Evidence map›Paper›PMID 35529190›Full record

ArticleRSC advances2019

Medium optimization based on comparative metabolomic analysis of chicken embryo fibroblast DF-1 cells.

Jia Lin, Xiaoping Yi, Yingping Zhuang

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. 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

3 authors at 1 institution in 1 country.

Jia LinState Key Laboratory of Bioreactor Engineering, School of Bioengineering, East China University of Science and Technology 130 Mei Long Road, Xu Hui District Shanghai 200237 China ypzhuang@ecust.edu.cn +86 21 64253337.ORCID https://orcid.org/0000-0001-8557-1942
Xiaoping YiState Key Laboratory of Bioreactor Engineering, School of Bioengineering, East China University of Science and Technology 130 Mei Long Road, Xu Hui District Shanghai 200237 China ypzhuang@ecust.edu.cn +86 21 64253337.
Yingping ZhuangState Key Laboratory of Bioreactor Engineering, School of Bioengineering, East China University of Science and Technology 130 Mei Long Road, Xu Hui District Shanghai 200237 China ypzhuang@ecust.edu.cn +86 21 64253337.
East China University of Science and Technology · CN

Funding

1/4 Alcohol Research Consortium in HIV-Administrative Core (ARCH-AC)U24AA020801 · NIAAA · JOHNS HOPKINS UNIVERSITY · PI CHANDER, GEETANJALI, MCCAUL, MARY E · 2011 to 2021
$3.5M
NIAAA NIH HHS U24 AA020801
6 · The paper itself

Abstract

Chicken embryo fibroblast DF-1 cells are increasingly being used in the production of avian virus vaccines. However, the relatively low proliferative capacity does not meet the requirements of industrial production. In this study, we attempted to improve the proliferative capacity of DF-1 cells. The results of intracellular metabolomics showed that 28 types of metabolites could play roles in DF-1 cell growth based on the variance and timing analysis of intracellular metabolites from DF-1 cells grown in two media with distinct growth difference, DMEM/F12 (1 : 1) and DMEM. By examining the differences in the components in the two media, DOE was used to screen and optimize the growth medium for DF-1 cells. The maximum cell density was 40.72% higher, and the infectious bursal disease virus (IBDV) titer was 2.68 times higher, in the optimized medium than in the control. This study proposes a complete solution from metabolomics to media optimization.

Identifiers

PMID35529190
PMCPMC9070647
OpenAlexW2970379896

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.