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B220 analysis with the local lymph node assay: proposal for a more flexible prediction model
Catherine J Betts1, Rebecca J Dearman, Ian Kimber
1Syngenta Central Toxicology Laboratory, Alderley Park, Macclesfield, Cheshire SK10 4TJ, UK. catherine.betts@syngenta.com
Journal of Applied Toxicology : JAT
|June 2, 2007
Summary
The mouse local lymph node assay (LLNA) can produce false positives. A refined LLNA model using B220(+) lymphocyte analysis aims to improve accuracy in identifying skin sensitizers and reduce false results.
Area of Science:
- Toxicology
- Immunology
- Dermatology
Background:
- The mouse local lymph node assay (LLNA) is a validated method for identifying skin sensitizers.
- The LLNA can yield false-positive results, particularly with skin irritants.
- An adjunct method measuring B220(+) lymphocytes aims to improve LLNA accuracy.
Purpose of the Study:
- To refine the predictive model for the LLNA by incorporating B220(+) lymphocyte analysis.
- To reduce false-positive reactions in skin sensitization testing.
- To develop a more robust method for distinguishing contact allergens from skin irritants.
Main Methods:
- Utilizing the mouse local lymph node assay (LLNA).
- Measuring the frequency of B220(+) lymphocytes in skin-draining lymph nodes.
- Comparing B220(+) lymphocyte levels against vehicle controls.
Main Results:
- Previous models defined sensitization based on a 1.25-fold increase in B220(+) cells.
- Variability in control group B220(+) lymphocyte counts was observed.
- A new prediction model is proposed to accommodate this variability.
Conclusions:
- The proposed LLNA refinement reduces reliance on absolute thresholds.
- The updated model aims for better accommodation of small changes in control values.
- This refinement is expected to enhance the reliability of skin sensitization testing.
