We are going to use LPS to stimulate inflammation and changes in lipid metabolism in HepG2. I have found in some papers that full DMEM (with FBS and penicillin/streptomycin) was used, but in another papers DMEM without FBS for 24 hours (for synchronization of growth stage) with subsequent treatment with LPS for next 24 hours was used. Some autors claim, HepG2 start to die substantially after 24 hours in DMEM without FBS also in conditions without additional stress with LPS. I will be gratefull for your answers.
There is no reason to synchronize the cells unless that is part of your analysis, looking at cell cycle. Otherwise, yes, use FBS.
And yes, cells can die with LPS stimulation. I would use less LPS if you want a longer time point.
I agree with Shen-An. I'll just add that antibiotics can affect inflammation, immune responses, and how fast cells grow (which means metabolism as well). I would highly recommend leaving them out for at least 12 hours prior to your treatment to avoid having the effects of antibiotics showing up in your experiments.
Dear Ludmila Paskova, Shen-An Hwang, Emily A Voigt, Katharina Iwanov
I am a librarian and have a weak experience of terms in this matter.
1. There were 3 articles, in the title of which there are words:
ti = ((inflammation OR changes) AND lipid AND ((((Hep G2) OR HepG2) AND cell) OR (liver cancer cell)))
see them below.
2. Usually we create a research topic map consisting of:
A. The basic articles - a few best articles containing basic information on the topic;
B. The articles potentially containing new methods, new information on the topic;
C. Terms - names of objects, properties, processes, methods that will be encountered in future research;
D. The questions that potentially arise in front of the researcher in the course of work on the topic, let's call them "subtopics".
The map is calculated by special programs based on the training model = a collection of articles on the topic. For a partial map, you need about 100 articles, and for a complete map, at least 500 articles on the topic.
We ourselves are engaged in the application of various programs to find potential directions of research for a given topic - the accumulation of experience in this area is our own research.
Therefore, we will be happy to make maps for you on the topics you are interested in (Of course totally free).
1.
Docosahexaenoic acid ameliorates palmitate-induced lipid accumulation and inflammation through repressing NLRC4 inflammasome activation in HepG2 cells
By: Luo, Xiaoqin; Yang, Yan; Shen, Tianran; et al.
NUTRITION & METABOLISM Volume: 9 Article Number: 34 Published: APR 19 2012
Free Full Text from Publisher View Abstract
Times Cited: 15
(from Web of Science Core Collection)
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2.
Changes in Lipid Metabolism by Soy beta-Conglycinin-Derived Peptides in HepG2 Cells
By: Mochizuki, Yuko; Maebuchi, Motohiro; Kohno, Mitsutaka; et al.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY Volume: 57 Issue: 4 Pages: 1473-1480 Published: FEB 25 2009
Full Text from Publisher View Abstract
Times Cited: 33
(from Web of Science Core Collection)
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3.
The growth inhibitory effect of conjugated linoleic acid on a human hepatoma cell line, HepG2, is induced by a change in fatty acid metabolism, but not the facilitation of lipid peroxidation in the cells
By: Igarashi, M; Miyazawa, T
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR AND CELL BIOLOGY OF LIPIDS Volume: 1530 Issue: 2-3 Pages: 162-171 Published: FEB 26 2001
Thank you for your answers. Another problem could be the composition of FBS: cytokines in serum. These could interfere with the LPS stimulation of inflammation.
Good afternoon
This is a map for the topic "Cytokines in serum and LPS stimulation of inflammation"
We can do an analysis of other topics, just help with a query to the Web of Science.
The procedure is as follows:
a query is being written for the Web of Science, which in the main finds articles relating to the topic under study.
Found articles become a learning model, from which the articles can be found with basic knowledge, with potential novelty and also terms and subtopics.
Therefore, the quality of the results depends on the quality of the query to the Web of Science.
file topic_report.docx = 20 topics from 1687 articles which have words
ts=(cytokines* serum LPS inflammat*)
in their titles, or keywords or abstracts.. Each topic is represented through 20 words and 20 thrases with which it is discussed in these articles. Really this terms are the names of methods, objects, properties, laws and so on for topic in question. In addition each topic has quotes from two articles in which it is most manifested.
file a1_basic.xlsm - articles with basic knowledge on the topic
file a3_novelty.xlsm - articles of last years potentially with novelty
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