Bengtssonkristiansen3511

The relativistic electron beam generation was simulated using a 2D particle-in-cell (PIC) code. Finally, three-dimensional hybrid-PIC simulations calculated the electron propagation and energy deposition inside the target and revealed the roles the compressed and self-generated B-fields play in transport. During a time window before the maximum compression time, the self-generated B-field on the compression front confines the injected electrons inside the target, increasing the temperature through Joule heating. For a stronger B-field seed of 20 T, the electrons are predicted to be guided into the compressed target and provide additional collisional heating. This article is part of a discussion meeting issue 'Prospects for high gain inertial fusion energy (part 2)'.Managing the IFE pathway to fusion electricity will involve management of commericalization scope, schedule, cost and risk. TAK-875 cell line The technology pathway to economical fusion power comprises the commercialization scope. Industry assumes commercialization risk in fielding its own pre-pilot plant research programme for this compact-fusion pathway without the benefit of a federally coordinated IFE research and development programme. The cost of commercializing the mass-production of inexpensive targets and insisting on high reliability, availability, maintainability and inspectability has a major impact on the economics of commercializing fusion power plants. Schedule vulnerability for inertial fusion energy arises from the sensitivity of time-based roadmap stages to uncertainties in the pace of scientific understanding and technology development, as well as to unexpected and inexplicable changes of the budgeting process. Rather than rely on a time-based roadmap, a milestone-based roadmap is maximally appropriate, especially for industry and investors who are particularly well-suited to taking the risks associated with reaching the target milestones provided by the government. link2 Milestones must be identified and optimally sequenced and the necessary resources must be delineated. Progress on the above factors, since the outcomes of recent U.S., U.K. and EUROfusion roadmapping exercises were released, are reported. This article is part of a discussion meeting issue 'Prospects for high gain inertial fusion energy (part 2)'.Since the seminal paper of Nuckolls triggering the quest of inertial confinement fusion (ICF) with lasers, hydrodynamic instabilities have been recognized as one of the principal hurdles towards ignition. This remains true nowadays for both main approaches (indirect drive and direct drive), despite the advent of MJ scale lasers with tremendous technological capabilities. From a fundamental science perspective, these gigantic laser facilities enable also the possibility to create dense plasma flows evolving towards turbulence, being magnetized or not. We review the state of the art of nonlinear hydrodynamics and turbulent experiments, simulations and theory in ICF and high-energy-density plasmas and draw perspectives towards in-depth understanding and control of these fascinating phenomena. This article is part of a discussion meeting issue 'Prospects for high gain inertial fusion energy (part 2)'.

To assess whether initial imaging characteristics independently predict 1-year neurological outcomes in childhood arterial ischemic stroke patients.

We used prospectively collected demographic and clinical data, imaging data, and 1-year outcomes from the VIPS study (Vascular Effects of Infection in Pediatric Stroke). link3 In 288 patients with first-time stroke, we measured infarct volume and location on the acute magnetic resonance imaging studies and hemorrhagic transformation on brain imaging studies during the acute presentation. Neurological outcome was assessed with the Pediatric Stroke Outcome Measure. We used univariate and multivariable ordinal logistic regression models to test the association between imaging characteristics and outcome.

Univariate analysis demonstrated that infarcts involving uncinate fasciculus, angular gyrus, insular cortex, or that extended from cortex to the subcortical nuclei were significantly associated with poorer outcomes with odds ratios ranging from 1.95 to 3.95. All locct upon outcome after childhood arterial ischemic stroke.

In the largest pediatric arterial ischemic stroke cohort collected to date, we showed that larger infarct volume and younger age at stroke were associated with poorer outcomes. We made the novel observation that the strength of these associations was modest and limits the ability to use these characteristics to predict outcome in children. Infarcts affecting specific locations were significantly associated with poorer outcomes in univariate and multivariable analyses but lost significance when adjusted for infarct volume. Our findings suggest that infarcts that disrupt critical networks have a disproportionate impact upon outcome after childhood arterial ischemic stroke.

Coronavirus disease 2019 (COVID-19) has been associated with an increased incidence of thrombotic events, including stroke. However, characteristics and outcomes of COVID-19 patients with stroke are not well known.

We conducted a retrospective observational study of risk factors, stroke characteristics, and short-term outcomes in a large health system in New York City. We included consecutively admitted patients with acute cerebrovascular events from March 1, 2020 through April 30, 2020. Data were stratified by COVID-19 status, and demographic variables, medical comorbidities, stroke characteristics, imaging results, and in-hospital outcomes were examined. Among COVID-19-positive patients, we also summarized laboratory test results.

Of 277 patients with stroke, 105 (38.0%) were COVID-19-positive. Compared with COVID-19-negative patients, COVID-19-positive patients were more likely to have a cryptogenic (51.8% versus 22.3%,

<0.0001) stroke cause and were more likely to suffer ischemic stroke in the . However, COVID-19-positive patients were more likely to experience stroke in a lobar location, more commonly had a cryptogenic cause, and had worse outcomes.

Time elapsed from last-known well (LKW) and baseline imaging results are influential on endovascular thrombectomy (EVT) outcomes.

In a prospective multicenter cohort study of imaging selection for endovascular thrombectomy (SELECT [Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke], the early infarct growth rate (EIGR) was defined as ischemic core volume on perfusion imaging (relative cerebral blood flow<30%) divided by the time from LKW to imaging. The optimal EIGR cutoff was identified by maximizing the sum of the sensitivity and specificity to correlate best with favorable outcome and to improve its the predictability. Patients were stratified into slow progressors if EIGR<cutoff and fast progressors if EIGR≥the optimal cutoff. Good collaterals were defined on computed tomography perfusion as a hypoperfusion intensity ratio <0.4 and on computed tomography angiography as collateral score >2. The primary outcome was 90-day functional independence (modified Ranurs. Registration URL https//clinicaltrials.gov. Unique identifier NCT02446587.

Prediction of infarct extent among patients with acute ischemic stroke using computed tomography perfusion is defined by predefined discrete computed tomography perfusion thresholds. Our objective is to develop a threshold-free computed tomography perfusion-based machine learning (ML) model to predict follow-up infarct in patients with acute ischemic stroke.

Sixty-eight patients from the PRoveIT study (Measuring Collaterals With Multi-Phase CT Angiography in Patients With Ischemic Stroke) were used to derive a ML model using random forest to predict follow-up infarction voxel by voxel, and 137 patients from the HERMES study (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) were used to test the derived ML model. Average map, T

, cerebral blood flow, cerebral blood volume, and time variables including stroke onset-to-imaging and imaging-to-reperfusion time, were used as features to train the ML model. Spatial and volumetric agreement between the ML model predicted follow-up i patients with acute ischemic stroke better than current methods.

The causes of recurrent ischemic stroke despite anticoagulation for atrial fibrillation are uncertain but might include small vessel occlusion. We investigated whether magnetic resonance imaging markers of cerebral small vessel disease (SVD) are associated with ischemic stroke risk during follow-up in patients anticoagulated for atrial fibrillation after recent ischemic stroke or transient ischemic attack.

We analyzed data from a prospective multicenter inception cohort study of ischemic stroke or transient ischemic attack anticoagulated for atrial fibrillation (CROMIS-2 [Clinical Relevance of Microbleeds in Stroke Study]). We rated markers of SVD on baseline brain magnetic resonance imaging basal ganglia perivascular spaces (number ≥11); cerebral microbleeds (number ≥1); lacunes (number ≥1); and white matter hyperintensities (periventricular Fazekas grade 3 or deep white matter Fazekas grade ≥2). We investigated the associations of SVD presence (defined as presence of ≥1 SVD marker) and severity (composik, magnetic resonance imaging markers of SVD are associated with an increased risk of ischemic stroke during follow-up; improved stroke prevention treatments are required in this population. Registration URL https//www.clinicaltrials.gov. Unique identifier NCT02513316.

In patients anticoagulated for atrial fibrillation after ischemic stroke or transient ischemic attack, magnetic resonance imaging markers of SVD are associated with an increased risk of ischemic stroke during follow-up; improved stroke prevention treatments are required in this population. Registration URL https//www.clinicaltrials.gov. Unique identifier NCT02513316.

Several clinical scoring systems as well as biomarkers have been proposed to predict stroke-associated pneumonia (SAP). We aimed to externally and competitively validate SAP scores and hypothesized that 5 selected biomarkers would improve performance of these scores.

We pooled the clinical data of 2 acute stroke studies with identical data assessment STRAWINSKI and PREDICT. Biomarkers (ultrasensitive procalcitonin; mid-regional proadrenomedullin; mid-regional proatrionatriuretic peptide; ultrasensitive copeptin; C-terminal proendothelin) were measured from hospital admission serum samples. A literature search was performed to identify SAP prediction scores. We then calculated multivariate regression models with the individual scores and the biomarkers. Areas under receiver operating characteristic curves were used to compare discrimination of these scores and models.

The combined cohort consisted of 683 cases, of which 573 had available backup samples to perform the biomarker analysis. Literature searchcapabilities, with better discrimination when stricter criteria for SAP diagnosis were applied. The selected biomarkers provided only limited added predictive value, currently not warranting addition of these markers to prediction models. Registration URL https//www.clinicaltrials.gov. Unique identifier NCT01264549 and NCT01079728.