Evidence map›Paper›PMID 40004121›Full record

ArticleInternational journal of molecular sciences2025

Sample Preparation Protocol for Laboratory Cryo-Soft X-Ray Microscopy for Studying Cellular Nanoparticle Uptake.

Komang G Y Arsana, Martin Svenda, Hans M Hertz

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Komang G Y ArsanaBiomedical and X-Ray Physics, Department of Applied Physics, KTH Royal Institute of Technology, 10691 Stockholm, Sweden.ORCID 0000-0002-0535-3708
Martin SvendaBiomedical and X-Ray Physics, Department of Applied Physics, KTH Royal Institute of Technology, 10691 Stockholm, Sweden.
Hans M HertzBiomedical and X-Ray Physics, Department of Applied Physics, KTH Royal Institute of Technology, 10691 Stockholm, Sweden.

Funding

Swedish Research Council VR 2020-04587
6 · The paper itself

Abstract

Soft X-ray microscopy (SXM) is a powerful technique for high-resolution biomedical imaging, enabling the observation of bio-nano interactions in near-native conditions without the need for heavy metal staining and fluorescence labeling. A laboratory soft X-ray microscope (LSXM) was developed to bridge the resolution gap between light microscopy and electron microscopy in cellular imaging. However, LSXMs employ a lower-brightness X-ray source in comparison to those operated in synchrotron facilities, which can negatively affect the contrast of X-ray micrographs. Therefore, proper sample preparation is essential to achieve optimal imaging results. This paper details an LSXM sample preparation protocol for investigating cellular nanoparticle uptake. Samples are prepared using optimized parameters for both manual plunge-freezing and automated vitrification, ensuring the rapid transition of biological material into a solid state with controllable thickness in the 5-10 μm range, preserving cellular structures and enabling optimal X-ray transmission for cellular imaging. We demonstrate the effectiveness of this protocol in facilitating the observation of nanoparticle uptake in two different biological samples: murine macrophages and acanthamoeba. Controlling ice thickness improves X-ray transmission through the specimen, enhancing the contrast and image quality of SXM.

Indexed as

MicroscopyNanoparticlesSpecimen HandlingAnimalsMacrophagesMiceVitrificationX-Rayscell imagingcryofixationnanoparticlesample preparationwater windowX-ray microscopy

Identifiers

PMID40004121
PMCPMC11855688

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.