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Related Concept Videos

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Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
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Studies that assess how a drug is absorbed, distributed, metabolized, and excreted (ADME) at toxic doses are termed toxicokinetics. Understanding toxicokinetics helps predict adverse drug reactions (ADRs) and manage toxicity in humans.Toxicokinetics differs from pharmacokinetics mainly in the dose levels studied, with toxicokinetics focusing on higher toxic doses. The kinetics at these levels can be non-linear due to altered physiological processes. Toxicodynamics examines the relationship...
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Assessing Cytotoxicity of Metabolites of Typical Triazole Pesticides in Plants
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STUDIES ON TOXICITY.

E I Fulmer1, R E Buchanan

  • 1Laboratories of Chemistry and of Bacteriology, Iowa State College, Ames.

The Journal of General Physiology
|October 30, 2009
PubMed
Summary

Survivor curves for yeast treated with phenol do not follow logarithmic patterns. This suggests that methods evaluating disinfectant power based on logarithmic models may be misleading due to cell resistance variations.

Area of Science:

  • Microbiology
  • Biophysics
  • Biochemistry

Background:

  • Assessing the efficacy of disinfectants like phenol and alcohol on microorganisms is crucial for public health and industrial applications.
  • Previous studies have sometimes interpreted microbial survivor curves using logarithmic or monomolecular reaction models.
  • Understanding the kinetics of microbial death under chemical stress is essential for developing effective sterilization protocols.

Purpose of the Study:

  • To investigate the survival kinetics of yeast cells exposed to phenol and phenol-alcohol mixtures.
  • To critically evaluate the applicability of logarithmic and monomolecular reaction models in describing microbial survivor curves.
  • To identify key factors influencing the rate of microbial death during disinfection.

Main Methods:

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  • Yeast cultures were subjected to treatment with phenol or a combination of phenol and alcohol.
  • The number of surviving yeast cells was quantified over time using resistance to methylene blue staining as a viability indicator.
  • Survivor counts were plotted against time to generate survival curves.

Main Results:

  • The generated survivor curves for yeast treated with phenol or phenol and alcohol were generally not logarithmic.
  • Observed similarities to logarithmic or monomolecular curves were deemed superficial and coincidental.
  • Significant variations in resistance among individual yeast cells were noted.

Conclusions:

  • Logarithmic and monomolecular reaction models are inappropriate for evaluating the disinfecting power of phenol and alcohol against yeast.
  • Such models can lead to misleading conclusions regarding disinfectant efficacy.
  • The inherent variation in resistance among individual microbial cells is a fundamental factor that must be considered when analyzing death rates.