Evidence map›Paper›PMID 29187898›Full record

ArticleTheranostics2017

Precisely Enumerating Circulating Tumor Cells Utilizing a Multi-Functional Microfluidic Chip and Unique Image Interpretation Algorithm.

Mingxing Zhou, Hui Zheng, Zhaoba Wang, Ren Li, Xiaoran Liu, Weikai Zhang, Zihua Wang, Huiping Li, Zewen Wei, Zhiyuan Hu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Theranostics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. Detection of HER2ChemMedChem · 2020
    Article
  4. Article
  5. A New Method for CTC Images Recognition Based on Machine Learning.Frontiers in bioengineering and biotechnology · 2020
    Article
  6. 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

10 authors at 4 institutions in 1 country.

Mingxing ZhouCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Hui ZhengCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Zhaoba WangSchool of Information and Communication Engineering, North University of China, Taiyuan 030051, China.
Ren LiCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Xiaoran LiuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Breast Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Weikai ZhangCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Zihua WangCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Huiping LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Breast Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Zewen WeiCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
Zhiyuan HuCAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology of China, Beijing 100190, China.
National Center for Nanoscience and Technology · CNNorth University of China · CNPeking University Cancer Hospital · CNUniversity of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enumerating circulating tumor cells (CTCs) has been demonstrably useful in cancer treatment. Although there are several approaches that have proved effective in isolating CTC-like cells, the crucial identification of CTCs continues to rely on the manual interpretation of immunofluorescence images of all cells that have been isolated. This procedure is time consuming and more importantly, CTC identification relies on subjective criteria that may differ between examiners. In this study, we describe the design, testing, and verification of a microfluidic platform that provides accurate and automated CTC enumeration using a common objective criterion.

Indexed as

Lab-On-A-Chip DevicesAlgorithmsBreast NeoplasmsCell Line, TumorFemaleHEK293 CellsHumansImage Processing, Computer-AssistedMicrofluidicsNeoplastic Cells, Circulatingautomated cell enumeration.breast cancercirculating tumor cellsmicrofluidic chip

Identifiers

PMID29187898
PMCPMC5706094
OpenAlexW2766601848

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.