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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.
In sterile neuroinflammation, a pathological role is proposed for microglia, whereas in viral encephalitis, their function is not entirely clear. Many viruses exploit the odorant system and enter the CNS via the olfactory bulb (OB). Upon intranasal vesicular stomatitis virus instillation, we show an accumulation of activated microglia and monocytes in the OB. Depletion of microglia during encephalitis results in enhanced virus spread and increased lethality. Activation, proliferation, and accumulation of microglia are regulated by type I IFN receptor signaling of neurons and astrocytes, but not of microglia. Morphological analysis of myeloid cells shows that type I IFN receptor signaling of neurons has a stronger impact on the activation of myeloid cells than of astrocytes. Thus, in the infected CNS, the cross talk among neurons, astrocytes, and microglia is critical for full microglia activation and protection from lethal encephalitis.
Fresh water is a vital natural resource. Earth observation time-series are well suited to monitor corresponding surface dynamics. The DLR-DFD Global WaterPack (GWP) provides daily information on globally distributed inland surface water based on MODIS (Moderate Resolution Imaging Spectroradiometer) images at 250 m spatial resolution. Operating on this spatiotemporal level comes with the drawback of moderate spatial resolution; only coarse pixel-based surface water quantification is possible. To enhance the quantitative capabilities of this dataset, we systematically access subpixel information on fractional water coverage. For this, a linear mixture model is employed, using classification probability and pure pixel reference information. Classification probability is derived from relative datapoint (pixel) locations in feature space. Pure water and non-water reference pixels are located by combining spatial and temporal information inherent to the time-series. Subsequently, the model is evaluated for different input sets to determine the optimal configuration for global processing and pixel coverage types. The performance of resulting water fraction estimates is evaluated on the pixel level in 32 regions of interest across the globe, by comparison to higher resolution reference data (Sentinel-2, Landsat 8). Results show that water fraction information is able to improve the product's performance regarding mixed water/non-water pixels by an average of 11.6% (RMSE). With a Nash-Sutcliffe efficiency of 0.61, the model shows good overall performance. The approach enables the systematic provision of water fraction estimates on a global and daily scale, using only the reflectance and temporal information contained in the input time-series.
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.
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.
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.
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.
MYC paralogs are frequently activated in small cell lung cancer (SCLC) but represent poor drug targets. Thus, a detailed mapping of MYC-paralog-specific vulnerabilities may help to develop effective therapies for SCLC patients. Using a unique cellular CRISPR activation model, we uncover that, in contrast to MYCN and MYCL, MYC represses BCL2 transcription via interaction with MIZ1 and DNMT3a. The resulting lack of BCL2 expression promotes sensitivity to cell cycle control inhibition and dependency on MCL1. Furthermore, MYC activation leads to heightened apoptotic priming, intrinsic genotoxic stress and susceptibility to DNA damage checkpoint inhibitors. Finally, combined AURK and CHK1 inhibition substantially prolongs the survival of mice bearing MYC-driven SCLC beyond that of combination chemotherapy. These analyses uncover MYC-paralog-specific regulation of the apoptotic machinery with implications for genotype-based selection of targeted therapeutics in SCLC patients.
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.
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.