Effects of Endocrine-Disrupting Chemicals on Adrenal Function
Bibliographic record
Abstract
The adrenal glands play crucial roles in regulating metabolism, blood pressure, immune system function, and response to stress through the secretion of hormones. Despite their critical functions, the adrenal glands are often overlooked in studies on the effects of potential toxicants. Research across human, animal, and in vitro studies has identified more than 60 compounds that can induce adrenocortical toxicity. These compounds, known as endocrine-disrupting chemicals (EDCs), are natural or synthetic substances that interfere with the endocrine system. This review aims to provide an overview of the effects of 4 major families of EDCs-flame retardants, bisphenols, phthalates, and microplastics-on the function of the adrenal glands. The PubMed database was searched for studies reporting the effects of the chemicals in these 4 families on the adrenal glands. There is clear evidence that the morphology and function of the adrenal gland are affected, particularly through disrupting the steroidogenic pathway. Additionally, some EDCs have been shown to exert transgenerational effects, raising further concerns about their long-term effect. However, most EDCs have not been thoroughly evaluated for their effects on the function of the adrenal glands, especially in human studies. Thus, developing regulatory testing guideline to include the adrenal glands in the screening of EDCs is urgently needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".