Experimental Exposure to Bisphenol A Has Minimal Effects on Bone Tissue in Growing Rams-A Preliminary Study.

Bisphenol A (BPA) is a well-known synthetic compound that belongs to the group of endocrine-disrupting chemicals. Although bone tissue is a target for these compounds, studies on BPA-related effects on bone morphology in farm animals are limited. In this preliminary study, we investigated the effects of short-term dietary BPA exposure on femoral morphology, metabolism, mineral content, and biomechanical behavior in rams aged 9-12 months. Fourteen rams of the Istrian Pramenka breed were randomly divided into a BPA group and a control group (seven rams/group) and exposed to 25 µg BPA/kg bw for 64 days in feed. Blood was collected for determination of bone turnover markers (procollagen N-terminal propeptide, C-terminal telopeptide), and femurs were assessed via computed tomography, histomorphometry, three-point bending test, and mineral analysis. BPA had no significant effects on most of the parameters studied. Only mineral analysis showed decreased manganese (50%; p ≤ 0.05) and increased copper content (25%; p ≤ 0.05) in the femurs of BPA-exposed rams. These results suggest that a 2-month, low-dose exposure to BPA in growing rams did not affect the histomorphology, metabolism, and biomechanical behavior of femurs; however, it affected the composition of microelements, which could affect the histometric and biophysical properties of bone in the long term.

The performance of the Xpert Bladder Cancer Monitor Test and voided urinary cytology in the follow-up of urinary bladder tumors.

BACKGROUND: Cystoscopy in complement with urinary cytology represents the gold standard for the follow-up of patients with urinary bladder tumours. Xpert Bladder Cancer Monitor Test (XBC) is a novel mRNA-based urine test for bladder cancer surveillance. The aim of the study was to evaluate the performance of the XBC and voided urinary cytology (VUC) in the follow-up of bladder tumours. PATIENTS AND METHODS: The XBC was performed on stabilized voided urine and VUC was performed on urine samples. The results were compared to cystoscopic findings and histopathological results after transurethral resection of the bladder lesion. RESULTS: For the prediction of malignant histopathological result sensitivity, the specificity and negative predictive value were 76.9%, 9 7.5% and 93.0% for the XBC and 38.4%, 9 7.5% and 83.3%, respectively for VUC. For the prediction of suspicious or positive cystoscopic finding sensitivity, the specificity and negative predictive value were 75.0%, 95.2%, and 93.0% respectively for the XBC and 41.7%, 97.6%, and 85.4% for VUC. The sensitivities for papilary urothelial neoplasms of low malignant potential (PUNLMP), low- and high-grade tumours were 0.0%, 66.7% an d 100.0% for the XBC and 0.0%, 66 .7% and 42.9%, respectively for VUC. CONCLUSIONS: The XBC showed significantly higher overall sensitivity and negative predictive value than VUC and could be used to increase the recommended follow-up cystoscopy time intervals. Complementing the XBC and voided urinary cytology does not improve performance in comparison to the XBC alone.

Urinary Markers of Oxidative Stress in Children with Autism Spectrum Disorder (ASD).

Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691-0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502-0.781) and the percentage of explained variance (R2 = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress.