Best practices for the use and evaluation of animal serum as a component of cell culture medium
Abstract
Animal serum is a common additive for cell culture medium and is often required at 5 to 10% (v/v) for the attachment and growth of primary and continuous anchorage-dependent (monolayer) cultures. The use of animal serum in cell culture medium confers several advantages and also some risks. This article discusses the use of animal serum as a component of cell culture medium. The best practices associated with the sourcing, storage, thawing, testing, and mitigation of risk associated with the use of animal sera are among the topics described in this article.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Animal sera present several limitations, mainly associated with their complexity: lability, viral contamination (potentially with multiple viruses), and batch-to-batch variability.
“Animal sera present several limitations, mainly associated with their complexity: lability, viral contamination (potentially with multiple viruses), and batch-to-batch variability (Brunner et al., 2010; Gstraunthaler, 2003; Nims and Harbell, 2017).”
From Guidance document on Good cell and tissue culture practice 2.0 (GCCP 2.0) (2021) · cites this paper as Nims and Harbell, 2017
Cites
Drexler, H. G., & Uphoff, C. C. (2002) · Cytotechnology · doi:10.1023/a:1022913015916 · Cited by 340 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Guidance document on Good cell and tissue culture practice 2.0 (GCCP 2.0)
Pamies, D. (2021) · ALTEX · doi:10.14573/altex.2111011 · Cited by 100 · see citing works
- Authors
- Nims, R. W., & Harbell, J. W.
- Venue
- In Vitro Cellular & Developmental Biology - Animal
- Published
- 2017-07-21
- Volume
- 53
- Issue
- 8
- Pages
- 682-690
- ISSN
- 1071-2690
- 1543-706X
- Cited by
- 17
- References
- 1
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review