Skip to main content

Methods of Chronobiometric Analysis of Mitochondrial Function

  • Chapter
Mitochondrial Medicine

The methodical hints are given on the basis of the inferential Halberg’s cosinor regression for obtaining the optimal information from experimental data organized in the frame of the Halberg’s circa(semi)dian design. First, the population of experimental animals has to be defined exactly to secure its homogeneity. Second, a random choice of separate animals must be kept. Third, optimal sampling times have to be settled and realized. Fourth, it is recommended to transform the measured data into the Mesor RelatedValues (MRV), to be able to compare mutually the results from various variables. Fifth, the best way of expressing the results for consecutive medical considerations and decisions is a graph of the approximating function, including confidence and tolerance corridors. Critically is mentioned the common practice to use standard errors or deviations (representing only 50–68% confidence or tolerance) and p-value, falsely overestimating the impression of an effect. Sixth, the same principles should be applied to differences between measurements – a relatively new idea. The evaluation of global effect can be misleading. These modes of presentation are illustrated on coenzymes Q9 and Q10, as well as on the oxidative phosphorylation cascade for Complex I using data from control and diabetic rats.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. D’Agostino RB (1971) An omnibus test of normality for moderate and large size samples. Biometrika 58:341–348

    Article  Google Scholar 

  2. Bingham Ch, Arbogast B, Cornélissen GG, Lee JK, Halberg F (1982) Inferential statistical methods for estimating and comparing cosinor parameters. Chronobiologia 9:397–439

    PubMed  CAS  Google Scholar 

  3. Diem K, Seldrup J (1982) Geigy scientific tables, Vol. 2. In: Lentner C (ed.) Introduction to Statistics. Statistical Tables. Mathematical Formulae, 8th edn. Ciba Geigy, Basle, 240 pp

    Google Scholar 

  4. Evans SJW, Mills P, Dawson J (1988) The end of the P value? Br Heart J 60:177–180

    Article  PubMed  CAS  Google Scholar 

  5. Fedor-Freybergh PG, Mikulecký M (2005) From the descriptive towards inferential statistics. Hundred years since conception of the Student’s t-distribution. Neuro Endocrinol Lett 26:167–171

    PubMed  Google Scholar 

  6. Gardner MJ, Altman DG (1986) Confidence intervals rather than P values: estimation rather than hypothesis testing. Br Med J 292:746–750

    Article  CAS  Google Scholar 

  7. Goodman SN (1992) A comment on replication, P-values and evidence. Stat Med 11:875–879

    Article  PubMed  CAS  Google Scholar 

  8. de Groot MH (1987) A conversion with CR Rao. Stat Sci 1:53–67

    Article  Google Scholar 

  9. Gvozdjáková A, Kucharská J, Cornélissen G, Mikulecký M, Singh RB, Halberg F (2004) Variation in cardiac mitochondrial coenzyme Q10 and oxidative phosphorylation. Int J Cardiol 97(2):S15. Third International Congress on Cardiovascular Disease, Taipei, Taiwan, 26–28 November 2004

    Google Scholar 

  10. Gvozdjáková A, Kucharská J, Cornélissen G, Mikulecký M, Singh RB, Halberg F (2005a) Circadian and semicircadian variations of heart mitochondrial coenzyme Q in relationship to oxidative phosphorylation. Fourth Conference of the International Coenzyme Q 10 Association, Los Angeles, USA, 14–17 April 2005, Abstract Book, pp 113–115

    Google Scholar 

  11. Gvozdjáková A, Kucharská J, Cornélissen G, Mikulecký M, Singh RB, Halberg F (2005b) Heart mitochondrial coenzyme “Q10-chronome” and variations of oxidative phosphorylation in diabetic rats. Mitochondrion 5:15–16. Mitochondrial Medicine 2005 Meeting, St. Louis, USA, 15–18 June 2005

    Google Scholar 

  12. Kubáček L, Valach A, Mikulecký M (1989) Time series analysis with periodic components. Software manual.Bratislava: ComTel

    Google Scholar 

  13. Mikulecký M (2004) Confidence and tolerance intervals–a tool for biomedical data analysis aimed at clear evidence. Cardiology 13:211–215

    Google Scholar 

  14. Rothman KJ, Greenland S (1998) Modern Epidemiology, 2nd edn. Lippincott-Raven, Philadelphia, pp737

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer Science + Business Media B.V

About this chapter

Cite this chapter

Mikulecký, M. (2008). Methods of Chronobiometric Analysis of Mitochondrial Function. In: Gvozdjáková, A. (eds) Mitochondrial Medicine. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6714-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4020-6714-3_4

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-6713-6

  • Online ISBN: 978-1-4020-6714-3

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics