An in vitro and in silico study on the antioxidant and cell culture-based study on the chemoprotective activities of fish muscle protein hydrolysates obtained from European seabass and gilthead seabream.

European seabass (Dicentrarchus labrax, Linnaeus, 1758) (L) and gilthead seabream (Sparus aurata, Linnaeus, 1758) (C) muscles were hydrolysated by Alcalase (Lalc, Calc) and Chymotrypsin (Lch, Cch) then hydrolysates were examined and their peptide profiles obtained. A total of 765, 794, 132 and 232 peptides were identified in Calc, Lalc, Cch and Lch, respectively. Although, Lch and Cch were expected to have more antioxidant capacity because of their peptide profiles, Alcalase hydrolysates observed in vitro, were slightly higher (TEAC assay for Calc: 848.11 ±â€¯60.78 µmol TE/g protein). Maximum inhibition of oxidative stress was determined for Lalc (12.8% ±â€¯4.5%) in MDCK1 cell lines. Highest proliferative capacity observed for Calc (147.0% ±â€¯3.1%) at MTT assay in MDCK1 cell culture. Lch showed the highest chemopreventive effect with a 40-60% decrease for human colon adenocarcinoma cell line HT-29. This research points out the importance of aquatic sources as raw materials for peptide researches.

Diagnostic Accuracy Comparison of Artificial Immune Algorithms for Primary Headaches.

The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not related to any organic etiology. They are divided into four types: migraine, tension, cluster, and other primary headaches. After we took this main objective into consideration, three different neurologists were required to fill in the medical records of 850 patients into our web-based expert system hosted on our project web site. In the evaluation process, Artificial Immune Systems (AIS) were used as the classification algorithms. The AIS are classification algorithms that are inspired by the biological immune system mechanism that involves significant and distinct capabilities. These algorithms simulate the specialties of the immune system such as discrimination, learning, and the memorizing process in order to be used for classification, optimization, or pattern recognition. According to the results, the accuracy level of the classifier used in this study reached a success continuum ranging from 95% to 99%, except for the inconvenient one that yielded 71% accuracy.