{
  "abstract": "Scanning transmission soft X-ray microscopy (STXM), combined with near-edge X-ray absorption fine structure (NEXAFS), enables the mapping of elemental distributions and chemical properties at a spatial resolution of tens of nanometers. A common approach for analyzing STXM data is to compare NEXAFS spectra obtained from regions of interest (ROIs). However, ROI-based spectral comparison typically requires frequent switching among multiple software applications. ROI spectrum extraction, spectrum normalization, and figure creation are often performed using separate applications, which increase analytical time and the likelihood of errors.•We developed a Python-based workflow for STXM-NEXAFS data analysis that implements functions for extracting mean ROI spectra in napari, an open-source multidimensional image viewer.•These napari-based functions provide a seamless workflow from ROI selection to figure preparation within Python, without switching between multiple software applications.•The seamless workflow improves analytical efficiency and facilitates broader use of STXM-NEXAFS analysis.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan",
    "Institute of Materials Structure Science Photon Factory, High Energy Accelerator Research Organization (KEK), 1-1 Oho, Tsukuba, Ibaraki, 305-0801, Japan",
    "Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Koya Kobayashi"
    },
    {
      "affs": [
        1
      ],
      "name": "Shohei Yamashita"
    },
    {
      "affs": [
        2
      ],
      "name": "Maki Asano"
    },
    {
      "affs": [
        0
      ],
      "name": "Rota Wagai"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7c6gv11aczb18.bib",
  "cited_by": 0,
  "doi": "10.1016/j.mex.2026.104212",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13718659/?tool=EBI",
  "id": "7c6gv11aczb18",
  "issns": [
    "2215-0161"
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  "landing_url": "https://europepmc.org/article/PMC/PMC13718659",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Chemistry"
    ],
    [
      "openalex",
      "3108|X-ray Spectroscopy and Fluorescence Analysis"
    ]
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  "openalex": "W7222847508",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13718659/pdf/?tool=EBI",
  "pmcid": "PMC13718659",
  "pmid": "42959939",
  "published": "2026-10-17",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/7c6gv11aczb18.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:38Z",
      "native_id": "PMC:PMC13718659",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13718659"
    },
    {
      "first_seen": "2026-11-01T00:20:50Z",
      "native_id": "MED:42959939",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42959939"
    },
    {
      "first_seen": "2026-11-02T12:22:38Z",
      "native_id": "PMC13718659",
      "source": "pmc",
      "url": "https://doi.org/10.1016/j.mex.2026.104212"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "openalex:3108|X-ray Spectroscopy and Fluorescence Analysis",
      "subfield": "applied-instrumentation"
    }
  ],
  "title": "A seamless workflow for STXM-NEXAFS data analysis using napari: implementation of an ROI spectrum extraction function",
  "title_text": "A seamless workflow for STXM-NEXAFS data analysis using napari: implementation of an ROI spectrum extraction function",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T12:22:38Z",
  "url": "https://research.draconitic.com/paper/7c6gv11aczb18",
  "venue": "MethodsX",
  "versions": []
}