Gold chloride technique to study articular innervation. A protocol validated through computer-assisted colorimetry

Authors

  • E. Gómez Barrena
  • E. Martínez Moreno
  • R. Ballesteros Massó
  • D. Martínez Pérez
  • L. Munuera Martínez

Keywords:

gold chloride, articular innervation, histological technique, computer-assisted colorimetry

Abstract

We studied variations in gold chloride techniques to elicit neural elements within articular samples, after "in toto" staining. These techniques attempt the differentiation of neural and vascular structures. Major changes in differential staining were observed when the gold chloride concentration was empirically modified. After the rest of the technique was standardized, we selected three gold chloride solutions to perform quantitative color experiments: l%, 0.75%, and 0.5%. Significant sections of the same thickness were acquired with a digital camera to perform computerassisted colorimetry. Color was measured through RGB (red-green-blue) channels in vessels, nerves, and background connective tissue as an internal control. By means of multivariate regression analysis, we compared differences in color measurements after l%, 0.75% and 0.5% gold chloride preparation. Statistically significant coefficients confirmed that red color signals in vessels after the 0.75% and the 0.5% solution were both less intense than after the 1% preparation. Green and blue signals in vessels were also significantly less intense after the 0.5% protocol than after using the 1% solution. Red color signals in nerves between the 1% and the 0.75% preparation protocols were more intense and not significantly different, while the 0.5% preparation produced significantly less intense red signals in nerves. Non-significant differences were observed in green or blue signals from nerves after any protocol. We concluded that the 0.75% gold chloride solution protocol produced more intense red signals in nerves and less intense red signals in vessels. This was the most discriminant protocol in our series, based on color signals.

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