63 research outputs found

    Histopathological diagnosis of Japanese spotted fever using formalin-fixed, paraffin-embedded skin biopsy specimens Usefulness of immunohistochemistry and real-time PCR analysis

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    AbstractJapanese spotted fever (JSF) is caused by Rickettsia japonica, and lethal cases are reported yearly in southwest Japan. We thus established the method of diagnosing JSF by immunohistochemistry (IHC) and real-time PCR (RT-PCR) using formalin-fixed, paraffin-embedded skin biopsy specimens. Two monoclonal antibodies were used for IHC, and the 17k genus common antigen gene served as the target of RT-PCR. We collected skin biopsy (n = 61) and autopsy (n = 1) specimens from 50 patients clinically suspected of JSF. Immunohistochemically, the rickettsial antigens were localized as coarse dots in the cytoplasm of endothelial cells and macrophages. Thirty-one seropositive cases plus one autopsy case (group A) and nine seronegative cases but with positive IHC and/or RT-PCR (group B) were judged as JSF. Nine cases were regarded as non-JSF disorders based on negative serology, IHC and RT-PCR (group C). Of 50 biopsies (eschar 34, eruptions 10, and scabs 6) from groups A and B, IHC and RT-PCR positivities were 94% (32/34) and 62% (21/34) for eschar, 80% (8/10) and 30% (3/10) for eruptions, and 33% (2/6) and 50% (3/6) for scabs. For IHC, eschar was most suitable, and scabs were insufficient. Unexpectedly, 18 biopsies happened to be fixed in 100% formalin, and this lowered the detection rate by RT-PCR, but IHC was tolerant. Sequence analysis using five skin biopsy specimens confirmed a 114 bp DNA stretch homologous to that reported for the target gene of R. japonica. In 26 (84%) of the 31 seropositive patients, the diagnosis was made by IHC and/or RT-PCR earlier than serology

    Emission pathways to achieve 2.0°C and 1.5°C climate targets

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    We investigated the feasibilities of 2.0°C and 1.5°C climate targets by considering the abatement potentials of a full suite of greenhouse gases, pollutants, and aerosols. We revised the inter-temporal dynamic optimization model DICE-2013R by introducing three features as follows. First, we applied a new marginal abatement cost curve derived under moderate assumptions regarding future socioeconomic development—the Shared Socioeconomic Pathways 2 (SSP2) scenario. Second, we addressed emission abatement for not only industrial CO2 but also land-use CO2, CH4, N2O, halogenated gases, CO, volatile organic compounds, SOx, NOx, black carbon and organic carbon. Third, we improved the treatment of the non-CO2 components in the climate module based on MAGICC 6.0. We obtained the following findings: (1) It is important to address the individual emissions in an analysis of low stabilization scenarios because abating land-use CO2, non-CO2 and aerosol emissions also contributes to maintaining a low level of radiative forcing and substantially affects the climate costs. (2) The 2.0°C target can be efficiently reached under the assumptions of the SSP2 scenario. (3) The 1.5°C target can be met with early deep cuts under the assumption of a temperature overshoot, and it will triple the carbon price and double the mitigation cost compared with the 2.0°C case

    How do climate-related uncertainties influence 2 and 1.5 °C pathways?

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    We investigate how uncertainties in key parameters in the carbon cycle and climate system propagate to the costs of climate change mitigation and adaptation needed to achieve the 2 and 1.5 °C targets by 2100 using a stochastic version of the simple climate model for optimization (SCM4OPT), an integrated assessment model. For the 2 °C target, we find a difference in 2100 CO2 emission levels of 20.5 GtCO2 (− 1.2 GtCO2 to 19.4 GtCO2), whereas this difference is 12.0 GtCO2 (− 6.9 GtCO2 to 5.1 GtCO2) for the 1.5 °C target (17–83% range). Total radiative forcing in 2100 is estimated to be 3.3 (2.7–3.9) Wm−2 for the 2 °C case and 2.5 (2.0–3.0) Wm−2 for the 1.5 °C case. Carbon prices in 2100 are 482 (181–732) USD(2005)/tCO2 and 713 (498–1014) USD(2005)/tCO2 for the 2 and 1.5 °C targets, respectively. We estimate GDP losses in 2100 that correspond to 1.9 (1.2–2.5)% of total gross output for the 2 °C target and 2.0 (1.5–2.7)% for the 1.5 °C target

    Impact of bioenergy crop expansion on climate–carbon cycle feedbacks in overshoot scenarios

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    Stringent mitigation pathways frame the deployment of second-generation bioenergy crops combined with carbon capture and storage (CCS) to generate negative CO2 emissions. This bioenergy with CCS (BECCS) technology facilitates the achievement of the long-term temperature goal of the Paris Agreement. Here, we use five state-of-the-art Earth system models (ESMs) to explore the consequences of large-scale BECCS deployment on the climate–carbon cycle feedbacks under the CMIP6 SSP5-3.4-OS overshoot scenario keeping in mind that all these models use generic crop vegetation to simulate BECCS. First, we evaluate the land cover representation by ESMs and highlight the inconsistencies that emerge during translation of the data from integrated assessment models (IAMs) that are used to develop the scenario. Second, we evaluate the land-use change (LUC) emissions of ESMs against bookkeeping models. Finally, we show that an extensive cropland expansion for BECCS causes ecosystem carbon loss that drives the acceleration of carbon turnover and affects the CO2 fertilization effect- and climate-change-driven land carbon uptake. Over the 2000–2100 period, the LUC for BECCS leads to an offset of the CO2 fertilization effect-driven carbon uptake by 12.2 % and amplifies the climate-change-driven carbon loss by 14.6 %. A human choice on land area allocation for energy crops should take into account not only the potential amount of the bioenergy yield but also the LUC emissions, and the associated loss of future potential change in the carbon uptake. The dependency of the land carbon uptake on LUC is strong in the SSP5-3.4-OS scenario, but it also affects other Shared Socioeconomic Pathway (SSP) scenarios and should be taken into account by the IAM teams. Future studies should further investigate the trade-offs between the carbon gains from the bioenergy yield and losses from the reduced CO2 fertilization effect-driven carbon uptake where BECCS is applied

    A comparison of bioclimatic conditions on Franz Josef Land (the Arctic) between the turn of the nineteenth to twentieth century and present day

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    The paper presents the variability of meteorological conditions: air temperature, wind speed and relative air humidity; and biometeorological indices: wind chill temperature, predicted clothing insulation and accepted level of physical activity on Franz Josef Land (in Teplitz Bay and Calm Bay) in the years 1899–1931. It employs meteorological measurements taken during four scientific expeditions to the study area. The analysis mainly covered the period October–April, for which the most complete data set is available. For that period of the year, which includes the part of the year with the Franz Josef Land’s coldest air temperatures, the range and nature of changes in meteorological and biometeorological conditions between historical periods and the modern period (1981–2010) were studied. The data analysis revealed that during the three oldest expeditions (which took place in the years 1899–1914), the biometeorological conditions in the study area were more harsh to humans than in the modern period (1981–2010) or similarly harsh. In contrast, during the 1930/1931 expedition, which represents the Early Twentieth CenturyWarming (ETCW), conditions were clearly more favourable (including predicted clothing insulation being 0.3 clo lower and 4.0 °C higher wind chill temperature than conditions observed nowadays)

    The timing of unprecedented hydrological drought under climate change

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    Droughts that exceed the magnitudes of historical variation ranges could occur increasingly frequently under future climate conditions. However, the time of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and existing water resource management measures and estimate the time of the first emergence of unprecedented regional drought conditions centered on the low-flow season. The times are detected for several subcontinental-scale regions, and three regions, namely, Southwestern South America, Mediterranean Europe, and Northern Africa, exhibit particularly robust results under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. However, appropriate and prior adaptation measures are considered indispensable when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons

    Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

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    The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way
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