Remote sensing of emperor penguin abundance and breeding success.

Emperor penguins (Aptenodytes forsteri) are under increasing environmental pressure. Monitoring colony size and population trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when light conditions levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that can predict the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are rare or unavailable.

Missing Genomic Resources for the Next Generation of Environmental Risk Assessment.

Environmental risk assessment traditionally relies on a wide range of in vivo testing to assess the potential hazards of chemicals in the environment. These tests are often time-consuming and costly and can cause test organisms' suffering. Recent developments of reliable low-cost alternatives, both in vivo- and in silico-based, opened the door to reconsider current toxicity assessment. However, many of these new approach methodologies (NAMs) rely on high-quality annotated genomes for surrogate species of regulatory risk assessment. Currently, a lack of genomic information slows the process of NAM development. Here, we present a phylogenetically resolved overview of missing genomic resources for surrogate species within a regulatory ecotoxicological risk assessment. We call for an organized and systematic effort within the (regulatory) ecotoxicological community to provide these missing genomic resources. Further, we discuss the potential of a standardized genomic surrogate species landscape to enable a robust and nonanimal-reliant ecotoxicological risk assessment in the systems ecotoxicology era.

Stereotactic body radiotherapy with volumetric intensity-modulated arc therapy and flattening filter-free beams: dosimetric considerations.

PURPOSE: The present study comparatively evaluates the impact of energy-matched flattening filter-free (FFF) photon beams with different energy levels on the physical-dosimetric quality of lung and liver stereotactic body radiotherapy (SBRT) treatment plans. METHODS: For this purpose, 54 different lung and liver lesions from 44 patients who had already received SBRT combined with volumetric modulated arc therapy (VMAT) were included in this retrospective planning study. Planning computed tomography scans already available were used for the renewed planning with 6 MV, 6 MV-FFF, 10 MV, and 10 MV-FFF under constant planning objectives. The treatment delivery data, dosimetric distributions, and dose-volume histograms as well as parameters such as the conformity index and gradient indices were the basis for the evaluation and comparison of treatment plans. RESULTS: A significant reduction of beam-on time (BOT) was achieved due to the high dose rates of FFF beams. In addition, we showed that for FFF beams compared to flattened beams of the same energy level, smaller planning target volumes (PTV) require fewer monitor units (MU) than larger PTVs. An equal to slightly superior target volume coverage and sparing of healthy tissue as well as organs at risk in both lung and liver lesions were found. Significant differences were seen mainly in the medium to lower dose range. CONCLUSION: We found that FFF beams together with VMAT represent an excellent combination for SBRT of lung or liver lesions with shortest BOT for 10 MV-FFF but significant dose savings for 6 MV-FFF in lung lesions.

Fiber alignment in 3D collagen networks as a biophysical marker for cell contractility.

Cells cultured in 3D fibrous biopolymer matrices exert traction forces on their environment that induce deformations and remodeling of the fiber network. By measuring these deformations, the traction forces can be reconstructed if the mechanical properties of the matrix and the force-free matrix configuration are known. These requirements limit the applicability of traction force reconstruction in practice. In this study, we test whether force-induced matrix remodeling can instead be used as a proxy for cellular traction forces. We measure the traction forces of hepatic stellate cells and different glioblastoma cell lines and quantify matrix remodeling by measuring the fiber orientation and fiber density around these cells. In agreement with simulated fiber networks, we demonstrate that changes in local fiber orientation and density are directly related to cell forces. By resolving Rho-kinase (ROCK) inhibitor-induced changes of traction forces, fiber alignment, and fiber density in hepatic stellate cells, we show that the method is suitable for drug screening assays. We conclude that differences in local fiber orientation and density, which are easily measurable, can be used as a qualitative proxy for changes in traction forces. The method is available as an open-source Python package with a graphical user interface.

Risk stratification by anamnesis increases SARS-CoV-2 test efficiency in cancer patients.

PURPOSE: To evaluate the impact of testing asymptomatic cancer patients, we analyzed all tests for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) before and during radiotherapy at a tertiary cancer center throughout the second wave of the pandemic in Germany. METHODS: Results of all real-time polymerase chain reaction (RT-PCR) tests for SARS-CoV­2 performed at our radio-oncology department between 13 October 2020 and 11 March 2021 were included. Clinical data and anamnestic information at the time of testing were documented and examined for (i) the presence of COVID-19-related symptoms and (ii) virus-related anamnesis (high-risk [prior positive test or contact to a positive tested person within the last 14 days] or low-risk [inconspicuous anamnesis within the last 14 days]). RESULTS: A total of 1056 SARS-CoV­2 tests in 543 patients were analyzed. Of those, 1015 tests were performed in asymptomatic patients and 41 tests in patients with COVID-19-associated symptoms. Two of 940 (0.2%) tests in asymptomatic patients with low-risk anamnesis and three of 75 (4.0%) tests in asymptomatic patients with high-risk anamnesis showed a positive result. For symptomatic patients, SARS-CoV­2 was detected in three of 36 (8.3%) low-risk and three of five (60.0%) high-risk tests. CONCLUSION: To the best of our knowledge, this is the first study evaluating the correlation between individual risk factors and positivity rates of SARS-CoV­2 tests in cancer patients. The data demonstrate that clinical and anamnestic assessment is a simple and effective measure to distinctly increase SARS-CoV­2 test efficiency. This might enable cancer centers to adjust test strategies in asymptomatic patients, especially when test resources are scarce.

Plant PhysioSpace: a robust tool to compare stress response across plant species.

Generalization of transcriptomics results can be achieved by comparison across experiments. This generalization is based on integration of interrelated transcriptomics studies into a compendium. Such a focus on the bigger picture enables both characterizations of the fate of an organism and distinction between generic and specific responses. Numerous methods for analyzing transcriptomics datasets exist. Yet, most of these methods focus on gene-wise dimension reduction to obtain marker genes and gene sets for, for example, pathway analysis. Relying only on isolated biological modules might result in missing important confounders and relevant contexts. We developed a method called Plant PhysioSpace, which enables researchers to compute experimental conditions across species and platforms without a priori reducing the reference information to specific gene sets. Plant PhysioSpace extracts physiologically relevant signatures from a reference dataset (i.e. a collection of public datasets) by integrating and transforming heterogeneous reference gene expression data into a set of physiology-specific patterns. New experimental data can be mapped to these patterns, resulting in similarity scores between the acquired data and the extracted compendium. Because of its robustness against platform bias and noise, Plant PhysioSpace can function as an inter-species or cross-platform similarity measure. We have demonstrated its success in translating stress responses between different species and platforms, including single-cell technologies. We have also implemented two R packages, one software and one data package, and a Shiny web application to facilitate access to our method and precomputed models.

Cryopreservation impairs 3-D migration and cytotoxicity of natural killer cells.

Natural killer (NK) cells are important effector cells in the immune response to cancer. Clinical trials on adoptively transferred NK cells in patients with solid tumors, however, have thus far been unsuccessful. As NK cells need to pass stringent safety evaluation tests before clinical use, the cells are cryopreserved to bridge the necessary evaluation time. Standard degranulation and chromium release cytotoxicity assays confirm the ability of cryopreserved NK cells to kill target cells. Here, we report that tumor cells embedded in a 3-dimensional collagen gel, however, are killed by cryopreserved NK cells at a 5.6-fold lower rate compared to fresh NK cells. This difference is mainly caused by a 6-fold decrease in the fraction of motile NK cells after cryopreservation. These findings may explain the persistent failure of NK cell therapy in patients with solid tumors and highlight the crucial role of a 3-D environment for testing NK cell function.

Collective forces of tumor spheroids in three-dimensional biopolymer networks.

We describe a method for quantifying the contractile forces that tumor spheroids collectively exert on highly nonlinear three-dimensional collagen networks. While three-dimensional traction force microscopy for single cells in a nonlinear matrix is computationally complex due to the variable cell shape, here we exploit the spherical symmetry of tumor spheroids to derive a scale-invariant relationship between spheroid contractility and the surrounding matrix deformations. This relationship allows us to directly translate the magnitude of matrix deformations to the total contractility of arbitrarily sized spheroids. We show that our method is accurate up to strains of 50% and remains valid even for irregularly shaped tissue samples when considering only the deformations in the far field. Finally, we demonstrate that collective forces of tumor spheroids reflect the contractility of individual cells for up to 1 hr after seeding, while collective forces on longer timescales are guided by mechanical feedback from the extracellular matrix.

Durotropic Growth of Pollen Tubes.

To reach the female gametophyte, growing pollen tubes must penetrate different tissues within the pistil, the female reproductive organ of a flower. Past research has identified various chemotropic cues that guide pollen tubes through the transmitting tract of the pistil, which represents the longest segment of its growth path. In addition, physical mechanisms also play a role in pollen tube guidance; however, these processes remain poorly understood. Here we show that pollen tubes from plants with solid transmitting tracts actively respond to the stiffness of the environment. We found that pollen tubes from Nicotiana tabacum and other plant species with a solid or semisolid transmitting tract increase their growth rate in response to an increasing matrix stiffness. By contrast, pollen tubes from Lilium longiflorum and other plant species with a hollow transmitting tract decrease their growth rate with increasing matrix stiffness, even though the forces needed to maintain a constant growth rate remain far below the maximum penetration force these pollen tubes are able to generate. Moreover, when confronted with a transition from a softer to a stiffer matrix, pollen tubes from N. tabacum display a greater ability to penetrate into a stiffer matrix compared with pollen tubes from L. longiflorum, even though the maximum force generated by pollen tubes from N. tabacum (11 µN) is smaller than the maximum force generated by pollen tubes from L. longiflorum (36 µN). These findings demonstrate a mechano-sensitive growth behavior, termed here durotropic growth, that is only expressed in pollen tubes from plants with a solid or semisolid transmitting tract and thus may contribute to an effective pollen tube guidance within the pistil.

Measurement of Skeletal Muscle Fiber Contractility with High-Speed Traction Microscopy.

We describe a technique for simultaneous quantification of the contractile forces and cytosolic calcium dynamics of muscle fibers embedded in three-dimensional biopolymer gels under auxotonic loading conditions. We derive a scaling law for linear elastic matrices such as basement membrane extract hydrogels (Matrigel) that allows us to measure contractile force from the shape of the relaxed and contracted muscle cell and the Young's modulus of the matrix without further knowledge of the matrix deformations surrounding the cell and without performing computationally intensive inverse force reconstruction algorithms. We apply our method to isolated mouse flexor digitorum brevis (FDB) fibers that are embedded in 10 mg/mL Matrigel. Upon electrical stimulation, individual FDB fibers show twitch forces of 0.37 ± 0.15 µN and tetanic forces (100-Hz stimulation frequency) of 2.38 ± 0.71 µN, corresponding to a tension of 0.44 ± 0.25 kPa and 2.53 ± 1.17 kPa, respectively. Contractile forces of FDB fibers increase in response to caffeine and the troponin-calcium stabilizer tirasemtiv, similar to responses measured in whole muscle. From simultaneous high-speed measurements of cell length changes and cytosolic calcium concentration using confocal line scanning at a frequency of 2048 Hz, we show that twitch and tetanic force responses to electric pulses follow the low-pass filtered calcium signal. In summary, we present a technically simple high-speed method for measuring contractile forces and cytosolic calcium dynamics of single muscle fibers. We expect that our method will help to reduce preparation time, costs, and the number of sacrificed animals needed for experiments such as drug testing.

Breast Cancer Cells Adapt Contractile Forces to Overcome Steric Hindrance.

Cell migration through the extracellular matrix is governed by the interplay between cell-generated propulsion forces, adhesion forces, and resisting forces arising from the steric hindrance of the matrix. Steric hindrance in turn depends on matrix porosity, matrix deformability, cell size, and cell deformability. In this study, we investigate how cells respond to changes in steric hindrance that arise from altered cell mechanical properties. Specifically, we measure traction forces, cell morphology, and invasiveness of MDA-MB 231 breast cancer cells in three-dimensional collagen gels. To modulate cell mechanical properties, we either decrease nuclear deformability by twofold overexpression of the nuclear protein lamin A or we introduce into the cells stiff polystyrene beads with a diameter larger than the average matrix pore size. Despite this increase of steric hindrance, we find that cell invasion is only marginally inhibited, as measured by the fraction of motile cells and the mean invasion depth. To compensate for increased steric hindrance, cells employ two alternative strategies. Cells with higher nuclear stiffness increase their force polarity, whereas cells with large beads increase their net contractility. Under both conditions, the collagen matrix surrounding the cells stiffens dramatically and carries increased strain energy, suggesting that increased force polarity and increased net contractility are functionally equivalent strategies for overcoming an increased steric hindrance.

CameraTransform: A Python package for perspective corrections and image mapping.

Camera images and video recordings are simple and non-invasive tools to investigate animals in their natural habitat. Quantitative evaluations, however, often require an exact reconstruction of object positions, sizes, and distances in the image. Here, we provide an open source software package to perform such calculations. Our approach allows the user to correct for perspective distortion, transform images to "bird's-eye" view projections, or transform image-coordinates to real-world coordinates and vice versa. The extrinsic camera parameters that are necessary to perform such image corrections and transformations (elevation, tilt/roll angle, and heading of the camera) are obtained from the image using contextual information such as a visible horizon, GPS coordinates of landmarks, known object sizes, or images of the same object obtained from different viewing angles. All mathematical operations are implemented in the Python package CameraTransform. The performance of the implementation is evaluated using computer-generated synthetic images with known camera parameters. Moreover, we test our algorithm on images of emperor penguin colonies, and demonstrate that the camera tilt and roll angles can be estimated with an error of less than one degree, and the camera elevation with an error of less than 5%. The CameraTransform software package simplifies camera matrix-based image transformations and the extraction of quantitative image information. An extensive documentation and usage examples in an ecological context are provided at http://cameratransform.readthedocs.io.

Bayesian model selection for complex dynamic systems.

Time series generated by complex systems like financial markets and the earth's atmosphere often represent superstatistical random walks: on short time scales, the data follow a simple low-level model, but the model parameters are not constant and can fluctuate on longer time scales according to a high-level model. While the low-level model is often dictated by the type of the data, the high-level model, which describes how the parameters change, is unknown in most cases. Here we present a computationally efficient method to infer the time course of the parameter variations from time-series with short-range correlations. Importantly, this method evaluates the model evidence to objectively select between competing high-level models. We apply this method to detect anomalous price movements in financial markets, characterize cancer cell invasiveness, identify historical policies relevant for working safety in coal mines, and compare different climate change scenarios to forecast global warming.

Data sets for author name disambiguation: an empirical analysis and a new resource.

Data sets of publication meta data with manually disambiguated author names play an important role in current author name disambiguation (AND) research. We review the most important data sets used so far, and compare their respective advantages and shortcomings. From the results of this review, we derive a set of general requirements to future AND data sets. These include both trivial requirements, like absence of errors and preservation of author order, and more substantial ones, like full disambiguation and adequate representation of publications with a small number of authors and highly variable author names. On the basis of these requirements, we create and make publicly available a new AND data set, SCAD-zbMATH. Both the quantitative analysis of this data set and the results of our initial AND experiments with a naive baseline algorithm show the SCAD-zbMATH data set to be considerably different from existing ones. We consider it a useful new resource that will challenge the state of the art in AND and benefit the AND research community.

Unique features of a global human ectoparasite identified through sequencing of the bed bug genome.

The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host-symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human-bed bug and symbiont-bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite.

Three-dimensional force microscopy of cells in biopolymer networks.

We describe a technique for the quantitative measurement of cell-generated forces in highly nonlinear three-dimensional biopolymer networks that mimic the physiological situation of living cells. We computed forces of MDA-MB-231 breast carcinoma cells from the measured network deformations around the cells using a finite-element approach based on a constitutive equation that captures the complex mechanical properties of diverse biopolymers such as collagen gels, fibrin gels and Matrigel. Our measurements show that breast carcinoma cells cultured in collagen gels generated nearly constant forces regardless of the collagen concentration and matrix stiffness. Furthermore, time-lapse force measurements showed that these cells migrated in a gliding motion with alternating phases of high and low contractility, elongation, migratory speed and persistence.

Migration in Confined 3D Environments Is Determined by a Combination of Adhesiveness, Nuclear Volume, Contractility, and Cell Stiffness.

In cancer metastasis and other physiological processes, cells migrate through the three-dimensional (3D) extracellular matrix of connective tissue and must overcome the steric hindrance posed by pores that are smaller than the cells. It is currently assumed that low cell stiffness promotes cell migration through confined spaces, but other factors such as adhesion and traction forces may be equally important. To study 3D migration under confinement in a stiff (1.77 MPa) environment, we use soft lithography to fabricate polydimethylsiloxane (PDMS) devices consisting of linear channel segments with 20 µm length, 3.7 µm height, and a decreasing width from 11.2 to 1.7 µm. To study 3D migration in a soft (550 Pa) environment, we use self-assembled collagen networks with an average pore size of 3 µm. We then measure the ability of four different cancer cell lines to migrate through these 3D matrices, and correlate the results with cell physical properties including contractility, adhesiveness, cell stiffness, and nuclear volume. Furthermore, we alter cell adhesion by coating the channel walls with different amounts of adhesion proteins, and we increase cell stiffness by overexpression of the nuclear envelope protein lamin A. Although all cell lines are able to migrate through the smallest 1.7 µm channels, we find significant differences in the migration velocity. Cell migration is impeded in cell lines with larger nuclei, lower adhesiveness, and to a lesser degree also in cells with lower contractility and higher stiffness. Our data show that the ability to overcome the steric hindrance of the matrix cannot be attributed to a single cell property but instead arises from a combination of adhesiveness, nuclear volume, contractility, and cell stiffness.

Superstatistical analysis and modelling of heterogeneous random walks.

Stochastic time series are ubiquitous in nature. In particular, random walks with time-varying statistical properties are found in many scientific disciplines. Here we present a superstatistical approach to analyse and model such heterogeneous random walks. The time-dependent statistical parameters can be extracted from measured random walk trajectories with a Bayesian method of sequential inference. The distributions and correlations of these parameters reveal subtle features of the random process that are not captured by conventional measures, such as the mean-squared displacement or the step width distribution. We apply our new approach to migration trajectories of tumour cells in two and three dimensions, and demonstrate the superior ability of the superstatistical method to discriminate cell migration strategies in different environments. Finally, we show how the resulting insights can be used to design simple and meaningful models of the underlying random processes.

RNA-Seq transcriptome analysis to identify genes involved in metabolism-based diclofop resistance in Lolium rigidum.

Weed control failures due to herbicide resistance are an increasing and worldwide problem that significantly affect crop yields. Metabolism-based herbicide resistance (referred to as metabolic resistance) in weeds is not well characterized at the genetic level. An RNA-Seq transcriptome analysis was used to find candidate genes that conferred metabolic resistance to the herbicide diclofop in a diclofop-resistant population (R) of the major global weed Lolium rigidum. A reference cDNA transcriptome (19 623 contigs) was assembled and assigned putative annotations. Global gene expression was measured using Illumina reads from untreated control, adjuvant-only control, and diclofop treatment of R and susceptible (S). Contigs that showed constitutive expression differences between untreated R and untreated S were selected for further validation analysis, including 11 contigs putatively annotated as cytochrome P450 (CytP450), glutathione transferase (GST), or glucosyltransferase (GT), and 17 additional contigs with annotations related to metabolism or signal transduction. In a forward genetics validation experiment, nine contigs had constitutive up-regulation in R individuals from a segregating F2 population, including three CytP450, one nitronate monooxygenase (NMO), three GST, and one GT. Principal component analysis using these nine contigs differentiated F2 -R from F2 -S individuals. In a physiological validation experiment in which 2,4-D pre-treatment induced diclofop protection in S individuals due to increased metabolism, seven of the nine genetically validated contigs were induced significantly. Four contigs (two CytP450, NMO, and GT) were consistently highly expressed in nine field-evolved metabolic resistant L. rigidum populations. These four contigs were strongly associated with the resistance phenotype and are major candidates for contributing to metabolic diclofop resistance.