Information entropy-based fitting of the disease trajectory of brain ischemia-induced vascular cognitive impairment.

Abstract

The present study investigated the disease trajectory of vascular cognitive impairment using the entropy of information in a neural network mathematical simulation based on the free radical and excitatory amino acids theories. Glutamate, malondialdehyde, and inducible nitric oxide synthase content was significantly elevated, but acetylcholine, catalase, superoxide dismutase, glutathione peroxidase and constitutive nitric oxide synthase content was significantly decreased in our vascular cognitive impairment model. The fitting curves for each factor were obtained using Matlab software. Nineteen, 30 and 49 days post ischemia were the main output time frames of the influence of these seven factors. Our results demonstrated that vascular cognitive impairment involves multiple factors. These factors include excitatory amino acid toxicity and nitric oxide toxicity. These toxicities disrupt the dynamic equilibrium of the production and removal of oxygen free radicals after cerebral ischemia, reducing the ability to clear oxygen free radicals and worsening brain injury.