Questions of quality: the Danish State Serum Institute, Thorvald Madsen and biological standardisation

The opening of the Danish State Serum Institute (SSI) in Copenhagen on 9 September 1902 was a festive occasion, attended by renowned figures from the wider bacteriological community including the German scientists Paul Ehrlich, Carl Weigert, and Julius Morgenroth, future Nobel prize-winner Svante Arrhenius from Sweden, Ole Malm and Armauer Hansen from Norway, and William Bulloch and German Sims Woodhead from England.1 Established as a national resource for the production of diphtheria antitoxin, the SSI was from its inception concerned to deliver a quality product at a minimum price, and to link pharmaceutical production with research into, and further development of, biological products. In the course of the twentieth century, the institute acquired an international reputation for the quality of its products and its cutting edge research, and, in the 1920s, achieved international authority as the League of Nations Health Commission’s central laboratory for the preservation and distribution of all standard sera and bacterial products.2 The rise of the SSI to international prominence came about through a combination of factors, personal, scientific and political, but above all, perhaps, from its early association with questions of quality in the production of the new generation biological medicines, of which diphtheria antitoxin was the first to emerge

Multimorbidity and survival for patients with acute myocardial infarction in England and Wales: Latent class analysis of a nationwide population-based cohort

Background: There is limited knowledge of the scale and impact of multimorbidity for patients who have had an acute myocardial infarction (AMI). Therefore, this study aimed to determine the extent to which multimorbidity is associated with long-term survival following AMI. Methods and findings: This national observational study included 693,388 patients (median age 70.7 years, 452,896 [65.5%] male) from the Myocardial Ischaemia National Audit Project (England and Wales) who were admitted with AMI between 1 January 2003 and 30 June 2013. There were 412,809 (59.5%) patients with multimorbidity at the time of admission with AMI, i.e., having at least 1 of the following long-term health conditions: diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, cerebrovascular disease, peripheral vascular disease, or hypertension. Those with heart failure, renal failure, or cerebrovascular disease had the worst outcomes (39.5 [95% CI 39.0–40.0], 38.2 [27.7–26.8], and 26.6 [25.2–26.4] deaths per 100 person-years, respectively). Latent class analysis revealed 3 multimorbidity phenotype clusters: (1) a high multimorbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2) a medium multimorbidity class, with peripheral vascular disease and hypertension, and (3) a low multimorbidity class. Patients in class 1 were less likely to receive pharmacological therapies compared with class 2 and 3 patients (including aspirin, 83.8% versus 87.3% and 87.2%, respectively; β-blockers, 74.0% versus 80.9% and 81.4%; and statins, 80.6% versus 85.9% and 85.2%). Flexible parametric survival modelling indicated that patients in class 1 and class 2 had a 2.4-fold (95% CI 2.3–2.5) and 1.5-fold (95% CI 1.4–1.5) increased risk of death and a loss in life expectancy of 2.89 and 1.52 years, respectively, compared with those in class 3 over the 8.4-year follow-up period. The study was limited to all-cause mortality due to the lack of available cause-specific mortality data. However, we isolated the disease-specific association with mortality by providing the loss in life expectancy following AMI according to multimorbidity phenotype cluster compared with the general age-, sex-, and year-matched population. Conclusions: Multimorbidity among patients with AMI was common, and conferred an accumulative increased risk of death. Three multimorbidity phenotype clusters that were significantly associated with loss in life expectancy were identified and should be a concomitant treatment target to improve cardiovascular outcomes

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl

Spatial and temporal variability of nitrous oxide emissions in a mixed farming landscape of Denmark

Nitrous oxide (N<sub>2</sub>O) emissions from agricultural land are variable at the landscape scale due to variability in land use, management, soil type, and topography. A field experiment was carried out in a typical mixed farming landscape in Denmark, to investigate the main drivers of variations in N<sub>2</sub>O emissions, measured using static chambers. Measurements were made over a period of 20 months, and sampling was intensified during two weeks in spring 2009 when chambers were installed at ten locations or fields to cover different crops and topography and slurry was applied to three of the fields. N<sub>2</sub>O emissions during spring 2009 were relatively low, with maximum values below 20 ng N m<sup>−2</sup> s<sup>−1</sup>. This applied to all land use types including winter grain crops, grasslands, meadows, and wetlands. Slurry application to wheat fields resulted in short-lived two-fold increases in emissions. The moderate N<sub>2</sub>O fluxes and their moderate response to slurry application were attributed to dry soil conditions due to the absence of rain during the four previous weeks. Cumulative annual emissions from two arable fields that were both fertilized with mineral fertilizer and manure were large (17 kg N<sub>2</sub>O-N ha<sup>−1</sup> yr<sup>−1</sup> and 5.5 kg N<sub>2</sub>O-N ha<sup>−1</sup> yr<sup>−1</sup>) during the previous year when soil water conditions were favourable for N<sub>2</sub>O production during the first month following fertilizer application. Our findings confirm the importance of weather conditions as well as nitrogen management on N<sub>2</sub>O fluxes

Remote sensing based mapping of leaf nitrogen and leaf area index in European landscapes using the REGularized canopy reFLECtance (REGFLEC) model

Mapping was conducted using the REGFLEC model which is an automatic and image-based methodology developed for regional chlorophyll (Cab) and LAI estimation (i.e., Houborg et al., 2007; Houborg and Boegh, 2008; Houborg and Andersen, JARS 3, 2009). REGFLEC combines models for atmospheric correction (6S), canopy reflectance (ACRM) and leaf optics (PROSPECT). The REGFLEC tool corrects for impacts of atmospheric scattering and absorption, soil background reflectance and species specific vegetation characteristics (ie. leaf angle distribution). In this study, the REGFLEC model tool is applied to high spatial (10-20 m) resolution SPOT satellite data for mapping LAI and leaf N of agricultural landscapes located in Denmark, Poland, Scotland, the Netherlands and Italy (Table 1). Non-destructive field measurements of LAI (LAI-2000, LiCor, USA), Cab and leaf N contents were made within 1-2 weeks of the date for satellite image acquisition and used to evaluate remote sensing predictions. A number of additional GPS registrations were made to support the image (land use) classification required by the REGFLEC methodology. Cab and leaf N contents were measured using a SPAD meter (SPAD 502-DL, Minolta, USA) which was calibrated for different leaf types to assess Cab (r2 = 0.73-0.93) and leaf N (r2 = 0.62-0.89) of the monitored crop types. In addition, the Cab and leaf N contents of leaf samples were analyzed in laboratory to establish empirical relationships for converting Cab predictions to leaf N contents