Diurnal variability of atmospheric O-2, CO2, and their exchange ratio above a boreal forest in southern Finland

The exchange ratio (ER) between atmospheric O(2 )and CO2 is a useful tracer for better understanding the carbon budget on global and local scales. The variability of ER (in mol O(2 )per mol CO2) between terrestrial ecosystems is not well known, and there is no consensus on how to derive the ER signal of an ecosystem, as there are different approaches available, either based on concentration (ERatmos) or flux measurements (ERforest). In this study we measured atmospheric O-2 and CO2 concentrations at two heights (23 and 125 m) above the boreal forest in Hyytiala, Finland. Such measurements of O-2 are unique and enable us to potentially identify which forest carbon loss and production mechanisms dominate over various hours of the day. We found that the ERatmos signal at 23 m not only represents the diurnal cycle of the forest exchange but also includes other factors, including entrainment of air masses in the atmospheric boundary layer before midday, with different thermodynamic and atmospheric composition characteristics. To derive ERforest, we infer O(2 )fluxes using multiple theoretical and observation-based micro-meteorological formulations to determine the most suitable approach. Our resulting ERforest shows a distinct difference in behaviour between daytime (0.92 +/- 0.17 mol mol(-1)) and nighttime (1.03 +/- 0.05 mol mol(-1)). These insights demonstrate the diurnal variability of different ER signals above a boreal forest, and we also confirmed that the signals of ERatmos and ERforest cannot be used interchangeably. Therefore, we recommend measurements on multiple vertical levels to derive O-2 and CO2 fluxes for the ERforest signal instead of a single level time series of the concentrations for the ERatmos signal. We show that ERforest can be further split into specific signals for respiration (1.03 +/-; 0.05 mol mol-1) and photosynthesis (0.96 +/- 0.12 molmol(-1)). This estimation allows us to separate the net ecosystem exchange (NEE) into gross primary production (GPP) and total ecosystem respiration (TER), giving comparable results to the more commonly used eddy covariance approach. Our study shows the potential of using atmospheric O-2 as an alternative and complementary method to gain new insights into the different CO2 signals that contribute to the forest carbon budget.Peer reviewe

Near real-time CO₂ fluxes from CarbonTracker Europe for high resolution atmospheric modeling

We present the CarbonTracker Europe High-Resolution system that estimates carbon dioxide (CO2) exchange over Europe at high-resolution (0.1 x 0.2°) and in near real-time (about 2 months latency). It includes a dynamic fossil fuel emission model, which uses easily available statistics on economic activity, energy-use, and weather to generate fossil fuel emissions with dynamic time profiles at high spatial and temporal resolution (0.1 x 0.2°, hourly). Hourly net biosphere exchange (NEE) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEE is downscaled to 0.1 x 0.2° using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map, and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. An ocean flux extrapolation and downscaling based on wind speed and temperature for Jena CarboScope ocean CO2 fluxes is included in our product. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe. We assess the ability of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 drought, (b) to capture the reduction of fossil fuel emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ERA5, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city centre of Amsterdam (The Netherlands). We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and fossil fuel emissions (COVID-19 pandemic in 2020). After transport with TM5, the CTE-HR fluxes have lower root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor-person inversion). RSMEs are close to those of the reanalysis with the data assimilation system CarbonTracker Europe (CTE). This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE. We furthermore compare CO2 observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different sectors in summer and winter. Interestingly, in periods where synoptic scale transport variability dominates CO2 variations, the CTE-HR fluxes perform similar to low-resolution fluxes (5–10x coarsened). The remaining 10 % of simulated CO2 mole fraction differ by > 2ppm between the low-resolution and high-resolution flux representation, and are clearly associated with coherent structures ("plumes") originating from emission hotspots, such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely-populated region like the Amsterdam city centre, our fluxes underestimate the magnitude of measured eddy-covariance fluxes, but capture their substantial diurnal variations in summer- and wintertime well. We conclude that our product is a promising tool to model the European carbon budget at a high-resolution in near real-time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near real-time monitoring and modeling, for example as a-priori flux product in a CO2 data-assimilation system. The data is available at https://doi.org/10.18160/20Z1-AYJ2

Rapid assessment of regional SARS-CoV-2 community transmission through a convenience sample of healthcare workers, the Netherlands, March 2020

To rapidly assess possible community transmission in Noord-Brabant, the Netherlands, healthcare workers (HCW) with mild respiratory complaints and without epidemiological link (contact with confirmed case or visited areas with active

Lymphovascular invasion quantification could improve risk prediction of lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma

AIM: To quantify lymphovascular invasion (LVI) and to assess the prognostic value in patients with pT1b esophageal adenocarcinoma. METHODS: In this nationwide, retrospective cohort study, patients were included if they were treated with surgery or endoscopic resection for pT1b esophageal adenocarcinoma. Primary endpoint was the presence of metastases, lymph node metastases, or distant metastases, in surgical resection specimens or during follow‐up. A prediction model to identify risk factors for metastases was developed and internally validated. RESULTS: 248 patients were included. LVI was distributed as follows: no LVI (n = 196; 79.0%), 1 LVI focus (n = 16; 6.5%), 2–3 LVI foci (n = 21; 8.5%) and ≥4 LVI foci (n = 15; 6.0%). Seventy‐eight patients had metastases. The risk of metastases was increased for tumors with 2–3 LVI foci [subdistribution hazard ratio (SHR) 3.39, 95% confidence interval (CI) 2.10–5.47] and ≥4 LVI foci (SHR 3.81, 95% CI 2.37–6.10). The prediction model demonstrated a good discriminative ability (c‐statistic 0.81). CONCLUSION: The risk of metastases is higher when more LVI foci are present. Quantification of LVI could be useful for a more precise risk estimation of metastases. This model needs to be externally validated before implementation into clinical practice

The Peripheral Arterial disease study (PERART/ARTPER): prevalence and risk factors in the general population

<p>Abstract</p> <p>Background</p> <p>The early diagnosis of atherosclerotic disease is essential for developing preventive strategies in populations at high risk and acting when the disease is still asymptomatic. A low ankle-arm index is a good marker of vascular events and may be diminished without presenting symptomatology (silent peripheral arterial disease). The aim of the study is to know the prevalence and associated risk factors of peripheral arterial disease in the general population.</p> <p>Methods</p> <p>We performed a cross-sectional, multicentre, population-based study in 3786 individuals >49 years, randomly selected in 28 primary care centres in Barcelona (Spain). Peripheral arterial disease was evaluated using the ankle-arm index. Values < 0.9 were considered as peripheral arterial disease.</p> <p>Results</p> <p>The prevalence (95% confidence interval) of peripheral arterial disease was 7.6% (6.7-8.4), (males 10.2% (9.2-11.2), females 5.3% (4.6-6.0); <it>p </it>< 0.001).</p> <p>Multivariate analysis showed the following risk factors: male sex [odds ratio (OR) 1.62; 95% confidence interval 1.01-2.59]; age OR 2.00 per 10 years (1.64-2.44); inability to perform physical activity [OR 1.77 (1.17-2.68) for mild limitation to OR 7.08 (2.61-19.16) for breathless performing any activity]; smoking [OR 2.19 (1.34-3.58) for former smokers and OR 3.83 (2.23-6.58) for current smokers]; hypertension OR 1.85 (1.29-2.65); diabetes OR 2.01 (1.42-2.83); previous cardiovascular disease OR 2.19 (1.52-3.15); hypercholesterolemia OR 1.55 (1.11-2.18); hypertriglyceridemia OR 1.55 (1.10-2.19). Body mass index ≥25 Kg/m²OR 0.57 (0.38-0.87) and walking >7 hours/week OR 0.67 (0.49-0.94) were found as protector factors.</p> <p>Conclusions</p> <p>The prevalence of peripheral arterial disease is low, higher in males and increases with age in both sexes. In addition to previously described risk factors we found a protector effect in physical exercise and overweight.</p

CT angiography and CT perfusion improve prediction of infarct volume in patients with anterior circulation stroke

Introduction: We investigated whether baseline CT angiography (CTA) and CT perfusion (CTP) in acute ischemic stroke could improve prediction of infarct presence and infarct volume on follow-up imaging. Methods: We analyzed 906 patients with suspected anterior circulation stroke from the prospective multicenter Dutch acute stroke study (DUST). All patients underwent baseline non-contrast CT, CTA, and CTP and follow-up non-contrast CT/MRI after 3 days. Multivariable regression models were developed including patient characteristics and non-contrast CT, and subsequently, CTA and CTP measures were added. The increase in area under the curve (AUC) and R2 was assessed to determine the additional value of CTA and CTP. Results: At follow-up, 612 patients (67.5 %) had a detectable infarct on CT/MRI; median infarct volume was 14.8 mL (interquartile range (IQR) 2.8–69.6). Regarding infarct presence, the AUC of 0.82 (95 % confidence interval (CI) 0.79–0.85) for patient characteristics and non-contrast CT was improved with addition of CTA measures (AUC 0.85 (95 % CI 0.82–0.87); p < 0.001) and was even higher after addition of CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001) and combined CTA/CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001). For infarct volume, adding combined CTA/CTP measures (R2 = 0.58) was superior to patient characteristics and non-contrast CT alone (R2 = 0.44) and to addition of CTA alone (R2 = 0.55) or CTP alone (R2 = 0.54; all p < 0.001). Conclusion: In the acute stage, CTA and CTP have additional value over patient characteristics and non-contrast CT for predicting infarct presence and infarct volume on follow-up imaging. These findings could be applied for patient selection in future trials on ischemic stroke treatment

Individual risk calculator to predict lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma:a multicenter cohort study

Background Lymph node metastasis (LNM) is possible after endoscopic resection of early esophageal adenocarcinoma (EAC). This study aimed to develop and internally validate a prediction model that estimates the individual risk of metastases in patients with pT1b EAC. Methods A nationwide, retrospective, multicenter cohort study was conducted in patients with pT1b EAC treated with endoscopic resection and/or surgery between 1989 and 2016. The primary end point was presence of LNM in surgical resection specimens or detection of metastases during follow-up. All resection specimens were histologically reassessed by specialist gastrointestinal pathologists. Subdistribution hazard regression analysis was used to develop the prediction model. The discriminative ability of this model was assessed using the c-statistic. Results 248 patients with pT1b EAC were included. Metastases were seen in 78 patients, and the 5-year cumulative incidence was 30.9 % (95 % confidence interval [CI] 25.1 %-36.8 %). The risk of metastases increased with submucosal invasion depth (subdistribution hazard ratio [SHR] 1.08, 95 %CI 1.02-1.14, for every increase of 500 μm), lymphovascular invasion (SHR 2.95, 95 %CI 1.95-4.45), and for larger tumors (SHR 1.23, 95 %CI 1.10-1.37, for every increase of 10 mm). The model demonstrated good discriminative ability (c-statistic 0.81, 95 %CI 0.75-0.86). Conclusions A third of patients with pT1b EAC experienced metastases within 5 years. The probability of developing post-resection metastases was estimated with a personalized predicted risk score incorporating tumor invasion depth, tumor size, and lymphovascular invasion. This model requires external validation before implementation into clinical practice

Prediction of outcome in patients with suspected acute ischaemic stroke with CT perfusion and CT angiography: The Dutch acute stroke trial (DUST) study protocol

Background: Prediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated.Methods/design: The DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0-2 represents good outcome, and a score of 3-6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests.Discussion: This study will provide insight in the added prognosti

Temporal profile of body temperature in acute ischemic stroke: Relation to infarct size and outcome

Background: High body temperatures after ischemic stroke have been associated with larger infarct size, but the temporal profile of this relation is unknown. We assess the relation between temporal profile of body temperature and infarct size and functional outcome in patients with acute ischemic stroke. Methods: In 419 patients with acute ischemic stroke we assessed the relation between body temperature on admission and during the first 3 days with both infarct size and functional outcome. Infarct size was measured in milliliters on CT or MRI after 3 days. Poor functional outcome was defined as a modified Rankin Scale score ≥3 at 3 months. Results: Body temperature on admission was not associated with infarct size or poor outcome in adjusted analyses. By contrast, each additional 1.0 °C in body temperature on day 1 was associated with 0.31 ml larger infarct size (95% confidence interval (CI) 0.04-0.59), on day 2 with 1.13 ml larger infarct size(95% CI, 0.83-1.43), and on day 3 with 0.80 ml larger infarct size (95% CI, 0.48-1.12), in adjusted linear regression analyses. Higher peak body temperatures on days two and three were also associated with poor outcome (adjusted relative risks per additional 1.0 °C in body temperature, 1.52 (95% CI, 1.17-1.99) and 1.47 (95% CI, 1.22-1.77), respectively). Conclusions: Higher peak body temperatures during the first days after ischemic stroke, rather than on admission, are associated with larger infarct size and poor functional outcome. This suggests that prevention of high temperatures may improve outcome if continued for at least 3 days