High-throughput heart rate monitoring in Daphnia magna for sublethal ecotoxicological assessment

Monitoring Daphnia magna heart rate provides significant potential as a sensitive physiological indicator for ecotoxicological assessment, yet its broader application has been limited by low-throughput, high variability, reliance on mean-based interpretation, and difficulties in analysing multiple individuals simultaneously. Here, we present an integrated methodology combining stress-minimised immobilisation, high-speed imaging, and Fourier-based analysis to monitor 150 individuals per hour. This high-throughput system enables distribution- and probability-based statistical analysis rather than conventional mean-based approaches. Using kernel density estimation and Gaussian deconvolution, multimodal cardiac response patterns and unrecognised subpopulations were identified. Distribution-based convergence analysis revealed stable estimation at N ≥ 63 (σ = 26.36 bpm; R² = 0.89), supporting N = 100 as a statistically robust sample size. Application to reference substances, such as hydrogen peroxide and caffeine validated the method for detecting chemically induced cardiac alterations. Additional exposure to paraquat and potassium dichromate revealed dose-dependent heart rate alterations below EC₅₀ levels. Copper oxide nanoparticles induced abnormal elevation below EC₁₀, and gold nanoparticles caused irregular distributions (∼ 31.2 %) below no observed effect concentration. These results demonstrate the improved sensitivity, reproducibility, and ecological relevance, offering a rapid, non-invasive, and probabilistic tool for early detection of sublethal stress in next-generation environmental risk assessment.