Literature DB >> 4762874

A quantitative analysis of the genetics of resting blood lactic acid levels in mice.

P L Hatchell, J W MacInnes.   

Abstract

Resting blood lactate levels were measured in inbred mouse strains, their F(1), and several of their segregating generations to determine whether the level of lactic acid is influenced by genetic factors. The inbred strains in each of the two sets used differed significantly from one another for this character. Only one strain showed a significant sex difference. The data could not be fully analyzed because of the failure to fulfill Mather's first criterion for an adequate scale. Nonallelic interactions, in particular, additive x dominance and dominance x dominance, were found to influence the generation means. Genotype x environment interaction was detected and eliminated by log transformation. Negative heterosis was exhibited by all but one noninbred generation.-The data suggest that genes influencing the character are dispersed between the parental lines and that interactions are predominantly of the duplicate kind. A buffering system by which lactate levels are kept at a minimum is proposed.

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Year:  1973        PMID: 4762874      PMCID: PMC1212996     

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  2 in total

1.  Assessment of tissue anoxemia in chronic anemia by the arterial lactate/pyruvate ratio and excess lactate formation.

Authors:  D J Seibert; F G Ebaugh
Journal:  J Lab Clin Med       Date:  1967-02

2.  Lactate metabolism in anxiety neurosis.

Authors:  F N Pitts; J N McClure
Journal:  N Engl J Med       Date:  1967-12-21       Impact factor: 91.245

  2 in total
  2 in total

1.  Combining nitrous oxide with carbon dioxide decreases the time to loss of consciousness during euthanasia in mice--refinement of animal welfare?

Authors:  Aurelie A Thomas; Paul A Flecknell; Huw D R Golledge
Journal:  PLoS One       Date:  2012-03-15       Impact factor: 3.240

2.  Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data.

Authors:  Irene Alfaras; Keisuke Ejima; Camila Vieira Ligo Teixeira; Clara Di Germanio; Sarah J Mitchell; Samuel Hamilton; Luigi Ferrucci; Nathan L Price; David B Allison; Michel Bernier; Rafael de Cabo
Journal:  Cell Rep       Date:  2021-08-17       Impact factor: 9.423

  2 in total

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