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.

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.

Cytomegalovirus (CMV) infection is a major cause of morbidity and mortality following hematopoietic stem cell transplantation (HSCT). Measuring CMV-specific cellular immunity may improve the risk stratification and management of patients. IFN-γ ELISpot assays, based on the stimulation of peripheral blood mononuclear cells with CMV pp65 and IE-1 proteins or peptides, have been validated in clinical settings. However, it remains unclear to which extend the T-cell response to synthetic peptides reflect that mediated by full-length proteins processed by antigen-presenting cells. We compared the stimulating ability of pp65 and IE-1 proteins and corresponding overlapping peptides in 16 HSCT recipients using a standardized IFN-γ ELISpot assay. Paired qualitative test results showed an overall 74.4% concordance. Discordant results were mainly due to low-response tests, with one exception. One patient with early CMV reactivation and graft-versus-host disease, sustained CMV DNAemia and high CD8\(^+\) counts showed successive negative protein-based ELISpot results but a high and sustained response to IE-1 peptides. Our results suggest that the response to exogenous proteins, which involves their uptake and processing by antigen-presenting cells, more closely reflects the physiological response to CMV infection, while the response to exogenous peptides may lead to artificial in vitro T-cell responses, especially in strongly immunosuppressed patients.

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.

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.