Colorimetric Au Nanoparticle Probe for Speciation Test of Arsenite and Arsenate Inspired by Selective Interaction between Phosphonium Ionic Liquid and Arsenite

The exposure of millions of people to unsafe levels of arsenite (As^III) and arsenate (As^V) in drinking waters calls for the development of low-cost methods for on-site monitoring these two arsenic species in waters. Herein, for the first time, tetradecyl (trihexyl) phosphonium chloride ionic liquid was found to selectively bind with As^III via extended X-ray absorption fine structure (EXAFS) analysis. Based on the finding, an As^III-specific probe was developed by modifying gold nanoparticles with the ionic liquid. Futhermore, Hofmeister effect was primarily observed to significantly affect the sensitivity of gold nanoparticle probe. With the colorimetric probe, we developed a protocol for naked eye speciation test of As^III and As^V at levels below the World Health Organization (WHO) guideline of 10 μg L^–1. This method featured with high tolerance to common coexisting ions such as 10 mM PO₄^3–, and was validated by assaying certified reference and environmental water samples

Submonolayer-Pt-Coated Ultrathin Au Nanowires and Their Self-Organized Nanoporous Film: SERS and Catalysis Active Substrates for Operando SERS Monitoring of Catalytic Reactions

For their unique properties, core–shell bimetal nanostructures are currently of immense interest. However, their synthesis is not a trivial work, and most works have been conducted on nanoparticles. We report herein a new synthetic tactic for submonolyer-Pt coated ultrathin Au nanowires (NWs). Besides providing a strong electromagnetic field for Raman signal enhancing, the underlined Au NWs markedly enhanced the catalytic activity of Pt atoms through increasing their dispersity and altering their electronic state. The integration of excellent SERS and high catalytic activity within Au@Pt NWs enable it work as platform for catalyzed reaction study. As a proof of principle, the self-organized Au@Pt NWs thin film is employed in operando SERS monitoring of the <i>p</i>-nitrothiophenol reduction process. In addition to providing kinetic data for structure–activity relationship study, the azo-intermidate independent path is also directly witnessed. This synthetic tactic can be extended to other metals, thus offering a general approach to modulate the physical/chemical properties of both core and shell metals

Toward Full Spectrum Speciation of Silver Nanoparticles and Ionic Silver by On-Line Coupling of Hollow Fiber Flow Field-Flow Fractionation and Minicolumn Concentration with Multiple Detectors

The intertransformation of silver nanoparticles (AgNPs) and ionic silver (Ag­(I)) in the environment determines their transport, uptake, and toxicity, demanding methods to simultaneously separate and quantify AgNPs and Ag­(I). For the first time, hollow fiber flow field-flow fractionation (HF5) and minicolumn concentration were on-line coupled together with multiple detectors (including UV–vis spectrometry, dynamic light scattering, and inductively coupled plasma mass spectrometry) for full spectrum separation, characterization, and quantification of various Ag­(I) species (<i>i.e</i>., free Ag­(I), weak and strong Ag­(I) complexes) and differently sized AgNPs. While HF5 was employed for filtration and fractionation of AgNPs (>2 nm), the minicolumn packed with Amberlite IR120 resin functioned to trap free Ag­(I) or weak Ag­(I) complexes coming from the radial flow of HF5 together with the strong Ag­(I) complexes and tiny AgNPs (<2 nm), which were further discriminated in a second run of focusing by oxidizing >90% of tiny AgNPs to free Ag­(I) and trapped in the minicolumn. The excellent performance was verified by the good agreement of the characterization results of AgNPs determined by this method with that by transmission electron microscopy, and the satisfactory recoveries (70.7–108%) for seven Ag species, including Ag­(I), the adduct of Ag­(I) and cysteine, and five AgNPs with nominal diameters of 1.4 nm, 10 nm, 20 nm, 40 nm, and 60 nm in surface water samples

Negatively charged silver nanoparticles cause retinal vascular permeability by activating plasma contact system and disrupting adherens junction

<p>Silver nanoparticles (AgNPs) have been extensively used as antibacterial component in numerous healthcare, biomedical and consumer products. Therefore, their adverse effects to biological systems have become a major concern. AgNPs have been shown to be absorbed into circulation and redistributed into various organs. It is thus of great importance to understand how these nanoparticles affect vascular permeability and uncover the underlying molecular mechanisms. A negatively charged mecaptoundeonic acid-capped silver nanoparticle (MUA@AgNP) was investigated in this work. <i>Ex vivo</i> experiments in mouse plasma revealed that MUA@AgNPs caused plasma prekallikrein cleavage, while positively charged or neutral AgNPs, as well as Ag ions had no effect. <i>In vitro</i> tests revealed that MUA@AgNPs activated the plasma kallikrein-kinin system (KKS) by triggering Hageman factor autoactivation. By using specific inhibitors aprotinin and HOE 140, we demonstrated that KKS activation caused the release of bradykinin, which activated B2 receptors and induced the shedding of adherens junction protein, VE-cadherin. These biological perturbations eventually resulted in endothelial paracellular permeability in mouse retina after intravitreal injection of MUA@AgNPs. The findings from this work provided key insights for toxicity modulation and biomedical applications of AgNPs.</p

Silver Nanoparticles Induced RNA Polymerase-Silver Binding and RNA Transcription Inhibition in Erythroid Progenitor Cells

Due to its antimicrobial activity, nanosilver (nAg) has become the most widely used nanomaterial. Thus far, the mechanisms responsible for nAg-induced antimicrobial properties and nAg-mediated toxicity to organisms have not been clearly recognized. Silver (Ag) ions certainly play a crucial role, and the form of nanoparticles can change the dissolution rate, bioavailability, biodistribution, and cellular uptake of Ag. However, whether nAg exerts direct “particle-specific” effects has been under debate. Here we demonstrated that nAg exhibited a robust inhibition on RNA polymerase activity and overall RNA transcription through direct Ag binding to RNA polymerase, which is separated from the cytotoxicity pathway induced by Ag ions. nAg treatment <i>in vitro</i> resulted in reduced hemoglobin concentration in erythroid cells; <i>in vivo</i> administration of nAg in mice caused profound reduction of hemoglobin content in embryonic erythrocytes, associated with anemia in the embryos. Embryonic anemia and general proliferation deficit due to the significant inhibition on RNA synthesis, at least partially, accounted for embryonic developmental retardation upon nAg administration. To date, there is no conclusive answer to the sources of nAg-mediated toxicity: Ag ions or “particle-specific” effects, or both. We here demonstrated that both Ag ions and nAg particles simultaneously existed inside cells, demonstrating the “Trojan horse” effects of nAg particles in posing biological impacts on erythroid cells. Moreover, our results suggested that “particle-specific” effects could be the predominant mediator in eliciting biological influences on erythroid cells under relatively low concentrations of nAg exposure. The combined data highlighted the inhibitory effect of nAg on RNA polymerase activity through a direct reciprocal interaction

Graphene Oxide Induces Toll-like Receptor 4 (TLR4)-Dependent Necrosis in Macrophages

Graphene and graphene-based nanomaterials display novel and beneficial chemical, electrical, mechanical, and optical characteristics, which endow these nanomaterials with promising applications in a wide spectrum of areas such as electronics and biomedicine. However, its toxicity on health remains unknown and is of great concern. In the present study, we demonstrated that graphene oxide (GO) induced necrotic cell death to macrophages. This toxicity is mediated by activation of toll-like receptor 4 (TLR4) signaling and subsequently in part <i>via</i> autocrine TNF-α production. Inhibition of TLR4 signaling with a selective inhibitor prevented cell death nearly completely. Furthermore, <i>TLR4</i>-deficient bone marrow-derived macrophages were resistant to GO-triggered necrosis. Similarly, GO did not induce necrosis of HEK293T/TLR4-null cells. Macrophagic cell death upon GO treatment was partially attributed to RIP1-RIP3 complex-mediated programmed necrosis downstream of TNF-α induction. Additionally, upon uptake into macrophages, GO accumulated primarily in cytoplasm causing dramatic morphologic alterations and a significant reduction of the macrophagic ability in phagocytosis. However, macrophagic uptake of GO may not be required for induction of necrosis. GO exposure also caused a large increase of intracellular reactive oxygen species (ROS), which contributed to the cause of cell death. The combined data reveal that interaction of GO with TLR4 is the predominant molecular mechanism underlying GO-induced macrophagic necrosis; also, cytoskeletal damage and oxidative stress contribute to decreased viability and function of macrophages upon GO treatment

m⁶A depletion enhances the stability of development- and apoptosis-associated gene transcripts.

(A) qRT-PCR results confirmed the up-regulated expression in P7 cKO cerebellums of selected genes. The major functions of detected genes are shown under the lines. (B) Immunostaining for Sox2 (red), Nestin (green), and Mettl3 (purple) in neural stem cell lines established from Ctrl and Mettl3 cKO neonatal mice. Scale bar, 100 μm. (C) The RNA half-lives of genes detected in (A). Values and error bars in (A) and (C) represent the mean and SEM of three independent experiments. (D) qRT-PCR results confirmed higher expression levels of apoptosis-promoting genes (Dapk1, Fadd, Ngfr) in cerebellums of P7 wild-type mice than those in the cortex. (E) qRT-PCR results confirmed the up-regulated expression of the apoptosis-promoting genes in the cKO CGCs. Data related to this figure are shown in S1 Data. Data shown are means ± SEM. *p-value p-value p-value p-value t test. CGC, cerebellar granule cell; cKO, Mettl3 conditional knockout; Ctrl, control; Mettl3, methyltransferase-like 3; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; RT-PCR, reverse transcription-polymerase chain reaction; SEM, standard error of the mean.</p

Characterization of the <i>Mettl3</i> conditional knockout mice.

<p>(A) Body weight changes of the Ctrl and cKO mice during the first 2 wk after birth. (B) Kaplan–Meier survival curves showing the survival rates of both Ctrl and cKO mice. (C) Tail suspension test of both Ctrl and cKO mice. (D, E) Open field test of Ctrl and cKO mice for their speed (D) and total traveled distance (E). (F) MRI of mice sagittal brain section. Scale bar, 1 mm. (G, H) Surface areas of the whole brain (G) and cerebellum (H) of Ctrl and cKO mice. Sagittal section. The data underlying this figure can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004880#pbio.2004880.s019" target="_blank">S1 Data</a>. Data shown are means ± SEM, <i>n</i> = 4. **<i>p</i>-value < 0.01, ***<i>p</i>-value < 0.001, Student <i>t</i> test. cKO, <i>Mettl3</i> conditional knockout; Ctrl, control; <i>Mettl3</i>, methyltransferase-like 3; MRI, magnetic resonance imaging; SEM, standard error of the mean.</p

<i>Mettl3</i> conditional knockout induces apoptosis of newborn granule cells.

<p>(A) BrdU (green), Ki67 (red), and DAPI (blue) immunofluorescent staining of Ctrl and cKO mouse cerebellums 2 h after BrdU injection. (B) TUNEL (green) and PI (red) staining of P7 Ctrl and cKO mouse cerebellums. (C) Cleaved Caspase-3 (green), Ki67 (red), and DAPI (blue) immunofluorescent staining of P7 Ctrl and cKO mouse cerebellums. (D) BrdU (green), Ki67 (red), and DAPI (blue) immunofluorescent staining of Ctrl and cKO mouse cerebellums 48 h after BrdU injection. (E) Proportion of Ki67⁺/DAPI⁺ cells in the EGL of P7 Ctrl and cKO mice. (F, G) Density of TUNEL⁺ (F) and Cleaved Caspase-3⁺ (G) cells in P7 Ctrl and cKO mouse cerebellums. (H) Density of BrdU⁺/Ki67⁻ cells in the EGL of Ctrl and cKO mice 48 h post–BrdU injection. Scale bars in (A–D), 200 μm for left panels; 25 μm for right panels. Data related to this figure are shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004880#pbio.2004880.s019" target="_blank">S1 Data</a>. Data shown are means ± SEM. Three sections of each sample were analyzed. ***<i>p</i>-value < 0.001, Student <i>t</i> test. BrdU, bromodeoxyuridine; cKO, <i>Mettl3</i> conditional knockout; Ctrl, control; EGL, external granular layer; Ki67, antigen identified by monoclonal antibody Ki 67; <i>Mettl3</i>, methyltransferase-like 3; PI, Propidium iodide; SEM, standard error of the mean.</p

<i>Mettl3</i> conditional knockout causes cerebellar hypoplasia in mice.

<p>(A) Macromorphological comparison between brains of the Ctrl and cKO mice. (B, C) Weight of the whole brain (B) and cerebellum (C) of the Ctrl and cKO mice. (D) Histological abnormalities of cerebellum in cKO mice shown by HE staining, NeuN, D-28K, and GFAP immunohistochemical staining. Scale bar, 200 μm. (E, F) Density difference of granule cells (E) and Purkinje cells (F) in the Ctrl and cKO mouse cerebellums. (G, H) Dendrite length (G) and mean calbindin D-28K staining intensity. (H) Difference of Purkinje cells in the Ctrl and cKO cerebellums. P14 mice were used in all studies. Data related to this figure are shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2004880#pbio.2004880.s019" target="_blank">S1 Data</a>. Data shown are means ± SEM. For cell number count in (E) and (F), <i>n</i> = 3; for dendrite length and D-28K staining intensity in (G) and (H), <i>n</i> = 10. ***<i>p</i>-value < 0.001, Student <i>t</i> test. cKO, <i>Mettl3</i> conditional knockout; Ctrl, control; D-28K, calbindin 1; EGL, external granular layer; GFAP, glial fibrillary acid protein; HE, hematoxylin and eosin; IGL, internal granular layer; <i>Mettl3</i>, methyltransferase-like 3; ML, molecular layer; NeuN, neuronal nuclei; PCL, Purkinje cell layer; SEM, standard error of the mean.</p