One-way layouts, i.e., a single factor with several levels and multiple observations at each level, frequently arise in various fields. Usually not only a global hypothesis is of interest but also ...multiple comparisons between the different treatment levels. In most practical situations, the distribution of observed data is unknown and there may exist a number of atypical measurements and outliers. Hence, use of parametric and semiparametric procedures that impose restrictive distributional assumptions on observed samples becomes questionable. This, in turn, emphasizes the demand on statistical procedures that enable us to accurately and reliably analyze one-way layouts with minimal conditions on available data. Nonparametric methods offer such a possibility and thus become of particular practical importance. In this article, we introduce a new R package nparcomp which provides an easy and user-friendly access to rank-based methods for the analysis of unbalanced one-way layouts. It provides procedures performing multiple comparisons and computing simultaneous confidence intervals for the estimated effects which can be easily visualized. The special case of two samples, the nonparametric Behrens-Fisher problem, is included. We illustrate the implemented procedures by examples from biology and medicine.
Climate change in Arctic ecosystems fosters permafrost thaw and makes massive amounts of ancient soil organic carbon (OC) available to microbial breakdown. However, fractions of the organic matter ...(OM) may be protected from rapid decomposition by their association with minerals. Little is known about the effects of mineral‐organic associations (MOA) on the microbial accessibility of OM in permafrost soils and it is not clear which factors control its temperature sensitivity. In order to investigate if and how permafrost soil OC turnover is affected by mineral controls, the heavy fraction (HF) representing mostly MOA was obtained by density fractionation from 27 permafrost soil profiles of the Siberian Arctic. In parallel laboratory incubations, the unfractionated soils (bulk) and their HF were comparatively incubated for 175 days at 5 and 15°C. The HF was equivalent to 70 ± 9% of the bulk CO2 respiration as compared to a share of 63 ± 1% of bulk OC that was stored in the HF. Significant reduction of OC mineralization was found in all treatments with increasing OC content of the HF (HF‐OC), clay‐size minerals and Fe or Al oxyhydroxides. Temperature sensitivity (Q10) decreased with increasing soil depth from 2.4 to 1.4 in the bulk soil and from 2.9 to 1.5 in the HF. A concurrent increase in the metal‐to‐HF‐OC ratios with soil depth suggests a stronger bonding of OM to minerals in the subsoil. There, the younger 14C signature in CO2 than that of the OC indicates a preferential decomposition of the more recent OM and the existence of a MOA fraction with limited access of OM to decomposers. These results indicate strong mineral controls on the decomposability of OM after permafrost thaw and on its temperature sensitivity. Thus, we here provide evidence that OM temperature sensitivity can be attenuated by MOA in permafrost soils.
The study investigated the temperature sensitivity of organic carbon in Siberian permafrost soils. The results showed that although substantial amounts of soil organic carbon are prone to degradation under rising global temperatures, strong mineral controls affect the temperature sensitivity of organic carbon mineralization. We here provide evidence that OM temperature sensitivity can be attenuated by mineral‐organic associations in permafrost soil.
Highlights • Three different T2-mapping sequences are compared at 1.5 and 3T. • T2 values vary significantly between field strengths and MR sequences. • Segmental reference T2 values for each ...sequence at 1.5 and 3T are presented. • Phantom experiments reveal a T1 shine through effect for the T2prep sequence.
Due to the overall high costs, technical replicates are usually omitted in RNA-seq experiments, but several methods exist to generate them artificially. Bootstrapping reads from FASTQ-files has ...recently been used in the context of other NGS analyses and can be used to generate artificial technical replicates. Bootstrapping samples from the columns of the expression matrix has already been used for DNA microarray data and generates a new artificial replicate of the whole experiment. Mixing data of individual samples has been used for data augmentation in machine learning. The aim of this comparison is to evaluate which of these strategies are best suited to study the reproducibility of differential expression and gene-set enrichment analysis in an RNA-seq experiment. To study the approaches under controlled conditions, we performed a new RNA-seq experiment on gene expression changes upon virus infection compared to untreated control samples. In order to compare the approaches for artificial replicates, each of the samples was sequenced twice, i.e. as true technical replicates, and differential expression analysis and GO term enrichment analysis was conducted separately for the two resulting data sets. Although we observed a high correlation between the results from the two replicates, there are still many genes and GO terms that would be selected from one replicate but not from the other. Cluster analyses showed that artificial replicates generated by bootstrapping reads produce it p values and fold changes that are close to those obtained from the true data sets. Results generated from artificial replicates with the approaches of column bootstrap or mixing observations were less similar to the results from the true replicates. Furthermore, the overlap of results among replicates generated by column bootstrap or mixing observations was much stronger than among the true replicates. Artificial technical replicates generated by bootstrapping sequencing reads from FASTQ-files are better suited to study the reproducibility of results from differential expression and GO term enrichment analysis in RNA-seq experiments than column bootstrap or mixing observations. However, FASTQ-bootstrapping is computationally more expensive than the other two approaches. The FASTQ-bootstrapping may be applicable to other applications of high-throughput sequencing.
Flower strips, which are created on arable land by sowing species-rich seed mixtures, are considered to have a high potential to counteract species decline of butterflies in the agricultural ...landscape. However, it remains largely unexplored how various factors (design, habitat quality, landscape context) interact to determine the occurrence of butterflies in flower strips. Therefore, butterflies were surveyed in 15 flower strips differing in age (first and second growing season). Flower strips were compared with 15 field margins, which were adjacent to arable land and were dominated by grasses. The field studies were conducted during two summers (2013, 2014) in Lower Saxony (Germany). Additionally, based on a literature study, 17 environmental variables likely to be decisive for the occurrence of butterflies were identified and recorded during these field studies or analyzed in GIS. Supported by a PCA, 8 environmental variables for flower strips and 7 for field margins, were selected and included in linear mixed-effects models in order to calculate their effect on butterflies.
We documented 19 butterfly species and 1,394 individuals in the flower strips and 13 species and 401 individuals in the field margins. The number of flowering plant species was the key factor for the occurrence of butterflies - both in flower strips and field margins. The diversity of the surrounding landscape (Shannon-Index H) had an additional significant influence on butterflies in flower strips, with more species and individuals being observed on areas with a lower Shannon-Index.
Number of flowering plant species is the key driver of butterfly diversity and abundance, which improves the habitat quality of flower strips in agricultural landscapes. In order to promote butterflies optimally, flower strips must have a good supply of flowers even over several years. This requires careful design and management, as flower supply often decreases with increasing age of the flower strips. The study indicates that flower strips have a particularly high effect in structurally simple landscapes.
Regulatory authorities have encouraged the usage of a risk-based monitoring (RBM) system in clinical trials before trial initiation for detection of potential risks and inclusion of a mitigation plan ...in the monitoring strategy. Several RBM tools were developed after the International Council for Harmonization gave sponsors the flexibility to initiate an approach to enhance quality management in a clinical trial. However, various studies have demonstrated the need for improvement of the available RBM tools as each does not provide a comprehensive overview of the characteristics, focus, and application.
This research lays out a rationale for a risk methodology assessment (RMA) within the RBM system. The core purpose of RMA is to deliver a scientifically based evaluation and decision of any potential risk in a clinical trial. Thereby, a monitoring plan can be developed to elude prior identified risk outcome.
To demonstrate RMA's theoretical approach in practice, a Shiny web application (R Foundation for Statistical Computing) was designed to describe the assessment process of risk analysis and visualization tools that eventually aid in focusing monitoring activities.
RMA focuses on the identification of an individual risk and visualizes its weight on the trial. The scoring algorithm of the presented approach computes the assessment of the individual risk in a radar plot and computes the overall score of the trial. Moreover, RMA's novelty lies in its ability to decrease biased decision making during risk assessment by categorizing risk influence and detectability; a characteristic pivotal to serve RBM in assessing risks, and in contributing to a better understanding in the monitoring technique necessary for developing a functional monitoring plan.
Future research should focus on validating the power of RMAs to demonstrate its efficiency. This would facilitate the process of characterizing the strengths and weaknesses of RMA in practice.
Understanding determinants shaping infection risk of endangered wildlife is a major topic in conservation medicine. The proboscis monkey, Nasalis larvatus, an endemic primate flagship species for ...conservation in Borneo, is endangered through habitat loss, but can still be found in riparian lowland and mangrove forests, and in some protected areas. To assess socioecological and anthropogenic influence on intestinal helminth infections in N. larvatus, 724 fecal samples of harem and bachelor groups, varying in size and the number of juveniles, were collected between June and October 2012 from two study sites in Malaysian Borneo: 634 samples were obtained from groups inhabiting the Lower Kinabatangan Wildlife Sanctuary (LKWS), 90 samples were collected from groups of the Labuk Bay Proboscis Monkey Sanctuary (LBPMS), where monkeys are fed on stationary feeding platforms. Parasite risk was quantified by intestinal helminth prevalence, host parasite species richness (PSR), and eggs per gram feces (epg). Generalized linear mixed effect models were applied to explore whether study site, group type, group size, the number of juveniles per group, and sampling month predict parasite risk. At the LBPMS, prevalence and epg of Trichuris spp., strongylids, and Strongyloides spp. but not Ascaris spp., as well as host PSR were significantly elevated. Only for Strongyloides spp., prevalence showed significant changes between months; at both sites, the beginning rainy season with increased precipitation was linked to higher prevalence, suggesting the external life cycle of Strongyloides spp. to benefit from humidity. Higher prevalence, epgs, and PSR within the LBPMS suggest that anthropogenic factors shape host infection risk more than socioecological factors, most likely via higher re-infection rates and chronic stress. Noninvasive measurement of fecal parasite stages is an important tool for assessing transmission dynamics and infection risks for endangered tropical wildlife. Findings will contribute to healthcare management in nature and in anthropogenically managed environments.
The aim of this study was to evaluate the diagnostic potential of a novel cardiovascular magnetic resonance (CMR) based multiparametric imaging approach in suspected myocarditis and to compare it to ...traditional Lake Louise criteria (LLC).
CMR data from 67 patients with suspected acute myocarditis were retrospectively analyzed. Seventeen age- and gender-matched healthy subjects served as control. T2-mapping data were acquired using a Gradient-Spin-Echo T2-mapping sequence in short-axis orientation. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values and pixel-standard deviation (SD) were recorded. Afterwards, the parameters maxT2 (the highest segmental T2 value) and madSD (the mean absolute deviation (MAD) of the pixel-SDs) were calculated for each subject. Cine sequences in three long axes and a stack of short-axis views covering the left and right ventricle were analyzed using a dedicated feature tracking algorithm.
A multiparametric imaging model containing madSD and LV global circumferential strain (GCS
) resulted in the highest diagnostic performance in receiver operating curve analyses (area under the curve AUC 0.84) when compared to any model containing a single imaging parameter or to LLC (AUC 0.79). Adding late gadolinium enhancement (LGE) to the model resulted in a further increased diagnostic performance (AUC 0.93) and yielded the highest diagnostic sensitivity of 97% and specificity of 77%.
A multiparametric CMR imaging model including the novel T2-mapping derived parameter madSD, the feature tracking derived strain parameter GCS
and LGE yields superior diagnostic sensitivity in suspected acute myocarditis when compared to any imaging parameter alone and to LLC.
Ectoparasitic infections are of particular interest for endangered wildlife, as ectoparasites are potential vectors for inter- and intraspecific pathogen transmission and may be indicators to assess ...the health status of endangered populations. Here, ectoparasite dynamics in sympatric populations of two Malagasy mouse lemur species, Microcebus murinus and M. ravelobensis, were investigated over an 11-month period. Furthermore, the animals' body mass was determined as an indicator of body condition, reflecting seasonal and environmental challenges. Living in sympatry, the two study species experience the same environmental conditions, but show distinct differences in socioecology: Microcebus murinus sleeps in tree holes, either solitarily (males) or sometimes in groups (females only), whereas M. ravelobensis sleeps in mixed-sex groups in more open vegetation.
Both mouse lemur species hosted ticks (Haemaphysalis sp.), lice (Lemurpediculus sp.) and mites (Trombiculidae gen. sp. and Laelaptidae gen. sp.). Host species, as well as temporal variations (month and year), were identified as the main factors influencing infestation. Tick infestation peaked in the late dry season and was significantly more often observed in M. murinus (P = 0.011), while lice infestation was more likely in M. ravelobensis (P < 0.001) and showed a continuous increase over the course of the dry season. Genetic analyses identified Lemurpediculus sp. infesting both mouse lemur species. Ticks morphologically conform to H. lemuris, but genetic analysis showed a clear differentiation of the specimens collected in this study, suggesting a potentially new tick species. Host body mass decreased from the early to the late dry season, indicating nutritional stress during this period, which may render individuals more susceptible to parasitic infections.
Seasonal differences and species-specific variations in sleeping site ecology in terms of sleeping site type and sociality were determined as key factors influencing ectoparasitism in M. murinus and M. ravelobensis. This needs to be taken into account when evaluating ectoparasite infestations at a given time point. The detection of the same parasite species on two closely related and sympatric host species furthermore indicates a potential pathway for disease transmission, not only within but also between lemur species.
The purpose of the present study was to investigate the diagnostic value of T2-mapping in acute myocarditis (ACM) and to define cut-off values for edema detection.
Cardiovascular magnetic resonance ...(CMR) data of 31 patients with ACM were retrospectively analyzed. 30 healthy volunteers (HV) served as a control. Additionally to the routine CMR protocol, T2-mapping data were acquired at 1.5 T using a breathhold Gradient-Spin-Echo T2-mapping sequence in six short axis slices. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values as well as the segmental pixel-standard deviation (SD) were analyzed.
Mean differences of global myocardial T2 or pixel-SD between HV and ACM patients were only small, lying in the normal range of HV. In contrast, variation of segmental T2 values and pixel-SD was much larger in ACM patients compared to HV. In random forests and multiple logistic regression analyses, the combination of the highest segmental T2 value within each patient (maxT2) and the mean absolute deviation (MAD) of log-transformed pixel-SD (madSD) over all 16 segments within each patient proved to be the best discriminators between HV and ACM patients with an AUC of 0.85 in ROC-analysis. In classification trees, a combined cut-off of 0.22 for madSD and of 68 ms for maxT2 resulted in 83% specificity and 81% sensitivity for detection of ACM.
The proposed cut-off values for maxT2 and madSD in the setting of ACM allow edema detection with high sensitivity and specificity and therefore have the potential to overcome the hurdles of T2-mapping for its integration into clinical routine.
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