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Light is a critical component of indoor plant cultivation, as different wavelengths can influence both the physiology and morphology of plants. Furthermore, fertilization and seeding density can also potentially interact with the light recipe to affect production outcomes. However, maximizing production is an ongoing research topic, and it is often divested from resource use efficiencies. In this study, three species of microgreens—kohlrabi; mustard; and radish—were grown under five light recipes; with and without fertilizer; and at two seeding densities. We found that the different light recipes had significant effects on biomass accumulation. More specifically, we found that Far-Red light was significantly positively associated with biomass accumulation, as well as improvements in height, leaf area, and leaf weight. We also found a less strong but positive correlation with increasing amounts of Green light and biomass. Red light was negatively associated with biomass accumulation, and Blue light showed a concave downward response. We found that fertilizer improved biomass by a factor of 1.60 across species and that using a high seeding density was 37% more spatially productive. Overall, we found that it was primarily the main effects that explained microgreen production variation, and there were very few instances of significant interactions between light recipe, fertilization, and seeding density. To contextualize the cost of producing these microgreens, we also measured resource use efficiencies and found that the cheaper 24-volt LEDs at a high seeding density with fertilizer were the most efficient production environment for biomass. Therefore, this study has shown that, even with a short growing period of only four days, there was a significant influence of light recipe, fertilization, and seeding density that can change morphology, biomass accumulation, and resource input costs. [ABSTRACT FROM AUTHOR]

Background and aims: Root distribution over the soil profile is important for crop resource uptake. Using machine learning (ML), this study investigated whether measured square root of planar root length density (Sqrt_pRLD) at different soil depths were related to uptake of isotope tracer (15N) and drought stress indicator (13C) in wheat, to reveal root function. Methods: In the RadiMax semi-field root-screening facility 95 winter wheat genotypes were phenotyped for root growth in 2018 and 120 genotypes in 2019. Using the minirhizotron technique, root images were acquired across a depth range from 80 to 250 cm in May, June, and July and RL was extracted using a convolutional neural network. We developed ML models to explore whether the Sqrt_pRLD estimates at different soil depths were predictive of the uptake of deep soil nitrogen - using deep placement of 15N tracer as well as natural abundance of 13C isotope. We analyzed the correlations to tracer levels to both a parametrized root depth estimation and an ML approach. We further analyzed the genotypic effects on root function using mediation analysis. Results: Both parametrized and ML models demonstrated clear correlations between Sqrt_pRLD distribution and resource uptake. Further, both models demonstrated that deep roots at approx. 150 to 170 cm depth were most important for explaining the plant content of 15N and 13C isotopes. The correlations were higher in 2018. Conclusions: The results demonstrated that, parametrized models and ML-based analysis provided complementary insight into the importance of deep rooting for water and nitrogen uptake. [ABSTRACT FROM AUTHOR]

The coffee research community has maintained a long ongoing debate regarding the implications of shade trees in coffee production. Historically, there has been contrasting results and opinions on this matter, thus recommendations for the use of shade (namely in coffee agroforestry systems) are often deemed controversial, particularly due to potential yield declines and farmers' income. This study is one of the first demonstrating how several Coffea arabica cultivars respond differently to shade with respect to yield. By standardising more than 200 coffee yield data from various in-field trials, we assembled the so-called "Ristretto" data pool, a one of a kind, open-source dataset, consolidating decades of coffee yield data under shaded systems. With this standardised dataset, our meta-analysis demonstrated significant genotypic heterogeneity in response to shade, showing neutral, inverted U-shaped and decreasing trends between yield and shade cover amongst 18 different cultivars. These findings encourage the examination of C. arabica at the cultivar level when assessing suitability for agroforestry systems. Comparison of productivity is also encouraged across a range of low to moderate shade levels (10–40%), in order to help elucidate potential unknown optimal shade levels for coffee production. [ABSTRACT FROM AUTHOR]

Deep rooting winter wheat genotypes can reduce nitrate leaching losses and increase N uptake. We aimed to investigate which deep root traits are correlated to deep N uptake and to estimate genetic variation in root traits and deep 15N tracer uptake. In 2 years, winter wheat genotypes were grown in RadiMax, a semifield root‐screening facility. Minirhizotron root imaging was performed three times during the main growing season. At anthesis, 15N was injected via subsurface drip irrigation at 1.8 m depth. Mature ears from above the injection area were analysed for 15N content. From minirhizotron image‐based root length data, 82 traits were constructed, describing root depth, density, distribution and growth aspects. Their ability to predict 15N uptake was analysed with the least absolute shrinkage and selection operator (LASSO) regression. Root traits predicted 24% and 14% of tracer uptake variation in 2 years. Both root traits and genotype showed significant effects on tracer uptake. In 2018, genotype and the three LASSO‐selected root traits predicted 41% of the variation in tracer uptake, in 2019 genotype and one root trait predicted 48%. In both years, one root trait significantly mediated the genotype effect on tracer uptake. Deep root traits from minirhizotron images can predict deep N uptake, indicating the potential to breed deep‐N‐uptake‐genotypes. Summary Statement: Root traits of winter wheat were constructed from minirhizotron image data. Root traits predicted 24% of 15N tracer uptake, which was injected at anthesis at 1.8 m depth, and explained genotypic variation in tracer uptake. [ABSTRACT FROM AUTHOR]

Plant reproduction in red clover requires cross-fertilization via insect pollination. However, the influences of visitation rate and timing on maximizing ovule utilization are yet to be determined. We aimed to study the influences of visitation rate, flowering stage, and self-incompatibility on reproductive success. We applied hand and honey bee pollination in the study of eight red clover cultivars with two ploidy levels released between 1964 and 2001. In hand pollination, increasing the visitation rates (from 10 to 80 pollinated florets per flower head) increased the seed number per flower head but reduced the seed number per pollinated floret. Different flowering stages (early, middle, and full flowering) did not influence the seed number per pollinated floret significantly. There was a marked difference in reproductive success depending on the ploidy level, with 0.52 seeds per pollinated floret in diploid and 0.16 in tetraploid cultivars. During the cultivar release history, seed number per pollinated floret seemed to decrease in diploid cultivars, whereas it increased in tetraploids. In honey bee pollination, diploid cultivars had more two-seeded florets than tetraploids. Different visitation rates and the stochastic nature of pollen transfer resulted in difficulties when the plant reproductive success between hand and bee pollination was compared. A maximum of 0.27 seeds per pollinated floret were produced in hand pollination compared to the 0.34 in honey bee pollination. In spite of this, hand pollination provided a valuable method for studying the pollination biology and reproduction of red clover. Future studies may employ hand pollination to unravel further aspects of the low reproductive success with the future perspective of improving seed number per pollinated floret in tetraploid red clover. [ABSTRACT FROM AUTHOR]

Datasets are sometimes divided into distinct subsets, e.g. due to multi-center sampling, or to variations in instruments, questionnaire item ordering or mode of administration, and the data analyst then needs to assess whether a joint analysis is meaningful. The Principal Component Analysis-based Data Structure Comparisons (PCADSC) tools are three new non-parametric, visual diagnostic tools for investigating differences in structure for two subsets of a dataset through covariance matrix comparisons by use of principal component analysis. The PCADCS tools are demonstrated in a data example using European Social Survey data on psychological well-being in three countries, Denmark, Sweden, and Bulgaria. The data structures are found to be different in Denmark and Bulgaria, and thus a comparison of for example mean psychological well-being scores is not meaningful. However, when comparing Denmark and Sweden, very similar data structures, and thus comparable concepts of well-being, are found. Therefore, inter-country comparisons are warranted for these countries. [ABSTRACT FROM AUTHOR]

Analyzing the progression of Alzheimer's disease (AD) is challenging due to lacking sensitivity in currently available measures. AD stages are typically defined based on cognitive cut-offs, but this results in heterogeneous patient groups. More accurate modeling of the continuous progression of the disease would enable more accurate patient prognosis. To address these issues, we propose a new multivariate continuous-time disease progression (MCDP) model. The model is formulated as a nonlinear mixed-effects model that aligns patients based on their predicted disease progression along a continuous latent disease timeline. The model is evaluated using long-term follow-up data from 2152 participants in the Alzheimer's Disease Neuroimaging Initiative. The MCDP model was used to simultaneously model three cognitive scales; the Alzheimer's Disease Assessment Scale-cognitive subscale, the Mini-Mental State Examination, and the Clinical Dementia Rating scale-sum of boxes. Compared with univariate modeling and previously proposed multivariate disease progression models, the MCDP model showed superior ability to predict future patient trajectories. Finally, based on the multivariate disease timeline estimated using the MCDP model, the sensitivity of the individual items of the cognitive scales along the different stages of disease was analyzed. The analysis showed that delayed memory recall items had the highest sensitivity in the early stages of disease, whereas language and attention items were sensitive later in disease. [ABSTRACT FROM AUTHOR]

Background: Methods to compare events defined as newly occurring characters in development has advanced vertebrate developmental research but events are not easily extrapolated into traditional staging systems used in biomedical research. Results: First, we scored 95 porcine embryos in the age range of 15 to 33 days post conception by stereomicroscopy using to a slightly modified version of the Standard Event System (SES). Subsequent statistical clustering allowed the embryos to be grouped into 15 clusters. Staging of the same embryos in a way that generally follow the description of external features of human embryos in the Carnegie stages 10 to 23 allowed us to describe 14 stages of porcine embryonic development that correlate to the Carnegie stages of human development with minor species differences. When arranged by average age, the statistic clusters had a distribution that correlated well with the stages produced by the Carnegie‐based staging system. Conclusions: Statistical analysis of developmental events allow grouping of porcine embryos into clusters that can be extrapolated into a Carnegie‐based staging system, thus serving the dual purpose of facilitating the use of the pig as a biomedical model animal and providing data for integrating porcine developmental events into a phylogenetic context. Key Findings: Porcine embryos (15‐33 dpi) were successfully grouped into 15 clusters by using a modified standard event system based on external characteristics and subsequent statistical clustering.Porcine embryos (15‐33 dpi) were staged using Carnegie‐based external features and some minor differences of porcine and human embryonic development were identified.The two staging systems generally correlate well. [ABSTRACT FROM AUTHOR]

We determined how conidia of arthropod-pathogenic fungi on leaves affected the behavior of two predators—Orius majusculus (Hemiptera: Anthocoridae) and Phytoseiulus persimilis (Acari: Phytoseiidae)—when offered a choice between preying on two-spotted spider mites, Tetranychus urticae (Acari: Tetranychidae), in the presence or absence of infective conidia of Metarhizium brunneum (Ascomycota: Hypocreales) and Neozygites floridana (Entomophthoromycota: Neozygitaceae). The results indicate no significant relation between the presence of conidia and predator behavior. The only indication of interference is between the generalists O. majusculus and M. brunneum, with a trend towards more time spent feeding and more prey encounters turning into feeding events on leaf discs without conidia than on leaf discs with conidia. Our results show that the presence of fungal conidia does not alter the preying behavior of the predators, and using predators and fungi together is not limited by any interference between organisms in the short term. [ABSTRACT FROM AUTHOR]

Despite Ghana's large contribution to global cocoa production, average yields are low. Policymakers and practitioners are calling for implementation of a climate smart strategy by increasing yields and augmenting shade tree cover in cocoa systems. However, there have been few studies in West Africa on the relationship between shade and cocoa yield under field conditions. The objective of this study was to determine the effect of shade tree cover and other factors on on-farm cocoa yields over a four-year period. The study was conducted on 86 farm plots of 8–28 years' cocoa trees with varied canopy cover (CC) in Ashanti and Western regions of Ghana. A linear mixed model analysis showed that yields increased significantly with increased CC of shade trees, and indicated a doubling of yields when going from zero to approximately 30% crown cover. Fertilizer use gave a yield increase of 7%. Farms located in Western region had higher yields compared to Ashanti, and cocoa systems on short fallows had lower yields than farms cultivated on recent forest clearings and old fallows. Fungicide use, seed sources and land ownership had no significant effects on yield. We conclude that for a sustainable climate-smart cocoa agenda, promotion of shade trees is key. [ABSTRACT FROM AUTHOR]

Entomophthoralean fungi are insect pathogenic fungi and are characterized by their active discharge of infective conidia that infect insects. Our aim was to study the effects of temperature on the discharge and to characterize the variation in the associated temporal pattern of a newly discovered Pandora species with focus on peak location and shape of the discharge. Mycelia were incubated at various temperatures in darkness, and conidial discharge was measured over time. We used a novel modification of a statistical model (pavpop), that simultaneously estimates phase and amplitude effects, into a setting of generalized linear models. This model is used to test hypotheses of peak location and discharge of conidia. The statistical analysis showed that high temperature leads to an early and fast decreasing peak, whereas there were no significant differences in total number of discharged conidia. Using the proposed model we also quantified the biological variation in the timing of the peak location at a fixed temperature. [ABSTRACT FROM AUTHOR]

Empirical evidence of the cost of producing toxic compounds in harmful microalgae is completely lacking. Yet costs are often assumed to be high, implying substantial ecological benefits with adaptive significance exist. To study potential fitness costs of toxin production, 16 strains including three species of the former Alexandrium tamarense species complex were grown under both carbon limitation and unlimited conditions. Growth rates, levels of intracellular paralytic shellfish toxins (PSTs), and effects of lytic compounds were measured to provide trade-off curves of toxicity for both PST and lytic toxicity under high light (300 μmol photons m−2 s−1) and under low light (i.e., carbon limited; 20 μmol photons m−2 s−1). Fitness costs in terms of reduced growth rates with increasing PST content were only evident under unlimited conditions, but not under carbon limitation, in which case PST production was positively correlated with growth. The cost of production of lytic compounds was detected both under carbon limitation and unlimited conditions, but only in strains producing PST. The results may direct future research in understanding the evolutionary role and ecological function of algal toxins. The intrinsic growth rate costs should be accounted for in relation to quantifying benefits such as grazer avoidance or toxin-mediated prey capture in natural food web settings. [ABSTRACT FROM AUTHOR]

Water availability is often described as one of the main drivers of phenology of tropical dry forests but experimental studies to identify the cues triggering phenological changes are few. In a greenhouse trial, we exposed seedlings of thirteen origins, seven from West and six from East Africa, respectively, of Adansonia digitata L.(baobab) to a well‐watered control treatment and a water withholding treatment in combination with exposure to three different daylengths (11.5, 12.0, and 12.5 hr). Responses were measured in terms of meristematic activity, number of leaves, and height growth followed over 6.5 months. Multi‐level mixed‐effects statistical models were used to analyze how environmental and inter‐population variables affected phenological behavior. Flushing was influenced by the daylength with the lowest degree of meristematic activity observed in the short daylength treatment. Daylength also influenced the number of leaves through an interaction with the water regime. The water regime influenced all variables through interactions with the origins. Seedlings subjected to water stress had higher meristematic activity, but initially lower numbers of leaves than continuously watered plants. Height growth in continuously watered plants was fastest or at par with water‐stressed plants, depending on the origin. Origins from West Africa tended to have higher meristematic activity and their phenology was found to be less influenced by water withholding than East African origins. There were no signs of significant differences between origins in their response to photoperiod. In conclusion, baobab seedlings show opportunistic behavior, setting leaves when water is available, but larger activity is found when days are long. We discuss the results in terms of triggering factors for baobab phenology and adaptation to specific environmental conditions at the site of origins. There are very few studies on triggering factors for phenology of dry zone tropical tree species, and even fewer studies that investigate how phenology is varying among origins in common garden experiments. In this study, we tested 13 baobab origins and their phenological response to drought stress and different daylengths. Our results demonstrate that both water availability and daylength influence flushing of leaves, and that origin react differently to these signals. [ABSTRACT FROM AUTHOR]

Summary: We consider inference for misaligned multivariate functional data that represents the same underlying curve, but where the functional samples have systematic differences in shape. We introduce a class of generally applicable models where warping effects are modelled through non‐linear transformation of latent Gaussian variables and systematic shape differences are modelled by Gaussian processes. To model cross‐covariance between sample co‐ordinates we propose a class of low dimensional cross‐covariance structures that are suitable for modelling multivariate functional data. We present a method for doing maximum likelihood estimation in the models and apply the method to three data sets. The first data set is from a motion tracking system where the spatial positions of a large number of body markers are tracked in three dimensions over time. The second data set consists of longitudinal height and weight measurements for Danish boys. The third data set consists of three‐dimensional spatial hand paths from a controlled obstacle avoidance experiment. We use the method to estimate the cross‐covariance structure and use a classification set‐up to demonstrate that the method outperforms state of the art methods for handling misaligned curve data. [ABSTRACT FROM AUTHOR]

Abstract: Plants produce a multitude of metabolites that contribute to their fitness and survival and play a role in local adaptation to environmental conditions. The effects of environmental variation are particularly well studied within the genus Plantago; however, previous studies have largely focused on targeting specific metabolites. Studies exploring metabolome‐wide changes are lacking, and the effects of natural environmental variation and herbivory on the metabolomes of plants growing in situ remain unknown. An untargeted metabolomic approach using ultra‐high‐performance liquid chromatography–mass spectrometry, coupled with variation partitioning, general linear mixed modeling, and network analysis was used to detect differences in metabolic phenotypes of Plantago major in fifteen natural populations across Denmark. Geographic region, distance, habitat type, phenological stage, soil parameters, light levels, and leaf area were investigated for their relative contributions to explaining differences in foliar metabolomes. Herbivory effects were further investigated by comparing metabolomes from damaged and undamaged leaves from each plant. Geographic region explained the greatest number of significant metabolic differences. Soil pH had the second largest effect, followed by habitat and leaf area, while phenological stage had no effect. No evidence of the induction of metabolic features was found between leaves damaged by herbivores compared to undamaged leaves on the same plant. Differences in metabolic phenotypes explained by geographic factors are attributed to genotypic variation and/or unmeasured environmental factors that differ at the regional level in Denmark. A small number of specialized features in the metabolome may be involved in facilitating the success of a widespread species such as Plantago major into such wide range of environmental conditions, although overall resilience in the metabolome was found in response to environmental parameters tested. Untargeted metabolomic approaches have great potential to improve our understanding of how specialized plant metabolites respond to environmental change and assist in adaptation to local conditions. [ABSTRACT FROM AUTHOR]

Objective To investigate parameters causing canine thromboelastographic hypercoagulability and to investigate whether thromboelastography (TEG) with Cytochalasin D (Cyt D) added is related to parameters of platelet activity. Design Prospective observational study on hemostatic and inflammatory parameters. Data were collected between November 2012 and July 2013. Setting University teaching hospital. Animals Twenty-eight dogs suffering from diseases predisposing to thrombosis and 19 clinically healthy dogs. Diseased dogs were enrolled if they fulfilled inclusion criteria regarding age, size, informed client consent, and obtained a diagnosis of a disease that has been associated with thrombosis or hypercoagulability. Interventions None. Measurements and Main Results Parameters of coagulation and anticoagulation, fibrinolysis, and antifibrinolysis, platelet activity, inflammation, platelet count, and hematocrit were measured using CBC, TEG, platelet aggregation on multiplate, platelet activity on flow cytometry, and hemostatic and inflammatory markers on plasma and serum analyses. ANOVA and multilinear regression analyses indicated that especially hematocrit and the inflammatory parameters C-reactive protein and interleukin-8 showed best association with overall clot strength in diseased dogs with hypercoagulable TEG tracings. Ratios presumed to reflect platelet contribution to the TEG tracing obtained in TEG analyses with Cyt D were related especially with hematocrit and P-selectin expression of platelets measured after γ-Thrombin activation on flow cytometry. Conclusion Overall clot strength in TEG analyses of the hypercoagulable dogs included in the present study appears to be primarily associated with inflammation as well as hematocrit. Furthermore, the ratio between standard TEG analyses and TEG analyses with Cyt D may reflect some degree of platelet activity. [ABSTRACT FROM AUTHOR]

Most cocoa farms in Ghana are cultivated in complex agroforest systems, with plant growth and cocoa productivity being affected. The objective of this study was to investigate how shade trees affect cocoa yield, temperature and soil nutrients in low-input cocoa systems. Establishing plots on 24 farms in four locations (districts) in Ghana, we assessed the influence of varying canopy cover and fertilization on cocoa yields. Results showed no relationship between canopy cover and cocoa yields in the light crop season (February to August). For the main crop season (September to January), there was an interaction between shade and yields: Yields were higher on no-shade plots than on shaded plots in two districts, whilst there were no differences at the two other districts possibly due to differences in precipitation and soil nutrient status. On the other hand, there was a positive effect of increased canopy cover on yields within the shaded plots. Soil nutrient analyses revealed no significant differences between shaded and no-shade plots and adequate levels of N, K+, Fe2+, Cu2+ and Zn2+ were recorded. However, soil contents of P, C, Mg2+ and Ca2+ were below recommended values. Peak temperatures recorded in the cocoa canopies were above the recommended range for this species. Although shade trees had a slight modifying effect on peak temperatures, the magnitude appeared too small to have any practical effects. [ABSTRACT FROM PUBLISHER]

Aim: To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science-based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location: Denmark, Europe. Methods: We used a point process model to estimate the effect of land cover and human infrastructure on the intensity of observations from four different citizen science species recording schemes. We then use these results to predict areas of under- and oversampling as well as relative biodiversity 'hotspots' and 'deserts', accounting for common spatial biases introduced in unstructured sampling designs. Results: We demonstrate that the explanatory power of spatial biases such as infrastructure and human population density increased as the complexity of the sampling schemes decreased. Despite a low absolute sampling effort in agricultural landscapes, these areas still appeared oversampled compared to the observed species richness. Conversely, forests and grassland appeared undersampled despite higher absolute sampling efforts. We also present a novel and effective analytical approach to address spatial biases in unstructured sampling schemes and a new way to address such biases, when more structured sampling is not an option. Main conclusions: We show that citizen science datasets, which rely on untrained amateurs, are more heavily prone to spatial biases from infrastructure and human population density. Objectives and protocols of mass-participating projects should thus be designed with this in mind. Our results suggest that, where contextual data is available, modelling the intensity of individual observation can help understand and quantify how spatial biases affect the observed biological patterns. [ABSTRACT FROM AUTHOR]

A central task in the analysis of human movement behavior is to determine systematic patterns and differences across experimental conditions, participants and repetitions. This is possible because human movement is highly regular, being constrained by invariance principles. Movement timing and movement path, in particular, are linked through scaling laws. Separating variations of movement timing from the spatial variations of movements is a well-known challenge that is addressed in current approaches only through forms of preprocessing that bias analysis. Here we propose a novel nonlinear mixed-effects model for analyzing temporally continuous signals that contain systematic effects in both timing and path. Identifiability issues of path relative to timing are overcome by using maximum likelihood estimation in which the most likely separation of space and time is chosen given the variation found in data. The model is applied to analyze experimental data of human arm movements in which participants move a hand-held object to a target location while avoiding an obstacle. The model is used to classify movement data according to participant. Comparison to alternative approaches establishes nonlinear mixed-effects models as viable alternatives to conventional analysis frameworks. The model is then combined with a novel factor-analysis model that estimates the low-dimensional subspace within which movements vary when the task demands vary. Our framework enables us to visualize different dimensions of movement variation and to test hypotheses about the effect of obstacle placement and height on the movement path. We demonstrate that the approach can be used to uncover new properties of human movement. [ABSTRACT FROM AUTHOR]

Background: Polyacrylamide hydrogel (PAAG) was evaluated recently to treat osteoarthritis (OA) in horses with highly encouraging results; however no long term field-study was done to explore its clinical efficacy and lasting effect. The objective of this study was to evaluate the efficacy of PAAG in improving clinical signs of OA in horses. We hypothesized that lameness grade would significantly improve and the effect would last at least 2 years in osteoarthritic joints treated with PAAG. Forty three horses older than 2 years with OA in only one joint based on clinical evaluation, intra-articular anaesthesia and imaging (radiography) were included in this study. Horses were injected with 2 ml of PAAG into the affected joint and were followed up at 1, 3, 6, 12 and 24 months. Efficacy of PAAG was evaluated by blinded clinical assessment of lameness. Adverse reactions to joint injection were assessed. Data relating to case details, type of activity, joint and limb involved, lameness duration, lameness grading, previous joint treatment, joint effusion grading, radiographic grading, and owner assessment were recorded. Factors associated with the outcome measure “lameness grading” were analyzed using generalized linear mixed model for logistic regression. Results: At 1, 3, 6, 12 and 24 months follow-up, 59%, 69%, 79%, 81/% and 82.5% of horses were non-lame respectively. Reduction of joint effusion was observed over time. No side effect was observed in the treated joints. There was a significant decrease in lameness grade from baseline to 1, 3, 6, 12 and 24 months (P < 0.0001) and a significant positive association with joint effusion (P < 0.0001). Estimates for odds ratio (OR) showed that the effect of treatment increased over time (OR for lower lameness from month 1 to month 24 relative to baseline increased from 20 to 58). Conclusions: PAAG significantly alleviated lameness and joint effusion in osteoarthritic joints. PAAG is a safe and lasting (at least 24 months) OA treatment in horses. PAAG is a promising new treatment for OA in horses. [ABSTRACT FROM AUTHOR]

Small-angle X-ray and neutron scattering have become increasingly popular owing to improvements in instrumentation and developments in data analysis, sample handling and sample preparation. For some time, it has been suggested that a more systematic approach to the quantification of the information content in small-angle scattering data would allow for a more optimal experiment planning and a more reliable data analysis. In the present article, it is shown how ray-tracing techniques in combination with a statistically rigorous data analysis provide an appropriate platform for such a systematic quantification of the information content in scattering data. As examples of applications, it is shown how the exposure time at different instrumental settings or contrast situations can be optimally prioritized in an experiment. Also, the gain in information by combining small-angle X-ray and neutron scattering is assessed. While solution small-angle scattering data of proteins and protein-lipid complexes are used as examples in the present case study, the approach is generalizable to a wide range of other samples and experimental techniques. The source code for the algorithms and ray-tracing components developed for this study has been made available on-line. [ABSTRACT FROM AUTHOR]

Background Insulin-like growth factor 1 ( IGF-1) has important roles in anabolic processes in the musculoskeletal system and has been reported to decrease with age in both people and horses. Objectives The objective of this study was to determine serum IGF-1 levels in the aging horse from early to late adulthood (age range 5-27 years). Methods Healthy horses ( n = 72) were used in a cross-sectional study, while 37 paired serum samples were available for a longitudinal study. Serum IGF-1 protein was determined using an ELISA kit validated for use in equine samples. Results No association was found between serum IGF-1 levels and age in the cross-sectional study. In the longitudinal study, a latent variable model fitted to the data revealed that horses in general experienced a 5.2% increase of serum IGF-1 levels over a 5-year period, but horses crossing a change point around 9 years of age between the 2 samples experienced an 11.0% decrease. Conclusions In this study, there was no evidence for aging being a factor in changes of IGF-1 levels in an adult and old horse population . [ABSTRACT FROM AUTHOR]

Background: Platinum-based chemotherapy has long been used in the treatment of a variety of cancers and functions by inducing DNA damage. ERCC1 and ERCC4 are involved in the removal of this damage and have previously been implicated in resistance to platinum compounds. The aim of the current investigation is to determine the presence, frequency and prognostic impact of ERCC1 or ERCC4 gene copy number alterations in colorectal cancer (CRC).Methods: Fluorescent in situ hybridization probes directed at ERCC1 and ERCC4 with relevant reference probes were constructed. Probes were tested in a CRC cell line panel and in tumor sections from 152 stage III CRC chemonaive patients. Relationships between biomarker status and clinical endpoints (overall survival, time to recurrence, and local recurrence in rectal cancer) were analyzed by survival statistics.Results: ERCC1-19q13 copy number alterations were observed in a single cell line metaphase (HT29). In patient material, ERCC1-19q13 copy number gains (ERCC1-19q13/CEN-2 ≥ 1.5) were detected in 27.0% of specimens, whereas ERCC1-19q13 deletions (ERCC1-19q13/CEN-2 < 0.8) were only detected in 1.3%. ERCC1-19q13 gain was significantly associated with longer survival (multivariate analysis, HR: 0.45, 95% CI: 0.20-1.00, p = 0.049) in patients with colon tumors, but not rectal tumors. No ERCC4 aberrations were detected and scoring was discontinued after 50 patients.Conclusions: ERCC1-19q13 copy number gains occur frequently in stage III CRC and influences survival in patients with colon tumors. Future studies will investigate the effect of ERCC1-19q13 aberrations in a platinum-treated patient population with the aim of developing a predictive biomarker profile for oxaliplatin sensitivity in CRC. [ABSTRACT FROM AUTHOR]

Background: Topoisomerase I (Top1) is the target of Top1 inhibitor chemotherapy. The TOP1 gene, located at 20q12-q13.1, is frequently detected at elevated copy numbers in colorectal cancer (CRC). The present study explores the mechanism, frequency and prognostic impact of TOP1 gene aberrations in stage III CRC and how these can be detected by fluorescent in situ hybridization (FISH). Methods: Nine CRC cell line metaphase spreads were analyzed by FISH with a TOP1 probe in combination with a reference probe covering either the centromeric region of chromosome 20 (CEN-20) or chromosome 2 (CEN-2). Tissue sections from 154 chemonaive stage III CRC patients, previously studied with TOP1/CEN-20, were analyzed with TOP1/CEN-2. Relationships between biomarker status and overall survival (OS), time to recurrence (TTR) in CRC and time to local recurrence (LR; rectal cancer only) were determined. Results: TOP1 aberrations were observed in four cell line metaphases. In all cell lines CEN-2 was found to reflect chromosomal ploidy levels and therefore the TOP1/CEN-2 probe combination was selected to identify TOP1 gene gains (TOP1/CEN-2≥1.5). One hundred and three patients (68.2%) had TOP1 gain, of which 15 patients (14.6%) harbored an amplification (TOP1/CEN-20≥2.0). TOP1 gene gain did not have any association with clinical endpoints, whereas TOP1 amplification showed a non-significant trend towards longer TTR (multivariate HR: 0.50, p = 0.08). Once amplified cases were segregated from other cases of gene gain, non-amplified gene increases (TOP1/CEN-2≥1.5 and TOP1/CEN-20<2.0) showed a trend towards shorter TTR (univariate HR: 1.57, p = 0.07). Conclusions: TOP1 gene copy number increase occurs frequently in stage III CRC in a mechanism that often includes CEN-20. Using CEN-2 as a measurement for tumor ploidy levels, we were able to discriminate between different mechanisms of gene gain, which appeared to differ in prognostic impact. TOP1 FISH guidelines have been updated. [ABSTRACT FROM AUTHOR]

1. Plant distributions are dynamic but the role of plant-insect interactions in controlling range dynamics is not well understood. Enemy release, for example could facilitate plant range expansion under climate change. 2. We conducted a transplant experiment with the evergreen tree Ilex aquifolium L. in both the historical and the expanding range in Denmark to study possible effects of geographical position, small-scale distance, and plant types on presence and performance of the monophagous insect leaf-miner Phytomyza ilicis Curtis. 3. The leaf miner was present in the entire range of I. aquifolium in Denmark, and there were no differences in emergence success depending on geographical position. Small-scale distance to existing adult plants influenced the activity of the insect on the transplants, and oviposition density was negatively correlated with distance to adult plants. 4. Plant type had an effect on leaf miner feeding, oviposition and mining, and the native provenance of I. aquifolium supported higher densities than two cultivars. 5. There was no evidence that enemy release facilitates the current range expansion of I. aquifolium. [ABSTRACT FROM AUTHOR]

Ascosphaera apis causes chalkbrood in honeybees, a chronic disease that reduces the number of viable offspring in the nest. Although lethal for larvae, the disease normally has relatively low virulence at the colony level. A recent study showed that there is genetic variation for host susceptibility, but whether Ascosphaera apis strains differ in virulence is unknown. We exploited a recently modified in vitro rearing technique to infect honeybee larvae from three colonies with naturally mated queens under strictly controlled laboratory conditions, using four strains from two distinct A. apis clades. We found that both strain and colony of larval origin affected mortality rates. The strains from one clade caused 12-14% mortality while those from the other clade induced 71-92% mortality. Larvae from one colony showed significantly higher susceptibility to chalkbrood infection than larvae from the other two colonies, confirming the existence of genetic variation in susceptibility across colonies. Our results are consistent with antagonistic coevolution between a specialized fungal pathogen and its host, and suggest that beekeeping industries would benefit from more systematic monitoring of this chronic stress factor of their colonies. [ABSTRACT FROM AUTHOR]

A goodness-of-fit test for continuous-time models is developed that examines if the parameter estimates are consistent with another for different sampling frequencies. The test compares parameter estimates obtained from estimating functions for downsamples of the data. We prove asymptotic results for stationary and ergodic processes, and apply the downsampling test to linear drift diffusions. Simulations indicate that the test is quite powerful in detecting non-Markovian deviations from the linear drift diffusions. [ABSTRACT FROM AUTHOR]

The theoretical underpinnings of the assessment of invasive alien species impacts need to be improved. At present most approaches are unreliable to quantify impact at regional scales and do not allow for comparison of different invasive species. There are four basic problems that need to be addressed: (1) Some impacted ecosystem traits are spatially not additive; (2) invader effects may increase non-linearly with abundance or there may be effect thresholds impairing estimates of linear impact models; (3) the abundance and impact of alien species will often co-vary with environmental variation; and (4) the total invaded range is an inappropriate measure for quantifying regional impact because the habitat area available for invasion can vary markedly among invasive species. Mathematical models and empirical data using an invasive alien plant species ( Heracleum mantegazzianum) indicate that ignoring these issues leads to impact estimates almost an order of magnitude from the real values. Thus, we propose a habitat-sensitive formula for regional impact assessment that is unaffected by non-linearity. Furthermore, we make some statistical suggestions on how to assess invader effects properly and we discuss the quantification of the invaded range. These improvements are crucial for impact assessment with the overall aim of prioritizing management of invasive species. [ABSTRACT FROM AUTHOR]