Evidence map›Paper›PMID 39115329›Full record

ArticleACS nano2024

Quantitative Three-Dimensional Imaging Analysis of HfO

Zuoxin Xi, Haodong Yao, Tingfeng Zhang, Zongyi Su, Bing Wang, Weiyue Feng, Qiumei Pu, Lina Zhao

Abstract read
In one paragraph

Article in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

8 authors.

Zuoxin XiMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0003-1237-7780
Haodong YaoMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0001-5959-8594
Tingfeng ZhangMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0003-4578-4729
Zongyi SuMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.
Bing WangMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0003-1632-3114
Weiyue FengMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0002-1869-8000
Qiumei PuSchool of Information Engineering, Minzu University of China, Beijing 100081, China.ORCID 0000-0002-2106-237X
Lina ZhaoMulti-disciplinary Research Division, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0002-9796-0221

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is crucial for understanding mechanisms of drug action to quantify the three-dimensional (3D) drug distribution within a single cell at nanoscale resolution. Yet it remains a great challenge due to limited lateral resolution, detection sensitivities, and reconstruction problems. The preferable method is using X-ray nano-computed tomography (Nano-CT) to observe and analyze drug distribution within cells, but it is time-consuming, requiring specialized expertise, and often subjective, particularly with ultrasmall metal nanoparticles (NPs). Furthermore, the accuracy of batch data analysis through conventional processing methods remains uncertain. In this study, we used radioenhancer ultrasmall HfO

Indexed as

Deep LearningImaging, Three-DimensionalTomography, X-Ray ComputedHumansMetal NanoparticlesNanoparticlesSingle-Cell Analysiscancerdeep learningHfO2 nanoparticlenano-CT imagingradioenhancer

Identifiers

PMID39115329
PMCPMC11342356

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.