The HelioMont method for assessing solar irradiance over complex terrain: Validation and improvements

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Addressing Grand Challenges in Earth Observation Science: The Earth Observation Data Centre for Water Resources Monitoring

Earth observation is entering a new era where the increasing availability of free and open global satellite data sets combined with the computing power offered by modern information technologies opens up the possibility to process high-resolution data sets at global scale and short repeat intervals in a fully automatic fashion. This will not only boost the availability of higher level earth observation data in purely quantitative terms, but can also be expected to trigger a step change in the quality and usability of earth observation data. However, the technical, scientific, and organisational challenges that need to be overcome to arrive at this point are significant. First of all, Petabyte-scale data centres are needed for storing and processing complete satellite data records. Second, innovative processing chains that allow fully automatic processing of the satellite data from the raw sensor records to higher-level geophysical products need to be developed. Last but not least, new models of cooperation between public and private actors need to be found in order to live up to the first two challenges. This paper offers a discussion of how the Earth Observation Data Centre for Water Resources Monitoring (EODC) – a catalyser for an open and international cooperation of public and private organisations – will address these three grand challenges with the aim to foster the use of earth observation for monitoring of global water resources

Climate Risk Sourcebook

The Climate Risks Sourcebook provides an updated methodological approach on how to design and conduct climate risk assessments and provides the necessary and state-of-the-art knowledge incorporating findings of the sixth Assessment Report of the IPCC. It is a user-friendly, step-by-step guide to operationalizing the theoretical concept of risk. The approach is location and context-specific and gives guidance on how climate risk assessments can inform and support evidence-based decision making. This includes impact chains as tailor-made conceptual models that illustrate key risks and their drivers for a specific context. The Climate Risk Sourcebook additionally offers expert material for further in-depth knowledge. Another novelty is its focus on communication, gender and vulnerable groups

LGR5 receptor promotes cell-cell adhesion in stem cells and colon cancer cells via the IQGAP1 -Rac1 pathway

Leucine-rich repeat-containing G protein–coupled receptor 5 (LGR5) is a bona fide marker of adult stem cells in several epithelial tissues, most notably in the intestinal crypts, and is highly up-regulated in many colorectal, hepatocellular, and ovarian cancers. LGR5 activation by R-spondin (RSPO) ligands potentiates Wnt/β-catenin signaling in vitro; however, deletion of LGR5 in stem cells has little or no effect on Wnt/β-catenin signaling or cell proliferation in vivo. Remarkably, modulation of LGR5 expression has a major impact on the actin cytoskeletal structure and cell adhesion in the absence of RSPO stimulation, but the molecular mechanism is unclear. Here, we show that LGR5 interacts with IQ motif-containing GTPase-activating protein 1 (IQGAP1), an effector of Rac1/CDC42 GTPases, in the regulation of actin cytoskeleton dynamics and cell–cell adhesion. Specifically, LGR5 decreased levels of IQGAP1 phosphorylation at Ser-1441/1443, leading to increased binding of Rac1 to IQGAP1 and thus higher levels of cortical F-actin and enhanced cell–cell adhesion. LGR5 ablation in colon cancer cells and crypt stem cells resulted in loss of cortical F-actin, reduced cell–cell adhesion, and disrupted localization of adhesion-associated proteins. No evidence of LGR5 coupling to any of the four major subtypes of heterotrimeric G proteins was found. These findings suggest that LGR5 primarily functions via the IQGAP1–Rac1 pathway to strengthen cell–cell adhesion in normal adult crypt stem cells and colon cancer cells

Adaptation in integrated assessment modeling: where do we stand?

Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up characteristics. Until this happens, we suggest, models may be too optimistic about the net benefits adaptation can provide, and therefore may underestimate the amount of mitigation they judge to be socially optimal. Under some conditions, better modeling of adaptation costs and benefits could have important implications for defining mitigation targets. © Springer Science+Business Media B.V. 2009

Cox proportional hazards deep neural network identifies peripheral blood complete remission to be at least equivalent to morphologic complete remission in predicting outcomes of patients treated with azacitidine - a prospective cohort study by the AGMT

The current gold standard of response assessment in patients with myelodysplastic syndromes (MDS), chronic myelomonocytic leukemia (CMML), and acute myeloid leukemia (AML) is morphologic complete remission (CR) and CR with incomplete count recovery (CRi), both of which require an invasive BM evaluation. Outside of clinical trials, BM evaluations are only performed in ~50% of patients during follow-up, pinpointing a clinical need for response endpoints that do not necessitate BM assessments. We define and validate a new response type termed "peripheral blood complete remission" (PB-CR) that can be determined from the differential blood count and clinical parameters without necessitating a BM assessment. We compared the predictive value of PB-CR with morphologic CR/CRi in 1441 non-selected, consecutive patients diagnosed with MDS (n = 522; 36.2%), CMML (n = 132; 9.2%), or AML (n = 787; 54.6%), included within the Austrian Myeloid Registry (aMYELOIDr; NCT04438889). Time-to-event analyses were adjusted for 17 covariates remaining in the final Cox proportional hazards (CPH) model. DeepSurv, a CPH neural network model, and permutation-based feature importance were used to validate results. 1441 patients were included. Adjusted median overall survival for patients achieving PB-CR was 22.8 months (95%CI 18.9-26.2) versus 10.4 months (95%CI 9.7-11.2) for those who did not; HR = 0.366 (95%CI 0.303-0.441; p < .0001). Among patients achieving CR, those additionally achieving PB-CR had a median adjusted OS of 32.6 months (95%CI 26.2-49.2) versus 21.7 months (95%CI 16.9-27.7; HR = 0.400 [95%CI 0.190-0.844; p = .0161]) for those who did not. Our deep neural network analysis-based findings from a large, prospective cohort study indicate that BM evaluations solely for the purpose of identifying CR/CRi can be omitted