Endocrine Disruptor Exposure Causes Infochemical Dysregulation and an Ecological Cascade from Zooplankton to Algae
Bibliographic record
Abstract
Endocrine disruption is intimately linked to controlling the population of pollutant-exposed organisms through reproduction and development dysregulation. This study investigated how endocrine disruption in a predator organism could affect prey species biology through infochemical communication. Daphnia magna and Chlorella vulgaris were chosen as model prey and predator planktons, respectively, and fenoxycarb was used for disrupting the endocrine system of D. magna . Hormones as well as endo- and exometabolomes were extracted from daphnids and algal cells and their culture media and analyzed using liquid chromatography with tandem mass spectrometry. Biomolecular perturbations of D. magna under impaired offspring production and hormone dysregulation were observed. Differential biomolecular responses of the prey C. vulgaris, indicating changes in methylation and infochemical communication, were subsequently observed under the exposure to predator culture media, containing infochemicals released from the reproducibly normal and abnormal D. magna, as results of fenoxycarb exposure. The observed cross-species transfer of the endocrine disruption consequences, initiated from D. magna, and mediated through infochemical communication, demonstrates a novel discovery and emphasizes the broader ecological risk of endocrine disruptors beyond reproduction disruption in target organisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".