Constraining ocean diffusivity from the 8.2 ka event

Greenland ice-core data containing the 8.2 ka event are utilized by a model-data intercomparison within the Earth system model of intermediate complexity, CLIMBER-2.3 to investigate their potential for constraining the range of uncertain ocean diffusivity properties. Within a stochastic version of the model (Bauer et al. in Paleoceanography 19:PA3014, 2004) it has been possible to mimic the pronounced cooling of the 8.2 ka event with relatively good accuracy considering the timing of the event in comparison to other modelling exercises. When statistically inferring from the 8.2 ka event on diffusivity the technical difficulty arises to establish the related likelihood numerically per realisation of the uncertain model parameters: while mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study the Bayesian Analysis leads to a sharp single-mode likelihood for ocean diffusivity parameters within CLIMBER-2.3. Depending on the prior distribution this likelihood leads to a reduction of uncertainty in ocean diffusivity parameters (e. g. for flat prior uncertainty in the vertical ocean diffusivity parameter is reduced by factor 2). These results highlight the potential of paleo data to constrain uncertain system properties and strongly suggest to make further steps with more complex models and richer data sets to harvest this potential. © The Author(s) 2009

Constraining ocean diffusivity from the 8.2 ka event

Greenland ice-core data containing the 8.2 ka event are utilized by a model-data intercomparison within the Earth system model of intermediate complexity, CLIMBER-2.3 to investigate their potential for constraining the range of uncertain ocean diffusivity properties. Within a stochastic version of the model (Bauer et al. in Paleoceanography 19:PA3014, 2004) it has been possible to mimic the pronounced cooling of the 8.2 ka event with relatively good accuracy considering the timing of the event in comparison to other modelling exercises. When statistically inferring from the 8.2 ka event on diffusivity the technical difficulty arises to establish the related likelihood numerically per realisation of the uncertain model parameters: while mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study the Bayesian Analysis leads to a sharp single-mode likelihood for ocean diffusivity parameters within CLIMBER-2.3. Depending on the prior distribution this likelihood leads to a reduction of uncertainty in ocean diffusivity parameters (e. g. for flat prior uncertainty in the vertical ocean diffusivity parameter is reduced by factor 2). These results highlight the potential of paleo data to constrain uncertain system properties and strongly suggest to make further steps with more complex models and richer data sets to harvest this potential. © The Author(s) 2009

Diagnostic, prognostic and predictive relevance of molecular markers in gliomas

The advances of genome-wide ‘discovery platforms’ and the increasing affordability of the analysis of significant sample sizes have led to the identification of novel mutations in brain tumours that became diagnostically and prognostically relevant. The development of mutation-specific antibodies has facilitated the introduction of these convenient biomarkers into most neuropathology laboratories and has changed our approach to brain tumour diagnostics. However, tissue diagnosis will remain an essential first step for the correct stratification for subsequent molecular tests, and the combined interpretation of the molecular and tissue diagnosis ideally remains with the neuropathologist. This overview will help our understanding of the pathobiology of common intrinsic brain tumours in adults and help guiding which molecular tests can supplement and refine the tissue diagnosis of the most common adult intrinsic brain tumours. This article will discuss the relevance of 1p/19q codeletions, IDH1/2 mutations, BRAF V600E and BRAF fusion mutations, more recently discovered mutations in ATRX, H3F3A, TERT, CIC and FUBP1, for diagnosis, prognostication and predictive testing. In a tumour-specific topic, the role of mitogen-activated protein kinase pathway mutations in the pathogenesis of pilocytic astrocytomas will be covered

INI1 mutations in meningiomas at a potential hotspot in exon 9

Rhabdoid tumours have been shown to carry somatic mutations in the INI1 (SMARCB1/hSNF5) gene. A considerable fraction of these tumours exhibit allelic losses on chromosome 22. Allelic loss on 22q also is characteristic for meningiomas, however most of these alterations are considered to be associated with mutations of the NF2 gene. We examined a series of 126 meningiomas for alterations in the INI1 gene. Four identical somatic mutations in exon 9 were detected resulting in an exchange of Arg to His in position 377 of INI1. Our observations were reproduced both by using DNA from a new round of extraction and by employing overlapping primers. This mutational hotspot therefore appears to be an important target in the formation of a fraction of meningiomas. In addition, 4 novel polymorphisms of INI1 were characterized. Our data indicate that the INI1 is a second tumour suppressor gene on chromosome 22 that may be important for the genesis of meningiomas. © 2001 Cancer Research Campaign http://www.bjcancer.co

Biomarker and Histopathology Evaluation of Patients with Recurrent Glioblastoma Treated with Galunisertib, Lomustine, or the Combination of Galunisertib and Lomustine

Galunisertib, a Transforming growth factor-βRI (TGF-βRI) kinase inhibitor, blocks TGF-β-mediated tumor growth in glioblastoma. In a three-arm study of galunisertib (300 mg/day) monotherapy (intermittent dosing; each cycle =14 days on/14 days off), lomustine monotherapy, and galunisertib plus lomustine therapy, baseline tumor tissue was evaluated to identify markers associated with tumor stage (e.g., histopathology, Ki67, glial fibrillary acidic protein) and TGF-β-related signaling (e.g., pSMAD2). Other pharmacodynamic assessments included chemokine, cytokine, and T cell subsets alterations. 158 patients were randomized to galunisertib plus lomustine (n = 79), galunisertib (n = 39) and placebo+lomustine (n = 40). In 127 of these patients, tissue was adequate for central pathology review and biomarker work. Isocitrate dehydrogenase (IDH1) negative glioblastoma patients with baseline pSMAD2+ in cytoplasm had median overall survival (OS) 9.5 months vs. 6.9 months for patients with no tumor pSMAD2 expression (p = 0.4574). Eight patients were IDH1 R132H+ and had a median OS of 10.4 months compared to 6.9 months for patients with negative IDH1 R132H (p = 0.5452). IDH1 status was associated with numerically higher plasma macrophage-derived chemokine (MDC/CCL22), higher whole blood FOXP3, and reduced tumor CD3+ T cell counts. Compared to the baseline, treatment with galunisertib monotherapy preserved CD4+ T cell counts, eosinophils, lymphocytes, and the CD4/CD8 ratio. The T-regulatory cell compartment was associated with better OS with MDC/CCL22 as a prominent prognostic marker. View Full-Tex

On the state dependency of fast feedback processes in (palaeo) climate sensitivity

Palaeo data have been frequently used to determine the equilibrium (Charney) climate sensitivity $S^a$, and - if slow feedback processes (e.g. land ice-albedo) are adequately taken into account - they indicate a similar range as estimates based on instrumental data and climate model results. Most studies implicitly assume the (fast) feedback processes to be independent of the background climate state, e.g., equally strong during warm and cold periods. Here we assess the dependency of the fast feedback processes on the background climate state using data of the last 800 kyr and a conceptual climate model for interpretation. Applying a new method to account for background state dependency, we find $S^a=0.61\pm0.06$ K(Wm$^{-2}$)$^{-1}$ using the latest LGM temperature reconstruction and significantly lower climate sensitivity during glacial climates. Due to uncertainties in reconstructing the LGM temperature anomaly, $S^a$ is estimated in the range $S^a=0.55-0.95$ K(Wm$^{-2}$)$^{-1}$.Comment: submitted to Geophysical Research Letter

The Panarea natural CO2 seeps: fate and impact of the leaking gas (PaCO2) ; R/V URANIA, Cruise No. U10/2011, 27 July – 01 August 2011, Naples (Italy) – Naples (Italy)

Carbon capture and storage (CCS), both on- and offshore, is expected to be an important technique to mitigate anthropogenic effects on global climate by isolating man-made carbon dioxide (CO2) in deep geological formations. In marine environments, however, the potential impacts of CO2 leakage, appropriate detection methods, and risk and pathways of atmospheric emissions are poorly defined. The natural CO2 gas seeps that occur in the relatively shallow waters off the coast of Panarea Island (Aeolian Islands, Italy) can be studied as a large-scale, real-world analogue of what might occur at a leaking offshore CCS site and what tools can be used to study it. The oceanographic survey PaCO2 was performed aboard R/V Urania from 27 July – 01 August 2011 (Naples – Naples). The project’s ship-time was funded by Eurofleets, with work being performed as a sub-project of the Seventh Framework Programme projects “ECO2” and “RISCS”, which provided subsidiary funding. Large amounts of data and samples were collected during the cruise which will be interpreted in the coming months, with preliminary results detailed here. Of particular importance was the discovery of much larger areas showing gas seepage than previously reported. Interdisciplinary measurements were performed at the Panarea seepage site. The international team of scientists onboard R/V Urania performed complementary sampling and measurements for biological, chemical, and physical parameters throughout the area. Together with the dedication of R/V Urania’s Captain and crew, and the eagerness and cooperation of the scientific crew, we were able to obtain excellent scientific results during this six-day cruise

Deep Yedoma permafrost: A synthesis of depositional characteristics and carbon vulnerability

Permafrost is a distinct feature of the terrestrial Arctic and is vulnerable to climate warming. Permafrost degrades in different ways, including deepening of a seasonally unfrozen surface and localized but rapid development of deep thaw features. Pleistocene ice-rich permafrost with syngenetic ice-wedges, termed Yedoma deposits, are widespread in Siberia, Alaska, and Yukon, Canada and may be especially prone to rapid-thaw processes. Freeze-locked organic matter in such deposits can be re-mobilized on short time-scales and contribute to a carbon cycle climate feedback. Here we synthesize the characteristics and vulnerability of Yedoma deposits by synthesizing studies on the Yedoma origin and the associated organic carbon pool. We suggest that Yedoma deposits accumulated under periglacial weathering, transport, and deposition dynamics in non-glaciated regions during the late Pleistocene until the beginning of late glacial warming. The deposits formed due to a combination of aeolian, colluvial, nival, and alluvial deposition and simultaneous ground ice accumulation. We found up to 130 gigatons organic carbon in Yedoma, parts of which are well-preserved and available for fast decomposition after thaw. Based on incubation experiments, up to 10% of the Yedoma carbon is considered especially decomposable and may be released upon thaw. The substantial amount of ground ice in Yedoma makes it highly vulnerable to disturbances such as thermokarst and thermo-erosion processes. Mobilization of permafrost carbon is expected to increase under future climate warming. Our synthesis results underline the need of accounting for Yedoma carbon stocks in next generation Earth-System-Models for a more complete representation of the permafrost-carbon feedback