Gies, L. | Search bioRxiv

bioRxiv2026

WhaleSonic: Recordings of cetacean vocal behaviour with hydrophone arrays in Northern Norway

Killer whales, humpback whales, fin whales, and sperm whales converged in a fjord system in Northern Norway during the 2023-2024 winter, where whale watching and fishing vessels add to the acoustic scene. Cetaceans are intensely studied for their acoustic behaviour and communication, and the co-occurrence of four species in confined waters offers a unique opportunity to record them with hydrophone arrays. We present WhaleSonic, a raw acoustic dataset recorded with two synchronised array systems. Four drifting buoys, each carrying a tetrahedral hydrophone array, captured 78 hours of calibrated recordings; seven bottom-mounted hydrophones yielded 52 days of continuous data. Both systems are synchronised to UTC (<1 us and 3-7 ms) and positioned to 2 m accuracy. Transmission experiments and sound velocity measurements provide in-situ ground truth. All data are in physical units and a unified coordinate system, self-documented in HDF5 files, and published with open-source tools. WhaleSonic supports the development of multichannel algorithms for source separation, localisation, sound field analysis, and group communication in free-ranging cetaceans.

animal behavior and cognition↗

bioRxiv2025

Beyond one-size-fits-all: single-cell transcriptomic signatures predict drug efficacy and reveal responder subgroups in endometriosis

Endometriosis affects [~]10% of reproductive-age women, yet targeted non-hormonal therapies remain unavailable, and treatment response is highly variable. Here, we apply a single-cell framework to resolve therapeutic heterogeneity at a resolution previously unattained in drug development efforts. Using scRNA-seq profiles from eutopic and ectopic tissues, combined with a machine learning-based drug response model, we identified compounds predicted to revert disease-associated transcriptional states and map cell-type-specific vulnerabilities across patients and tissues. Our analysis revealed pronounced tissue-specific and inter-patient heterogeneity in predicted responses. Stromal, endothelial, and stem cell populations emerged as the dominant therapeutic targets, collectively revealing selective sensitivity to two recurrent drug classes, histone deacetylase and tubulin polymerisation inhibitors. Transcriptomic comparison of predicted responders and non-responders to these drugs pointed to conserved molecular programmes involving extracellular matrix remodelling, angiogenesis, and proliferative activation. These signatures were shared between eutopic and ectopic stromal compartments, supporting the feasibility of assessing therapeutic response using readily accessible eutopic tissue. Our findings show that this single-cell framework can dissect therapeutic heterogeneity in endometriosis, support the development of precision non-hormonal therapies and identify responder subgroups relevant for patient stratification. Together, these results highlight that underlying molecular diversity in endometriosis necessitates therapeutic approaches beyond a one-size-fits-all model.

molecular biology↗