Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

214
Body:The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...
214
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

644
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
644
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

967
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
967
Bone Marrow Sampling and Transplants01:22

Bone Marrow Sampling and Transplants

1.1K
Bone marrow transplant is a potential cure for several diseases, including cancer and specific genetic disorders. Notably, this procedure is applicable for patients suffering from aplastic anemia, certain types of leukemia, severe combined immunodeficiency disease (SCID), Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, thalassemia, sickle-cell disease, and certain cancers.
The transplant begins with high doses of chemotherapy and radiation treatment, which aim to destroy...
1.1K
Statistical Significance01:50

Statistical Significance

21.8K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
21.8K
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

1.6K
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating the Suitability of HepaRG Cells for Regulatory Micronucleus Testing: Comparing Results for a Diverse Set of 28 Chemicals to Regulatory Accepted TK6 Cells.

Environmental and molecular mutagenesis·2026
Same author

Transitional initiatives for advancing the phasing out of the use of animals for drug and chemical safety testing: The IHI VICT3R project for reducing the use of animals by implementing virtual control groups.

NAM journal·2026
Same author

Ensuring Quality in Preclinical Research: The Importance of Being Human.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

The Liver S9 Proteome of Rat and Hamster: Global Profiling and Targeted Cytochrome P450 Quantification Reveal Induction-Responsive Remodeling.

Journal of proteome research·2026
Same author

<i>In Silico</i> Prediction of Potential Bile Salt Export Pump Inhibitors Using Pharmacophore Models and Consensus Machine Learning.

Journal of chemical information and modeling·2026
Same author

The nitrovinyl moiety determines the cyto- and genotoxic profiles of β-nitrostyrene derivatives: evidence from in silico and in vitro evaluation.

Archives of toxicology·2026

Related Experiment Video

Updated: Jan 31, 2026

Author Spotlight: Optimized Method for Isolating Rat Neutrophils and NETs from Bone Marrow
08:56

Author Spotlight: Optimized Method for Isolating Rat Neutrophils and NETs from Bone Marrow

Published on: April 26, 2024

2.7K

The rat bone marrow micronucleus test: Statistical considerations on historical negative control data.

Bernd-Wolfgang Igl1, Annette Bitsch2, Frank Bringezu3

  • 1Bayer AG, Research and Clinical Sciences Statistics, Müllerstr. 178, 13353, Berlin, Germany.

Regulatory Toxicology and Pharmacology : RTP
|December 21, 2018
PubMed
Summary

This study proposes statistical methods for analyzing historical control data in the mammalian erythrocyte micronucleus test (OECD 474). It provides reference data and validated tolerance limits for genotoxicity testing.

Keywords:
Bone marrowHistorical negative control dataMicronucleus testRatStatistical analysesStratification parametersTolerance intervals

More Related Videos

Isolation and Cultivation of Mandibular Bone Marrow Mesenchymal Stem Cells in Rats
08:58

Isolation and Cultivation of Mandibular Bone Marrow Mesenchymal Stem Cells in Rats

Published on: August 25, 2020

5.9K
Technique for Isolation and Culture of Rat Jaw Bone Marrow Mesenchymal Stem Cells
04:04

Technique for Isolation and Culture of Rat Jaw Bone Marrow Mesenchymal Stem Cells

Published on: May 31, 2024

1.5K

Related Experiment Videos

Last Updated: Jan 31, 2026

Author Spotlight: Optimized Method for Isolating Rat Neutrophils and NETs from Bone Marrow
08:56

Author Spotlight: Optimized Method for Isolating Rat Neutrophils and NETs from Bone Marrow

Published on: April 26, 2024

2.7K
Isolation and Cultivation of Mandibular Bone Marrow Mesenchymal Stem Cells in Rats
08:58

Isolation and Cultivation of Mandibular Bone Marrow Mesenchymal Stem Cells in Rats

Published on: August 25, 2020

5.9K
Technique for Isolation and Culture of Rat Jaw Bone Marrow Mesenchymal Stem Cells
04:04

Technique for Isolation and Culture of Rat Jaw Bone Marrow Mesenchymal Stem Cells

Published on: May 31, 2024

1.5K

Area of Science:

  • Toxicology
  • Genotoxicity Testing
  • Regulatory Science

Background:

  • Recent OECD Guidelines for the Testing of Chemicals emphasize statistical rigor in genotoxicity testing.
  • The mammalian erythrocyte micronucleus test (OECD 474) is a key regulatory in vivo assay requiring robust data analysis.
  • Accurate assessment of historical negative control data is crucial for experiment validity and result interpretation.

Purpose of the Study:

  • To evaluate statistical methodologies for handling historical negative control data in OECD 474 studies.
  • To propose validated statistical approaches and reference data for genotoxicity testing.
  • To ensure reliable interpretation of regulatory in vivo test results.

Main Methods:

  • Compilation of 891 negative control rat data from valid OECD 474 studies across four laboratories.
  • Analysis-of-Variance (ANOVA) to identify significant stratification parameters (laboratory, strain).
  • Development of one-sided parametric tolerance intervals to establish historical negative control limits, assuming near-normal distribution of micronucleus frequencies.

Main Results:

  • Laboratory and strain were identified as significant factors influencing micronucleus frequencies, while gender was not.
  • Micronucleus frequencies in polychromatic erythrocytes per animal were found to be approximately normally distributed.
  • A simulation-based strategy was employed to assess the stability of control limits based on the number of experiments.

Conclusions:

  • The proposed statistical methods provide a robust framework for analyzing historical control data in OECD 474 studies.
  • Validated tolerance limits enhance the reliability of genotoxicity test validity and result interpretation.
  • These findings support the updated OECD guidelines for improved regulatory toxicology assessments.