bioRxiv Science⌕ Search

Biology subjects

Boerner, K.

Publications and source records attributed to Boerner, K..

5 recordsLinked to original sources

Movement strategies reveal the success of mammals in urban areas

Various hypotheses have been proposed to explain why some species persist or even flourish in urban areas. Yet, despite its central role in determining when and where animals encounter resources, disturbance, and risk, movement behaviour remains an overlooked mechanism of urban success. In urban areas, human activities are strongly periodic, i.e. predictable in space and time. This may favour species able to adjust their behaviour to predictable cycles of resources and risks in space and time. Here, we tested this hypothesis and tracked movement behaviour along an urbanisation gradient in three mammal species with different urban success: red fox (Vulpes vulpes), an urban dweller; raccoon (Procyon lotor), an invasive urban dweller; and wild boar (Sus scrofa), an urban utiliser. We analysed periodicity in movement behaviour and investigated whether increasing urbanisation is associated with periodic reorganisation of activity timing, space use, and further analysed alterations in habitat selection along the urbanisation gradient. Our results show that foxes aligned their movement behaviour with human activity, having stronger day-night contrasts and more repeatable space use than their rural counterparts. Urban raccoons showed a contrasting strategy; they were more active during the day, without changes in their movement routines under increasing urbanisation, suggesting a flexible strategy that explains their urban success. In contrast, wild boars reduced routine movement behaviours with increasing urbanisation, consistent with their occurrence in less predictable suburban environments and avoidance of city centres. In summary, our results suggest that movement behaviour may be a key mechanism enabling animals to persist in cities, revealing distinct behavioural strategies for coping with urban environments.

ecology↗

Multiscale harmonization and semantic integration of biomedical data enable biological insights through immersive exploration

Single-cell atlassing efforts like the Human BioMolecular Atlas Program (HuBMAP) and the Cellular Senescence Network (SenNet) are producing multiscale datasets across the healthy, adult, human body, but this data is typically explored only on 2D screens with limited 3D affordances, even though understanding a cells location within a tissue, organ, and body requires reasoning across many orders of spatial magnitude. The Human Reference Atlas (HRA) provides standard terminologies and a Common Coordinate Framework (CCF) for harmonizing such data spatially and semantically. Building on the HRA Organ Gallery in virtual reality (VR) application, we present "HRA: Powers of Ten," which integrates, harmonizes, and visualizes biological data from these efforts immersively in VR using a Multiscale Elevator System that lets users descend, like riding an elevator through an inverted skyscraper, from a whole body view of 81 reference organs to datasets across 5 organs (lymph node, brain, large intestine, small intestine, liver), 5 assay types (CODEX, Visium, v-CyCIF, Xenium, SBF-SEM), and 4 spatial scales. Contributed by Data Providers, these VR scenes enable biological insights into senescence patterns, cellular neighborhoods, 3D tissue reconstruction, and subcellular liver architecture. A standard operating procedure supports adding further datasets. Freely available on the Meta Store to over 20 million headset owners, the application, data, and code are open-source.

bioinformatics↗

Constructing and Using Cell Type Populations of the Human Reference Atlas

The human body contains [~]27-36 trillion cells of up to 10,000 cell types (CTs) within a volume of [~]62-120 liters (males) and 52-89 liters (females). The Human Reference Atlas (HRA) v2.3 provides a quantitative 3D framework of CTs across 73 reference organs and 1,283 3D anatomical structures (ASs). The HRA Cell Type Population (HRApop) effort has quantified CTs per AS using high-quality single-cell datasets processed through scalable, reproducible workflows and cell type annotation (CTann) tools. HRApop v1.0 includes reference CT populations for 73 ASs (112 when sex-specific) using 662 datasets spatially registered to 230 locations across 17 organs (31 when sex-specific). For 558 single-cell (sc-)transcriptomics datasets (11,042,750 cells), CTs and biomarker expressions were computed using Azimuth, CellTypist, and popV. To test generalizability, 104 sc-proteomics datasets (16,576,863 cells) were integrated. In total, HRApop includes 27,619,613 cells and serves as a healthy reference for researchers aiming to elucidate mechanisms underlying cellular interactions, FTU operations, and cellular and tissue level disease progression, which may facilitate advancements in basic discovery and lead to new therapeutic strategies.

bioinformatics↗

Construction, Deployment, and Usage of the Human Reference Atlas Knowledge Graph for Linked Open Data

The Human Reference Atlas (HRA) for the healthy, adult body is being developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions of experimental datasets and ontology-linked reference anatomical structures (AS), cell types (CT), and biomarkers (B). We introduce the HRA Knowledge Graph (KG) as central data resource for HRA v2.2, supporting cross-scale, biological queries to Resource Description Framework graphs using SPARQL. In February 2025, the HRA KG covered 71 organs with 5,800 AS, 2,268 CT, 2,531 B; it had 10,064,033 nodes, 171,250,177 edges, and a size of 125.84 GB. The HRA KG comprises 13 types of Digital Objects (DOs) using the Common Coordinate Framework Ontology to standardize core concepts and relationships across DOs. We (1) provide data and code for HRA KG construction; (2) detail HRA KG deployment by Linked Open Data principles; and (3) illustrate HRA KG usage via application programming interfaces, user interfaces, data products. A companion website is at https://cns-iu.github.io/hra-kg-supporting-information.

bioinformatics↗

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage

The Human BioMolecular Atlas Program (HuBMAP) aims to construct a reference 3D structural, cellular, and molecular atlas of the healthy adult human body. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) serves experimental datasets and supports data processing, search, filtering, and visualization. The Human Reference Atlas (HRA) Portal (https://humanatlas.io) provides open access to atlas data, code, procedures, and instructional materials. Experts from more than 20 consortia are collaborating to construct the HRAs Common Coordinate Framework (CCF), knowledge graphs, and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes, and biomarkers) and to use the HRA to understand changes that occur at each of these levels with aging, disease, and other perturbations. The 6th release of the HRA v2.0 covers 36 organs with 4,499 unique anatomical structures, 1,195 cell types, and 2,089 biomarkers (e.g., genes, proteins, lipids) linked to ontologies and 2D/3D reference objects. New experimental data can be mapped into the HRA using (1) three cell type annotation tools (e.g., Azimuth) or (2) validated antibody panels (OMAPs), or (3) by registering tissue data spatially. This paper describes the HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interface (APIs), flexible hybrid cloud infrastructure, and previews atlas usage applications.

bioinformatics↗