Literature DB >> 16391426

Design and statistical methods in studies using animal models of development.

Michael F W Festing.   

Abstract

Experiments involving neonates should follow the same basic principles as most other experiments. They should be unbiased, be powerful, have a good range of applicability, not be excessively complex, and be statistically analyzable to show the range of uncertainty in the conclusions. However, investigation of growth and development in neonatal multiparous animals poses special problems associated with the choice of "experimental unit" and differences between litters: the "litter effect." Two main types of experiments are described, with recommendations regarding their design and statistical analysis: First, the "between litter design" is used when females or whole litters are assigned to a treatment group. In this case the litter, rather than the individuals within a litter, is the experimental unit and should be the unit for the statistical analysis. Measurements made on individual neonatal animals need to be combined within each litter. Counting each neonate as a separate observation may lead to incorrect conclusions. The number of observations for each outcome ("n") is based on the number of treated females or whole litters. Where litter sizes vary, it may be necessary to use a weighted statistical analysis because means based on more observations are more reliable than those based on a few observations. Second, the more powerful "within-litter design" is used when neonates can be individually assigned to treatment groups so that individuals within a litter can have different treatments. In this case, the individual neonate is the experimental unit, and "n" is based on the number of individual pups, not on the number of whole litters. However, variation in litter size means that it may be difficult to perform balanced experiments with equal numbers of animals in each treatment group within each litter. This increases the complexity of the statistical analysis. A numerical example using a general linear model analysis of variance is provided in the Appendix. The use of isogenic strains should be considered in neonatal research. These strains are like immortal clones of genetically identical individuals (i.e., they are uniform, stable, and repeatable), and their use should result in more powerful experiments. Inbred females mated to males of a different inbred strain will produce F1 hybrid offspring that will be uniform, vigorous, and genetically identical. Different strains may develop at different rates and respond differently to experimental treatments.

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Year:  2006        PMID: 16391426     DOI: 10.1093/ilar.47.1.5

Source DB:  PubMed          Journal:  ILAR J        ISSN: 1084-2020


  76 in total

1.  Examining differences in local collagen fiber crimp frequency throughout mechanical testing in a developmental mouse supraspinatus tendon model.

Authors:  Kristin S Miller; Brianne K Connizzo; Elizabeth Feeney; Jennica J Tucker; Louis J Soslowsky
Journal:  J Biomech Eng       Date:  2012-04       Impact factor: 2.097

2.  Characterizing local collagen fiber re-alignment and crimp behavior throughout mechanical testing in a mature mouse supraspinatus tendon model.

Authors:  Kristin S Miller; Brianne K Connizzo; Elizabeth Feeney; Louis J Soslowsky
Journal:  J Biomech       Date:  2012-07-08       Impact factor: 2.712

3.  Global undernutrition during gestation influences learning during adult life.

Authors:  Jason Landon; Michael Davison; Christian U Krägeloh; Nichola M Thompson; Jennifer L Miles; Mark H Vickers; Mhoyra Fraser; Bernhard H Breier
Journal:  Learn Behav       Date:  2007-05       Impact factor: 1.986

4.  Mouse Models of Lung Fibrosis.

Authors:  Olivia Mekhael; Safaa Naiel; Megan Vierhout; Aaron I Hayat; Spencer D Revill; Soumeya Abed; Mark D Inman; Martin R J Kolb; Kjetil Ask
Journal:  Methods Mol Biol       Date:  2021

5.  Prenatal bisphenol A exposure alters sex-specific estrogen receptor expression in the neonatal rat hypothalamus and amygdala.

Authors:  Jinyan Cao; Meghan E Rebuli; James Rogers; Karina L Todd; Stephanie M Leyrer; Sherry A Ferguson; Heather B Patisaul
Journal:  Toxicol Sci       Date:  2013-03-01       Impact factor: 4.849

6.  A call for transparent reporting to optimize the predictive value of preclinical research.

Authors:  Story C Landis; Susan G Amara; Khusru Asadullah; Chris P Austin; Robi Blumenstein; Eileen W Bradley; Ronald G Crystal; Robert B Darnell; Robert J Ferrante; Howard Fillit; Robert Finkelstein; Marc Fisher; Howard E Gendelman; Robert M Golub; John L Goudreau; Robert A Gross; Amelie K Gubitz; Sharon E Hesterlee; David W Howells; John Huguenard; Katrina Kelner; Walter Koroshetz; Dimitri Krainc; Stanley E Lazic; Michael S Levine; Malcolm R Macleod; John M McCall; Richard T Moxley; Kalyani Narasimhan; Linda J Noble; Steve Perrin; John D Porter; Oswald Steward; Ellis Unger; Ursula Utz; Shai D Silberberg
Journal:  Nature       Date:  2012-10-11       Impact factor: 49.962

7.  The response of C57BL/6J and BALB/cJ mice to increased housing density.

Authors:  Anthony Nicholson; Rachel D Malcolm; Phillip L Russ; Kristin Cough; Chadi Touma; Rupert Palme; Michael V Wiles
Journal:  J Am Assoc Lab Anim Sci       Date:  2009-11       Impact factor: 1.232

8.  Maternal undernutrition programmes atherosclerosis in the ApoE*3-Leiden mouse.

Authors:  Zoe Yates; Elizabeth J Tarling; Simon C Langley-Evans; Andrew M Salter
Journal:  Br J Nutr       Date:  2008-09-10       Impact factor: 3.718

9.  To breed or not to breed? Empirical evaluation of drug effects in adolescent rats.

Authors:  Jenny L Wiley; Rhys L Evans
Journal:  Int J Dev Neurosci       Date:  2008-11-08       Impact factor: 2.457

10.  The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis?

Authors:  Stanley E Lazic
Journal:  BMC Neurosci       Date:  2010-01-14       Impact factor: 3.288

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