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The first publication to consider the relationship between these two major artists of the High Renaissance. Through most of Michelangelo's working life, one of his closest colleagues was the great Venetian painter Sebastiano del Piombo (1485--1541). The two men met in Rome in 1511, shortly after Sebastiano's arrival from his native city, and while Michelangelo was based in Florence from 1516 to 1534 Sebastiano remained one of his Roman confidants, painting several works after partial designs by him. This landmark publication is about the artists' extraordinary professional alliance and the friendship that underpinned it. It situates them in the dramatic context of their time, tracing their evolving artistic relationship through more than three decades of creative dialogue. Matthias Wivel and other leading scholars investigate Michelangelo's profound influence on Sebastiano and the Venetian artist's highly original interpretation of his friend's formal and thematic concerns. The lavishly illustrated text examines their shared preoccupation with the depiction of death and resurrection, primarily in the life of Christ, through a close analysis of drawings, paintings, and sculpture. The book also brings the austerely beautiful work of Sebastiano to a new audience, offering a reappraisal of this less famous but most accomplished artist.

PCR-based methods to amplify the 3′ untranslated region (3′-UTR) of the heat shock protein 70 (type I) gene ( HSP70-I ) have previously been used for typing of Leishmania but not with Leishmania ( Mundinia ) martiniquensis and L . ( Mundinia ) orientalis , newly identified human pathogens. Here, the 3′-UTRs of HSP70-I of L . martiniquensis , L . orientalis , and 10 other species were sequenced and analyzed. PCR-Restriction Fragment Length Polymorphism (RFLP) analysis targeting the 3′-UTR of HSP70-I was developed. Also, the detection limit of HSP70-I -3′-UTR PCR methods was compared with two other commonly used targets: the 18S small subunit ribosomal RNA (SSU-rRNA) gene and the internal transcribed spacer 1 region of the rRNA (ITS1-rRNA) gene. Results showed that HSP70-I -3′-UTR PCR methods could be used to identify and differentiate between L . martiniquensis (480–2 bp) and L . orientalis (674 bp) and distinguished them from parasites of the subgenus Viannia and of the subgenus Leishmania . PCR-RFLP patterns of the 3′-UTR of HSP70-I fragments digested with Bsu RI restriction enzyme successfully differentiated L . martiniquensis , L . orientalis , L . braziliensis , L . guyanensis = L . panamensis , L . mexicana = L . aethiopica = L . tropica , L . amazonensis , L . major , and L . donovani = L . infantum . For the detection limit, the HSP70-I -3′-UTR PCR method could detect the DNA of L . martiniquensis and L . orientalis at the same concentration, 1 pg/μL, at a similar level to the SSU-rRNA PCR. The PCR that amplified ITS1-rRNA was more sensitive (0.01 pg/μL) than that of the HSP70-I -3′-UTR PCR. However, the sizes of both SSU-rRNA and ITS1-rRNA PCR amplicons could not differentiate between L . martiniquensis and L . orientalis . This is the first report of using HSP70-I -3′-UTR PCR based methods to identify the parasites causing leishmaniasis in Thailand. Also, the Bsu RI-PCR-RFLP method can be used for differentiating some species within other subgenera.

Since 1996, there have been several case reports of autochthonous visceral leishmaniasis in Thailand. Here we report a case in a 52-year-old Thai male from northern Thailand, who presented with subacute fever, huge splenomegaly and pancytopenia. Bone marrow aspiration revealed numerous amastigotes within macrophages. Isolation of Leishmania LSCM1 into culture and DNA sequence analysis (ribosomal RNA ITS-1 and large subunit of RNA polymerase II) revealed the parasites to be members of the Leishmania enriettii complex, and apparently identical to L. martiniquensis previously reported from the Caribbean island of Martinique. This is the first report of visceral leishmaniasis caused by L. martiniquensis from the region. Moreover, the majority of parasites previously identified as \"L. siamensis\" also appear to be L. martiniquensis.

Improvements in modelling power and input data have vastly improved the precision of physical flood models, but translation into economic outputs requires depth–damage functions that are inadequately verified. In particular, flood damage is widely assumed to increase monotonically with water depth. Here, we assess flood vulnerability in the US using >2 million claims from the National Flood Insurance Program (NFIP). NFIP claims data are messy, but the size of the dataset provides powerful empirical tests of damage patterns and modelling approaches. We show that current depth–damage functions consist of disparate relationships that match poorly with observations. Observed flood losses are not monotonic functions of depth, but instead better follow a beta function, with bimodal distributions for different water depths. Uncertainty in flood losses has been called the main bottleneck in flood risk studies, an obstacle that may be remedied using large-scale empirical flood damage data. Economic estimates of flood damages rely on depth–damage functions that are inadequately verified. Here, the authors assessed flood vulnerability in the US and found that current depth–damage functions consist of disparate relationships that match poorly with observations which better follow a bimodal beta distribution.

Current estimates of global flood exposure are made using datasets that distribute population counts homogenously across large lowland floodplain areas. When intersected with simulated water depths, this results in a significant mis-estimation. Here, we use new highly resolved population information to show that, in reality, humans make more rational decisions about flood risk than current demographic data suggest. In the new data, populations are correctly represented as risk-averse, largely avoiding obvious flood zones. The results also show that existing demographic datasets struggle to represent concentrations of exposure, with the total exposed population being spread over larger areas. In this analysis we use flood hazard data from a ~90 m resolution hydrodynamic inundation model to demonstrate the impact of different population distributions on flood exposure calculations for 18 developing countries spread across Africa, Asia and Latin America. The results suggest that many published large-scale flood exposure estimates may require significant revision. Flood risk modelling neglects the location of people and assets. Here the authors applied machine learning techniques and high-resolution population data to reinvestigate the impact of population distributions on flood exposure and showed that populations are generally represented as risk-averse and largely avoiding obvious flood zones.

Current flood risk mapping, relying on historical observations, fails to account for increasing threat under climate change. Incorporating recent developments in inundation modelling, here we show a 26.4% (24.1–29.1%) increase in US flood risk by 2050 due to climate change alone under RCP4.5. Our national depiction of comprehensive and high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5–33.8 billion) in 2020’s climate, which are borne disproportionately by poorer communities with a proportionally larger White population. The future increase in risk will disproportionately impact Black communities, while remaining concentrated on the Atlantic and Gulf coasts. Furthermore, projected population change (SSP2) could cause flood risk increases that outweigh the impact of climate change fourfold. These results make clear the need for adaptation to flood and emergent climate risks in the United States, with mitigation required to prevent the acceleration of these risks.Climate change is increasing flood risk, yet models based on historical data alone cannot capture the impact. Granular mapping of national flood risk shows that losses caused by flooding in the United States will increase substantially by 2050 and disproportionately burden less advantaged communities.

Significant uncertainties remain of how global change impacts on species richness, relative abundance and species composition. Recently, a discussion emerged on the importance of detecting and understanding long-term fluctuations in species composition and relative abundance and whether deterministic or non-deterministic factors can explain any temporal change. However, currently, one of the main impediments to providing answers to these questions is the relatively short time series of species diversity datasets. Many datasets are limited to 2 years and it is rare for a few decades of data to be available. In addition, long-term data typically has standardization issues from the past and/or the methods are not comparable. We address several of these uncertainties by investigating bird diversity in a globally important mountain ecosystem of the Hkakabo Razi Landscape in northern Myanmar. The study compares bird communities in two periods (pre-1940: 1900–1939 vs. post-2000: 2001–2006). Land-cover classes have been included to provide understanding of their potential role as drivers. While species richness did not change, species composition and relative abundance differed, indicating a significant species turn over and hence temporal change. Only 19.2% of bird species occurred during both periods. Land-cover model predictors explained part of the species richness variability but not relative abundance nor species composition changes. The temporal change is likely caused by minimal methodological differences and partially by land-cover.

This paper presents a new computationally efficient hydraulic model for simulating the spatially distributed dynamics of water surface elevation, wave speed, and inundation extent over large data sparse domains. The numerical scheme is based on an extension of the hydraulic model LISFLOOD‐FP to include a subgrid‐scale representation of channelized flows, which allows river channels with any width below that of the grid resolution to be simulated. The scheme is shown to be numerically stable and scalable, before being applied to an 800 km reach of the river Niger in Mali. The Niger application focused on the performance of four different model structures: a model without channels (two‐dimensional (2‐D) model), a model without a floodplain (one‐dimensional (1‐D) model), a model of the main channels and floodplain (1‐D/2‐D model), and the subgrid approach developed here. Inclusion of both the channel network and the floodplain was shown to be essential, meaning that large scale models of this region, including routing models for land surface schemes, will require a floodplain component. Including subgrid‐scale channels on the floodplain changed inundation dynamics over the delta significantly and increased simulation accuracy in terms of water level, wave propagation speed, and inundation extent. Furthermore, only the subgrid model showed a consistent parameterization when calibrated against either gauge or ICESat water level data, suggesting that connectivity provided by small channels is a strong control on the hydraulics of the floodplain, or, at the very least, that low resolution gridded hydraulic models require additional connectivity to represent the delta flow dynamics. Key Points A new sub‐grid hydraulic model was developed and evaluated The model was designed for application over large data sparse regions Assess the impact of small channels on the floodplain hydraulics

Past attempts to estimate rainfall-driven flood risk across the US either have incomplete coverage, coarse resolution or use overly simplified models of the flooding process. In this paper, we use a new 30 m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data. These flood depths are combined with exposure datasets of commensurate resolution to calculate current and future flood risk. Our data show that the total US population exposed to serious flooding is 2.6-3.1 times higher than previous estimates, and that nearly 41 million Americans live within the 1% annual exceedance probability floodplain (compared to only 13 million when calculated using FEMA flood maps). We find that population and GDP growth alone are expected to lead to significant future increases in exposure, and this change may be exacerbated in the future by climate change.

Vascular abnormalities contribute to many diseases such as cancer and diabetic retinopathy. In angiogenesis new blood vessels, headed by a migrating tip cell, sprout from pre-existing vessels in response to signals, e.g., vascular endothelial growth factor (VEGF). Tip cells meet and fuse (anastomosis) to form blood-flow supporting loops. Tip cell selection is achieved by Dll4-Notch mediated lateral inhibition resulting, under normal conditions, in an interleaved arrangement of tip and non-migrating stalk cells. Previously, we showed that the increased VEGF levels found in many diseases can cause the delayed negative feedback of lateral inhibition to produce abnormal oscillations of tip/stalk cell fates. Here we describe the development and implementation of a novel physics-based hierarchical agent model, tightly coupled to in vivo data, to explore the system dynamics as perpetual lateral inhibition combines with tip cell migration and fusion. We explore the tipping point between normal and abnormal sprouting as VEGF increases. A novel filopodia-adhesion driven migration mechanism is presented and validated against in vivo data. Due to the unique feature of ongoing lateral inhibition, 'stabilised' tip/stalk cell patterns show sensitivity to the formation of new cell-cell junctions during fusion: we predict cell fates can reverse. The fusing tip cells become inhibited and neighbouring stalk cells flip fate, recursively providing new tip cells. Junction size emerges as a key factor in establishing a stable tip/stalk pattern. Cell-cell junctions elongate as tip cells migrate, which is shown to provide positive feedback to lateral inhibition, causing it to be more susceptible to pathological oscillations. Importantly, down-regulation of the migratory pathway alone is shown to be sufficient to rescue the sprouting system from oscillation and restore stability. Thus we suggest the use of migration inhibitors as therapeutic agents for vascular normalisation in cancer.