Highly variable friction and slip observed at Antarctic ice stream bed

The slip of glaciers over the underlying bed is the dominant mechanism governing the migration of ice from land into the oceans, with accelerating slip contributing to sea-level rise. Yet glacier slip remains poorly understood, and observational constraints are sparse. Here we use passive seismic observations to measure both frictional shear stress and slip at the bed of the Rutford Ice Stream in Antarctica using 100,000 repetitive stick-slip icequakes. We find that basal shear stresses and slip rates vary from 104 to 107 Pa and 0.2 to 1.5 m per day, respectively. Friction and slip vary temporally over the order of hours, and spatially over 10s of metres, due to corresponding variations in effective normal stress and ice–bed interface material. Our findings suggest that the bed is substantially more complex than currently assumed in ice stream models and that basal effective normal stresses may be significantly higher than previously thought. Our observations can provide constraints on the basal boundary conditions for ice-dynamics models. This is critical for constraining the primary contribution of ice mass loss in Antarctica and hence for reducing uncertainty in sea-level rise projections

Depressive symptoms and anti-N-methyl-D-aspartate-receptor GluN1 antibody seropositivity in the PROSpective cohort with incident stroke

Background: Anti-NMDA-receptor GluN1 antibodies (NMDAR1-abs) are present in an autoimmune encephalitis with severe neuropsychiatric symptoms. We aimed to estimate the impact of serum NMDAR1-abs on depressive symptoms years after first-ever ischemic stroke (IS). Methods: Data were used from the PROSpective Cohort with Incident Stroke-Berlin (PROSCIS-B; NCT01363856). Serum NMDAR1-abs (IgM/IgA/IgG) were measured within 7 days after IS using cell-based assays. We defined seropositivity as titers ≥1:10, thereof low titers as ≤1:100 and high titers as >1:100. We used the Center for Epidemiological Studies–Depression (CES-D) scale to measure depressive symptoms at year one, two and three following IS. We calculated crude and confounder adjusted weighted generalized linear models to quantify the impact of NMDAR1-abs on CES-D assessed at three annual time-points. Results: NMDAR1-abs were measured in 583 PROSCIS-B IS patients (mean age = 67 [SD = 13]; 42%female; median NIHSS = 2 [IQR = 1–4]) of whom 76 (13%; IgM: n = 49/IgA: n = 43/IgG: n = 2) were seropositive, 55 (9%) with low and 21 (4%) with high titers. CES-D regarded over all follow-up time-points was higher in seropositive patients (β(crude) = 2.56 [95%CI = −0.34 to 5.45]; β(adjusted) = 2.26 [95%CI = −0.68 to 5.20]) and effects were highest in patients with high titer (low titers: β(crude) = 1.42 [95%CI = −1.79 to 4.62], β(adjusted) = 0.53 [95%CI = −2.47 to 3.54]; high titers: β(crude) = 5.85 [95%CI = 0.20 to 11.50]; β(adjusted) = 7.20 [95%CI = 0.98 to 13.43]). Conclusion: Patients with serum NMDAR1-abs (predominantly IgM&IgA) suffer more severe depressive symptoms after mild-to-moderate IS compared to NMDAR1-abs seronegative patients

Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke

BACKGROUND: Accurate prediction of clinical outcomes in individual patients following acute stroke is vital for healthcare providers to optimize treatment strategies and plan further patient care. Here, we use advanced machine learning (ML) techniques to systematically compare the prediction of functional recovery, cognitive function, depression, and mortality of first-ever ischemic stroke patients and to identify the leading prognostic factors. METHODS: We predicted clinical outcomes for 307 patients (151 females, 156 males; 68 ± 14 years) from the PROSpective Cohort with Incident Stroke Berlin study using 43 baseline features. Outcomes included modified Rankin Scale (mRS), Barthel Index (BI), Mini-Mental State Examination (MMSE), Modified Telephone Interview for Cognitive Status (TICS-M), Center for Epidemiologic Studies Depression Scale (CES-D) and survival. The ML models included a Support Vector Machine with a linear kernel and a radial basis function kernel as well as a Gradient Boosting Classifier based on repeated 5-fold nested cross-validation. The leading prognostic features were identified using Shapley additive explanations. RESULTS: The ML models achieved significant prediction performance for mRS at patient discharge and after 1 year, BI and MMSE at patient discharge, TICS-M after 1 and 3 years and CES-D after 1 year. Additionally, we showed that National Institutes of Health Stroke Scale (NIHSS) was the top predictor for most functional recovery outcomes as well as education for cognitive function and depression. CONCLUSION: Our machine learning analysis successfully demonstrated the ability to predict clinical outcomes after first-ever ischemic stroke and identified the leading prognostic factors that contribute to this prediction

Associations of clonal hematopoiesis with recurrent vascular events and death in patients with incident ischemic stroke

Clonal hematopoiesis (CH) is common among older people and associated with an increased risk of atherosclerosis, inflammation, and shorter overall survival. Age and inflammation are major risk factors for ischemic stroke, yet the association of CH with risk of secondary vascular events and death is unknown. We investigated CH in peripheral blood DNA from 581 patients with first-ever ischemic stroke from the Prospective Cohort with Incident Stroke-Berlin study (PROSCIS-B) using error-corrected targeted sequencing. The primary composite endpoint (CEP) consisted of recurrent stroke, myocardial infarction, and all-cause mortality. 348 somatic mutations with a variant allele frequency ≥ 1% were identified in 236/581 patients (41%). CH was associated with large-artery atherosclerosis stroke (P = 0.01) and white matter lesion (P < 0.001). CH-positive patients showed increased levels of pro-inflammatory cytokines such as IL-6, IFN-γ, hsCRP, and VCAM-1. CH-positive patients had a higher risk for the primary CEP (HR: 1.55, 95%-CI 1.04 - 2.31, P = 0.03), which was more pronounced in patients with larger clones. CH clone size remained an independent risk factor (HR 1.30, 95%-CI 1.04 - 1.62, P = 0.022) in multivariable Cox regression. While our data show that in particular larger and TET2- or PPM1D-mutated clones are associated with increased risk of recurrent vascular events and death, this risk is partially mitigated by a common germline variant of the IL-6 receptor (IL-6R p.D358A). The CH mutation profile is accompanied by a pro-inflammatory profile opening new avenues for preventive precision medicine approaches to resolve the self-perpetuating cycle of inflammation and clonal expansion