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We describe here efforts to create and study magnetized electron–positron pair plasmas, the existence of which in astrophysical environments is well-established. Laboratory incarnations of such systems are becoming ever more possible due to novel approaches and techniques in plasma, beam and laser physics. Traditional magnetized plasmas studied to date, both in nature and in the laboratory, exhibit a host of different wave types, many of which are generically unstable and evolve into turbulence or violent instabilities. This complexity and the instability of these waves stem to a large degree from the difference in mass between the positively and the negatively charged species: the ions and the electrons. The mass symmetry of pair plasmas, on the other hand, results in unique behaviour, a topic that has been intensively studied theoretically and numerically for decades, but experimental studies are still in the early stages of development. A levitated dipole device is now under construction to study magnetized low-energy, short-Debye-length electron–positron plasmas; this experiment, as well as a stellarator device that is in the planning stage, will be fuelled by a reactor-based positron source and make use of state-of-the-art positron cooling and storage techniques. Relativistic pair plasmas with very different parameters will be created using pair production resulting from intense laser–matter interactions and will be confined in a high-field mirror configuration. We highlight the differences between and similarities among these approaches, and discuss the unique physics insights that can be gained by these studies.
As current vehicle development processes in the automotive industry are highly distributed, the interaction between design teams is limited. In this paper we use a simulation in order to investigate how the rate of design team interaction affects the solution quality and development cost. Results show, that in case of no limiting constraints, a low rate of interaction yields the best results regarding solution quality and development cost. If design activities are affected by constraints, however, the rate of interaction is subject to a conflict between solution quality and development cost.
Seasonal patterns in hospitalizations have been observed in various psychiatric disorders, however, it is unclear whether they also exist in schizophrenia. Previous studies found mixed results and those reporting the presence of seasonality differ regarding the characteristics of these patterns. Further, they are inconclusive whether sex is an influencing factor. The aim of this study was therefore to examine if seasonal patterns in hospitalizations can be found in schizophrenia, with special regard to a possible influence of sex, by using a large national dataset.
Data on all hospital admissions within Austria due to schizophrenia (F20.0–F20.6) for the time period of 2003–2016 were included. Age standardized monthly variation of hospitalization for women and men was analyzed and the level of significance adjusted for multiple testing.
The database comprised of 110,735 admissions (59.6% men). Significant seasonal variations were found in the total sample with hospitalization peaks in January and June and a trough in December (p < 0.0001). No significant difference in these patterns was found between women and men with schizophrenia (p < 0.0001).
Our study shows that schizophrenia-related hospitalizations follow a seasonal pattern in both men and women. The distribution of peaks might be influenced by photoperiod changes which trigger worsening of symptoms and lead to exacerbations in schizophrenia. Further research is necessary to identify underlying factors influencing seasonal patterns and to assess whether a subgroup of patients with schizophrenia is especially vulnerable to the impact of seasonal variations.
To quantify and compare the resource consumption and direct costs of medical mental health care of patients suffering from schizophrenia in France, Germany and the United Kingdom.
In the European Cohort Study of Schizophrenia, a naturalistic two-year follow-up study, patients were recruited in France (N = 288), Germany (N = 618), and the United Kingdom (N = 302). Data about the use of services and medication were collected. Unit cost data were obtained and transformed into United States Dollar Purchasing Power Parities (USD-PPP). Mean service use and costs were estimated using between-effects regression models.
In the French/German/UK sample estimated means for a six-month period were respectively 5.7, 7.5 and 6.4 inpatient days, and 11.0, 1.3, and 0.7 day-clinic days. After controlling for age, sex, number of former hospitalizations and psychopathology (CGI score), mean costs were 3700/2815/3352 USD-PPP.
Service use and estimated costs varied considerably between countries. The greatest differences were related to day-clinic use. The use of services was not consistently higher in one country than in the others. Estimated costs did not necessarily reflect the quantity of service use, since unit costs for individual types of service varied considerably between countries.
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
Early improvement (EI), i.e. a symptom reduction from baseline of at least 20% after 2 weeks, has been proven to be a clinically useful predictor for later treatment outcome. In most studies EI is identified by using the sum score of the Hamilton Depression Rating Scale (HAMD). Several unidimensional subscales of the HAMD exist, which have proven to be an economic measure of treatment change. Their ability to detect onset of improvement in comparison to the full HAMD has not been researched yet. The present study investigated in patients with major depression (MD) (1) whether the HAMD subscales are a valid and economic option to predict antidepressant treatment response in the early course of treatment and, (2) to validate the 20% EI criterion.
Based on data from 210 patients of a 6-week randomised, placebo-controlled trial comparing mirtazapine (MIR) and paroxetine (PAR) in patients with MD, the discriminative and predictive validity of EI for (stable) response/remission at treatment end was evaluated for the existing subscales in comparison to the HAMD17 in the total group as well as in the different treatment arms (MIR vs. PAR). Receiver operating characteristics (ROC) curves were used to validate the 20% EI criterion for the subscales.
Two subscales had similar predictive values than the full HAMD17, but overall, the HAMD17qualifies best for predicting antidepressant treatmentresponse/remission in the early course of treatment. The established 20%threshold of EI of the full HAMD17 scale also seems appropriate for the subscales.
Black and White dual-purpose cattle (DSN) are kept in diverse production systems, but the same set of genetic parameters is used for official national genetic evaluations, neglecting the herd or production system characteristics. The aim of the present study was to infer genetic (co)variance components within and across defined herd descriptor groups or clusters, considering only herds keeping the local and endangered DSN breed. The study considered 3659 DSN and 2324 Holstein Friesian (HF) cows from parities one to three. The 46 herds always kept DSN cows, but in most cases, herds were ‘mixed’ herds (Mixed), including both genetic lines HF and DSN. In order to study environmental sensitivity, we had a focus on the naturally occurring negative energy balance in the early lactation period. In consequence, traits were records from the 1st official test-day after calving for milk yield (Milk-kg), somatic cell score (SCS) and fat-to-protein ratio (FPR). Genetic parameters were estimated in bivariate runs (separate runs for the three genetic lines Mixed, HF and DSN), defining the same trait from different herd groups or clusters as different traits. Additive-genetic variances and heritabilities were larger in herd groups that indicated superior herd management, implying that cow records from these herds allow a better genetic differentiation. Superior herd management included larger herds, low calving age, high herd production levels and low intra-herd somatic cell count. Herd descriptor group differences in additive-genetic variances for Milk-kg were stronger in HF than in DSN, indicating environmental sensitivity for DSN. Similar variance components and heritabilities across groups, clusters and genetic lines were found for data stratification according to geographical descriptors altitude and latitude. Considering 72 bivariate herd group runs, 29 genetic correlations were very close to 1 (mostly for Milk-kg). Somatic cell score was the trait showing the smallest genetic correlations, especially in the DSN analyses, and when stratifying herds according to genetic line compositions (rg=0.11), or according to the percentage of natural service sires (rg=0.08). For estimations based on the results of a cluster analysis considering several herd descriptors simultaneously, indications for genotype × environment interactions could be found for SCS, but genetic correlations were larger than 0.80 for Milk-kg and FPR. In conclusion, we suggest multiple-trait animal model applications in genetic evaluations, in order to select the best sires for specific herd environments or herd clusters.
In dairy cattle, resistance, tolerance and resilience refer to the adaptation ability to a broad range of environmental conditions, implying stable performances (e.g. production level, fertility status) independent from disease or infection pressure. All three mechanisms resistance, tolerance and resilience contribute to overall robustness, implying the evaluation of phenotyping and breeding strategies for improved robustness in dairy cattle populations. Classically, breeding approaches on improved robustness rely on simple production traits, in combination with detailed environmental descriptors and enhanced statistical modelling to infer possible genotype by environment interactions. In this regard, innovative environmental descriptors were heat stress indicators, and statistical modelling focussed on random regression or reaction norm methodology. A robust animal has high breeding values over a broad spectra of environmental levels. During the last years, direct health traits were included into selection indices, implying advances in genetic evaluations for traits being linked to resistance or tolerance against infectious and non-infectious diseases. Up to now, genetic evaluation for health traits is primarily based on subjectively measured producer-recorded data, with disease trait heritabilities in a low-to-moderate range. Thus, it is imperative to identify objectively measurable phenotypes as suitable biomarkers. New technologies (e.g. mid-infrared spectrometry) offer possibilities to determine potential biomarkers via laboratory analyses. Novel biomarkers include measurable physiological traits (e.g. serum metabolites, hormone levels) as indicators for a current infection, or the host’s reaction to environmental stressors. The rumen microbiome composition is proposed as a biomarker to detect interactions between host genotype and environmental effects. The understanding of host genetic variation in disease resistance and individual expression of robustness encourages analyses on the underlying immune response (IR) system. Recent advances have been made in order to infer the genetic background of IR traits and cows immunological competence in relation to functional and production traits. Thus, a last aspect of this review addresses the genetic background and current state of genetic control for resistance to economically relevant infectious and non-infectious dairy cattle diseases by considering immune-related factors.
Anorexia nervosa (AN) is a serious illness leading to substantial morbidity and mortality. The treatment of AN very often is protracted; repeated hospitalizations and lost productivity generate substantial economic costs in the health care system. Therefore, this study aimed to determine the differential cost-effectiveness of out-patient focal psychodynamic psychotherapy (FPT), enhanced cognitive–behavioural therapy (CBT-E), and optimized treatment as usual (TAU-O) in the treatment of adult women with AN.
The analysis was conducted alongside the randomized controlled Anorexia Nervosa Treatment of OutPatients (ANTOP) study. Cost-effectiveness was determined using direct costs per recovery at 22 months post-randomization (n = 156). Unadjusted incremental cost-effectiveness ratios (ICERs) were calculated. To derive cost-effectiveness acceptability curves (CEACs) adjusted net-benefit regressions were applied assuming different values for the maximum willingness to pay (WTP) per additional recovery. Cost–utility and assumptions underlying the base case were investigated in exploratory analyses.
Costs of in-patient treatment and the percentage of patients who required in-patient treatment were considerably lower in both intervention groups. The unadjusted ICERs indicated FPT and CBT-E to be dominant compared with TAU-O. Moreover, FPT was dominant compared with CBT-E. CEACs showed that the probability for cost-effectiveness of FTP compared with TAU-O and CBT-E was ⩾95% if the WTP per recovery was ⩾€9825 and ⩾€24 550, respectively. Comparing CBT-E with TAU-O, the probability of being cost-effective remained <90% for all WTPs. The exploratory analyses showed similar but less pronounced trends.
Depending on the WTP, FPT proved cost-effective in the treatment of adult AN.
Feedback learning is essential for behavioral development. We investigated feedback learning in relation to behavior problems after pediatric traumatic brain injury (TBI).
Children aged 6–13 years diagnosed with TBI (n = 112; 1.7 years post-injury) were compared with children with traumatic control (TC) injury (n = 52). TBI severity was defined as mild TBI without risk factors for complicated TBI (mildRF− TBI, n = 24), mild TBI with ⩾1 risk factor for complicated TBI (mildRF+ TBI, n = 51) and moderate/severe TBI (n = 37). The Probabilistic Learning Test was used to measure feedback learning, assessing the effects of inconsistent feedback on learning and generalization of learning from the learning context to novel contexts. The relation between feedback learning and behavioral functioning rated by parents and teachers was explored.
No evidence was found for an effect of TBI on learning from inconsistent feedback, while the moderate/severe TBI group showed impaired generalization of learning from the learning context to novel contexts (p = 0.03, d = −0.51). Furthermore, the mildRF+ TBI and moderate/severe TBI groups had higher parent and teacher ratings of internalizing problems (p's ⩽ 0.04, d's ⩾ 0.47) than the TC group, while the moderate/severe TBI group also had higher parent ratings of externalizing problems (p = 0.006, d = 0.58). Importantly, poorer generalization of learning predicted higher parent ratings of externalizing problems in children with TBI (p = 0.03, β = −0.21) and had diagnostic utility for the identification of children with TBI and clinically significant externalizing behavior problems (area under the curve = 0.77, p = 0.001).
Moderate/severe pediatric TBI has a negative impact on generalization of learning, which may contribute to post-injury externalizing problems.
Theoretical models of high-mass star formation lie between two extreme scenarios. At one extreme, all the mass comes from an initially gravitationally bound core. At the other extreme, the majority of the mass comes from cluster scale gas, which lies far outside the initial core boundary. One way to unambiguously show high-mass stars can assemble their gas through the former route would be to find a high-mass star forming in isolation. Making use of recently available CORNISH and ATLASGAL Galactic plane survey data, we develop sample selection criteria to try and find such an object. From an initial list of approximately 200 sources, we identify the high-mass star-forming region G13.384 + 0.064 as the most promising candidate. The region contains a strong radio continuum source, that is powered by an early B-type star. The bolometric luminosity, derived from infrared measurements, is consistent with this. However, sub-millimetre continuum emission, measured in ATLASGAL, as well as dense gas tracers, such as HCO+(3–2) and N2H+(3–2) indicate that there is less than ~ 100 M⊙ of material surrounding this star. We conclude that this region is indeed a promising candidate for a high-mass star forming in isolation.
In endangered and local pig breeds of small population sizes, production has to focus on alternative niche markets with an emphasis on specific product and meat quality traits to achieve economic competiveness. For designing breeding strategies on meat quality, an adequate performance testing scheme focussing on phenotyped selection candidates is required. For the endangered German pig breed ‘Bunte Bentheimer’ (BB), no breeding program has been designed until now, and no performance testing scheme has been implemented. For local breeds, mainly reared in small-scale production systems, a performance test based on in vivo indicator traits might be a promising alternative in order to increase genetic gain for meat quality traits. Hence, the main objective of this study was to design and evaluate breeding strategies for the improvement of meat quality within the BB breed using in vivo indicator traits and genetic markers. The in vivo indicator trait was backfat thickness measured by ultrasound (BFiv), and genetic markers were allele variants at the ryanodine receptor 1 (RYR1) locus. In total, 1116 records of production and meat quality traits were collected, including 613 in vivo ultrasound measurements and 713 carcass and meat quality records. Additionally, 700 pigs were genotyped at the RYR1 locus. Data were used (1) to estimate genetic (co)variance components for production and meat quality traits, (2) to estimate allele substitution effects at the RYR1 locus using a selective genotyping approach and (3) to evaluate breeding strategies on meat quality by combining results from quantitative-genetic and molecular-genetic approaches. Heritability for the production trait BFiv was 0.27, and 0.48 for backfat thickness measured on carcass. Estimated heritabilities for meat quality traits ranged from 0.14 for meat brightness to 0.78 for the intramuscular fat content (IMF). Genetic correlations between BFiv and IMF were higher than estimates based on carcass backfat measurements (0.39 v. 0.25). The presence of the unfavorable n allele was associated with increased electric conductivity, paler meat and higher drip loss. The allele substitution effect on IMF was unfavorable, indicating lower IMF when the n allele is present. A breeding strategy including the phenotype (BFiv) combined with genetic marker information at the RYR1 locus from the selection candidate, resulted in a 20% increase in accuracy and selection response when compared with a breeding strategy without genetic marker information.
The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either ‘conventional’ estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h2=0.05) and moderate heritability (h2=0.30). GEBV were calculated for different accuracies (rmg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from rg=0.5 to 1.0. For both traits (h2=0.05 and 0.30) and rmg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (rg=0.5), and for highly accurate GEBV for natural service bulls (rmg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices.
As physical activity may modify the effect of the apolipoprotein E (APOE) ε4 allele on the risk of dementia and Alzheimer's disease (AD) dementia, we tested for such a gene–environment interaction in a sample of general practice patients aged ⩾75 years.
Data were derived from follow-up waves I–IV of the longitudinal German study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe). The Kaplan–Meier survival method was used to estimate dementia- and AD-free survival times. Multivariable Cox regression was used to assess individual associations of APOE ε4 and physical activity with risk for dementia and AD, controlling for covariates. We tested for gene–environment interaction by calculating three indices of additive interaction.
Among the randomly selected sample of 6619 patients, 3327 (50.3%) individuals participated in the study at baseline and 2810 (42.5%) at follow-up I. Of the 2492 patients without dementia included at follow-up I, 278 developed dementia (184 AD) over the subsequent follow-up interval of 4.5 years. The presence of the APOE ε4 allele significantly increased and higher physical activity significantly decreased risk for dementia and AD. The co-presence of APOE ε4 with low physical activity was associated with higher risk for dementia and AD and shorter dementia- and AD-free survival time than the presence of APOE ε4 or low physical activity alone. Indices of interaction indicated no significant interaction between low physical activity and the APOE ε4 allele for general dementia risk, but a possible additive interaction for AD risk.
Physical activity even in late life may be effective in reducing conversion to dementia and AD or in delaying the onset of clinical manifestations. APOE ε4 carriers may particularly benefit from increasing physical activity with regard to their risk for AD.
It is well documented that global warming is unequivocal. Dairy production systems are considered as important sources of greenhouse gas emissions; however, little is known about the sensitivity and vulnerability of these production systems themselves to climate warming. This review brings different aspects of dairy cow production in Central Europe into focus, with a holistic approach to emphasize potential future consequences and challenges arising from climate change. With the current understanding of the effects of climate change, it is expected that yield of forage per hectare will be influenced positively, whereas quality will mainly depend on water availability and soil characteristics. Thus, the botanical composition of future grassland should include species that are able to withstand the changing conditions (e.g. lucerne and bird's foot trefoil). Changes in nutrient concentration of forage plants, elevated heat loads and altered feeding patterns of animals may influence rumen physiology. Several promising nutritional strategies are available to lower potential negative impacts of climate change on dairy cow nutrition and performance. Adjustment of feeding and drinking regimes, diet composition and additive supplementation can contribute to the maintenance of adequate dairy cow nutrition and performance. Provision of adequate shade and cooling will reduce the direct effects of heat stress. As estimated genetic parameters are promising, heat stress tolerance as a functional trait may be included into breeding programmes. Indirect effects of global warming on the health and welfare of animals seem to be more complicated and thus are less predictable. As the epidemiology of certain gastrointestinal nematodes and liver fluke is favourably influenced by increased temperature and humidity, relations between climate change and disease dynamics should be followed closely. Under current conditions, climate change associated economic impacts are estimated to be neutral if some form of adaptation is integrated. Therefore, it is essential to establish and adopt mitigation strategies covering available tools from management, nutrition, health and plant and animal breeding to cope with the future consequences of climate change on dairy farming.
Whether late-onset depression is a risk factor for or a prodrome of dementia remains unclear. We investigated the impact of depressive symptoms and early- v. late-onset depression on subsequent dementia in a cohort of elderly general-practitioner patients (n = 2663, mean age = 81.2 years).
Risk for subsequent dementia was estimated over three follow-ups (each 18 months apart) depending on history of depression, particularly age of depression onset, and current depressive symptoms using proportional hazard models. We also examined the additive prediction of incident dementia by depression beyond cognitive impairment.
An increase of dementia risk for higher age cut-offs of late-onset depression was found. In analyses controlling for age, sex, education, and apolipoprotein E4 genotype, we found that very late-onset depression (aged ⩾70 years) and current depressive symptoms separately predicted all-cause dementia. Combined very late-onset depression with current depressive symptoms was specifically predictive for later Alzheimer's disease (AD; adjusted hazard ratio 5.48, 95% confidence interval 2.41–12.46, p < 0.001). This association was still significant after controlling for cognitive measures, but further analyses suggested that it was mediated by subjective memory impairment with worries.
Depression might be a prodrome of AD but not of dementia of other aetiology as very late-onset depression in combination with current depressive symptoms, possibly emerging as a consequence of subjectively perceived worrisome cognitive deterioration, was most predictive. As depression parameters and subjective memory impairment predicted AD independently of objective cognition, clinicians should take this into account.