Disruption by stealth - Interference of endocrine disrupting chemicals on hormonal crosstalk with thyroid axis function in humans and other animals
Bibliographic record
Abstract
Thyroid hormones (THs) are important regulators of growth, development, and homeostasis of all vertebrates. There are many environmental contaminants that are known to disrupt TH action, yet their mechanisms are only partially understood. While the effects of Endocrine Disrupting Chemicals (EDCs) are mostly studied as "hormone system silos", the present critical review highlights the complexity of EDCs interfering with TH function through their interactions with other hormonal axes involved in reproduction, stress, and energy metabolism. The impact of EDCs on components that are shared between hormone signaling pathways or intersect between pathways can thus extend beyond the molecular ramifications to cellular, physiological, behavioral, and whole-body consequences for exposed organisms. The comparatively more extensive studies conducted in mammalian models provides encouraging support for expanded investigation and highlight the paucity of data generated in other non-mammalian vertebrate classes. As greater genomics-based resources become available across vertebrate classes, better identification and delineation of EDC effects, modes of action, and identification of effective biomarkers suitable for HPT disruption is possible. EDC-derived effects are likely to cascade into a plurality of physiological effects far more complex than the few variables tested within any research studies. The field should move towards understanding a system of hormonal systems' interactions rather than maintaining hormone system silos.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".