3,3'-Dichlorobiphenyl (PCB 11) is a byproduct of industrial processes and detected in environmental samples. PCB 11 and its metabolites are present in human serum, and emerging evidence demonstrates that PCB 11 is a developmental neurotoxicant. However, little is known about the metabolism of PCB 11 in humans. Here we investigated the metabolism of PCB 11 and the associated metabolomics changes in HepG2 cells using untargeted high-resolution mass spectrometry. HepG2 cells were exposed for 24 h to PCB 11 in DMSO or DMSO alone. Cell culture media were analyzed with ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Thirty different metabolites were formed by HepG2 cells exposed to 10 μM PCB 11, including monohydroxylated, dihydroxylated, hydroxylatedmethoxylated, and methoxylated-di-hydroxylated metabolites, and the corresponding sulfo and glucuronide conjugates. The methoxylated PCB metabolites were observed for the first time in a human-relevant model. 4-OH-PCB 11 (3,3'-dichlorobiphenyl-4-ol) and the corresponding catechol metabolite, 4,5-di-OH-PCB 11 (3',5-dichloro-3,4-dihydroxybiphenyl), were unambiguously

Large-scale knowledge graphs (KGs) are shown to become more important in current information systems. To expand the coverage of KGs, previous studies on knowledge graph completion need to collect adequate training instances for newly-added relations. In this paper, we consider a novel formulation, zero-shot learning, to free this cumbersome curation. For newly-added relations, we attempt to learn their semantic features from their text descriptions and hence recognize the facts of unseen relations with no examples being seen. For this purpose, we leverage Generative Adversarial Networks (GANs) to establish the connection between text and knowledge graph domain: The generator learns to generate the reasonable relation embeddings merely with noisy text descriptions. Under this setting, zero-shot learning is naturally converted to a traditional supervised classification task. Empirically, our method is model-agnostic that could be potentially applied to any version of KG embeddings, and consistently yields performance improvements on NELL and Wiki dataset.

The characterization of the metabolism of lower chlorinated PCB, such as 4-chlorobiphenyl (PCB3), is challenging because of the complex metabolite mixtures formed in vitro and in vivo. We performed parallel metabolism studies with PCB3 and its hydroxylated metabolites to characterize the metabolism of PCB3 in HepG2 cells using nontarget high-resolution mass spectrometry (Nt-HRMS). Briefly, HepG2 cells were exposed for 24 h to 10 μM PCB3 or its seven hydroxylated metabolites in DMSO or DMSO alone. Six classes of metabolites were identified with Nt-HRMS in the culture medium exposed to PCB3, including monosubstituted metabolites at the 3′-, 4′-, 3-, and 4-(1,2-shift product) positions and disubstituted metabolites at the 3′,4′-position. 3′,4′-Di-OH-3 (4′-chloro-3,4-dihydroxybiphenyl), which can be oxidized to a reactive and toxic PCB3 quinone, was a central metabolite that was rapidly methylated. The resulting hydroxylated-methoxylated metabolites underwent further sulfation and, to a lesser extent, glucuronidation. Metabolomic analyses revealed an altered tryptophan metabolism in HepG2 cells following PCB3 exposure. Some PCB3 metabolites were associated with alterations of endogenous metabolic pathways, including amino acid metabolism, vitamin A (retinol) metabolism, and bile acid biosynthesis. Indepth studies are needed to investigate the toxicities of PCB3 metabolites, especially the 3′,4′-di-OH-3 derivatives identified in this study.

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