Sensitivity of Surface Urban Energy and Water Balance Scheme (SUEWS) to downscaling of reanalysis forcing data

Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Peer reviewe

Cancer risk and mortality after solid organ transplantation : A population-based 30-year cohort study in Finland

Cancer is a significant cause of morbidity and mortality after solid organ transplantation (SOT) and related to lifelong immunosuppression. This retrospective registry study assessed for the first time in Finland population-based cancer risk and cancer mortality after all SOTs (lung and childhood transplantations included) as standardized incidence ratios (SIRs) and standardized mortality ratios (SMRs). Data from transplant registries were linked with the data of Finnish Cancer Registry and Statistics Finland. We followed 6548 consecutive first SOT recipients from 1 January 1987 to 31 December 2016 translating to 66 741 person-years (median follow-up time 8.9 years [interquartile range 4.0-15.1]). In total, 2096 cancers were found in 1483 patients (23% of all patients). Majority of cancers (53%) were nonmelanoma skin cancers (NMSCs). The overall SIR was 3.6 (95% confidence interval [CI]: 3.5-3.8) and the SIR excluding NMSCs was 2.2 (95% CI: 2.0-2.3). SIR for all cancers was highest for heart (5.0) and lowest for liver (2.7) recipients. Most common cancer types after NMSCs were non-Hodgkin lymphoma (NHL), SIR 9.9 (95% CI: 8.5-11.4) and kidney cancer, SIR 7.3 (95% CI: 6.0-8.8). Cancer-related deaths were 17% (n = 408) of all deaths after first month post transplantation. SMR for all cancers was 2.5 (95% CI: 2.2-2.7) and for NHL 13.6 (95% CI: 10.7-16.8). Notably, overall SIR for cancer was lower in later period (2000-2016), 3.0 (95% CI: 2.8-3.2), than in earlier period (1987-1999), 4.3 (95% CI: 4.0-4.5), P < .001. Decrease in cancer incidence was temporally associated with major changes in immunosuppression in the 2000s.Peer reviewe

Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach

The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012-2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 mu gm(-3)) into three sub-categories - low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) - proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ngm 3 h 1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-yearlong time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.Peer reviewe

Optical Monitoring of Microplastics Filtrated from Wastewater Sludge and Suspended in Ethanol

The abundance of microplastics (MPs) in the atmosphere, on land, and especially in water bodies is well acknowledged. In this study, we establish an optical method based on three different techniques, namely, specular reflection to probe the medium, transmission spectroscopy measurements for the detection and identification, and a speckle pattern for monitoring the sedimentation of MPs filtrated from wastewater sludge and suspended in ethanol. We used first Raman measurements to estimate the presence and types of different MPs in wastewater sludge samples. We also used microscopy to identify the shapes of the main MPs. This allowed us to create a teaching set of samples to be characterized with our optical method. With the developed method, we clearly show that MPs from common plastics, such as polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), and polyethylene (PE), are present in wastewater sludge and can be identified. Additionally, the results also indicate that the density of the plastics, which influences the sedimentation, is an essential parameter to consider in optical detection of microplastics in complex natural environments. All of the methods are in good agreement, thus validating the optics-based solution

A minor role of asparaginase in predisposing to cerebral venous thromboses in adult acute lymphoblastic leukemia patients

Cerebral venous thrombosis (CVT) covers up to a third of all venous thromboses (VTs) detected in patients with acute lymphoblastic leukemia (ALL). It usually hampers patients' lives and may also endanger efficient leukemia treatment. Although many factors have been suggested to account for an elevated risk of VTs in patients with ALL, there still is a lack of studies focusing on CVTs and especially in the setting of adult ALL patients. We studied in our retrospective population-based cohort the occurrence, characteristics, as well as risk factors for VTs in 186 consecutively diagnosed Finnish adult ALL patients treated with a national pediatric-inspired treatment protocol ALL2000. In the risk factor analyses for VTs we found a distinction of the characteristics of the patients acquiring CVT from those with other kinds of VTs or without thrombosis. In contrast to previous studies we were also able to compare the effects of asparaginase in relation to CVT occurrence. Notably, more than half of the CVTs were diagnosed prior the administration of asparaginase which accentuates the role of other risk factors on the pathophysiology of CVT compared to truncal or central venous line (CVL) VTs in adult ALL patients

Penumbral Rescue by normobaric O = O administration in patients with ischemic stroke and target mismatch proFile (PROOF): Study protocol of a phase IIb trial.

Oxygen is essential for cellular energy metabolism. Neurons are particularly vulnerable to hypoxia. Increasing oxygen supply shortly after stroke onset could preserve the ischemic penumbra until revascularization occurs. PROOF investigates the use of normobaric oxygen (NBO) therapy within 6 h of symptom onset/notice for brain-protective bridging until endovascular revascularization of acute intracranial anterior-circulation occlusion. Randomized (1:1), standard treatment-controlled, open-label, blinded endpoint, multicenter adaptive phase IIb trial. Primary outcome is ischemic core growth (mL) from baseline to 24 h (intention-to-treat analysis). Secondary efficacy outcomes include change in NIHSS from baseline to 24 h, mRS at 90 days, cognitive and emotional function, and quality of life. Safety outcomes include mortality, intracranial hemorrhage, and respiratory failure. Exploratory analyses of imaging and blood biomarkers will be conducted. Using an adaptive design with interim analysis at 80 patients per arm, up to 456 participants (228 per arm) would be needed for 80% power (one-sided alpha 0.05) to detect a mean reduction of ischemic core growth by 6.68 mL, assuming 21.4 mL standard deviation. By enrolling endovascular thrombectomy candidates in an early time window, the trial replicates insights from preclinical studies in which NBO showed beneficial effects, namely early initiation of near 100% inspired oxygen during short temporary ischemia. Primary outcome assessment at 24 h on follow-up imaging reduces variability due to withdrawal of care and early clinical confounders such as delayed extubation and aspiration pneumonia. ClinicalTrials.gov: NCT03500939; EudraCT: 2017-001355-31

Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019)

Plant cell culture technology in the cosmetics and food industries : current state and future trends

The production of drugs, cosmetics, and food which are derived from plant cell and tissue cultures has a long tradition. The emerging trend of manufacturing cosmetics and food products in a natural and sustainable manner has brought a new wave in plant cell culture technology over the past 10 years. More than 50 products based on extracts from plant cell cultures have made their way into the cosmetics industry during this time, whereby the majority is produced with plant cell suspension cultures. In addition, the first plant cell culture-based food supplement ingredients, such as Echigena Plus and Teoside 10, are now produced at production scale. In this mini review, we discuss the reasons for and the characteristics as well as the challenges of plant cell culture-based productions for the cosmetics and food industries. It focuses on the current state of the art in this field. In addition, two examples of the latest developments in plant cell culture-based food production are presented, that is, superfood which boosts health and food that can be produced in the lab or at home

“It was Pretty Scary”: The Theme of Fear in Young Adult Women's Descriptions of a History of Adolescent Dating Abuse

The mental health impact of abusive adolescent dating relationships has not been well described, but fear related to abuse has been reported. We elaborate the theme of fear in women's descriptions of a history of adolescent dating abuse. A sample of community-based women, ages 19-34, who experienced an abusive dating relationship during adolescence (ages 11-20) was used. Data were analyzed via thematic analysis. Fear was a consistent and resonant theme. Three types of fear were identified: fear for self, fear for other relationships, and fearful expectation. These results offer important insights into the impact of abusive adolescent relationships on women's mental health