Evidence map›Paper›PMID 30718672›Full record

ArticleScientific reports2019

Biophysical Insights on the Enrichment of Cancer Cells from Whole Blood by (Affinity) Filtration.

Marc Zinggeler, Thomas Brandstetter, Jürgen Rühe

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
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 at 1 institution in 1 country.

Marc ZinggelerLaboratory for Chemistry and Physics of Interfaces, Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Koehler-Allee 103, 79110, Freiburg, Germany.
Thomas BrandstetterLaboratory for Chemistry and Physics of Interfaces, Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Koehler-Allee 103, 79110, Freiburg, Germany.
Jürgen RüheLaboratory for Chemistry and Physics of Interfaces, Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Koehler-Allee 103, 79110, Freiburg, Germany. ruehe@imtek.de.
University of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating tumor cells (CTCs) play a key role during the metastatic process of human cancers and their reliable detection and characterization could enable new and effective ways of cancer diagnosis, monitoring and treatment. However, due to their ultralow concentration in patient blood, the CTCs must first be enriched before such analysis can be performed. Classical microfiltration is an important and widely used method for the mechanical enrichment of CTCs. This method exploits that CTCs are generally larger than the accompanying blood cells, however, does not differentiate the cells in other ways. In an affinity filtration, selectivity is added by functionalizing the membrane with specific antibodies against a CTC-characteristic surface protein such as the epithelial cell adhesion molecule (EpCAM). A common shortcoming of both filtration approaches is that there is still a poor understanding of the enrichment process and the systems developed so far are frequently operated under non-optimized conditions. To address this, systematic filtration experiments are performed in this work using the EpCAM

Indexed as

Membranes, ArtificialCell SeparationEquipment DesignFiltrationHumansMCF-7 CellsNeoplasmsNeoplastic Cells, CirculatingMembranes, Artificial

Identifiers

PMID30718672
PMCPMC6362249
OpenAlexW2913695190

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.