Hong-Ying Hu

Operational water quality management relies on physicochemical monitoring and targeted chemical analysis, but routine surveillance covers only a prioritized subset of high-risk contaminants and does not capture biological activity from unmonitored chemicals, transformation products, or complex mixtures. Whole-organism bioassays provide complementary effect information, yet the conventional Daphnia magna (D. magna) acute immobilization end point requires 48 h. Here, we introduce D-HEART (Daphnia-based Heartbeat Evaluation and Analysis for Rapid Toxicity Screening), a microfluidic imaging and analysis framework that converts high-speed cardiac recordings into 116 descriptors spanning morphology, pumping, wall motion kinematics, and synchrony. Within the tested response space, D-HEART assigns cardiac-response classes using a six-contaminant reference library, while its Heartbeat Toxicity Index (HTI) estimates 48 h immobilization from the predicted class and phenotype. Transcriptomic profiles provided molecular context for differentiated 1 h cardiac states. Post-training Cd(II) tests across environmental water matrices tracked immobilization with greater uncertainty than in laboratory water, and two untreated industrial wastewaters showed dose-responsive HTI estimates for mixed exposures from unseen contaminant classes. By linking early physiological states to transcriptional responses and later apical toxicity, D-HEART provides a rapid, cross-time scale effect-screening layer for operational water-quality evaluation, reducing the detection window by approximately 98% relative to the conventional 48 h immobilization end point.

The growing number and diversity of chemical contaminants threaten aquatic ecosystem integrity, yet conventional risk assessments often overlook food-web interactions and require extensive toxicological and ecological data. We developed the Generalized Ecotox-Criticality Framework (GECF), which reframes ecosystem risk assessment as a targeted dimensionality-reduction problem. GECF integrates food-web energy flux, ecological redundancy, and chemical-specific toxicity sensitivity to prioritize pollutant-specific nodal taxa for direct toxicity-data generation while retaining the complete ecosystem network. In the Baiyangdian case study, a cutoff sensitivity analysis supported the 80% relative criticality index (RCI) setting as a practical balance between response fidelity and testing burden. At this setting, nodal scenarios retained the principal ecosystem responses simulated by AQUATOX and yielded indicator-specific candidate ecological thresholds (ECO-thresholds) internally benchmarked against full-organism scenarios. Relative to the 14-taxon full-organism evidence set, the 80% RCI setting reduced the standardized weighted assay burden by 71.1%, the number of tested taxa by 69.1%, and the number of vertebrate test taxa by 66.7%. Additional analyses showed that nodal composition varied across chemicals and ecosystems and that candidate thresholds shifted under warming and nutrient-enrichment backgrounds. GECF provides a model-based decision-support approach for prioritizing toxicity-data generation and conducting scenario-dependent regional aquatic-ecosystem risk screening.

Harmful algal blooms, the most severe ecological hazards worldwide, terminate abruptly within a few days. In this work, we identified that iron-catalyzed active lipid peroxides predominantly trigger individual cell ferroptosis and drive the population collapse of blooming cyanobacteria. We reveal the chronological sequence of labile iron burst, oxidative stress, lipid peroxidation, and cell death during a Microcystis bloom demise event. Dead cells exhibit a nonrandom spatial distribution within colonies. Intensifying lipid peroxidation catalyzed by cellular labile iron generates truncated phospholipids with shortened fatty acyl chains bearing alkyl groups. These active lipid peroxides destabilize plasma membranes and induce nanoscale membrane pore formation, resulting in individual cell ferroptosis and lysis. Oxidized lipids are also released from ferroptotic cells, propagating lipid peroxidation to neighboring cells, thereby spreading death throughout the population.

Water quality criteria (WQC) serve as a scientific foundation for pollutant risk assessment and control in aquatic ecosystems. The development of regionally differentiated WQC tailored to specific regional characteristics has become an emerging trend. However, the current WQC is constrained by a lack of regional species toxicity data. To address these limitations, this study proposes the biological toxicity effect ratio (BER) method, which indirectly reflects the toxicity sensitivity of the overall aquatic ecosystem through the toxicity information on a limited number of species, enabling rapid WQC prediction. Using the established WQC in China and the USA as a case study, we combined mathematical derivation and data validation to evaluate the BER method. Among various species-taxon groups of freshwater organisms, planktonic crustaceans demonstrated the highest predictive accuracy. Our analysis further revealed that species toxicity sensitivity and regional variability jointly influence the prediction accuracy. Regardless of the evaluation indexes, planktonic crustaceans emerged as the most suitable species-taxon group for the BER method. Additionally, the BER method is particularly applicable to pollutants with conserved mechanisms across species. This study systematically explores the feasibility of using the BER method and offers new insights for deriving regionally differentiated WQC.

There exists a significant risk of water blooms during the utilization of recycled water in landscape environments. The nitrogen and phosphorus discharge standards of sewage treatment plants are very low. Controlling hydraulic retention time (HRT) is currently the most effective means to control water bloom. This article proposes a new method for determining the HRT threshold based on water transparency as a control indicator. The following results were obtained: (1) with the nitrogen and phosphorus concentrations of 15 and 0.5 mg/L, respectively, the threshold for HRT under high temperature and strong light is 4.6 days, while the threshold under low temperature and low light is 11.5 days. (2) With the nitrogen and phosphorus concentrations of 10 and 0.3 mg/L, respectively, the threshold for HRT under high temperature and strong light is 5 days, while the threshold under low temperature and low light conditions is 12.3 days. (3) The HRT threshold obtained under high temperature and strong light is lower than that obtained under low temperature and low light conditions. (4) The higher the concentrations of nitrogen and phosphorus, the smaller the HRT threshold obtained. (5) Blue algae have stronger adaptability than green algae and diatoms.