ReviewEnvironment & health (Washington, D.C.)2024
Thyroid Hormone Biomonitoring: A Review on Their Metabolism and Machine-Learning Based Analysis on Effects of Endocrine Disrupting Chemicals.
Review in Environment & health (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Exploring thyroid function in main domestic ruminants: a scoping review of physio-anatomy, diseases and diagnostic tools.The veterinary quarterly · 2026Article
- Per- and Polyfluoroalkyl Substances and Papillary Thyroid Carcinoma: An Integrative Study of Bioinformatics, Epidemiological Associations, and In Vitro Responses.International journal of molecular sciences · 2026Article
- Mapping Steroidogenic Perturbations Under Endocrine Disruptor Mixtures Across Demographic Subgroups: Structural and Metabolomic Insights.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Quantitative Characterization of the Serum Elemental Signatures in HBV Infection.Biological trace element research · 2026Article
- Studying endocrine disrupting chemicals from molecular targets to mixture model approach: lessons from the thyroid model.The Journal of clinical endocrinology and metabolism · 2026Review
- Deep learning based thyroid prediction with opposition learning based red panda optimization feature selection.Scientific reports · 2025Article
- Short-Chain Polychlorinated Alkanes Exposure and Risk of Thyroid Cancer in a Population-Based Case-Control Study.Environment & health (Washington, D.C.) · 2025Article
- The impact of environmental factors and contaminants on thyroid function and disease from fetal to adult life: current evidence and future directions.Frontiers in endocrinology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The thyroid is an essential endocrine organ in human body, and thyroid hormones (THs) are pivotal signaling molecules and mediators in various physiological processes. THs, particularly in their free form, play a critical role in regulating body temperature and in the metabolism of lipid and glucose, making the maintenance of TH levels crucial for human health. THs undergo a series of metabolic processes, producing TH metabolites (THMs). THMs are significant in endocrine regulation, such as 3,5-diiothyronine (3,5-T2) and 3-iodothyronamine (3-T1AM), which exhibit activities akin to THs. The production and distribution of THMs are intricately linked to the function of specific organs and tissues, highlighting the need for advanced research into the determination and mechanisms of THMs in body. Exposure to endocrine disrupting chemicals (EDCs) can significantly affect the levels of thyroid stimulating hormone (TSH) and THs. This review utilizes machine learning to analyze epidemiological data, identifying potential EDCs that pose risks of hyperthyroidism and hypothyroidism. Additionally, it delves into the toxicological mechanisms of these EDCs, examining their effects on TH production, binding processes, related proteins, and metabolic enzymes. This approach effectively bridges the gap between epidemiological studies and toxicological researches, laying the groundwork for future research trends. By integrating epidemiological studies with machine learning, this review offers insightful perspectives on the potential risks associated with chemical exposure and underscores the necessity for further research in understanding the impact of EDCs on TH metabolism and TH-related health effects.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.