Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Abteilungen OPUS4-30464 Wissenschaftlicher Artikel Schilcher, Felix; Hilsmann, Lioba; Ankenbrand, Markus J.; Krischke, Markus; Mueller, Martin J.; Steffan-Dewenter, Ingolf; Scheiner, Ricarda Honeybees are buffered against undernourishment during larval stages The negative impact of juvenile undernourishment on adult behavior has been well reported for vertebrates, but relatively little is known about invertebrates. In honeybees, nutrition has long been known to affect task performance and timing of behavioral transitions. Whether and how a dietary restriction during larval development affects the task performance of adult honeybees is largely unknown. We raised honeybees in-vitro, varying the amount of a standardized diet (150 µl, 160 µl, 180 µl in total). Emerging adults were marked and inserted into established colonies. Behavioral performance of nurse bees and foragers was investigated and physiological factors known to be involved in the regulation of social organization were quantified. Surprisingly, adult honeybees raised under different feeding regimes did not differ in any of the behaviors observed. No differences were observed in physiological parameters apart from weight. Honeybees were lighter when undernourished (150 µl), while they were heavier under the overfed treatment (180 µl) compared to the control group raised under a normal diet (160 µl). These data suggest that dietary restrictions during larval development do not affect task performance or physiology in this social insect despite producing clear effects on adult weight. We speculate that possible effects of larval undernourishment might be compensated during the early period of adult life. 2022 Frontiers in Insect Science 2 urn:nbn:de:bvb:20-opus-304646 10.3389/finsc.2022.951317 Julius-von-Sachs-Institut für Biowissenschaften OPUS4-25230 Wissenschaftlicher Artikel Schilcher, Felix; Hilsmann, Lioba; Rauscher, Lisa; Değirmenci, Laura; Krischke, Markus; Krischke, Beate; Ankenbrand, Markus; Rutschmann, Benjamin; Mueller, Martin J.; Steffan-Dewenter, Ingolf; Scheiner, Ricarda In vitro rearing changes social task performance and physiology in honeybees In vitro rearing of honeybee larvae is an established method that enables exact control and monitoring of developmental factors and allows controlled application of pesticides or pathogens. However, only a few studies have investigated how the rearing method itself affects the behavior of the resulting adult honeybees. We raised honeybees in vitro according to a standardized protocol: marking the emerging honeybees individually and inserting them into established colonies. Subsequently, we investigated the behavioral performance of nurse bees and foragers and quantified the physiological factors underlying the social organization. Adult honeybees raised in vitro differed from naturally reared honeybees in their probability of performing social tasks. Further, in vitro-reared bees foraged for a shorter duration in their life and performed fewer foraging trips. Nursing behavior appeared to be unaffected by rearing condition. Weight was also unaffected by rearing condition. Interestingly, juvenile hormone titers, which normally increase strongly around the time when a honeybee becomes a forager, were significantly lower in three- and four-week-old in vitro bees. The effects of the rearing environment on individual sucrose responsiveness and lipid levels were rather minor. These data suggest that larval rearing conditions can affect the task performance and physiology of adult bees despite equal weight, pointing to an important role of the colony environment for these factors. Our observations of behavior and metabolic pathways offer important novel insight into how the rearing environment affects adult honeybees. 2021 Insects 13 1 urn:nbn:de:bvb:20-opus-252305 10.3390/insects13010004 Julius-von-Sachs-Institut für Biowissenschaften OPUS4-14795 Wissenschaftlicher Artikel Ankenbrand, Markus J.; Weber, Lorenz; Becker, Dirk; Förster, Frank; Bemm, Felix TBro: visualization and management of de novo transcriptomes RNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A key challenge, especially for non-computational personnal, is the management of the resulting datasets, consisting of different data types and formats. Here, we present TBro, a flexible de novo transcriptome browser, tackling this challenge. TBro aggregates sequences, their annotation, expression levels as well as differential testing results. It provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro's modular architecture allows easy extension of its functionalities in the future. Especially, the integration of new data types such as proteomic quantifications or array-based gene expression data is straightforward. Thus, TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers. 2016 baw146 Database 2016 urn:nbn:de:bvb:20-opus-147954 10.1093/database/baw146 Theodor-Boveri-Institut für Biowissenschaften OPUS4-12573 Wissenschaftlicher Artikel Sickel, Wiebke; Ankenbrand, Markus J.; Grimmer, Gudrun; Holzschuh, Andrea; Härtel, Stephan; Lanzen, Jonathan; Steffan-Dewenter, Ingolf; Keller, Alexander Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach Background Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing. Results We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000-3,000 high quality reads per sample were sufficient to assess the complete diversity of 95% of the samples. We were able to detect 650 different plant taxa in total, of which 95% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93% increase). Conclusions This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples. 2015 BMC Ecology 15 20 urn:nbn:de:bvb:20-opus-125730 10.1186/s12898-015-0051-y Theodor-Boveri-Institut für Biowissenschaften OPUS4-9645 Wissenschaftlicher Artikel Wolf, Matthias; Chen, Shilin; Song, Jingyuan; Ankenbrand, Markus; Müller, Tobias Compensatory Base Changes in ITS2 Secondary Structures Correlate with the Biological Species Concept Despite Intragenomic Variability in ITS2 Sequences - A Proof of Concept Compensatory base changes (CBCs) in internal transcribed spacer 2 (ITS2) rDNA secondary structures correlate with Ernst Mayr's biological species concept. This hypothesis also referred to as the CBC species concept recently was subjected to large-scale testing, indicating two distinct probabilities. (1) If there is a CBC then there are two different species with a probability of ~0.93. (2) If there is no CBC then there is the same species with a probability of ~0.76. In ITS2 research, however, the main problem is the multicopy nature of ITS2 sequences. Most recently, 454 pyrosequencing data have been used to characterize more than 5000 intragenomic variations of ITS2 regions from 178 plant species, demonstrating that mutation of ITS2 is frequent, with a mean of 35 variants per species, respectively per individual organism. In this study, using those 454 data, the CBC criterion is reconsidered in the light of intragenomic variability, a proof of concept, a necessary criterion, expecting no intragenomic CBCs in variant ITS2 copies. In accordance with the CBC species concept, we could demonstrate that the probability that there is no intragenomic CBC is ~0.99. 2013 PLoS ONE urn:nbn:de:bvb:20-opus-96450 10.1371/journal.pone.0066726 Theodor-Boveri-Institut für Biowissenschaften OPUS4-25760 Wissenschaftlicher Artikel Ankenbrand, Markus Johannes; Lohr, David; Schlötelburg, Wiebke; Reiter, Theresa; Wech, Tobias; Schreiber, Laura Maria Deep learning-based cardiac cine segmentation: Transfer learning application to 7T ultrahigh-field MRI Purpose Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians. Methods A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning. Results Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805). Conclusions This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available. 2021 2179–2191 Magnetic Resonance in Medicine 86 4 urn:nbn:de:bvb:20-opus-257604 10.1002/mrm.28822 Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) OPUS4-32341 unpublished Heidenreich, Julius F.; Gassenmaier, Tobias; Ankenbrand, Markus J.; Bley, Thorsten A.; Wech, Tobias Self-configuring nnU-net pipeline enables fully automatic infarct segmentation in late enhancement MRI after myocardial infarction Purpose To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy. Methods In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework ("nnU-net") was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels. Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the Sørensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson's r correlation and Bland-Altman analysis. Results The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network. Conclusion The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR. accepted version 2021 urn:nbn:de:bvb:20-opus-323418 10.1016/j.ejrad.2021.109817 Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) OPUS4-18879 Wissenschaftlicher Artikel Bemm, Felix; Becker, Dirk; Larisch, Christina; Kreuzer, Ines; Escalante-Perez, Maria; Schulze, Waltraud X.; Ankenbrand, Markus; Van de Weyer, Anna-Lena; Krol, Elzbieta; Al-Rasheid, Khaled A.; Mithöfer, Axel; Weber, Andreas P.; Schultz, Jörg; Hedrich, Rainer Venus flytrap carnivorous lifestyle builds on herbivore defense strategies Although the concept of botanical carnivory has been known since Darwin's time, the molecular mechanisms that allow animal feeding remain unknown, primarily due to a complete lack of genomic information. Here, we show that the transcriptomic landscape of the Dionaea trap is dramatically shifted toward signal transduction and nutrient transport upon insect feeding, with touch hormone signaling and protein secretion prevailing. At the same time, a massive induction of general defense responses is accompanied by the repression of cell death-related genes/processes. We hypothesize that the carnivory syndrome of Dionaea evolved by exaptation of ancient defense pathways, replacing cell death with nutrient acquisition. 2016 812-825 Genome Research 26 6 urn:nbn:de:bvb:20-opus-188799 10.1101/gr.202200.115 Theodor-Boveri-Institut für Biowissenschaften OPUS4-17755 Wissenschaftlicher Artikel Keller, Alexander; Brandel, Annette; Becker, Mira C.; Balles, Rebecca; Abdelmohsen, Usama Ramadan; Ankenbrand, Markus J.; Sickel, Wiebke Wild bees and their nests host Paenibacillus bacteria with functional potential of avail Background: In previous studies, the gram-positive firmicute genus Paenibacillus was found with significant abundances in nests of wild solitary bees. Paenibacillus larvae is well-known for beekeepers as a severe pathogen causing the fatal honey bee disease American foulbrood, and other members of the genus are either secondary invaders of European foulbrood or considered a threat to honey bees. We thus investigated whether Paenibacillus is a common bacterium associated with various wild bees and hence poses a latent threat to honey bees visiting the same flowers. Results: We collected 202 samples from 82 individuals or nests of 13 bee species at the same location and screened each for Paenibacillus using high-throughput sequencing-based 16S metabarcoding. We then isolated the identified strain Paenibacillus MBD-MB06 from a solitary bee nest and sequenced its genome. We did find conserved toxin genes and such encoding for chitin-binding proteins, yet none specifically related to foulbrood virulence or chitinases. Phylogenomic analysis revealed a closer relationship to strains of root-associated Paenibacillus rather than strains causing foulbrood or other accompanying diseases. We found anti-microbial evidence within the genome, confirmed by experimental bioassays with strong growth inhibition of selected fungi as well as gram-positive and gram-negative bacteria. Conclusions: The isolated wild bee associate Paenibacillus MBD-MB06 is a common, but irregularly occurring part of wild bee microbiomes, present on adult body surfaces and guts and within nests especially in megachilids. It was phylogenetically and functionally distinct from harmful members causing honey bee colony diseases, although it shared few conserved proteins putatively toxic to insects that might indicate ancestral predisposition for the evolution of insect pathogens within the group. By contrast, our strain showed anti-microbial capabilities and the genome further indicates abilities for chitin-binding and biofilm-forming, suggesting it is likely a useful associate to avoid fungal penetration of the bee cuticula and a beneficial inhabitant of nests to repress fungal threats in humid and nutrient-rich environments of wild bee nests. 2018 Microbiome 6 229 urn:nbn:de:bvb:20-opus-177554 10.1186/s40168-018-0614-1 Julius-von-Sachs-Institut für Biowissenschaften OPUS4-25761 Wissenschaftlicher Artikel Wech, Tobias; Ankenbrand, Markus Johannes; Bley, Thorsten Alexander; Heidenreich, Julius Frederik A data-driven semantic segmentation model for direct cardiac functional analysis based on undersampled radial MR cine series Purpose Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing. Methods A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses. Results Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data. Conclusion A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis. 2022 972–983 Magnetic Resonance in Medicine 87 2 urn:nbn:de:bvb:20-opus-257616 10.1002/mrm.29017 Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) OPUS4-15634 Dissertation Ankenbrand, Markus Johannes Squeezing more information out of biological data - development and application of bioinformatic tools for ecology, evolution and genomics New experimental methods have drastically accelerated the pace and quantity at which biological data is generated. High-throughput DNA sequencing is one of the pivotal new technologies. It offers a number of novel applications in various fields of biology, including ecology, evolution, and genomics. However, together with those opportunities many new challenges arise. Specialized algorithms and software are required to cope with the amount of data, often requiring substantial training in bioinformatic methods. Another way to make those data accessible to non-bioinformaticians is the development of programs with intuitive user interfaces. In my thesis I developed analyses and programs to tackle current problems with high-throughput data in biology. In the field of ecology this covers the establishment of the bioinformatic workflow for pollen DNA meta-barcoding. Furthermore, I developed an application that facilitates the analysis of ecological communities in the context of their traits. Information from multiple public databases have been aggregated and can now be mapped automatically to existing community tables for interactive inspection. In evolution the new data are used to reconstruct phylogenetic trees from multiple genes. I developed the tool bcgTree to automate this process for bacteria. Many plant genomes have been sequenced in current years. Sequencing reads of those projects also contain data from the chloroplasts. The tool chloroExtractor supports the targeted extraction and analysis of the chloroplast genome. To compare the structure of multiple genomes specialized software is required for calculation and visualization of the relationships. I developed AliTV to address this. In contrast to existing programs for this task it allows interactive adjustments of produced graphics. Thus, facilitating the discovery of biologically relevant information. Another application I developed helps to analyze transcriptomes even if no reference genome is present. This is achieved by aggregating the different pieces of information, like functional annotation and expression level, for each transcript in a web platform. Scientists can then search, filter, subset, and visualize the transcriptome. Together the methods and tools expedite insights into biological systems that were not possible before. 2018 urn:nbn:de:bvb:20-opus-156344 Graduate School of Life Sciences OPUS4-20174 Wissenschaftlicher Artikel Voulgari-Kokota, Anna; Ankenbrand, Markus J.; Grimmer, Gudrun; Steffan-Dewenter, Ingolf; Keller, Alexander Linking pollen foraging of megachilid bees to their nest bacterial microbiota Solitary bees build their nests by modifying the interior of natural cavities, and they provision them with food by importing collected pollen. As a result, the microbiota of the solitary bee nests may be highly dependent on introduced materials. In order to investigate how the collected pollen is associated with the nest microbiota, we used metabarcoding of the ITS2 rDNA and the 16S rDNA to simultaneously characterize the pollen composition and the bacterial communities of 100 solitary bee nest chambers belonging to seven megachilid species. We found a weak correlation between bacterial and pollen alpha diversity and significant associations between the composition of pollen and that of the nest microbiota, contributing to the understanding of the link between foraging and bacteria acquisition for solitary bees. Since solitary bees cannot establish bacterial transmission routes through eusociality, this link could be essential for obtaining bacterial symbionts for this group of valuable pollinators. 2019 10788–10800 Ecology and Evolution 2019 9 urn:nbn:de:bvb:20-opus-201749 10.1002/ece3.5599 Theodor-Boveri-Institut für Biowissenschaften OPUS4-21276 Wissenschaftlicher Artikel Hesselbach, Hannah; Seeger, Johannes; Schilcher, Felix; Ankenbrand, Markus; Scheiner, Ricarda Chronic exposure to the pesticide flupyradifurone can lead to premature onset of foraging in honeybees Apis mellifera 1.Honeybees Apis mellifera and other pollinating insects suffer from pesticides in agricultural landscapes. Flupyradifurone is the active ingredient of a novel pesticide by the name of 'Sivanto', introduced by Bayer AG (Crop Science Division, Monheim am Rhein, Germany). It is recommended against sucking insects and marketed as 'harmless' to honeybees. Flupyradifurone binds to nicotinergic acetylcholine receptors like neonicotinoids, but it has a different mode of action. So far, little is known on how sublethal flupyradifurone doses affect honeybees. 2. We chronically applied a sublethal and field-realistic concentration of flupyradifurone to test for long-term effects on flight behaviour using radio-frequency identification. We examined haematoxylin/eosin-stained brains of flupyradifurone-treated bees to investigate possible changes in brain morphology and brain damage. 3. A field-realistic flupyradifurone dose of approximately 1.0 μg/bee/day significantly increased mortality. Pesticide-treated bees initiated foraging earlier than control bees. No morphological damage in the brain was observed. 4. Synthesis and applications. The early onset of foraging induced by a chronical application of flupyradifurone could be disadvantageous for honeybee colonies, reducing the period of in-hive tasks and life expectancy of individuals. Radio-frequency identification technology is a valuable tool for studying pesticide effects on lifetime foraging behaviour of insects. 2020 609-618 Journal of Applied Ecology 57 3 urn:nbn:de:bvb:20-opus-212769 10.1111/1365-2664.13555 Theodor-Boveri-Institut für Biowissenschaften OPUS4-21809 Wissenschaftlicher Artikel Hock, Michael; Terekhov, Maxim; Stefanescu, Maria Roxana; Lohr, David; Herz, Stefan; Reiter, Theresa; Ankenbrand, Markus; Kosmala, Aleksander; Gassenmaier, Tobias; Juchem, Christoph; Schreiber, Laura Maria B\(_{0}\) shimming of the human heart at 7T Purpose Inhomogeneities of the static magnetic B\(_{0}\) field are a major limiting factor in cardiac MRI at ultrahigh field (≥ 7T), as they result in signal loss and image distortions. Different magnetic susceptibilities of the myocardium and surrounding tissue in combination with cardiac motion lead to strong spatio-temporal B\(_{0}\)-field inhomogeneities, and their homogenization (B0 shimming) is a prerequisite. Limitations of state-of-the-art shimming are described, regional B\(_{0}\) variations are measured, and a methodology for spherical harmonics shimming of the B\(_{0}\) field within the human myocardium is proposed. Methods The spatial B\(_{0}\)-field distribution in the heart was analyzed as well as temporal B\(_{0}\)-field variations in the myocardium over the cardiac cycle. Different shim region-of-interest selections were compared, and hardware limitations of spherical harmonics B\(_{0}\) shimming were evaluated by calibration-based B0-field modeling. The role of third-order spherical harmonics terms was analyzed as well as potential benefits from cardiac phase-specific shimming. Results The strongest B\(_{0}\)-field inhomogeneities were observed in localized spots within the left-ventricular and right-ventricular myocardium and varied between systolic and diastolic cardiac phases. An anatomy-driven shim region-of-interest selection allowed for improved B\(_{0}\)-field homogeneity compared with a standard shim region-of-interest cuboid. Third-order spherical harmonics terms were demonstrated to be beneficial for shimming of these myocardial B\(_{0}\)-field inhomogeneities. Initial results from the in vivo implementation of a potential shim strategy were obtained. Simulated cardiac phase-specific shimming was performed, and a shim term-by-term analysis revealed periodic variations of required currents. Conclusion Challenges in state-of-the-art B\(_{0}\) shimming of the human heart at 7 T were described. Cardiac phase-specific shimming strategies were found to be superior to vendor-supplied shimming. 2021 14 Magnetic Resonance in Medicine 85 1 182 196 urn:nbn:de:bvb:20-opus-218096 10.1002/mrm.28423 Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) OPUS4-25916 Wissenschaftlicher Artikel Ankenbrand, Markus J.; Shainberg, Liliia; Hock, Michael; Lohr, David; Schreiber, Laura M. Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance. Results We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model. Conclusions Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable. 2021 27 BMC Medical Imaging 21 1 urn:nbn:de:bvb:20-opus-259169 10.1186/s12880-021-00551-1 Deutsches Zentrum für Herzinsuffizienz (DZHI) OPUS4-25821 Wissenschaftlicher Artikel Vedder, Daniel; Ankenbrand, Markus; Sarmento Cabral, Juliano Dealing with software complexity in individual-based models Individual-based models are doubly complex: as well as representing complex ecological systems, the software that implements them is complex in itself. Both forms of complexity must be managed to create reliable models. However, the ecological modelling literature to date has focussed almost exclusively on the biological complexity. Here, we discuss methods for containing software complexity. Strategies for containing complexity include avoiding, subdividing, documenting and reviewing it. Computer science has long-established techniques for all of these strategies. We present some of these techniques and set them in the context of IBM development, giving examples from published models. Techniques for avoiding software complexity are following best practices for coding style, choosing suitable programming languages and file formats and setting up an automated workflow. Complex software systems can be made more tractable by encapsulating individual subsystems. Good documentation needs to take into account the perspectives of scientists, users and developers. Code reviews are an effective way to check for errors, and can be used together with manual or automated unit and integration tests. Ecological modellers can learn from computer scientists how to deal with complex software systems. Many techniques are readily available, but must be disseminated among modellers. There is a need for further work to adapt software development techniques to the requirements of academic research groups and individual-based modelling. 2021 2324–2333 Methods in Ecology and Evolution 12 12 urn:nbn:de:bvb:20-opus-258214 10.1111/2041-210X.13716 Center for Computational and Theoretical Biology