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Related Concept Videos

Teratogenicity01:07

Teratogenicity

The ability of a drug to produce structural deformations and functional abnormalities in the developing embryo or the fetus is called teratogenicity, and the drug producing this effect is known as a teratogen. Teratogenic effects include stillbirth, miscarriage, intrauterine growth restriction, and neurocognitive delay. A teratogen may affect the embryo at different stages of development, which is important in determining the type and extent of the damage. During blastocyst formation, the early...
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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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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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In Vivo Modeling of the Morbid Human Genome using Danio rerio
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Published on: August 24, 2013

A mixed model framework for teratology studies.

Johan Braeken1, Francis Tuerlinckx

  • 1Department of Methodology and Statistics, Tilburg University, Tilburg, the Netherlands and CITO, Arnhem, the Netherlands. j.braeken@uvt.nl

Biostatistics (Oxford, England)
|July 25, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel mixed model framework for analyzing complex teratology data, improving understanding of anomaly relationships and covariate effects in developmental toxicity studies.

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Assessing Teratogenic Changes in a Zebrafish Model of Fetal Alcohol Exposure
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Area of Science:

  • Biostatistics
  • Developmental Toxicology
  • Statistical Modeling

Background:

  • Teratology studies often involve complex multivariate binary anomaly data.
  • Existing models may not fully capture inter-anomaly relationships or covariate effects.

Purpose of the Study:

  • To present a flexible mixed model framework for analyzing multivariate binary anomaly data in teratology.
  • To incorporate covariate effects, flexible random effects distributions, and copula functions for modeling anomaly interrelations.
  • To provide an integrated approach for investigating exposure effects and anomaly correlations.

Main Methods:

  • Developed a mixed model framework utilizing finite mixture distributions for random effects.
  • Applied copula functions to model the dependency structure among different anomalies.
  • Incorporated covariate effects to assess general and anomaly-specific influences.

Main Results:

  • The proposed framework effectively models characteristic multivariate binary anomaly data.
  • Demonstrated the ability to account for complex interrelations between anomalies.
  • Facilitated the investigation of covariate effects on anomaly occurrence.

Conclusions:

  • The presented mixed model framework offers a robust and integrated approach for teratology data analysis.
  • This method enhances the understanding of covariate impacts and anomaly interdependencies.
  • Applicable to studies like the Boston Anticonvulsant Teratogenesis study for objective diagnostic measurement.