Chest X-rays are less sensitive than multiple breath washout examinations when it comes to detecting early cystic fibrosis lung disease

Aim: Annual chest X-ray is recommended as routine surveillance to track cystic fibrosis (CF) lung disease. The aim of this study was to investigate the clinical utility of chest X-rays to track CF lung disease. Methods: Children at Gothenburg\u27s CF centre who underwent chest X-rays, multiple breath washouts and chest computed tomography examinations between 1996 and 2016 were included in the study. Chest X-rays were interpreted with Northern Score (NS). We compared NS to lung clearance index (LCI) and structural lung damage measured by computed tomography using a logistic regression model. Results: A total of 75 children were included over a median period of 13\ua0years (range: 3.0-18.0\ua0years). The proportion of children with abnormal NS was significantly lower than the proportion of abnormal LCI up to the age of 4\ua0years (p\ua0<\ua00.05). A normal NS and a normal LCI at age 6\ua0years were associated with a median (10-90th percentile) total airway disease of 1.8% (0.4-4.7%) and bronchiectasis of 0.2% (0.0-1.5%). Conclusion: Chest X-rays were less sensitive than multiple breath washout examinations to detect early CF lung disease. The combined results from both methods can be used as an indicator to perform chest computed tomography less frequently

Associations between the Bacterial Composition of Farm Bulk Milk and the Microbiota in the Resulting Swedish Long-Ripened Cheese

The maturation of a traditional Swedish long-ripened cheese has shown increasing variation in recent years and the ripening time is now generally longer than in the past. While the cheese is reliant on non-starter lactic acid bacteria for the development of its characteristic flavour, we hypothesised that the observed changes could be due to variations in the microbiota composition and number of bacteria in the raw milk used for production of the cheese. To evaluate associations between microbiota in the raw milk and the resulting cheese, three clusters of commercial farms were created to increase variation in the microbiota of dairy silo milk used for cheese production. Cheese production was performed in three periods over one year. Within each period, milk from the three farm clusters was collected separately and transported to the cheese production facility. Following pasteurisation, the milk was processed into the granular-eyed cheese and matured at a dedicated cheese-ripening facility. For each cheese batch, farm bulk and dairy silo milk samples, a starter culture, early process samples and cheese samples from different stages of maturation (7-20 months) were collected and their microbiota characterised using 16S rRNA amplicon sequencing. The microbiota in the farm bulk milk differed significantly between periods and clusters. Differences in microbiota in dairy silo milk were observed between periods, but not between farm clusters, while the cheese microbiota differed between periods and clusters. The top 13 amplicon sequence variants were dominant in early process samples and the resulting cheese, making up at least 93.3% of the relative abundance (RA). Lactococcus was the dominant genus in the early process samples and, together with Leuconostoc, also dominated in the cheese samples. Contradicting expectations, the RA of the aroma-producing genus Lactobacillus was low in cheese during ripening and there was an unexpected dominance of starter lactic acid bacteria even at the later stages of cheese ripening. To identify factors behind the recent variations in ripening time of this cheese, future studies should address the effects of process variables and the dairy environment

A Cross-National Investigation into the Marketing Department\u27s Influence Within the Firm: Toward Initial Empirical Generalizations

This study of the influence of the marketing department (MD), as well as its relationship with firm performance, includes seven industrialized countries and aims to generalize the conceptual model presented by Verhoef and Leeflang (2009). This investigation considers the antecedents of perceived MD influence, top management respect for the MD, and MD decision influence, as well as the relationships of these three influence variables with market orientation (MO) and business performance (BP). Meta-analytic procedures reveal initial empirical generalizations: Accountability, MD innovativeness, and the customer connection capabilities of the MD relate consistently to all three studied MD influence measures. The generalization also shows that MD influence contributes to BP indirectly through its positive relationship with MO and directly through its positive direct relationship with BP

Milking system and premilking routines have strong effect on the microbial community in bulk tank milk

In this study, we investigated the variation in the microbial community present in bulk tank milk samples and the potential effect of different farm management factors. Bulk tank milk samples were collected repeatedly over one year from 42 farms located in northern Sweden. Total and thermoresistant bacteria counts and 16S rRNA gene-based amplicon sequencing were used to characterize microbial community composition. The microbial community was in general heterogeneous both within and between different farms and the community composition in the bulk tank milk was commonly dominated by Pseudomonas, Acinetobacter, Streptococcus, unclassified Peptostreptococcaceae, and Staphylococcus. Principal component analysis including farm factor variables and microbial taxa data revealed that the microbial community in milk was affected by type of milking system. Milk from farms using an automatic (robot) milking system (AMS) and loose housing showed different microbial community composition compared with milk from tiestall farms. A discriminant analysis model revealed that this difference was dependent on several microbial taxa. Among farms using an automatic milking system, there were further differences in the microbial community composition depending on the brand of the milking robot used. On tiestall farms, routines for teat preparation and cleaning of the milking equipment affected the microbial community composition in milk. Total bacteria count (TBC) in milk differed between the farm types, and TBC were higher on AMS than tiestall farms (log 4.05 vs. log 3.79 TBC/mL for AMS and tiestalls, respectively). Among tiestall farms, milk from farms using a chemical agent in connection to teat preparation and a more frequent use of acid to clean the milking equipment had lower TBC in milk, than milk from farms using water for teat preparation and a less frequent use of acid to clean the milking equipment (log 3.68 vs. 4.02 TBC/mL). There were no significant differences in the number of thermoresistant bacteria between farm types. The evaluated factors explained only a small proportion of total variation in the microbiota data, however, despite this, the study highlights the effect of routines associated with teat preparation and cleaning of the milking equipment on raw milk microbiota, irrespective of type of milking system used

Assessment of eutrophication abatement scenarios for the Baltic Sea by multi-model ensemble simulations

Peer reviewe

Assessment of Uncertainties in Scenario Simulations of Biogeochemical Cycles in the Baltic Sea

Following earlier regional assessment studies, such as the Assessment of Climate Change for the Baltic Sea Basin and the North Sea Region Climate Change Assessment, knowledge acquired from available literature about future scenario simulations of biogeochemical cycles in the Baltic Sea and their uncertainties is assessed. The identification and reduction of uncertainties of scenario simulations are issues for marine management. For instance, it is important to know whether nutrient load abatement will meet its objectives of restored water quality status in future climate or whether additional measures are required. However, uncertainties are large and their sources need to be understood to draw conclusions about the effectiveness of measures. The assessment of sources of uncertainties in projections of biogeochemical cycles based on authors' own expert judgment suggests that the biggest uncertainties are caused by (1) unknown current and future bioavailable nutrient loads from land and atmosphere, (2) the experimental setup (including the spin up strategy), (3) differences between the projections of global and regional climate models, in particular, with respect to the global mean sea level rise and regional water cycle, (4) differing model-specific responses of the simulated biogeochemical cycles to long-term changes in external nutrient loads and climate of the Baltic Sea region, and (5) unknown future greenhouse gas emissions. Regular assessments of the models' skill (or quality compared to observations) for the Baltic Sea region and the spread in scenario simulations (differences among projected changes) as well as improvement of dynamical downscaling methods are recommended.Peer reviewe

The puzzling dredge-up pattern in NGC 1978

Low-mass stars are element factories that efficiently release their products in the final stages of their evolution by means of stellar winds. Since they are large in number, they contribute significantly to the cosmic matter cycle. To assess this contribution quantitatively, it is crucial to obtain a detailed picture of the stellar interior, particularly with regard to nucleosynthesis and mixing mechanisms. We seek to benchmark stellar evolutionary models of low-mass stars. In particular, we measure the surface abundance of ^{12}C in thermally pulsing AGB stars with well-known mass and metallicity, which can be used to infer information about the onset and efficiency of the third dredge-up. We recorded high-resolution near-infrared spectra of AGB stars in the LMC cluster NGC 1978. The sample comprised both oxygen-rich and carbon-rich stars, and is well-constrained in terms of the stellar mass, metallicity, and age. We derived the C/O and ^{12}C/^{13}C ratio from the target spectra by a comparison to synthetic spectra. Then, we compared the outcomes of stellar evolutionary models with our measurements. The M stars in NGC 1978 show values of C/O and ^{12}C/^{13}C that can best be explained with moderate extra-mixing on the RGB coupled to a moderate oxygen enhancement in the chemical composition. These oxygen-rich stars do not seem to have undergone third dredge-up episodes (yet). The C stars show carbon-to-oxygen and carbon isotopic ratios consistent with the occurrence of the third dredge-up. We did not find S stars in this cluster. None of the theoretical schemes that we considered was able to reproduce the observations appropriately. Instead, we discuss some non-standard scenarios to explain the puzzling abundance pattern in NGC 1978.Comment: 16 pages, 9 figures, 4 tables, accepted for publication in A&A, language revise

Simulations of the solar near-surface layers with the CO5BOLD, MURaM, and Stagger codes

Radiative hydrodynamic simulations of solar and stellar surface convection have become an important tool for exploring the structure and gas dynamics in the envelopes and atmospheres of late-type stars and for improving our understanding of the formation of stellar spectra. We quantitatively compare results from three-dimensional, radiative hydrodynamic simulations of convection near the solar surface generated with three numerical codes CO5BOLD, MURaM, and STAGGER and different simulation setups in order to investigate the level of similarity and to cross-validate the simulations. For all three simulations, we considered the average stratifications of various quantities (temperature, pressure, flow velocity, etc.) on surfaces of constant geometrical or optical depth, as well as their temporal and spatial fluctuations. We also compared observables, such as the spatially resolved patterns of the emerging intensity and of the vertical velocity at the solar optical surface as well as the center-to-limb variation of the continuum intensity at various wavelengths. The depth profiles of the thermodynamical quantities and of the convective velocities as well as their spatial fluctuations agree quite well. Slight deviations can be understood in terms of differences in box size, spatial resolution and in the treatment of non-gray radiative transfer between the simulations. The results give confidence in the reliability of the results from comprehensive radiative hydrodynamic simulations.Comment: Astronomy & Astrophysics, in pres

Formation of Zr I and II lines under non-LTE conditions of stellar atmospheres

The non-local thermodynaic equilibrium (non-LTE) line formation for the two ions of zirconium is considered through a range of spectral types when the Zr abundance varies from the solar value down to [Zr/H] = -3. The model atom was built using 148 energy levels of Zr I, 772 levels of Zr II, and the ground state of Zr III. It was shown that the main non-LTE mechnism for the minority species Zr I is ultraviolet overionization. Non-LTE leads to systematically depleted total absorption in the Zr I lines and positive abundance corrections, reaching to 0.33 dex for the solar metallicity models. The excited levels of Zr II are overpopulated relative to their thermodynamic equilibrium populations in the line formation layers due to radiative pumping from the low-excitation levels. As a result, the line source function exceeds the Planck function leading to weakening the Zr II lines and positive non-LTE abundance corrections. Such corrections grow towards lower metallicity and lower surface gravity and reach to 0.34 dex for Teff = 5500 K, log g = 2.0, [M/H] = -2. As a test and first application of the Zr I-Zr II model atom, Zr abundance was determined for the Sun on the basis of 1D LTE model atmosphere. Lines of Zr I and Zr II give consistent within the error bars non-LTE abundances, while the difference in LTE abundances amounts to 0.28 dex. The solar abundance of zirconium obtained with the MAFAGS solar model atmosphere is log eps(Zr) = 2.63+-0.07.Comment: published in Astron. Letters, 36, 664 (2010); Erratum was submitte

Forskning pågår - från foder till ost

I ett samarbete mellan Norrmejerier, Växa Sverige och institutioner vid SLU i Umeå och i Uppsala pågår tre sammanlänkade projekt där vi studerar hur ostens kvalitet påverkas av olika faktorer, från gård till mejeri. De bakterier och andra mikroorganismer som finns i foder, mjölk och ost studeras särskilt noga. Vi vill bland annat veta vad mikrofloran har för inverkan på ostens lagringstid och på dess smak och konsistens