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Protein kinases are highly tractable targets for drug discovery. However, the biological function and therapeutic potential of the majority of the 500+ human protein kinases remains unknown. We have developed physical and virtual collections of small molecule inhibitors, which we call chemogenomic sets, that are designed to inhibit the catalytic function of almost half the human protein kinases. In this manuscript we share our progress towards generation of a comprehensive kinase chemogenomic set (KCGS), release kinome profiling data of a large inhibitor set (Published Kinase Inhibitor Set 2 (PKIS2)), and outline a process through which the community can openly collaborate to create a KCGS that probes the full complement of human protein kinases.
Objective: The glucose stimulation of insulin secretion (GSIS) by pancreatic β-cells critically depends on increased production of metabolic coupling factors, including NADPH. Nicotinamide nucleotide transhydrogenase (NNT) typically produces NADPH at the expense of NADH and ΔpH in energized mitochondria. Its spontaneous inactivation in C57BL/6J mice was previously shown to alter ATP production, Ca2+ influx, and GSIS, thereby leading to glucose intolerance. Here, we tested the role of NNT in the glucose regulation of mitochondrial NADPH and glutathione redox state and reinvestigated its role in GSIS coupling events in mouse pancreatic islets.
Methods: Islets were isolated from female C57BL/6J mice (J-islets), which lack functional NNT, and genetically close C57BL/6N mice (N-islets). Wild-type mouse NNT was expressed in J-islets by adenoviral infection. Mitochondrial and cytosolic glutathione oxidation was measured with glutaredoxin 1-fused roGFP2 probes targeted or not to the mitochondrial matrix. NADPH and NADH redox state was measured biochemically. Insulin secretion and upstream coupling events were measured under dynamic or static conditions by standard procedures.
Results: NNT is largely responsible for the acute glucose-induced rise in islet NADPH/NADP+ ratio and decrease in mitochondrial glutathione oxidation, with a small impact on cytosolic glutathione. However, contrary to current views on NNT in β-cells, these effects resulted from a glucose-dependent reduction in NADPH consumption by NNT reverse mode of operation, rather than from a stimulation of its forward mode of operation. Accordingly, the lack of NNT in J-islets decreased their sensitivity to exogenous H2O2 at non-stimulating glucose. Surprisingly, the lack of NNT did not alter the glucose-stimulation of Ca2+ influx and upstream mitochondrial events, but it markedly reduced both phases of GSIS by altering Ca2+-induced exocytosis and its metabolic amplification.
Conclusion: These results drastically modify current views on NNT operation and mitochondrial function in pancreatic β-cells.
Global change effects on biodiversity and human wellbeing call for improved long-term environmental data as a basis for science, policy and decision making, including increased interoperability, multifunctionality, and harmonization. Based on the example of two global initiatives, the International Long-Term Ecological Research (ILTER) network and the Group on Earth Observations Biodiversity Observation Network (GEO BON), we propose merging the frameworks behind these initiatives, namely ecosystem integrity and essential biodiversity variables, to serve as an improved guideline for future site-based long-term research and monitoring in terrestrial, freshwater and coastal ecosystems. We derive a list of specific recommendations of what and how to measure at a monitoring site and call for an integration of sites into co-located site networks across individual monitoring initiatives, and centered on ecosystems. This facilitates the generation of linked comprehensive ecosystem monitoring data, supports synergies in the use of costly infrastructures, fosters cross-initiative research and provides a template for collaboration beyond the ILTER and GEO BON communities.
Background: In oldest-old patients (>80), few trials showed efficacy of treating hypertension and they included mostly the healthiest elderly. The resulting lack of knowledge has led to inconsistent guidelines, mainly based on systolic blood pressure (SBP), cardiovascular disease (CVD) but not on frailty despite the high prevalence in oldest-old. This may lead to variation how General Practitioners (GPs) treat hypertension. Our aim was to investigate treatment variation of GPs in oldest-olds across countries and to identify the role of frailty in that decision.
Methods: Using a survey, we compared treatment decisions in cases of oldest-old varying in SBP, CVD, and frailty. GPs were asked if they would start antihypertensive treatment in each case. In 2016, we invited GPs in Europe, Brazil, Israel, and New Zealand. We compared the percentage of cases that would be treated per countries. A logistic mixed-effects model was used to derive odds ratio (OR) for frailty with 95% confidence intervals (CI), adjusted for SBP, CVD, and GP characteristics (sex, location and prevalence of oldest-old per GP office, and years of experience). The mixed-effects model was used to account for the multiple assessments per GP.
Results: The 29 countries yielded 2543 participating GPs: 52% were female, 51% located in a city, 71% reported a high prevalence of oldest-old in their offices, 38% and had >20 years of experience. Across countries, considerable variation was found in the decision to start antihypertensive treatment in the oldest-old ranging from 34 to 88%. In 24/29 (83%) countries, frailty was associated with GPs’ decision not to start treatment even after adjustment for SBP, CVD, and GP characteristics (OR 0.53, 95%CI 0.48–0.59; ORs per country 0.11–1.78).
Conclusions: Across countries, we found considerable variation in starting antihypertensive medication in oldest-old. The frail oldest-old had an odds ratio of 0.53 of receiving antihypertensive treatment. Future hypertension trials should also include frail patients to acquire evidence on the efficacy of antihypertensive treatment in oldest-old patients with frailty, with the aim to get evidence-based data for clinical decision-making.
Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human–water interface in hydrological models.
Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1–10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.
Land surface and hydrologic models (LSM/HM) are used at diverse spatial resolutions ranging from 1-10 km in catchment-scale applications to over 50 km in global-scale applications. Application of the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the model resolution and fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent and realistic parameter fields for land surface geophysical properties. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB and WaterGAP models are conducted to demonstrate the pitfalls of poor parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge’s 1982 statement on the unsolved problem of parameterization in these models remains true. We provide a short review of existing parameter regionalization techniques and discuss a method for obtaining seamless hydrological predictions of water fluxes and states across multiple spatial resolutions. The multiscale parameter regionalization (MPR) technique is a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. A general model protocol is presented to describe how MPR can be applied to a specific model, with an example of this application using the PCR-GLOBWB model. Applying MPR to PCR-GLOBWB substantially improves the flux-matching condition. Estimation of evapotranspiration without MPR at 5 arcmin and 30 arcmin spatial resolutions for the Rhine river basin results in a difference of approximately 29%. Applying MPR reduce this difference to 9%. For total soil water, the differences without and with MPR are 25% and 7%, respectively.
A measurement of dijet correlations in p-Pb collisions at sNN−−−√=5.02 TeV with the ALICE detector is presented. Jets are reconstructed from charged particles measured in the central tracking detectors and neutral energy deposited in the electromagnetic calorimeter. The transverse momentum of the full jet (clustered from charged and neutral constituents) and charged jet (clustered from charged particles only) is corrected event-by-event for the contribution of the underlying event, while corrections for underlying event fluctuations and finite detector resolution are applied on an inclusive basis. A projection of the dijet transverse momentum, kTy=pch+neT,jetsin(Δφdijet) with Δφdijet the azimuthal angle between a full and charged jet and pch+neT,jet the transverse momentum of the full jet, is used to study nuclear matter effects in p-Pb collisions. This observable is sensitive to the acoplanarity of dijet production and its potential modification in p-Pb collisions with respect to pp collisions. Measurements of the dijet kTy as a function of the transverse momentum of the full and recoil charged jet, and the event multiplicity are presented. No significant modification of kTy due to nuclear matter effects in p-Pb collisions with respect to the event multiplicity or a PYTHIA8 reference is observed.