Literature DB >> 21265003

Interpretation of cellular proliferation data: avoid the panglossian.

Mario Roederer.   

Abstract

There are several statistics that may be calculated to characterize a cellular proliferation experiment. By far, the most commonly-reported statistic is the percent of cells in the final culture that have divided; however, this statistic has significant limitations. Other statistics provided by software modeling provide a much richer characterization of the biological response; however, their use also comes with caveats. Here, I discuss the practical application of these statistics, including their limitations and interdependencies, using hypothetical data. The goal of this perspective is to prevent the blind reliance or overly optimistic ("panglossian") interpretation of the statistics generated by software, so that researchers and reviewers have a more-informed basis for drawing conclusions from the data. Published 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21265003     DOI: 10.1002/cyto.a.21010

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  94 in total

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2.  Combined supplementation of ascorbic acid and thyroid hormone T3 affects tenocyte proliferation. The effect of ascorbic acid in the production of nitric oxide.

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3.  Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division.

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Journal:  J Math Biol       Date:  2013-12-13       Impact factor: 2.259

4.  Human labour is associated with altered regulatory T cell function and maternal immune activation.

Authors:  N M Shah; L F Edey; N Imami; M R Johnson
Journal:  Clin Exp Immunol       Date:  2019-11-03       Impact factor: 4.330

5.  IL-2 Modulates the TCR Signaling Threshold for CD8 but Not CD4 T Cell Proliferation on a Single-Cell Level.

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Journal:  J Immunol       Date:  2017-02-03       Impact factor: 5.422

6.  Optimized staining and proliferation modeling methods for cell division monitoring using cell tracking dyes.

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Authors:  Yael M Abadi; Hyungjun Jeon; Kim C Ohaegbulam; Lisa Scandiuzzi; Kaya Ghosh; Kimberly A Hofmeyer; Jun Sik Lee; Anjana Ray; Claudia Gravekamp; Xingxing Zang
Journal:  J Immunol       Date:  2013-03-01       Impact factor: 5.422

Review 8.  Epigenetic editing: How cutting-edge targeted epigenetic modification might provide novel avenues for autoimmune disease therapy.

Authors:  Matlock A Jeffries
Journal:  Clin Immunol       Date:  2018-02-06       Impact factor: 3.969

9.  Viral-mimicking protein nanoparticle vaccine for eliciting anti-tumor responses.

Authors:  Nicholas M Molino; Medea Neek; Jo Anne Tucker; Edward L Nelson; Szu-Wen Wang
Journal:  Biomaterials       Date:  2016-02-01       Impact factor: 12.479

10.  CD122 blockade restores immunological tolerance in autoimmune type 1 diabetes via multiple mechanisms.

Authors:  Xiaomei Yuan; Yi Dong; Naoya Tsurushita; J Yun Tso; Wenxian Fu
Journal:  JCI Insight       Date:  2018-01-25
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