ABSTRACT
OBJECTIVE: The objective of this study is to investigate the neuroprotective effects of ß- sitosterol using the AlCl3 model of Alzheimer's Disease. METHODS: AlCl3 model was used to study cognition decline and behavioral impairments in C57BL/6 mice. Animals were randomly assigned into 4 groups with the following treatments: Group 1 received normal saline for 21 days, Group 2 received AlCl3 (10 mg/kg) for 14 days; Group 3 received AlCl3(10 mg/kg) for 14 days + ß-sitosterol (25mg/kg) for 21 days; while Group 4 was administered ß-sitosterol (25mg/kg) for 21 days. On day 22, we performed the behavioral studies using a Y maze, passive avoidance test, and novel object recognition test for all groups. Then the mice were sacrificed. The corticohippocampal region of the brain was isolated for acetylcholinesterase (AChE), acetylcholine (ACh), and GSH estimation. We conducted histopathological studies using Congo red staining to measure ß -amyloid deposition in the cortex and hippocampal region for all animal groups. RESULTS: AlCl3 successfully induced cognitive decline in mice following a 14-day induction period, as shown by significantly decreased (p < 0.001) in step-through latency, % alterations, and preference index values. These animals also exhibited a substantial decrease in ACh (p <0.001) and GSH (p < 0.001) and a rise in AChE (p < 0.001) compared to the control group. Mice administered with AlCl3 and ß-sitosterol showed significantly higher step-through latency time, % alteration time, and % preference index (p < 0.001) and higher levels of ACh, GSH, and lower levels of AChE in comparison to the AlCl3 model. AlCl3-administered animals also showed higher ß-amyloid deposition, which got significantly reduced in the ß-sitosterol treated group. CONCLUSION: AlCl3 was effectively employed to induce a cognitive deficit in mice, resulting in neurochemical changes and cognitive decline. ß -sitosterol treatment mitigated AlCl3-mediated cognitive impairment.
Subject(s)
Aluminum Chloride , Alzheimer Disease , Cognitive Dysfunction , Neuroprotective Agents , Sitosterols , Animals , Mice , Acetylcholine/metabolism , Acetylcholinesterase/metabolism , Aluminum Chloride/administration & dosage , Aluminum Chloride/toxicity , Alzheimer Disease/chemically induced , Alzheimer Disease/drug therapy , Alzheimer Disease/prevention & control , Avoidance Learning/drug effects , Case-Control Studies , Cerebral Cortex/drug effects , Cerebral Cortex/metabolism , Cerebral Cortex/pathology , Cognition/drug effects , Cognitive Dysfunction/chemically induced , Cognitive Dysfunction/drug therapy , Cognitive Dysfunction/prevention & control , Computer Simulation , Disease Models, Animal , Glutathione/metabolism , Hippocampus/drug effects , Hippocampus/metabolism , Hippocampus/pathology , Maze Learning/drug effects , Mice, Inbred C57BL , Neuroprotective Agents/pharmacology , Sitosterols/pharmacologyABSTRACT
Diabetes is a chronic disease that is not easily curable but can be managed efficiently. Artificial Intelligence is a powerful tool that may help in diabetes prediction, continuous glucose monitoring, Insulin injection guidance, and other areas of diabetes care. Diabetes, if not appropriately managed, leads to secondary complications like retinopathy, nephropathy, and neuropathy. Artificial intelligence helps minimize the risk of these complications through software and Artificial Intelligence-based devices. Artificial Intelligence can also help physicians in the early diagnosis and management of diabetes while reducing medical errors. Here we review the advancement of Artificial Intelligence in diabetes management.
