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Estrogens

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Estrogen-mediated modulation of sterile inflammatory markers and baroreflex sensitivity in ovariectomized female Wistar rats.

Archives of endocrinology and metabolism
OBJECTIVE: This study aims to explore the role of estrogen in providing cardioprotective benefits to premenopausal women, examining how hormonal differences between sexes influence the prevalence of cardiovascular diseases (CVDs) in women.

A Cohort Study Investigating Zearalenone Concentrations and Selected Steroid Levels in Patients with Sigmoid Colorectal Cancer or Colorectal Cancer.

Toxins
THE AIM: In this study was to determine if sigmoid colorectal cancer (SCC) and colorectal cancer (CRC) in women (W) and men (M) is accompanied by zearalenone (ZEN) mycotoxicosis and changes in selected steroid levels.

Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.

PLoS computational biology
Environmental toxicants affect human health in various ways. Of the thousands of chemicals present in the environment, those with adverse effects on the endocrine system are referred to as endocrine-disrupting chemicals (EDCs). Here, we focused on a ...

Association between phthalate exposure and accelerated bone maturation in Chinese girls with early puberty onset: a propensity score-matched case-control analysis.

Scientific reports
Estrogen can promote the acceleration of bone maturation and phthalate esters (PAEs) have estrogen-mimicking effects. We investigated whether PAEs are associated with the acceleration of bone age (BA) in girls with early onset of puberty (EOP). This ...

Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. Nonetheless, and perhaps surprisingly, only few image AI systems ...

MATH: A Deep Learning Approach in QSAR for Estrogen Receptor Alpha Inhibitors.

Molecules (Basel, Switzerland)
Breast cancer ranks as the second leading cause of death among women, but early screening and self-awareness can help prevent it. Hormone therapy drugs that target estrogen levels offer potential treatments. However, conventional drug discovery entai...

A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening.

Environmental science & technology
The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significant attention. However, the currently available DL model for screening EEs lacks both a transparent de...

Assessment of estrogenic potential from exudates of microcystin-producing and non-microcystin-producing Microcystis by metabolomics, machine learning and E-screen assay.

Journal of hazardous materials
Cyanobacterial blooms, often dominated by Microcystis aeruginosa, are capable of producing estrogenic effects. It is important to identify specific estrogenic compounds produced by cyanobacteria, though this can prove challenging owing to the complex...

Development of a deep neural network model based on high throughput screening data for predicting synergistic estrogenic activity of binary mixtures for consumer products.

Journal of hazardous materials
A paradigm of chemical risk assessment is continuously extending from focusing on 'single substances' to more comprehensive approaches that examines the combined toxicity among different components in 'mixtures.' This change aims to account for the c...

Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.

Ecotoxicology and environmental safety
Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been strongly associated with chronic kidney disease (CKD). An interpretable machine learning (ML) model was developed to predict CKD using data from the ...