. This approach combines a method of separating the principal subcellular compartments of neurons—cell bodies and neurites—with a massively parallel reporter assay. N-zip identifies the let-7 binding site and (AU)n motif as de novo zipcodes in mouse primary cortical neurons. Our analysis also provides, to our knowledge, the first demonstration of an miRNA affecting mRNA localization and suggests a strategy for detecting many more zipcodes

Defining Optimal Brain Health in Adults A Presidential Advisory From the American Heart Association/American Stroke Association

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index < 25 kg/m(2)) and 3 ideal health factors (untreated blood pressure < 120/< 80 mm Hg, untreated total cholesterol < 200 mg/dL, and fasting blood glucose < 100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA's Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention

Eleven strategies for making reproducible research and open science training the norm at research institutions

Across disciplines, researchers increasingly recognize that open science and reproducible research practices may accelerate scientific progress by allowing others to reuse research outputs and by promoting rigorous research that is more likely to yield trustworthy results. While initiatives, training programs, and funder policies encourage researchers to adopt reproducible research and open science practices, these practices are uncommon inmanyfields. Researchers need training to integrate these practicesinto their daily work. We organized a virtual brainstorming event, in collaboration with the German Reproducibility Network, to discuss strategies for making reproducible research and open science training the norm at research institutions. Here, weoutline eleven strategies, concentrated in three areas:(1)offering training, (2)adapting research assessment criteria and program requirements, and (3) building communities. We provide a brief overview of each strategy, offer tips for implementation,and provide links to resources. Our goal is toencourage members of the research community to think creatively about the many ways they can contribute and collaborate to build communities,and make reproducible research and open sciencetraining the norm. Researchers may act in their roles as scientists, supervisors, mentors, instructors, and members of curriculum, hiring or evaluation committees. Institutionalleadership and research administration andsupport staff can accelerate progress by implementing change across their institution

Eleven strategies for making reproducible research and open science training the norm at research institutions

Reproducible research and open science practices have the potential to accelerate scientific progress by allowing others to reuse research outputs, and by promoting rigorous research that is more likely to yield trustworthy results. However, these practices are uncommon in many fields, so there is a clear need for training that helps and encourages researchers to integrate reproducible research and open science practices into their daily work. Here, we outline eleven strategies for making training in these practices the norm at research institutions. The strategies, which emerged from a virtual brainstorming event organized in collaboration with the German Reproducibility Network, are concentrated in three areas: (i) adapting research assessment criteria and program requirements; (ii) training; (iii) building communities. We provide a brief overview of each strategy, offer tips for implementation, and provide links to resources. We also highlight the importance of allocating resources and monitoring impact. Our goal is to encourage researchers - in their roles as scientists, supervisors, mentors, instructors, and members of curriculum, hiring or evaluation committees - to think creatively about the many ways they can promote reproducible research and open science practices in their institutions