{'fraction_non_alphanumeric': 0.03902116402116402, 'fraction_numerical': 0.005291005291005291, 'mean_word_length': 5.304166666666666, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evaluation of matrix metalloproteinases in serum of patients with amyotrophic lateral sclerosis with pattern recognition methods.

Matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases, which are present in central and peripheral nervous system. They are considered to be involved in the pathogenesis of several neurological diseases, as multiple sclerosis, Alzheimer disease, and amyotrophic lateral sclerosis (ALS). The aim of the present study was to evaluate the application of the pattern recognition methods for the assessment of MMPs in serum of patients with ALS. Thirty patients with amyotrophic lateral sclerosis (ALS), in two subgroups: (i) with mild and (ii) severe progressing ALS, and 15 control healthy subjects were studied. The metalloproteinases MT-MMP-1, MMP-2, MMP-9 were examined. Additional variables (age of subjects and disease duration) were also analyzed by using a standard, parallel and hierarchical classifiers. Our results indicate that: (i) MMP-2 in serum may be an important marker for the evaluation of ALS progress; (ii) the set of two features {MT-MMP-1, MMP-9} may be helpful in differentiation between ALS and healthy subjects; (iii) the error rates obtained for the pair-wise linear classifier were similar to those received for the classifiers (standard, parallel, and hierarchical) based on k-NN rule. We conclude that the pattern recognition methods may be useful for the evaluation of significance MMPs as markers in neurodegenerative diseases, such as ALS.