We determined metabolites of acrylamide and glycidamide concentrations (AAMA and GAMA, respectively) in urine of 93 women within the first days after delivery, using LC-MS/MS. The median AAMA and GAMA levels in urine were 20.9 μg/l (2.3÷399.0 μg/l) and 8.6 μg/l (1.3÷85.0 μg/l), respectively. In smokers we found significantly (P<0.01) higher levels of metabolites in comparison with the non-smoking women. As demonstrated by the 24-h dietary recall, acrylamide intake was low (median: 7.04 μg/day). Estimated exposure to acrylamide based on AAMA and GAMA levels in the whole group of women was 0.16 μg/kg b.w./day (1.15 μg/kg b.w./day, P95). We found significantly (P<0.05) higher exposure in women who consumed higher amount of acrylamide in the diet (≥10 μg/day vs <10 μg/day). A weak but significant positive correlation between acrylamide intake calculated on the basis of urinary levels of AAMA and GAMA and estimated on the basis of 24-h dietary recall (r=0.26, P<0.05) was found. The estimated margin of exposure values were below 10 000 and ranged from 156 for 95th percentile to 1938 for median acrylamide intake. Our results have shown that even a low dietary acrylamide intake may be associated with health risk.
Acrylamide in food is formed by the Maillard reaction. Numerous studies have shown that acrylamide is a neurotoxic and carcinogenic compound. The aim of this study was to determine the level of acrylamide in breast milk at different lactation stages and to evaluate the impact of breastfeeding women’s diet on the content of this compound in breast milk. The acrylamide level in breast milk samples was determined by LC–MS/MS. Breastfeeding women’s diet was evaluated based on the 24 h dietary recall. The median acrylamide level in colostrum (n = 47) was significantly (p < 0.0005) lower than in the mature milk (n = 26)—0.05 µg/L and 0.14 µg/L, respectively. The estimated breastfeeding women’s acrylamide intake from the hospital diet was significantly (p < 0.0001) lower than that from the home diet. We found positive—although modest and borderline significant—correlation between acrylamide intake by breastfeeding women from the hospital diet µg/day) and acrylamide level in the colostrum (µg/L). Acrylamide has been detected in human milk samples, and a positive correlation between dietary acrylamide intake by breastfeeding women and its content in breast milk was observed, which suggests that the concentration can be reduced. Breastfeeding women should avoid foods that may be a source of acrylamide in their diet.
The choice of management for patients with adnexal tumors requires careful pre-surgical assessment. In case of adnexal masses, the diagnostic difficulties arise from the heterogenic nature of the adnexal diseases, presence of multiple functional changes, and lack of early symptoms of malignancy. A reliable pre-surgical differentiation cannot be performed using clinical features, ultrasound examination, or tumor markers alone. New diagnostic techniques and novel markers are under investigations, however no single test can be used to conclusively differentiate between malignant and non-malignant adnexal masses. Mathematical models and scoring systems based on different clinical, ultrasonographic and laboratory parameters alone or together may facilitate the diagnosis. Selected mathematical models and scoring systems are presented in this article. Models using only ultrasound features include simple rules, regression models, Gynecologic Imaging Report and Data System, and various morphologic scores. Some logistic regression models are based on multiple clinical and ultrasound data. The OVA1 test is based on five tumor markers without using other data. The Risk of Malignancy Algorithm uses two tumor markers with one clinical parameter. i.e. the menopausal status. Some models used clinical, ultrasound and tumor marker data together. This group of models includes risk of malignancy indices, artificial neural networks, and the ADNEX model. Although some of these models have been compared in the literature, more prospective studies are needed to select the most effective model, to develop the existing models, or to create new more effective models of oncological assessment of the adnexal tumors.
Introduction: Acrylamide (AA) is a “probably carcinogenic to humans” monomer that can form in heated starchy food and in tobacco smoke. N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) and N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA), acrylamide metabolites in urine, are recognized as good markers of exposure to acrylamide. Aim: The aim of the study is a preliminary assessment whether the levels of AAMA and GAMA in urine after childbirth are good markers of acrylamide exposure due to passive smoking during pregnancy. Material and method: The study group consisted 67 non-smokers and 10 passive-smoker women during pregnancy. AAMA and GAMA levels in urine samples were determined using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Results: The median AAMA levels in urine of non-smoking and passively smoking women were 30.7 μg/g creatinine and 25.2 μg/g creatinine, respectively. Much lower values were determined for GAMA: 11.4 μg/g creatinine and 10.3 μg/g creatinine, respectively. There is no significant difference between AAMA and GAMA content in urine samples between both groups of women as well as in the anthropometric parameters of newborns between those two groups of mothers. Conclusion: Our pilot study did not confirm that postpartum AAMA and GAMA concentrations in urine are good markers of exposure to acrylamide from passive smoking during pregnancy. It is probably due to the different ways of acrylamide absorption from tobacco smoke by active and passive smokers. Exposure of pregnant women to acrylamide from passive smoking requires further research.
We determined metabolites of acrylamide and glycidamide concentrations (AAMA and GAMA, respectively) in urine of 93 Polish women within the first days after delivery, using LC-MS/MS. The median AAMA and GAMA levels in urine were 20.9 μg/L (2.3 ÷ 399.0 μg/L) and 8.6 μg/L (1.3 ÷ 85.0 μg/L), respectively. In smokers we found significantly (p < 0.01) higher levels of metabolites in comparison with the non-smoking women.
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