In Artificial intelligence in medicine ; h5-index 34.0
BACKGROUND : Any ailment in our organs can be visualized by using different modality signals and images. Hospitals are encountering a massive influx of large multimodality patient data to be analysed accurately and with context understanding. The deep learning techniques, like convolution neural networks (CNN), long short-term memory (LSTM), autoencoders, deep generative models and deep belief networks have already been applied to efficiently analyse possible large collections of data. Application of these methods to medical signals and images can aid the clinicians in clinical decision making.
PURPOSE : The aim of this study was to explore its potential application mechanism to the abalone basal ganglia neurons in rats based on deep learning.
PATIENTS AND METHODS : Firstly, in the GEO database, we obtained data on rat anesthesia, performing differential analysis, co-expression analysis, and enrichment analysis, and then we received the relevant module genes. Besides, the potential regulation of multi-factors on the module was calculated by hypergeometric test, and a series of ncRNA and TF were identified. Finally, we screened the target genes of anesthetized rats to gain insight into the potential role of anesthesia in rat basal lateral nucleus neurons.
RESULTS : A total of 535 differentially expressed genes in rats were obtained, involving Mafb and Ryr2. These genes are clustered into 17 anesthesia-related expression disorder modules. At the same time, the biological processes favored by the module are regulation of neuron apoptotic process and transforming growth factor beta2 production. Pivot analysis found that 39 ncRNAs and 4 TFs drive anesthesia-related disorders. Finally, the mechanism of action was analyzed and predicted. The module was regulated by Acvr1. We believe that miR-384-5p in anesthetized rats can activate the TGF-beta signaling pathway. Further, it promotes anesthesia and causes exposure to the basal ganglia neuron damage of the amygdala.
CONCLUSION : In this study, the imbalance module was used to explore the multi-factor-mediated anesthesia application mechanism, which provided new methods and ideas for subsequent research. The results suggest that miR-384-5p can promote anesthesia damage to the abalone basal ganglia neurons in rats through a variety of biological processes and signaling pathways. This result lays a solid theoretical foundation for biologists to explore the application mechanism of anesthesiology further.
Wang Zhen, Du Xiaoyan, Yang Yang, Zhang Guoqing
Anesthesia, Basal lateral nucleus neurons, Dysfunction module, Multifactorial