Reproducibility Assessment
Reproducibility Assessment - Related Videos
08:49
Reproducible Mouse Sciatic Nerve Crush and Subsequent Assessment of Regeneration by Whole Mount Muscle Analysis
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Cited by 59 •
2012
In this report we describe a method to crush mouse sciatic nerve. This method uses readily available hemostatic forceps and easily and reproducibly produces complete sciatic nerve crush. In addition, we describe a method to prepare muscle whole mounts suitable for analysis of nerve regeneration after sciatic nerve crush.
09:02
Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
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Cited by 2 •
2025
Here, we present the measurement protocol of the bi-directional axial transmission (BDAT) ultrasonic device in detail and test it in a reproducibility study, considering 14 healthy participants and 3 operators. Reliability, measured with the intraclass correlation coefficients (ICC), was good to excellent for four parameters of interest.
05:17
A Reproducible Computerized Method for Quantitation of Capillary Density using Nailfold Capillaroscopy
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Cited by 17 •
2015
Capillaroscopy is a non-invasive, efficient, relatively inexpensive and easy-to-learn methodology for directly visualizing capillaries in the microcirculation. However, only one publication to date describes the reliability of a complex software program available for quantitating capillaroscopy data. Here, we present a simple, reliable protocol for quantitating capillaries using a standardized algorithm.
08:33
Reproducible Arterial Denudation Injury by Infrarenal Abdominal Aortic Clamping in a Murine Model
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Cited by 5 •
2016
Understanding the cellular and molecular mechanisms of re-endothelialization following arterial denudation injury is of paramount importance in preventing thrombosis and restenosis of arteries. Here we describe a protocol for reproducible arterial denudation injury of the infrarenal abdominal aorta. The procedure was developed to investigate the underlying mechanisms that regulate endothelial regeneration using mouse models.
08:26
Refinement of OnePot PURE and Crude Ribosome Production for Reproducible Cell-free Protein Synthesis
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2025
We present an updated protocol for the production of the OnePot 'Protein synthesis Using Recombinant Elements' (PURE) system and crude ribosomes for cell-free protein synthesis, focusing on controlling cell growth to minimize batch-to-batch variations.
FAQs
Reproducibility assessment gains credibility by testing whether reported results remain stable when key study features are examined systematically. Protocols, sample characteristics, measurement choices, data-processing decisions, statistical analyses, and reported outcomes can each influence the apparent finding. Separating these factors helps researchers identify whether variation reflects the phenomenon itself or the study design.
Repeated analysis examines whether the original data produce the reported outcome when the stated processing and statistical procedures are followed. An independent experimental approach asks whether comparable results emerge through a separate investigation under similar conditions. Considering both approaches can reveal whether a conclusion depends mainly on the original dataset, analytical choices, or broader experimental consistency.
Neural findings may vary because researchers measure related features in different ways or because biological samples do not respond identically. Reproducibility assessment therefore considers measurement choices alongside sample characteristics rather than treating every discrepancy as evidence against the underlying result. This distinction is important when interpreting neural mechanisms or disease-related findings across studies.
A practical assessment begins by reviewing the protocol and sample characteristics, then tracing data-processing steps and statistical analyses before comparing the reported outcomes. Researchers can repeat the analysis with the original data or conduct an experiment under comparable conditions. Recording where procedures or results diverge helps locate sources of variation and clarifies how strongly the conclusion is supported.
It is especially useful when researchers need to judge the reliability of proposed neural mechanisms or findings related to neurological disease. Examining whether results persist across analyses or comparable experiments can expose effects linked to limited sample sizes, incomplete methodological reporting, or biological variation. The resulting evidence supports more cautious interpretation and better-informed experimental design.
Findings from an assessment can show which conclusions remain consistent and which depend on measurement, processing, sampling, or reporting choices. Researchers can use that information to refine experimental designs and distinguish robust patterns from unstable ones. In neuroscience, this strengthens the evidence used to build models of brain function and interpret disease-related neural processes.