دانلود رایگان مقاله روش خودکار تحلیل خالص perineuronal با شدت رنگ اگگلوتینین فلوریبوندا

Abstract

Perineuronal nets (PNNs) are aggregations of extracellular matrix molecules that are critical for plasticity. Their altered development or changes during adulthood appear to contribute to a wide range of diseases/disorders of the brain. An increasing number of studies examining the contribution of PNN to various behaviors and types of plasticity have analyzed the fluorescence intensity of Wisteria floribunda agglutinin (WFA) as an indirect measure of the maturity of PNNs, with brighter WFA staining corresponding to a more mature PNN and dim WFA staining corresponding to an immature PNN. However, a clearly-defined and unified method for assessing the intensity of PNNs is critical to allow us to make comparisons across studies and to advance our understanding of how PNN plasticity contributes to normal brain function and brain disease states. Here we examined methods of PNN intensity quantification and demonstrate that creating a region of interest around each PNN and subtracting appropriate background is a viable method for PNN intensity quantification that can be automated. This method produces less variability and bias across experiments compared to other published analyses, and this method increases reproducibility and reliability of PNN intensity measures, which is critical for comparisons across studies in this emerging field.

4. Conclusions

In conclusion, we have demonstrated that the automated ROI method produces results similar to those using the Point method with greater reproducibility and less potential for bias. The current hypothesis in the PNN field is that increased WFA intensity corresponds to a mature PNN with decreased capacity for plasticity and that decreased WFA intensity corresponds to an immature PNN with increased capacity for plasticity (Wang and Fawcett, 2012).However, supporting this hypothesis requires a unified method of intensity measurement to advance this emerging field.