Partitioning uncertainty in projections of Arctic sea ice

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice

Partitioning uncertainty in projections of Arctic sea ice

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic ecosystem. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice extent (SIE) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIE, internal variability accounts for as much as 60% of the total uncertainty in the next few decades, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for approximately 70% of the total uncertainty by mid-century and declines to 20% at the end of the 21st century. For projections of wintertime Arctic SIE, internal variability contributes as much as 60% of the total uncertainty in the first few decades and impacts total uncertainty at longer lead times when compared to summer SIE. Model structure contributes the rest of the uncertainty with emissions scenario contributing little to the total uncertainty. At regional scales, the contribution of internal variability can vary widely and strongly depends on the month and region. For wintertime SIE in the GIN and Barents Seas, internal variability contributes approximately 70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate the need to improve the representation of internal variability of Arctic SIE in models, which is a significant source of uncertainty in future projections

Follow-Up in Aphasia Caused by Acute Stroke in a Prospective, Randomized, Clinical, and Experimental Controlled Noninvasive Study With an iPad-Based App (Neolexon®): Study Protocol of the Lexi Study

Rationale: Treatment of aphasia is still challenging for clinicians and patients. So far, there is proven evidence for “face-to-face” speech therapy. However, the digital age potentially offers new and complementary strategies that may add to treatment outcome in a cost-effective way. Neolexon® is a commercial tablet-based software for treatment of aphasia, which can be applied with the help of a therapist or as self-training by the patient. Aims and hypothesis: In the Lexi study, we aim to determine whether treatment with Neolexon® is superior to standard therapy in acute post-stroke aphasia. Sample size estimates: A sample size of 180 patients, 90 for each group, will be included with an assumed dropout rate of ~20%. Methods and design: Prospective, randomized, parallel group, open-label, blinded-endpoint clinical, and experimental controlled non-invasive trial (PROBE). Adult German native speakers with acute aphasia after stroke are included. Computer-generated, blocked, and stratified randomization by aphasia severity will assign patients to one of two groups: 4 weeks of either standard logopedic speech therapy or logopedic speech therapy with the app version of Neolexon®. Both groups will be instructed in self-training: the frequency and duration of self-training will be documented. Screening for aphasia will be performed using the Language Screening Test (LAST). The severity of aphasia in general and in subitems will be assessed using the Bielefelder Aphasie Screening (BIAS) and the Aphasia Check List (ACL). Follow-up will be assessed after 3 months. Study outcomes: Based on the consensus in our study team, we considered a 10% mean difference in the change of percentile rank (PR) of BIAS to be a minimal and clinically important difference. The primary endpoint is defined as a significant difference in BIAS comparing the two groups. Differences in quality of life, Beck Depression Inventory (BDI), and modified Ranking Scale (mRS) will be evaluated as secondary outcome parameters. Discussion: This trial will determine whether speech therapy with the use of Neolexon® is superior to standard logopedic therapy. Subgroups with the greatest response to Neolexon® will be described. The trial was prospectively registered on the “EU Clinical Trials Register” (NCT04080817)

PI5P4Kα supports prostate cancer metabolism and exposes a survival vulnerability during androgen receptor inhibition.

Phosphatidylinositol (PI)regulating enzymes are frequently altered in cancer and have become a focus for drug development. Here, we explore the phosphatidylinositol-5-phosphate 4-kinases (PI5P4K), a family of lipid kinases that regulate pools of intracellular PI, and demonstrate that the PI5P4Kα isoform influences androgen receptor (AR) signaling, which supports prostate cancer (PCa) cell survival. The regulation of PI becomes increasingly important in the setting of metabolic stress adaptation of PCa during androgen deprivation (AD), as we show that AD influences PI abundance and enhances intracellular pools of PI-4,5-P2. We suggest that this PI5P4Kα-AR relationship is mitigated through mTORC1 dysregulation and show that PI5P4Kα colocalizes to the lysosome, the intracellular site of mTORC1 complex activation. Notably, this relationship becomes prominent in mouse prostate tissue following surgical castration. Finally, multiple PCa cell models demonstrate marked survival vulnerability following stable PI5P4Kα inhibition. These results nominate PI5P4Kα as a target to disrupt PCa metabolic adaptation to castrate resistance

Grafted neural progenitor cells persist in the injured site and differentiate neuronally in a rodent model of cardiac arrest-induced global brain ischemia.

Hypoxic-ischemic brain injury is the leading cause of disability and death after successful resuscitation from cardiac arrest, and, to date, no specific treatment option is available to prevent subsequent neurofunctional impairments. The hippocampal cornu ammonis segment 1 (CA1) is one of the brain areas most affected by hypoxia, and its degeneration is correlated with memory deficits in patients and corresponding animal models. The aim of the present work was to evaluate the feasibility of neural progenitor cell (NPC) transplantation into the hippocampus in a refined rodent cardiac arrest model. Adult rats were subjected to 12 minutes of potassium-induced cardiac arrest and followed up to 6 weeks. Histological analysis showed extensive neuronal cell death specifically in the hippocampal CA1 segment, without any spontaneous regeneration. Neurofunctional assessment revealed transient memory deficits in ischemic animals compared to controls, detectable after 4, but not after 6 weeks. Using stereotactic surgery, embryonic NPCs were transplanted in a subset of animals 1 week after cardiac arrest and their survival, migration and differentiation were assessed histologically. Transplanted cells showed a higher persistence in the CA1 segment of animals after ischemia. Glia in the damaged CA1 segment expressed the chemotactic factor SDF-1, while transplanted NPCs expressed its receptor CXCR4, suggesting that the SDF-1/CXCR4 pathway, known to be involved in the migration of neural stem cells towards injured brain regions, directs the observed retention of cells in the damaged area. Using immunostaining, we could demonstrate that transplanted cells differentiated into mature neurons. In conclusion, our data document the survival, persistence in the injured area and neuronal differentiation of transplanted NPCs, and thus their potential to support brain regeneration after hypoxic-ischemic injury. This may represent an option worth further investigation in order to improve the outcome of patients after cardiac arrest

Partitioning uncertainty in projections of Arctic sea ice

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.ISSN:1748-9326ISSN:1748-931