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In 1989, the need for reliable gridded land surface precipitation data sets, in view of the large uncertainties in the assessment of the global energy and water cycle, has led to the establishment of the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst on invitation of the WMO. The GPCC has calculated a precipitation climatology for the global land areas for the target period 1951–2000 by objective analysis of climatological normals of about 67,200 rain gauge stations from its data base. GPCC's new precipitation climatology is compared to several other station-based precipitation climatologies as well as to precipitation climatologies derived from the GPCP V2.2 data set and from ECMWF's model reanalyses ERA-40 and ERA-Interim. Finally, how GPCC's best estimate for terrestrial mean precipitation derived from the precipitation climatology of 786 mm per year (equivalent to a water transport of 117,000 km³) is fitting into the global water cycle context is discussed.

The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.

The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5° × 2.5° latitude–longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Niño–Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

During the past decade, the Arctic has experienced its highest temperatures of the instrumental record, even exceeding the warmth of the 1930s and 1940s. Recent paleo-reconstructions also show that recent Arctic summer temperatures are higher than at any time in the past 2000 years. The geographical distribution of the recent warming points strongly to an influence of sea ice reduction. The spatial pattern of the near-surface warming also shows the signature of the Pacific Decadal Oscillation in the Pacific sector as well as the influence of a dipole-like circulation pattern in the Atlantic sector. Areally averaged Arctic precipitation over the land areas north of 55°N shows large year-to-year variability, superimposed on an increase of about 5% since 1950. The years since 2000 have been wetter than average according to both precipitation and river discharge data. There are indications of increased cloudiness over the Arctic, especially low clouds during the warm season, consistent with a longer summer and a reduction of summer sea ice. Storm events and extreme high temperature show signs of increases. The Arctic Ocean has experienced enhanced oceanic heat inflows from both the North Atlantic and the North Pacific. The Pacific inflows evidently played a role in the retreat of sea ice in the Pacific sector of the Arctic Ocean, while the Atlantic water heat influx has been characterized by increasingly warm pulses. Recent shipboard observations show increased ocean heat storage in newly sea-ice-free ocean areas, with increased influence on autumn atmospheric temperature and wind fields.

The \"satellite-gauge-model\" (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5° × 2.5° lat–long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40°N–40°S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brought in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields. The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions.

The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.The amyloid hypothesis has been the dominant model for the pathogenesis of Alzheimer disease for several decades. In this Perspective, Giovanni Frisoni and colleagues examine evidence for and against this hypothesis before outlining an alternative model, the probabilistic model of Alzheimer disease.

Roots of land plants are populated by a specific microbiota capable of modulating plant growth and development; here large-scale sequencing analysis shows that the bacterial community inhabiting Arabidopsis roots is influenced by soil type and plant genotype, and that plant cell-wall features serve as colonization cue for a subcommunity of the root microbiota. Root dwellers: bacterial communities in the plant root microbiome The association between a land plant and the soil microbes of the root microbiome is important for the plant's well-being. A deeper understanding of these microbial communities will offer opportunities to control plant growth and susceptibility to pathogens, particularly in sustainable agricultural regimes. Two groups, working separately but developing best-practice protocols in parallel, have characterized the root microbiota of the model plant Arabidopis thaliana . Working on two continents and with five different soil types, they reach similar general conclusions. The bacterial communities in each root compartment — the rhizosphere immediately surrounding the root and the endophytic compartment within the root — are most strongly influenced by soil type, and to a lesser degree by host genotype. In natural soils, Arabidopsis plants are preferentially colonized by Actinobacteria, Proteobacteria, Bacteroidetes and Chloroflexi species. And — an important point for future work — Arabidopsis root selectivity for soil bacteria under controlled environmental conditions mimics that of plants grown in a natural environment. The plant root defines the interface between a multicellular eukaryote and soil, one of the richest microbial ecosystems on Earth 1 . Notably, soil bacteria are able to multiply inside roots as benign endophytes and modulate plant growth and development 2 , with implications ranging from enhanced crop productivity 3 to phytoremediation 4 . Endophytic colonization represents an apparent paradox of plant innate immunity because plant cells can detect an array of microbe-associated molecular patterns (also known as MAMPs) to initiate immune responses to terminate microbial multiplication 5 . Several studies attempted to describe the structure of bacterial root endophytes 6 ; however, different sampling protocols and low-resolution profiling methods make it difficult to infer general principles. Here we describe methodology to characterize and compare soil- and root-inhabiting bacterial communities, which reveals not only a function for metabolically active plant cells but also for inert cell-wall features in the selection of soil bacteria for host colonization. We show that the roots of Arabidopsis thaliana , grown in different natural soils under controlled environmental conditions, are preferentially colonized by Proteobacteria, Bacteroidetes and Actinobacteria, and each bacterial phylum is represented by a dominating class or family. Soil type defines the composition of root-inhabiting bacterial communities and host genotype determines their ribotype profiles to a limited extent. The identification of soil-type-specific members within the root-inhabiting assemblies supports our conclusion that these represent soil-derived root endophytes. Surprisingly, plant cell-wall features of other tested plant species seem to provide a sufficient cue for the assembly of approximately 40% of the Arabidopsis bacterial root-inhabiting microbiota, with a bias for Betaproteobacteria. Thus, this root sub-community may not be Arabidopsis -specific but saprophytic bacteria that would naturally be found on any plant root or plant debris in the tested soils. By contrast, colonization of Arabidopsis roots by members of the Actinobacteria depends on other cues from metabolically active host cells.

Background Frailty is a frequent and underdiagnosed functional syndrome involving reduced physiological reserves and an increased vulnerability against stressors, with severe individual and socioeconomic consequences. A routine frailty assessment was implemented at our preoperative anaesthesia clinic to identify patients at risk. Objective This study examines the relationship between frailty status and the incidence of in-hospital postoperative complications in elderly surgical patients across several surgical disciplines. Design Retrospective observational analysis. Setting Single center, major tertiary care university hospital. Data collection took place between June 2016 and March 2017. Patients Patients 65 years old or older were evaluated for frailty using Fried’s 5-point frailty assessment prior to elective non-cardiac surgery. Patients were classified into non-frail (0 criteria, reference group), pre-frail (1–2 positive criteria) and frail (3–5 positive criteria) groups. Main outcome measures The incidence of postoperative complications was assessed until discharge from the hospital, using the roster from the National VA Surgical Quality Improvement Program. Propensity score matching and logistic regression analysis were performed. Results From 1186 elderly patients, 46.9% were classified as pre-frail ( n  = 556), and 11.4% as frail ( n  = 135). The rate of complications were significantly higher in the pre-frail (34.7%) and frail groups (47.4%), as compared to the non-frail group (27.5%). Similarly, length of stay (non-frail: 5.0 [3.0;7.0], pre-frail: 7.0 [3.0;9.0], frail 8.0 [4.5;12.0]; p  < 0.001) and discharges to care facilities (non-frail:1.6%, pre-frail: 7.4%, frail: 17.8%); p < 0.001) were significantly associated with frailty status. After propensity score matching and logistic regression analysis, the risk for developing postoperative complications was approximately two-fold for pre-frail (OR 1.78; 95% CI 1.04–3.05) and frail (OR 2.08; 95% CI 1.21–3.60) patients. Conclusions The preoperative frailty assessment of elderly patients identified pre-frail and frail subgroups to have the highest rate of postoperative complications, regardless of age, surgical discipline, and surgical risk. Significantly increased length of hospitalisation and discharges to care facilities were also observed. Implementation of routine frailty assessments appear to be an effective tool in identifying patients with increased risk. Now future studies are needed to investigate whether patients benefit from optimization of patient counselling, process planning, and risk reduction protocols based on the application of risk stratification.

Background Marine microalgae (phytoplankton) mediate almost half of the worldwide photosynthetic carbon dioxide fixation and therefore play a pivotal role in global carbon cycling, most prominently during massive phytoplankton blooms. Phytoplankton biomass consists of considerable proportions of polysaccharides, substantial parts of which are rapidly remineralized by heterotrophic bacteria. We analyzed the diversity, activity, and functional potential of such polysaccharide-degrading bacteria in different size fractions during a diverse spring phytoplankton bloom at Helgoland Roads (southern North Sea) at high temporal resolution using microscopic, physicochemical, biodiversity, metagenome, and metaproteome analyses. Results Prominent active 0.2–3 µm free-living clades comprised Aurantivirga , “Formosa”, Cd . Prosiliicoccus, NS4, NS5, Amylibacter , Planktomarina , SAR11 Ia, SAR92, and SAR86, whereas BD1-7, Stappiaceae , Nitrincolaceae , Methylophagaceae , Sulfitobacter , NS9, Polaribacter , Lentimonas , CL500-3, Algibacter , and Glaciecola dominated 3–10 µm and > 10 µm particles. Particle-attached bacteria were more diverse and exhibited more dynamic adaptive shifts over time in terms of taxonomic composition and repertoires of encoded polysaccharide-targeting enzymes. In total, 305 species-level metagenome-assembled genomes were obtained, including 152 particle-attached bacteria, 100 of which were novel for the sampling site with 76 representing new species. Compared to free-living bacteria, they featured on average larger metagenome-assembled genomes with higher proportions of polysaccharide utilization loci. The latter were predicted to target a broader spectrum of polysaccharide substrates, ranging from readily soluble, simple structured storage polysaccharides (e.g., laminarin, α-glucans) to less soluble, complex structural, or secreted polysaccharides (e.g., xylans, cellulose, pectins). In particular, the potential to target poorly soluble or complex polysaccharides was more widespread among abundant and active particle-attached bacteria. Conclusions Particle-attached bacteria represented only 1% of all bloom-associated bacteria, yet our data suggest that many abundant active clades played a pivotal gatekeeping role in the solubilization and subsequent degradation of numerous important classes of algal glycans. The high diversity of polysaccharide niches among the most active particle-attached clades therefore is a determining factor for the proportion of algal polysaccharides that can be rapidly remineralized during generally short-lived phytoplankton bloom events. 9xVFsdNaK4F9f5nWnV_ZPh Video Abstract