Automatic chronic degenerative diseases identification using enteric nervous system images.

Studies recently accomplished on the Enteric Nervous System have shown that chronic degenerative diseases affect the Enteric Glial Cells (EGC) and, thus, the development of recognition methods able to identify whether or not the EGC are affected by these type of diseases may be helpful in its diagnoses. In this work, we propose the use of pattern recognition and machine learning techniques to evaluate if a given animal EGC image was obtained from a healthy individual or one affect by a chronic degenerative disease. In the proposed approach, we have performed the classification task with handcrafted features and deep learning-based techniques, also known as non-handcrafted features. The handcrafted features were obtained from the textural content of the ECG images using texture descriptors, such as the Local Binary Pattern (LBP). Moreover, the representation learning techniques employed in the approach are based on different Convolutional Neural Network (CNN) architectures, such as AlexNet and VGG16, with and without transfer learning. The complementarity between the handcrafted and non-handcrafted features was also evaluated with late fusion techniques. The datasets of EGC images used in the experiments, which are also contributions of this paper, are composed of three different chronic degenerative diseases: Cancer, Diabetes Mellitus, and Rheumatoid Arthritis. The experimental results, supported by statistical analysis, show that the proposed approach can distinguish healthy cells from the sick ones with a recognition rate of 89.30% (Rheumatoid Arthritis), 98.45% (Cancer), and 95.13% (Diabetes Mellitus), being achieved by combining classifiers obtained on both feature scenarios.

Experimental Cancer Cachexia Changes Neuron Numbers and Peptide Levels in the Intestine: Partial Protective Effects after Dietary Supplementation with L-Glutamine.

Gastrointestinal dysmotility frequently occurs in cancer cachexia and may result from damage to enteric innervation caused by oxidative stress, especially due to glutathione depletion. We assessed the effect of dietary supplementation with 20 g/kg l-glutamine (a glutathione precursor) on the intrinsic innervation of the enteric nervous system in healthy and Walker 256 tumor-bearing Wistar rats during the development of experimental cachexia (14 days), in comparison with non-supplemented rats, by using immunohistochemical methods and Western blotting. The total neural population and cholinergic subpopulation densities in the myenteric plexus, as well as the total population and VIPergic subpopulation in the submucosal plexus of the jejunum and ileum, were reduced in cachectic rats, resulting in adaptive morphometric alterations and an increase in vasoactive intestinal peptide (VIP) and calcitonin gene-related peptide (CGRP) expression, suggesting a neuroplastic response. l-glutamine supplementation prevented decrease in myenteric neuronal density in the ileum, morphometric alterations in the neurons and nerve fibers (in both the plexuses of the jejunum and ileum), and the overexpression of VIP and CGRP. Cancer cachexia severely affected the intrinsic innervation of the jejunum and ileum to various degrees and this injury seems to be associated with adaptive neural plasticity. l-glutamine supplementation presented partial protective effects on the enteric innervation against cancer cachexia, possibly by attenuating oxidative stress.