Evidence map›Paper›PMID 29780258›Full record

ArticleOncoTargets and therapy2018

Influence of different ex vivo cell culture methods on the proliferation and anti-tumor activity of cytokine-induced killer cells from gastric cancer patients.

Bin Shi, Aixia Sun, Xiaorui Zhang

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2018. 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
0.2field-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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Research Progress of Immunotherapy for Gastric Cancer.Technology in cancer research & treatment
    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.

Bin ShiDepartment of Gastrointestinal Surgery, Liaocheng People's Hospital of Taishan Medical University, Liaocheng, Shandong Province, China.
Aixia SunDepartment of Clinical Laboratory, Liaocheng People's Hospital, Liaocheng Clinical School of Taishan Medical University, Liaocheng, Shandong Province, China.
Xiaorui ZhangDepartment of Health, Liaocheng People's Hospital of Taishan Medical University, Liaocheng, Shandong Province, China.
Liaocheng People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn cytokine-induced killer (CIK) cell therapy, the phenotypes and the numbers of CIK cells have a great influence on the therapeutic effects. This study aimed to investigate the effects of different ex vivo cell culture methods on the proliferation and cytotoxicity of CIK cells that were obtained from gastric cancer patients. PATIENTS AND

methodsCIK precursor (Pre-CIK) cells were collected by either hydroxyethyl starch (HES) sedimentation (HES method, unpurified group) or Ficoll-Hypaque density gradient centrifugation (Ficoll method, purified group). Cell number, collection time, and morphology of Pre-CIK cells in the two groups were determined. The proliferation ability, cytokines, phenotypes, and cytotoxicity of CIK cells in the two groups were evaluated ex vivo and in vivo.

resultsIn this study, the number of Pre-CIK cells in the unpurified group was significantly higher than that in the purified group (

conclusionThe removal of Ficoll-Hypaque purification step reduces the time and cost of the Pre-CIK separation and provides more CIK cells with higher cytotoxicity, which is of great importance in the clinical application of CIK cell therapy.

Indexed as

CIK precursor cellscytokine-induced killer cellsgastric cancerred blood cells

Identifiers

PMID29780258
PMCPMC5951225
OpenAlexW2799889912

What OpenQuestion holds

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LicenceCC BY-NC
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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.