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Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.
Mapping Sleeping Bees within Their Nest: Spatial and Temporal Analysis of Worker Honey Bee Sleep
(2014)
Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns.
Cytotoxic T lymphocytes are effector CD8\(^{+}\) T cells that eradicate infected and malignant cells. Here we show that the transcription factor NFATc1 controls the cytotoxicity of mouse cytotoxic T lymphocytes. Activation of Nfatc1\(^{-/-}\) cytotoxic T lymphocytes showed a defective cytoskeleton organization and recruitment of cytosolic organelles to immunological synapses. These cells have reduced cytotoxicity against tumor cells, and mice with NFATc1-deficient T cells are defective in controlling Listeria infection. Transcriptome analysis shows diminished RNA levels of numerous genes in Nfatc1\(^{-/-}\) CD8\(^{+}\) T cells, including Tbx21, Gzmb and genes encoding cytokines and chemokines, and genes controlling glycolysis. Nfatc1\(^{-/-}\), but not Nfatc2\(^{-/-}\) CD8\(^{+}\) T cells have an impaired metabolic switch to glycolysis, which can be restored by IL-2. Genome-wide ChIP-seq shows that NFATc1 binds many genes that control cytotoxic T lymphocyte activity. Together these data indicate that NFATc1 is an important regulator of cytotoxic T lymphocyte effector functions.
Early detection of cancer holds high promise for reducing cancer-related mortality. Detection of circulating tumor-specific nucleic acids holds promise, but sensitivity and specificity issues remain with current technology. We studied cell-free RNA (cfRNA) in patients with non-small cell lung cancer (NSCLC; n = 56 stage IV, n = 39 stages I-III), pancreatic cancer (PDAC, n = 20 stage III), malignant melanoma (MM, n = 12 stage III-IV), urothelial bladder cancer (UBC, n = 22 stage II and IV), and 65 healthy controls by means of next generation sequencing (NGS) and real-time droplet digital PCR (RT-ddPCR). We identified 192 overlapping upregulated transcripts in NSCLC and PDAC by NGS, more than 90% of which were noncoding. Previously reported transcripts (e.g., HOTAIRM1) were identified. Plasma cfRNA transcript levels of POU6F2-AS2 discriminated NSCLC from healthy donors (AUC = 0.82 and 0.76 for stages IV and I–III, respectively) and significantly associated (p = 0.017) with the established tumor marker Cyfra 21-1. cfRNA yield and POU6F2-AS transcript abundance discriminated PDAC patients from healthy donors (AUC = 1.0). POU6F2-AS2 transcript was significantly higher in MM (p = 0.044). In summary, our findings support further validation of cfRNA detection by RT-ddPCR as a biomarker for early detection of solid cancers.
Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided.
Biodiversity loss can affect the viability of ecosystems by decreasing the ability of communities to respond to environmental change and disturbances. Agricultural intensification is a major driver of biodiversity loss and has multiple components operating at different spatial scales: from in-field management intensity to landscape-scale simplification. Here we show that landscape-level effects dominate functional community composition and can even buffer the effects of in-field management intensification on functional homogenization, and that animal communities in real-world managed landscapes show a unified response (across orders and guilds) to both landscape-scale simplification and in-field intensification. Adults and larvae with specialized feeding habits, species with shorter activity periods and relatively small body sizes are selected against in simplified landscapes with intense in-field management. Our results demonstrate that the diversity of land cover types at the landscape scale is critical for maintaining communities, which are functionally diverse, even in landscapes where in-field management intensity is high.
In effector T and B cells immune receptor signals induce within minutes a rise of intracellular Ca++, the activation of the phosphatase calcineurin and the translocation of NFAT transcription factors from cytosol to nucleus. In addition to this first wave of NFAT activation, in a second step the occurrence of NFATc1/αA, a short isoform of NFATc1, is strongly induced. Upon primary stimulation of lymphocytes the induction of NFATc1/αA takes place during the G1 phase of cell cycle. Due to an auto-regulatory feedback circuit high levels of NFATc1/αA are kept constant during persistent immune receptor stimulation. Contrary to NFATc2 and further NFATc proteins which dampen lymphocyte proliferation, induce anergy and enhance activation induced cell death (AICD), NFATc1/αA supports antigenmediated proliferation and protects lymphocytes against rapid AICD. Whereas high concentrations of NFATc1/αA can also lead to apoptosis, in collaboration with NF-κB-inducing co-stimulatory signals they support the survival of mature lymphocytes in late phases after their activation. However, if dysregulated, NFATc1/αA appears to contribute to lymphoma genesis and – as we assume – to further disorders of the lymphoid system. While the molecular details of NFATc1/αA action and its contribution to lymphoid disorders have to be investigated, NFATc1/αA differs in its generation and function markedly from all the other NFAT proteins which are expressed in lymphoid cells. Therefore, it represents a prime target for causal therapies of immune disorders in future.
By virtue of mitochondrial control of energy production, reactive oxygen species (ROS) generation, and maintenance of Ca\(^{2+}\) homeostasis, mitochondria play an essential role in modulating T cell function. The mitochondrial Ca\(^{2+}\) uniporter (MCU) is the pore-forming unit in the main protein complex mediating mitochondrial Ca\(^{2+}\) uptake. Recently, MCU has been shown to modulate Ca\(^{2+}\) signals at subcellular organellar interfaces, thus fine-tuning NFAT translocation and T cell activation. The mechanisms underlying this modulation and whether MCU has additional T cell subpopulation-specific effects remain elusive. However, mice with germline or tissue-specific ablation of Mcu did not show impaired T cell responses in vitro or in vivo, indicating that ‘chronic’ loss of MCU can be functionally compensated in lymphocytes. The current work aimed to specifically investigate whether and how MCU influences the suppressive potential of regulatory CD4 T cells (Treg). We show that, in contrast to genetic ablation, acute siRNA-mediated downregulation of Mcu in murine Tregs results in a significant reduction both in mitochondrial Ca\(^{2+}\) uptake and in the suppressive capacity of Tregs, while the ratios of Treg subpopulations and the expression of hallmark transcription factors were not affected. These findings suggest that permanent genetic inactivation of MCU may result in compensatory adaptive mechanisms, masking the effects on the suppressive capacity of Tregs.
Metaphors, Dead and Alive
(2023)
This paper examins how the medieval distinction between proper and improper signification can give a plausible explanation of both metaphorical use and the usual transformations a language can undergo. I will show how Thomas Aquinas distinguishes between ordinary ambiguous terms and metaphors, whereas William of Ockham and Walter Burley do not leave room for this distinction. I will argue that Ockham’s conception of transfer of sense through subsequent institution of words is best thought of as an explanation of how ordinary usage can contain ambiguities, whereas Burley’s conception of transfer of sense without new imposition is more plausible when it comes to explaining metaphors. If metaphorical use is lumped together with equivocation, the account of how they work cannot do full justice to either, an insight that we already find in Peter Abelard, if not in Boethius.
Earth observation time series are well suited to monitor global surface dynamics. However, data products that are aimed at assessing large-area dynamics with a high temporal resolution often face various error sources (e.g., retrieval errors, sampling errors) in their acquisition chain. Addressing uncertainties in a spatiotemporal consistent manner is challenging, as extensive high-quality validation data is typically scarce. Here we propose a new method that utilizes time series inherent information to assess the temporal interpolation uncertainty of time series datasets. For this, we utilized data from the DLR-DFD Global WaterPack (GWP), which provides daily information on global inland surface water. As the time series is primarily based on optical MODIS (Moderate Resolution Imaging Spectroradiometer) images, the requirement of data gap interpolation due to clouds constitutes the main uncertainty source of the product. With a focus on different temporal and spatial characteristics of surface water dynamics, seven auxiliary layers were derived. Each layer provides probability and reliability estimates regarding water observations at pixel-level. This enables the quantification of uncertainty corresponding to the full spatiotemporal range of the product. Furthermore, the ability of temporal layers to approximate unknown pixel states was evaluated for stratified artificial gaps, which were introduced into the original time series of four climatologic diverse test regions. Results show that uncertainty is quantified accurately (>90%), consequently enhancing the product's quality with respect to its use for modeling and the geoscientific community.