Roxarsone (ROX) is an organoarsenic compound that is widely used as an additive in swine and poultry feed to inhibit disease and promote growth. Due to its low metabolism in animals, it is excreted in animal urine and feces leading to its widespread contamination of soils and aquatic ecosystems. Herein, we demonstrated that ROX can be adsorbed and subsequently reduced by a common iron sulfide (greigite - Fe3S4) in the pH range of 3.6 to 8.6. ROX removal processes followed a pseudo-second-order kinetic model that was strongly pH dependent. The nitro group of ROX was reduced by structural sulfide rather than dissolved sulfide or ferrous iron to generate an amino-group containing product, 4-hydroxy-3-aminophenylarsonic acid (HAPA). At neutral to alkaline pH values ROX and HAPA are preferentially adsorbed rather than reduced on the Fe3S4 surface. The interaction between ROX and Fe3S4 was minimally affected by interactions with coexisting cations, anions and natural organic matter (humic acid). These novel findings provide new insights for understanding the transformation mechanism of ROX by iron sulfides minerals, and have practical application for designing efficient systems for advanced treatment of ROX.

Herein, sulfur vacancies in magnetic greigite (SVs-Fe₃S₄) nanosheets were synthesized by a one-step solvothermal method by adjusting the ethylene glycol: water ratio. Electron paramagnetic resonance spectroscopy (EPR) and X-ray photoelectron spectroscopy (XPS) revealed that SV-rich Fe₃S₄ and SV-poor Fe₃S₄ were acquired using 100% ethylene glycol and 100% water as solvent, respectively. A peroxidase-like activity assay demonstrated that maximum reaction rates for H₂O₂-mediated oxidation of 3,3',5,5'-tetramethyl-benzidine (TMB) catalyzed by the SV-rich Fe₃S₄ was 2.3 times higher than SV-poor Fe₃S₄. Density functional theory (DFT) calculations and reactive oxygen species (ROS) detection confirmed that the enhanced peroxidase-like activity by SV-rich Fe₃S₄ was attributed to efficient adsorption of H₂O₂ and subsequent decomposition to hydroxyl radicals (•OH) on the SVs sites of Fe₃S₄. The SV-rich Fe₃S₄ nanozyme was employed to develop a simple, highly sensitive and selective assay for glucose detection with a linear range of 0.5-150 μM and a detection limit of 0.1 μM (S/N = 3). A smartphone application (App) was designed and applied to efficiently detect serum glucose with the integrated analytical system based on the SV-rich Fe₃S₄. These new findings highlight the important role of surface defects in nanozymes on generating peroxidase-like activity for glucose detection in point-of-care diagnosis.

Unlabelled

Desmoplasia and an inflammatory environment are defining features of pancreatic cancer. Unclear is how pancreatic cells that undergo oncogenic transformation can cross-talk with immune cells and how this contributes to the development of pancreatic lesions. Here, we demonstrate that pancreatic acinar cells expressing mutant KRAS can expedite their transformation to a duct-like phenotype by inducing local inflammation. Specifically, we show that KRAS(G12D) induces the expression of intercellular adhesion molecule-1 (ICAM-1), which serves as chemoattractant for macrophages. Infiltrating macrophages amplify the formation of KRAS(G12D)-caused abnormal pancreatic structures by remodeling the extracellular matrix and providing cytokines such as TNF. Depletion of macrophages or treatment with a neutralizing antibody for ICAM-1 in mice expressing oncogenic Kras under an acinar cell-specific promoter resulted in both a decreased formation of abnormal structures and decreased progression of acinar-to-ductal metaplasia to pancreatic intraepithelial neoplastic lesions.

Significance

We here show that oncogenic KRAS in pancreatic acinar cells upregulates the expression of ICAM-1 to attract macrophages. Hence, our results reveal a direct cooperative mechanism between oncogenic Kras mutations and the inflammatory environment to drive the initiation of pancreatic cancer.

Conventional epitaxy of semiconductor films requires a compatible single crystalline substrate and precisely controlled growth conditions, which limit the price competitiveness and versatility of the process. We demonstrate substrate-tolerant nano-heteroepitaxy (NHE) of high-quality formamidinium-lead-tri-iodide (FAPbI₃) perovskite films. The layered perovskite templates the solid-state phase conversion of FAPbI₃ from its hexagonal non-perovskite phase to the cubic perovskite polymorph, where the growth kinetics are controlled by a synergistic effect between strain and entropy. The slow heteroepitaxial crystal growth enlarged the perovskite crystals by 10-fold with a reduced defect density and strong preferred orientation. This NHE is readily applicable to various substrates used for devices. The proof-of-concept solar cell and light-emitting diode devices based on the NHE-FAPbI₃ showed efficiencies and stabilities superior to those of devices fabricated without NHE.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19846-y .

(Cell Reports 23, 313–326; April 3, 2018) In the originally published version of this article, the author list contained two errors. Specifically, David J. Kwiatkowski was misspelled as David J. Kwaitkowski, and William Y. Kim was inadvertently written as William T. Kim. Both names have been corrected online. The authors regret this error.

(Immunity 48, 812–830.e1–e14; April 17, 2018) In the originally published version of this article, the authors neglected to include Younes Mokrab and Aaron M. Newman as co-authors and misspelled the names of authors Charles S. Rabkin and Ilya Shmulevich. The author names have been corrected here and online. In addition, the concluding sentence of the subsection “Immune Signature Compilation” in the Method Details in the original published article was deemed unclear because it did not specify differences among the gene set scoring methods. The concluding sentences now reads “Gene sets from Bindea et al., Senbabaoglu et al., and the MSigDB C7 collection were scored using single-sample gene set enrichment (ssGSEA) analysis (Barbie et al., 2009), as implemented in the GSVA R package (Hänzelmann et al., 2013). All other signatures were scored using methods found in the associated citations.”

(Cell 173, 371–385.e1–e9; April 5, 2018) It has come to our attention that we made two errors in preparation of this manuscript. First, in the STAR Methods, under the subheading of “Hypermutators and Immune Infiltrates” within the “Quantification and Statistical Analysis” section, we inadvertently referred to Figures S7A–S7C for data corresponding to sample stratification by hypermutator status alone in the last sentence. It should have referred to Figure S6A–S6C. Second, the lists of highly frequent missense mutations for COAD (colon adenocarcinoma) and READ (rectum adenocarcinoma) displayed in Figure S7 were incorrect because when we ordered the mutations in the initial analysis, we mistakenly combined the two cancer types COAD and READ for analysis, despite the fact that they were listed as two separate cancer types in the x-axis of the figure. After re-ordering the mutations by frequency for COAD and READ independently, information on highly frequent missense mutations for each of these cancer types is different and updated now in the revised Figure S7. These errors don't change the major conclusions of the paper and have been corrected online. We apologize for any confusion they may have caused. [Figure-presented]

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on "chromatin-state" to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.