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2025年12月嘲风作品集(一)

已有 794 次阅读 2026-1-30 17:01 |个人分类:作品发表|系统分类:论文交流

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▲ Vol 97 Issue 47 | December , 2025

Adjuvant Tracer Strategy Combined with a Portable Steam Penetration Gas Membrane Separation Device for Peroxynitrite Detection

Chenbing Xi,Minyi Luo,Yong Zhang,Zhengyi Chen

Sample pretreatment is an indispensable part of the analysis of complex biological matrices to ensure the accuracy and reliability of analytical results, but it is rather difficult to develop a miniaturized and portable strategy to minimize matrix interference. In light of the difficulties resulted by interference from biological matrices and the short half-life of some constituents, this work introduces a combination of an adjuvant tracer with a high-efficiency and portable sample pretreatment device, the portable steam penetration gas membrane separation (PSPGMS) device, achieving analysis of complex biological samples under the interference of matrices. In this work, methanol was utilized as adjuvant to capture free ONOO– in living cells under UV irradiation for its low background signal and eco-friendliness; the PSPGMS device conducted all-in-one separation, absorption, and derivatization for the detection of formaldehyde generated by the oxidization between methanol and the products of ONOO– photolysis, achieving a linear response (R2 = 0.9919) across 2.0–20.0 μmol/L and a recovery rate of 87.4–115.0% in the analysis of rat hepatocytes. With a detection limit of 0.5 μmol/L, excellent portability, and integration, this strategy is well-suited for on-site rapid and visualized detection, independent of bulky and expensive instruments.

https://pubs.acs.org/doi/10.1021/acs.analchem.5c04503

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▲ Vol 97 Issue 51 | 30 December , 2025

RSR-MSI: Reference-Based Super-Resolution for Mass Spectrometry Imaging of Tissues and Single Cells

Yifan Fang, Cipeng Wu, Chentao Zhang, Yizhu Xu, Zhibin Yin, Zhouyi Xu, Wei Hang

learning approaches have demonstrated significant potential in MSI, they typically require large training data sets or paired images, which are often unavailable. Herein, we propose the reference-based super-resolution for mass spectrometry imaging (RSR-MSI) method, with optical microscopy images as reference frames to extract abundant texture information. By integrating this with ion intensity data from the original MS images, we develop an image-specific super-resolution network. Employing solely a single low-resolution MS image coupled with a reference optical image, we successfully reconstruct high-resolution MS images for biological tissues and single cells, producing results with rich chemical and textural details. This approach significantly decreases the routine pixel-by-pixel scanning time by an order of magnitude while achieving high spatial resolution using existing mass spectrometry instruments without any customized modifications. Overall, our work introduces and validates the application of image super-resolution methods within the realm of single-cell MSI at subcellular resolution, paving the way for the development of high-spatial-resolution and high-throughput MSI for cellular biology research.

https://pubs.acs.org/doi/10.1021/acs.analchem.5c05933

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静远嘲风-南京(MY Scimage) 成立于2007年,嘲风取自中国传统文化中龙生九子,子子不同的传说,嘲风为守护屋脊之瑞兽,喜登高望远;静远取自成语“宁静致远”,登高莫忘初心,远观而不可务远。

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