Chlorinated paraffins (CPs) are produced at more than one million tons per year. Technical CPs mixtures may contain impurities, which end up in consumer products. In the present study, 17 technical CPs mixtures were investigated for the potential occurrence of potential impurities. By applying the DR-CALUX bioassay, 3 out of 17 technical mixtures were shown to elicit responses at 4 h exposure time, but much lower at 48 h. Constitutional defined CPs materials did not show responses. Subsequently different groups of known AhR-agonists and compounds suspected to be present in technical CPs mixtures were investigated. Benzene, (poly)chlorobenzene, non-dioxin like polychlorinated naphthalenes (PCNs), and three-ringed polyaromatic hydrocarbons (PAHs) did not result in a significant response at 4 h or 48 h. TCDD, non-ortho PCBs, dioxin-like PCNs, four or five ringed PAHs and their chlorinated analogues resulted in a significant response. TCDD and the non-ortho PCBs showed the highest potency and stability, while dioxin-like PCNs, PAHs, and the chlorinated PAHs were clearly inactivated (metabolized) at longer incubation. Altogether, the present findings substantiate that AhR-mediated responses of CPs technical mixtures in the DR-CALUX bioassay are caused by impurities, most likely some intermediate stable AhR-agonists such as dioxin-like PCNs or (chlorinated) PAHs. The current study shows that impurities in CPs technical mixtures need to be investigated for assessing the safety of technical CPs mixtures.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.tiv.2021.105098 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Class-Wise Combination of Mixture-Based Data Augmentation for Class Imbalance Learning of Focal Liver Lesions in Abdominal CT Images.
J Imaging Inform Med
January 2025
Department of Software Convergence, Seoul Women's University, Hwarango 621, Nowongu, Seoul, 01797, Republic of Korea.
In this paper, we propose a method to address the class imbalance learning in the classification of focal liver lesions (FLLs) from abdominal CT images. Class imbalance is a significant challenge in medical image analysis, making it difficult for machine learning models to learn to classify them accurately. To overcome this, we propose a class-wise combination of mixture-based data augmentation (CCDA) method that uses two mixture-based data augmentation techniques, MixUp and AugMix.
View Article and Find Full Text PDFCharacterization of insulin and bile acid complexes in liposome by different mass spectrometry techniques.
Anal Bioanal Chem
January 2025
Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, Jiangsu Key Laboratory of Biomedical Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China.
Insulin bound with ligand molecules can improve its bioavailability in oral formulations. In this work, the interactions between insulin and bile acids of taurocholic acid (TCA) and glycocholic acid (GCA) are characterized using different mass spectrometry (MS) methods. Electrospray (ESI)-MS analysis revealed that GCA and TCA could interact with insulin individually or together through non-covalent bonds, and the products included mGCA-insulin, nTCA-insulin, and mGCA-nTCA-insulin complexes.
View Article and Find Full Text PDFUnsupervised data imputation with multiple importance sampling variational autoencoders.
Sci Rep
January 2025
School of Mathematics and Statistics, Shaoguan University, Shaoguan, 512005, China.
Recently, deep latent variable models have made significant progress in dealing with missing data problems, benefiting from their ability to capture intricate and non-linear relationships within the data. In this work, we further investigate the potential of Variational Autoencoders (VAEs) in addressing the uncertainty associated with missing data via a multiple importance sampling strategy. We propose a Missing data Multiple Importance Sampling Variational Auto-Encoder (MMISVAE) method to effectively model incomplete data.
View Article and Find Full Text PDFA quantitative prediction method utilizing whole omics data for biosensing.
Sci Rep
January 2025
BioResource Research Center, RIKEN, 3-1-1, Koyadai, Tsukuba, 305-0074, Ibaraki, Japan.
Omics data provide a plethora of quantifiable information that can potentially be used to identify biomarkers targeting the physiological processes and ecological phenomena of organisms. However, omics data have not been fully utilized because current prediction methods in biomarker construction are susceptible to data multidimensionality and noise. We developed OmicSense, a quantitative prediction method that uses a mixture of Gaussian distributions as the probability distribution, yielding the most likely objective variable predicted for each biomarker.
View Article and Find Full Text PDFEnhanced breathing effort in pulmonary function tests by CO2/O2 gas mixture and barometric whole-body plethysmography in healthy and feline lower airway disease cats.
Am J Vet Res
January 2025
National Taiwan University Veterinary Hospital, National Taiwan University, Taipei, Taiwan.
Objective: Enhancing ventilatory effort during pulmonary function testing can help reveal flow limitations not evident in normal tidal breathing. This study aimed to assess the efficacy and tolerability of using a CO2/O2 gas mixture to enhance tidal breathing with a barometric whole-body plethysmography system in both healthy cats and those with feline lower airway disease (FLAD).
Methods: This prospective study included healthy cats and those with FLAD, which underwent pulmonary function testing and were exposed to a 10% CO2/90% O2 gas mixture in a barometric whole-body plethysmography chamber, with CO2 concentrations maintained within the target range of 5% to 10%.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!