A method for studying glyoxylic acid induced fluorescence and ultrastructure of monoamine neurons

Inasmuch as precise correlations of light- and electronmicroscopy are crucial for understanding biostructure, it seemed necessary to bring together the advantages of the glyoxylic acid (GA) method (for inducing monoamine fluorescence) and electron microscopy. A combined fluorescence and electron microscope method using GA is introduced. The brain is perfused by 2% GA in Krebs-Ringer bicarbonate buffer (pH 7.0) and this solution is followed by 4% paraformaldehyde containing 0.5% glutaraldehyde in Sorensen's phosphate buffer (pH 7.4). Sections are cut by cryostat or by vitratome and incubated in 2% GA in phosphate buffer (pH 7.0). Using fluorescence microscopy, features of interest are sketched and/or photographed. Afterwards, the same or subsequent section is processed for electron microscopy. Since axons of catecholamine-containing neurons (as well as their perikarya and terminals) are visualized by GA, the recommended procedure expands the range of studies concerning monoamine neurons that can now be carried out effectively.     

Nerve fibre velocity and refractory period distributions in nerve trunks

With the use of a double stimulus technique, nerve fibre velocity range measurements were performed over a single conduction distance in 13 normal subjects and over two conduction distances in another 12 normal subjects. The velocity ranges were found to be dependent upon the conduction distance, owing to unknown refractory period delays. Refractory period values were calculated for the 12 subjects and also direct refractory period distribution measurements were made on 15 normal subjects using a twin stimulus and automatic subtraction technique. Corrections to the velocity range measurements were made upon differing assumptions as to the correlation between refractory period and fibre conduction velocity. It was concluded that a single median value refractory period obtained from the distribution was the best correction to use, based upon the hypothesis that for group A fibres the random scatter of refractory period values is far greater than any variation due to a correlation between refractory period and fibre conduction velocity. It was found important to recognize that calculated values of velocity range are a function not only of the spread of fibre conduction velocities but also of refractory periods.     

Automated design of robust discriminant analysis classifier for foot pressure lesions using kinematic data

In the recent years, the use of motion tracking systems for acquisition of functional biomechanical gait data, has received increasing interest due to the richness and accuracy of the measured kinematic information. However, costs frequently restrict the number of subjects employed, and this makes the dimensionality of the collected data far higher than the available samples. This paper applies discriminant analysis algorithms to the classification of patients with different types of foot lesions, in order to establish an association between foot motion and lesion formation. With primary attention to small sample size situations, we compare different types of Bayesian classifiers and evaluate their performance with various dimensionality reduction techniques for feature extraction, as well as search methods for selection of raw kinematic variables. Finally, we propose a novel integrated method which fine-tunes the classifier parameters and selects the most relevant kinematic variables simultaneously. Performance comparisons are using robust resampling techniques such as Bootstrap 632+ and k-fold cross-validation. Results from experimentations with lesion subjects suffering from pathological plantar hyperkeratosis, show that the proposed method can lead to approximately 96% correct classification rates with less than 10% of the original features.