79 research outputs found

    (E)-2-[2-(4-Chloro­benzyl­idene)hydrazin­yl]-4-[3-(morpholin-4-ium-4-yl)propyl­amino]­quinazolin-1-ium bis­(perchlorate)

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    In the title compound, C22H27ClN6O2 2+·2ClO4 −, the mol­ecule adopts an E conformation about the C=N double bond. The quinazoline ring is approximately planar, with an r.m.s. deviation of 0.0432 Å, and forms a dihedral angle of 5.77 (4)° with the chloro­phenyl ring. The crystal packing features N—H⋯O hydrogen bonds

    Fusion of Hsp70 to Mage-a1 enhances the potency of vaccine-specific immune responses

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    Mapping winter wheat with combinations of temporally aggregated Sentinel-2 and Landsat-8 data in Shandong Province, China

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    Winter wheat is one of the major cereal crops in China. The spatial distribution of winter wheat planting areas is closely related to food security; however, mapping winter wheat with time-series finer spatial resolution satellite images across large areas is challenging. This paper explores the potential of combining temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data available via the Google Earth Engine (GEE) platform for mapping winter wheat in Shandong Province, China. First, six phenological median composites of Landsat-8 OLI and Sentinel-2 MSI reflectance measures were generated by a temporal aggregation technique according to the winter wheat phenological calendar, which covered seedling, tillering, over-wintering, reviving, jointing-heading and maturing phases, respectively. Then, Random Forest (RF) classifier was used to classify multi-temporal composites but also mono-temporal winter wheat development phases and mono-sensor data. The results showed that winter wheat could be classified with an overall accuracy of 93.4% and F1 measure (the harmonic mean of producer’s and user’s accuracy) of 0.97 with temporally aggregated Landsat-8 and Sentinel-2 data were combined. As our results also revealed, it was always good to classify multi-temporal images compared to mono-temporal imagery (the overall accuracy dropped from 93.4% to as low as 76.4%). It was also good to classify Landsat-8 OLI and Sentinel-2 MSI imagery combined instead of classifying them individually. The analysis showed among the mono-temporal winter wheat development phases that the maturing phase’s and reviving phase’s data were more important than the data for other mono-temporal winter wheat development phases. In sum, this study confirmed the importance of using temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data combined and identified key winter wheat development phases for accurate winter wheat classification. These results can be useful to benefit on freely available optical satellite data (Landsat-8 OLI and Sentinel-2 MSI) and prioritize key winter wheat development phases for accurate mapping winter wheat planting areas across China and elsewhere

    External α-carbonic anhydrase and solute carrier 4 are required for bicarbonate uptake in a freshwater angiosperm

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    The freshwater monocot Ottelia alismoides is the only known species to operate three CO2-concentrating mechanisms (CCMs): constitutive bicarbonate (HCO3–) use, C4 photosynthesis, and facultative Crassulacean acid metabolism, but the mechanism of HCO3– use is unknown. We found that the inhibitor of an anion exchange protein, 4,4'-diisothio-cyanatostilbene-2,2'-disulfonate (DIDS), prevented HCO3– use but also had a small effect on CO2 uptake. An inhibitor of external carbonic anhydrase (CA), acetazolamide (AZ), reduced the affinity for CO2 uptake but also prevented HCO3– use via an effect on the anion exchange protein. Analysis of mRNA transcripts identified a homologue of solute carrier 4 (SLC4) responsible for HCO3– transport, likely to be the target of DIDS, and a periplasmic α-carbonic anhydrase 1 (α-CA1). A model to quantify the contribution of the three different pathways involved in inorganic carbon uptake showed that passive CO2 diffusion dominates inorganic carbon uptake at high CO2 concentrations. However, as CO2 concentrations fall, two other pathways become predominant: conversion of HCO3– to CO2 at the plasmalemma by α-CA1 and transport of HCO3– across the plasmalemma by SLC4. These mechanisms allow access to a much larger proportion of the inorganic carbon pool and continued photosynthesis during periods of strong carbon depletion in productive ecosystems

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    The effect of organic matter type on formation and evolution of diamondoids

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    A series of anhydrous pyrolysis experiments, using sealed gold tubes, were performed on three types of kerogen to investigate the effect organic matter type has on the generation and evolution of thermogenic diamondoids. Based on, the compositional variation of pyrolysis products, the cracking of kerogens can be divided into three stages: oil generation (0.6%4.5% EasyRo), wet-gas generation (1.5%-2.1% EasyRo) and dry-gas generation ( > 2.1% EasyRo). The experimental results indicate that diamondoids were mainly generated in the oil and wet gas generation stages and decomposed in the dry-gas generation stage. In addition to thermal maturity, the formation of diamondoids is also influenced by the type of organic matter. Type I and IIA kerogens produced more diamondoids than Type III kerogen, and diamondoids generated from Type III kerogen were dominantly adamantanes. Therefore, the concentration and concentration ratios of diamondoids can be used to assess the maturity of source rocks (1.0%-1.5% EasyRo) and determine the type of organic matter (1.0%-2.0% EasyRo). Isomerization ratios of diamondoids depend mainly on thermal maturity and the type of organic matter has little effect. The use of isomerization ratios to determine thermal maturity is best for source rocks at higher maturity levels (1.50/0-3.0% EasyRo). Therefore, bivariate diagrams of concentration versus isomerization indices of diamondoids (e.g., DMAs/MDs vs. DMAI-1 and DMAs/MDs vs. TMAI-1) can be used to evaluate the source rock maturity over a wider EasyRo range (1.0%-3.0% EasyRo) than single diamondoid parameters. As there are differences in the concentration and distribution of diamondoids in the extracts of three source rocks, the possibility exists to use diamondoid indices of immature rocks to determine the type of source rock

    Source and thermal maturity of crude oils in the Junggar Basin in northwest China determined from the concentration and distribution of diamondoids

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    Here we discuss three types of diamondoid parameters for oils from the Junggar Basin. These are: absolute concentrations, concentration ratios, and isomerization ratios. According to the absolute diamondoid concentrations, the oils collected from different areas of the basin were broadly divided into three maturity stages: (1) low-mature (1000 ppm adamantanes; >50 ppm diamantanes). The oils in the northwestern region of the Junggar Basin are in the low-mature to mature stages. Based on a combination of diamondoid concentration ratios and biomarker indices, these oils can be divided into three groups, i.e., Group I oils in the Wuxia Zone derived from the lower Permian Fengcheng Formation (P-1f), Group II oils in the Kebai Zone sourced from middle Permian Lower Wuerhe Formation (P-2w), and Group III oils in the Mahu Depression generated from more mature source rocks of Jiamuhe Formation (P-1j) or the P-1f. Diamondoid concentrations and isomerization ratios were used to precisely evaluate the thermal maturity of mature oils and highly mature condensates, respectively. Our results indicate that the oils in the central part of the basin have decreasing thermal maturity from south to north, whereas the oils in the Kelameili area display increasing thermal maturity from east to west. In this study we found that different diamondoid indices are useful only in certain thermal maturity ranges. Therefore, at least for the Junggar Basin, it is crucial to know which thermal region one is in before using diamondoid ratios for maturity assessment. (C) 2019 Elsevier Ltd. All rights reserved
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