Neuroscience
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Apelin, an endogenous ligand of G protein-coupled receptor APJ, is widely distributed in the central nervous system (CNS). It can be divided into such subtypes as Apelin-13, Apelin-17, and Apelin-36 as they have different amino acid structures. ⋯ As an adipokine, Apelin has been found to play a crucial role in cardiovascular disease development. In this paper, we reviewed the effects and mechanisms of Apelin in treating CNS diseases, such as neurotrauma, stroke, spinal cord injury, primary tumors, neurodegenerative diseases, psychiatric diseases, epilepsy, and pain.
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Neurodegenerative diseases (ND) are complex diseases of still unknown etiology. Lately, long non-coding RNAs (lncRNAs) have become increasingly popular and implicated in several pathologies as they have several roles and appear to be involved in all biological processes such as cell signaling and cycle control as well as translation and transcription. MEG3 is one of these and acts by binding proteins or directly or competitively binding miRNAs. ⋯ This review examines the current state of knowledge concerning the level of expression and the regulatory function of MEG3 in relation to several NDs. In addition, we examined the relation of MEG3 with neurotrophic factors such as Tumor growth factor β (TGFβ) and its possible mechanism of action. A comprehensive and in-depth analysis of the role of MEG3 in ND could give a clearer picture about the initiation of the process of neuronal death and help develop an alternative therapy that targets MEG3.
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This review explores the significant roles of neurotransmitters, focusing on dopamine and serotonin, in inflammation and cancer. These neurotransmitters are vital for neural signaling and play crucial roles in various physiological and pathological processes. ⋯ The interplay between dopamine and serotonin systems extends beyond neural communication, significantly affecting immune responses and inflammation. Dopamine's role in modulating immune cell activity highlights its potential in treating inflammatory conditions and cancer. Similarly, serotonin's extensive physiological impact underscores the importance of targeting 5-HT pathways in various disorders. Future research should focus on developing therapeutic strategies that leverage these neurotransmitters' regulatory functions in both the CNS and peripheral systems.
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Accurate analysis of anxiety behaviors in animal models is pivotal for advancing neuroscience research and drug discovery. This study compares the potential of DeepLabCut, ZebraLab, and machine learning models to analyze anxiety-related behaviors in adult zebrafish. Using a dataset comprising video recordings of unstressed and pre-stressed zebrafish, we extracted features such as total inactivity duration/immobility, time spent at the bottom, time spent at the top and turn angles (large and small). ⋯ The effectiveness of these machine learning models was validated and tested on independent datasets. We found that some machine learning models, such as Decision Tree and Random Forests, performed excellently to differentiate between anxious and non-anxious behavior, even in the control group, where the differences between subjects were more subtle. Our findings show that upcoming technologies, such as machine learning models, are able to effectively and accurately analyze anxiety behaviors in zebrafish and provide a cost-effective method to analyze animal behavior.