21 research outputs found

    Tiny Grains Give Huge Gains: Nanocrystal-Based Signal Amplification for Biomolecule Detection

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    Nanocrystals, despite their tiny sizes, contain thousands to millions of atoms. Here we show that the large number of atoms packed in each metallic nanocrystal can provide a huge gain in signal amplification for biomolecule detection. We have devised a highly sensitive, linear amplification scheme by integrating the dissolution of bound nanocrystals and metal-induced stoichiometric chromogenesis, and demonstrated that signal amplification is fully defined by the size and atom density of nanocrystals, which can be optimized through well-controlled nanocrystal synthesis. Further, the rich library of chromogenic reactions allows implementation of this scheme in various assay formats, as demonstrated by the iron oxide nanoparticle linked immunosorbent assay (ILISA) and blotting assay developed in this study. Our results indicate that, owing to the inherent simplicity, high sensitivity and repeatability, the nanocrystal based amplification scheme can significantly improve biomolecule quantification in both laboratory research and clinical diagnostics. This novel method adds a new dimension to current nanoparticle-based bioassays

    Self-Assembly of Phospholipid–PEG Coating on Nanoparticles through Dual Solvent Exchange

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    We coated nanoparticles including iron oxide nanoparticles and quantum dots with phospholipid–PEG using the newly developed dual solvent exchange method and demonstrated that, compared with the conventional film hydration method, the coating efficiency and quality of coated nanoparticles can be significantly improved. A better control of surface coating density and the amount of reactive groups on nanoparticle surface is achieved, allowing conjugation of different moieties with desirable surface concentrations, thus facilitating biomedical applications of nanoparticles

    The relationship between Rubisco content and total chloroplast volume per leaf area.

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    <p>The line represents the regression equation: y = 0.79x+1.36, R<sup>2</sup> = 0.88, <i>P</i><<i>0.01</i>. Data sources: <i>Nicotiana tabacum</i> □ <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062036#pone.0062036-Evans3" target="_blank">[21]</a>; <i>Chenopodium album</i> ▴ <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062036#pone.0062036-Oguchi1" target="_blank">[48]</a>; <i>Aucuba japonica</i> Thunb. △ <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062036#pone.0062036-Muller1" target="_blank">[24]</a>. The two data points in dotted cycles are from transgenic tobacco with a reduced Rubisco content.</p

    <i>A</i>/C<sub>i</sub> response curves of newly expanded leaves in Shanyou 63 (a) and Yangdao 6 (b).

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    <p>The symbols of solid cycles, open cycles and solid triangles represent high, intermediate and low N supply, respectively.</p

    The relationships between chloroplast size and the ratio of mesophyll conductance (g<sub>m</sub>) to Rubisco content on Shanyou 63 (solid cycles) and Yangdao 6 (open cycles).

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    <p>Chloroplast surface area (S<sub>chl</sub>) and volume (V<sub>chl</sub>) were calculated from the Cesaro formula. The lines represent the following regressions: (a) y = 2.54x/(x−1.98) R<sup>2</sup> = 0.63 <i>P</i> > 0.05; (b) y = 2.99x/(x−0.73) R<sup>2</sup> = 0.88 <i>P</i><0.01; (c) y = 3.72x/(x−1.91) R<sup>2</sup> = 0.89 <i>P</i><0.01; (d) y = 1.15x+2.06 R<sup>2</sup> = 0.82 <i>P</i><0.05.</p

    The relationships between leaf photosynthetic rate (<i>A</i>) and (a) leaf N content, and (b) Rubisco content and in Shanyou 63 (closed cycles) and Yangdao 6 (open cycles).

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    <p>The lines represent the following regression equations: (a) y = 0.12x+6.33 R<sup>2</sup> = 0.82 <i>P</i><0.01 for Shanyou 63; y = 0.17x−0.60 R<sup>2</sup> = 0.79 <i>P</i><0.01 for Yangdao 6; (b) y = 0.22x+8.59R<sup>2</sup> = 0.78 <i>P</i><0.01 for Shanyou 63; y = 0.40x−1.53 R<sup>2</sup> = 0.91 <i>P</i><0.01.</p

    Growth variables of rice seedlings grown at different N supplies.

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    <p>Rice plants (<i>cv.</i> Shanyou 63 and Yangdao 6) were supplied with N at three different levels (low: 20 mg L<sup>−1</sup> N, intermediate: 40 mg L<sup>−1</sup> N, and high: 100 mg L<sup>−1</sup> N). Data are means ± SD of 5 individual plants. Variables were determined 40 days after the start of treatment.</p><p>Notes: Significant differences (<i>P</i><5%) between N supplies or varieties were indicated by different lowercase letters or different uppercase letters, respectively. RMR, SCMR and LMR represent root mass ratio, leaf sheath and culm mass ratio and leaf mass ratio, respectively. They were calculated as the ratio of separate dry mass to whole plant dry mass. SLW represents specific leaf weight, and was calculated as the ratio of leaf fresh weight to leaf area.</p

    The relationships between chloroplast size and photosynthetic N-use efficiency (PNUE), and the ratio of leaf photosynthetic rate (<i>A</i>) to Rubisco.

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    <p>The lines represent the following regression equations: (a) y = 91.04x/(x–2.87), R<sup>2</sup> = 0.53, <i>P</i><0.01; (b) y = 121.76x/(x–0.96), R<sup>2</sup> = 0.75, <i>P</i><0.01; (c) y = 180.56x/(x–2.12), R<sup>2</sup> = 0.72, <i>P</i><0.01; (d) y = 0.21x/(x–2.86), R<sup>2</sup> = 0.53, <i>P</i><0.01; (e) y = 0.29x/(x–0.95), R<sup>2</sup> = 0.69, <i>P</i><0.01; (f) y = 0.42x/(x–2.06), R<sup>2</sup> = 0.63, <i>P</i><0.01. Data sources: data of solid squares were collected from Wuyujing 3 (<i>Oryza sativa</i> L. ssp. japonica) with different N supplies; data of open squares were from Shanyou 63 with different N forms and water supply <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062036#pone.0062036-Li2" target="_blank">[42]</a>; data of solid and open cycles were from Shanyou 63 and Yangdao 6 with different N supplies.</p
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