Does Müller cell differentiation occur prior to the emergence of synapses in embryonic turtle retina?

Müller cells are the main glial cells in the retina, and are related to plexiform layer activity. Recent studies have demonstrated that Müller cells are involved in the synaptic conservation, plasticity, development and metabolism of glutamate. During turtle retinal development, layers, cells and synapses appear at different times. The aim of this research is to study the emergence of Müller cells during embryonic development and their relationship with the synaptogenesis. The authors used retinas from Trachemys scripta elegans embryos at stages S14, 18, 20, 23, and 26. Some retinas were processed with immunocytochemistry in order to detect the presence of glutamine synthetase in Müller cells, which was used as a marker of these cells. Other retinas from the same stages were processed for ultrastructural studies. Samples were observed in confocal and transmission electron microscopes, respectively. The present results show that glutamine synthetase expression in Müller cells occurs at S18, before the emergence of the retinal layers and the early synapses.

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.