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Metabolic preconditioning, characterized by conditions like obesity and insulin resistance syndrome, disrupts hormonal balance. Elevated androgen levels stimulate excessive sebum production and follicular cell proliferation, leading to acne lesions. Similarly, thyroid hormone imbalances affect sebaceous gland activity, epidermal lipid composition, and skin cell turnover, impacting acne occurrence and severity. This study aimed to assess the potential contribution of metabolic and endocrine preconditions to acne development. A total of 389 patients diagnosed with acne were included and divided into three groups: the metabolic precondition group (MPG, N = 163, 41.9%), the endocrine precondition group (EPG, N = 162, 41.65%), and the control group (CG, N = 89, 22.88%). Data related to the degree of acne severity and comorbidities of interest were collected from the patients’ medical records. In the groups with concomitant diseases, moderate and severe acne were significantly more prevalent (56.44% and 41.10% in MPG, and 35.80% and 61.11% in EPG) compared to the control group (5.61% and 4.89%). The most prevalent preconditions observed were insulin resistance syndrome in MPG (63.8%) and autoimmune thyroiditis in EPG (95.06%). Significant age-related differences in acne severity were found across all study groups (p < 0.05). In MPG, the age variable was significantly higher in the presence of mild acne, while in EPG, the age variable was significantly lower for the mild acne group. A positive association was observed between the severity of acne and insulin resistance syndrome, obesity, autoimmune thyroiditis, and hypothyroidism (p < 0.05). Risk analysis indicated a significantly higher risk (RR > 1, 95% CI RR > 1, p < 0.001) of developing moderate and severe acne in the presence of these preconditions. The presence of both metabolic and endocrine preconditions significantly increased the likelihood of developing severe acne, leading to the hypothesis that both conditions may be contributing factors to the development of acne. Full article

Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed. Full article