eng Oriental Scientific Publishing Company Biosciences Biotechnology Research Asia 0973-1245 2026-10-10 23 3 60102 article Fatima Jovana Cid-Galiot 1 Jonathan Josué Cid-Galiot 1 Alberto Alfonso Aguilar-Lasserre 1 Daniel Cuervo-Zanatta 2 Cecilia Elizabeth García-Puga 1 Graduate Studies and Research Division, Instituto Tecnológico de Orizaba, Tecnológico Nacional de México, Orizaba, Veracruz, México. University of Vienna Department of Pharmaceutical Sciences Division of Pharmacology and Toxicology UZA II; Josef-Holaubek-Platz Vienna. Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, neuroinflammation, and complex alterations involving genetic, metabolic, and environmental factors. In recent years, short-chain fatty acids (SCFAs), derived from gut microbiota fermentation, have attracted particular interest for their potential role in neuroprotective mechanisms and in modulating cognitive decline. In this study, an interpretable computational system, based on Fuzzy Logic (FL) and Artificial Neural Networks (ANN), was developed to analyze patterns of neuroprotection and behavioral loss in a murine model of AD under different dietary and microbial conditions. The Intelligent Decision Support System (IDSS) was built on previously reported experimental evidence from wild-type and transgenic mice fed a control diet, fiber supplementation, or fiber combined with antibiotics. A Mamdani-type fuzzy system was designed to estimate the level of neuroprotection based on acetate, propionate, butyrate, genotype, and diet-related variables, while an artificial neural network was trained to predict behavioral decline based on standard cognitive tests, including the T-Maze, novel object recognition, elevated cross maze, and water maze. The system's purpose was not to replace biological evidence, but rather to organize, simulate, and validate whether the same experimentally observed trend could be reproduced computationally. The results showed that fiber-associated conditions were associated with more favorable neuroprotective profiles, whereas antibiotic-associated conditions were associated with a loss of this benefit. Overall, the proposed system constitutes an interpretable, biologically meaningful tool to support preclinical research on AD and to validate neuroprotective patterns associated with the gut microbiota. https://www.biotech-asia.org/vol23no3/an-interpretable-fuzzy-logic-and-artificial-neural-network-decision-support-system-for-evaluating-short-chain-fatty-acid-associated-neuroprotection-and-behavioral-decline-in-alzheimer/ Alzheimer's disease (AD); Artificial Neural Networks (ANN); Fuzzy Logic (FL) Intelligent Decision Support System (IDSS); Murine Model Short-Chain Fatty Acids (SCFAs)