An Alternative to Dye-Based Approaches to Remove Background Autofluorescence From Primate Brain Tissue

Area of Science:

• Neuroscience
• Microscopy
• Image Processing

Background:

• Brain tissue exhibits autofluorescence from molecules like lipofuscin, complicating neuron visualization.
• Autofluorescence spectral profiles can interfere with common fluorophore emission ranges in microscopy.
• Traditional methods use lipophilic dyes (e.g., Sudan Black B) to reduce autofluorescence, but these can obscure probe signals.

Purpose of the Study:

• To investigate an image processing approach for autofluorescence removal in aged primate midbrain tissue.
• To compare the efficacy of spectral imaging and linear unmixing against dye-based methods for neuron quantification.

Main Methods:

• Utilized aged primate midbrain tissue stained for tyrosine hydroxylase and calbindin.
• Applied spectral imaging and linear unmixing for autofluorescence removal.
• Compared computational method with traditional Sudan Black B (SBB) staining.

Main Results:

• Spectral imaging and linear unmixing identified significantly more cells than SBB treatment.
• The computational approach proved more effective in preserving fluorescent probe signals.

Conclusions:

• Computational autofluorescence removal via spectral imaging and linear unmixing is a viable and preferred method.
• This technique offers more accurate cell body enumeration in neural tissue than dye-based approaches.