Evidence map›Paper›PMID 35282100›Full record

ArticleAnnals of translational medicine2022

A novel combined fluorescent probe staining method for circulating tumor cell identification.

Huansheng Wang, Fajun Pei, Hao Li, Bing Li, Shili Han, Huajie Yu, Sheng Li

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 4 institutions in 1 country.

Huansheng Wang *Cheeloo College of Medicine, Shandong University, Jinan, China.
Fajun Pei *Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Hao LiShandong Pharmaceutical Research Institute, Jinan, China.
Bing LiShandong Pharmaceutical Research Institute, Jinan, China.
Shili HanWuhan YZY Medical Science and Technology Co., Wuhan, China.
Huajie YuDepartment of Anesthesiology, Zhangqiu District People's Hospital, Jinan, China.
Sheng LiCheeloo College of Medicine, Shandong University, Jinan, China.
Shandong First Medical University · CNShandong Academy of Pharmaceutical Sciences · CNWuhan YZY Biopharma (China) · CNZhangqiu City People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To develop a novel highly accurate circulating tumor cell (CTC) identification method and to validate its application in cancer diagnostics and/or prognostics. Methods: We verified and validated the combined fluorescent probe staining protocol (combination of three fluorescent probes: Dil, Hoechst 33342, and PY) through CTC and non-CTC (white blood cell) morphological comparison of five tumor cell lines (THP-1, HEC, HEPG2, Eca-109, HeLa) Results: We successfully developed and optimized the protocol, and validated the use of combined fluorescent probe staining for the identification of CTCs in the peripheral blood (PB) of tumor cell lines and tumor patients. Comparable CTC and non-CTC morphologies were observed for combined fluorescent probe staining and Giemsa staining methods Conclusions: We developed a combined fluorescent probe staining method with higher CTC identification accuracy than Wright's Giemsa staining, and propose this technique as a novel clinical diagnostic/prognostic tool.

Indexed as

circulating tumor cell (CTC)Fluorescent probeidentificationimmunocytochemistry (ICC)

Identifiers

PMID35282100
PMCPMC8848375
OpenAlexW4206806162

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.