β‐blockers as endocrine disruptors: the potential effects of human β‐blockers on aquatic organisms
Bibliographic record
Abstract
β-Adrenergic blockers or β-blockers have been used therapeutically to treat human hypertension since the late 1960s. The global market value and prescription rates of β-blockers keep rising substantially each year, and over the past decade the number of prescriptions has doubled. The widespread use of β-blockers has resulted in their appearance in the aquatic environment originating primarily from sewage effluents. The objective of this review is to analyze the literature as a means to determine the endocrine-disrupting potential of β-blockers in aquatic organisms. The mammalian adrenergic system is compared with the adrenergic system of fish and the homologous octopaminergic system in aquatic invertebrates, in particular mollusks. The structure and functions of these systems are linked to the molecular similarities between adrenoceptors and the octopaminergic/tyraminergic receptors, the various catecholamine molecules (epinephrine, norepinephrine, octopamine, and tyramine), and the processes controlled. Knowledge of these similarities as well as the effects of β-blockers, mainly in humans, is then used to create a broad picture of the endocrine-disrupting potential of β-blockers, particularly during the stress response. The main conclusion is that β-blockers have endocrine-disrupting effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".